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Andre Lucas

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.

    Mentioned in:

    1. Testing for ARCH in the presence of additive outliers (Journal of Applied Econometrics 1999) in ReplicationWiki ()

Working papers

  1. Joao, Igor Custodio & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2023. "Dynamic nonparametric clustering of multivariate panel data," Working Paper Series 2780, European Central Bank.

    Cited by:

    1. Igor Custodio João, 2024. "Testing for Clustering Under Switching," Tinbergen Institute Discussion Papers 24-052/III, Tinbergen Institute.
    2. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.

  2. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.

    Cited by:

    1. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
    2. Yicong Lin & André Lucas, 2025. "Functional Location-Scale Models with Robust Observation-Driven Dynamics," Tinbergen Institute Discussion Papers 25-027/III, Tinbergen Institute.

  3. Schwaab, Bernd & Zhang, Xin & Lucas, André, 2021. "Modeling extreme events: time-varying extreme tail shape," Working Paper Series 2524, European Central Bank.

    Cited by:

    1. Eric Beutner & Julia Schaumburg & Barend Spanjers, 2024. "Bootstrapping GARCH Models Under Dependent Innovations," Tinbergen Institute Discussion Papers 24-008/III, Tinbergen Institute.
    2. D’Innocenzo, Enzo & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2025. "Joint extreme Value-at-Risk and Expected Shortfall dynamics with a single integrated tail shape parameter," Working Paper Series 446, Sveriges Riksbank (Central Bank of Sweden).
    3. Julien Hambuckers & Li Sun & Luca Trapin, 2023. "Measuring tail risk at high-frequency: An $L_1$-regularized extreme value regression approach with unit-root predictors," Papers 2301.01362, arXiv.org.
    4. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    5. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2025. "Tail risk dynamics of banks with score-driven extreme value models," Journal of Empirical Finance, Elsevier, vol. 81(C).
    6. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).

  4. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.

    Cited by:

    1. Abdelhamid Hassairi & Fatma Ktari & Raoudha Zine, 2022. "On the Gaussian representation of the Riesz probability distribution on symmetric matrices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 609-632, December.
    2. Anne Opschoor & Dewi Peerlings & Luca Rossini & Andre Lucas, 2024. "Density Forecasting for Electricity Prices under Tail Heterogeneity with the t-Riesz Distribution," Tinbergen Institute Discussion Papers 24-049/III, Tinbergen Institute.

  5. Joao, Igor Custodio & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2021. "Dynamic clustering of multivariate panel data," Working Paper Series 2577, European Central Bank.

    Cited by:

    1. Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
    2. Igor Custodio João & Andre Lucas & Julia Schaumburg, 2021. "Clustering Dynamics and Persistence for Financial Multivariate Panel Data," Tinbergen Institute Discussion Papers 21-040/III, Tinbergen Institute.

  6. Anne Opschoor & André Lucas & Istvan Barra & Dick van Dijk, 2019. "Closed-Form Multi-Factor Copula Models with Observation-Driven Dynamic Factor Loadings," Tinbergen Institute Discussion Papers 19-013/IV, Tinbergen Institute, revised 23 Oct 2019.

    Cited by:

    1. Chen Tong & Peter Reinhard Hansen & Ilya Archakov, 2024. "Cluster GARCH," Papers 2406.06860, arXiv.org.
    2. Peter Reinhard Hansen & Chen Tong, 2024. "Convolution-t Distributions," Papers 2404.00864, arXiv.org.
    3. Tong, Chen & Hansen, Peter Reinhard, 2023. "Characterizing correlation matrices that admit a clustered factor representation," Economics Letters, Elsevier, vol. 233(C).
    4. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    5. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    6. Chen, Yanghan & Lin, Juan, 2024. "Measuring systemic risk in Asian foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 146(C).
    7. Jie Cheng, 2024. "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3617-3643, December.
    8. Fritzsch, Simon & Timphus, Maike & Weiß, Gregor, 2024. "Marginals versus copulas: Which account for more model risk in multivariate risk forecasting?," Journal of Banking & Finance, Elsevier, vol. 158(C).
    9. Chen, Zhenlong & Chang, Jing & Hao, Xiaozhen, 2024. "Portfolio selection via high-dimensional stochastic factor Copula," Finance Research Letters, Elsevier, vol. 67(PA).
    10. Chen Tong & Peter Reinhard Hansen, 2025. "Dynamic Factor Correlation Model," Papers 2503.01080, arXiv.org.
    11. Giuseppe Buccheri & Fulvio Corsi & Emilija Dzuverovic, 2024. "From rotational to scalar invariance: Enhancing identifiability in score-driven factor models," Papers 2412.01367, arXiv.org.
    12. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    13. Lin Deng & Michael Stanley Smith & Worapree Maneesoonthorn, 2023. "Large Skew-t Copula Models and Asymmetric Dependence in Intraday Equity Returns," Papers 2308.05564, arXiv.org, revised Jul 2024.
    14. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    15. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).

  7. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.

    Cited by:

    1. V. A. Mau, 2022. "Trends in Economic Science: Discussions of the Paths of Russian Modernization in the 19th–20th Centuries," Studies on Russian Economic Development, Springer, vol. 33(5), pages 506-512, October.
    2. Marco Fruzzetti & Giulio Gariano & Gerardo Palazzo & Antonio Scalia, 2021. "From SMP to PEPP: a further look at the risk endogeneity of the Central Bank," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems) 11, Bank of Italy, Directorate General for Markets and Payment System.
    3. Chavleishvili, Sulkhan & Fahr, Stephan & Kremer, Manfred & Manganelli, Simone & Schwaab, Bernd, 2021. "A risk management perspective on macroprudential policy," Working Paper Series 2556, European Central Bank.
    4. Laeven, Luc & Maddaloni, Angela & Mendicino, Caterina, 2022. "Monetary policy, macroprudential policy and financial stability," Working Paper Series 2647, European Central Bank.

  8. Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2017. "Bank business models at zero interest rates," Working Paper Series 2084, European Central Bank.

    Cited by:

    1. Molyneux, Philip & Pancotto, Livia & Reghezza, Alessio & Rodriguez d'Acri, Costanza, 2022. "Interest rate risk and monetary policy normalisation in the euro area," Journal of International Money and Finance, Elsevier, vol. 124(C).
    2. Nucera, Federico & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2017. "Do negative interest rates make banks less safe?," Working Paper Series 2098, European Central Bank.
    3. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    4. Matteo Farnè & Angelos T. Vouldis, 2021. "Banks’ business models in the euro area: a cluster analysis in high dimensions," Annals of Operations Research, Springer, vol. 305(1), pages 23-57, October.
    5. Schwaab, Bernd, 2017. "Bank business models at negative interest rates," Research Bulletin, European Central Bank, vol. 40.
    6. Whelsy Boungou, 2020. "Empirical Evidence of the Lending Channel of Monetary Policy under Negative Interest Rates," Working Papers hal-03258222, HAL.
    7. Katrin Assenmacher & Signe Krogstrup, 2021. "Monetary Policy with Negative Interest Rates: De-linking Cash from Digital Money," International Journal of Central Banking, International Journal of Central Banking, vol. 17(1), pages 67-106, March.
    8. Philip Molyneux & Alessio Reghezza & Chiara Torriero & Jonathan Williams, 2021. "Banks' noninterest income and securities holdings in a low interest rate environment: The case of Italy," European Financial Management, European Financial Management Association, vol. 27(1), pages 98-119, January.
    9. Michael Kumhof & Xuan Wang, 2020. "Banks, Money, and the Zero Lower Bound on Deposit Rates," Tinbergen Institute Discussion Papers 20-050/VI, Tinbergen Institute.
    10. Kang‐Soek Lee & Richard A. Werner, 2023. "Are lower interest rates really associated with higher growth? New empirical evidence on the interest rate thesis from 19 countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3960-3975, October.
    11. Roberto Savona, 2022. "Bank business models, negative policy rates, and prudential regulation," Annals of Finance, Springer, vol. 18(3), pages 355-392, September.
    12. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    13. Hoffmann, Peter & Langfield, Sam & Pierobon, Federico & Vuillemey, Guillaume, 2018. "Who bears interest rate risk?," Working Paper Series 2176, European Central Bank.
    14. Joao, Igor Custodio & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2023. "Dynamic nonparametric clustering of multivariate panel data," Working Paper Series 2780, European Central Bank.
    15. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    16. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    17. Giese, Julia & Joyce, Michael & Meaning, Jack & Worlidge, Jack, 2024. "Do preferred habitat investors exist? Evidence from the UK government bond market," Economics Letters, Elsevier, vol. 234(C).
    18. Katrin Assenmacher & Signe Krogstrup, 2018. "Monetary Policy with Negative Interest Rates: Decoupling Cash from Electronic Money," IMF Working Papers 2018/191, International Monetary Fund.
    19. López-Penabad, Maria Celia & Iglesias-Casal, Ana & Silva Neto, José Fernando, 2022. "Effects of a negative interest rate policy in bank profitability and risk taking: Evidence from European banks," Research in International Business and Finance, Elsevier, vol. 60(C).
    20. Farnè, Matteo & Vouldis, Angelos, 2024. "Do retail-oriented banks have less non-performing loans?," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    21. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    22. Selva Demiralp & Jens Eisenschmidt & Thomas Vlassopoulos, 2021. "Negative interest rates, excess liquidity and retail deposits: Banks’ reaction to unconventional monetary policy in the euro area," Koç University-TUSIAD Economic Research Forum Working Papers 1910, Koc University-TUSIAD Economic Research Forum.
    23. Christoph Basten & Mike Mariathasan, 2020. "Interest rate pass-through and bank risk-taking under negative-rate policies with tiered remuneration of Central Bank Reserves," Swiss Finance Institute Research Paper Series 20-98, Swiss Finance Institute.
    24. Igor Custodio João & Andre Lucas & Julia Schaumburg, 2021. "Clustering Dynamics and Persistence for Financial Multivariate Panel Data," Tinbergen Institute Discussion Papers 21-040/III, Tinbergen Institute.
    25. Stieglitz, Moritz & Wagner, Konstantin, 2020. "Marginal returns to talent for material risk takers in banking," IWH Discussion Papers 20/2020, Halle Institute for Economic Research (IWH).
    26. Laeven, Luc & Maddaloni, Angela & Mendicino, Caterina, 2022. "Monetary policy, macroprudential policy and financial stability," Working Paper Series 2647, European Central Bank.

  9. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.

    Cited by:

    1. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    2. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.

  10. Nucera, Federico & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2017. "Do negative interest rates make banks less safe?," Working Paper Series 2098, European Central Bank.

    Cited by:

    1. Johannes Bubeck & Angela Maddaloni & José-Luis Peydró, 2019. "Negative Monetary Policy Rates and Systemic Banks' Risk-Taking: Evidence from the Euro Area Securities Register," Working Papers 1128, Barcelona School of Economics.
    2. Name 1 Dieter Wang Email 1 & Iman (I.P.P.) van Lelyveld & Julia (J.) Schaumburg, 2018. "Do information contagion and business model similarities explain bank credit risk commonalities?," Tinbergen Institute Discussion Papers 18-100/IV, Tinbergen Institute.
    3. Abildgren, Kim & Kuchler, Andreas, 2023. "Firm behaviour under negative deposit rates," European Economic Review, Elsevier, vol. 151(C).
    4. Mayu Kikuchi & Alfred Wong & Jiayue Zhang, 2019. "Risk of window dressing: quarter-end spikes in the Japanese yen Libor-OIS spread," Journal of Regulatory Economics, Springer, vol. 56(2), pages 149-166, December.
    5. Jeffrey R. Campbell & Thomas B. King & Anna Orlik & Rebecca Zarutskie, 2020. "Issues Regarding the Use of the Policy Rate Tool," Finance and Economics Discussion Series 2020-070, Board of Governors of the Federal Reserve System (U.S.).
    6. Avinadav, Tal & Levy, Priel, 2024. "Improving efficiency in supply chains with a capital-constrained app developer under the agency contract," European Journal of Operational Research, Elsevier, vol. 315(3), pages 991-1005.
    7. Jose A. Lopez & Andrew K. Rose & Mark M. Spiegel, 2018. "Why Have Negative Nominal Interest Rates Had Such a Small Effect on Bank Performance? Cross Country Evidence," Working Paper Series 2018-7, Federal Reserve Bank of San Francisco.
    8. Bongiovanni, Alessio & Reghezza, Alessio & Santamaria, Riccardo & Williams, Jonathan, 2021. "Do negative interest rates affect bank risk-taking?," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 350-364.
    9. Kang‐Soek Lee & Richard A. Werner, 2023. "Are lower interest rates really associated with higher growth? New empirical evidence on the interest rate thesis from 19 countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3960-3975, October.
    10. Avignone, Giuseppe & Girardone, Claudia & Pancaro, Cosimo & Pancotto, Livia & Reghezza, Alessio, 2022. "Making a virtue out of necessity: the effect of negative interest rates on bank cost efficiency," Working Paper Series 2718, European Central Bank.
    11. Klein, Melanie, 2020. "Implications of negative interest rates for the net interest margin and lending of euro area banks," Discussion Papers 10/2020, Deutsche Bundesbank.
    12. Ni, Jianhui & Ruan, Jia, 2024. "Contagion effects of external monetary shocks on systemic financial risk in China: Evidence from the Euro area and Japan," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    13. Whelsy Boungou & Charles Mawusi, 2023. "Bank lending margins in a negative interest rate environment," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 886-901, January.
    14. Carlo Altavilla & Miguel Boucinha & Sarah Holton & Steven Ongena, 2021. "Credit Supply and Demand in Unconventional Times," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 2071-2098, December.
    15. Petra Jílková & Jana Kotěšovcová, 2022. "Determinanty výnosnosti evropského bankovního systému v letech 2012-2019 [Determinants of European Bank Profitability in 2012-2019]," Politická ekonomie, Prague University of Economics and Business, vol. 2022(5), pages 552-573.
    16. Klaus, Juergen & Selga, Eriks & Klein, Tony, 2019. "Floating Rate Notes and Stakeholder Activities During Zero and Negative Interest Rate Regimes," QBS Working Paper Series 2019/03, Queen's University Belfast, Queen's Business School.
    17. Roberto Savona, 2022. "Bank business models, negative policy rates, and prudential regulation," Annals of Finance, Springer, vol. 18(3), pages 355-392, September.
    18. Vu, Anh Nguyet, 2020. "On the impact of quantitative easing on credit standards and systemic risk: The Japanese experience," Economics Letters, Elsevier, vol. 186(C).
    19. Buchholz, Manuel & Schmidt, Kirsten & Tonzer, Lena, 2019. "Do conventional monetary policy instruments matter in unconventional times?," Discussion Papers 27/2019, Deutsche Bundesbank.
    20. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol, 2022. "Does the choice of monetary policy tool matter for systemic risk? The curious case of negative interest rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    21. Liñares-Zegarra, José M. & Willesson, Magnus, 2021. "The effects of negative interest rates on cash usage: Evidence for EU countries," Economics Letters, Elsevier, vol. 198(C).
    22. Nicolas Reigl & Karsten Staehr, 2020. "Negative Interest Rates in the Five Eurozone Countries from Central and Eastern Europe," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(01), pages 24-30, April.
    23. Klaus, Jürgen & Selga, Ēriks K., 2021. "How floating rate notes stopped floating: Evidence from the negative interest rate regime," International Review of Financial Analysis, Elsevier, vol. 75(C).
    24. Junttila, Juha & Nguyen, Vo Cao Sang, 2022. "Impacts of sovereign risk premium on bank profitability: Evidence from euro area," International Review of Financial Analysis, Elsevier, vol. 81(C).
    25. Gee Hee Hong & John Kandrac, 2022. "Pushed Past the Limit? How Japanese Banks Reacted to Negative Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 1027-1063, June.
    26. Katrin Assenmacher & Signe Krogstrup, 2018. "Monetary Policy with Negative Interest Rates: Decoupling Cash from Electronic Money," IMF Working Papers 2018/191, International Monetary Fund.
    27. Hartmann, Philipp & Smets, Frank, 2018. "The first twenty years of the European Central Bank: monetary policy," CEPR Discussion Papers 13411, C.E.P.R. Discussion Papers.
    28. Borri, Nicola & Giorgio, Giorgio di, 2022. "Systemic risk and the COVID challenge in the european banking sector," Journal of Banking & Finance, Elsevier, vol. 140(C).
    29. Hiroshi Gunji, 2025. "Did the BOJ’s negative interest rate policy increase bank lending?," The Japanese Economic Review, Springer, vol. 76(1), pages 91-120, January.
    30. Barry Eichengreen, 2020. "Keynesian economics: can it return if it never died?," Review of Keynesian Economics, Edward Elgar Publishing, vol. 8(1), pages 23-35, January.
    31. Peydró, José-Luis & Maddaloni, Angela, 2020. "Negative Monetary Policy Rates and Systemic Banks’ Risk-Taking: Evidence from the Euro Area Securities Register," CEPR Discussion Papers 14988, C.E.P.R. Discussion Papers.
    32. Whelsy Boungou, 2020. "Negative Interest Rates Policy and Banks' Risk-Taking: Empirical Evidence," Post-Print hal-03709855, HAL.
    33. Selva Demiralp & Jens Eisenschmidt & Thomas Vlassopoulos, 2021. "Negative interest rates, excess liquidity and retail deposits: Banks’ reaction to unconventional monetary policy in the euro area," Koç University-TUSIAD Economic Research Forum Working Papers 1910, Koc University-TUSIAD Economic Research Forum.
    34. Martin Brown, 2020. "Negative Interest Rates and Bank Lending," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(01), pages 18-23, April.
    35. Molterer, Manuel, 2019. "Tougher than the rest? The resilience of specialized financial intermediation to macroeconomic shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 163-174.
    36. Cynthia Balloch & Yann Koby & Mauricio Ulate, 2022. "Making Sense of Negative Nominal Interest Rates," Working Paper Series 2022-12, Federal Reserve Bank of San Francisco.
    37. Luis Brandao-Marques & Marco Casiraghi & Gaston Gelos & Gunes Kamber & Roland Meeks, 2021. "Negative Interest Rate Policies: Taking Stock of the Experience So Far," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 22(06), pages 27-32, November.
    38. Lagasio, Valentina & Quaranta, Anna Grazia, 2022. "Cluster analysis of bank business models: The connection with performance, efficiency and risk," Finance Research Letters, Elsevier, vol. 47(PA).
    39. Uwe Vollmer, 2022. "Monetary policy or macroprudential policies: What can tame the cycles?," Journal of Economic Surveys, Wiley Blackwell, vol. 36(5), pages 1510-1538, December.
    40. Mr. Gee Hee Hong & John Kandrac, 2018. "Pushed Past the Limit? How Japanese Banks Reacted to Negative Interest Rates," IMF Working Papers 2018/131, International Monetary Fund.

  11. Andre Lucas & Anne Opschoor & Julia Schaumburg, 2016. "Accounting for Missing Values in Score-Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 16-067/IV, Tinbergen Institute.

    Cited by:

    1. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    2. Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
    3. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    4. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.

  12. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2016. "Model-based Business Cycle and Financial Cycle Decomposition for Europe and the U.S," Tinbergen Institute Discussion Papers 16-051/IV, Tinbergen Institute.

    Cited by:

    1. R. Basselier & G. Langenus & P. Reusens, 2017. "The potential growth of the Belgian economy," Economic Review, National Bank of Belgium, issue ii, pages 37-53, september.
    2. Škare, Marinko & Porada-Rochoń, Małgorzata, 2020. "Multi-channel singular-spectrum analysis of financial cycles in ten developed economies for 1970–2018," Journal of Business Research, Elsevier, vol. 112(C), pages 567-575.

  13. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.

    Cited by:

    1. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    2. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    3. Jalan, Akanksha & Matkovskyy, Roman, 2023. "Systemic risks in the cryptocurrency market: Evidence from the FTX collapse," Finance Research Letters, Elsevier, vol. 53(C).
    4. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2021. "Systemic-systematic risk in financial system: A dynamic ranking based on expectiles," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 330-365.
    5. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring interconnectedness between financial institutions with Bayesian time-varying vector autoregressions," Working Papers ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    6. Duan, Yuejiao & Goodell, John W. & Li, Haoran & Li, Xinming, 2022. "Assessing machine learning for forecasting economic risk: Evidence from an expanded Chinese financial information set," Finance Research Letters, Elsevier, vol. 46(PA).
    7. Michele Leonardo Bianchi & Alberto Maria Sorrentino, 2020. "Measuring CoVaR: An Empirical Comparison," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 511-528, February.
    8. Borri, Nicola, 2019. "Conditional tail-risk in cryptocurrency markets," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 1-19.
    9. Brealey, Richard A & Cooper, Ian A & Kaplanis, Evi, 2019. "The effect of mergers on US bank risk in the short run and in the long run," Journal of Banking & Finance, Elsevier, vol. 108(C).
    10. Michele Leonardo Bianchi & Alberto Maria Sorrentino, 2022. "Exploring the Systemic Risk of Domestic Banks with ΔCoVaR and Elastic-Net," Journal of Financial Services Research, Springer;Western Finance Association, vol. 62(1), pages 127-141, October.
    11. Abendschein, Michael & Grundke, Peter, 2018. "On the ranking consistency of global systemic risk measures: empirical evidence," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181623, Verein für Socialpolitik / German Economic Association.
    12. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    13. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    14. Edward M. H. Lin & Edward W. Sun & Min-Teh Yu, 2018. "Systemic risk, financial markets, and performance of financial institutions," Annals of Operations Research, Springer, vol. 262(2), pages 579-603, March.
    15. Borri, Nicola & Giorgio, Giorgio di, 2022. "Systemic risk and the COVID challenge in the european banking sector," Journal of Banking & Finance, Elsevier, vol. 140(C).
    16. Zhang, Ping & Yin, Shiqi & Sha, Yezhou, 2023. "Global systemic risk dynamic network connectedness during the COVID-19: Evidence from nonlinear Granger causality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    17. Antonio Di Cesare & Anna Rogantini Picco, 2018. "A Survey of Systemic Risk Indicators," Questioni di Economia e Finanza (Occasional Papers) 458, Bank of Italy, Economic Research and International Relations Area.
    18. Mutiara Aini & Deddy Priatmodjo Koesrindartoto, 2020. "The Determinants Of Systemic Risk: Evidence From Indonesian Commercial Banks," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 23(1), pages 101-120, April.
    19. Caporin, Massimiliano & Costola, Michele & Garibal, Jean-Charles & Maillet, Bertrand, 2022. "Systemic risk and severe economic downturns: A targeted and sparse analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    20. Jokivuolle, Esa & Tunaru, Radu & Vioto, Davide, 2018. "Testing the systemic risk differences in banks," Bank of Finland Research Discussion Papers 13/2018, Bank of Finland.
    21. Carmela Cappelli & Francesca Iorio & Angela Maddaloni & Pierpaolo D’Urso, 2021. "Atheoretical Regression Trees for classifying risky financial institutions," Annals of Operations Research, Springer, vol. 299(1), pages 1357-1377, April.
    22. Kräussl, Roman & Lehnert, Thorsten & Stefanova, Denitsa, 2016. "The European sovereign debt crisis: What have we learned?," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 363-373.
    23. Marina Brogi & Valentina Lagasio & Luca Riccetti, 2021. "Systemic risk measurement: bucketing global systemically important banks," Annals of Finance, Springer, vol. 17(3), pages 319-351, September.
    24. Borri, Nicola, 2019. "Redenomination-risk spillovers in the Eurozone," Economics Letters, Elsevier, vol. 174(C), pages 173-178.
    25. Peter Grundke, 2019. "Ranking consistency of systemic risk measures: a simulation-based analysis in a banking network model," Review of Quantitative Finance and Accounting, Springer, vol. 52(4), pages 953-990, May.
    26. Zhou, Dong-hai & Liu, Xiao-xing, 2024. "Does systemic risk in the fund markets predict future economic downturns?," International Review of Financial Analysis, Elsevier, vol. 92(C).
    27. Goldman, Elena, 2023. "Uncertainty in systemic risks rankings: Bayesian and frequentist analysis," Finance Research Letters, Elsevier, vol. 56(C).
    28. Wang, Dan & Huang, Wei-Qiang, 2021. "Centrality-based measures of financial institutions’ systemic importance: A tail dependence network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    29. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    30. Matteo Foglia & Eliana Angelini, 2021. "The triple (T3) dimension of systemic risk: Identifying systemically important banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 7-26, January.

  14. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.

    Cited by:

    1. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.

  15. Michiel C.W. van de Leur & Andre Lucas, 2016. "Network, Market, and Book-Based Systemic Risk Rankings," Tinbergen Institute Discussion Papers 16-074/IV, Tinbergen Institute.

    Cited by:

    1. He, Chengying & Wen, Zhang & Huang, Ke & Ji, Xiaoqin, 2022. "Sudden shock and stock market network structure characteristics: A comparison of past crisis events," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    2. Duan, Yuejiao & El Ghoul, Sadok & Guedhami, Omrane & Li, Haoran & Li, Xinming, 2021. "Bank systemic risk around COVID-19: A cross-country analysis," Journal of Banking & Finance, Elsevier, vol. 133(C).
    3. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    4. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2017. "The changing international network of sovereign debt and financial institutions," Working Papers 2017-04, University of Tasmania, Tasmanian School of Business and Economics.
    5. Linhai Zhao & Yingjie Li & Yenchun Jim Wu, 2022. "An Identification Algorithm of Systemically Important Financial Institutions Based on Adjacency Information Entropy," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1735-1753, April.
    6. Jin, Justin Y. & Ma, Mary L.Z. & Song, Victor & Guo, Mengyang, 2021. "Banks’ loan charge-offs and macro-level risk," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    7. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    8. Miriam Kamah & Joshua Riti, 2024. "Measuring the connectedness of the Nigerian banking network and its implications for systemic risk," Modern Finance, Modern Finance Institute, vol. 2(2), pages 96-119.
    9. Chen, Muzi & Li, Nan & Zheng, Lifen & Huang, Difang & Wu, Boyao, 2022. "Dynamic correlation of market connectivity, risk spillover and abnormal volatility in stock price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    10. Jean-Baptiste Hasse, 2020. "Systemic Risk: a Network Approach," Working Papers halshs-02893780, HAL.
    11. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    12. Qian, Shuitu & You, Hang & Zhang, Xiaoyuan, 2025. "Systemic risk between banks and firms in dual-layer dynamic networks," Emerging Markets Review, Elsevier, vol. 66(C).
    13. Jean-Baptiste Hasse, 2022. "Systemic risk: a network approach," Post-Print hal-03740283, HAL.
    14. Huo, Da & Shi, Yongdong & Wang, Chao & Wang, Lihan & Xing, Weize & Yang, Mo & Zhao, Jingjing, 2025. "Measuring systemic risk in China: A new hybrid approach incorporating ensemble learning and risk spillover networks," Pacific-Basin Finance Journal, Elsevier, vol. 91(C).
    15. Dungey, Mardi & Harvey, John & Siklos, Pierre & Volkov, Vladimir, 2017. "Signed spillover effects building on historical decompositions," Working Papers 2017-11, University of Tasmania, Tasmanian School of Business and Economics.
    16. Biplob Chowdhury & Mardi Dungey & Moses Kangogo & Mohammad Abu Sayeed & Vladimir Volkov, 2018. "The Changing Network of Financial Market Linkages: The Asian Experience," Working Papers id:12924, eSocialSciences.
    17. Zhang, Ping & Yin, Shiqi & Sha, Yezhou, 2023. "Global systemic risk dynamic network connectedness during the COVID-19: Evidence from nonlinear Granger causality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    18. Yevgeny V. POPOV, 2018. "Economic Sociotronics of the 21st Century," Upravlenets, Ural State University of Economics, vol. 9(2), pages 2-5, April.
    19. Muzi Chen & Nan Li & Lifen Zheng & Difang Huang & Boyao Wu, 2024. "Dynamic Correlation of Market Connectivity, Risk Spillover and Abnormal Volatility in Stock Price," Papers 2403.19363, arXiv.org.
    20. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    21. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    22. Xi, Xian & Gao, Xiangyun & Zhong, Weiqiong, 2025. "How risk spillover network structure affects VaR: A study using complex networks and quantile regression," International Review of Economics & Finance, Elsevier, vol. 98(C).
    23. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2018. "Systemic risk in the US: Interconnectedness as a circuit breaker," Economic Modelling, Elsevier, vol. 71(C), pages 305-315.

  16. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.

    Cited by:

    1. Hoang Nguyen & Audron.e Virbickait.e & M. Concepci'on Aus'in & Pedro Galeano, 2024. "Structured factor copulas for modeling the systemic risk of European and United States banks," Papers 2401.03443, arXiv.org.
    2. Bonga-Bonga, Lumengo & Manguzvane, Mathias Mandla, 2018. "Assessing the extent of contagion of sovereign credit risk among BRICS countries," MPRA Paper 89200, University Library of Munich, Germany.
    3. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," Working Paper Series in Economics 123, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    4. J. W. Muteba Mwamba & Mathias Manguzvane, 2020. "Contagion risk in african sovereign debt markets: A spatial econometrics approach," International Finance, Wiley Blackwell, vol. 23(3), pages 506-536, December.

  17. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2016. "Global credit risk: world country and industry factors," Working Paper Series 1922, European Central Bank.

    Cited by:

    1. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    2. Barra, Cristian & Ruggiero, Nazzareno, 2021. "Do microeconomic and macroeconomic factors influence Italian bank credit risk in different local markets? Evidence from cooperative and non-cooperative banks," Journal of Economics and Business, Elsevier, vol. 114(C).
    3. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    4. Álvaro Chamizo & Alfonso Novales, 2019. "Looking through systemic credit risk: determinants, stress testing and market value," Documentos de Trabajo del ICAE 2019-27, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. Areski Cousin & J'er^ome Lelong & Tom Picard, 2021. "Rating transitions forecasting: a filtering approach," Papers 2109.10567, arXiv.org, revised Jun 2023.
    6. Li, Tangrong & Sun, Xuchu, 2023. "Is controlling shareholders' credit risk contagious to firms? — Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    7. Alfonso Novales & Alvaro Chamizo, 2019. "Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components," JRFM, MDPI, vol. 12(3), pages 1-33, August.
    8. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    9. Doemeland,Doerte & Estevão,Marcello & Jooste,Charl & Sampi Bravo,James Robert Ezequiel & Tsiropoulos,Vasileios, 2022. "Debt Vulnerability Analysis : A Multi-Angle Approach," Policy Research Working Paper Series 9929, The World Bank.
    10. Li, Zhong-fei & Zhou, Qi & Chen, Ming & Liu, Qian, 2021. "The impact of COVID-19 on industry-related characteristics and risk contagion," Finance Research Letters, Elsevier, vol. 39(C).
    11. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2024. "Temporal networks and financial contagion," Journal of Financial Stability, Elsevier, vol. 71(C).
    12. Takefumi Yamazaki, 2018. "Financial friction sources in emerging economies: Structural estimation of sovereign default models," Discussion papers ron303, Policy Research Institute, Ministry of Finance Japan.
    13. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Rating transitions forecasting: a filtering approach," Post-Print hal-03347521, HAL.
    14. Oliver Blümke, 2020. "Estimating the probability of default for no‐default and low‐default portfolios," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 89-107, January.
    15. Dong, Manh Cuong & Tian, Shaonan & Chen, Cathy W.S., 2018. "Predicting failure risk using financial ratios: Quantile hazard model approach," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 204-220.
    16. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    17. Kwon, Tae Yeon & Lee, Yoonjung, 2018. "Industry specific defaults," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 45-58.
    18. Kocsis, Zalan & Monostori, Zoltan, 2016. "The role of country-specific fundamentals in sovereign CDS spreads: Eastern European experiences," Emerging Markets Review, Elsevier, vol. 27(C), pages 140-168.
    19. Paulo V. Carvalho & José D. Curto & Rodrigo Primor, 2022. "Macroeconomic determinants of credit risk: Evidence from the Eurozone," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2054-2072, April.

  18. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.

    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.

  19. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.

    Cited by:

    1. Ruben Loaiza-Maya & Didier Nibbering & Dan Zhu, 2023. "Hybrid unadjusted Langevin methods for high-dimensional latent variable models," Papers 2306.14445, arXiv.org.
    2. Dimitrakopoulos, Stefanos & Tsionas, Mike, 2019. "Ordinal-response GARCH models for transaction data: A forecasting exercise," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1273-1287.
    3. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    4. Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Filtering the intensity of public concern from social media count data with jumps," Papers 2012.13267, arXiv.org.
    5. Lange, Rutger-Jan, 2024. "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, vol. 238(2).
    6. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    7. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    8. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    9. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
    10. Loaiza-Maya, Rubén & Nibbering, Didier & Zhu, Dan, 2024. "Hybrid unadjusted Langevin methods for high-dimensional latent variable models," Journal of Econometrics, Elsevier, vol. 241(2).
    11. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
    12. Kung, Ko-Lun & Liu, I-Chien & Wang, Chou-Wen, 2021. "Modeling and pricing longevity derivatives using Skellam distribution," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 341-354.
    13. Zhanyu Chen & Kai Zhang & Hongbiao Zhao, 2022. "A Skellam market model for loan prime rate options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 525-551, March.
    14. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
    15. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    16. Baena-Mirabete, S. & Puig, P., 2020. "Computing probabilities of integer-valued random variables by recurrence relations," Statistics & Probability Letters, Elsevier, vol. 161(C).
    17. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    18. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
    19. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    20. Xiaofei Hu & Beth Andrews, 2021. "Integer‐valued asymmetric garch modeling," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 737-751, September.

  20. Lucas, André & Zhang, Xin, 2015. "Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting," Working Paper Series 309, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    2. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    3. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    4. Qiu, Zhiguo & Lazar, Emese & Nakata, Keiichi, 2024. "VaR and ES forecasting via recurrent neural network-based stateful models," International Review of Financial Analysis, Elsevier, vol. 92(C).
    5. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    6. Gkillas, Konstantinos & Konstantatos, Christoforos & Papathanasiou, Spyros & Wohar, Mark, 2023. "Estimation of value at risk for copper," Journal of Commodity Markets, Elsevier, vol. 32(C).
    7. Song, Shijia & Li, Handong, 2023. "A method for predicting VaR by aggregating generalized distributions driven by the dynamic conditional score," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 203-214.
    8. A. Gabrielsen & P. Zagaglia & A. Kirchner & Z. Liu, 2012. "Forecasting Value-at-Risk with Time-Varying Variance, Skewnessn and Kurtosis in an Exponential Weighted Moving Average Framework," Working Papers wp831, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. André Lucas & Julia Schaumburg & Bernd Schwaab, 2019. "Bank Business Models at Zero Interest Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 542-555, July.
    10. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    11. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    12. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    13. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    14. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    15. Arian, Hamid & Moghimi, Mehrdad & Tabatabaei, Ehsan & Zamani, Shiva, 2022. "Encoded Value-at-Risk: A machine learning approach for portfolio risk measurement," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 500-525.
    16. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    17. Ching-Jui Tien & Chia-Sheng Tu & Ming-Tang Tsai, 2022. "Risk Assessment of User Aggregators in Demand Bidding Markets," Energies, MDPI, vol. 16(1), pages 1-14, December.
    18. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    19. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    20. Liu, Wei & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models," Research in International Business and Finance, Elsevier, vol. 54(C).
    21. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    22. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    23. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    24. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    25. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.
    26. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.

  21. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.

    Cited by:

    1. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.
    2. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    3. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    4. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    5. Mamode Khan Naushad & Rumjaun Wasseem & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Computing with bivariate COM-Poisson model under different copulas," Monte Carlo Methods and Applications, De Gruyter, vol. 23(2), pages 131-146, June.
    6. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.

  22. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.

    Cited by:

    1. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    2. Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
    3. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    4. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    5. Lilis Yuaningsih & R. Adjeng Mariana Febrianti & Hafiz Waqas Kamran, 2020. "Reducing CO2 Emissions through Biogas, Wind and Solar Energy Production: Evidence from Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 684-689.
    6. Liyuan Cui & Guanhao Feng & Yongmiao Hong, 2024. "Regularized Gmm For Time‐Varying Models With Applications To Asset Pricing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(2), pages 851-883, May.
    7. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.

  23. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 1837, European Central Bank.

    Cited by:

    1. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    2. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    3. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    4. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
    5. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    6. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    7. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    8. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    9. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    10. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    11. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2016. "International stock market cointegration under the risk-neutral measure," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 243-255.
    12. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    13. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    14. Lin Deng & Michael Stanley Smith & Worapree Maneesoonthorn, 2023. "Large Skew-t Copula Models and Asymmetric Dependence in Intraday Equity Returns," Papers 2308.05564, arXiv.org, revised Jul 2024.
    15. Linda Mhalla & Julien Hambuckers & Marie Lambert, 2022. "Extremal connectedness of hedge funds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 988-1009, August.

  24. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models," Tinbergen Institute Discussion Papers 15-083/III, Tinbergen Institute.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
    2. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    3. Pál, Tibor & Storti, Giuseppe, 2025. "Estimating the R-Star in the US: A Score-Driven State-Space Model with Time-Varying Volatility Persistence," MPRA Paper 125338, University Library of Munich, Germany.
    4. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    5. Schwaab, Bernd & Zhang, Xin & Lucas, André, 2021. "Modeling extreme events: time-varying extreme tail shape," Working Paper Series 2524, European Central Bank.
    6. Hong, Yanran & Yu, Jize & Su, Yuquan & Wang, Lu, 2023. "Southern oscillation: Great value of its trends for forecasting crude oil spot price volatility," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 358-368.
    7. D’Innocenzo, Enzo & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2025. "Joint extreme Value-at-Risk and Expected Shortfall dynamics with a single integrated tail shape parameter," Working Paper Series 446, Sveriges Riksbank (Central Bank of Sweden).
    8. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    9. Jiawen Xu & Pierre Perron, 2015. "Forecasting in the presence of in and out of sample breaks," Boston University - Department of Economics - Working Papers Series wp2015-012, Boston University - Department of Economics.
    10. Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2017. "A Justification of Conditional Confidence Intervals," Papers 1710.00643, arXiv.org, revised Jan 2019.
    11. F. Campigli & G. Bormetti & F. Lillo, 2022. "Measuring price impact and information content of trades in a time-varying setting," Papers 2212.12687, arXiv.org, revised Dec 2023.
    12. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    13. Gorgi, Paolo & Koopman, Siem Jan & Schaumburg, Julia, 2024. "Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 244(2).
    14. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    15. Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
    16. Mariana Arozo B. de Melo & Cristiano A. C. Fernandes & Eduardo F. L. de Melo, 2018. "Forecasting aggregate claims using score‐driven time series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 354-374, August.
    17. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    18. Olofsson, Petter & Råholm, Anna & Uddin, Gazi Salah & Troster, Victor & Kang, Sang Hoon, 2021. "Ethical and unethical investments under extreme market conditions," International Review of Financial Analysis, Elsevier, vol. 78(C).
    19. Paolo Gorgi & Siem Jan Koopman & Rutger Lit, 2020. "Estimation of final standings in football competitions with premature ending: the case of COVID-19," Tinbergen Institute Discussion Papers 20-070/III, Tinbergen Institute.
    20. Peng, Kang-Lin & Wu, Chih-Hung & Lin, Pearl M.C. & Kou, IokTeng Esther, 2023. "Investor sentiment in the tourism stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    21. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).

  25. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.

    Cited by:

    1. Emilian DOBRESCU, 2017. "Modelling an Emergent Economy and Parameter Instability Problem," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-28, June.
    2. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.

  26. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.

    Cited by:

    1. Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations Of Market Forecasts, And Sentiment," Discussion Papers 17-10, University of Copenhagen. Department of Economics.
    2. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    3. Francisco Blasques & Christian Francq & Sébastien Laurent, 2020. "A New Class of Robust Observation-Driven Models," Tinbergen Institute Discussion Papers 20-073/III, Tinbergen Institute.
    4. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    5. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    6. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    7. Hoeltgebaum, Henrique & Borenstein, Denis & Fernandes, Cristiano & Veiga, Álvaro, 2021. "A score-driven model of short-term demand forecasting for retail distribution centers," Journal of Retailing, Elsevier, vol. 97(4), pages 715-725.
    8. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

  27. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    2. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    3. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    4. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
    5. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    6. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    7. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    8. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    9. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    10. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    11. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.

  28. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.

    Cited by:

    1. Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2025. "Score-driven time-varying parameter models with splinebased densities," Tinbergen Institute Discussion Papers 25-011/III, Tinbergen Institute.
    2. Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    4. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    5. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    6. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
    7. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    8. Harvey, Andrew & Palumbo, Dario, 2023. "Score-driven models for realized volatility," Journal of Econometrics, Elsevier, vol. 237(2).
    9. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    10. Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    12. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
    13. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    14. Harvey, Andrew & Hurn, Stan & Palumbo, Dario & Thiele, Stephen, 2024. "Modelling circular time series," Journal of Econometrics, Elsevier, vol. 239(1).
    15. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    16. Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    17. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    18. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    19. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    20. De Polis, Andrea & Melosi, Leonardo & Petrella, Ivan, 2024. "The Taming of the Skew : Asymmetric Inflation Risk and Monetary Policy," The Warwick Economics Research Paper Series (TWERPS) 1530, University of Warwick, Department of Economics.
    21. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
    22. Frederik Krabbe, 2024. "Asymptotic Properties of the Maximum Likelihood Estimator for Markov-switching Observation-driven Models," Papers 2412.19555, arXiv.org, revised Jul 2025.
    23. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.
    24. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    25. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.
    26. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    27. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    28. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
    29. Francisco Blasques & Siem Jan Koopman & Max Mallee, 2014. "Low Frequency and Weighted Likelihood Solutions for Mixed Frequency Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-105/III, Tinbergen Institute.
    30. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    31. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    32. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    33. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    34. Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2023. "Fiscal Policy Regimes in Resource-Rich Economies," Working Papers No 13/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    35. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    36. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    37. Mariia Artemova & Francisco Blasques & Siem Jan Koopman, 2023. "A Multilevel Factor Model for Economic Activity with Observation Driven Dynamic Factors," Tinbergen Institute Discussion Papers 23-021/III, Tinbergen Institute.
    38. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    39. Francisco Blasques & Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2024. "Robust Multivariate Observation-Driven Filtering for a Common Stochastic Trend: Theory and Application," Tinbergen Institute Discussion Papers 24-062/III, Tinbergen Institute.
    40. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    41. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    42. Gabriele Mingoli, 2024. "Modeling Common Bubbles: A Mixed Causal Non-Causal Dynamic Factor Model," Tinbergen Institute Discussion Papers 24-072/III, Tinbergen Institute.
    43. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    44. Yicong Lin & André Lucas, 2025. "Functional Location-Scale Models with Robust Observation-Driven Dynamics," Tinbergen Institute Discussion Papers 25-027/III, Tinbergen Institute.
    45. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    46. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    47. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    48. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.
    49. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
    50. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    51. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.

  29. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.

    Cited by:

    1. István Barra & Agnieszka Borowska & Siem Jan Koopman, 2018. "Bayesian Dynamic Modeling of High-Frequency Integer Price Changes," Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 384-424.
    2. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.

  30. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations Of Market Forecasts, And Sentiment," Discussion Papers 17-10, University of Copenhagen. Department of Economics.
    3. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    4. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    5. Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
    6. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    7. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    8. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    9. Ioanna-Yvonni Tsaknaki & Fabrizio Lillo & Piero Mazzarisi, 2023. "Online Learning of Order Flow and Market Impact with Bayesian Change-Point Detection Methods," Papers 2307.02375, arXiv.org, revised May 2024.
    10. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

  31. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.

    Cited by:

    1. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    2. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
    3. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.

  32. István Barra & Lennart Hoogerheide & Siem Jan Koopman & André Lucas, 2014. "Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 14-118/III, Tinbergen Institute, revised 31 Mar 2016.

    Cited by:

    1. P. de Zea Bermudez & J. Miguel Marín & Helena Veiga, 2020. "Data cloning estimation for asymmetric stochastic volatility models," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1057-1074, November.
    2. David Winkelmann & Christian Deutscher, 2025. "Do Betting Markets Sense a Goal Coming? Evidence from the German Bundesliga," Papers 2505.21275, arXiv.org.

  33. Francisco Blasques & Siem Jan Koopman & Andre Lucas & Julia Schaumburg, 2014. "Spillover Dynamics for Systemic Risk Measurement using Spatial Financial Time Series Models," Tinbergen Institute Discussion Papers 14-107/III, Tinbergen Institute.

    Cited by:

    1. Narayan, Shivani & Kumar, Dilip, 2024. "Unveiling interconnectedness and risk spillover among cryptocurrencies and other asset classes," Global Finance Journal, Elsevier, vol. 62(C).
    2. Xu, Yuhong & Yang, Zhenlin, 2020. "Specification Tests for Temporal Heterogeneity in Spatial Panel Data Models with Fixed Effects," Regional Science and Urban Economics, Elsevier, vol. 81(C).
    3. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    4. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    5. Nicolas Debarsy & Cyrille Dossougoin & Cem Ertur & Jean-Yves Gnabo, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Post-Print hal-01744629, HAL.
    6. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
    7. Böhm, Hannes & Schaumburg, Julia & Tonzer, Lena, 2020. "Financial linkages and sectoral business cycle synchronisation: Evidence from Europe," IWH Discussion Papers 2/2020, Halle Institute for Economic Research (IWH).
    8. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    9. Capasso, Salvatore & D'Uva, Marcella & Fiorelli, Cristiana & Napolitano, Oreste, 2023. "Cross-border Italian sovereign risk transmission in EMU countries," Economic Modelling, Elsevier, vol. 126(C).
    10. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    11. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    12. Gül Huyugüzel Kışla & Y. Gülnur Muradoğlu & A. Özlem Önder, 2022. "Spillovers from one country’s sovereign debt to CDS (credit default swap) spreads of others during the European crisis: a spatial approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 277-296, July.
    13. Niko Hauzenberger & Michael Pfarrhofer, 2021. "Bayesian State‐Space Modeling for Analyzing Heterogeneous Network Effects of US Monetary Policy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(4), pages 1261-1291, October.
    14. Hüttner, Amelie & Scherer, Matthias & Gräler, Benedikt, 2020. "Geostatistical modeling of dependent credit spreads: Estimation of large covariance matrices and imputation of missing data," Journal of Banking & Finance, Elsevier, vol. 118(C).
    15. Qicheng Zhao & Zhouwei Wang & Yuping Song, 2024. "Systematic Research on Multi-dimensional and Multiple Correlation Contagion Networks of Extreme Risk in China’s Banking Industry," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1137-1162, August.
    16. Agathe Sadeghi & Zachary Feinstein, 2024. "Statistical Validation of Contagion Centrality in Financial Networks," Papers 2404.14337, arXiv.org, revised Feb 2025.
    17. Zornitsa Todorova, 2020. "Network Risk in the European Sovereign CDS Market," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 12(2), pages 137-154, December.
    18. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring interconnectedness between financial institutions with Bayesian time-varying vector autoregressions," Working Papers ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    19. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
    20. Li, Liyao & Yang, Zhenlin, 2020. "Estimation of fixed effects spatial dynamic panel data models with small T and unknown heteroskedasticity," Regional Science and Urban Economics, Elsevier, vol. 81(C).
    21. Yun Feng & Xin Li, 2021. "Does cross-shareholding lead to China's stock returns comovement? Evidence from a GMM-based spatial AR model," Empirical Economics, Springer, vol. 61(6), pages 3213-3237, December.
    22. Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    23. F. Blasques & P. Gorgi & S. J. Koopman & J. Sampi, 2023. "Does trade integration imply growth in Latin America? Evidence from a dynamic spatial spillover model," Tinbergen Institute Discussion Papers 23-007/IVI, Tinbergen Institute.
    24. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
    25. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    26. Sophie Béreau & Nicolas Debarsy & Cyrille Dossougoin & Jean-Yves Gnabo, 2022. "Contagion in the Banking Industry: a Robust-to-Endogeneity Analysis," Working Papers halshs-03513049, HAL.
    27. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    28. Deng, Chao & Su, Xiaojian & Wang, Gangjin & Peng, Cheng, 2022. "The existence of flight-to-quality under extreme conditions: Evidence from a nonlinear perspective in Chinese stocks and bonds' sectors," Economic Modelling, Elsevier, vol. 113(C).
    29. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    30. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    31. Marius C. O. Amba & Julie Gallo, 2022. "Specification and estimation of a periodic spatial panel autoregressive model," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-34, December.
    32. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    33. Lee, Chien-Chiang & Zhou, Hegang & Xu, Chao & Zhang, Xiaoming, 2023. "Dynamic spillover effects among international crude oil markets from the time-frequency perspective," Resources Policy, Elsevier, vol. 80(C).
    34. Shinya Fukui, 2020. "Business Cycle Spatial Synchronization: Measuring a Synchronization Parameter," Discussion Papers 2009, Graduate School of Economics, Kobe University.
    35. Chengliang Liu & Qingbin Guo, 2019. "Technology Spillover Effect in China: The Spatiotemporal Evolution and Its Drivers," Sustainability, MDPI, vol. 11(6), pages 1-14, March.
    36. Tim Kutzker & Dominik Wied, 2024. "Testing the correct specification of a system of spatial dependence models for stock returns," Empirical Economics, Springer, vol. 66(5), pages 2083-2103, May.
    37. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2018. "Networks in risk spillovers: A multivariate GARCH perspective," SAFE Working Paper Series 225, Leibniz Institute for Financial Research SAFE.
    38. Rubo Zhao & Yixiang Tian & Ao Lei & Francis Boadu & Ze Ren, 2019. "The Effect of Local Government Debt on Regional Economic Growth in China: A Nonlinear Relationship Approach," Sustainability, MDPI, vol. 11(11), pages 1-22, May.
    39. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
    40. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    41. Hongjun Zeng & Ran Lu & Abdullahi D. Ahmed, 2023. "Dynamic dependencies and return connectedness among stock, gold and Bitcoin markets: Evidence from South Asia and China," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 18(1), pages 49-87, March.
    42. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    43. Pino, Gabriel & Herrera, Rodrigo & Rodríguez, Alejandro, 2019. "Geographical spillovers on the relation between risk-taking and market power in the US banking sector," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 351-364.
    44. Matteo Foglia & Eliana Angelini, 2019. "The Time-Spatial Dimension of Eurozone Banking Systemic Risk," Risks, MDPI, vol. 7(3), pages 1-25, July.
    45. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
    46. Chen, Na & Jin, Xiu, 2020. "Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    47. Yun Feng & Xin Li, 2022. "The Cross-Shareholding Network and Risk Contagion from Stochastic Shocks: An Investigation Based on China’s Market," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 357-381, January.
    48. Füss, Roland & Ruf, Daniel, 2021. "Bank systemic risk exposure and office market interconnectedness," Journal of Banking & Finance, Elsevier, vol. 133(C).
    49. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    50. Chen, Na & Jin, Xiu, 2023. "Cross-industry asset allocation with the spatial interaction on multiple risk transmission channels," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    51. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    52. Berloco, Claudia & Argiento, Raffaele & Montagna, Silvia, 2023. "Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1065-1077.
    53. Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    54. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2024. "Temporal networks and financial contagion," Journal of Financial Stability, Elsevier, vol. 71(C).
    55. Guo, Juncong & Qu, Xi, 2020. "Fixed effects spatial panel data models with time-varying spatial dependence," Economics Letters, Elsevier, vol. 196(C).
    56. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    57. Zheng, Yingfei & Shen, Anran & Li, Ruihai & Yang, Yuhong & Wang, Shengjin & Cheng, Lee-Young, 2023. "Spillover effects between internet financial industry and traditional financial industry: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    58. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    59. Jingyi TIAN & Jun NAGAYASU, 2024. "AI and Financial Systemic Risk in the Global Market," TUPD Discussion Papers 55, Graduate School of Economics and Management, Tohoku University.
    60. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    61. Ou Bianling & Zhao Xin & Wang Mingxi, 2015. "Power of Moran’s I Test for Spatial Dependence in Panel Data Models with Time Varying Spatial Weights Matrices," Journal of Systems Science and Information, De Gruyter, vol. 3(5), pages 463-471, October.
    62. Peter Schwendner & Martin Schuele & Thomas Ott & Martin Hillebrand, 2015. "European Government Bond Dynamics and Stability Policies: Taming Contagion Risks," Working Papers 8, European Stability Mechanism.
    63. J. W. Muteba Mwamba & Mathias Manguzvane, 2020. "Contagion risk in african sovereign debt markets: A spatial econometrics approach," International Finance, Wiley Blackwell, vol. 23(3), pages 506-536, December.
    64. Katarina Valaskova & Tomas Kliestik & Lucia Svabova & Peter Adamko, 2018. "Financial Risk Measurement and Prediction Modelling for Sustainable Development of Business Entities Using Regression Analysis," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
    65. Debarsy, Nicolas & Yang, Zhenlin, 2018. "Editorial for the special issue entitled: New advances in spatial econometrics: Interactions matter," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 1-5.
    66. Choi, Sun-Yong, 2022. "Credit risk interdependence in global financial markets: Evidence from three regions using multiple and partial wavelet approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    67. Dieter Wang & Julia Schaumburg, 2020. "Smooth marginalized particle filters for dynamic network effect models," Tinbergen Institute Discussion Papers 20-023/III, Tinbergen Institute.
    68. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.
    69. Capasso Salvatore & D’Uva Marcella, & Fiorelli Cristiana & Napolitano Oreste, 2022. "Assessing the Impact of Country-Specific Sovereign Risk on Financial and Banking System in EMU: the Role of Italy," CSEF Working Papers 654, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    70. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    71. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.

  34. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Time Varying Transition Probabilities for Markov Regime Switching Models," Tinbergen Institute Discussion Papers 14-072/III, Tinbergen Institute.

    Cited by:

    1. Chotipong Charoensom, 2024. "An Estimation of Regime Switching Models with Nonlinear Endogenous Switching," PIER Discussion Papers 217, Puey Ungphakorn Institute for Economic Research.
    2. Christopher K. Allsup & Irene S. Gabashvili, 2024. "Modeling the Dynamics of Growth in Master-Planned Communities," Papers 2408.14214, arXiv.org, revised Aug 2024.
    3. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    4. Marie Bessec, 2019. "Revisiting the transitional dynamics of business-cycle phases with mixed-frequency data," Post-Print hal-02181552, HAL.
    5. Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021. "Origins of monetary policy shifts: A New approach to regime switching in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    6. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    7. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    8. Holm-Hadulla, Fédéric & Hubrich, Kirstin, 2017. "Macroeconomic implications of oil price fluctuations: a regime-switching framework for the euro area," Working Paper Series 2119, European Central Bank.
    9. Paul Doukhan & Konstantinos Fokianos & Joseph Rynkiewicz, 2021. "Mixtures of Nonlinear Poisson Autoregressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 107-135, January.
    10. Yoosoon Chang & Junior Maih & Fei Tan, 2018. "State Space Models with Endogenous Regime Switching," Working Papers No 9/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    11. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    12. Lu, Xinjie & Zeng, Qing & Zhong, Juandan & Zhu, Bo, 2024. "International stock market volatility: A global tail risk sight," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    13. Stefano Grassi & Francesco Ravazzolo & Joaquin Vespignani & Giorgio Vocalelli, 2023. "Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach," BEMPS - Bozen Economics & Management Paper Series BEMPS100, Faculty of Economics and Management at the Free University of Bozen.
    14. Aye, Goodness C. & Chang, Tsangyao & Gupta, Rangan, 2016. "Is gold an inflation-hedge? Evidence from an interrupted Markov-switching cointegration model," Resources Policy, Elsevier, vol. 48(C), pages 77-84.
    15. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    16. Keddad, Benjamin, 2024. "Asian stock market volatility and economic policy uncertainty: The role of world and regional leaders," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    17. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    18. Zacharias Psaradakis & Martin Sola, 2017. "Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities," Birkbeck Working Papers in Economics and Finance 1702, Birkbeck, Department of Economics, Mathematics & Statistics.
    19. Chang, Yoosoon & Choi, Yongok & Park, Joon Y., 2017. "A new approach to model regime switching," Journal of Econometrics, Elsevier, vol. 196(1), pages 127-143.
    20. Tharcisio Leone, 2019. "Intergenerational Mobility in Education: Estimates of the Worldwide Variation," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(4), pages 1-42, December.
    21. Spezia, Luigi, 2020. "Bayesian variable selection in non-homogeneous hidden Markov models through an evolutionary Monte Carlo method," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    22. Mohammad Enamul Hoque & Mohd Azlan Shah Zaidi & M. Kabir Hassan, 2021. "Geopolitical Uncertainties and Malaysian Stock Market Returns: Do Market Conditions Matter?," Mathematics, MDPI, vol. 9(19), pages 1-16, September.
    23. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.
    24. Zeng, Qing & Zhang, Jixiang & Zhong, Juandan, 2024. "China's futures market volatility and sectoral stock market volatility prediction," Energy Economics, Elsevier, vol. 132(C).
    25. Wang, Lu & Ma, Feng & Hao, Jianyang & Gao, Xinxin, 2021. "Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?," International Review of Financial Analysis, Elsevier, vol. 76(C).
    26. Jonathan Olusegun Famoroti & Omolade Adeleke, 2023. "Analysis of Wamz’s Economic Growth and Monetary Policy Using the Markov Switching Approach," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(4), pages 142-156, April.
    27. Kirstin Hubrich & Daniel F. Waggoner, 2022. "The transmission of financial shocks and leverage of financial institutions: An endogenous regime switching framework," Finance and Economics Discussion Series 2022-034, Board of Governors of the Federal Reserve System (U.S.).
    28. Lu, Xinjie & Ma, Feng & Li, Haibo & Wang, Jianqiong, 2023. "INE oil futures volatility prediction: Exchange rates or international oil futures volatility?," Energy Economics, Elsevier, vol. 126(C).
    29. Leone, Tharcisio, 2021. "The gender gap in intergenerational mobility," World Development Perspectives, Elsevier, vol. 21(C).
    30. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    31. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
    32. Bram van Os & Dick van Dijk, 2020. "Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model," Tinbergen Institute Discussion Papers 20-057/VI, Tinbergen Institute, revised 14 Dec 2020.
    33. Giulio Cifarelli, 2023. "Commodity Pricing Volatility Shifts in a Highly Turbulent Time Period. A Time-varying Transition Probability Markov Switching Analysis," Working Papers - Economics wp2023_11.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    34. Qingfu Liu & Yiuman Tse & Kaixin Zheng, 2021. "The impact of trading behavioral biases on market liquidity under different volatility levels: Evidence from the Chinese commodity futures market," The Financial Review, Eastern Finance Association, vol. 56(4), pages 671-692, November.
    35. Andrei A. Sirchenko, 2017. "An endogenous regime-switching model of ordered choice with an application to federal funds rate target," 2017 Papers psi424, Job Market Papers.
    36. Stefan Fiesel & Marliese Uhrig-Homburg, 2016. "Illiquidity Transmission in a Three-Country Framework: A Conditional Approach," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 17(3), pages 261-284, December.
    37. Marie Bessec, 2015. "Revisiting the transitional dynamics of business-cycle phases with mixed frequency data," Post-Print hal-01276824, HAL.
    38. Leone, Tharcisio, 2017. "The gender gap in intergenerational mobility: Evidence of educational persistence in Brazil," Discussion Papers 2017/27, Free University Berlin, School of Business & Economics.
    39. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    40. Paidamoyo Aurleen Shenjere & Sune Ferreira-Schenk & Fabian Moodley, 2025. "Does Investor Sentiment Influence South African ETF Flows During Different Market Conditions?," Economies, MDPI, vol. 13(1), pages 1-19, January.

  35. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).

    Cited by:

    1. Tola, Albi & Wälti, Sébastien, 2012. "Deciphering financial contagion in the euro area during the crisis," MPRA Paper 49251, University Library of Munich, Germany.
    2. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Nucera, Federico, 2016. "The information in systemic risk rankings," Working Paper Series 1875, European Central Bank.
    3. Russell Cooper & Kalin Nikolov, 2013. "Government Debt and Banking Fragility: The Spreading of Strategic Uncertainty," NBER Working Papers 19278, National Bureau of Economic Research, Inc.
    4. Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Hoang Nguyen & Audron.e Virbickait.e & M. Concepci'on Aus'in & Pedro Galeano, 2024. "Structured factor copulas for modeling the systemic risk of European and United States banks," Papers 2401.03443, arXiv.org.
    6. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    7. Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
    8. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    9. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    10. Augustin, Patrick & Subrahmanyam, Marti G. & Tang, Dragon Yongjun & Wang, Sarah Qian, 2014. "Credit Default Swaps: A Survey," Foundations and Trends(R) in Finance, now publishers, vol. 9(1-2), pages 1-196, December.
    11. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    12. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
    13. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    14. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    15. Harvey, Andrew & Palumbo, Dario, 2023. "Score-driven models for realized volatility," Journal of Econometrics, Elsevier, vol. 237(2).
    16. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    17. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    18. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    19. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    20. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    21. Ehrmann, Michael & Fratzscher, Marcel, 2017. "Euro area government bonds – Fragmentation and contagion during the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 26-44.
    22. Brownlees, Christian & Engle, Robert F., 2017. "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series 37, European Systemic Risk Board.
    23. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula," Working Papers 2015_15, Business School - Economics, University of Glasgow.
    24. Marta Gómez-Puig & Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2014. "“An Update on EMU Sovereign Yield Spread Drivers in Times of Crisis: A Panel Data Analysis”," IREA Working Papers 201407, University of Barcelona, Research Institute of Applied Economics, revised Mar 2014.
    25. Bernardi Mauro & Roy Cerqueti & Arsen Palestini, 2016. "Allocation of risk capital in a cost cooperative game induced by a modified Expected Shortfall," Papers 1608.02365, arXiv.org.
    26. Michael Ehrmann & Marcel Fratzscher, 2015. "Euro Area Government Bonds: Integration and Fragmentation during the Sovereign Debt Crisis," Discussion Papers of DIW Berlin 1479, DIW Berlin, German Institute for Economic Research.
    27. Joshua Aizenman & Mahir Binici & Michael Mercier Hutchison, 2013. "Credit Ratings and the Pricing of Sovereign Debt during the Euro Crisis," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 5, Ekonomik Yaklasim Association.
    28. Alain MONFORT & Jean-Paul RENNE & Guillaume ROUSSELLET, 2020. "Affine Modeling of Credit Risk, Pricing of Credit Events and Contagion," Working Papers 2020-01, Center for Research in Economics and Statistics.
    29. Gül Huyugüzel Kışla & Y. Gülnur Muradoğlu & A. Özlem Önder, 2022. "Spillovers from one country’s sovereign debt to CDS (credit default swap) spreads of others during the European crisis: a spatial approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 277-296, July.
    30. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    31. André Lucas & Julia Schaumburg & Bernd Schwaab, 2019. "Bank Business Models at Zero Interest Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 542-555, July.
    32. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    33. Riadh El Abed & Sahar Boukadida & Warda Jaidane, 2019. "Financial Stress Transmission from Sovereign Credit Market to Financial Market: A Multivariate FIGARCH-DCC Approach," Global Business Review, International Management Institute, vol. 20(5), pages 1122-1140, October.
    34. Massimiliano Caporin & Loriana Pelizzon & Francesco Ravazzolo & Roberto Rigobon, 2013. "Measuring Sovereign Contagion in Europe," NBER Working Papers 18741, National Bureau of Economic Research, Inc.
    35. Morgan Escalera & Wayne Tarrant, 2018. "Sovereign Adaptive Risk Modeling and Implications for the Eurozone GREXIT Case," IJFS, MDPI, vol. 6(2), pages 1-11, May.
    36. Arbia, Giuseppe & Bramante, Riccardo & Facchinetti, Silvia & Zappa, Diego, 2018. "Modeling inter-country spatial financial interactions with Graphical Lasso: An application to sovereign co-risk evaluation," Regional Science and Urban Economics, Elsevier, vol. 70(C), pages 72-79.
    37. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2016. "Causes and hazards of the euro area sovereign debt crisis: Pure and fundamentals-based contagion," Economic Modelling, Elsevier, vol. 56(C), pages 133-147.
    38. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    39. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    40. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    41. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    42. Pierre-Richard Agénor & Luiz A. Pereira da Silva, 2022. "Financial spillovers, spillbacks, and the scope for international macroprudential policy coordination," International Economics and Economic Policy, Springer, vol. 19(1), pages 79-127, February.
    43. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    44. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    45. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    46. Marta Gómez-Puig & Simón Sosvilla-Rivero, 2014. "EMU sovereign debt market crisis: Fundamentals-based or pure contagion?," Working Papers 14-08, Asociación Española de Economía y Finanzas Internacionales.
    47. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    48. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    49. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    50. Pagano, Michael S. & Sedunov, John, 2016. "A comprehensive approach to measuring the relation between systemic risk exposure and sovereign debt," Journal of Financial Stability, Elsevier, vol. 23(C), pages 62-78.
    51. Michael A. Goldstein & Joseph McCarthy & Alexei G. Orlov, 2019. "The Core, Periphery, and Beyond: Stock Market Comovements among EU and Non‐EU Countries," The Financial Review, Eastern Finance Association, vol. 54(1), pages 5-56, February.
    52. Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2017. "Credit risk interconnectedness: What does the market really know?," Journal of Financial Stability, Elsevier, vol. 29(C), pages 1-12.
    53. Fuertes, Ana-Maria & Kalotychou, Elena & Saka, Orkun, 2014. "ECB Policy and Eurozone Fragility: Was De Grauwe Right?," CEPS Papers 9414, Centre for European Policy Studies.
    54. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    55. Nadal De Simone, Francisco, 2021. "Measuring the deadly embrace: Systemic and sovereign risks," Research in International Business and Finance, Elsevier, vol. 56(C).
    56. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    57. Dieppe, Alistair & Mourinho Félix, Ricardo & Marchiori, Luca & Grech, Owen & Albani, Maria & Lalouette, Laure & Kulikov, Dmitry & Papadopoulou, Niki & Sideris, Dimitris & Irac, Delphine & Gordo Mora, , 2015. "Public debt, population ageing and medium-term growth," Occasional Paper Series 165, European Central Bank.
    58. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
    59. Burkhard Raunig, 2018. "Economic Policy Uncertainty and the Volatility of Sovereign CDS Spreads," Working Papers 219, Oesterreichische Nationalbank (Austrian Central Bank).
    60. Choe, Geon Ho & Choi, So Eun & Jang, Hyun Jin, 2020. "Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    61. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
    62. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    63. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    64. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    65. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    66. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2017. "Multiple risk measures for multivariate dynamic heavy–tailed models," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 1-32.
    67. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
    68. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    69. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    70. Clancy, Daragh & Gabriele, Carmine & Žigraiová, Diana, 2022. "Sovereign bond market spillovers from crisis-time developments in Greece," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    71. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    72. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    73. Mathias Mandla Manguzvane & John Weirstrass Muteba Mwamba, 2022. "South African Banks’ Cross-Border Systemic Risk Exposure: An Application of the GAS Copula Marginal Expected Shortfall," IJFS, MDPI, vol. 10(1), pages 1-19, March.
    74. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2022. "Assessing the impact of policy and regulation interventions in European sovereign credit risk networks: What worked best?," Journal of International Economics, Elsevier, vol. 139(C).
    75. Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    76. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    77. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    78. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    79. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    80. Recchioni, Maria Cristina & Tedeschi, Gabriele, 2017. "From bond yield to macroeconomic instability: A parsimonious affine model," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1116-1135.
    81. Eijffinger, Sylvester C.W. & Pieterse-Bloem, Mary, 2023. "Eurozone government bond spreads: A tale of different ECB policy regimes," Journal of International Money and Finance, Elsevier, vol. 139(C).
    82. Hyun Jin Jang & Kiseop Lee & Kyungsub Lee, 2020. "Systemic Risk in Market Microstructure of Crude Oil and Gasoline Futures Prices: A Hawkes Flocking Model Approach," Papers 2012.04181, arXiv.org.
    83. Breckenfelder, Johannes & Schwaab, Bernd, 2018. "Bank to sovereign risk spillovers across borders: Evidence from the ECB’s Comprehensive Assessment," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 247-262.
    84. Mody, Ashoka & Nedeljkovic, Milan, 2024. "Central bank policies and financial markets: Lessons from the euro crisis," Journal of Banking & Finance, Elsevier, vol. 158(C).
    85. Cifarelli, Giulio & Paladino, Giovanna, 2020. "A non-linear analysis of the sovereign bank nexus in the EU," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    86. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    87. Bartl, Jonas & Bostandzic, Denefa & Irresberger, Felix & Weiß, Gregor & Yang, Ruomei, 2024. "The 2008 short-selling ban’s impact on tail risk," Journal of Empirical Finance, Elsevier, vol. 78(C).
    88. Sachapon Tungsong & Fabio Caccioli & Tomaso Aste, 2017. "Relation between regional uncertainty spillovers in the global banking system," Papers 1702.05944, arXiv.org.
    89. Sedunov, John, 2021. "Federal reserve intervention and systemic risk during financial crises," Journal of Banking & Finance, Elsevier, vol. 133(C).
    90. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
    91. Xiao Jiang & Saralees Nadarajah & Thomas Hitchen, 2024. "A Review of Generalized Hyperbolic Distributions," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 595-624, July.
    92. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    93. Maria Cristina Recchioni & Gabriele Tedeschi, 2016. "From bond yield to macroeconomic instability: The effect of negative interest rates," Working Papers 2016/06, Economics Department, Universitat Jaume I, Castellón (Spain).

  36. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.

  37. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André & Creal, Drew, 2013. "Observation driven mixed-measurement dynamic factor models with an application to credit risk," Working Paper Series 1626, European Central Bank.

    Cited by:

    1. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    2. Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2025. "Score-driven time-varying parameter models with splinebased densities," Tinbergen Institute Discussion Papers 25-011/III, Tinbergen Institute.
    3. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    4. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
    5. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    6. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    7. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    8. Bart Keijsers & Bart Diris & Erik Kole, 2018. "Cyclicality in losses on bank loans," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 533-552, June.
    9. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    10. Moratis, Georgios & Sakellaris, Plutarchos, 2021. "Measuring the systemic importance of banks," Journal of Financial Stability, Elsevier, vol. 54(C).
    11. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    12. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    13. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    14. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    15. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    16. Kun Liang & Cuiqing Jiang & Zhangxi Lin & Weihong Ning & Zelin Jia, 2017. "The nature of sellers’ cyber credit in C2C e-commerce: the perspective of social capital," Electronic Commerce Research, Springer, vol. 17(1), pages 133-147, March.
    17. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    18. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    19. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula," Working Papers 2015_15, Business School - Economics, University of Glasgow.
    20. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    21. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    22. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    23. Pearlean Chadha & Jenny Berrill, 2025. "The Indirect Diversification Benefits of Investing in Japanese Firms: An Alternative Perspective," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 32(1), pages 117-145, March.
    24. Paloma Lopez-Garcia & Filippo di Mauro, 2014. "Assessing competitiveness: initial results from the new compnet micro-based database," Research Bulletin, European Central Bank, vol. 21, pages 2-7.
    25. André Lucas & Julia Schaumburg & Bernd Schwaab, 2019. "Bank Business Models at Zero Interest Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 542-555, July.
    26. Mohamed Belkhir & Sami Ben Naceur & Bertrand Candelon & Jean-Charles Wijnandts, 2020. "Macroprudential Policies, Economic Growth, and Banking Crises," IMF Working Papers 2020/065, International Monetary Fund.
    27. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    28. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
    29. Schwaab, Bernd & Eser, Fabian, 2013. "Assessing asset purchases within the ECB’s securities markets programme," Working Paper Series 1587, European Central Bank.
    30. Goldmann, Leonie & Crook, Jonathan & Calabrese, Raffaella, 2024. "A new ordinal mixed-data sampling model with an application to corporate credit rating levels," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1111-1126.
    31. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    32. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    33. Ha Nguyen, 2023. "Particle MCMC in forecasting frailty correlated default models with expert opinion," Papers 2304.11586, arXiv.org, revised Aug 2023.
    34. Krist'of N'emeth & D'aniel Hadh'azi, 2024. "Generating density nowcasts for U.S. GDP growth with deep learning: Bayes by Backprop and Monte Carlo dropout," Papers 2405.15579, arXiv.org.
    35. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    36. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    37. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    38. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    39. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    40. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
    41. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    42. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    43. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    44. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    45. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    46. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    47. Wang, Fa, 2022. "Maximum likelihood estimation and inference for high dimensional generalized factor models with application to factor-augmented regressions," Journal of Econometrics, Elsevier, vol. 229(1), pages 180-200.
    48. Sebastian Schmidt, 2014. "Dealing with a liquidity trap when government debt matters," Research Bulletin, European Central Bank, vol. 21, pages 8-11.
    49. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    50. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.
    51. Ha Nguyen, 2023. "Particle MCMC in Forecasting Frailty-Correlated Default Models with Expert Opinion," JRFM, MDPI, vol. 16(7), pages 1-16, July.
    52. Markus Leippold & Hanlin Yang, 2023. "Mixed‐frequency predictive regressions with parameter learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1955-1972, December.
    53. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    54. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    55. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    56. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    57. Li, Aimin & Li, Zhiyong & Bellotti, Anthony, 2023. "Predicting loss given default of unsecured consumer loans with time-varying survival scores," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    58. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    59. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    60. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    61. James Wolter, 2013. "Separating the impact of macroeconomic variables and global frailty in event data," Economics Series Working Papers 667, University of Oxford, Department of Economics.
    62. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    63. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    64. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    65. Antoine Djogbenou & Christian Gouri'eroux & Joann Jasiak & Maygol Bandehali, 2021. "Composite Likelihood for Stochastic Migration Model with Unobserved Factor," Papers 2109.09043, arXiv.org, revised Nov 2023.
    66. Francisco Blasques & Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2024. "Robust Multivariate Observation-Driven Filtering for a Common Stochastic Trend: Theory and Application," Tinbergen Institute Discussion Papers 24-062/III, Tinbergen Institute.
    67. Caterina Mendicino, 2014. "House prices and expectations," Research Bulletin, European Central Bank, vol. 21, pages 12-15.
    68. Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    69. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    70. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    71. Giuseppe Buccheri & Fulvio Corsi & Emilija Dzuverovic, 2024. "From rotational to scalar invariance: Enhancing identifiability in score-driven factor models," Papers 2412.01367, arXiv.org.
    72. Mariana Arozo B. de Melo & Cristiano A. C. Fernandes & Eduardo F. L. de Melo, 2018. "Forecasting aggregate claims using score‐driven time series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 354-374, August.
    73. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    74. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    75. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    76. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    77. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
    78. Anisa Caja & Quentin Guibert & Frédéric Planchet, 2015. "Influence of Economic Factors on the Credit Rating Transitions and Defaults of Credit Insurance Business," Working Papers hal-01178812, HAL.
    79. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    80. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
    81. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    82. Hirk, Rainer & Vana, Laura & Hornik, Kurt, 2022. "A corporate credit rating model with autoregressive errors," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 224-240.

  38. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.

    Cited by:

    1. Yuta Kurose & Yasuhiro Omori, 2014. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-941, CIRJE, Faculty of Economics, University of Tokyo.
    2. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    3. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models," Tinbergen Institute Discussion Papers 15-083/III, Tinbergen Institute.
    4. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-953, CIRJE, Faculty of Economics, University of Tokyo.
    5. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    6. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    7. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Bounds for Time-Varying Parameters of Observation Driven Models," Tinbergen Institute Discussion Papers 15-027/III, Tinbergen Institute, revised 07 Sep 2015.

  39. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.

    Cited by:

    1. Fratzscher, Marcel & Rieth, Malte, 2015. "Monetary policy, bank bailouts and the sovereign-bank risk nexus in the euro area," CEPR Discussion Papers 10370, C.E.P.R. Discussion Papers.
    2. Andreeva, Desislava & Vlassopoulos, Thomas, 2016. "Home bias in bank sovereign bond purchases and the bank-sovereign nexus," Working Paper Series 1977, European Central Bank.

  40. Roman Kraussl & Andre Lucas & David R. Rijsbergen & Pieter Jelle van der Sluis & Evert B. Vrugt, 2013. "Washington Meets Wall Street: A Closer Examination of the Presidential Cylce Puzzle," LSF Research Working Paper Series 13-4, Luxembourg School of Finance, University of Luxembourg.

    Cited by:

    1. Eric Dubois, 2016. "Political business cycles 40 years after Nordhaus," Public Choice, Springer, vol. 166(1), pages 235-259, January.
    2. Samar Ashour & David A. Rakowski & Salil K. Sarkar, 2019. "U.S. presidential cycles and the foreign exchange market," Review of Financial Economics, John Wiley & Sons, vol. 37(4), pages 523-540, October.
    3. Chan, Kam Fong & Marsh, Terry, 2021. "Asset prices, midterm elections, and political uncertainty," Journal of Financial Economics, Elsevier, vol. 141(1), pages 276-296.
    4. Eric Dubois, 2016. "Political Business Cycles 40 Years after Nordhaus," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01291401, HAL.
    5. Alnahedh, Saad & Alhashel, Bader, 2024. "Firm executive political leanings, Washington, and stock market returns," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 476-491.
    6. Samar Ashour & David Rakowski & Salil K. Sarkar, 2021. "Currency risk exposure and the presidential effect in stock returns," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(3), pages 469-485, July.
    7. Eric Dubois, 2016. "Political Business Cycles 40 Years after Nordhaus," Post-Print hal-01291401, HAL.
    8. Wisniewski, Tomasz Piotr, 2016. "Is there a link between politics and stock returns? A literature survey," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 15-23.
    9. Alvarez-Ramirez, J. & Rodriguez, E. & Ibarra-Valdez, C., 2020. "Medium-term cycles in the dynamics of the Dow Jones Index for the period 1985–2019," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    10. William T. Chittenden, 2020. "Political Parties In Power And U.S. Economic Performance," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 14(2), pages 21-36.

  41. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2012. "Dynamic factor models with macro, frailty and industry effects for US default counts: the credit crisis of 2008," Working Paper Series 1459, European Central Bank.

    Cited by:

    1. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    2. Raffaella Calabrese & Johan A. Elkink & Paolo Giudici, 2014. "Measuring Bank Contagion in Europe Using Binary Spatial Regression Models," DEM Working Papers Series 096, University of Pavia, Department of Economics and Management.
    3. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    4. Pedro H. C. Sant’Anna, 2017. "Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 349-358, July.
    5. Philip Vermeulen, 2012. "Bank dependence and investment during the financial crisis," Research Bulletin, European Central Bank, vol. 17, pages 12-14.
    6. Nickerson, Jordan & Griffin, John M., 2017. "Debt correlations in the wake of the financial crisis: What are appropriate default correlations for structured products?," Journal of Financial Economics, Elsevier, vol. 125(3), pages 454-474.
    7. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    8. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    9. Schwaab, Bernd & Eser, Fabian, 2013. "Assessing asset purchases within the ECB’s securities markets programme," Working Paper Series 1587, European Central Bank.
    10. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    11. Ha Nguyen, 2023. "Particle MCMC in forecasting frailty correlated default models with expert opinion," Papers 2304.11586, arXiv.org, revised Aug 2023.
    12. De Santis, Roberto A., 2018. "Unobservable country bond premia and fragmentation," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 1-25.
    13. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    14. Josef Brechler & Vaclav Hausenblas & Zlatuse Komarkova & Miroslav Plasil, 2014. "Similarity and Clustering of Banks: Application to the Credit Exposures of the Czech Banking Sector," Research and Policy Notes 2014/04, Czech National Bank, Research and Statistics Department.
    15. Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.
    16. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    17. Ho, Kung-Cheng & Yen, Huang-Ping & Gu, Yan & Shi, Lisi, 2020. "Does societal trust make firms more trustworthy?," Emerging Markets Review, Elsevier, vol. 42(C).
    18. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    19. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    20. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    21. Liu, Zhenqing & Luo, Yi & Duan, Mohan, 2025. "Macroeconomic factors, industrial enterprises, and debt default prediction: Based on the VAR-GRU model," Finance Research Letters, Elsevier, vol. 78(C).
    22. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2021. "Systematic credit risk in securitised mortgage portfolios," Journal of Banking & Finance, Elsevier, vol. 122(C).
    23. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    24. Simone Manganelli, 2012. "The impact of the Securities Markets Programme," Research Bulletin, European Central Bank, vol. 17, pages 2-5.
    25. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    26. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    27. Sopitpongstorn, Nithi & Silvapulle, Param & Gao, Jiti & Fenech, Jean-Pierre, 2021. "Local logit regression for loan recovery rate," Journal of Banking & Finance, Elsevier, vol. 126(C).
    28. Truong, Chi & Trück, Stefan, 2016. "It’s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events," European Journal of Operational Research, Elsevier, vol. 253(3), pages 856-868.
    29. Geert Mesters & Bernd Schwaab & Siem Jan Koopman, 2014. "A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area," Tinbergen Institute Discussion Papers 14-071/III, Tinbergen Institute.
    30. Campolieti, Michele & Gefang, Deborah & Koop, Gary, 2014. "A new look at variation in employment growth in Canada: The role of industry, provincial, national and external factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 257-275.
    31. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    32. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    33. Choros-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2013. "CDO surfaces dynamics," SFB 649 Discussion Papers 2013-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "A new look at variation in employment growth in Canada," Working Papers 26145565, Lancaster University Management School, Economics Department.
    35. Qin, Zhaohui & Wang, Xiaowan & Chen, Yijie & Fan, Yali & Andrianarimanana, Mihasina Harinaivo & Gai, Dhornor Tarir Duok, 2024. "Time-varying default risk of Chinese-listed companies: From empirical test to theoretical conjecture," Finance Research Letters, Elsevier, vol. 67(PA).

  42. Andre Lucas & Bastiaan Verhoef, 2012. "Aggregating Credit and Market Risk: The Impact of Model Specification," Tinbergen Institute Discussion Papers 12-057/2/DSF36, Tinbergen Institute.

    Cited by:

    1. Szybisz, Martin Andres, 2019. "Interactions between Credit and Market Risk, Diversification vs Compounding effects," MPRA Paper 93173, University Library of Munich, Germany.
    2. Božović, Miloš & Ivanović, Jelena, 2017. "Adverse risk interaction: An integrated approach," Economic Modelling, Elsevier, vol. 65(C), pages 67-74.

  43. Kris Boudt & Jon Danielsson & Siem Jan Koopman & Andre Lucas, 2012. "Regime switches in the volatility and correlation of financial institutions," Working Paper Research 227, National Bank of Belgium.

    Cited by:

    1. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
    2. BAUWENS, Luc & otranto, EDOARDO, 2013. "Modeling the dependence of conditional correlations on volatility," LIDAM Discussion Papers CORE 2013014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. H. Dewachter & G. de Walque & M. Emiris & P. Ilbas & J. Mitchell & R. Wouters, 2012. "Endogenous financial risk : The seventh international conference of the NBB," Economic Review, National Bank of Belgium, issue iii, pages 135-146, December.
    4. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.

  44. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.

    Cited by:

    1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    2. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    3. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    4. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    5. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    6. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    7. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    8. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    9. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    10. Sherzod N. Tashpulatov, 2022. "Modeling Electricity Price Dynamics Using Flexible Distributions," Mathematics, MDPI, vol. 10(10), pages 1-15, May.
    11. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    12. Roy Cerqueti & Raffaele Mattera & Germana Scepi, 2024. "Multiway clustering with time-varying parameters," Computational Statistics, Springer, vol. 39(1), pages 51-92, February.
    13. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    14. Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
    15. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    16. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    17. Lange, Rutger-Jan, 2024. "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, vol. 238(2).
    18. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    19. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    20. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    21. Lin Zhao & Sweder van Wijnbergen, 2015. "Asset Pricing in Incomplete Markets: Valuing Gas Storage Capacity," Tinbergen Institute Discussion Papers 15-104/VI/DSF95, Tinbergen Institute.
    22. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    23. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    24. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    25. Hoang Nguyen & Trong-Nghia Nguyen & Minh-Ngoc Tran, 2023. "A dynamic leverage stochastic volatility model," Applied Economics Letters, Taylor & Francis Journals, vol. 30(1), pages 97-102, January.
    26. Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    27. Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
    28. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    29. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    30. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, Enero-Abr.
    31. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    32. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.
    33. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    34. Nonejad, Nima, 2018. "Déjà vol oil? Predicting S&P 500 equity premium using crude oil price volatility: Evidence from old and recent time-series data," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 260-270.
    35. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    36. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    37. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
    38. Nima Nonejad, 2020. "Does the price of crude oil help predict the conditional distribution of aggregate equity return?," Empirical Economics, Springer, vol. 58(1), pages 313-349, January.
    39. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    40. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    41. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    42. Cem Cakmakli & Yasin Simsek, 2020. "Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model," Papers 2007.02726, arXiv.org, revised Feb 2021.
    43. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    44. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    45. Helske, Jouni, 2017. "KFAS: Exponential Family State Space Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i10).
    46. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
    47. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    48. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    49. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    50. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    51. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    52. Huawei Niu & Tianyu Liu, 2024. "Forecasting the volatility of European Union allowance futures with macroeconomic variables using the GJR-GARCH-MIDAS model," Empirical Economics, Springer, vol. 67(1), pages 75-96, July.
    53. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    54. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Mar 2025.
    55. Alexander Kreuzer & Luciana Dalla Valle & Claudia Czado, 2022. "A Bayesian non‐linear state space copula model for air pollution in Beijing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 613-638, June.
    56. Bram van Os & Dick van Dijk, 2020. "Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model," Tinbergen Institute Discussion Papers 20-057/VI, Tinbergen Institute, revised 14 Dec 2020.
    57. T. -N. Nguyen & M. -N. Tran & R. Kohn, 2020. "Recurrent Conditional Heteroskedasticity," Papers 2010.13061, arXiv.org, revised Jan 2022.
    58. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    59. Nima Nonejad, 2021. "Using the conditional volatility channel to improve the accuracy of aggregate equity return predictions," Empirical Economics, Springer, vol. 61(2), pages 973-1009, August.
    60. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    61. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    62. Xie, Nan & Wang, Zongrun & Chen, Sicen & Gong, Xu, 2019. "Forecasting downside risk in China’s stock market based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 530-541.
    63. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    64. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    65. Niu, Zibo & Ma, Feng & Zhang, Hongwei, 2022. "The role of uncertainty measures in volatility forecasting of the crude oil futures market before and during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 112(C).
    66. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    67. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    68. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    69. Hashem Zarafat & Sascha Liebhardt & Mustafa Hakan Eratalay, 2022. "Do ESG Ratings Reduce the Asymmetry Behavior in Volatility?," JRFM, MDPI, vol. 15(8), pages 1-32, July.
    70. Harvey, A. & Liao, Y., 2019. "Dynamic Tobit models," Cambridge Working Papers in Economics 1913, Faculty of Economics, University of Cambridge.
    71. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    72. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    73. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
    74. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    75. Chen Liu & Minh-Ngoc Tran & Chao Wang & Richard Gerlach & Robert Kohn, 2023. "Global Neural Networks and The Data Scaling Effect in Financial Time Series Forecasting," Papers 2309.02072, arXiv.org, revised Feb 2025.

  45. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    2. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    3. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    4. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    5. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    6. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    7. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    8. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    9. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    10. Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
    11. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    12. David Ardia & Kris Boudt & Leopoldo Catania, 2016. "Generalized Autoregressive Score Models in R: The GAS Package," Papers 1609.02354, arXiv.org.
    13. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.

  46. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.

    Cited by:

    1. Tola, Albi & Wälti, Sébastien, 2012. "Deciphering financial contagion in the euro area during the crisis," MPRA Paper 49251, University Library of Munich, Germany.
    2. Augustin, Patrick & Subrahmanyam, Marti G. & Tang, Dragon Yongjun & Wang, Sarah Qian, 2014. "Credit Default Swaps: A Survey," Foundations and Trends(R) in Finance, now publishers, vol. 9(1-2), pages 1-196, December.
    3. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    4. Beyer, Andreas & Alter, Adrian, 2013. "The dynamics of spillover effects during the European sovereign debt crisis," Working Paper Series 1558, European Central Bank.
    5. Massimiliano Caporin & Loriana Pelizzon & Francesco Ravazzolo & Roberto Rigobon, 2013. "Measuring Sovereign Contagion in Europe," NBER Working Papers 18741, National Bureau of Economic Research, Inc.
    6. Radev, Deyan, 2013. "Systemic risk and sovereign debt in the Euro area," SAFE Working Paper Series 37, Leibniz Institute for Financial Research SAFE.
    7. Alter, Adrian & Beyer, Andreas, 2014. "The dynamics of spillover effects during the European sovereign debt turmoil," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 134-153.
    8. Ferhat Camlica & Didem Gunes & Etkin Ozen, 2017. "A Financial Connectedness Analysis for Turkey," Working Papers 1719, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    9. Cho-Hoi Hui & Chi-Fai Lo & Xiao-Fen Zheng & Tom Fong, 2018. "Probabilistic approach to measuring early-warning signals of systemic contagion risk," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-25, June.
    10. Cho-Hoi Hui & Chi-Fai Lo & Xiao-Fen Zheng & Tom Fong, 2015. "Measuring Contagion-Induced Funding Liquidity Risk in Sovereign Debt Markets," Working Papers 182015, Hong Kong Institute for Monetary Research.
    11. D’Agostino, Antonello & Ehrmann, Michael, 2014. "The pricing of G7 sovereign bond spreads – The times, they are a-changin," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 155-176.
    12. R. Pianeti & R. Giacometti, 2015. "Estimating the probability of multiple EU sovereign defaults using CDS and bond data," Quantitative Finance, Taylor & Francis Journals, vol. 15(1), pages 61-78, January.
    13. Dieppe, Alistair & Mourinho Félix, Ricardo & Marchiori, Luca & Grech, Owen & Albani, Maria & Lalouette, Laure & Kulikov, Dmitry & Papadopoulou, Niki & Sideris, Dimitris & Irac, Delphine & Gordo Mora, , 2015. "Public debt, population ageing and medium-term growth," Occasional Paper Series 165, European Central Bank.
    14. Gorea, Denis & Radev, Deyan, 2014. "The euro area sovereign debt crisis: Can contagion spread from the periphery to the core?," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 78-100.
    15. Edirisinghe, Chanaka & Gupta, Aparna & Roth, Wendy, 2015. "Risk assessment based on the analysis of the impact of contagion flow," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 209-223.
    16. Constancio, V., 2012. "Contagion and the European debt crisis," Financial Stability Review, Banque de France, issue 16, pages 109-121, April.
    17. Deyan Radev, 2012. "Systemic Risk, Banking and Sovereign Debt in the Euro Area," Working Papers 1207, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    18. Jin, Xisong & Nadal De Simone, Francisco, 2014. "A framework for tracking changes in the intensity of investment funds' systemic risk," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 343-368.
    19. Andrew Ang & Francis A. Longstaff, 2011. "Systemic Sovereign Credit Risk: Lessons from the U.S. and Europe," NBER Working Papers 16982, National Bureau of Economic Research, Inc.
    20. Xisong Jin & Francisco Nadal De Simone, 2016. "Tracking Changes in the Intensity of Financial Sector's Systemic Risk," BCL working papers 102, Central Bank of Luxembourg.
    21. Broto, Carmen & Pérez-Quirós, Gabriel, 2015. "Disentangling contagion among sovereign CDS spreads during the European debt crisis," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 165-179.
    22. Radev, Deyan, 2014. "Assessing systemic fragility: A probabilistic perspective," SAFE Working Paper Series 70, Leibniz Institute for Financial Research SAFE.

  47. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2011. "Systemic risk diagnostics: coincident indicators and early warning signals," Working Paper Series 1327, European Central Bank.

    Cited by:

    1. Matkovskyy, Roman, 2013. "To the Problem of Financial Safety Estimation: the Index of Financial Safety of Turkey," MPRA Paper 47673, University Library of Munich, Germany.
    2. Bierth, Christopher & Irresberger, Felix & Weiß, Gregor N.F., 2015. "Systemic risk of insurers around the globe," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 232-245.
    3. Christian Meine & Hendrik Supper & Gregor N. F. Weiß, 2016. "Is Tail Risk Priced in Credit Default Swap Premia?," Review of Finance, European Finance Association, vol. 20(1), pages 287-336.
    4. Xingxing Ye & Raphael Douady, 2018. "Systemic Risk Indicators Based on Nonlinear PolyModel," JRFM, MDPI, vol. 12(1), pages 1-24, December.
    5. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Biljana Ružièiæ, 2015. "Strengthening of the Swiss Franc through an Example of Housing Loans," Proceedings of FIKUSZ 2015, in: Jolán Velencei (ed.),Proceedings of FIKUSZ '15, pages 153-168, Óbuda University, Keleti Faculty of Business and Management.
    7. Tomas Adam & Sona Benecka, 2013. "Financial Stress Spillover and Financial Linkages between the Euro Area and the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(1), pages 46-64, March.
    8. Olivier de Bandt & Jean-Cyprien Héam & Claire Labonne & Santiago Tavolaro, 2015. "La mesure du risque systémique après la crise financière," Revue économique, Presses de Sciences-Po, vol. 66(3), pages 481-500.
    9. Alexey Vasilenko, 2018. "Systemic Risk and Financial Fragility in the Chinese Economy: A Dynamic Factor Model Approach," Bank of Russia Working Paper Series wps30, Bank of Russia.
    10. Pinar Yesin, 2013. "Foreign Currency Loans and Systemic Risk in Europe," Working Papers 13.06, Swiss National Bank, Study Center Gerzensee.
    11. Andrea Mazzocchetti & Eliana Lauretta & Marco Raberto & Andrea Teglio & Silvano Cincotti, 2020. "Systemic financial risk indicators and securitised assets: an agent-based framework," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 9-47, January.
    12. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," Working Paper Series in Economics 123, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    13. Peter Claeys & Borek Vašícek, 2013. "“How systemic is Spain for Europe?”," IREA Working Papers 201301, University of Barcelona, Research Institute of Applied Economics, revised Feb 2013.
    14. Detken, Carsten & Weeken, Olaf & Alessi, Lucia & Bonfim, Diana & Boucinha, Miguel & Castro, Christian & Frontczak, Sebastian & Giordana, Gaston & Giese, Julia & Wildmann, Nadya & Kakes, Jan & Klaus, B, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 5, European Systemic Risk Board.
    15. Claudio Morana, 2013. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure," Working Papers 233, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    16. R. Pianeti & R. Giacometti, 2015. "Estimating the probability of multiple EU sovereign defaults using CDS and bond data," Quantitative Finance, Taylor & Francis Journals, vol. 15(1), pages 61-78, January.
    17. Antonio Di Cesare & Anna Rogantini Picco, 2018. "A Survey of Systemic Risk Indicators," Questioni di Economia e Finanza (Occasional Papers) 458, Bank of Italy, Economic Research and International Relations Area.
    18. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    19. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. O. de Bandt & J.-C. Héam & C. Labonne & S. Tavolaro, 2013. "Measuring Systemic Risk in a Post-Crisis World," Débats Economiques et financiers 6, Banque de France.
    21. Xingxing Ye & Raphaël Douady, 2019. "Risk and Financial Management Article Systemic Risk Indicators Based on Nonlinear PolyModel," Post-Print hal-02488592, HAL.
    22. Eleonora Iachini & Stefano Nobili, 2014. "An indicator of systemic liquidity risk in the Italian financial markets," Questioni di Economia e Finanza (Occasional Papers) 217, Bank of Italy, Economic Research and International Relations Area.
    23. Fiordelisi, Franco & Marqués-Ibañez, David, 2013. "Is bank default risk systematic?," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2000-2010.
    24. Matkovskyy, Roman, 2012. "The Index of the Financial Safety (IFS) of South Africa and Bayesian Estimates for IFS Vector-Autoregressive Model," MPRA Paper 42173, University Library of Munich, Germany.
    25. Rodríguez-Moreno, María & Peña, Juan Ignacio, 2010. "Systemic risk measures: the simpler the better," DEE - Working Papers. Business Economics. WB 9291, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    26. Mr. Ivailo Arsov & Mr. Elie Canetti & Ms. Laura E. Kodres & Ms. Srobona Mitra, 2013. "Near-Coincident Indicators of Systemic Stress," IMF Working Papers 2013/115, International Monetary Fund.
    27. Weiß, Gregor N.F. & Mühlnickel, Janina, 2014. "Why do some insurers become systemically relevant?," Journal of Financial Stability, Elsevier, vol. 13(C), pages 95-117.
    28. Grilli, Ruggero & Giri, Federico & Gallegati, Mauro, 2020. "Collateral rehypothecation, safe asset scarcity, and unconventional monetary policy," Economic Modelling, Elsevier, vol. 91(C), pages 633-645.

  48. Pawel Janus & Siem Jan Koopman & André Lucas, 2011. "Long Memory Dynamics for Multivariate Dependence under Heavy Tails," Tinbergen Institute Discussion Papers 11-175/2/DSF28, Tinbergen Institute.

    Cited by:

    1. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    2. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    3. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    4. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    5. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    6. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, Department of Economics and Business Economics, Aarhus University.
    7. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    8. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    9. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    10. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    11. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2024. "Anthropogenic effects of climate change: Further evidence from a fractionally integrated ice-age model," UC3M Working papers. Economics 44712, Universidad Carlos III de Madrid. Departamento de Economía.
    12. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    13. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    14. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    15. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    16. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.
    17. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    18. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    19. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    20. Christos Agiakloglou & Anil Bera & Emmanouil Deligiannakis, 2022. "Evaluating measures of dependence for linearly generated nonlinear time series along with spurious correlation," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 535-552, July.
    21. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    22. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    23. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    24. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    25. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    26. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    27. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
    28. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.

  49. Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.

    Cited by:

    1. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    2. Bao, Te & Diks, Cees & Li, Hao, 2018. "A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction," Economic Modelling, Elsevier, vol. 68(C), pages 611-621.
    3. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    4. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    5. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    6. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    7. Jouchi Nakajima, 2017. "Bayesian analysis of multivariate stochastic volatility with skew return distribution," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 546-562, May.
    8. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    9. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    10. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.

  50. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.

    Cited by:

    1. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    2. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    3. Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
    4. Lange, Rutger-Jan, 2024. "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, vol. 238(2).
    5. István Barra & Lennart Hoogerheide & Siem Jan Koopman & André Lucas, 2017. "Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 1003-1026, August.
    6. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    7. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    8. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman van Dijk, 2022. "A Flexible Predictive Density Combination Model for Large Financial Data Sets in Regular and Crisis Periods," Tinbergen Institute Discussion Papers 22-013/III, Tinbergen Institute.
    9. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2015. "Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model," Tinbergen Institute Discussion Papers 15-076/IV/DSF94, Tinbergen Institute.
    10. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira da Veiga, María Helena, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    12. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
    13. Jean-François Richard, 2015. "Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables," Working Paper 5778, Department of Economics, University of Pittsburgh.
    14. Blanc-Blocquel, Augusto & Ortiz-Gracia, Luis & Oviedo, Rodolfo, 2024. "Efficient likelihood estimation of Heston model for novel climate-related financial contracts valuation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 225(C), pages 430-445.
    15. Hong Li & Yang Lu, 2018. "A Bayesian non-parametric model for small population mortality," Post-Print hal-02419000, HAL.
    16. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
    17. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    18. Siem Jan Koopman & Marcel Scharth, 2011. "The Analysis of Stochastic Volatility in the Presence of Daily Realised Measures," Tinbergen Institute Discussion Papers 11-132/4, Tinbergen Institute.
    19. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.
    20. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
    21. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
    22. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    23. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
    24. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.

  51. Drew Creal & Siem Jan Koopman & André Lucas, 2010. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Tinbergen Institute Discussion Papers 10-032/2, Tinbergen Institute.

    Cited by:

    1. Guo, Dong & Zhou, Peng, 2021. "Green bonds as hedging assets before and after COVID: A comparative study between the US and China," Energy Economics, Elsevier, vol. 104(C).
    2. Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2025. "Score-driven time-varying parameter models with splinebased densities," Tinbergen Institute Discussion Papers 25-011/III, Tinbergen Institute.
    3. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," JRFM, MDPI, vol. 12(2), pages 1-12, April.
    5. Kawakatsu Hiroyuki, 2021. "Simple Multivariate Conditional Covariance Dynamics Using Hyperbolically Weighted Moving Averages," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 33-52, January.
    6. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    7. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    8. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    9. Peter Reinhard Hansen & Chen Tong, 2024. "Convolution-t Distributions," Papers 2404.00864, arXiv.org.
    10. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    11. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    12. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    13. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    14. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    15. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    16. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
    17. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    18. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    19. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    20. Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
    21. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    22. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    23. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    24. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    25. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    26. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
    27. Böhm, Hannes & Schaumburg, Julia & Tonzer, Lena, 2020. "Financial linkages and sectoral business cycle synchronisation: Evidence from Europe," IWH Discussion Papers 2/2020, Halle Institute for Economic Research (IWH).
    28. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    29. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    30. Luca Vincenzo Ballestra & Enzo D’Innocenzo & Andrea Guizzardi, 2024. "Score-Driven Modeling with Jumps: An Application to S&P500 Returns and Options," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 375-406.
    31. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    32. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    33. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    34. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    35. Escribano, Alvaro & Sucarrat, Genaro, 2018. "Equation-by-equation estimation of multivariate periodic electricity price volatility," Energy Economics, Elsevier, vol. 74(C), pages 287-298.
    36. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    37. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    38. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    39. Lin Zhao & Sweder van Wijnbergen, 2015. "Asset Pricing in Incomplete Markets: Valuing Gas Storage Capacity," Tinbergen Institute Discussion Papers 15-104/VI/DSF95, Tinbergen Institute.
    40. Michele Caivano & Andrew Harvey, 2014. "Two EGARCH models and one fat tail," Temi di discussione (Economic working papers) 954, Bank of Italy, Economic Research and International Relations Area.
    41. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    42. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    43. André Lucas & Julia Schaumburg & Bernd Schwaab, 2019. "Bank Business Models at Zero Interest Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 542-555, July.
    44. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    45. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    46. Chong, Terence Tai Leung & Ding, Yue & Pang, Tianxiao, 2017. "Extreme Risk Value and Dependence Structure of the China Securities Index 300," MPRA Paper 80556, University Library of Munich, Germany.
    47. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    48. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models," Tinbergen Institute Discussion Papers 15-083/III, Tinbergen Institute.
    49. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    50. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    51. Drew D. Creal & Jing Cynthia Wu, 2014. "Estimation of Affine Term Structure Models with Spanned or Unspanned Stochastic Volatility," NBER Working Papers 20115, National Bureau of Economic Research, Inc.
    52. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
    53. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    54. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    55. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    56. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, Enero-Abr.
    57. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    58. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    59. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    60. Andrew Harvey & Alessandra Luati, 2014. "Filtering With Heavy Tails," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1112-1122, September.
    61. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    62. Mohamed El Ghourabi & Asma Nani & Imed Gammoudi, 2021. "A value‐at‐risk computation based on heavy‐tailed distribution for dynamic conditional score models," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2790-2799, April.
    63. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    64. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    65. Bahcivan, Hulusi & Karahan, Cenk C., 2022. "High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange," International Review of Financial Analysis, Elsevier, vol. 80(C).
    66. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    67. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    68. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.
    69. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    70. Lin Zhao & Sweder van Wijnbergen, 2014. "Decision Making in Incomplete Markets with Ambiguity -- A Case Study of a Gas Field Acquisition," Tinbergen Institute Discussion Papers 14-149/VI, Tinbergen Institute.
    71. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    72. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    73. Hetland, Simon & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2023. "Dynamic conditional eigenvalue GARCH," Journal of Econometrics, Elsevier, vol. 237(2).
    74. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    75. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.
    76. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    77. Chen Tong & Peter Reinhard Hansen, 2025. "Dynamic Factor Correlation Model," Papers 2503.01080, arXiv.org.
    78. Hasanov, Akram Shavkatovich & Poon, Wai Ching & Al-Freedi, Ajab & Heng, Zin Yau, 2018. "Forecasting volatility in the biofuel feedstock markets in the presence of structural breaks: A comparison of alternative distribution functions," Energy Economics, Elsevier, vol. 70(C), pages 307-333.
    79. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    80. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    81. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    82. Hafner, Christian M. & Herwartz, Helmut, 2022. "Dynamic score driven independent component analysis," LIDAM Reprints ISBA 2022010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    83. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    84. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    85. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    86. Fernanda Maria Müller & Fábio M Bayer, 2017. "Improved two-component tests in Beta-Skew-t-EGARCH models," Economics Bulletin, AccessEcon, vol. 37(4), pages 2364-2373.
    87. Zhang, Yongli & Rolling, Craig & Yang, Yuhong, 2021. "Estimating and forecasting dynamic correlation matrices: A nonlinear common factor approach," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    88. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    89. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
    90. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    91. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    92. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Bounds for Time-Varying Parameters of Observation Driven Models," Tinbergen Institute Discussion Papers 15-027/III, Tinbergen Institute, revised 07 Sep 2015.
    93. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    94. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    95. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    96. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    97. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    98. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    99. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    100. Kris Boudt & Jon Danielsson & Siem Jan Koopman & Andre Lucas, 2012. "Regime switches in the volatility and correlation of financial institutions," Working Paper Research 227, National Bank of Belgium.
    101. Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
    102. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    103. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    104. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
    105. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    106. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).
    107. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    108. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    109. Ruey S. Tsay & Mohsen Pourahmadi, 2017. "Modelling structured correlation matrices," Biometrika, Biometrika Trust, vol. 104(1), pages 237-242.
    110. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    111. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    112. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    113. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    114. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    115. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    116. Galin Todorov & Prasad Bidarkota, 2014. "Time-varying financial spillovers from the US to frontier markets," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 7(2), pages 246-283, September.
    117. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    118. Karim M Abadir, 2023. "Explicit minimal representation of variance matrices, and its implication for dynamic volatility models," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 88-104.
    119. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    120. Giuseppe Buccheri & Fulvio Corsi & Emilija Dzuverovic, 2024. "From rotational to scalar invariance: Enhancing identifiability in score-driven factor models," Papers 2412.01367, arXiv.org.
    121. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    122. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    123. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
    124. Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
    125. Lin, Min-Bin & Wang, Bingling & Bocart, Fabian Y.R.P. & Hafner, Christian M. & Härdle, Wolfgang K., 2022. "DAI Digital Art Index : a robust price index for heterogeneous digital assets," LIDAM Discussion Papers ISBA 2022036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    126. Sergio Contreras-Espinoza & Francisco Novoa-Muñoz & Szabolcs Blazsek & Pedro Vidal & Christian Caamaño-Carrillo, 2022. "COVID-19 Active Case Forecasts in Latin American Countries Using Score-Driven Models," Mathematics, MDPI, vol. 11(1), pages 1-17, December.
    127. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    128. Francisco (F.) Blasques & Marc Nientker, 2017. "A Stochastic Recurrence Equation Approach to Stationarity and phi-Mixing of a Class of Nonlinear ARCH Models," Tinbergen Institute Discussion Papers 17-072/III, Tinbergen Institute.
    129. Sonia Benito Muela & Carmen López-Martín & Mª Ángeles Navarro, 2017. "The Role of the Skewed Distributions in the Framework of Extreme Value Theory (EVT)," International Business Research, Canadian Center of Science and Education, vol. 10(11), pages 88-102, November.
    130. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
    131. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    132. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    133. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    134. Riccardo Lucchetti & Luca Pedini, 2025. "Correction to: The Spherical Parametrisation for Correlation Matrices and its Computational Advantages," Computational Economics, Springer;Society for Computational Economics, vol. 65(4), pages 2449-2450, April.
    135. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
    136. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    137. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    138. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    139. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  52. Roman Kraeussl & Andre Lucas & Arjen Siegmann, 2010. "Risk Aversion under Preference Uncertainty," Tinbergen Institute Discussion Papers 10-117/2/DSF 4, Tinbergen Institute.

    Cited by:

    1. Sascha Desmettre & Mogens Steffensen, 2023. "Equilibrium investment with random risk aversion," Mathematical Finance, Wiley Blackwell, vol. 33(3), pages 946-975, July.

  53. Bernd Schwaab & Andre Lucas & Siem Jan Koopman, 2010. "Systemic Risk Diagnostics," Tinbergen Institute Discussion Papers 10-104/2/DSF 2, Tinbergen Institute, revised 29 Nov 2010.

    Cited by:

    1. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    2. Andrea Mazzocchetti & Eliana Lauretta & Marco Raberto & Andrea Teglio & Silvano Cincotti, 2020. "Systemic financial risk indicators and securitised assets: an agent-based framework," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 9-47, January.
    3. Xisong Jin & Francisco Nadal De Simone, 2012. "An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal," BCL working papers 75, Central Bank of Luxembourg.
    4. Claudio Morana, 2013. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure," Working Papers 233, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    5. Dungey, Mardi & Luciani, Matteo & Veredas, David, 2012. "Ranking systemically important financial institutions," Working Papers 15473, University of Tasmania, Tasmanian School of Business and Economics, revised 21 Nov 2012.
    6. Ini S Udom & Sani Ibrahim Doguwa, 2015. "Generating a composite index to support monetary and financial stability analysis in Nigeria," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Indicators to support monetary and financial stability analysis: data sources and statistical methodologies, volume 39, Bank for International Settlements.
    7. Xisong Jin & Francisco Nadal De Simone, 2017. "Systemic Financial Sector and Sovereign Risks," BCL working papers 109, Central Bank of Luxembourg.
    8. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Kauko, Karlo, 2014. "How to foresee banking crises? A survey of the empirical literature," Economic Systems, Elsevier, vol. 38(3), pages 289-308.

  54. Lee, Carmen & Kräussl, Roman & Lucas, André & Paas, Leo, 2010. "Why do investors sell losers? How adaptation to losses affects future capitulation decisions," CFS Working Paper Series 2010/23, Center for Financial Studies (CFS).

    Cited by:

    1. Lee, K.M.C. & Kraeussl, R.G.W. & Paas, L.J., 2010. "Personality and investment: Personality differences affect investors' adaptation to losses," Serie Research Memoranda 0007, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

  55. Mahmoud Botshekan & Roman Kraeussl & Andre Lucas, 2010. "Cash Flow and Discount Rate Risk in Up and Down Markets: What is actually priced?," Tinbergen Institute Discussion Papers 10-116/2/DSF 3, Tinbergen Institute.

    Cited by:

    1. Maio, Paulo, 2013. "Return decomposition and the Intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4958-4972.
    2. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    3. Wu, Ming & Ohk, Kiyool & Ko, Kwangsoo, 2019. "Are cash-flow betas really bad? Evidence from the Greater Chinese stock markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 58-68.
    4. Kryzanowski, Lawrence & Mohsni, Sana, 2015. "Earnings forecasts and idiosyncratic volatilities," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 107-123.
    5. Narayan, Paresh Kumar & Westerlund, Joakim, 2015. "Does cash flow predict returns?," Working Papers fe_2015_03, Deakin University, Department of Economics.
    6. Wu, Ming & Ohk, Kiyool & Ko, Kwangsoo, 2021. "Does cash-flow news play a better role than discount-rate news? Evidence from global regional stock markets," Journal of International Money and Finance, Elsevier, vol. 110(C).
    7. Maio, Paulo & Philip, Dennis, 2015. "Macro variables and the components of stock returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 287-308.
    8. Ilan Cooper & Paulo Maio, 2019. "Asset Growth, Profitability, and Investment Opportunities," Management Science, INFORMS, vol. 65(9), pages 3988-4010, September.
    9. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    10. Atanasov, Victoria & Nitschka, Thomas, 2014. "Currency excess returns and global downside market risk," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 268-285.
    11. Olaf Stotz, 2021. "Expected and realized returns on stocks with high- and low-ESG exposure," Journal of Asset Management, Palgrave Macmillan, vol. 22(2), pages 133-150, March.
    12. Piccotti, Louis R., 2017. "Financial contagion risk and the stochastic discount factor," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 230-248.
    13. Ehab Yamani & David Rakowski, 2018. "Cash Flow and Discount Rate Risk in the Investment Effect: A Downside Risk Approach," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 1-40, September.
    14. Kausar, Rabia & Qayyum, Abdul, 2018. "How Cash Flow News and Discount Rate News Impact the Unexpected Stock Returns of Energy Firms of Pakistan," MPRA Paper 91165, University Library of Munich, Germany.

  56. Siem Jan Koopman & Andre Lucas & Bernd Schwaab, 2010. "Macro, Industry and Frailty Effects in Defaults: The 2008 Credit Crisis in Perspective," Tinbergen Institute Discussion Papers 10-004/2, Tinbergen Institute, revised 24 Aug 2010.

    Cited by:

    1. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    2. Xisong Jin & Francisco Nadal De Simone, 2012. "An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal," BCL working papers 75, Central Bank of Luxembourg.
    3. Xisong Jin & Francisco Nadal De Simone, 2017. "Systemic Financial Sector and Sovereign Risks," BCL working papers 109, Central Bank of Luxembourg.
    4. Xisong Jin & Francisco Nadal De Simone, 2016. "Tracking Changes in the Intensity of Financial Sector's Systemic Risk," BCL working papers 102, Central Bank of Luxembourg.

  57. Drew Creal & Siem Jan Koopman & Andre Lucas, 2009. "A General Framework for Observation Driven Time-Varying Parameter Models," Global COE Hi-Stat Discussion Paper Series gd08-038, Institute of Economic Research, Hitotsubashi University.

    Cited by:

    1. Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
    3. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    4. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    5. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    6. Delle Monache, Davide & Petrella, Ivan & Venditti, Fabrizio, 2020. "Price dividend ratio and long-run stock returns: a score driven state space model," Temi di discussione (Economic working papers) 1296, Bank of Italy, Economic Research and International Relations Area.
    7. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    8. Francq, Christian & Zakoian, Jean-Michel, 2021. "Local asymptotic normality of general conditionally heteroskedastic and score-driven time-series models," MPRA Paper 106542, University Library of Munich, Germany.
    9. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
    10. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    11. Blazsek, Szabolcs & Kong, Dejun & Shadoff, Samantha R., 2025. "Within-regime volatility dynamics for observable- and Markov-switching score-driven models," Finance Research Letters, Elsevier, vol. 73(C).
    12. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    13. Hendrych, R. & Cipra, T., 2016. "On conditional covariance modelling: An approach using state space models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 304-317.
    14. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, Enero-Abr.
    15. Naeem, Muhammad Abubakr & Bouri, Elie & Costa, Mabel D. & Naifar, Nader & Shahzad, Syed Jawad Hussain, 2021. "Energy markets and green bonds: A tail dependence analysis with time-varying optimal copulas and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
    16. Bahcivan, Hulusi & Karahan, Cenk C., 2022. "High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange," International Review of Financial Analysis, Elsevier, vol. 80(C).
    17. Shinya Fukui, 2020. "Business Cycle Spatial Synchronization: Measuring a Synchronization Parameter," Discussion Papers 2009, Graduate School of Economics, Kobe University.
    18. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
    19. Julia Kielmann & Hans Manner & Aleksey Min, 2021. "Stock Market Returns and Oil Price Shocks: A CoVaR Analysis based on Dynamic Vine Copula Models," Graz Economics Papers 2021-01, University of Graz, Department of Economics.
    20. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    21. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    22. Karim, Sitara & Lucey, Brian M. & Naeem, Muhammad Abubakr & Vigne, Samuel A., 2023. "The dark side of Bitcoin: Do Emerging Asian Islamic markets help subdue the ethical risk?," Emerging Markets Review, Elsevier, vol. 54(C).
    23. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    24. Syed Jawad Hussain Shahzad & Elie Bouri & Mobeen Ur Rehman & Muhammad Abubakr Naeem & Tareq Saeed, 2022. "Oil price risk exposure of BRIC stock markets and hedging effectiveness," Annals of Operations Research, Springer, vol. 313(1), pages 145-170, June.
    25. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    26. Tsyplakov, Alexander, 2015. "Quasifiltering for time-series modeling," MPRA Paper 66453, University Library of Munich, Germany.
    27. Szabolcs Blazsek & Alvaro Escribano, 2022. "Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models," Econometrics, MDPI, vol. 10(1), pages 1-29, February.
    28. Zhang, Yi & Cheng, Chuntian & Cao, Rui & Li, Gang & Shen, Jianjian & Wu, Xinyu, 2021. "Multivariate probabilistic forecasting and its performance’s impacts on long-term dispatch of hydro-wind hybrid systems," Applied Energy, Elsevier, vol. 283(C).
    29. Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
    30. Hans Manner & Olga Reznikova, 2012. "A Survey on Time-Varying Copulas: Specification, Simulations, and Application," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 654-687, November.
    31. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    32. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).

  58. Sander J.J. Konijn & Roman Kraeussl & Andre Lucas, 2009. "Blockholder Dispersion and Firm Value," Tinbergen Institute Discussion Papers 09-113/2, Tinbergen Institute, revised 03 Jan 2011.

    Cited by:

    1. Carlos Pombo & Cristian Pinto-Gutierrez & Mauricio Jara-BetÔøΩn, 2022. "Multiple large shareholder coalitions, institutional ownership and investment decisions: Evidence from cross-border deals in Latin America," Documentos CEDE 20333, Universidad de los Andes, Facultad de Economía, CEDE.
    2. Mohd Mohid Rahmat & Kamran Ahmed & Gerald J. Lobo, 2020. "Related Party Transactions, Value Relevance and Informativeness of Earnings: Evidence from Four Economies in East Asia," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 23(01), pages 1-42, March.
    3. Yung, Kenneth & Jian, Yi, 2017. "Effects of the shareholder base on firm behavior and firm value in China," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 370-385.
    4. Adeel Mustafa & Abubakr Saeed & Muhammad Awais & Shahab Aziz, 2020. "Board-Gender Diversity, Family Ownership, and Dividend Announcement: Evidence from Asian Emerging Economies," JRFM, MDPI, vol. 13(4), pages 1-20, March.
    5. Lu Zhang & Yuan George Shan & Millicent Chang, 2021. "Can CSR Disclosure Protect Firm Reputation During Financial Restatements?," Journal of Business Ethics, Springer, vol. 173(1), pages 157-184, September.
    6. Fang-Yi LO & Shih-Kuan CHIU & Pei-Wen SHIH, 2016. "Ownership Concentration, Location, and Internalization Advantage in Financial Performance," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 82-93, September.
    7. José María Díez-Esteban & Jorge Bento Farinha & Conrado Diego García-Gómez, 2019. "How does national culture affect corporate risk-taking?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 49-68, March.
    8. Silvia Rossetto & Nassima Selmane & Raffaele Staglianò, 2023. "Ownership concentration and firm risk: The moderating role of mid‐sized blockholders," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 50(1-2), pages 377-410, January.
    9. Annalisa Russino, 2023. "Multiple Blockholders and Firm Value: A Simulation Analysis," IJFS, MDPI, vol. 11(2), pages 1-15, March.
    10. Pombo, Carlos & Taborda, Rodrigo, 2017. "Stock liquidity and second blockholder as drivers of corporate value: Evidence from Latin America," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 214-234.
    11. Muhammad Yar Khan & Anam Javeed & Ly Kim Cuong & Ha Pham, 2020. "Corporate Governance and Cost of Capital: Evidence from Emerging Market," Risks, MDPI, vol. 8(4), pages 1-29, October.
    12. Mário Santos & António Moreira & Elisabete Vieira, 2014. "Ownership concentration, contestability, family firms, and capital structure," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 18(4), pages 1063-1107, November.
    13. Kandil Magda Elsayed & Markovski Minko, 2017. "The Impact of Ownership on Corporate Performance: The Case of the UAE," Review of Middle East Economics and Finance, De Gruyter, vol. 13(3), pages 1-25, December.
    14. Qaiser Rafique Yasser & Abdullah Al Mamun, 2017. "The Impact of Ownership Concentration on Firm Performance: Evidence from an Emerging Market," Emerging Economy Studies, International Management Institute, vol. 3(1), pages 34-53, May.
    15. Bajo, Emanuele & Croci, Ettore & Marinelli, Nicoletta, 2020. "Institutional investor networks and firm value," Journal of Business Research, Elsevier, vol. 112(C), pages 65-80.
    16. Merkel, Matthias F., 2018. "Foreign exchange derivative use and firm value: Evidence from German non-financial firms," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe B-33-18, University of Passau, Faculty of Business and Economics.
    17. Amin, Qazi Awais & Cumming, Douglas, 2021. "Blockholders and real earnings management-the emerging markets context," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    18. Polovina, Nereida & Peasnell, Ken, 2020. "Do minority acquisitions transfer better corporate governance practices? An analysis of UK's cross-border minority investments," The British Accounting Review, Elsevier, vol. 52(3).
    19. Amir Gholami & John Sands & Habib Ur Rahman, 2022. "Environmental, Social and Governance Disclosure and Value Generation: Is the Financial Industry Different?," Sustainability, MDPI, vol. 14(5), pages 1-17, February.
    20. Lionel Almeida, 2015. "Who are the controlling shareholders? Degree and seniority of control, and CEO pay monitoring," EconomiX Working Papers 2015-27, University of Paris Nanterre, EconomiX.
    21. Trinh, Quoc Dat & Haddad, Christian & Salameh, Elie, 2023. "Financial institutional blockholders and earnings quality: Do blockholders contestability and countries' institutions matter?," International Review of Financial Analysis, Elsevier, vol. 87(C).
    22. Ravid, S. Abraham & Sekerci, Naciye, 2020. "Large investors’ portfolio composition and firms value," Journal of Corporate Finance, Elsevier, vol. 61(C).
    23. Jordi Paniagua & Rafael Rivelles & Juan Sapena, 2019. "Social Determinants of Success: Social Media, Corporate Governance and Revenue," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    24. Ernest Gyapong & Ammad Ahmed & Collins G Ntim & Muhammad Nadeem, 2021. "Board gender diversity and dividend policy in Australian listed firms: the effect of ownership concentration," Asia Pacific Journal of Management, Springer, vol. 38(2), pages 603-643, June.
    25. Alex Edmans, 2013. "Blockholders and Corporate Governance," NBER Working Papers 19573, National Bureau of Economic Research, Inc.
    26. Paniagua, Jordi & Rivelles, Rafael & Sapena, Juan, 2018. "Corporate governance and financial performance: The role of ownership and board structure," Journal of Business Research, Elsevier, vol. 89(C), pages 229-234.
    27. Zhang, Lipai & Li, Biao, 2022. "Mutual supervision or conspiracy? The incentive effect of multiple large shareholders on audit quality requirements," International Review of Financial Analysis, Elsevier, vol. 83(C).
    28. Mabel D Costa & Ahsan Habib, 2023. "Cost stickiness and firm value," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 34(2), pages 235-273, June.
    29. Devra L. Golbe & Ingmar Nyman, 2010. "How do share repurchases affect ownership concentration?," Economics Working Paper Archive at Hunter College 430, Hunter College Department of Economics, revised 2012.
    30. Bian, Wenlong & Ren, Yan & Zhang, Hao, 2022. "Do multiple large shareholders matter in financial firms? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    31. García-Sánchez, Isabel-María & Aibar-Guzmán, Cristina & Aibar-Guzmán, Beatriz, 2020. "The effect of institutional ownership and ownership dispersion on eco-innovation," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    32. Tsai, Han-Fang & Lin, Tsui-Jung & Hung, Jung-Hua, 2015. "The effects of the split share structure reform on Chinese listed firms’ leverage decisions," The Quarterly Review of Economics and Finance, Elsevier, vol. 57(C), pages 86-100.
    33. Andrey B. Ankudinov & Bela S. Bataeva, 2021. "Capital structure and market capitalization: Empirical analysis of Russian public companies," Upravlenets, Ural State University of Economics, vol. 12(2), pages 35-42, April.
    34. Berkman, Henk & Jona, Jonathan & Soderstrom, Naomi, 2024. "Firm-specific climate risk and market valuation," Accounting, Organizations and Society, Elsevier, vol. 112(C).
    35. Edmans, Alex & Holderness, Clifford, 2016. "Blockholders: A Survey of Theory and Evidence," CEPR Discussion Papers 11442, C.E.P.R. Discussion Papers.
    36. Lela Nurlaela Wati & Hj. Ina Primiana & Kashan Pirzada & Rachmat Sudarsono, 2019. "Political connection, blockholder ownership and performance," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(1), pages 52-68, September.
    37. Phuoc Vu Ha & Michael Frömmel, 2023. "Corruption, business environment, and firm growth in Vietnam," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2512-2529, July.
    38. Pattarin Adithipyangkul & T. Y. Leung, 2018. "Incentive pay for non-executive directors: The direct and interaction effects on firm performance," Asia Pacific Journal of Management, Springer, vol. 35(4), pages 943-964, December.
    39. Imani Mokhtar* & Sharifah Raihan Syed Mohd Zain & Jarita Duasa & Azhar Mohamad, 2018. "Blockholders and Firm Performance: A Malaysian Evidence," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 885-893:5.
    40. Jae Eun Shin & Seung-Weon Yoo & Gun Lee, 2020. "The Effects of Blockholder Dispersion on the Informativeness of Earnings: Evidence from Korea," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    41. Crisóstomo, Vicente Lima & Brandão, Isac de Freitas & López-Iturriaga, Félix Javier, 2020. "Large shareholders’ power and the quality of corporate governance: An analysis of Brazilian firms," Research in International Business and Finance, Elsevier, vol. 51(C).
    42. Zhu, JianJun (John) & Tse, Caleb H. & Li, Xu, 2019. "Unfolding China’s state-owned corporate empires and mitigating agency hazards: Effects of foreign investments and innovativeness," Journal of World Business, Elsevier, vol. 54(3), pages 191-212.
    43. Cheng, Minying & Lin, Bingxuan & Wei, Minghai, 2013. "How does the relationship between multiple large shareholders affect corporate valuations? Evidence from China," Journal of Economics and Business, Elsevier, vol. 70(C), pages 43-70.
    44. Maria Camila De-La-Hoz & Carlos Pombo, 2015. "Institutional Investors and Firm Valuation: Evidence from Latin America," Documentos CEDE 12849, Universidad de los Andes, Facultad de Economía, CEDE.
    45. Mangena, Musa & Priego, Alba Maria & Manzaneque, Montserrat, 2020. "Bank power, block ownership, boards and financial distress likelihood: An investigation of Spanish listed firms," Journal of Corporate Finance, Elsevier, vol. 64(C).
    46. Roberto √Ålvarez & Mauricio Jara-BertÔøΩn & Carlos Pombo, 2016. "Do institutional investors unbind firm financial constraints? Evidence from emerging markets," Documentos CEDE 15114, Universidad de los Andes, Facultad de Economía, CEDE.
    47. Carosi, Andrea, 2016. "Do local causations matter? The effect of firm location on the relations of ROE, R&D, and firm SIZE with MARKET-TO-BOOK," Journal of Corporate Finance, Elsevier, vol. 41(C), pages 388-409.
    48. Yasuharu Aoki, 2014. "How Does the Largest Shareholder Affect Dividends?," International Review of Finance, International Review of Finance Ltd., vol. 14(4), pages 613-645, December.
    49. Gilson, Ronald J. & Schwartz, Alan, 2015. "Corporate control and credible commitment," International Review of Law and Economics, Elsevier, vol. 43(C), pages 119-130.
    50. Jiang, Fuxiu & Kim, Kenneth A. & Nofsinger, John R. & Zhu, Bing, 2017. "A pecking order of shareholder structure," Journal of Corporate Finance, Elsevier, vol. 44(C), pages 1-14.
    51. Amir Gholami & Peter A. Murray & John Sands, 2022. "Environmental, Social, Governance & Financial Performance Disclosure for Large Firms: Is This Different for SME Firms?," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    52. De-la-Hoz, Maria Camila & Pombo, Carlos, 2016. "Institutional investor heterogeneity and firm valuation: Evidence from Latin America," Emerging Markets Review, Elsevier, vol. 26(C), pages 197-221.
    53. Rossi, Fabrizio & Barth, James R. & Cebula, Richard J., 2018. "Do shareholder coalitions affect agency costs? Evidence from Italian-listed companies," Research in International Business and Finance, Elsevier, vol. 46(C), pages 181-200.
    54. Khaleed Omair Alotaibi & Khaled Hussainey, 2016. "Determinants of CSR disclosure quantity and quality: Evidence from non-financial listed firms in Saudi Arabia," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 13(4), pages 364-393, November.
    55. Benamraoui, Abdelhafid & Jory, Surendranath Rakesh & Mazouz, Khelifa & Shah, Neeta & Gough, Orla, 2019. "The effect of block ownership on future firm value and performance," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    56. Alex Edmans & Gustavo Manso, 2011. "Governance Through Trading and Intervention: A Theory of Multiple Blockholders," The Review of Financial Studies, Society for Financial Studies, vol. 24(7), pages 2395-2428.
    57. Marquardt, Blair B. & Sanchez, Juan Manuel, 2022. "Blockholder board representation and debt contracting," Journal of Banking & Finance, Elsevier, vol. 142(C).
    58. Muhammad Sadiq Shahid & Razaz Houssien Felimban & Khawar Naheed & Usman Aleem & Shaiza Nawaz, 2018. "Ownership Structures, Investors Confidence And Financial Decisions In Family Firms: Evidence From Gcc Markets," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 14(1), pages 52-68.
    59. Basu, Nilanjan & Paeglis, Imants & Toffanin, Melissa, 2017. "Reading between the blocks," Journal of Corporate Finance, Elsevier, vol. 45(C), pages 294-317.
    60. Jia, Ning & Wang, Dan, 2017. "Skin in the game: General partner capital commitment, investment behavior and venture capital fund performance," Journal of Corporate Finance, Elsevier, vol. 47(C), pages 110-130.

  59. Oleg Sheremet & André Lucas, 2008. "Global Loss Diversification in the Insurance Sector," Tinbergen Institute Discussion Papers 08-086/2, Tinbergen Institute.

    Cited by:

    1. Manuel Ordóñez Cabrera & Andrew Rosalsky & Andrei Volodin, 2012. "Some theorems on conditional mean convergence and conditional almost sure convergence for randomly weighted sums of dependent random variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 369-385, June.
    2. Pai, Jeffrey & Li, Yunxian & Yang, Aijun & Li, Chenxu, 2022. "Earthquake parametric insurance with Bayesian spatial quantile regression," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 1-12.

  60. Carmen Lee & Roman Kraeussl & André Lucas & Leonard J. Paas, 2008. "A Dynamic Model of Investor Decision-Making: How Adaptation to Losses affects Future Selling Decisions," Tinbergen Institute Discussion Papers 08-112/2, Tinbergen Institute, revised 02 Sep 2013.

    Cited by:

    1. Fabio L. Mattos & Jamie Zinn, 2016. "Formation and adaptation of reference prices in grain marketing: an experimental study," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 621-632, November.

  61. Siem Jan Koopman & André Lucas & Bernd Schwaab, 2008. "Forecasting Cross-Sections of Frailty-Correlated Default," Tinbergen Institute Discussion Papers 08-029/4, Tinbergen Institute.

    Cited by:

    1. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    2. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    3. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    4. Bernd Schwaab & Andre Lucas & Siem Jan Koopman, 2010. "Systemic Risk Diagnostics," Tinbergen Institute Discussion Papers 10-104/2/DSF 2, Tinbergen Institute, revised 29 Nov 2010.

  62. Konrad Banachewicz & André Lucas, 2007. "Quantile Forecasting for Credit Risk Management using possibly Mis-specified Hidden Markov Models," Tinbergen Institute Discussion Papers 07-046/2, Tinbergen Institute.

    Cited by:

    1. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2015. "Forecasting ICT development through quantile confidence intervals," Journal of Business Research, Elsevier, vol. 68(11), pages 2295-2298.
    2. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2014. "A new quantile regression forecasting model," Journal of Business Research, Elsevier, vol. 67(5), pages 779-784.

  63. Siem Jan Koopman & André Lucas & Marius Ooms & Kees van Montfort & Victor van der Geest, 2007. "Estimating Systematic Continuous-time Trends in Recidivism using a Non-Gaussian Panel Data Model," Tinbergen Institute Discussion Papers 07-027/4, Tinbergen Institute.

    Cited by:

    1. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    2. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    3. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    4. Suncica Vujic & Jacques Commandeur & Siem Jan Koopman, 2012. "Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia," Tinbergen Institute Discussion Papers 12-007/4, Tinbergen Institute.

  64. Andre Monteiro & Georgi V. Smirnov & Andre Lucas, 2006. "Nonparametric Estimation for Non-Homogeneous Semi-Markov Processes: An Application to Credit Risk," Tinbergen Institute Discussion Papers 06-024/2, Tinbergen Institute, revised 27 Mar 2006.

    Cited by:

    1. Sabine Zinn, 2014. "The MicSim Package of R: An Entry-Level Toolkit for Continuous-Time Microsimulation," International Journal of Microsimulation, International Microsimulation Association, vol. 7(3), pages 3-32.
    2. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    3. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Qi Cao & Erik Buskens & Talitha Feenstra & Tiny Jaarsma & Hans Hillege & Douwe Postmus, 2016. "Continuous-Time Semi-Markov Models in Health Economic Decision Making," Medical Decision Making, , vol. 36(1), pages 59-71, January.

  65. Koopman, Siem Jan & Kräussl, Roman & Lucas, André, 2006. "Credit cycles and macro fundamentals," CFS Working Paper Series 2006/33, Center for Financial Studies (CFS).

    Cited by:

    1. Guillermo Ordonez, 2008. "Fragility of Reputation and Clustering in Risk Taking," 2008 Meeting Papers 441, Society for Economic Dynamics.
    2. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    3. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    4. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    5. Hasan, Iftekhar & Kim, Suk-Joong & Politsidis, Panagiotis & Wu, Eliza, 2021. "Loan syndication under Basel II: How do firm credit ratings affect the cost of credit?," MPRA Paper 107083, University Library of Munich, Germany.
    6. Bezemer, Dirk J & Werner, Richard A, 2009. "Disaggregated Credit Flows and Growth in Central Europe," MPRA Paper 17456, University Library of Munich, Germany.
    7. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    8. Narasimhan Jegadeesh & Roman Kräussl & Joshua Pollet, 2009. "Risk and Expected Returns of Private Equity Investments: Evidence Based on Market Prices," NBER Working Papers 15335, National Bureau of Economic Research, Inc.
    9. Carlos Castro, 2012. "Confidence sets for asset correlations in portfolio credit risk," Revista de Economía del Rosario, Universidad del Rosario.
    10. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    11. Guillaume Horny & M. Manganelli & Benoit Mojon, 2016. "Measuring Financial Fragmentation in the Euro Area Corporate Bond Market," Working papers 582, Banque de France.
    12. Jones, Stewart & Wang, Tim, 2019. "Predicting private company failure: A multi-class analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 161-188.
    13. Michala, Dimitra & Grammatikos, Theoharry & Ferreira Filipe, Sara, 2013. "Forecasting distress in European SME portfolios," EIF Working Paper Series 2013/17, European Investment Fund (EIF).
    14. Figlewski, Stephen & Frydman, Halina & Liang, Weijian, 2012. "Modeling the effect of macroeconomic factors on corporate default and credit rating transitions," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 87-105.
    15. Catherine Bruno & Olivier de Bandt & Widad El Amri, 2008. "Macroeconomic Fluctuations and Corporate Financial Fragility," Working papers 226, Banque de France.
    16. Stewart Jones, 2017. "Corporate bankruptcy prediction: a high dimensional analysis," Review of Accounting Studies, Springer, vol. 22(3), pages 1366-1422, September.
    17. Olfa Maalaoui & Georges Dionne & Pascal François, 2009. "Credit Spread Changes within Switching Regimes," Cahiers de recherche 0905, CIRPEE.
    18. Hasan, Iftekhar & Kim, Suk-Joong & Politsidis, Panagiotis & Wu, Eliza, 2020. "Syndicated bank lending and rating downgrades: Do sovereign ceiling policies really matter?," MPRA Paper 102941, University Library of Munich, Germany.
    19. Konrad Banachewicz & Aad van der Vaart & André Lucas, 2006. "Modeling Portfolio Defaults using Hidden Markov Models with Covariates," Tinbergen Institute Discussion Papers 06-094/2, Tinbergen Institute.
    20. Judith Eidenberger & Benjamin Neudorfer & Michael Sigmund & Ingrid Stein, 2013. "Quantifying Financial Stability in Austria, New Tools for Macroprudential Supervision," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 26, pages 62-81.
    21. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    22. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    23. Stephanie F. Cheng & Dushyantkumar Vyas & Regina Wittenberg-Moerman & Wuyang Zhao, 2025. "Exposure to superstar firms and financial distress," Review of Accounting Studies, Springer, vol. 30(2), pages 1355-1396, June.
    24. John Beirne, 2019. "Financial Cycles in Asset Markets and Regions," ADBI Working Papers 1052, Asian Development Bank Institute.
    25. Broto, Carmen & Molina, Luis, 2016. "Sovereign ratings and their asymmetric response to fundamentals," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 206-224.
    26. Konrad Banachewicz & André Lucas, 2008. "Quantile forecasting for credit risk management using possibly misspecified hidden Markov models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 566-586.
    27. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    28. Bezemer, Dirk J, 2009. "Disaggregated Credit Flows and Growth in Central Europe," MPRA Paper 15896, University Library of Munich, Germany.
    29. Ilyes Abid & Farid Mkaouar & Olfa Kaabia, 2018. "Dynamic analysis of the forecasting bankruptcy under presence of unobserved heterogeneity," Annals of Operations Research, Springer, vol. 262(2), pages 241-256, March.
    30. Dimitra Michala & Theoharry Grammatikos & Sara Ferreira Filipe, 2013. "Forecasting distress in European SME portfolios," DEM Discussion Paper Series 13-2, Department of Economics at the University of Luxembourg.
    31. Jones, Stewart & Johnstone, David & Wilson, Roy, 2015. "An empirical evaluation of the performance of binary classifiers in the prediction of credit ratings changes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 72-85.
    32. Haipeng Xing & Ying Chen, 2018. "Dependence of Structural Breaks in Rating Transition Dynamics on Economic and Market Variations," Review of Economics & Finance, Better Advances Press, Canada, vol. 11, pages 1-18, February.
    33. Duan, Jin-Chuan & Sun, Jie & Wang, Tao, 2012. "Multiperiod corporate default prediction—A forward intensity approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 191-209.
    34. Anisa Caja & Frédéric Planchet, 2014. "Modeling Cycle Dependence in Credit Insurance," Risks, MDPI, vol. 2(1), pages 1-15, March.
    35. Orth, Walter, 2013. "Multi-period credit default prediction with time-varying covariates," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 214-222.
    36. Miroslav Plasil & Tomas Konecny & Jakub Seidler & Petr Hlavac, 2015. "In the Quest of Measuring the Financial Cycle," Working Papers 2015/05, Czech National Bank, Research and Statistics Department.
    37. Yang, Lu & Yang, Lei & Ho, Kung-Cheng & Hamori, Shigeyuki, 2020. "Dependence structures and risk spillover in China’s credit bond market: A copula and CoVaR approach," Journal of Asian Economics, Elsevier, vol. 68(C).
    38. Lee, Shih-Cheng & Lin, Chien-Ting & Yang, Chih-Kai, 2011. "The asymmetric behavior and procyclical impact of asset correlations," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2559-2568, October.
    39. Bitar, Mohammad & Pukthuanthong, Kuntara & Walker, Thomas, 2020. "Efficiency in Islamic vs. conventional banking: The role of capital and liquidity," Global Finance Journal, Elsevier, vol. 46(C).
    40. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    41. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    42. Paolo Agnese & Manuel Rizzo & Gianfranco A. Vento, 2018. "SMEs finance and bankruptcies: The role of credit guarantee schemes in the UK," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(3), pages 1-1.
    43. Eidenberger, Judith & Neudorfer, Benjamin & Sigmund, Michael & Stein, Ingrid, 2014. "What predicts financial (in)stability? A Bayesian approach," Discussion Papers 36/2014, Deutsche Bundesbank.
    44. Adam Gersl & Petr Jakubik, 2010. "Procyclicality of the Financial System and Simulation of the Feedback Effect," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2009/2010, chapter 0, pages 110-119, Czech National Bank, Research and Statistics Department.
    45. Edirisinghe, Chanaka & Sawicki, Julia & Zhao, Yonggan & Zhou, Jun, 2022. "Predicting credit rating changes conditional on economic strength," Finance Research Letters, Elsevier, vol. 47(PB).
    46. André A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
    47. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    48. Bitar, Mohammad & Hassan, M. Kabir & Walker, Thomas, 2017. "Political systems and the financial soundness of Islamic banks," Journal of Financial Stability, Elsevier, vol. 31(C), pages 18-44.
    49. Salma Louati & Younes Boujelbene, 2021. "Basel Regulations and Banks’ Risk-efficiency Nexus: Evidence from Dynamic Simultaneous-equation Models," Journal of African Business, Taylor & Francis Journals, vol. 22(4), pages 578-602, October.
    50. Xing, Kai & Yang, Xiaoguang, 2020. "Predicting default rates by capturing critical transitions in the macroeconomic system," Finance Research Letters, Elsevier, vol. 32(C).
    51. Oliver Blümke, 2020. "Estimating the probability of default for no‐default and low‐default portfolios," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 89-107, January.
    52. Voß, Sebastian & Weißbach, Rafael, 2014. "A score-test on measurement errors in rating transition times," Journal of Econometrics, Elsevier, vol. 180(1), pages 16-29.
    53. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    54. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
    55. Dimitra Michala & Theoharry Grammatikos & Sara Ferreira Filipe, 2013. "Forecasting distress in European SME portfolios," LSF Research Working Paper Series 13-2, Luxembourg School of Finance, University of Luxembourg.
    56. Klein, Arne C. & Pliszka, Kamil, 2018. "The time-varying impact of systematic risk factors on corporate bond spreads," Discussion Papers 14/2018, Deutsche Bundesbank.
    57. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    58. Salnikov, V. & Mogilat, A. & Maslov, I., 2012. "Stress Testing for Russian Real Sector: First Approach," Journal of the New Economic Association, New Economic Association, vol. 16(4), pages 46-70.
    59. Banu Simmons-Sueer, 2013. "Forecasting High-Yield Bond Spreads Using the Loan Market as Leading Indicator," KOF Working papers 13-328, KOF Swiss Economic Institute, ETH Zurich.
    60. Kauko, Karlo, 2010. "The feasibility of through-the-cycle ratings," Bank of Finland Research Discussion Papers 14/2010, Bank of Finland.
    61. Georges Dionne & Pascal François & Olfa Maalaoui Chun, 2009. "Detecting Regime Shifts in Corporate Credit Spreads," Cahiers de recherche 0929, CIRPEE.
    62. Ming-Chin Hung & Yung-Kang Ching & Shih-Kuei Lin, 2021. "Impact of COVID-19 on the Robustness of the Probability of Default Estimation Model," Mathematics, MDPI, vol. 9(23), pages 1-13, November.

  66. Koopman, Siem Jan & Kräussl, Roman & Lucas, André, 2006. "Credit cycles and macro fundamentals," CFS Working Paper Series 2006/33, Center for Financial Studies (CFS).

    Cited by:

    1. Guillermo Ordonez, 2008. "Fragility of Reputation and Clustering in Risk Taking," 2008 Meeting Papers 441, Society for Economic Dynamics.
    2. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    3. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    4. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    5. Hasan, Iftekhar & Kim, Suk-Joong & Politsidis, Panagiotis & Wu, Eliza, 2021. "Loan syndication under Basel II: How do firm credit ratings affect the cost of credit?," MPRA Paper 107083, University Library of Munich, Germany.
    6. Bezemer, Dirk J & Werner, Richard A, 2009. "Disaggregated Credit Flows and Growth in Central Europe," MPRA Paper 17456, University Library of Munich, Germany.
    7. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    8. Narasimhan Jegadeesh & Roman Kräussl & Joshua Pollet, 2009. "Risk and Expected Returns of Private Equity Investments: Evidence Based on Market Prices," NBER Working Papers 15335, National Bureau of Economic Research, Inc.
    9. Carlos Castro, 2012. "Confidence sets for asset correlations in portfolio credit risk," Revista de Economía del Rosario, Universidad del Rosario.
    10. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    11. Guillaume Horny & M. Manganelli & Benoit Mojon, 2016. "Measuring Financial Fragmentation in the Euro Area Corporate Bond Market," Working papers 582, Banque de France.
    12. Jones, Stewart & Wang, Tim, 2019. "Predicting private company failure: A multi-class analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 161-188.
    13. Michala, Dimitra & Grammatikos, Theoharry & Ferreira Filipe, Sara, 2013. "Forecasting distress in European SME portfolios," EIF Working Paper Series 2013/17, European Investment Fund (EIF).
    14. Figlewski, Stephen & Frydman, Halina & Liang, Weijian, 2012. "Modeling the effect of macroeconomic factors on corporate default and credit rating transitions," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 87-105.
    15. Catherine Bruno & Olivier de Bandt & Widad El Amri, 2008. "Macroeconomic Fluctuations and Corporate Financial Fragility," Working papers 226, Banque de France.
    16. Stewart Jones, 2017. "Corporate bankruptcy prediction: a high dimensional analysis," Review of Accounting Studies, Springer, vol. 22(3), pages 1366-1422, September.
    17. Olfa Maalaoui & Georges Dionne & Pascal François, 2009. "Credit Spread Changes within Switching Regimes," Cahiers de recherche 0905, CIRPEE.
    18. Hasan, Iftekhar & Kim, Suk-Joong & Politsidis, Panagiotis & Wu, Eliza, 2020. "Syndicated bank lending and rating downgrades: Do sovereign ceiling policies really matter?," MPRA Paper 102941, University Library of Munich, Germany.
    19. Konrad Banachewicz & Aad van der Vaart & André Lucas, 2006. "Modeling Portfolio Defaults using Hidden Markov Models with Covariates," Tinbergen Institute Discussion Papers 06-094/2, Tinbergen Institute.
    20. Judith Eidenberger & Benjamin Neudorfer & Michael Sigmund & Ingrid Stein, 2013. "Quantifying Financial Stability in Austria, New Tools for Macroprudential Supervision," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 26, pages 62-81.
    21. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    22. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    23. Stephanie F. Cheng & Dushyantkumar Vyas & Regina Wittenberg-Moerman & Wuyang Zhao, 2025. "Exposure to superstar firms and financial distress," Review of Accounting Studies, Springer, vol. 30(2), pages 1355-1396, June.
    24. John Beirne, 2019. "Financial Cycles in Asset Markets and Regions," ADBI Working Papers 1052, Asian Development Bank Institute.
    25. Broto, Carmen & Molina, Luis, 2016. "Sovereign ratings and their asymmetric response to fundamentals," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 206-224.
    26. Konrad Banachewicz & André Lucas, 2008. "Quantile forecasting for credit risk management using possibly misspecified hidden Markov models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 566-586.
    27. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    28. Bezemer, Dirk J, 2009. "Disaggregated Credit Flows and Growth in Central Europe," MPRA Paper 15896, University Library of Munich, Germany.
    29. Ilyes Abid & Farid Mkaouar & Olfa Kaabia, 2018. "Dynamic analysis of the forecasting bankruptcy under presence of unobserved heterogeneity," Annals of Operations Research, Springer, vol. 262(2), pages 241-256, March.
    30. Dimitra Michala & Theoharry Grammatikos & Sara Ferreira Filipe, 2013. "Forecasting distress in European SME portfolios," DEM Discussion Paper Series 13-2, Department of Economics at the University of Luxembourg.
    31. Jones, Stewart & Johnstone, David & Wilson, Roy, 2015. "An empirical evaluation of the performance of binary classifiers in the prediction of credit ratings changes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 72-85.
    32. Haipeng Xing & Ying Chen, 2018. "Dependence of Structural Breaks in Rating Transition Dynamics on Economic and Market Variations," Review of Economics & Finance, Better Advances Press, Canada, vol. 11, pages 1-18, February.
    33. Duan, Jin-Chuan & Sun, Jie & Wang, Tao, 2012. "Multiperiod corporate default prediction—A forward intensity approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 191-209.
    34. Anisa Caja & Frédéric Planchet, 2014. "Modeling Cycle Dependence in Credit Insurance," Risks, MDPI, vol. 2(1), pages 1-15, March.
    35. Orth, Walter, 2013. "Multi-period credit default prediction with time-varying covariates," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 214-222.
    36. Miroslav Plasil & Tomas Konecny & Jakub Seidler & Petr Hlavac, 2015. "In the Quest of Measuring the Financial Cycle," Working Papers 2015/05, Czech National Bank, Research and Statistics Department.
    37. Yang, Lu & Yang, Lei & Ho, Kung-Cheng & Hamori, Shigeyuki, 2020. "Dependence structures and risk spillover in China’s credit bond market: A copula and CoVaR approach," Journal of Asian Economics, Elsevier, vol. 68(C).
    38. Lee, Shih-Cheng & Lin, Chien-Ting & Yang, Chih-Kai, 2011. "The asymmetric behavior and procyclical impact of asset correlations," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2559-2568, October.
    39. Bitar, Mohammad & Pukthuanthong, Kuntara & Walker, Thomas, 2020. "Efficiency in Islamic vs. conventional banking: The role of capital and liquidity," Global Finance Journal, Elsevier, vol. 46(C).
    40. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    41. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    42. Paolo Agnese & Manuel Rizzo & Gianfranco A. Vento, 2018. "SMEs finance and bankruptcies: The role of credit guarantee schemes in the UK," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(3), pages 1-1.
    43. Eidenberger, Judith & Neudorfer, Benjamin & Sigmund, Michael & Stein, Ingrid, 2014. "What predicts financial (in)stability? A Bayesian approach," Discussion Papers 36/2014, Deutsche Bundesbank.
    44. Adam Gersl & Petr Jakubik, 2010. "Procyclicality of the Financial System and Simulation of the Feedback Effect," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2009/2010, chapter 0, pages 110-119, Czech National Bank, Research and Statistics Department.
    45. Edirisinghe, Chanaka & Sawicki, Julia & Zhao, Yonggan & Zhou, Jun, 2022. "Predicting credit rating changes conditional on economic strength," Finance Research Letters, Elsevier, vol. 47(PB).
    46. André A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
    47. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    48. Bitar, Mohammad & Hassan, M. Kabir & Walker, Thomas, 2017. "Political systems and the financial soundness of Islamic banks," Journal of Financial Stability, Elsevier, vol. 31(C), pages 18-44.
    49. Salma Louati & Younes Boujelbene, 2021. "Basel Regulations and Banks’ Risk-efficiency Nexus: Evidence from Dynamic Simultaneous-equation Models," Journal of African Business, Taylor & Francis Journals, vol. 22(4), pages 578-602, October.
    50. Xing, Kai & Yang, Xiaoguang, 2020. "Predicting default rates by capturing critical transitions in the macroeconomic system," Finance Research Letters, Elsevier, vol. 32(C).
    51. Oliver Blümke, 2020. "Estimating the probability of default for no‐default and low‐default portfolios," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 89-107, January.
    52. Voß, Sebastian & Weißbach, Rafael, 2014. "A score-test on measurement errors in rating transition times," Journal of Econometrics, Elsevier, vol. 180(1), pages 16-29.
    53. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    54. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
    55. Dimitra Michala & Theoharry Grammatikos & Sara Ferreira Filipe, 2013. "Forecasting distress in European SME portfolios," LSF Research Working Paper Series 13-2, Luxembourg School of Finance, University of Luxembourg.
    56. Klein, Arne C. & Pliszka, Kamil, 2018. "The time-varying impact of systematic risk factors on corporate bond spreads," Discussion Papers 14/2018, Deutsche Bundesbank.
    57. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    58. Salnikov, V. & Mogilat, A. & Maslov, I., 2012. "Stress Testing for Russian Real Sector: First Approach," Journal of the New Economic Association, New Economic Association, vol. 16(4), pages 46-70.
    59. Banu Simmons-Sueer, 2013. "Forecasting High-Yield Bond Spreads Using the Loan Market as Leading Indicator," KOF Working papers 13-328, KOF Swiss Economic Institute, ETH Zurich.
    60. Kauko, Karlo, 2010. "The feasibility of through-the-cycle ratings," Bank of Finland Research Discussion Papers 14/2010, Bank of Finland.
    61. Georges Dionne & Pascal François & Olfa Maalaoui Chun, 2009. "Detecting Regime Shifts in Corporate Credit Spreads," Cahiers de recherche 0929, CIRPEE.
    62. Ming-Chin Hung & Yung-Kang Ching & Shih-Kuei Lin, 2021. "Impact of COVID-19 on the Robustness of the Probability of Default Estimation Model," Mathematics, MDPI, vol. 9(23), pages 1-13, November.

  67. Konrad Banachewicz & Aad van der Vaart & André Lucas, 2006. "Modeling Portfolio Defaults using Hidden Markov Models with Covariates," Tinbergen Institute Discussion Papers 06-094/2, Tinbergen Institute.

    Cited by:

    1. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    2. Spezia, L. & Cooksley, S.L. & Brewer, M.J. & Donnelly, D. & Tree, A., 2014. "Modelling species abundance in a river by Negative Binomial hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 599-614.
    3. Anastasios Petropoulos & Vasilis Siakoulis & Dionysios Mylonas & Aristotelis Klamargias, 2018. "A combined statistical framework for forecasting default rates of Greek Financial Institutions' credit portfolios," Working Papers 243, Bank of Greece.
    4. Sylvia Frühwirth-Schnatter & Andrea Weber & Rudolf Winter-Ebmer, 2010. "Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering," Economics working papers 2010-11, Department of Economics, Johannes Kepler University Linz, Austria.
    5. Konrad Banachewicz & André Lucas, 2008. "Quantile forecasting for credit risk management using possibly misspecified hidden Markov models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 566-586.
    6. Yao-Zhi Xu & Jian-Lin Zhang & Ying Hua & Lin-Yue Wang, 2019. "Dynamic Credit Risk Evaluation Method for E-Commerce Sellers Based on a Hybrid Artificial Intelligence Model," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    7. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    8. Vrontos, Spyridon D. & Galakis, John & Vrontos, Ioannis D., 2021. "Modeling and predicting U.S. recessions using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 37(2), pages 647-671.
    9. Elliott, Robert J. & Chen, Zhiping & Duan, Qihong, 2009. "Insurance claims modulated by a hidden Brownian marked point process," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 163-172, October.
    10. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," IJFS, MDPI, vol. 2(1), pages 1-22, March.
    11. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Migration Analysis; Conditioning Transition Matrices on the Stage of the Business Cycle," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(2), pages 151-166, May.
    12. Benjamin Neudorfer & Michael Sigmund & Alexander Trachta, 2011. "Detecting Financial Stability Vulnerabilities in Due Time: Can Simple Indicators Identify a Complex Issue?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 59-71.
    13. Shima Ghassempour & Federico Girosi & Anthony Maeder, 2014. "Clustering Multivariate Time Series Using Hidden Markov Models," IJERPH, MDPI, vol. 11(3), pages 1-23, March.
    14. Ioannis D. Vrontos & John Galakis & Ekaterini Panopoulou & Spyridon D. Vrontos, 2024. "Forecasting GDP growth: The economic impact of COVID‐19 pandemic," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 1042-1086, July.

  68. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.

    Cited by:

    1. Chen, Peimin & Wu, Chunchi, 2014. "Default prediction with dynamic sectoral and macroeconomic frailties," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 211-226.
    2. Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
    3. Weißbach, Rafael & Walter, Ronja, 2010. "A likelihood ratio test for stationarity of rating transitions," Journal of Econometrics, Elsevier, vol. 155(2), pages 188-194, April.
    4. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    5. Bátiz-Zuk Enrique & Mohamed Abdulkadir & Sánchez-Cajal Fátima, 2021. "Exploring the sources of loan default clustering using survival analysis with frailty," Working Papers 2021-14, Banco de México.
    6. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    7. Areski Cousin & J'er^ome Lelong & Tom Picard, 2021. "Rating transitions forecasting: a filtering approach," Papers 2109.10567, arXiv.org, revised Jun 2023.
    8. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    9. Elena Kalotychou & Ana-Maria Fuertes, 2006. "On Sovereign Credit Migration: A Study of Alternative Estimators and Rating Dynamics," Computing in Economics and Finance 2006 509, Society for Computational Economics.
    10. Haipeng Xing & Yang Yu, 2018. "Firm’s Credit Risk in the Presence of Market Structural Breaks," Risks, MDPI, vol. 6(4), pages 1-16, December.
    11. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    12. István Barra & Lennart Hoogerheide & Siem Jan Koopman & André Lucas, 2017. "Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 1003-1026, August.
    13. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2011. "Systemic risk diagnostics: coincident indicators and early warning signals," Working Paper Series 1327, European Central Bank.
    14. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    15. Correa, Arnildo & Marins, Jaqueline & Neves, Myrian & da Silva, Antonio Carlos, 2014. "Credit Default and Business Cycles: An Empirical Investigation of Brazilian Retail Loans," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(3), September.
    16. Figlewski, Stephen & Frydman, Halina & Liang, Weijian, 2012. "Modeling the effect of macroeconomic factors on corporate default and credit rating transitions," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 87-105.
    17. Matthies, Alexander B., 2013. "Empirical research on corporate credit-ratings: A literature review," SFB 649 Discussion Papers 2013-003, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    19. Hautsch, Nikolaus, 2007. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," CFS Working Paper Series 2007/25, Center for Financial Studies (CFS).
    20. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    21. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    22. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    23. Cuadros-Solas, Pedro Jesús & Salvador Muñoz, Carlos, 2022. "Disentangling the sources of sovereign rating adjustments: An examination of changes in rating policies following the GFC," Research in International Business and Finance, Elsevier, vol. 59(C).
    24. Patrick GAGLIARDINI & Christian GOURIEROUX, 2010. "Efficiency in Large Dynamic Panel Models with Common Factor," Working Papers 2010-05, Center for Research in Economics and Statistics.
    25. Broto, Carmen & Molina, Luis, 2016. "Sovereign ratings and their asymmetric response to fundamentals," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 206-224.
    26. Sigrist, Fabio & Hirnschall, Christoph, 2019. "Grabit: Gradient tree-boosted Tobit models for default prediction," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 177-192.
    27. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    28. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    29. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    30. Marius Pfeuffer & Goncalo dos Reis & Greig smith, 2018. "Capturing Model Risk and Rating Momentum in the Estimation of Probabilities of Default and Credit Rating Migrations," Papers 1809.09889, arXiv.org, revised Feb 2020.
    31. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," LIDAM Discussion Papers CORE 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    32. Duan, Jin-Chuan & Sun, Jie & Wang, Tao, 2012. "Multiperiod corporate default prediction—A forward intensity approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 191-209.
    33. Jian He & Asma Khedher & Peter Spreij, 2024. "Calibration of the rating transition model for high and low default portfolios," Papers 2405.00576, arXiv.org.
    34. Jeffrey R. Stokes, 2023. "A nonlinear inversion procedure for modeling the effects of economic factors on credit risk migration," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 855-878, October.
    35. Chew Lian Chua & G. C. Lim & Penelope Smith, 2008. "A Bayesian Simulation Approach to Inference on a Multi-State Latent Factor Intensity Model," Melbourne Institute Working Paper Series wp2008n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    36. Wang, Fa, 2022. "Maximum likelihood estimation and inference for high dimensional generalized factor models with application to factor-augmented regressions," Journal of Econometrics, Elsevier, vol. 229(1), pages 180-200.
    37. Bernd Schwaab & Andre Lucas & Siem Jan Koopman, 2010. "Systemic Risk Diagnostics," Tinbergen Institute Discussion Papers 10-104/2/DSF 2, Tinbergen Institute, revised 29 Nov 2010.
    38. Elkamhi, Redouane & Nozawa, Yoshio, 2022. "Fire-sale risk in the leveraged loan market," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1120-1147.
    39. Orth, Walter, 2013. "Multi-period credit default prediction with time-varying covariates," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 214-222.
    40. Takeaki Kariya & Yoko Tanokura & Hideyuki Takada & Yoshiro Yamamura, 2016. "Measuring Credit Risk of Individual Corporate Bonds in US Energy Sector," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 23(3), pages 229-262, September.
    41. Miroslav Plasil & Tomas Konecny & Jakub Seidler & Petr Hlavac, 2015. "In the Quest of Measuring the Financial Cycle," Working Papers 2015/05, Czech National Bank, Research and Statistics Department.
    42. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    43. Kabuche, Doreen & Sherris, Michael & Villegas, Andrés M. & Ziveyi, Jonathan, 2024. "Pooling functional disability and mortality in long-term care insurance and care annuities: A matrix approach for multi-state pools," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 165-188.
    44. Andre Lucas & Bastiaan Verhoef, 2012. "Aggregating Credit and Market Risk: The Impact of Model Specification," Tinbergen Institute Discussion Papers 12-057/2/DSF36, Tinbergen Institute.
    45. Areski Cousin & Mohamed Reda Kheliouen, 2016. "A comparative study on the estimation of factor migration models," Working Papers halshs-01351926, HAL.
    46. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    47. Giesecke, Kay & Schwenkler, Gustavo, 2018. "Filtered likelihood for point processes," Journal of Econometrics, Elsevier, vol. 204(1), pages 33-53.
    48. Antoine Djogbenou & Christian Gouri'eroux & Joann Jasiak & Maygol Bandehali, 2021. "Composite Likelihood for Stochastic Migration Model with Unobserved Factor," Papers 2109.09043, arXiv.org, revised Nov 2023.
    49. André A. Monteiro, 2008. "Parameter Driven Multi-state Duration Models: Simulated vs. Approximate Maximum Likelihood Estimation," Tinbergen Institute Discussion Papers 08-021/2, Tinbergen Institute.
    50. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    51. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Rating transitions forecasting: a filtering approach," Post-Print hal-03347521, HAL.
    52. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," IJFS, MDPI, vol. 2(1), pages 1-22, March.
    53. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Migration Analysis; Conditioning Transition Matrices on the Stage of the Business Cycle," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(2), pages 151-166, May.
    54. Xavier Hollandts & Daniela Borodak & Ariane Tichit, 2018. "La dynamique de changement des formes de gouvernance : le cas français (2000-2014)," Post-Print hal-02022915, HAL.
    55. Hidetoshi Nakagawa & Hideyuki Takada, 2014. "Numerical analysis of rating transition matrix depending on latent macro factor via nonlinear particle filter method," Journal of Financial Engineering (JFE), World Scientific Publishing Co. Pte. Ltd., vol. 1(03), pages 1-31.
    56. Xiaoqi Zhang & Yi Chen & Yi Yao, 2021. "Dynamic information asymmetry in micro health insurance: implications for sustainability," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(3), pages 468-507, July.
    57. Andre Monteiro & Georgi V. Smirnov & Andre Lucas, 2006. "Nonparametric Estimation for Non-Homogeneous Semi-Markov Processes: An Application to Credit Risk," Tinbergen Institute Discussion Papers 06-024/2, Tinbergen Institute, revised 27 Mar 2006.
    58. Voß, Sebastian & Weißbach, Rafael, 2014. "A score-test on measurement errors in rating transition times," Journal of Econometrics, Elsevier, vol. 180(1), pages 16-29.
    59. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
    60. Kay Giesecke & Baeho Kim, 2011. "Systemic Risk: What Defaults Are Telling Us," Management Science, INFORMS, vol. 57(8), pages 1387-1405, August.
    61. Chew Lian Chua & Robert Dixon & G. C. Lim, 2007. "What Drives Worker Flows?," Melbourne Institute Working Paper Series wp2007n34, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    62. Samuel N. Cohen & Robert J. Elliott, 2013. "Filters and smoothers for self-exciting Markov modulated counting processes," Papers 1311.6257, arXiv.org.
    63. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    64. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
    65. Ji, Guseon & Dai, Bingcun & Park, Sung-Pil & Ahn, Kwangwon, 2020. "The origin of collective phenomena in firm sizes," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).

  69. Siem Jan Koopman & André Lucas & Robert Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Tinbergen Institute Discussion Papers 05-060/4, Tinbergen Institute.

    Cited by:

    1. Siem Jan Koopman & Rutger Lit, 2015. "A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 167-186, January.
    2. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    3. Weißbach, Rafael & Mollenhauer, Thomas, 2011. "Modelling Rating Transitions," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48698, Verein für Socialpolitik / German Economic Association.
    4. Carlos Castro, 2012. "Confidence sets for asset correlations in portfolio credit risk," Revista de Economía del Rosario, Universidad del Rosario.
    5. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2011. "Systemic risk diagnostics: coincident indicators and early warning signals," Working Paper Series 1327, European Central Bank.
    6. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    7. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
    8. Konrad Banachewicz & Aad van der Vaart & André Lucas, 2006. "Modeling Portfolio Defaults using Hidden Markov Models with Covariates," Tinbergen Institute Discussion Papers 06-094/2, Tinbergen Institute.
    9. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    10. Ha Nguyen, 2023. "Particle MCMC in forecasting frailty correlated default models with expert opinion," Papers 2304.11586, arXiv.org, revised Aug 2023.
    11. Geert Mesters & Siem Jan Koopman, 2012. "Generalized Dynamic Panel Data Models with Random Effects for Cross-Section and Time," Tinbergen Institute Discussion Papers 12-009/4, Tinbergen Institute, revised 18 Mar 2014.
    12. Konrad Banachewicz & André Lucas, 2008. "Quantile forecasting for credit risk management using possibly misspecified hidden Markov models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 566-586.
    13. Nikola A. Tarashev & Haibin Zhu, 2006. "The pricing of portfolio credit risk," BIS Working Papers 214, Bank for International Settlements.
    14. Wang, Fa, 2022. "Maximum likelihood estimation and inference for high dimensional generalized factor models with application to factor-augmented regressions," Journal of Econometrics, Elsevier, vol. 229(1), pages 180-200.
    15. Bernd Schwaab & Andre Lucas & Siem Jan Koopman, 2010. "Systemic Risk Diagnostics," Tinbergen Institute Discussion Papers 10-104/2/DSF 2, Tinbergen Institute, revised 29 Nov 2010.
    16. Xin Huang & Hao Zhou & Haibin Zhu, 2009. "A Framework for Assessing the Systemic Risk of Major Financial Institutions," BIS Working Papers 281, Bank for International Settlements.
    17. Mathias Mandla Manguzvane & John Weirstrass Muteba Mwamba, 2020. "GAS Copula models on who’s systemically important in South Africa: Banks or Insurers?," Empirical Economics, Springer, vol. 59(4), pages 1573-1604, October.
    18. Truong, Chi & Trück, Stefan & Mathew, Supriya, 2018. "Managing risks from climate impacted hazards – The value of investment flexibility under uncertainty," European Journal of Operational Research, Elsevier, vol. 269(1), pages 132-145.
    19. Andre Lucas & Bastiaan Verhoef, 2012. "Aggregating Credit and Market Risk: The Impact of Model Specification," Tinbergen Institute Discussion Papers 12-057/2/DSF36, Tinbergen Institute.
    20. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    21. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
    22. Zhu, Haibin & Tarashev, Nikola A., 2008. "The pricing of correlated default risk: evidence from the credit derivatives market," Discussion Paper Series 2: Banking and Financial Studies 2008,09, Deutsche Bundesbank.
    23. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    24. Abel Elizalde, 2006. "Credit Risk Models IV: Understanding and Pricing CDOs," Working Papers wp2006_0608, CEMFI.
    25. Michael Kalkbrener & Akwum Onwunta, 2009. "Validating Structural Credit Portfolio Models," Working Papers 014, COMISEF.
    26. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    27. Qin, Zhaohui & Wang, Xiaowan & Chen, Yijie & Fan, Yali & Andrianarimanana, Mihasina Harinaivo & Gai, Dhornor Tarir Duok, 2024. "Time-varying default risk of Chinese-listed companies: From empirical test to theoretical conjecture," Finance Research Letters, Elsevier, vol. 67(PA).
    28. Tobias Neumann, 2018. "Mortgages: estimating default correlation and forecasting default risk," Bank of England working papers 708, Bank of England.

  70. Siem Jan Koopman & André Lucas, 2003. "Business and Default Cycles for Credit Risk," Tinbergen Institute Discussion Papers 03-062/2, Tinbergen Institute, revised 09 Jan 2003.

    Cited by:

    1. Guillermo Ordonez, 2008. "Fragility of Reputation and Clustering in Risk Taking," 2008 Meeting Papers 441, Society for Economic Dynamics.
    2. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    3. Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
    4. Koopman, Siem Jan & Lucas, Andre & Klaassen, Pieter, 2005. "Empirical credit cycles and capital buffer formation," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3159-3179, December.
    5. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
    6. Siem Jan Koopman & André Lucas & Robert Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Tinbergen Institute Discussion Papers 05-060/4, Tinbergen Institute.
    7. Cipollini, Andrea & Missaglia, Giuseppe, 2007. "Dynamic Factor analysis of industry sector default rates and implication for Portfolio Credit Risk Modelling," MPRA Paper 3582, University Library of Munich, Germany.
    8. Susan K. Schroeder, 2008. "The Underpinnings Of Country Risk Assessment," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 498-535, July.
    9. Bhattacharjee, Arnab & Hany, Jie, 2010. "Financial Distress in Chinese Industry: Microeconomic, Macroeconomic and Institutional Infuences," SIRE Discussion Papers 2010-53, Scottish Institute for Research in Economics (SIRE).
    10. Diana Barro & Antonella Basso, 2008. "Credit contagion in a network of firms with spatial interaction," Working Papers 186, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    11. Inekwe, John Nkwoma & Jin, Yi & Valenzuela, Ma. Rebecca, 2018. "The effects of financial distress: Evidence from US GDP growth," Economic Modelling, Elsevier, vol. 72(C), pages 8-21.
    12. Rob Luginbuhl, 2020. "Estimation of the Financial Cycle with a Rank-Reduced Multivariate State-Space Model," CPB Discussion Paper 409, CPB Netherlands Bureau for Economic Policy Analysis.
    13. Gabriele Galati & Irma Hindrayanto & Siem Jan Koopman & Marente Vlekke, 2016. "Measuring Financial Cycles in a Model-Based Analysis: Empirical Evidence for the United States and the Euro Area," Tinbergen Institute Discussion Papers 16-029/III, Tinbergen Institute.
    14. Makram El‐Shagi & Gregor von Schweinitz, 2022. "Why they keep missing: An empirical investigation of sovereign bond ratings and their timing," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 186-224, May.
    15. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    16. Linda Allen & Anthony Saunders, 2004. "Incorporating Systemic Influences Into Risk Measurements: A Survey of the Literature," Journal of Financial Services Research, Springer;Western Finance Association, vol. 26(2), pages 161-191, October.
    17. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    18. Petr Jakubík, 2006. "Does Credit Risk Vary with Economic Cycles? The Case of Finland," Working Papers IES 2006/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2006.
    19. Correa, Arnildo & Marins, Jaqueline & Neves, Myrian & da Silva, Antonio Carlos, 2014. "Credit Default and Business Cycles: An Empirical Investigation of Brazilian Retail Loans," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(3), September.
    20. Lu, Yang-Cheng & Shen, Chung-Hua & Wei, Yu-Chen, 2013. "Revisiting early warning signals of corporate credit default using linguistic analysis," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 1-21.
    21. Catherine Bruno & Olivier de Bandt & Widad El Amri, 2008. "Macroeconomic Fluctuations and Corporate Financial Fragility," Working papers 226, Banque de France.
    22. Olfa Maalaoui & Georges Dionne & Pascal François, 2009. "Credit Spread Changes within Switching Regimes," Cahiers de recherche 0905, CIRPEE.
    23. Mizen, Paul & Tsoukas, Serafeim, 2011. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," SIRE Discussion Papers 2011-69, Scottish Institute for Research in Economics (SIRE).
    24. Fabien Tripier & Kevin E. Beaubrun-Diant, 2010. "The Credit Spread Cycle with Matching Friction," 2010 Meeting Papers 76, Society for Economic Dynamics.
    25. Kuang-Hua Hu & Shih-Kuei Lin & Yung-Kang Ching & Ming-Chin Hung, 2021. "Goodness-of-Fit of Logistic Regression of the Default Rate on GDP Growth Rate and on CDX Indices," Mathematics, MDPI, vol. 9(16), pages 1-14, August.
    26. Peter Fuleky & Carl, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 2013-5, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    27. Hayette Gatfaoui, 2004. "Idiosyncratic Risk, Systematic Risk and Stochastic Volatility: An Implementation of Merton's Credit Risk Valuation," Research Paper Series 123, Quantitative Finance Research Centre, University of Technology, Sydney.
    28. Jang, Bong-Gyu & Rhee, Yuna & Yoon, Ji Hee, 2016. "Business cycle and credit risk modeling with jump risks," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 15-36.
    29. Strohsal, Till & Proaño Acosta, Christian & Wolters, Jürgen, 2015. "Characterizing the financial cycle: Evidence from a frequency domain analysis," SFB 649 Discussion Papers 2015-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    30. Han-Liang Cheng & Nan-Kuang Chen, 2021. "A study of financial cycles and the macroeconomy in Taiwan," Empirical Economics, Springer, vol. 61(4), pages 1749-1778, October.
    31. Rebekka Topp & Robert Perl, 2010. "Through‐the‐Cycle Ratings Versus Point‐in‐Time Ratings and Implications of the Mapping Between Both Rating Types," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 19(1), pages 47-61, February.
    32. N. Dewaelheyns & C. van Hulle, 2007. "Aggregate Bankruptcy Rates and the Macroeconomic Environment. Forecasting Systematic Probabilities of Default," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(4), pages 541-566.
    33. Myriam Ben Ayed & Adel Karaa & Jean-Luc Prigent, 2018. "Duration Models For Credit Rating Migration: Evidence From The Financial Crisis," Post-Print hal-03679407, HAL.
    34. Tajik, Mohammad & Aliakbari, Saeideh & Ghalia, Thaana & Kaffash, Sepideh, 2015. "House prices and credit risk: Evidence from the United States," Economic Modelling, Elsevier, vol. 51(C), pages 123-135.
    35. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    36. Pederzoli, Chiara & Torricelli, Costanza, 2005. "Capital requirements and business cycle regimes: Forward-looking modelling of default probabilities," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3121-3140, December.
    37. De Santis, Roberto A., 2018. "Unobservable country bond premia and fragmentation," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 1-25.
    38. Agostino, Mariarosaria & Errico, Lucia & Rondinella, Sandro & Trivieri, Francesco, 2023. "Enduring lending relationships and european firms default," Research in Economics, Elsevier, vol. 77(4), pages 459-477.
    39. Andrew E. Evans, 2020. "Average labour productivity dynamics over the business cycle," Empirical Economics, Springer, vol. 59(4), pages 1833-1863, October.
    40. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2011. "Anchoring countercyclical capital buffers: the role of credit aggregates," BIS Working Papers 355, Bank for International Settlements.
    41. Wagner, Stephan M. & Mizgier, Kamil J. & Papageorgiou, Stylianos, 2017. "Operational disruptions and business cycles," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 66-78.
    42. Alejandro Ferrer Pérez & José Casals Carro & Sonia Sotoca López, 2014. "Linking the problems of estimating and allocating unconditional capital," Documentos de Trabajo del ICAE 2014-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    43. Jian He & Asma Khedher & Peter Spreij, 2024. "Calibration of the rating transition model for high and low default portfolios," Papers 2405.00576, arXiv.org.
    44. Bhattacharjee, Arnab & Han, Jie, 2014. "Financial distress of Chinese firms: Microeconomic, macroeconomic and institutional influences," China Economic Review, Elsevier, vol. 30(C), pages 244-262.
    45. Patrik Kupkovic & Martin Suster, 2020. "Identifying the Financial Cycle in Slovakia," Working and Discussion Papers WP 2/2020, Research Department, National Bank of Slovakia.
    46. Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2022. "Measuring financial cycles: Empirical evidence for Germany, United Kingdom and United States of America," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 599-630.
    47. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
    48. Chew Lian Chua & G. C. Lim & Penelope Smith, 2008. "A Bayesian Simulation Approach to Inference on a Multi-State Latent Factor Intensity Model," Melbourne Institute Working Paper Series wp2008n16, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    49. Anisa Caja & Frédéric Planchet, 2014. "Modeling Cycle Dependence in Credit Insurance," Risks, MDPI, vol. 2(1), pages 1-15, March.
    50. Odermann, Alexander & Cremers, Heinz, 2013. "Komponenten und Determinanten des Credit Spreads: Empirische Untersuchung während Phasen von Marktstress," Frankfurt School - Working Paper Series 204, Frankfurt School of Finance and Management.
    51. Zhao, Weijia & Cui, Xin & Wang, Chunfeng & Wu, Ji (George) & He, Feng, 2022. "Couple-based leadership and default risk: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 439-463.
    52. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    53. Petr JAKUBÍK, 2007. "Macroeconomic Environment and Credit Risk (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(1-2), pages 60-78, March.
    54. Yao, Fang, 2022. "Estimating the Trend of the House Price to Income Ratio in Ireland," Research Technical Papers 8/RT/22, Central Bank of Ireland.
    55. Ptak-Chmielewska Aneta & Matuszyk Anna, 2019. "Macroeconomic Factors in Modelling the SMEs Bankruptcy Risk. The Case of the Polish Market," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(3), pages 40-49, September.
    56. Cifter, Atilla & Yilmazer, Sait & Cifter, Elif, 2009. "Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey," Economic Modelling, Elsevier, vol. 26(6), pages 1382-1388, November.
    57. Harada, Nobuyuki & Kageyama, Noriyuki, 2011. "Bankruptcy dynamics in Japan," Japan and the World Economy, Elsevier, vol. 23(2), pages 119-128, March.
    58. Roland Meeks, 2006. "Credit Shocks and Cycles: a Bayesian Calibration Approach," Economics Papers 2006-W11, Economics Group, Nuffield College, University of Oxford.
    59. Jasper de Winter & Siem Jan Koopman & Irma Hindrayanto, 2022. "Joint Decomposition of Business and Financial Cycles: Evidence from Eight Advanced Economies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 57-79, February.
    60. Guler Aras & Lale Aslan, 2011. "Capital structure and credit risk management: evidence from Turkey," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 3(1), pages 1-20.
    61. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2021. "Systematic credit risk in securitised mortgage portfolios," Journal of Banking & Finance, Elsevier, vol. 122(C).
    62. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    63. Jaehoon Hahn & Ho-Seong Moon, 2016. "Credit Cycle and the Macroeconomy: Empirical Evidence from Korea," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 22(4), pages 76-108, December.
    64. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," IJFS, MDPI, vol. 2(1), pages 1-22, March.
    65. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    66. Petr Jakubík, 2007. "Credit Risk and the Finnish Economy," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 1(3), pages 254-285, November.
    67. Dietske Simons & Ferdinand Rolwes, 2009. "Macroeconomic efault Modeling and Stress Testing," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 177-204, September.
    68. Lando, David & Nielsen, Mads Stenbo, 2010. "Correlation in corporate defaults: Contagion or conditional independence?," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 355-372, July.
    69. Ugur, Mehmet & Solomon, Edna & Zeynalov, Ayaz, 2022. "Leverage, competition and financial distress hazard: Implications for capital structure in the presence of agency costs," Economic Modelling, Elsevier, vol. 108(C).
    70. Chen, Xiaoshan & Kontonikas, Alexandros & Montagnoli, Alberto, 2012. "Asset prices, credit and the business cycle," Economics Letters, Elsevier, vol. 117(3), pages 857-861.
    71. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    72. Canepa, Alessandra & Alqaralleh, Huthaifa, 2019. "Housing Market Cycles in Large Urban Areas," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201903, University of Turin.
    73. Greg Farrell & Esti Kemp, 2020. "Measuring the Financial Cycle in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 123-144, June.
    74. Malgorzata Porada - Rochon, 2020. "The Length of Financial Cycle and its Impact on Business Cycle in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1278-1290.
    75. Paulo V. Carvalho & José D. Curto & Rodrigo Primor, 2022. "Macroeconomic determinants of credit risk: Evidence from the Eurozone," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2054-2072, April.
    76. Jorge E. Galán & Javier Mencía, 2021. "Model-based indicators for the identification of cyclical systemic risk," Empirical Economics, Springer, vol. 61(6), pages 3179-3211, December.
    77. Georges Dionne & Pascal François & Olfa Maalaoui Chun, 2009. "Detecting Regime Shifts in Corporate Credit Spreads," Cahiers de recherche 0929, CIRPEE.

  71. Albert J. Menkveld & Siem Jan Koopman & André Lucas, 2003. "Round-the-Clock Price Discovery for Cross-Listed Stocks: US-Dutch Evidence," Tinbergen Institute Discussion Papers 03-037/2, Tinbergen Institute, revised 13 Oct 2003.

    Cited by:

    1. Menkveld, Albert J., 2006. "Splitting orders in overlapping markets: a study of cross-listed stocks," Serie Research Memoranda 0003, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    2. Chan, Justin S.P. & Hong, Dong & Subrahmanyam, Marti G., 2008. "A tale of two prices: Liquidity and asset prices in multiple markets," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 947-960, June.
    3. K.C. Chen & Guangzhong Li & Lifan Wu, 2010. "Price Discovery for Segmented US‐Listed Chinese Stocks: Location or Market Quality?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(1‐2), pages 242-269, January.
    4. Yaseen S. Alhaj-Yaseen & Dana Ladd, 2019. "Which sentiments do US investors follow when trading ADRs?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(3), pages 506-527, July.

  72. André Lucas & Pieter Klaassen, 2003. "Discrete versus Continuous State Switching Models for Portfolio Credit Risk," Tinbergen Institute Discussion Papers 03-075/2, Tinbergen Institute, revised 30 Sep 2003.

    Cited by:

    1. Ferrer, Alex & Casals, José & Sotoca, Sonia, 2015. "Sample dependency during unconditional credit capital estimation," Finance Research Letters, Elsevier, vol. 15(C), pages 175-186.
    2. Thomas Lagner & Dodozu Knyphausen‐Aufseß, 2012. "Rating Agencies as Gatekeepers to the Capital Market: Practical Implications of 40 Years of Research," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 21(3), pages 157-202, August.
    3. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    4. Petr Jakubík, 2006. "Does Credit Risk Vary with Economic Cycles? The Case of Finland," Working Papers IES 2006/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2006.
    5. Konrad Banachewicz & Aad van der Vaart & André Lucas, 2006. "Modeling Portfolio Defaults using Hidden Markov Models with Covariates," Tinbergen Institute Discussion Papers 06-094/2, Tinbergen Institute.
    6. Konrad Banachewicz & André Lucas, 2008. "Quantile forecasting for credit risk management using possibly misspecified hidden Markov models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 566-586.
    7. Petr JAKUBÍK, 2007. "Macroeconomic Environment and Credit Risk (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(1-2), pages 60-78, March.
    8. Guler Aras & Lale Aslan, 2011. "Capital structure and credit risk management: evidence from Turkey," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 3(1), pages 1-20.
    9. Kim, Mi Ae & Jang, Bong-Gyu & Lee, Ho-Seok, 2008. "A first-passage-time model under regime-switching market environment," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2617-2627, December.
    10. Illanes, Gabriel & Pena, Alejandro & Sosa Rodriguez, Andrés Ricardo, 2016. "A Macroeconomic Model of Credit Risk in Uruguay," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 70(4), December.
    11. L. Jeff Hong & Guangxin Jiang, 2019. "Offline Simulation Online Application: A New Framework of Simulation-Based Decision Making," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-22, December.
    12. Marcucci, Juri & Quagliariello, Mario, 2009. "Asymmetric effects of the business cycle on bank credit risk," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1624-1635, September.
    13. Iulia Cristina Iuga, 2007. "The Tipology Of Information Necessary For The Banks And The Factors That Influence Credit Risk," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(9), pages 1-19.
    14. Petr Jakubík, 2007. "Credit Risk and the Finnish Economy," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 1(3), pages 254-285, November.
    15. Gabriel Illanes & Alejandro Pena & Andrés Sosa, 2014. "Un Modelo Macroeconómico del Riesgo de Crédito en Uruguay," Documentos de trabajo 2014002, Banco Central del Uruguay.
    16. Alejandro Ferrer Pérez & José Casals Carro & Sonia Sotoca López, 2014. "A new approach to the unconditional measurement of default risk," Documentos de Trabajo del ICAE 2014-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

  73. Siem Jan Koopman & André Lucas & Pieter Klaassen, 2002. "Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation," Tinbergen Institute Discussion Papers 02-107/2, Tinbergen Institute.

    Cited by:

    1. Lucas, Andre & Klaassen, Pieter, 2006. "Discrete versus continuous state switching models for portfolio credit risk," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 23-35, January.
    2. Pederzoli, Chiara & Torricelli, Costanza, 2005. "Capital requirements and business cycle regimes: Forward-looking modelling of default probabilities," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3121-3140, December.
    3. Ji, Tingting, 2004. "Consumer Credit Delinquency And Bankruptcy Forecasting Using Advanced Econometrc Modeling," MPRA Paper 3187, University Library of Munich, Germany.
    4. Pesola, Jarmo, 2005. "Banking fragility and distress: an econometric study of macroeconomic determinants," Bank of Finland Research Discussion Papers 13/2005, Bank of Finland.

  74. Arjen Siegmann & André Lucas, 2002. "Explaining Hedge Fund Investment Styles by Loss Aversion," Tinbergen Institute Discussion Papers 02-046/2, Tinbergen Institute.

    Cited by:

    1. Morton, David P. & Popova, Elmira & Popova, Ivilina, 2006. "Efficient fund of hedge funds construction under downside risk measures," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 503-518, February.

  75. André Lucas & Pieter Klaassen & Peter Spreij & Stefan Straetmans, 2001. "Tail Behavior of Credit Loss Distributions for General Latent Factor Models," Tinbergen Institute Discussion Papers 01-023/2, Tinbergen Institute.

    Cited by:

    1. Hsieh, Ming-Hua & Lee, Yi-Hsi & Shyu, So-De & Chiu, Yu-Fen, 2019. "Estimating multifactor portfolio credit risk: A variance reduction approach," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    2. Dilip B. Madan & Haluk Ünal, 2008. "Pricing Reinsurance Contracts on FDIC Losses," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 17(3), pages 225-247, August.
    3. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    4. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    5. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    6. Matthias Fischer & Thorsten Moser & Marius Pfeuffer, 2018. "A Discussion on Recent Risk Measures with Application to Credit Risk: Calculating Risk Contributions and Identifying Risk Concentrations," Risks, MDPI, vol. 6(4), pages 1-28, December.
    7. Albrecht, Peter, 2005. "Kreditrisiken - Modellierung und Management: Ein Überblick," German Risk and Insurance Review (GRIR), University of Cologne, Department of Risk Management and Insurance, vol. 1(2), pages 22-152.
    8. Hayette Gatfaoui, 2003. "How Does Systematic Risk Impact US Credit Spreads? A Copula Study," Risk and Insurance 0308002, University Library of Munich, Germany.
    9. Sak Halis, 2010. "Increasing the number of inner replications of multifactor portfolio credit risk simulation in the t-copula model," Monte Carlo Methods and Applications, De Gruyter, vol. 16(3-4), pages 361-377, January.
    10. Yaroslav Bologov, 2013. "A copula-based approach to portfolio credit risk modeling," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 29(1), pages 45-66.

  76. André Lucas & Ronald van Dijk & Teun Kloek, 2001. "Stock Selection, Style Rotation, and Risk," Tinbergen Institute Discussion Papers 01-021/2, Tinbergen Institute.

    Cited by:

    1. Sandrine de Moerloose & Pierre Giot, 2011. "Style investing and momentum investing: A case study," Journal of Asset Management, Palgrave Macmillan, vol. 12(6), pages 407-417, December.
    2. Yu-Shang Kuo & Jen-Tsung Huang, 2022. "Factor-Based Investing in Market Cycles: Fama–French Five-Factor Model of Market Interest Rate and Market Sentiment," JRFM, MDPI, vol. 15(10), pages 1-24, October.
    3. Andrew Clare & Svetlana Sapuric & Natasa Todorovic, 2010. "Quantitative or momentum-based multi-style rotation? UK experience," Journal of Asset Management, Palgrave Macmillan, vol. 10(6), pages 370-381, February.
    4. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla & Masih, A. Mansur M., 2014. "Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model," MPRA Paper 56965, University Library of Munich, Germany.
    5. Chou, Pin-Huang & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2019. "Asset growth, style investing, and momentum," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 108-124.
    6. Manuel Ammann & Michael Verhofen, 2006. "The Effect of Market Regimes on Style Allocation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 309-337, September.
    7. Wolfgang Drobetz & Rebekka Haller & Christian Jasperneite & Tizian Otto, 2019. "Predictability and the cross section of expected returns: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 508-533, December.
    8. Chen, Hsiu-Lang & De Bondt, Werner, 2004. "Style momentum within the S&P-500 index," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 483-507, September.
    9. Ardia, David & Boudt, Kris & Wauters, Marjan, 2016. "The economic benefits of market timing the style allocation of characteristic-based portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 38-62.
    10. Bauer, Rob & Derwall, Jeroen & Molenaar, Roderick, 2004. "The real-time predictability of the size and value premium in Japan," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 503-523, November.
    11. Golam Sarwar & Cesario Mateus & Natasa Todorovic, 2017. "A tale of two states: asymmetries in the UK small, value and momentum premiums," Applied Economics, Taylor & Francis Journals, vol. 49(5), pages 456-476, January.
    12. Georgi Nalbantov & Rob Bauer & Ida Sprinkhuizen-Kuyper, 2006. "Equity style timing using support vector regressions," Applied Financial Economics, Taylor & Francis Journals, vol. 16(15), pages 1095-1111.
    13. Thorsten Hock, 2010. "Tactical Size Rotation in Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 146(III), pages 553-576, September.
    14. Chen Su, 2021. "A comprehensive investigation into style momentum strategies in China," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(1), pages 101-144, March.
    15. Chao, Hsiao-Ying & Collver, Charles & Limthanakom, Natcha, 2012. "Global style momentum," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 319-333.

  77. Arjen H. Siegmann & André Lucas, 2000. "Analytic Decision Rules for Financial Stochastic Programs," Tinbergen Institute Discussion Papers 00-041/2, Tinbergen Institute.

    Cited by:

    1. Serguei Kaniovski, 2003. "Risk-Averse Monopolist with Aspiration," WIFO Working Papers 196, WIFO.
    2. Arjen Siegmann & André Lucas, 2002. "Explaining Hedge Fund Investment Styles by Loss Aversion," Tinbergen Institute Discussion Papers 02-046/2, Tinbergen Institute.

  78. Karim M. Abadir & Andre Lucas, 2000. "A Comparison of Minimum MSE and Maximum Power for the nearly Integrated Non-Gaussian Model," Tinbergen Institute Discussion Papers 00-033/4, Tinbergen Institute.

    Cited by:

    1. J. Roderick McCrorie, 2021. "Moments in Pearson's Four-Step Uniform Random Walk Problem and Other Applications of Very Well-Poised Generalized Hypergeometric Series," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 244-281, November.

  79. Marc G. Genton & André Lucas, 2000. "Comprehensive Definitions of Breakdown-Points for Independent and Dependent Observations," Tinbergen Institute Discussion Papers 00-040/2, Tinbergen Institute.

    Cited by:

    1. Cizek, P., 2005. "Trimmed Likelihood-based Estimation in Binary Regression Models," Other publications TiSEM 8b789cab-97b8-451f-b37c-9, Tilburg University, School of Economics and Management.
    2. Cizek, P., 2007. "General Trimmed Estimation : Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaces DP 2007-1)," Discussion Paper 2007-65, Tilburg University, Center for Economic Research.
    3. Cizek, P., 2009. "Generalized Methods of Trimmed Moments," Other publications TiSEM 46607f30-95c0-430a-8ef9-2, Tilburg University, School of Economics and Management.
    4. Lorenzo Camponovo & Olivier Scaillet & Fabio Trojani, 2016. "Predictability Hidden by Anomalous Observations," Papers 1612.05072, arXiv.org.
    5. Croux, Christophe & Flandre, Cécile & Haesbroeck, Gentiane, 2002. "The breakdown behavior of the maximum likelihood estimator in the logistic regression model," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 377-386, December.
    6. Tino Werner, 2023. "Quantitative robustness of instance ranking problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(2), pages 335-368, April.
    7. Sally G. Arcidiacono & Damiano Rossello, 2022. "A hybrid approach to the discrepancy in financial performance’s robustness," Operational Research, Springer, vol. 22(5), pages 5441-5476, November.
    8. Cizek, P. & Aquaro, M., 2015. "Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models," Other publications TiSEM 39d0f613-007f-4d21-b1e2-b, Tilburg University, School of Economics and Management.
    9. Cizek, P., 2007. "Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models," Discussion Paper 2007-12, Tilburg University, Center for Economic Research.
    10. Aquaro, M. & Čížek, P., 2013. "One-step robust estimation of fixed-effects panel data models," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 536-548.
    11. Jaakko Nevalainen & Denis Larocque & Hannu Oja, 2007. "A weighted spatial median for clustered data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 355-379, February.
    12. Cizek, P., 2007. "Efficient Robust Estimation of Time-Series Regression Models," Discussion Paper 2007-95, Tilburg University, Center for Economic Research.
    13. Luke A. Prendergast & Robert G. Staudte, 2017. "When large n is not enough – Distribution-free interval estimators for ratios of quantiles," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 277-293, September.
    14. Čížek, Pavel, 2012. "Semiparametric robust estimation of truncated and censored regression models," Journal of Econometrics, Elsevier, vol. 168(2), pages 347-366.
    15. Alessio Farcomeni & Luca Greco, 2015. "S-estimation of hidden Markov models," Computational Statistics, Springer, vol. 30(1), pages 57-80, March.
    16. Cizek, P., 2010. "Reweighted Least Trimmed Squares : An Alternative to One-Step Estimators," Other publications TiSEM 850c8dcb-835b-4d68-ab98-6, Tilburg University, School of Economics and Management.
    17. Daniel Kosiorowski, 2015. "Two procedures for robust monitoring of probability distributions of economic data stream induced by depth functions," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 25(1), pages 55-79.
    18. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Luke A. Prendergast & Robert G. Staudte, 2017. "When large n is not enough – Distribution-free interval estimators for ratios of quantiles," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 277-293, September.
    20. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    21. Cízek, Pavel, 2011. "Semiparametrically weighted robust estimation of regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 774-788, January.
    22. Genton, Mark G. & Ruiz-Gazen, Anne, 2009. "Visualizing Influential Observations in Dependent Data," TSE Working Papers 09-051, Toulouse School of Economics (TSE).
    23. Hella, Heikki, 2003. "On robust ESACF identification of mixed ARIMA models," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2003_027, December.

  80. Lucas, André & Klaassen, Pieter & Spreij, Peter, 1999. "An analytic approach to credit risk of large corporate bond and loan portfolios," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Mohamed A. Ayadi & Hatem Ben-Ameur & Nabil Channouf & Quang Khoi Tran, 2019. "NORTA for portfolio credit risk," Annals of Operations Research, Springer, vol. 281(1), pages 99-119, October.
    2. Hsieh, Ming-Hua & Lee, Yi-Hsi & Shyu, So-De & Chiu, Yu-Fen, 2019. "Estimating multifactor portfolio credit risk: A variance reduction approach," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    3. Patrick GAGLIARDINI & Christian GOURIEROUX, 2010. "Approximate Derivative Pricing for Large Classes of Homogeneous Assets with Systematic Risk," Working Papers 2010-07, Center for Research in Economics and Statistics.
    4. Parrini, Alessandro, 2013. "Importance Sampling for Portfolio Credit Risk in Factor Copula Models," MPRA Paper 103745, University Library of Munich, Germany.
    5. Koopman, Siem Jan & Lucas, Andre & Klaassen, Pieter, 2005. "Empirical credit cycles and capital buffer formation," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3159-3179, December.
    6. Andrew G. Atkeson & Adrien d’Avernas & Andrea L. Eisfeldt & Pierre-Olivier Weill, 2019. "Government Guarantees and the Valuation of American Banks," NBER Macroeconomics Annual, University of Chicago Press, vol. 33(1), pages 81-145.
    7. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    8. M. Dietsch & C. Welter-Nicol, 2014. "Do LTV and DSTI caps make banks more resilient?," Débats Economiques et financiers 13, Banque de France.
    9. Cipollini, Andrea & Missaglia, Giuseppe, 2007. "Dynamic Factor analysis of industry sector default rates and implication for Portfolio Credit Risk Modelling," MPRA Paper 3582, University Library of Munich, Germany.
    10. Thomas Lagner & Dodozu Knyphausen‐Aufseß, 2012. "Rating Agencies as Gatekeepers to the Capital Market: Practical Implications of 40 Years of Research," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 21(3), pages 157-202, August.
    11. Diana Barro & Antonella Basso, 2008. "Credit contagion in a network of firms with spatial interaction," Working Papers 186, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    12. David Saunders & Costas Xiouros & Stavros Zenios, 2007. "Credit risk optimization using factor models," Annals of Operations Research, Springer, vol. 152(1), pages 49-77, July.
    13. Adam Gersl, 2008. "Three Indirect Effects of Foreign Direct Investment: Evidence from the Czech Republic," ACTA VSFS, University of Finance and Administration, vol. 2(1), pages 15-37.
    14. Hamerle, Alfred & Liebig, Thilo & Rösch, Daniel, 2003. "Credit Risk Factor Modeling and the Basel II IRB Approach," Discussion Paper Series 2: Banking and Financial Studies 2003,02, Deutsche Bundesbank.
    15. Siem Jan Koopman & André Lucas & Pieter Klaassen, 2002. "Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation," Tinbergen Institute Discussion Papers 02-107/2, Tinbergen Institute.
    16. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    17. Kay Giesecke & Konstantinos Spiliopoulos & Richard B. Sowers & Justin A. Sirignano, 2011. "Large Portfolio Asymptotics for Loss From Default," Papers 1109.1272, arXiv.org, revised Feb 2015.
    18. Schönbucher, Philipp J., 2000. "Factor Models for Portofolio Credit Risk," Bonn Econ Discussion Papers 16/2001, University of Bonn, Bonn Graduate School of Economics (BGSE).
    19. Lucas, Andre & Klaassen, Pieter, 2006. "Discrete versus continuous state switching models for portfolio credit risk," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 23-35, January.
    20. Paiva, Eduardo Vieira dos Santos & Savoia, José Roberto Ferreira, 2009. "Pricing corporate bonds in Brazil: 2000 to 2004," Journal of Business Research, Elsevier, vol. 62(9), pages 916-919, September.
    21. Hayette Gatfaoui, 2004. "Idiosyncratic Risk, Systematic Risk and Stochastic Volatility: An Implementation of Merton's Credit Risk Valuation," Research Paper Series 123, Quantitative Finance Research Centre, University of Technology, Sydney.
    22. André Lucas & Siem Jan Koopman, 2005. "Business and default cycles for credit risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 311-323.
    23. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    24. Samuel Hanson & M. Hashem Pesaran & Til Schuermann, 2005. "Firm Heterogeneity and Credit Risk Diversification," CESifo Working Paper Series 1531, CESifo.
    25. Giesecke, Kay & Weber, Stefan, 2004. "Cyclical correlations, credit contagion, and portfolio losses," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 3009-3036, December.
    26. Bandyopadhyay, Arindam, 2010. "Understanding the Effect of Concentration Risk in the Banks’ Credit Portfolio: Indian Cases," MPRA Paper 24822, University Library of Munich, Germany.
    27. Albanese, Claudio & Vidler, Alicia, 2007. "A STRUCTURAL MODEL FOR CREDIT-EQUITY DERIVATIVES AND BESPOKE CDOs," MPRA Paper 5227, University Library of Munich, Germany, revised 09 Sep 2007.
    28. Li, Ping & Han, Yingwei & Xia, Yong, 2016. "Portfolio optimization using asymmetry robust mean absolute deviation model," Finance Research Letters, Elsevier, vol. 18(C), pages 353-362.
    29. Konstantinos Spiliopoulos, 2014. "Systemic Risk and Default Clustering for Large Financial Systems," Papers 1402.5352, arXiv.org, revised Feb 2015.
    30. Filip Novotný, 2008. "The Exchange Rate Adjustment Role in Imperfect Competition: the Case of the Czech Republic," ACTA VSFS, University of Finance and Administration, vol. 2(1), pages 38-55.
    31. Dietsch, Michel & Petey, Joël, 2015. "The credit-risk implications of home ownership promotion: The effects of public subsidies and adjustable-rate loans," Journal of Housing Economics, Elsevier, vol. 28(C), pages 103-120.
    32. André Lucas & Pieter Klaassen & Peter Spreij & Stefan Straetmans, 2001. "Tail Behavior of Credit Loss Distributions for General Latent Factor Models," Tinbergen Institute Discussion Papers 01-023/2, Tinbergen Institute.
    33. Dirk Tasche, 2005. "Measuring sectoral diversification in an asymptotic multi-factor framework," Papers physics/0505142, arXiv.org, revised Jul 2006.
    34. Giesecke, Kay & Weber, Stefan, 2006. "Credit contagion and aggregate losses," Journal of Economic Dynamics and Control, Elsevier, vol. 30(5), pages 741-767, May.
    35. Tang, Qihe & Tong, Zhiwei & Yang, Yang, 2021. "Large portfolio losses in a turbulent market," European Journal of Operational Research, Elsevier, vol. 292(2), pages 755-769.
    36. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    37. Jacques Pézier, 2011. "Rationalization of Investment Preference Criteria," ICMA Centre Discussion Papers in Finance icma-dp2011-12, Henley Business School, University of Reading.
    38. Straetmans, Stefan, 2000. "Extremal spillovers in financial markets," Serie Research Memoranda 0013, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    39. Gagliardini, P. & Gourieroux, C., 2005. "Migration correlation: Definition and efficient estimation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 865-894, April.
    40. Andre Lucas & Bastiaan Verhoef, 2012. "Aggregating Credit and Market Risk: The Impact of Model Specification," Tinbergen Institute Discussion Papers 12-057/2/DSF36, Tinbergen Institute.
    41. Albanese, Claudio & Vidler, Alicia, 2008. "Dynamic Conditioning and Credit Correlation Baskets," MPRA Paper 8368, University Library of Munich, Germany, revised 21 Apr 2008.
    42. Carling, Kenneth & Rönnegård, Lars & Roszbach, Kasper, 2004. "Is Firm Interdependence within Industries Important for Portfolio Credit Risk?," Working Paper Series 168, Sveriges Riksbank (Central Bank of Sweden).
    43. Ulrich Kaiser & Andrea Szczesny, 2003. "Ökonometrische Verfahren zur Modellierung von Kreditausfallwahrscheinlichkeiten: Logit- und Probit-Modelle," Schmalenbach Journal of Business Research, Springer, vol. 55(8), pages 790-822, December.
    44. Lucas, André & Straetmans, Stefan & Klaassen, Pieter, 1999. "Tail behavior of credit loss distributions," Serie Research Memoranda 0060, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    45. Konstantinos Spiliopoulos & Jia Yang, 2018. "Network effects in default clustering for large systems," Papers 1812.07645, arXiv.org, revised Feb 2020.
    46. Cowan, Adrian M. & Cowan, Charles D., 2004. "Default correlation: An empirical investigation of a subprime lender," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 753-771, April.
    47. Gunter Loffler, 2004. "Implied asset value distributions," Applied Financial Economics, Taylor & Francis Journals, vol. 14(12), pages 875-883.
    48. Astrid Van Landschoot, 2004. "The Determinants of Credit Spreads," Financial Stability Review, National Bank of Belgium, vol. 2(1), pages 135-155, June.
    49. Y. Malevergne & D. Sornette, 2002. "Tail Dependence of Factor Models," Papers cond-mat/0202356, arXiv.org.
    50. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    51. Roman Horvath, 2008. "Monetary Policy Stance and Future Inflation: The Case of Czech Republic," ACTA VSFS, University of Finance and Administration, vol. 2(1), pages 80-106.
    52. Albrecht, Peter, 2005. "Kreditrisiken - Modellierung und Management: Ein Überblick," German Risk and Insurance Review (GRIR), University of Cologne, Department of Risk Management and Insurance, vol. 1(2), pages 22-152.
    53. Tang, Qihe & Tang, Zhaofeng & Yang, Yang, 2019. "Sharp asymptotics for large portfolio losses under extreme risks," European Journal of Operational Research, Elsevier, vol. 276(2), pages 710-722.
    54. Michel Dietsch & Henri Fraisse & Mathias Lé & Sandrine Lecarpentier, 2019. "Lower bank capital requirements as a policy tool to support credit to SMEs: evidence from a policy experiment," EconomiX Working Papers 2019-12, University of Paris Nanterre, EconomiX.
    55. Petr Jakubik, 2008. "Credit risk and stress testing of the Czech Banking Sector," ACTA VSFS, University of Finance and Administration, vol. 2(1), pages 107-123.
    56. Diana Barro & Antonella Basso, 2006. "A credit contagion model for loan portfolios in a network of firms with spatial interaction," Working Papers 143, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    57. Andreas Mühlbacher & Thomas Guhr, 2018. "Extreme Portfolio Loss Correlations in Credit Risk," Risks, MDPI, vol. 6(3), pages 1-25, July.
    58. Robert P. Gray & Frank L. Clarke, 2004. "A Methodology for Calculating the Allowance for Loan Losses in Commercial Banks," Abacus, Accounting Foundation, University of Sydney, vol. 40(3), pages 321-341, October.
    59. David Prusvic, 2008. "Interaction between Monetary and Fiscal Policy in a Small Open Economy with Autonomous Monetary Policy and Fiscal Policy Rule," ACTA VSFS, University of Finance and Administration, vol. 2(1), pages 56-79.

  81. Nick Taylor & Dick van Dijk & Philip Hans Franses & André Lucas, 1999. "SETS, Arbitrage Activity, and Stock Price Dynamics," Tinbergen Institute Discussion Papers 99-003/4, Tinbergen Institute.

    Cited by:

    1. Chelley-Steeley, Patricia L., 2008. "Market quality changes in the London Stock Market," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2248-2253, October.
    2. Yiuman Tse & Paramita Bandyopadhyay & Yang‐Pin Shen, 2006. "Intraday Price Discovery in the DJIA Index Markets," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1572-1585, November.
    3. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    4. Canto, Bea & Kräussl, Roman, 2007. "Electronic trading systems and intraday non-linear dynamics: An examination of the FTSE 100 cash and futures returns," CFS Working Paper Series 2007/20, Center for Financial Studies (CFS).
    5. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    6. Assaf, Ata, 2006. "The stochastic volatility in mean model and automation: Evidence from TSE," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(2), pages 241-253, May.
    7. Jürgen Gaul & Erik Theissen, 2015. "A Partially Linear Approach to Modeling the Dynamics of Spot and Futures Prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 371-384, April.
    8. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, Enero-Abr.
    9. Tse, Yiuman & Xiang, Ju, 2005. "Market quality and price discovery: Introduction of the E-mini energy futures," Global Finance Journal, Elsevier, vol. 16(2), pages 164-179, December.
    10. Angelidis, Timotheos & Andrikopoulos, Andreas, 2010. "Idiosyncratic risk, returns and liquidity in the London Stock Exchange: A spillover approach," International Review of Financial Analysis, Elsevier, vol. 19(3), pages 214-221, June.
    11. Wanbing Zhang & Sisi Zhang & Peibiao Zhao, 2019. "On Double Value at Risk," Risks, MDPI, vol. 7(1), pages 1-22, March.
    12. Patricia Chelley-Steeley & Antonios Siganos, 2005. "Momentum Profits in Alternative Stock Market Structures," Money Macro and Finance (MMF) Research Group Conference 2005 63, Money Macro and Finance Research Group.
    13. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    14. Garrett Ian & Taylor Nicholas, 2001. "Intraday and Interday Basis Dynamics: Evidence from the FTSE 100 Index Futures Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(2), pages 1-22, July.
    15. Lekkos, Ilias & Milas, Costas, 2004. "Time-varying excess returns on UK government bonds: A non-linear approach," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 45-62, January.
    16. Joseph K.W. Fung & Philip Yu, 2007. "Order Imbalance and the Dynamics of Index and Futures Prices," Working Papers 072007, Hong Kong Institute for Monetary Research.
    17. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    18. Robles-Fernandez M. Dolores & Nieto Luisa & Fernandez M. Angeles, 2004. "Nonlinear Intraday Dynamics in Eurostoxx50 Index Markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-28, December.
    19. Juan A. Lafuente & Manuel Illueca Muñoz, 2003. "The Effect Of Futures Trading Activity On The Distribution Of Spot Market Returns," Working Papers. Serie EC 2003-23, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    20. Yiu‐Kuen Tse & Wai‐Sum Chan, 2010. "The Lead–Lag Relation Between The S&P500 Spot And Futures Markets: An Intraday‐Data Analysis Using A Threshold Regression Model," The Japanese Economic Review, Japanese Economic Association, vol. 61(1), pages 133-144, March.
    21. Nicholas Taylor, 2004. "A New Econometric Model Of Index Arbitrage," Royal Economic Society Annual Conference 2004 69, Royal Economic Society.
    22. Ivan Paya & David A. Peel, 2011. "Systematic sampling of nonlinear models: Evidence on speed of adjustment in index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 192-203, February.
    23. Charlie X. Cai & Robert Hudson & Kevin Keasey, 2004. "Intra Day Bid‐Ask Spreads, Trading Volume and Volatility: Recent Empirical Evidence from the London Stock Exchange," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 647-676, June.
    24. Christopher L. Gilbert & Herbert A. Rijken, 2006. "How is Futures Trading Affected by the Move to a Computerized Trading System? Lessons from the LIFFE FTSE 100 Contract," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(7‐8), pages 1267-1297, September.
    25. Chen, Shiyi & Chng, Michael T. & Liu, Qingfu, 2021. "The implied arbitrage mechanism in financial markets," Journal of Econometrics, Elsevier, vol. 222(1), pages 468-483.
    26. Stephen Norman, 2009. "Testing for a unit root against ESTAR nonlinearity with a delay parameter greater than one," Economics Bulletin, AccessEcon, vol. 29(3), pages 2152-2173.

  82. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.

    Cited by:

    1. Krauss, Christopher & Herrmann, Klaus & Teis, Stefan, 2015. "On the power and size properties of cointegration tests in the light of high-frequency stylized facts," FAU Discussion Papers in Economics 11/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    2. Martin Wagner, 2004. "A Comparison of Johansen's, Bierens’ and the Subspace Algorithm Method for Cointegration Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 399-424, July.
    3. Giulio Cifarelli & Giovanna Paladino, 2008. "Reserve overstocking in a highly integrated world. New evidence from Asia and Latin America," The European Journal of Finance, Taylor & Francis Journals, vol. 14(4), pages 315-336.
    4. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. David O. Cushman, 2003. "Further evidence on the size and power of the Bierens and Johansen cointegration procedures," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.
    6. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.

  83. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. David O. Cushman, 2003. "Further evidence on the size and power of the Bierens and Johansen cointegration procedures," Economics Bulletin, AccessEcon, vol. 3(25), pages 1-7.

  84. Patrick A. Groenendijk & André Lucas & Casper G. de Vries, 1998. "A Hybrid Joint Moment Ratio Test for Financial Time Series," Tinbergen Institute Discussion Papers 98-104/2, Tinbergen Institute.

    Cited by:

    1. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    2. T. Di Matteo & T. Aste & M. M. Dacorogna, 2003. "Using the Scaling Analysis to Characterize Financial Markets," Papers cond-mat/0302434, arXiv.org.
    3. Faheem Aslam & Paulo Ferreira & Haider Ali & Sumera Kauser, 2022. "Herding behavior during the Covid-19 pandemic: a comparison between Asian and European stock markets based on intraday multifractality," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(2), pages 333-359, June.
    4. T. Di Matteo & T. Aste & Michel M. Dacorogna, 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Econometrics 0503004, University Library of Munich, Germany.
    5. Danielsson, Jon & Zigrand, Jean-Pierre, 2006. "On time-scaling of risk and the square-root-of-time rule," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2701-2713, October.
    6. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    7. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    8. T. Di Matteo, 2007. "Multi-scaling in finance," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 21-36.

  85. Lucas, André, 1998. "Testing backtesting : an evaluation of the Basle guidelines for backtesting internal risk management models of banks," Serie Research Memoranda 0001, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Flavio Bazzana, 2001. "I modelli interni per la valutazione del rischio di mercato secondo l'approccio del Value at Risk," Alea Tech Reports 011, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
    2. Jeremy Berkowitz, 1999. "Evaluating the forecasts of risk models," Finance and Economics Discussion Series 1999-11, Board of Governors of the Federal Reserve System (U.S.).

  86. Philip Hans Franses & Dick van Dijk & André Lucas, 1998. "Short Patches of Outliers, ARCH and Volatility Modeling," Tinbergen Institute Discussion Papers 98-057/4, Tinbergen Institute.

    Cited by:

    1. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Par Sjolander, 2009. "Are the Basel II requirements justified in the presence of structural breaks?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(12), pages 985-998.
    3. Lanne, Markku & Saikkonen, Pentti, 2007. "A Multivariate Generalized Orthogonal Factor GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 61-75, January.
    4. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, Enero-Abr.
    5. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    6. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, Enero-Abr.
    7. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    8. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Miralles-Quirós, José Luis & Daza-Izquierdo, Julio, 2015. "Do DOW returns really influence the intraday Spanish stock market behavior?," Research in International Business and Finance, Elsevier, vol. 33(C), pages 99-126.
    10. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    11. Juncal Cunado Eizaguirre & Javier Gomez Biscarri & Fernando Perez de Gracia Hidalgo, 2009. "Financial liberalization, stock market volatility and outliers in emerging economies," Applied Financial Economics, Taylor & Francis Journals, vol. 19(10), pages 809-823.
    12. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    13. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    14. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    15. Amado Peir, 2016. "Changes in the Unconditional Variance and Autoregressive Conditional Heteroscedasticity," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1338-1343.
    16. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
    17. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    18. Par Sjolander, 2010. "A stationary unbiased finite sample ARCH-LM test procedure," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 1019-1033.
    19. Jose Luis Miralles-Marcelo & Jose Luis Miralles-Quiros & Maria del Mar Miralles-Quiros, 2010. "Intraday linkages between the Spanish and the US stock markets: evidence of an overreaction effect," Applied Economics, Taylor & Francis Journals, vol. 42(2), pages 223-235.

  87. Lucas, André, 1997. "A note on optimal estimation from a risk management perspective under possibly mis-specified tail behavior," Serie Research Memoranda 0056, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    2. Nikola Radivojevic & Milena Cvjetkovic & Saša Stepanov, 2016. "The new hybrid value at risk approach based on the extreme value theory," Estudios de Economia, University of Chile, Department of Economics, vol. 43(1 Year 20), pages 29-52, June.
    3. Alejandro Bernales & Diether W. Beuermann & Gonzalo Cortazar, 2014. "Thinly traded securities and risk management," Estudios de Economia, University of Chile, Department of Economics, vol. 41(1 Year 20), pages 5-48, June.
    4. Cortazar, Gonzalo & Beuermann, Diether & Bernales, Alejandro, 2013. "Risk Management with Thinly Traded Securities: Methodology and Implementation," IDB Publications (Working Papers) 4647, Inter-American Development Bank.

  88. Boswijk, H. Peter & Lucas, André, 1997. "Semi-nonparametric cointegration testing," Serie Research Memoranda 0041, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Ted Juhl & Zhijie Xiao, 2000. "N-Consistent Semiparametric Regression: Partially Linear Models with Unit Roots," Econometric Society World Congress 2000 Contributed Papers 1532, Econometric Society.
    2. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    3. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    5. H. Peter Boswijk & Jurgen A. Doornik, 1999. "Distribution Approximations for Cointegration Tests with Stationary Exogenous Regressors," Tinbergen Institute Discussion Papers 99-013/4, Tinbergen Institute.
    6. Al-Sadoon, Majid M., 2017. "A unifying theory of tests of rank," Journal of Econometrics, Elsevier, vol. 199(1), pages 49-62.
    7. H. Peter Boswijk, 2000. "Testing for a Unit Root with Near-Integrated Volatility," Econometric Society World Congress 2000 Contributed Papers 1101, Econometric Society.
    8. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Bo Zhou, 2023. "Semiparametrically Optimal Cointegration Test," Papers 2305.08880, arXiv.org.
    10. H. Peter Boswijk & Franc Klaassen, 2005. "Why Frequency Matters for Unit Root Testing," Tinbergen Institute Discussion Papers 04-119/4, Tinbergen Institute.
    11. Nikolaus A. Siegfried, 2002. "An information-theoretic extension to structural VAR modelling," Econometrics 0203005, University Library of Munich, Germany.
    12. Juhl, Ted & Xiao, Zhijie, 2005. "Testing for cointegration using partially linear models," Journal of Econometrics, Elsevier, vol. 124(2), pages 363-394, February.
    13. Zhou, Bo, 2024. "Semiparametrically optimal cointegration test," Journal of Econometrics, Elsevier, vol. 242(2).

  89. Groenendijk, Patrick A. & Lucas, André & Vries, Casper G. de, 1997. "Stochastic processes, non-normal innovations, and the use of scaling ratios," Serie Research Memoranda 0058, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Dacorogna, Michel & Elbahtouri, Laila & Kratz, Marie, 2015. "Explicit diversifiction benefit for dependent risks," ESSEC Working Papers WP1522, ESSEC Research Center, ESSEC Business School.
    2. Patrick A. Groenendijk & André Lucas & Casper G. de Vries, 1998. "A Hybrid Joint Moment Ratio Test for Financial Time Series," Tinbergen Institute Discussion Papers 98-104/2, Tinbergen Institute.

  90. Lucas, André, 1997. "Strategic and tactical asset allocation and the effect of long-run equilibrium relations," Serie Research Memoranda 0042, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Erie Febrian & Aldrin Herwany, 2010. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Business, Management and Finance 201005, Department of Management and Business, Padjadjaran University, revised May 2010.
    2. Bruno Breyer Caldas & João Frois Caldeira & Guilherme Vale Moura, 2016. "Is Pairs Trading Performance Sensitive To The Methodologies?: A Comparison," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 130, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. João Frois Caldeira & Marcelo Savino Portugal, 2010. "Long-Short Market Neutral and Index Tracking Strategies Based on Cointegrated Portfolios," Brazilian Review of Finance, Brazilian Society of Finance, vol. 8(4), pages 469-504.
    4. Marcel Aloy & Mohamed Boutahar & Karine Gente & Anne P駵in-Feissolle, 2013. "Long-run relationships between international stock prices: further evidence from fractional cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 45(7), pages 817-828, March.
    5. João Frois Caldeira & Gulherme Valle Moura, 2013. "Selection of a Portfolio of Pairs Based on Cointegration: A Statistical Arbitrage Strategy," Brazilian Review of Finance, Brazilian Society of Finance, vol. 11(1), pages 49-80.
    6. Aldrin Herwany & Erie Febrian, 2010. "Co-integration and Causality Analysis on Developed Asian Markets For Risk Management & Portfolio Selection," Working Papers in Business, Management and Finance 201001, Department of Management and Business, Padjadjaran University, revised Jan 2010.
    7. Aldrin Herwany & Erie Febrian, 2013. "Global Stock Price Linkages Around The Us Financial Crisis: Evidence From Indonesia," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 7(5), pages 35-45.
    8. Zhijie Xiao, 2009. "Quantile Cointegrating Regression," Boston College Working Papers in Economics 708, Boston College Department of Economics.
    9. Febrian, Erie & Herwany, Aldrin, 2007. "Co-integration and Causality Among Jakarta Stock Exchange, Singapore Stock Exchange, and Kuala Lumpur Stock Exchange," MPRA Paper 9632, University Library of Munich, Germany.
    10. Sant’Anna, Leonardo R. & Filomena, Tiago P. & Caldeira, João F., 2017. "Index tracking and enhanced indexing using cointegration and correlation with endogenous portfolio selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 146-157.
    11. Krishna M. Kasibhatla & David Stewart & Swapan Sen & John Malindretos, 2006. "Are Daily Stock Price Indices in the Major European Equity Markets Cointegrated? Tests and Evidence," The American Economist, Sage Publications, vol. 50(2), pages 47-57, October.
    12. Roland Füss & Felix Schindler, 2011. "Diversifikationsvorteile verbriefter Immobilienanlagen in einem Mixed‐Asset‐Portfolio," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 12(2), pages 170-191, May.

  91. Franses, Philip Hans & Lucas, André, 1997. "Outlier robust cointegration analysis," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

    Cited by:

    1. Arranz, Miguel A. & Escribano, Álvaro, 1998. "Detrending procedures and cointegration testing: ECM tests under structural breaks," DES - Working Papers. Statistics and Econometrics. WS 4551, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Miguel Arranz & Alvaro Escribano, 2004. "Outliers - robust ECM cointegration tests based on the trend components," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(4), pages 243-266, December.
    3. Aparicio, Felipe M. & Escribano, Álvaro & García, Ana, 2004. "A range unit root test," DES - Working Papers. Statistics and Econometrics. WS ws041104, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Lucas, André, 1997. "A note on optimal estimation from a risk management perspective under possibly mis-specified tail behavior," Serie Research Memoranda 0056, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. Colombier, Carsten, 2012. "Healthcare expenditure projections up to 2060," MPRA Paper 104919, University Library of Munich, Germany.

  92. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for ARCH in the Presence of Additive Outliers," Econometric Institute Research Papers EI 9659-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. E. Ruiz & M.A. Carnero & D. Pereira, 2004. "Effects of Level Outliers on the Identification and Estimation of GARCH Models," Econometric Society 2004 Australasian Meetings 21, Econometric Society.
    2. Daiki Maki, 2015. "Wild bootstrap tests for unit root in ESTAR models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 475-490, September.
    3. Jinliang Li & Chihwa Kao & Wei David Zhang, 2010. "Bounded influence estimator for GARCH models: evidence from foreign exchange rates," Applied Economics, Taylor & Francis Journals, vol. 42(11), pages 1437-1445.
    4. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2008. "Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 109, Economics, The University of Manchester.
    5. WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working papers 2012-11, University of Connecticut, Department of Economics.
    6. Jurgen A. Doornik & Marius Ooms, 2003. "Multimodality in the GARCH Regression Model," Economics Papers 2003-W20, Economics Group, Nuffield College, University of Oxford.
    7. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    8. Daiki Maki & Yasushi Ota, 2021. "Testing for Time-Varying Properties Under Misspecified Conditional Mean and Variance," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1167-1182, April.
    9. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Maki, Daiki, 2015. "Wild bootstrap testing for cointegration in an ESTAR error correction model," Economic Modelling, Elsevier, vol. 47(C), pages 292-298.
    11. Dejan Živkov & Jovan Njegić & Mirela Momčilović & Ivan Milenković, 2016. "Exchange Rate Volatility and Uncovered Interest Rate Parity in the European Emerging Economies," Prague Economic Papers, Prague University of Economics and Business, vol. 2016(3), pages 253-270.
    12. Burkhard Raunig, 2003. "Testing for Longer Horizon Predictability of Return Volatility with an Application to the German," Working Papers 86, Oesterreichische Nationalbank (Austrian Central Bank).
    13. Lumsdaine, Robin L. & Ng, Serena, 1999. "Testing for ARCH in the presence of a possibly misspecified conditional mean," Journal of Econometrics, Elsevier, vol. 93(2), pages 257-279, December.
    14. Grané Chávez, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Martha Cecilia García & Aura Mar�a Jalal & Luis Alfonso Garz�n & Jorge Mario L�pez, 2013. "Métodos para predecir índices Bursátiles," Revista Ecos de Economía, Universidad EAFIT.
    17. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    18. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2008. "Estimating and Forecasting GARCH Volatility in the Presence of Outiers," Working Papers. Serie AD 2008-13, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    19. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    20. Daiki Maki & Yasushi Ota, 2019. "Testing for time-varying properties under misspecified conditional mean and variance," Papers 1907.12107, arXiv.org, revised Aug 2019.
    21. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March.
    22. Francesco Battaglia & Lia Orfei, 2005. "Outlier Detection And Estimation In NonLinear Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 107-121, January.
    23. Daiki Maki & Yasushi Ota, 2019. "Robust tests for ARCH in the presence of the misspecified conditional mean: A comparison of nonparametric approches," Papers 1907.12752, arXiv.org, revised Sep 2019.
    24. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
    25. Lei Shi & Md. Mostafizur Rahman & Wen Gan & Jianhua Zhao, 2015. "Stepwise local influence in generalized autoregressive conditional heteroskedasticity models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 428-444, February.
    26. Franses, Ph.H.B.F. & van Dijk, D.J.C., 1997. "Do We Often Find ARCH Because Of Neglected Outliers?," Econometric Institute Research Papers EI 9706-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    27. Marcelo Cunha Medeiros & Alvaro Veiga, 2004. "Modelling multiple regimes in financial volatility with a flexible coefficient GARCH model," Textos para discussão 486, Department of Economics PUC-Rio (Brazil).
    28. Fokianos, Konstantions & Fried, Roland, 2009. "Interventions in ingarch processes," Technical Reports 2009,11, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    29. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, Enero-Abr.
    30. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    31. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    32. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, Enero-Abr.
    33. Charles, Amélie & Darné, Olivier & Pop, Adrian, 2015. "Risk and ethical investment: Empirical evidence from Dow Jones Islamic indexes," Research in International Business and Finance, Elsevier, vol. 35(C), pages 33-56.
    34. Paulo M. M. Rodrigues & Antonio Rubia, 2011. "The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(4), pages 449-468, August.
    35. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    36. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    37. WenShwo Fang & Stephen M. Miller, 2008. "Modeling the Volatility of Real GDP Growth: The Case of Japan Revisited," Working papers 2008-47, University of Connecticut, Department of Economics.
    38. Cizek, P., 2007. "Efficient Robust Estimation of Regression Models (Revision of DP 2006-08)," Other publications TiSEM e88ea267-ce68-4569-98c3-7, Tilburg University, School of Economics and Management.
    39. Cizek, P., 2007. "Efficient Robust Estimation of Time-Series Regression Models," Discussion Paper 2007-95, Tilburg University, Center for Economic Research.
    40. Amélie Charles & Olivier Darné, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Post-Print hal-01122507, HAL.
    41. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    42. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    43. Vanessa Berenguer Rico & Ines Wilms, 2018. "White heteroscedasticty testing after outlier removal," Economics Series Working Papers 853, University of Oxford, Department of Economics.
    44. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.
    45. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    46. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    47. Bali, Rakesh & Guirguis, Hany, 2007. "Extreme observations and non-normality in ARCH and GARCH," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 332-346.
    48. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    49. Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
    50. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    51. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    52. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    53. Xibin Zhang & Maxwell L. King, 2002. "Influence Diagnostics in GARCH Processes," Monash Econometrics and Business Statistics Working Papers 19/02, Monash University, Department of Econometrics and Business Statistics.
    54. Grané Chávez, Aurea & Veiga, Helena, 2009. "Wavelet-based detection of outliers in volatility models," DES - Working Papers. Statistics and Econometrics. WS ws090403, Universidad Carlos III de Madrid. Departamento de Estadística.
    55. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    56. Dilip M. Nachane, 2011. "Selected Problems in the Analysis of Nonstationary & Nonlinear Time Series," Journal of Quantitative Economics, The Indian Econometric Society, vol. 9(1), pages 1-17.
    57. Yaqoob, Tanzeela & Maqsood, Arfa, 2024. "The potency of time series outliers in volatile models: An empirical analysis of fintech, and mineral resources," Resources Policy, Elsevier, vol. 89(C).
    58. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    59. Vasiliki Chatzikonstanti & Michail Karoglou, 2022. "Can black swans be tamed with a flexible mean‐variance specification?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3202-3227, July.
    60. Cízek, Pavel, 2011. "Semiparametrically weighted robust estimation of regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 774-788, January.
    61. Duchesne, Pierre, 2004. "On robust testing for conditional heteroscedasticity in time series models," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 227-256, June.
    62. Amélie Charles, 2008. "Forecasting volatility with outliers in GARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 551-565.
    63. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
    64. Li, Yushu & Shukur, Ghazi, 2009. "Testing for Unit Root against LSTAR Model: Wavelet Improvement under GARCH Distortion," CAFO Working Papers 2009:6, Linnaeus University, Centre for Labour Market Policy Research (CAFO), School of Business and Economics.
    65. Battaglia, Francesco, 2005. "Outliers in functional autoregressive time series," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 323-332, May.
    66. You‐How Go & Jia‐Jun Teo & Kam Fong Chan, 2023. "The effectiveness of crude oil futures hedging during infectious disease outbreaks in the 21st century," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1559-1575, November.
    67. Grané Chávez, Aurea & Martín-Barragán, Belén & Veiga, Helena, 2014. "Outliers in multivariate Garch models," DES - Working Papers. Statistics and Econometrics. WS ws140503, Universidad Carlos III de Madrid. Departamento de Estadística.
    68. Anatolyev, Stanislav & Tarasyuk, Irina, 2015. "Missing mean does no harm to volatility!," Economics Letters, Elsevier, vol. 134(C), pages 62-64.
    69. Xibin Zhang, 2004. "Assessment of Local Influence in GARCH Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 301-313, March.
    70. Bhaumik, S. & Karanasos, M. & Kartsaklas, A., 2016. "The informative role of trading volume in an expanding spot and futures market," Journal of Multinational Financial Management, Elsevier, vol. 35(C), pages 24-40.

  93. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Econometric Institute Research Papers EI 9622-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2018. "Oil Prices and GCC Stock Markets: New Evidence from Smooth Transition Models," CESifo Working Paper Series 7072, CESifo.
    2. Daiki Maki, 2015. "Wild bootstrap tests for unit root in ESTAR models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 475-490, September.
    3. Chan Wai-Sum & Hung King-Chi, 2011. "On Robust Testing and Modelling of Threshold-Type Non-Linearity in ASEAN Foreign Exchange Markets," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 5(2), pages 1-16, July.
    4. Shelley, Gary L. & Wallace, Frederick H., 2011. "Further evidence regarding nonlinear trend reversion of real GDP and the CPI," Economics Letters, Elsevier, vol. 112(1), pages 56-59, July.
    5. Daiki Maki & Yasushi Ota, 2021. "Testing for Time-Varying Properties Under Misspecified Conditional Mean and Variance," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1167-1182, April.
    6. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    7. Maki, Daiki, 2015. "Wild bootstrap testing for cointegration in an ESTAR error correction model," Economic Modelling, Elsevier, vol. 47(C), pages 292-298.
    8. Ben Cheikh, Nidhaleddine & Ben Naceur, Sami & Kanaan, Oussama & Rault, Christophe, 2020. "Investigating the Asymmetric Impact of Oil Prices on GCC Stock Markets," IZA Discussion Papers 13853, Institute of Labor Economics (IZA).
    9. Brannolte Cord & Kim Jeong-Ryeol & Hansen Gerd, 1999. "Nonlinear Error Correction Modeling in German Interest Rates / Ein nichtlineares Fehlerkorrekturmodell für die deutsche Zinsstruktur," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 219(3-4), pages 271-283, June.
    10. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    11. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    12. Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
    13. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    14. Otero, Jesus & Smith, Jeremy, 2003. "The KPSS test with outliers," Economic Research Papers 269574, University of Warwick - Department of Economics.
    15. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    16. Franchi, Massimo & Ordóñez, Javier, 2011. "Multiple equilibria in Spanish unemployment," Structural Change and Economic Dynamics, Elsevier, vol. 22(1), pages 71-80, February.
    17. M Sensier & D R Osborn & N Öcal, 2002. "Asymmetric Interest Rate Effects for the UK Real Economy," Centre for Growth and Business Cycle Research Discussion Paper Series 10, Economics, The University of Manchester.
    18. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
    19. Hirsch, Tristan & Rinke, Saskia, 2017. "Changes in Persistence in Outlier Contaminated Time Series," Hannover Economic Papers (HEP) dp-583, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    20. Daiki Maki & Yasushi Ota, 2019. "Testing for time-varying properties under misspecified conditional mean and variance," Papers 1907.12107, arXiv.org, revised Aug 2019.
    21. Arghyrou, Michael G & Gregoriou, Andros & Kontonikas, Alexandros, 2007. "Do real interest rates converge? Evidence from the European Union," Cardiff Economics Working Papers E2007/26, Cardiff University, Cardiff Business School, Economics Section.
    22. Rinke, Saskia, 2016. "The Influence of Additive Outliers on the Performance of Information Criteria to Detect Nonlinearity," Hannover Economic Papers (HEP) dp-575, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    23. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    24. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    25. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    26. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for ARCH in the Presence of Additive Outliers," Econometric Institute Research Papers EI 9659-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    27. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, Enero-Abr.
    28. Dick van Dijk & Philip Hans Franses, 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 727-744, December.
    29. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.
    30. NIDHALEDDINE BEN CHEIKH & SAMI BEN NACEUR & OUSSAMA KANAAN & Christophe RAULT, 2019. "Oil Prices and GCC Stock Markets: New Evidence from Vector Smooth Transition Models," LEO Working Papers / DR LEO 2697, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    31. López Villavicencio, Antonia, 2008. "Nonlinearities or outliers in real exchange rates?," Economic Modelling, Elsevier, vol. 25(4), pages 714-730, July.
    32. Fok, D. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2003. "A multi-level panel smooth transition autoregression for US sectoral production," Econometric Institute Research Papers EI 2003-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    33. Hafsa Hina & Abdul Qayyum, 2015. "Re-estimation of Keynesian Model by Considering Critical Events and Multiple Cointegrating Vectors," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 54(2), pages 123-145.
    34. Hina, Hafsa & Qayyum, Abdul, 2013. "Estimation of Keynesian Exchange Rate Model of Pakistan by Considering Critical Events and Multiple Cointegrating Vectors," MPRA Paper 52611, University Library of Munich, Germany.
    35. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    36. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Nonlinear Error-Correction Models for Interest Rates in The Netherlands," Econometric Institute Research Papers EI 9704-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    37. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    38. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    39. Mohamed Ali Houfi & Ghassen El Montasser, 2010. "Effets des points aberrants sur les tests de normalité et de linéarité. Applications à la bourse de Tokyo," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(36), pages 15-51, June.
    40. Yamin Ahmad & Stuart Glosser, 2007. "Searching for Nonlinearities in Real Exchange Rates?," Working Papers 09-01, UW-Whitewater, Department of Economics, revised Jan 2009.
    41. King Chi Hung & Siu Hung Cheung & Wai-Sum Chan & Li-Xin Zhang, 2009. "On a robust test for SETAR-type nonlinearity in time series analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 445-464.
    42. Matas-Mir, Antonio & Osborn, Denise R., 2004. "Does seasonality change over the business cycle? An investigation using monthly industrial production series," European Economic Review, Elsevier, vol. 48(6), pages 1309-1332, December.
    43. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    44. González-Sánchez, Mariano, 2021. "Is there a relationship between the time scaling property of asset returns and the outliers? Evidence from international financial markets," Finance Research Letters, Elsevier, vol. 38(C).
    45. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2006. "Não Linearidade Nos Ciclos De Negócios: Modelo Auto-Regressivo “Smooth Transition” Para O Índice Geral De Produção Industrial Brasileiro E Bens De Capital," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 10, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    46. Arghyrou, Michael G. & Gregoriou, Andros, 2008. "Non-linearity versus non-normality in real exchange rate dynamics," Economics Letters, Elsevier, vol. 100(2), pages 200-203, August.
    47. Mendoza Lugo, Omar & Pedauga, Luis Enrique, 2006. "Efecto transferencia (pass-through) del tipo de cambio en los precios de bienes y servicios en Venezuela [Exchange rate pass-through on prices of goods and services in Venezuela]," MPRA Paper 14874, University Library of Munich, Germany.
    48. Zhou, Jian, 2016. "A high-frequency analysis of the interactions between REIT return and volatility," Economic Modelling, Elsevier, vol. 56(C), pages 102-108.
    49. Arghyrou, Michael G. & Gregoriou, Andros, 2007. "Testing for Purchasing Power Parity correcting for non-normality using the wild bootstrap," Economics Letters, Elsevier, vol. 95(2), pages 285-290, May.
    50. Heravi, Saeed & Osborn, Denise R. & Birchenhall, C. R., 2004. "Linear versus neural network forecasts for European industrial production series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 435-446.
    51. Paolo Giordani, 2006. "A cautionary note on outlier robust estimation of threshold models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 37-47.
    52. Samira Haddou, 2011. "Is Tunisian Real Effective Exchange Rate Mean Reverting? Evidence from Nonlinear Models," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 18(1), pages 164-178, September.
    53. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.
    54. Escribano, A. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 1998. "Nonlinearities and outliers: robust specification of STAR models," Econometric Institute Research Papers EI 9832, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    55. Hina, Hafsa & Qayyum, Abdul, 2015. "Exchange Rate Determination and Out of Sample Forecasting: Cointegration Analysis," MPRA Paper 61997, University Library of Munich, Germany.
    56. Jawadi, Fredj & Namouri, Hela & Ftiti, Zied, 2018. "An analysis of the effect of investor sentiment in a heterogeneous switching transition model for G7 stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 469-484.
    57. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.

  94. Franses, Ph.H.B.F. & Kloek, T. & Lucas, A., 1996. "Outlier Robust Analysis of Market Share and Distribution Relations for Weekly Scanning Data," Econometric Institute Research Papers EI 9646-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.

Articles

  1. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.

    Cited by:

    1. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.

  2. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).

    Cited by:

    1. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
    2. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
    3. Li, Haiqi & Zhou, Jin & Hong, Yongmiao, 2024. "Estimating and testing for smooth structural changes in moment condition models," Journal of Econometrics, Elsevier, vol. 246(1).
    4. Yicong Lin & André Lucas, 2025. "Functional Location-Scale Models with Robust Observation-Driven Dynamics," Tinbergen Institute Discussion Papers 25-027/III, Tinbergen Institute.

  3. Enzo D’Innocenzo & André Lucas & Bernd Schwaab & Xin Zhang, 2024. "Modeling Extreme Events: Time-Varying Extreme Tail Shape," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 903-917, July.
    See citations under working paper version above.
  4. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).

    Cited by:

    1. Giuseppe Buccheri & Fulvio Corsi & Emilija Dzuverovic, 2024. "From rotational to scalar invariance: Enhancing identifiability in score-driven factor models," Papers 2412.01367, arXiv.org.

  5. Igor Custodio João & Julia Schaumburg & André Lucas & Bernd Schwaab, 2024. "Dynamic Nonparametric Clustering of Multivariate Panel Data," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 335-374.
    See citations under working paper version above.
  6. Custodio João, Igor & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2023. "Dynamic clustering of multivariate panel data," Journal of Econometrics, Elsevier, vol. 237(2).
    See citations under working paper version above.
  7. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).

    Cited by:

    1. Rehman, Obaid Ur & Wu, Kai & Liu, Jia, 2024. "COVID-19 exposure, financial flexibility, and corporate leverage adjustment," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    2. Stepankova, Barbora & Teply, Petr, 2023. "Consistency of banks' internal probability of default estimates: Empirical evidence from the COVID-19 crisis," Journal of Banking & Finance, Elsevier, vol. 154(C).

  8. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.

    Cited by:

    1. Harvey, Andrew & Palumbo, Dario, 2023. "Score-driven models for realized volatility," Journal of Econometrics, Elsevier, vol. 237(2).

  9. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    See citations under working paper version above.
  10. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    See citations under working paper version above.
  11. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.

    Cited by:

    1. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    2. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    3. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).

  12. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.

    Cited by:

    1. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
    2. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
    3. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.

  13. Francisco Blasques & Siem Jan Koopman & André Lucas, 2020. "Nonlinear autoregressive models with optimality properties," Econometric Reviews, Taylor & Francis Journals, vol. 39(6), pages 559-578, July.

    Cited by:

    1. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    2. Martí de Castro-Cros & Manel Velasco & Cecilio Angulo, 2021. "Machine-Learning-Based Condition Assessment of Gas Turbines—A Review," Energies, MDPI, vol. 14(24), pages 1-27, December.
    3. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.

  14. Caballero, Diego & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2020. "Risk endogeneity at the lender/investor-of-last-resort," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 283-297.
    See citations under working paper version above.
  15. André Lucas & Julia Schaumburg & Bernd Schwaab, 2019. "Bank Business Models at Zero Interest Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 542-555, July.
    See citations under working paper version above.
  16. Anne Opschoor & André Lucas, 2019. "Fractional Integration and Fat Tails for Realized Covariance Kernels," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 66-90.

    Cited by:

    1. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    2. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2024. "Anthropogenic effects of climate change: Further evidence from a fractionally integrated ice-age model," UC3M Working papers. Economics 44712, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    4. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    5. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    6. Astrid Ayala & Szabolcs Blazsek & Adrian Licht, 2022. "Score-driven stochastic seasonality of the Russian rouble: an application case study for the period of 1999 to 2020," Empirical Economics, Springer, vol. 62(5), pages 2179-2203, May.
    7. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).

  17. Anne Opschoor & Pawel Janus & André Lucas & Dick Van Dijk, 2018. "New HEAVY Models for Fat-Tailed Realized Covariances and Returns," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 643-657, October.

    Cited by:

    1. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    2. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    3. Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
    4. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    5. Harvey, Andrew & Palumbo, Dario, 2023. "Score-driven models for realized volatility," Journal of Econometrics, Elsevier, vol. 237(2).
    6. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    7. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    8. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2025. "The Role of Uncertainty in Forecasting Realized Covariance of US State-Level Stock Returns: A Reverse-MIDAS Approach," Working Papers 202501, University of Pretoria, Department of Economics.
    9. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    10. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    11. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    12. Laura Capera Romero & Anne Opschoor, 2025. "Revisiting EWMA in High-Frequency Portfolio Optimization: A Comparative Assessment," Tinbergen Institute Discussion Papers 25-041/III, Tinbergen Institute.
    13. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
    14. Marco Piña & Rodrigo Herrera, 2021. "Risk modeling with option-implied correlations and score-driven dynamics," Working Papers Central Bank of Chile 932, Central Bank of Chile.
    15. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    16. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    17. BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    19. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    20. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    21. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
    22. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    23. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    24. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    25. Xu, Buyun & Wu, Zhimin, 2025. "Real-time GARCH@CARR: A joint model of returns, realized measure of volatility and current intraday information," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
    26. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    27. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    28. Manabu Asai & Mike K. P. So, 2021. "Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 271-294, May.
    29. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    30. Asai Manabu & So Mike K. P., 2023. "Realized BEKK-CAW Models," Journal of Time Series Econometrics, De Gruyter, vol. 15(1), pages 49-77, January.
    31. Bauwens, Luc & Dzuverovic, Emilija & Hafner, Christian, 2024. "Asymmetric Models for Realized Covariances," LIDAM Discussion Papers ISBA 2024022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    32. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    33. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    34. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    35. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    36. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    37. Herrera, Rodrigo & Piña, Marco, 2024. "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).

  18. Francisco Blasques & André Lucas & Erkki Silde, 2018. "A stochastic recurrence equations approach for score driven correlation models," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 166-181, February.

    Cited by:

    1. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    2. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    3. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    4. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    5. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
    6. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).

  19. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.

    Cited by:

    1. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2019. "Dynamic discrete mixtures for high frequency prices," Discussion Papers 19/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    2. Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
    3. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    4. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    5. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
    6. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    7. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.

  20. Francesco Calvori & Drew Creal & Siem Jan Koopman & André Lucas, 2017. "Testing for Parameter Instability across Different Modeling Frameworks," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 223-246.

    Cited by:

    1. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    2. Davide Delle Monache & Andrea De Polis & Ivan Petrella, 2024. "Modeling and Forecasting Macroeconomic Downside Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 1010-1025, July.
    3. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    4. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    5. F. Campigli & G. Bormetti & F. Lillo, 2022. "Measuring price impact and information content of trades in a time-varying setting," Papers 2212.12687, arXiv.org, revised Dec 2023.
    6. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    7. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    8. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.

  21. István Barra & Lennart Hoogerheide & Siem Jan Koopman & André Lucas, 2017. "Joint Bayesian Analysis of Parameters and States in Nonlinear non‐Gaussian State Space Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 1003-1026, August.
    See citations under working paper version above.
  22. André Lucas & Bernd Schwaab & Xin Zhang, 2017. "Modeling Financial Sector Joint Tail Risk in the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 171-191, January.
    See citations under working paper version above.
  23. Siem Jan Koopman & Rutger Lit & André Lucas, 2017. "Intraday Stochastic Volatility in Discrete Price Changes: The Dynamic Skellam Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1490-1503, October.
    See citations under working paper version above.
  24. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    See citations under working paper version above.
  25. J.F. McCARTHY & D.J. Steenbergen & C. Warren & G. Acciaioli & G. Baker & A. Lucas & V. Rambe, 2017. "Community Driven Development and Structural Disadvantage: Interrogating the Social Turn in Development Programming in Indonesia," Journal of Development Studies, Taylor & Francis Journals, vol. 53(12), pages 1988-2004, December.

    Cited by:

    1. Muhammad Syukri, 2024. "Neglecting the poor and marginalized: Participatory village governance in Indonesia's New Developmentalist state," Development Policy Review, Overseas Development Institute, vol. 42(4), July.

  26. Nucera, Federico & Lucas, André & Schaumburg, Julia & Schwaab, Bernd, 2017. "Do negative interest rates make banks less safe?," Economics Letters, Elsevier, vol. 159(C), pages 112-115.
    See citations under working paper version above.
  27. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    See citations under working paper version above.
  28. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    See citations under working paper version above.
  29. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    See citations under working paper version above.
  30. Nucera, Federico & Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2016. "The information in systemic risk rankings," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 461-475.
    See citations under working paper version above.
  31. Lucas, André & Zhang, Xin, 2016. "Score-driven exponentially weighted moving averages and Value-at-Risk forecasting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 293-302.
    See citations under working paper version above.
  32. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.

    Cited by:

    1. Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2025. "Score-driven time-varying parameter models with splinebased densities," Tinbergen Institute Discussion Papers 25-011/III, Tinbergen Institute.
    2. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    3. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    4. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.

  33. Blasques, Francisco & Koopman, Siem Jan & Łasak, Katarzyna & Lucas, André, 2016. "In-sample confidence bands and out-of-sample forecast bands for time-varying parameters in observation-driven models," International Journal of Forecasting, Elsevier, vol. 32(3), pages 875-887.
    See citations under working paper version above.
  34. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    See citations under working paper version above.
  35. Siem Jan Koopman & André Lucas & Marcel Scharth, 2016. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," The Review of Economics and Statistics, MIT Press, vol. 98(1), pages 97-110, March.
    See citations under working paper version above.
  36. F. Blasques & S. J. Koopman & A. Lucas, 2015. "Information-theoretic optimality of observation-driven time series models for continuous responses," Biometrika, Biometrika Trust, vol. 102(2), pages 325-343.

    Cited by:

    1. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    2. Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations Of Market Forecasts, And Sentiment," Discussion Papers 17-10, University of Copenhagen. Department of Economics.
    3. Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
    4. F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
    5. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    6. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
    7. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    8. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    9. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    10. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
    11. Xu, Yingying & Lien, Donald, 2022. "COVID-19 and currency dependences: Empirical evidence from BRICS," Finance Research Letters, Elsevier, vol. 45(C).
    12. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    13. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    14. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    15. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    16. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    17. Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
    18. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
    19. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    20. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    21. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    22. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    23. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    24. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    25. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
    26. Schwaab, Bernd & Zhang, Xin & Lucas, André, 2021. "Modeling extreme events: time-varying extreme tail shape," Working Paper Series 2524, European Central Bank.
    27. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
    28. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    29. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    30. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.
    31. Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    32. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    33. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    34. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    35. Francisco Blasques & Christian Francq & Sébastien Laurent, 2020. "A New Class of Robust Observation-Driven Models," Tinbergen Institute Discussion Papers 20-073/III, Tinbergen Institute.
    36. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    37. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
    38. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    39. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    40. D’Innocenzo, Enzo & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2025. "Joint extreme Value-at-Risk and Expected Shortfall dynamics with a single integrated tail shape parameter," Working Paper Series 446, Sveriges Riksbank (Central Bank of Sweden).
    41. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    42. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    43. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    44. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
    45. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
    46. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    47. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    48. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
    49. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    50. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    51. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    52. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    53. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    54. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    55. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    56. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    57. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    58. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    59. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    60. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    61. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    62. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Mar 2025.
    63. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
    64. Bram van Os & Dick van Dijk, 2020. "Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model," Tinbergen Institute Discussion Papers 20-057/VI, Tinbergen Institute, revised 14 Dec 2020.
    65. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    66. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    67. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    68. Mariana Arozo B. de Melo & Cristiano A. C. Fernandes & Eduardo F. L. de Melo, 2018. "Forecasting aggregate claims using score‐driven time series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 354-374, August.
    69. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    70. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    71. Yicong Lin & André Lucas, 2025. "Functional Location-Scale Models with Robust Observation-Driven Dynamics," Tinbergen Institute Discussion Papers 25-027/III, Tinbergen Institute.
    72. Shijia Song & Handong Li, 2023. "A new model for forecasting VaR and ES using intraday returns aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1039-1054, August.
    73. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    74. Yu‐Sheng Lai, 2021. "Generalized autoregressive score model with high‐frequency data for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2023-2045, December.
    75. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    76. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    77. Rogier Quaedvlieg & Peter Schotman, 2022. "Hedging Long-Term Liabilities [Pricing the Term Structure with Linear Regressions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 505-538.
    78. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    79. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
    80. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  37. Siem Jan Koopman & André Lucas & Marcel Scharth, 2015. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State-Space Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 114-127, January.
    See citations under working paper version above.
  38. Kräussl, Roman & Lucas, André & Rijsbergen, David R. & van der Sluis, Pieter Jelle & Vrugt, Evert B., 2014. "Washington meets Wall Street: A closer examination of the presidential cycle puzzle," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 50-69.
    See citations under working paper version above.
  39. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.

    Cited by:

    1. Peter Grundke & Kamil Pliszka, 2018. "A macroeconomic reverse stress test," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1093-1130, May.
    2. Mikhail Stolbov & Alexander Karminsky & Maria Shchepeleva, 2018. "Does Economic Policy Uncertainty Lead Systemic Risk? A Comparative Analysis of Selected European Countries," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(3), pages 332-360, September.
    3. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    4. Yinghua Song & Minzhe Jiang & Shixuan Li & Shengzhe Zhao, 2024. "Class‐imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 593-614, April.
    5. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

  40. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    See citations under working paper version above.
  41. André Lucas & Bernd Schwaab & Xin Zhang, 2014. "Conditional Euro Area Sovereign Default Risk," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 271-284, April.
    See citations under working paper version above.
  42. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andr� Lucas, 2014. "Observation-Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 898-915, December.
    See citations under working paper version above.
  43. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.

    Cited by:

    1. Matkovskyy, Roman & Jalan, Akanksha & Dowling, Michael, 2020. "Effects of economic policy uncertainty shocks on the interdependence between Bitcoin and traditional financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 150-155.
    2. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    3. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    4. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    5. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    6. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    7. Blasques, F. & van Brummelen, J. & Gorgi, P. & Koopman, S.J., 2024. "A robust Beveridge–Nelson decomposition using a score-driven approach with an application," Economics Letters, Elsevier, vol. 236(C).
    8. Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2025. "Score-driven time-varying parameter models with splinebased densities," Tinbergen Institute Discussion Papers 25-011/III, Tinbergen Institute.
    9. Chen Tong & Peter Reinhard Hansen & Ilya Archakov, 2024. "Cluster GARCH," Papers 2406.06860, arXiv.org.
    10. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    11. Tobias Fissler & Yannick Hoga, 2024. "How to Compare Copula Forecasts?," Papers 2410.04165, arXiv.org.
    12. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    13. Barbara Rossi & Atsushi Inoue & Yiru Wang, 2024. "Has the Phillips curve flattened?," French Stata Users' Group Meetings 2024 22, Stata Users Group.
    14. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    15. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    16. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    17. Kazeem Abimbola Sanusi & Zandri Dickason-Koekemoer, 2022. "Cryptocurrency Returns, Cybercrime and Stock Market Volatility: GAS and Regime Switching Approaches," International Journal of Economics and Financial Issues, Econjournals, vol. 12(6), pages 52-64, November.
    18. Shi, Yong & Zhang, Linzi, 2023. "Modelling long- and short-term multi-dimensional patterns in predictive maintenance with accumulative attention," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    19. Massimiliano Giacalone & Demetrio Panarello, 2022. "A Nonparametric Approach for Testing Long Memory in Stock Returns’ Higher Moments," Mathematics, MDPI, vol. 10(5), pages 1-21, February.
    20. Tachibana, Minoru, 2022. "Safe haven assets for international stock markets: A regime-switching factor copula approach," Research in International Business and Finance, Elsevier, vol. 60(C).
    21. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    22. Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
    23. Xingyu Dai & Dongna Zhang & Chi Keung Marco Lau & Qunwei Wang, 2023. "Multiobjective portfolio optimization: Forecasting and evaluation under investment horizon heterogeneity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2167-2196, December.
    24. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    25. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
    26. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    27. Andries C. van Vlodrop & Andre (A.) Lucas, 2018. "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers 18-099/III, Tinbergen Institute.
    28. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    29. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    30. F Blasques & P Gorgi & S Koopman & O Wintenberger, 2016. "Feasible Invertibility Conditions for Maximum Likelihood Estimation for Observation-Driven Models," Papers 1610.02863, arXiv.org.
    31. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    32. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    33. André Lucas & Julia Schaumburg & Bernd Schwaab, 2020. "Dynamic clustering of multivariate panel data," Tinbergen Institute Discussion Papers 20-009/III, Tinbergen Institute.
    34. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    35. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    36. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    37. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    38. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
    39. Xu, Yingying & Lien, Donald, 2022. "COVID-19 and currency dependences: Empirical evidence from BRICS," Finance Research Letters, Elsevier, vol. 45(C).
    40. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    41. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2017. "Relation between higher order comoments and dependence structure of equity portfolio," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 101-120.
    42. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    43. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    44. Blasques, Francisco & Koopman, Siem Jan & Nientker, Marc, 2022. "A time-varying parameter model for local explosions," Journal of Econometrics, Elsevier, vol. 227(1), pages 65-84.
    45. Leopoldo Catania & Stefano Grassi, 2017. "Modelling Crypto-Currencies Financial Time-Series," CEIS Research Paper 417, Tor Vergata University, CEIS, revised 11 Dec 2017.
    46. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
    47. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
    48. Abdelkamel Alj & Christophe Ley & Guy Melard, 2015. "Asymptotic Properties of QML Estimators for VARMA Models with Time-Dependent Coefficients: Part I," Working Papers ECARES ECARES 2015-21, ULB -- Universite Libre de Bruxelles.
    49. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    50. Pál, Tibor & Storti, Giuseppe, 2025. "Estimating the R-Star in the US: A Score-Driven State-Space Model with Time-Varying Volatility Persistence," MPRA Paper 125338, University Library of Munich, Germany.
    51. Francq, Christian & Zakoian, Jean-Michel, 2024. "Finite moments testing in a general class of nonlinear time series models," MPRA Paper 121193, University Library of Munich, Germany.
    52. Harvey, Andrew & Palumbo, Dario, 2023. "Score-driven models for realized volatility," Journal of Econometrics, Elsevier, vol. 237(2).
    53. Timo Dimitriadis & iaochun Liu & Julie Schnaitmann, 2023. "Encompassing Tests for Value at Risk and Expected Shortfall Multistep Forecasts Based on Inference on the Boundary," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 412-444.
    54. Udichibarna Bose & Ronald MacDonald & Serafeim Tsoukas, 2014. "The role of education in equity portfolios during the recent financial crisis," Working Papers 2014_17, Business School - Economics, University of Glasgow.
    55. Laurent Callot & Johannes Tang Kristensen, 2014. "Vector Autoregressions with parsimoniously Time Varying Parameters and an Application to Monetary Policy," Tinbergen Institute Discussion Papers 14-145/III, Tinbergen Institute, revised 09 Apr 2015.
    56. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    57. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    58. Blasques, Francisco & van Brummelen, Janneke & Gorgi, Paolo & Koopman, Siem Jan, 2024. "Maximum Likelihood Estimation for Non-Stationary Location Models with Mixture of Normal Distributions," Journal of Econometrics, Elsevier, vol. 238(1).
    59. Dimitriadis, Timo & Schnaitmann, Julie, 2021. "Forecast encompassing tests for the expected shortfall," International Journal of Forecasting, Elsevier, vol. 37(2), pages 604-621.
    60. Liu, Jianing & Man, Yuanyuan & Dong, Xiuliang, 2023. "Tail dependence and risk spillover effects between China's carbon market and energy markets," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 553-567.
    61. Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
    62. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    63. Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman van Dijk, 2019. "Partially Censored Posterior for Robust and Efficient Risk Evaluation," Tinbergen Institute Discussion Papers 19-057/III, Tinbergen Institute.
    64. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    65. Gabriele Fiorentini & Enrique Sentana, 2018. "New Testing Approaches for Mean-Variance Predictability," Working Papers wp2018_1814, CEMFI.
    66. Denuit, Michel & Lu, Yang, 2020. "Wishart-Gamma mixtures for multiperil experience ratemaking, frequency-severity experience rating and micro-loss reserving," LIDAM Discussion Papers ISBA 2020016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    67. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    68. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
    69. Böhm, Hannes & Schaumburg, Julia & Tonzer, Lena, 2020. "Financial linkages and sectoral business cycle synchronisation: Evidence from Europe," IWH Discussion Papers 2/2020, Halle Institute for Economic Research (IWH).
    70. Abdelhakim Aknouche & Christian Francq, 2022. "Stationarity and ergodicity of Markov switching positive conditional mean models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 436-459, May.
    71. Harvey, A. & Hurn, S. & Thiele, S., 2019. "Modeling directional (circular) time series," Cambridge Working Papers in Economics 1971, Faculty of Economics, University of Cambridge.
    72. Zhang, Guofu & Liu, Wei, 2018. "Analysis of the international propagation of contagion between oil and stock markets," Energy, Elsevier, vol. 165(PA), pages 469-486.
    73. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    74. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    75. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    76. Wolf, Elias, 2022. "Estimating growth at risk with skewed stochastic volatility models," Discussion Papers 2022/2, Free University Berlin, School of Business & Economics.
    77. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    78. Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016. "Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
    79. Zhimin Wu & Guanghui Cai, 2024. "Can intraday data improve the joint estimation and prediction of risk measures? Evidence from a variety of realized measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1956-1974, September.
    80. Francq, Christian & Zakoian, Jean-Michel, 2021. "Local asymptotic normality of general conditionally heteroskedastic and score-driven time-series models," MPRA Paper 106542, University Library of Munich, Germany.
    81. Wen, Xiaoqian & Cheng, Hua, 2018. "Which is the safe haven for emerging stock markets, gold or the US dollar?," Emerging Markets Review, Elsevier, vol. 35(C), pages 69-90.
    82. Luca Vincenzo Ballestra & Enzo D’Innocenzo & Andrea Guizzardi, 2024. "Score-Driven Modeling with Jumps: An Application to S&P500 Returns and Options," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 375-406.
    83. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    84. Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
    85. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    86. Gkillas, Konstantinos & Konstantatos, Christoforos & Papathanasiou, Spyros & Wohar, Mark, 2023. "Estimation of value at risk for copper," Journal of Commodity Markets, Elsevier, vol. 32(C).
    87. Wen, Xiaoqian & Xie, Yuxin & Pantelous, Athanasios A., 2022. "Extreme price co-movement of commodity futures and industrial production growth: An empirical evaluation," Energy Economics, Elsevier, vol. 108(C).
    88. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    89. Han, Yingwei & Li, Jie, 2022. "Should investors include green bonds in their portfolios? Evidence for the USA and Europe," International Review of Financial Analysis, Elsevier, vol. 80(C).
    90. Olusanya E. Olubusoye & OlaOluwa S. Yaya, 2016. "Time series analysis of volatility in the petroleum pricing markets: the persistence, asymmetry and jumps in the returns series," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 40(3), pages 235-262, September.
    91. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
    92. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, Department of Economics and Business Economics, Aarhus University.
    93. Bai, Xiwen & Kavussanos, Manolis G., 2022. "Hedging IMO2020 compliant fuel price exposure using futures contracts," Energy Economics, Elsevier, vol. 110(C).
    94. Lu Yang & Jason Z. Ma & Shigeyuki Hamori, 2018. "Dependence Structures and Systemic Risk of Government Securities Markets in Central and Eastern Europe: A CoVaR-Copula Approach," Sustainability, MDPI, vol. 10(2), pages 1-23, January.
    95. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Volatility jumps and their economic determinants," CREATES Research Papers 2014-27, Department of Economics and Business Economics, Aarhus University.
    96. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    97. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    98. Javier Ojea Ferreiro, 2018. "Contagion spillovers between sovereign and financial European sector from a Delta CoVaR approach," Documentos de Trabajo del ICAE 2018-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    99. Francesco Calvori & Fabrizio Cipollini & Giampiero M. Gallo, 2014. "Go with the Flow: A GAS model for Predicting Intra-daily Volume Shares," Econometrics Working Papers Archive 2014_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    100. Dickhaus, Thorsten & Sirotko-Sibirskaya, Natalia, 2019. "Simultaneous statistical inference in dynamic factor models: Chi-square approximation and model-based bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 30-46.
    101. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    102. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula," Working Papers 2015_15, Business School - Economics, University of Glasgow.
    103. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2020. "Can Volatility Solve the Naive Portfolio Puzzle?," Papers 2005.03204, arXiv.org, revised Feb 2022.
    104. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    105. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
    106. Michele Caivano & Andrew Harvey, 2014. "Time-series models with an EGB2 conditional distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 558-571, November.
    107. Niţoi, Mihai & Pochea, Maria Miruna, 2020. "Time-varying dependence in European equity markets: A contagion and investor sentiment driven analysis," Economic Modelling, Elsevier, vol. 86(C), pages 133-147.
    108. M. Angeles Carnero Fernández & Ana Pérez Espartero, 2018. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Working Papers. Serie AD 2018-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    109. Xiangdong Liu & Sicheng Fu & Shaopeng Hong, 2025. "Forecasting realized volatility in the stock market: a path-dependent perspective," Papers 2503.00851, arXiv.org.
    110. Maziar Sahamkhadam, 2021. "Dynamic copula-based expectile portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 209-223, May.
    111. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    112. Michele Caivano & Andrew Harvey, 2014. "Two EGARCH models and one fat tail," Temi di discussione (Economic working papers) 954, Bank of Italy, Economic Research and International Relations Area.
    113. Francisco Blasques & Meindert Heres Hoogerkamp & Siem Jan Koopman & Ilka van de Werve, 2020. "Dynamic Factor Models with Clustered Loadings: Forecasting Education Flows using Unemployment Data," Tinbergen Institute Discussion Papers 20-078/III, Tinbergen Institute, revised 21 Jan 2021.
    114. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    115. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    116. Harvey, Andrew & Hurn, Stan & Palumbo, Dario & Thiele, Stephen, 2024. "Modelling circular time series," Journal of Econometrics, Elsevier, vol. 239(1).
    117. Schwaab, Bernd & Zhang, Xin & Lucas, André, 2021. "Modeling extreme events: time-varying extreme tail shape," Working Paper Series 2524, European Central Bank.
    118. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
    119. Francq, Christian & Zakoian, Jean-Michel, 2021. "Testing the existence of moments and estimating the tail index of augmented garch processes," MPRA Paper 110511, University Library of Munich, Germany.
    120. Creal, Drew & Koopman, Siem Jan & Lucas, André, 2011. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 552-563.
    121. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    122. Leopoldo Catania & Mads Sandholdt, 2019. "Bitcoin at High Frequency," JRFM, MDPI, vol. 12(1), pages 1-20, February.
    123. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    124. Matthias Pelster & Johannes Vilsmeier, 2018. "The determinants of CDS spreads: evidence from the model space," Review of Derivatives Research, Springer, vol. 21(1), pages 63-118, April.
    125. Gavronski, Pedro Gerhardt & Ziegelmann, Flavio A., 2021. "Measuring systemic risk via GAS models and extreme value theory: Revisiting the 2007 financial crisis," Finance Research Letters, Elsevier, vol. 38(C).
    126. André Lucas & Julia Schaumburg & Bernd Schwaab, 2019. "Bank Business Models at Zero Interest Rates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 542-555, July.
    127. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    128. Zhao, Zifeng & Zhang, Zhengjun & Chen, Rong, 2018. "Modeling maxima with autoregressive conditional Fréchet model," Journal of Econometrics, Elsevier, vol. 207(2), pages 325-351.
    129. Alexander Mayer & Dominik Wied, 2021. "Estimation and Inference in Factor Copula Models with Exogenous Covariates," Papers 2107.03366, arXiv.org, revised Dec 2022.
    130. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    131. Babii, Andrii & Chen, Xi & Ghysels, Eric, 2019. "Commercial and Residential Mortgage Defaults: Spatial Dependence with Frailty," Journal of Econometrics, Elsevier, vol. 212(1), pages 47-77.
    132. Pircalabu, A. & Hvolby, T. & Jung, J. & Høg, E., 2017. "Joint price and volumetric risk in wind power trading: A copula approach," Energy Economics, Elsevier, vol. 62(C), pages 139-154.
    133. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    134. Armillotta, Mirko & Gorgi, Paolo, 2024. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Journal of Econometrics, Elsevier, vol. 246(1).
    135. Algaba, Andres & Borms, Samuel & Boudt, Kris & Verbeken, Brecht, 2023. "Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 266-278.
    136. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    137. Ilya Archakov & Peter Reinhard Hansen, 2021. "A New Parametrization of Correlation Matrices," Econometrica, Econometric Society, vol. 89(4), pages 1699-1715, July.
    138. Sarlo, Rodrigo & Fernandes, Cristiano & Borenstein, Denis, 2023. "Lumpy and intermittent retail demand forecasts with score-driven models," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1146-1160.
    139. Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    140. F. Blasques & P. Gorgi & S. J. Koopman & J. Sampi, 2023. "Does trade integration imply growth in Latin America? Evidence from a dynamic spatial spillover model," Tinbergen Institute Discussion Papers 23-007/IVI, Tinbergen Institute.
    141. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    142. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models," Tinbergen Institute Discussion Papers 15-083/III, Tinbergen Institute.
    143. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Maximum Likelihood Estimation for correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties," Tinbergen Institute Discussion Papers 14-074/III, Tinbergen Institute.
    144. Mensah, Jones Odei & Alagidede, Paul, 2017. "How are Africa's emerging stock markets related to advanced markets? Evidence from copulas," Economic Modelling, Elsevier, vol. 60(C), pages 1-10.
    145. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Information Theoretic Optimality of Observation Driven Time Series Models," Tinbergen Institute Discussion Papers 14-046/III, Tinbergen Institute.
    146. Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
    147. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonal Quasi-Vector Autoregressive Models with an Application to Crude Oil Production and Economic Activity in the United States and Canada," UC3M Working papers. Economics 27484, Universidad Carlos III de Madrid. Departamento de Economía.
    148. Saverio Ranciati & Alberto Roverato & Alessandra Luati, 2021. "Fused graphical lasso for brain networks with symmetries," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1299-1322, November.
    149. Vladimír Holý & Jan Zouhar, 2022. "Modelling time‐varying rankings with autoregressive and score‐driven dynamics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1427-1450, November.
    150. Drew D. Creal & Jing Cynthia Wu, 2014. "Estimation of Affine Term Structure Models with Spanned or Unspanned Stochastic Volatility," NBER Working Papers 20115, National Bureau of Economic Research, Inc.
    151. Francq, Christian & Sucarrat, Genaro, 2013. "An Exponential Chi-Squared QMLE for Log-GARCH Models Via the ARMA Representation," MPRA Paper 51783, University Library of Munich, Germany.
    152. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
    153. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    154. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    155. Chen, Yanghan & Lin, Juan, 2024. "Measuring systemic risk in Asian foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 146(C).
    156. Chen Tong & Peter Reinhard Hansen & Zhuo Huang, 2021. "Option Pricing with State-dependent Pricing Kernel," Papers 2112.05308, arXiv.org, revised Apr 2022.
    157. Zhou, You & Lin, Lichao & Huang, Ziling, 2024. "Diversification value of green Bonds: Fresh evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    158. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    159. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    160. Krist'of N'emeth & D'aniel Hadh'azi, 2024. "Generating density nowcasts for U.S. GDP growth with deep learning: Bayes by Backprop and Monte Carlo dropout," Papers 2405.15579, arXiv.org.
    161. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    162. Jie Cheng, 2024. "Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3617-3643, December.
    163. Christensen, Troels Sønderby & Pircalabu, Anca & Høg, Esben, 2019. "A seasonal copula mixture for hedging the clean spark spread with wind power futures," Energy Economics, Elsevier, vol. 78(C), pages 64-80.
    164. Blasques, F. & Gorgi, P. & Koopman, S.J., 2021. "Missing observations in observation-driven time series models," Journal of Econometrics, Elsevier, vol. 221(2), pages 542-568.
    165. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    166. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
    167. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    168. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    169. Sheng Fang & Paul Egan, 2021. "Tail dependence between oil prices and China's A‐shares: Evidence from firm‐level data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1469-1487, January.
    170. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    171. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    172. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    173. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    174. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    175. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    176. Laura Capera Romero & Anne Opschoor, 2025. "Revisiting EWMA in High-Frequency Portfolio Optimization: A Comparative Assessment," Tinbergen Institute Discussion Papers 25-041/III, Tinbergen Institute.
    177. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Dependence structure in the Australian electricity markets: New evidence from regular vine copulae," Energy Economics, Elsevier, vol. 90(C).
    178. Labonne, Paul, 2025. "Asymmetric uncertainty: Nowcasting using skewness in real-time data," International Journal of Forecasting, Elsevier, vol. 41(1), pages 229-250.
    179. Mohamed El Ghourabi & Asma Nani & Imed Gammoudi, 2021. "A value‐at‐risk computation based on heavy‐tailed distribution for dynamic conditional score models," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2790-2799, April.
    180. Candia, Claudio & Herrera, Rodrigo, 2024. "An empirical review of dynamic extreme value models for forecasting value at risk, expected shortfall and expectile," Journal of Empirical Finance, Elsevier, vol. 77(C).
    181. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
    182. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    183. De Polis, Andrea & Melosi, Leonardo & Petrella, Ivan, 2024. "The Taming of the Skew : Asymmetric Inflation Risk and Monetary Policy," The Warwick Economics Research Paper Series (TWERPS) 1530, University of Warwick, Department of Economics.
    184. Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
    185. Man Wang & Yihan Cheng, 2022. "Forecasting value at risk and expected shortfall using high‐frequency data of domestic and international stock markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1595-1607, December.
    186. Lasek, Jan & Gagolewski, Marek, 2021. "Interpretable sports team rating models based on the gradient descent algorithm," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1061-1071.
    187. Pierluigi Vallarino, 2024. "Dynamic kernel models," Tinbergen Institute Discussion Papers 24-082/III, Tinbergen Institute.
    188. Harvey, Andew & Liao, Yin, 2023. "Dynamic Tobit models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 72-83.
    189. Bei, Zeyun & Lin, Juan & Zhou, Yinggang, 2024. "No safe haven, only diversification and contagion — Intraday evidence around the COVID-19 pandemic," Journal of International Money and Finance, Elsevier, vol. 143(C).
    190. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
    191. Marco Piña & Rodrigo Herrera, 2021. "Risk modeling with option-implied correlations and score-driven dynamics," Working Papers Central Bank of Chile 932, Central Bank of Chile.
    192. Chen, Zhenlong & Chang, Jing & Hao, Xiaozhen, 2024. "Portfolio selection via high-dimensional stochastic factor Copula," Finance Research Letters, Elsevier, vol. 67(PA).
    193. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    194. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    195. Bahcivan, Hulusi & Karahan, Cenk C., 2022. "High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange," International Review of Financial Analysis, Elsevier, vol. 80(C).
    196. D’Innocenzo, Enzo & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2025. "Joint extreme Value-at-Risk and Expected Shortfall dynamics with a single integrated tail shape parameter," Working Paper Series 446, Sveriges Riksbank (Central Bank of Sweden).
    197. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    198. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    199. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira da Veiga, María Helena, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.
    200. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
    201. Tobias Fissler & Yannick Hoga, 2021. "Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability," Papers 2104.10673, arXiv.org, revised Feb 2022.
    202. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
    203. Hiroyuki Kawakatsu, 2022. "Modeling Realized Variance with Realized Quarticity," Stats, MDPI, vol. 5(3), pages 1-25, September.
    204. Andrew Harvey & Rutger-Jan Lange, 2015. "Modeling the Interactions between Volatility and Returns," Cambridge Working Papers in Economics 1518, Faculty of Economics, University of Cambridge.
    205. Storti, Giuseppe & Wang, Chao, 2022. "A multivariate semi-parametric portfolio risk optimization and forecasting framework," MPRA Paper 115266, University Library of Munich, Germany.
    206. Chao Wang & Richard Gerlach & Qian Chen, 2018. "A Semi-parametric Realized Joint Value-at-Risk and Expected Shortfall Regression Framework," Papers 1807.02422, arXiv.org, revised Jan 2021.
    207. Rakesh K. Bissoondeeal & Leonidas Tsiaras, 2023. "Investigating the Links between UK House Prices and Share Prices with Copulas," The Journal of Real Estate Finance and Economics, Springer, vol. 67(3), pages 423-452, October.
    208. Harvey, Andrew & Ito, Ryoko, 2020. "Modeling time series when some observations are zero," Journal of Econometrics, Elsevier, vol. 214(1), pages 33-45.
    209. Fei Chen & Francis X. Diebold & Frank Schorfheide, 2012. "A Markov-Switching Multi-Fractal Inter-Trade Duration Model, with Application to U.S. Equities," NBER Working Papers 18078, National Bureau of Economic Research, Inc.
    210. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    211. Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).
    212. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
    213. Lin Zhao & Sweder van Wijnbergen, 2014. "Decision Making in Incomplete Markets with Ambiguity -- A Case Study of a Gas Field Acquisition," Tinbergen Institute Discussion Papers 14-149/VI, Tinbergen Institute.
    214. G.M. Gallo & O. Okhrin & G. Storti, 2024. "Dynamic tail risk forecasting: what do realized skewness and kurtosis add?," Working Paper CRENoS 202416, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    215. Martin Weale & Paul Labonne, 2022. "Nowcasting in the presence of large measurement errors and revisions," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-05, Economic Statistics Centre of Excellence (ESCoE).
    216. Bruzda, Joanna, 2020. "Demand forecasting under fill rate constraints—The case of re-order points," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1342-1361.
    217. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    218. Christian Conrad & Robert F. Engle, 2025. "Modelling Volatility Cycles: The MF2‐GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 438-454, June.
    219. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
    220. Jiang, Kunliang & Zeng, Linhui & Song, Jiashan & Liu, Yimeng, 2022. "Forecasting Value-at-Risk of cryptocurrencies using the time-varying mixture-accelerating generalized autoregressive score model," Research in International Business and Finance, Elsevier, vol. 61(C).
    221. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    222. Lu Yang & Shigeyuki Hamori, 2020. "Forecasts of Value-at-Risk and Expected Shortfall in the Crude Oil Market: A Wavelet-Based Semiparametric Approach," Energies, MDPI, vol. 13(14), pages 1-27, July.
    223. Hetland, Simon & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2023. "Dynamic conditional eigenvalue GARCH," Journal of Econometrics, Elsevier, vol. 237(2).
    224. Alex Karagrigoriou & George-Jason Siouris & Despoina Skilogianni, 2019. "Adjusted Evaluation Measures for Asymmetrically Important Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(1), pages 41-66, June.
    225. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    226. Harvey, Andrew & Thiele, Stephen, 2016. "Testing against changing correlation," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 575-589.
    227. Federico Gatta & Fabrizio Lillo & Piero Mazzarisi, 2024. "CAESar: Conditional Autoregressive Expected Shortfall," Papers 2407.06619, arXiv.org.
    228. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
    229. Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
    230. Bu, Di & Liao, Yin & Shi, Jing & Peng, Hongfeng, 2019. "Dynamic expected shortfall: A spectral decomposition of tail risk across time horizons," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    231. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
    232. Owusu Junior, Peterson & Alagidede, Imhotep, 2020. "Risks in emerging markets equities: Time-varying versus spatial risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    233. Harvey, A. & Palumbo, D., 2021. "Regime switching models for directional and linear observations," Cambridge Working Papers in Economics 2123, Faculty of Economics, University of Cambridge.
    234. Giuseppe Storti & Chao Wang, 2022. "A semi-parametric dynamic conditional correlation framework for risk forecasting," Papers 2207.04595, arXiv.org, revised Dec 2024.
    235. Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2017. "A Justification of Conditional Confidence Intervals," Papers 1710.00643, arXiv.org, revised Jan 2019.
    236. Pelster, Matthias & Vilsmeier, Johannes, 2016. "The determinants of CDS spreads: Evidence from the model space," Discussion Papers 43/2016, Deutsche Bundesbank.
    237. F. Campigli & G. Bormetti & F. Lillo, 2022. "Measuring price impact and information content of trades in a time-varying setting," Papers 2212.12687, arXiv.org, revised Dec 2023.
    238. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    239. Xing, Xiaoyun & Xu, Zihan & Chen, Ying & Ouyang, WenPei & Deng, Jing & Pan, Huanxue, 2023. "The impact of the Russia–Ukraine conflict on the energy subsector stocks in China: A network-based approach," Finance Research Letters, Elsevier, vol. 53(C).
    240. Chen Tong & Peter Reinhard Hansen, 2025. "Dynamic Factor Correlation Model," Papers 2503.01080, arXiv.org.
    241. Laura Capera Romero & Anne Opschoor, 2024. "Realized Variances vs. Correlations: Unlocking the Gains in Multivariate Volatility Forecasting," Tinbergen Institute Discussion Papers 24-059/III, Tinbergen Institute.
    242. Leopoldo Catania & Stefano Grassi & Francesco Ravazzolo, 2018. "Predicting the Volatility of Cryptocurrency Time Series," Working Papers No 3/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    243. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    244. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    245. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.
    246. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.
    247. Cem Cakmakli & Yasin Simsek, 2020. "Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model," Papers 2007.02726, arXiv.org, revised Feb 2021.
    248. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
    249. Giuseppe Storti & Chao Wang, 2023. "Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1648-1663, November.
    250. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    251. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    252. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
    253. Tata Subba Rao & Granville Tunnicliffe Wilson & Andrew Harvey & Rutger-Jan Lange, 2017. "Volatility Modeling with a Generalized t Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 175-190, March.
    254. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
    255. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
    256. Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2023. "Fiscal Policy Regimes in Resource-Rich Economies," Working Papers No 13/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    257. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    258. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    259. Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
    260. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    261. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Measuring Success: Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers 11-19, Association Française de Cliométrie (AFC).
    262. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    263. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    264. Xu, Buyun & Wu, Zhimin, 2025. "Real-time GARCH@CARR: A joint model of returns, realized measure of volatility and current intraday information," The North American Journal of Economics and Finance, Elsevier, vol. 76(C).
    265. Ke, Rui & Yang, Luyao & Tan, Changchun, 2022. "Forecasting tail risk for Bitcoin: A dynamic peak over threshold approach," Finance Research Letters, Elsevier, vol. 49(C).
    266. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    267. Chen, Cathy W.S. & Hsu, Hsiao-Yun & Watanabe, Toshiaki, 2023. "Tail risk forecasting of realized volatility CAViaR models," Finance Research Letters, Elsevier, vol. 51(C).
    268. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
    269. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    270. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
    271. Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    272. Gong, Yuting & Ma, Chao & Chen, Qiang, 2022. "Exchange rate dependence and economic fundamentals: A Copula-MIDAS approach," Journal of International Money and Finance, Elsevier, vol. 123(C).
    273. Hotta, Luiz & Trucíos, Carlos & Ruiz Ortega, Esther, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    274. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    275. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
    276. Francisco Blasques & Siem Jan Koopman & Katarzyna Lasak & André Lucas, 2015. "In-Sample Bounds for Time-Varying Parameters of Observation Driven Models," Tinbergen Institute Discussion Papers 15-027/III, Tinbergen Institute, revised 07 Sep 2015.
    277. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    278. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
    279. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    280. Petrella, Ivan & Venditti, Fabrizio & Delle Monache, Davide, 2016. "Adaptive state space models with applications to the business cycle and financial stress," CEPR Discussion Papers 11599, C.E.P.R. Discussion Papers.
    281. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    282. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    283. Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    284. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    285. Triki, Mohamed Bilel & Ben Maatoug, Abderrazek, 2021. "The GOLD market as a safe haven against the stock market uncertainty: Evidence from geopolitical risk," Resources Policy, Elsevier, vol. 70(C).
    286. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    287. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    288. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    289. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    290. Gong, Yuting & He, Zhongzhi & Xue, Wenjun, 2022. "EPU spillovers and stock return predictability: A cross-country study," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    291. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    292. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
    293. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    294. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
    295. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    296. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    297. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    298. Enilov, Martin & Mensi, Walid & Stankov, Petar, 2023. "Does safe haven exist? Tail risks of commodity markets during COVID-19 pandemic," Journal of Commodity Markets, Elsevier, vol. 29(C).
    299. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
    300. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
    301. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    302. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2020. "Sequential forecasting of downside extreme risk during overnight and daytime: Evidence from the Chinese Stock Market☆," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    303. Yang, Lu & Hamori, Shigeyuki, 2021. "The role of the carbon market in relation to the cryptocurrency market: Only diversification or more?," International Review of Financial Analysis, Elsevier, vol. 77(C).
    304. Yang, Bingduo & Cai, Zongwu & Hafner, Christian M. & Liu, Guannan, 2018. "Trending Mixture Copula Models with Copula Selection," IRTG 1792 Discussion Papers 2018-057, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    305. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    306. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    307. Manabu Asai & Mike K. P. So, 2021. "Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 271-294, May.
    308. Kazim Azam & Andre Lucas, 2015. "Mixed Density based Copula Likelihood," Tinbergen Institute Discussion Papers 15-003/IV/DSF084, Tinbergen Institute.
    309. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    310. John Weirstrass Muteba Mwamba & Ehounou Serge Eloge Florentin Angaman, 2021. "Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach," IJFS, MDPI, vol. 9(2), pages 1-17, May.
    311. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    312. Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
    313. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    314. Blasques, Francisco & Nientker, Marc, 2023. "Stochastic properties of nonlinear locally-nonstationary filters," Journal of Econometrics, Elsevier, vol. 235(2), pages 2082-2095.
    315. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    316. Hoeltgebaum, Henrique & Borenstein, Denis & Fernandes, Cristiano & Veiga, Álvaro, 2021. "A score-driven model of short-term demand forecasting for retail distribution centers," Journal of Retailing, Elsevier, vol. 97(4), pages 715-725.
    317. Gao, Chun-Ting & Zhou, Xiao-Hua, 2016. "Forecasting VaR and ES using dynamic conditional score models and skew Student distribution," Economic Modelling, Elsevier, vol. 53(C), pages 216-223.
    318. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    319. Francisco Blasques & Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2024. "Robust Multivariate Observation-Driven Filtering for a Common Stochastic Trend: Theory and Application," Tinbergen Institute Discussion Papers 24-062/III, Tinbergen Institute.
    320. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    321. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    322. Liu, Zhenqing & Luo, Yi & Duan, Mohan, 2025. "Macroeconomic factors, industrial enterprises, and debt default prediction: Based on the VAR-GRU model," Finance Research Letters, Elsevier, vol. 78(C).
    323. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    324. David Blake & Marco Morales & Hua Chen & Richard D. MacMinn & Tao Sun, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 393-415, April.
    325. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    326. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    327. Ames, Matthew & Bagnarosa, Guillaume & Peters, Gareth W., 2017. "Violations of uncovered interest rate parity and international exchange rate dependences," Journal of International Money and Finance, Elsevier, vol. 73(PA), pages 162-187.
    328. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    329. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Mar 2025.
    330. Ioanna-Yvonni Tsaknaki & Fabrizio Lillo & Piero Mazzarisi, 2023. "Online Learning of Order Flow and Market Impact with Bayesian Change-Point Detection Methods," Papers 2307.02375, arXiv.org, revised May 2024.
    331. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    332. Harvey, Andrew & Sucarrat, Genaro, 2014. "EGARCH models with fat tails, skewness and leverage," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 320-338.
    333. Bram van Os & Dick van Dijk, 2020. "Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model," Tinbergen Institute Discussion Papers 20-057/VI, Tinbergen Institute, revised 14 Dec 2020.
    334. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2024. "Extreme risk contagions among fossil energy companies in China: Insights from a multilayer dynamic network analysis," Energy, Elsevier, vol. 306(C).
    335. Bogdan, Dima & Ştefana Maria, Dima & Roxana, Ioan, 2022. "A Value-at-Risk forecastability indicator in the framework of a Generalized Autoregressive Score with “Asymmetric Laplace Distribution”," Finance Research Letters, Elsevier, vol. 45(C).
    336. Cipollini, Fabrizio & Gallo, Giampiero M., 2025. "Multiplicative Error Models: 20 years on," Econometrics and Statistics, Elsevier, vol. 33(C), pages 209-229.
    337. Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    338. Liu, Wei & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models," Research in International Business and Finance, Elsevier, vol. 54(C).
    339. Giuseppe Storti & Chao Wang, 2021. "Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach," Papers 2104.04918, arXiv.org, revised Jul 2021.
    340. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
    341. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    342. Stephanie Danielle Subramoney & Knowledge Chinhamu & Retius Chifurira, 2021. "Value at Risk estimation using GAS models with heavy tailed distributions for cryptocurrencies," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 40-54, October.
    343. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    344. Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
    345. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.
    346. Zongwu Cai & Ying Fang & Dingshi Tian, 2024. "CAViaR Model Selection Via Adaptive Lasso," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202403, University of Kansas, Department of Economics, revised Jan 2024.
    347. Dennis Umlandt, 2020. "Likelihood-based Dynamic Asset Pricing: Learning Time-varying Risk Premia from Cross-Sectional Models," Working Paper Series 2020-06, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    348. Spilger, Maike & Schneider, Dennis & Weber, Christoph, 2025. "Uncertainty characterization for generation adequacy assessments – Including an application to the recent European energy crisis," Energy Economics, Elsevier, vol. 144(C).
    349. Djennad, Abdelmajid & Rigby, Robert & Stasinopoulos, Dimitrios & Voudouris, Vlasios & Eilers, Paul, 2015. "Beyond location and dispersion models: The Generalized Structural Time Series Model with Applications," MPRA Paper 62807, University Library of Munich, Germany.
    350. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    351. Wang, Jie & Xue, Weina & Song, Jiashan, 2022. "Economic policy uncertainty and industry risk on China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    352. Siyao Wei & Pengfei Luo & Jiashan Song & Kunliang Jiang, 2025. "Portfolio Optimization During the COVID-19 Epidemic: Based on an Improved QBAS Algorithm and a Dynamic Mixed Frequency Model," Computational Economics, Springer;Society for Computational Economics, vol. 65(4), pages 1999-2028, April.
    353. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    354. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    355. Manner, Hans & Stark, Florian & Wied, Dominik, 2019. "Testing for structural breaks in factor copula models," Journal of Econometrics, Elsevier, vol. 208(2), pages 324-345.
    356. Trimborn, Simon & Peng, Hanqiu & Chen, Ying, 2024. "Influencer detection meets network autoregression — Influential regions in the bitcoin blockchain," Journal of Empirical Finance, Elsevier, vol. 78(C).
    357. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    358. Karim M Abadir, 2023. "Explicit minimal representation of variance matrices, and its implication for dynamic volatility models," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 88-104.
    359. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    360. Holý, Vladimír, 2024. "Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education," Operations Research Perspectives, Elsevier, vol. 12(C).
    361. Giuseppe Buccheri & Fulvio Corsi & Emilija Dzuverovic, 2024. "From rotational to scalar invariance: Enhancing identifiability in score-driven factor models," Papers 2412.01367, arXiv.org.
    362. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
    363. Harvey, A. & Simons, J., 2024. "Hidden Threshold Models with applications to asymmetric cycles," Cambridge Working Papers in Economics 2448, Faculty of Economics, University of Cambridge.
    364. Mariana Arozo B. de Melo & Cristiano A. C. Fernandes & Eduardo F. L. de Melo, 2018. "Forecasting aggregate claims using score‐driven time series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 354-374, August.
    365. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
    366. Zhicheng Liang & Junwei Wang & Kin Keung Lai, 2020. "Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 169-193, February.
    367. Aryan Singh & Paul O Reilly & Daim Sharif & Patrick Haughey & Eoghan McCarthy & Sathvika Thorali Suresh & Aakhil Anvar & Adarsh Sajeev Kumar, 2025. "Copula Analysis of Risk: A Multivariate Risk Analysis for VaR and CoVaR using Copulas and DCC-GARCH," Papers 2505.06950, arXiv.org.
    368. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
    369. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    370. Szabolcs Blazsek & William M. Dos Santos & Andreco S. Edwards, 2024. "Score-Driven Interactions for “Disease X” Using COVID and Non-COVID Mortality," Econometrics, MDPI, vol. 12(3), pages 1-24, September.
    371. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    372. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    373. Andrew Harvey & Dario Palumbo, 2023. "Regime switching models for circular and linear time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 374-392, July.
    374. Yinhao Wu & Ping He, 2024. "The continuous-time limit of quasi score-driven volatility models," Papers 2409.14734, arXiv.org, revised Jun 2025.
    375. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2020. "Prediction accuracy of bivariate score-driven risk premium and volatility filters: an illustration for the Dow Jones," UC3M Working papers. Economics 31339, Universidad Carlos III de Madrid. Departamento de Economía.
    376. Tsyplakov, Alexander, 2015. "Quasifiltering for time-series modeling," MPRA Paper 66453, University Library of Munich, Germany.
    377. Guy Mélard, 2025. "Estimator’s Properties of Specific Time-Dependent Multivariate Time Series," Mathematics, MDPI, vol. 13(7), pages 1-23, March.
    378. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    379. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    380. Wolf, Elias, 2023. "Estimating Growth at Risk with Skewed Stochastic Volatility Models," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277696, Verein für Socialpolitik / German Economic Association.
    381. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    382. Blazsek Szabolcs & Escribano Alvaro & Licht Adrian, 2021. "Identification of Seasonal Effects in Impulse Responses Using Score-Driven Multivariate Location Models," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 53-66, January.
    383. Storti, Giuseppe & Wang, Chao, 2022. "Nonparametric expected shortfall forecasting incorporating weighted quantiles," International Journal of Forecasting, Elsevier, vol. 38(1), pages 224-239.
    384. de Oliveira, Felipe A. & Maia, Sinézio F. & de Jesus, Diego P. & Besarria, Cássio da N., 2018. "Which information matters to market risk spreading in Brazil? Volatility transmission modelling using MGARCH-BEKK, DCC, t-Copulas," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 83-100.
    385. Katarzyna Łasak & Johannes Lont, 2020. "Observation Driven Long Run Equilibria," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 551-575, February.
    386. Yicong Lin & André Lucas, 2025. "Functional Location-Scale Models with Robust Observation-Driven Dynamics," Tinbergen Institute Discussion Papers 25-027/III, Tinbergen Institute.
    387. Shijia Song & Handong Li, 2023. "A new model for forecasting VaR and ES using intraday returns aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1039-1054, August.
    388. Xingyu Dai & Roy Cerqueti & Qunwei Wang & Ling Xiao, 2025. "Volatility forecasting: a new GARCH-type model for fuzzy sets-valued time series," Annals of Operations Research, Springer, vol. 348(1), pages 735-775, May.
    389. Lin, Min-Bin & Wang, Bingling & Bocart, Fabian Y.R.P. & Hafner, Christian M. & Härdle, Wolfgang K., 2022. "DAI Digital Art Index : a robust price index for heterogeneous digital assets," LIDAM Discussion Papers ISBA 2022036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    390. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    391. Yu‐Sheng Lai, 2021. "Generalized autoregressive score model with high‐frequency data for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2023-2045, December.
    392. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2025. "Tail risk dynamics of banks with score-driven extreme value models," Journal of Empirical Finance, Elsevier, vol. 81(C).
    393. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    394. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    395. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    396. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    397. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
    398. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    399. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2014. "Improving Density Forecasts and Value-at-Risk Estimates by Combining Densities," Tinbergen Institute Discussion Papers 14-090/III, Tinbergen Institute.
    400. Francisco (F.) Blasques & Marc Nientker, 2017. "A Stochastic Recurrence Equation Approach to Stationarity and phi-Mixing of a Class of Nonlinear ARCH Models," Tinbergen Institute Discussion Papers 17-072/III, Tinbergen Institute.
    401. Alanya-Beltran, Willy, 2022. "Modelling stock returns volatility with dynamic conditional score models and random shifts," Finance Research Letters, Elsevier, vol. 45(C).
    402. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    403. Zhang, Ning & Su, Xiaoman & Qi, Shuyuan, 2023. "An empirical investigation of multiperiod tail risk forecasting models," International Review of Financial Analysis, Elsevier, vol. 86(C).
    404. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    405. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
    406. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
    407. D’Innocenzo, Enzo & Lucas, Andre, 2024. "Dynamic partial correlation models," Journal of Econometrics, Elsevier, vol. 241(2).
    408. Lazar, Emese & Pan, Jingqi & Wang, Shixuan, 2024. "On the estimation of Value-at-Risk and Expected Shortfall at extreme levels," Journal of Commodity Markets, Elsevier, vol. 34(C).
    409. Andrew Harvey & Rutger‐Jan Lange, 2018. "Modeling the Interactions between Volatility and Returns using EGARCH‐M," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 909-919, November.
    410. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
    411. Li, Haiping & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "The relationship between oil and financial markets in emerging economies: The significant role of Kazakhstan as the oil exporting country," Finance Research Letters, Elsevier, vol. 32(C).
    412. Debbie J. Dupuis & Nicolas Papageorgiou & Bruno Rémillard, 2015. "Robust Conditional Variance and Value-at-Risk Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 896-921.
    413. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
    414. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    415. Felipe de Oliveira & Sinézio Fernandes Maia & Diego Pita de Jesus, 2017. "Which information matters to Market risk spreading in Brazil? Volatility transmission modeling using MGARH-BEKK, DCC, t-COPULAS," EcoMod2017 10378, EcoMod.
    416. Palumbo, D., 2021. "Testing and Modelling Time Series with Time Varying Tails," Cambridge Working Papers in Economics 2111, Faculty of Economics, University of Cambridge.
    417. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.
    418. Ivanovski, Kris & Hailemariam, Abebe, 2023. "Forecasting the stock-cryptocurrency relationship: Evidence from a dynamic GAS model," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 97-111.
    419. Herrera, Rodrigo & Piña, Marco, 2024. "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    420. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.
    421. Boako, Gideon & Alagidede, Paul, 2017. "Currency price risk and stock market returns in Africa: Dependence and downside spillover effects with stochastic copulas," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 92-114.
    422. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    423. Francisco Blasques & Andre Lucas & Erkki Silde, 2013. "Stationarity and Ergodicity Regions for Score Driven Dynamic Correlation Models," Tinbergen Institute Discussion Papers 13-097/IV/DSF59, Tinbergen Institute.
    424. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
    425. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
    426. Bai, Xiwen & Lam, Jasmine Siu Lee, 2019. "A copula-GARCH approach for analyzing dynamic conditional dependency structure between liquefied petroleum gas freight rate, product price arbitrage and crude oil price," Energy Economics, Elsevier, vol. 78(C), pages 412-427.
    427. Guizhou Liu & Shigeyuki Hamori, 2020. "Can One Reinforce Investments in Renewable Energy Stock Indices with the ESG Index?," Energies, MDPI, vol. 13(5), pages 1-19, March.
    428. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    429. Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
    430. Heil, Thomas L.A. & Peter, Franziska J. & Prange, Philipp, 2022. "Measuring 25 years of global equity market co-movement using a time-varying spatial model," Journal of International Money and Finance, Elsevier, vol. 128(C).
    431. Xu, Yingying & Lien, Donald, 2020. "Dynamic exchange rate dependences: The effect of the U.S.-China trade war," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 68(C).
    432. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    433. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    434. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.
    435. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
    436. Bladt, Martin & McNeil, Alexander J., 2022. "Time series copula models using d-vines and v-transforms," Econometrics and Statistics, Elsevier, vol. 24(C), pages 27-48.
    437. Mohammed A. Bou-Rabee & Muhammad Yasin Naz & Imad ED. Albalaa & Shaharin Anwar Sulaiman, 2022. "BiLSTM Network-Based Approach for Solar Irradiance Forecasting in Continental Climate Zones," Energies, MDPI, vol. 15(6), pages 1-12, March.
    438. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.
    439. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    440. Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.
    441. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.
    442. Ivanovski, Kris & Hailemariam, Abebe, 2021. "Forecasting the dynamic relationship between crude oil and stock prices since the 19th century," Journal of Commodity Markets, Elsevier, vol. 24(C).

  44. Kräussl, Roman & Lucas, André & Siegmann, Arjen, 2012. "Risk aversion under preference uncertainty," Finance Research Letters, Elsevier, vol. 9(1), pages 1-7.
    See citations under working paper version above.
  45. Botshekan, Mahmoud & Kraeussl, Roman & Lucas, Andre, 2012. "Cash Flow and Discount Rate Risk in Up and Down Markets: What Is Actually Priced?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(6), pages 1279-1301, December.
    See citations under working paper version above.
  46. Siem Jan Koopman & André Lucas & Bernd Schwaab, 2012. "Dynamic Factor Models With Macro, Frailty, and Industry Effects for U.S. Default Counts: The Credit Crisis of 2008," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 521-532, May.
    See citations under working paper version above.
  47. Drew Creal & Siem Jan Koopman & André Lucas, 2011. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 552-563, October.
    See citations under working paper version above.
  48. Konijn, Sander J.J. & Kräussl, Roman & Lucas, Andre, 2011. "Blockholder dispersion and firm value," Journal of Corporate Finance, Elsevier, vol. 17(5), pages 1330-1339.
    See citations under working paper version above.
  49. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.

    Cited by:

    1. Azamat Abdymomunov & Filippo Curti & Atanas Mihov, 2020. "U.S. Banking Sector Operational Losses and the Macroeconomic Environment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(1), pages 115-144, February.
    2. Xiao, Tim, 2017. "The Impact of Default Dependency and Collateralization on Asset Pricing and Credit Risk Modeling," FrenXiv mt637, Center for Open Science.
    3. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    5. Bátiz-Zuk Enrique & Mohamed Abdulkadir & Sánchez-Cajal Fátima, 2021. "Exploring the sources of loan default clustering using survival analysis with frailty," Working Papers 2021-14, Banco de México.
    6. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
    7. Pedro H. C. Sant’Anna, 2017. "Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 349-358, July.
    8. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
    9. Qi, Min & Zhang, Xiaofei & Zhao, Xinlei, 2014. "Unobserved systematic risk factor and default prediction," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 216-227.
    10. Drew Creal & Bernd Schwaab & Siem Jan Koopman & Andre Lucas, 2011. "Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk," Tinbergen Institute Discussion Papers 11-042/2/DSF16, Tinbergen Institute.
    11. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
    12. Xiao, Tim, 2019. "The Valuation of Credit Default Swap with Counterparty Risk and Collateralization," FrenXiv 6m73z, Center for Open Science.
    13. Jones, Stewart & Wang, Tim, 2019. "Predicting private company failure: A multi-class analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 161-188.
    14. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," LIDAM Reprints LFIN 2023009, Université catholique de Louvain, Louvain Finance (LFIN).
    15. Nickerson, Jordan & Griffin, John M., 2017. "Debt correlations in the wake of the financial crisis: What are appropriate default correlations for structured products?," Journal of Financial Economics, Elsevier, vol. 125(3), pages 454-474.
    16. Stewart Jones, 2017. "Corporate bankruptcy prediction: a high dimensional analysis," Review of Accounting Studies, Springer, vol. 22(3), pages 1366-1422, September.
    17. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    18. Frame, W. Scott & Lazaryan, Nika & McLemore, Ping & Mihov, Atanas, 2024. "Operational loss recoveries and the macroeconomic environment: Evidence from the U.S. banking sector," Journal of Banking & Finance, Elsevier, vol. 165(C).
    19. Schwaab, Bernd & Eser, Fabian, 2013. "Assessing asset purchases within the ECB’s securities markets programme," Working Paper Series 1587, European Central Bank.
    20. Hu, Nan & Liang, Peng & Liu, Ling & Zhu, Lu, 2022. "The bullwhip effect and credit default swap market: A study based on firm-specific bullwhip effect measure," International Review of Financial Analysis, Elsevier, vol. 84(C).
    21. Xiao, Tim, 2019. "Pricing Financial Derivatives Subject to Multilateral Credit Risk and Collateralization," SocArXiv 84xjn, Center for Open Science.
    22. Pascal Kundig & Fabio Sigrist, 2024. "A Spatio-Temporal Machine Learning Model for Mortgage Credit Risk: Default Probabilities and Loan Portfolios," Papers 2410.02846, arXiv.org, revised Jul 2025.
    23. Bernd Schwaab & Siem Jan Koopman & André Lucas, 2017. "Global Credit Risk: World, Country and Industry Factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 296-317, March.
    24. Ha Nguyen, 2023. "Particle MCMC in forecasting frailty correlated default models with expert opinion," Papers 2304.11586, arXiv.org, revised Aug 2023.
    25. De Santis, Roberto A., 2018. "Unobservable country bond premia and fragmentation," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 1-25.
    26. Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    27. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    28. Sigrist, Fabio & Leuenberger, Nicola, 2023. "Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1390-1406.
    29. Josef Brechler & Vaclav Hausenblas & Zlatuse Komarkova & Miroslav Plasil, 2014. "Similarity and Clustering of Banks: Application to the Credit Exposures of the Czech Banking Sector," Research and Policy Notes 2014/04, Czech National Bank, Research and Statistics Department.
    30. Jones, Stewart & Johnstone, David & Wilson, Roy, 2015. "An empirical evaluation of the performance of binary classifiers in the prediction of credit ratings changes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 72-85.
    31. Nazemi, Abdolreza & Heidenreich, Konstantin & Fabozzi, Frank J., 2018. "Improving corporate bond recovery rate prediction using multi-factor support vector regressions," European Journal of Operational Research, Elsevier, vol. 271(2), pages 664-675.
    32. Daniel Rösch & Harald Scheule, 2014. "Forecasting Mortgage Securitization Risk Under Systematic Risk and Parameter Uncertainty," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 563-586, September.
    33. Nazemi, Abdolreza & Fabozzi, Frank J., 2018. "Macroeconomic variable selection for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 14-25.
    34. Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.
    35. Giovanni Amisano & Oreste Tristani, 2011. "The euro area sovereign crisis: monitoring spillovers and contagion," Research Bulletin, European Central Bank, vol. 14, pages 2-4.
    36. Wang, Fa, 2022. "Maximum likelihood estimation and inference for high dimensional generalized factor models with application to factor-augmented regressions," Journal of Econometrics, Elsevier, vol. 229(1), pages 180-200.
    37. J. Molins & E. Vives, 2015. "Model risk on credit risk," Papers 1502.06984, arXiv.org, revised Dec 2015.
    38. Mark Clintworth & Dimitrios Lyridis & Evangelos Boulougouris, 2023. "Financial risk assessment in shipping: a holistic machine learning based methodology," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 90-121, March.
    39. Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 13 Oct 2014.
    40. Ha Nguyen, 2023. "Particle MCMC in Forecasting Frailty-Correlated Default Models with Expert Opinion," JRFM, MDPI, vol. 16(7), pages 1-16, July.
    41. Nazemi, Abdolreza & Fatemi Pour, Farnoosh & Heidenreich, Konstantin & Fabozzi, Frank J., 2017. "Fuzzy decision fusion approach for loss-given-default modeling," European Journal of Operational Research, Elsevier, vol. 262(2), pages 780-791.
    42. White, Alan, 2018. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," MPRA Paper 85331, University Library of Munich, Germany.
    43. Michele Lenza, 2011. "Revisiting the information content of core inflation," Research Bulletin, European Central Bank, vol. 14, pages 11-13.
    44. Yun Xie & Yixiang Tian & Zhuang Xiao & Xiangyun Zhou, 2018. "Dependence of credit spread and macro-conditions based on an alterable structure model," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-15, May.
    45. Lee, Yongwoong & Yang, Kisung, 2019. "Modeling diversification and spillovers of loan portfolios' losses by LHP approximation and copula," International Review of Financial Analysis, Elsevier, vol. 66(C).
    46. James Wolter, 2013. "Separating the impact of macroeconomic variables and global frailty in event data," Economics Series Working Papers 667, University of Oxford, Department of Economics.
    47. Schwaab, Bernd & Koopman, Siem Jan & Lucas, André, 2014. "Nowcasting and forecasting global financial sector stress and credit market dislocation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 741-758.
    48. Giesecke, Kay & Schwenkler, Gustavo, 2018. "Filtered likelihood for point processes," Journal of Econometrics, Elsevier, vol. 204(1), pages 33-53.
    49. Liu, Zhenqing & Luo, Yi & Duan, Mohan, 2025. "Macroeconomic factors, industrial enterprises, and debt default prediction: Based on the VAR-GRU model," Finance Research Letters, Elsevier, vol. 78(C).
    50. Thomas Hartmann-Wendels & Christopher Paulus Imanto, 2023. "Is the regulatory downturn LGD adequate? Performance analysis and alternative methods," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(3), pages 736-747, March.
    51. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Forecasting systemic impact in financial networks," SFB 649 Discussion Papers 2013-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    52. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2021. "Systematic credit risk in securitised mortgage portfolios," Journal of Banking & Finance, Elsevier, vol. 122(C).
    53. Tim, Xiao, 2019. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," MPRA Paper 94701, University Library of Munich, Germany.
    54. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2016. "Accuracy of mortgage portfolio risk forecasts during financial crises," European Journal of Operational Research, Elsevier, vol. 249(2), pages 440-456.
    55. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    56. Giovanni Lombardo & Luca Dedola, 2011. "Financial frictions, financial integration and the international propagation of shocks," Research Bulletin, European Central Bank, vol. 14, pages 5-10.
    57. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    58. Xing, Kai & Yang, Xiaoguang, 2020. "Predicting default rates by capturing critical transitions in the macroeconomic system," Finance Research Letters, Elsevier, vol. 32(C).
    59. Oliver Blümke, 2020. "Estimating the probability of default for no‐default and low‐default portfolios," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 89-107, January.
    60. Voß, Sebastian & Weißbach, Rafael, 2014. "A score-test on measurement errors in rating transition times," Journal of Econometrics, Elsevier, vol. 180(1), pages 16-29.
    61. Alexander Kremer & Rafael Weißbach, 2013. "Consistent estimation for discretely observed Markov jump processes with an absorbing state," Statistical Papers, Springer, vol. 54(4), pages 993-1007, November.
    62. Alan White, 2018. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," Papers 1803.07843, arXiv.org.
    63. Ahelegbey, Daniel Felix & Celani, Alessandro & Cerchiello, Paola, 2024. "Measuring the impact of the EU health emergency response authority on the economic sectors and the public sentiment," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    64. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    65. Kwon, Tae Yeon & Lee, Yoonjung, 2018. "Industry specific defaults," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 45-58.
    66. Betz, Jennifer & Krüger, Steffen & Kellner, Ralf & Rösch, Daniel, 2020. "Macroeconomic effects and frailties in the resolution of non-performing loans," Journal of Banking & Finance, Elsevier, vol. 112(C).
    67. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    68. Alan White, 2018. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," Working Papers hal-01739310, HAL.
    69. Tobias Neumann, 2018. "Mortgages: estimating default correlation and forecasting default risk," Bank of England working papers 708, Bank of England.

  50. Koopman, Siem Jan & Kräussl, Roman & Lucas, André & Monteiro, André B., 2009. "Credit cycles and macro fundamentals," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 42-54, January.
    See citations under working paper version above.
  51. Sheremet, Oleg & Lucas, André, 2009. "Global loss diversification in the insurance sector," Insurance: Mathematics and Economics, Elsevier, vol. 44(3), pages 415-425, June.
    See citations under working paper version above.
  52. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    See citations under working paper version above.
  53. Konrad Banachewicz & André Lucas, 2008. "Quantile forecasting for credit risk management using possibly misspecified hidden Markov models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 566-586.
    See citations under working paper version above.
  54. Konrad Banachewicz & André Lucas & Aad van der Vaart, 2008. "Modelling Portfolio Defaults Using Hidden Markov Models with Covariates," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 155-171, March.
    See citations under working paper version above.
  55. Koopman, Siem Jan & Lucas, André, 2008. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 510-525.
    See citations under working paper version above.
  56. André Lucas & Arjen Siegmann, 2008. "The Effect of Shortfall as a Risk Measure for Portfolios with Hedge Funds," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(1‐2), pages 200-226, January.

    Cited by:

    1. Madalina Gabriela ANGHEL & Gyorgy BODO & Okwiet BARTEK, 2016. "Model of Static Portfolio Choices," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 49-53, January.
    2. Liu, Shuangzhe & Ma, Tiefeng & Polasek, Wolfgang, 2012. "Spatial System Estimators for Panel Models: A Sensitivity and Simulation Study," Economics Series 294, Institute for Advanced Studies.
    3. Zymler, Steve & Rustem, Berç & Kuhn, Daniel, 2011. "Robust portfolio optimization with derivative insurance guarantees," European Journal of Operational Research, Elsevier, vol. 210(2), pages 410-424, April.
    4. Ines Fortin & Jaroslava Hlouskova, 2015. "Downside loss aversion: Winner or loser?," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(2), pages 181-233, April.
    5. Fortin, Ines & Hlouskova, Jaroslava, 2012. "Optimal Asset Allocation under Quadratic Loss Aversion," Economics Series 291, Institute for Advanced Studies.

  57. Siem Jan Koopman & Marius Ooms & André Lucas & Kees van Montfort & Victor Van Der Geest, 2008. "Estimating systematic continuous‐time trends in recidivism using a non‐Gaussian panel data model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(1), pages 104-130, February.
    See citations under working paper version above.
  58. Menkveld, Albert J. & Koopman, Siem Jan & Lucas, Andre, 2007. "Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 213-225, April.

    Cited by:

    1. Menkveld, Albert J., 2006. "Splitting orders in overlapping markets: a study of cross-listed stocks," Serie Research Memoranda 0003, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    2. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    3. Korczak, Piotr & Phylaktis, Kate, 2010. "Related securities and price discovery: Evidence from NYSE-listed Non-U.S. stocks," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 566-584, September.
    4. Piotr Korczak & Kate Phylaktis, 2009. "Related Securities, Allocation of Attention and Price Discovery: Evidence from NYSE-Listed Non-U.S. Stocks," Bristol Economics Discussion Papers 09/612, School of Economics, University of Bristol, UK.
    5. Cédric Poutré & Georges Dionne & Gabriel Yergeau, 2022. "The Profitability of Lead-Lag Arbitrage at High-Frequency," Working Papers 22-5, HEC Montreal, Canada Research Chair in Risk Management.
    6. Naohiko Baba & Yasuaki Amatatsu, 2008. "Price discovery from cross-currency and FX swaps: a structural analysis," BIS Working Papers 264, Bank for International Settlements.
    7. Daures-Lescourret, Laurence & Fulop, Andras, 2022. "Standardization, transparency initiatives, and liquidity in the CDS market," Journal of Financial Markets, Elsevier, vol. 59(PA).
    8. Brugler, James & Khomyn, Marta & Putniņs̆, Tālis, 2025. "Benchmarking benchmarks," Journal of Financial Economics, Elsevier, vol. 168(C).
    9. Sait Ozturk & Michel van der Wel, 2014. "Intraday Price Discovery in Fragmented Markets," Tinbergen Institute Discussion Papers 14-027/III, Tinbergen Institute.
    10. Hendershott, Terrence & Menkveld, Albert J., 2014. "Price pressures," Journal of Financial Economics, Elsevier, vol. 114(3), pages 405-423.
    11. Wang, Jianxin & Yang, Minxian, 2011. "Housewives of Tokyo versus the gnomes of Zurich: Measuring price discovery in sequential markets," Journal of Financial Markets, Elsevier, vol. 14(1), pages 82-108, February.
    12. Michel van der Wel & Albert Menkveld & Asani Sarkar, 2009. "Are Market Makers Uninformed and Passive? Signing Trades in The Absence of Quotes," Tinbergen Institute Discussion Papers 09-046/3, Tinbergen Institute.
    13. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    14. Tao Chen, 2020. "Trade‐size clustering and informed trading in global markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 579-597, October.
    15. Eun Jung Lee, 2015. "High Frequency Trading in the Korean Index Futures Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(1), pages 31-51, January.
    16. Rzayev, Khaladdin & Sakkas, Athanasios & Urquhart, Andrew, 2025. "An adoption model of cryptocurrencies," European Journal of Operational Research, Elsevier, vol. 323(1), pages 253-266.
    17. Joel Hasbrouck, 2021. "Rejoinder on: Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 465-471.
    18. Dimpfl, Thomas & Schweikert, Karsten, 2023. "Information shares for markets with partially overlapping trading hours," Journal of Banking & Finance, Elsevier, vol. 154(C).
    19. Frijns, Bart & Schotman, Peter, 2009. "Price discovery in tick time," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 759-776, December.
    20. Alhaj-Yaseen, Yaseen S. & Lam, Eddery & Barkoulas, John T., 2014. "Price discovery for cross-listed firms with foreign IPOs," International Review of Financial Analysis, Elsevier, vol. 31(C), pages 80-87.
    21. Ibikunle, Gbenga & McGroarty, Frank & Rzayev, Khaladdin, 2020. "More heat than light: Investor attention and bitcoin price discovery," International Review of Financial Analysis, Elsevier, vol. 69(C).
    22. Fuertes, Ana-Maria & Phylaktis, Kate & Yan, Cheng, 2016. "Hot money in bank credit flows to emerging markets during the banking globalization era," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 29-52.
    23. Thomas Dimpfl & Robert Jung, 2011. "Financial market spillovers around the globe," Global Financial Markets Working Paper Series 20-2011, Friedrich-Schiller-University Jena.
    24. de Jong, F.C.J.M. & Schotman, P.C., 2010. "Price discovery in fragmented markets," Other publications TiSEM 4650a9e7-c4cf-41cf-a771-e, Tilburg University, School of Economics and Management.
    25. Zhou, Hao & Elliott, Robert J. & Kalev, Petko S., 2019. "Information or noise: What does algorithmic trading incorporate into the stock prices?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 27-39.
    26. Jaiswal-Dale, Ameeta & Jithendranathan, Thadavillil, 2009. "Transmission of shocks from cross-listed markets to the return and volatility of domestic stocks," Journal of Multinational Financial Management, Elsevier, vol. 19(5), pages 395-408, December.
    27. Gregory Boadu-Sebbe, 2022. "Effect of Exchange-Traded Funds Arbitrage Transactions on their Underlying Holdings," CERGE-EI Working Papers wp738, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    28. Cartea, Álvaro & Karyampas, Dimitrios, 2009. "Volatility and covariation of financial assets: a high-frequency analysis," DEE - Working Papers. Business Economics. WB wb097609, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    29. Marc Pomp & Suncica Vujic, 2008. "Rising health spending, new medical technology and the Baumol effect," CPB Discussion Paper 115, CPB Netherlands Bureau for Economic Policy Analysis.
    30. Brogaard, Jonathan & Hendershott, Terrence & Riordan, Ryan, 2013. "High frequency trading and price discovery," Working Paper Series 1602, European Central Bank.
    31. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    32. Paulo Pereira da Silva & Carlos Vieira & Isabel Vieira, 2018. "Central clearing and CDS market quality," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 731-753, June.
    33. Baba, Naohiko & Sakurai, Yuji, 2011. "When and how US dollar shortages evolved into the full crisis? Evidence from the cross-currency swap market," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1450-1463, June.
    34. Menkveld, Albert J. & Wang, Ting, 2013. "How do designated market makers create value for small-caps?," Journal of Financial Markets, Elsevier, vol. 16(3), pages 571-603.
    35. Yasuaki Amatatsu & Naohiko Baba, 2007. "Price Discovery from Cross-Currency and FX Swaps: A Structural Analysis," Bank of Japan Working Paper Series 07-E-12, Bank of Japan.
    36. Peter Koudijs, 2013. "The boats that did not sail: Asset Price Volatility and Market Efficiency in a Natural Experiment," NBER Working Papers 18831, National Bureau of Economic Research, Inc.
    37. Moulton, Pamela C. & Wei, Li, 2009. "A tale of two time zones: The impact of substitutes on cross-listed stock liquidity," Journal of Financial Markets, Elsevier, vol. 12(4), pages 570-591, November.
    38. Otsubo, Yoichi, 2014. "International cross-listing and price discovery under trading concentration in the domestic market: Evidence from Japanese shares," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 36-51.
    39. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).

  59. Lucas, Andre & Klaassen, Pieter, 2006. "Discrete versus continuous state switching models for portfolio credit risk," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 23-35, January.
    See citations under working paper version above.
  60. Arjen Siegmann & André Lucas, 2005. "Discrete-Time Financial Planning Models Under Loss-Averse Preferences," Operations Research, INFORMS, vol. 53(3), pages 403-414, June.

    Cited by:

    1. Gao, Jianjun & Xiong, Yan & Li, Duan, 2016. "Dynamic mean-risk portfolio selection with multiple risk measures in continuous-time," European Journal of Operational Research, Elsevier, vol. 249(2), pages 647-656.
    2. Michael Best & Robert Grauer & Jaroslava Hlouskova & Xili Zhang, 2014. "Loss-Aversion with Kinked Linear Utility Functions," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 45-65, June.
    3. Fortin, Ines & Hlouskova, Jaroslava, 2024. "Prospect theory and asset allocation," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 214-240.
    4. E. Borgonovo & L. Peccati, 2010. "Moment calculations for piecewise-defined functions: an application to stochastic optimization with coherent risk measures," Annals of Operations Research, Springer, vol. 176(1), pages 235-258, April.
    5. Liu, Shuangzhe & Ma, Tiefeng & Polasek, Wolfgang, 2012. "Spatial System Estimators for Panel Models: A Sensitivity and Simulation Study," Economics Series 294, Institute for Advanced Studies.
    6. Ines Fortin & Jaroslava Hlouskova, 2015. "Downside loss aversion: Winner or loser?," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(2), pages 181-233, April.
    7. Fortin, Ines & Hlouskova, Jaroslava, 2012. "Optimal Asset Allocation under Quadratic Loss Aversion," Economics Series 291, Institute for Advanced Studies.
    8. André Lucas & Arjen Siegmann, 2008. "The Effect of Shortfall as a Risk Measure for Portfolios with Hedge Funds," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(1‐2), pages 200-226, January.
    9. Shushang Zhu & Duan Li & Shouyang Wang, 2009. "Robust portfolio selection under downside risk measures," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 869-885.

  61. André Lucas & Siem Jan Koopman, 2005. "Business and default cycles for credit risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 311-323.
    See citations under working paper version above.
  62. Koopman, Siem Jan & Lucas, Andre & Klaassen, Pieter, 2005. "Empirical credit cycles and capital buffer formation," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 3159-3179, December.

    Cited by:

    1. Panicos Demetriades & David Fielding, 2009. "Information, Institutions and Banking Sector Development in West Africa," Discussion Papers in Economics 09/4, Division of Economics, School of Business, University of Leicester.
    2. Ferrer, Alex & Casals, José & Sotoca, Sonia, 2015. "Sample dependency during unconditional credit capital estimation," Finance Research Letters, Elsevier, vol. 15(C), pages 175-186.
    3. Siem Jan Koopman & André Lucas & Robert Daniels, 2005. "A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk," Tinbergen Institute Discussion Papers 05-060/4, Tinbergen Institute.
    4. Repullo, R. & Suarez, J., 2010. "The Procyclical Effects of Bank Capital Regulation," Other publications TiSEM 0b64ec97-95cc-45bf-b271-4, Tilburg University, School of Economics and Management.
    5. Cipollini, Andrea & Missaglia, Giuseppe, 2007. "Dynamic Factor analysis of industry sector default rates and implication for Portfolio Credit Risk Modelling," MPRA Paper 3582, University Library of Munich, Germany.
    6. Romila Qamar & Shahid Mansoor Hashmi & Jaleel Ahmed & Ahmed N.K. AlFarra, 2016. "Are Capital Buffers Countercyclical ? An Evidence From Pakistan," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(61), pages 123-146, September.
    7. Correa, Arnildo & Marins, Jaqueline & Neves, Myrian & da Silva, Antonio Carlos, 2014. "Credit Default and Business Cycles: An Empirical Investigation of Brazilian Retail Loans," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(3), September.
    8. Alejandro Ferrer Pérez & José Casals Carro & Sonia Sotoca López, 2014. "Conditional coverage and its role in determining and assessing long-term capital requirements," Documentos de Trabajo del ICAE 2014-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. Rebekka Topp & Robert Perl, 2010. "Through‐the‐Cycle Ratings Versus Point‐in‐Time Ratings and Implications of the Mapping Between Both Rating Types," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 19(1), pages 47-61, February.
    10. Koopman, Siem Jan & Lucas, Andre & Monteiro, Andre, 2008. "The multi-state latent factor intensity model for credit rating transitions," Journal of Econometrics, Elsevier, vol. 142(1), pages 399-424, January.
    11. Daniel Roesch & Harald Scheule, 2011. "Securitization Rating Performance and Agency Incentives," Working Papers 182011, Hong Kong Institute for Monetary Research.
    12. Daniel Rösch & Harald Scheule, 2014. "Forecasting Mortgage Securitization Risk Under Systematic Risk and Parameter Uncertainty," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 563-586, September.
    13. Jian He & Asma Khedher & Peter Spreij, 2024. "Calibration of the rating transition model for high and low default portfolios," Papers 2405.00576, arXiv.org.
    14. Haibin Zhu, 2007. "Capital regulation and banks' financial decisions," BIS Working Papers 232, Bank for International Settlements.
    15. Claudio Borio & Haibin Zhu, 2008. "Capital regulation, risk-taking and monetary policy: a missing link in the transmission mechanism?," BIS Working Papers 268, Bank for International Settlements.
    16. Romila Qamar & Shahid Mansoor Hashmi & Mughees Tahir Bhalli, 2016. "Are Basel Capital Standards Implemented Successfully in Pakistan?," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 19(62), pages 119-152, December.
    17. Ji, Tingting, 2004. "Essays on consumer portfolio choice and credit risk," MPRA Paper 3161, University Library of Munich, Germany.
    18. Cifter, Atilla & Yilmazer, Sait & Cifter, Elif, 2009. "Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey," Economic Modelling, Elsevier, vol. 26(6), pages 1382-1388, November.
    19. Ferrer, Alex & Casals, José & Sotoca, Sonia, 2015. "Capital cyclicality, conditional coverage and long-term capital assessment," Finance Research Letters, Elsevier, vol. 15(C), pages 246-256.
    20. Rafael Repullo & Javier Suarez, 2008. "The Procyclical Effects of Basel II," Working Papers wp2008_0809, CEMFI.
    21. Bank for International Settlements, 2011. "Portfolio and risk management for central banks and sovereign wealth funds," BIS Papers, Bank for International Settlements, number 58.
    22. Ferrer, Alex & Casals, José & Sotoca, Sonia, 2016. "Efficient estimation of unconditional capital by Monte Carlo simulation," Finance Research Letters, Elsevier, vol. 16(C), pages 75-84.
    23. Jaehoon Hahn & Ho-Seong Moon, 2016. "Credit Cycle and the Macroeconomy: Empirical Evidence from Korea," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 22(4), pages 76-108, December.
    24. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," IJFS, MDPI, vol. 2(1), pages 1-22, March.
    25. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    26. Lützenkirchen, Kristina & Rösch, Daniel & Scheule, Harald, 2014. "Asset portfolio securitizations and cyclicality of regulatory capital," European Journal of Operational Research, Elsevier, vol. 237(1), pages 289-302.
    27. Chi Xie & Changqing Luo & Xiang Yu, 2011. "Financial distress prediction based on SVM and MDA methods: the case of Chinese listed companies," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(3), pages 671-686, April.
    28. Alejandro Ferrer Pérez & José Casals Carro & Sonia Sotoca López, 2014. "A new approach to the unconditional measurement of default risk," Documentos de Trabajo del ICAE 2014-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    29. Ana Clara Bueno Teixeira Feitosa Noronha & Daniel Oliveira Cajueiro & Benjamin Miranda Tabak, 2011. "Bank Capital Buffers, Lending Growth Andeconomic Cycle: Empirical Evidence For Brazil," Anais do XXXVIII Encontro Nacional de Economia [Proceedings of the 38th Brazilian Economics Meeting] 035, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    30. Georges Dionne & Pascal François & Olfa Maalaoui Chun, 2009. "Detecting Regime Shifts in Corporate Credit Spreads," Cahiers de recherche 0929, CIRPEE.

  63. Abadir, Karim M. & Lucas, Andre, 2004. "A comparison of minimum MSE and maximum power for the nearly integrated non-Gaussian model," Journal of Econometrics, Elsevier, vol. 119(1), pages 45-71, March.
    See citations under working paper version above.
  64. Philip Hans Franses & Dick van Dijk & Andre Lucas, 2004. "Short patches of outliers, ARCH and volatility modelling," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 221-231.
    See citations under working paper version above.
  65. Andre Lucas & Pieter Klaassen & Peter Spreij & Stefan Straetmans, 2003. "Tail behaviour of credit loss distributions for general latent factor models," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(4), pages 337-357.
    See citations under working paper version above.
  66. Marc G. Genton & André Lucas, 2003. "Comprehensive definitions of breakdown points for independent and dependent observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 81-94, February.
    See citations under working paper version above.
  67. Boswijk, H. Peter & Lucas, Andre, 2002. "Semi-nonparametric cointegration testing," Journal of Econometrics, Elsevier, vol. 108(2), pages 253-280, June.
    See citations under working paper version above.
  68. Lucas, Andre & van Dijk, Ronald & Kloek, Teun, 2002. "Stock selection, style rotation, and risk," Journal of Empirical Finance, Elsevier, vol. 9(1), pages 1-34, January.
    See citations under working paper version above.
  69. Lucas, Andre & Klaassen, Pieter & Spreij, Peter & Straetmans, Stefan, 2001. "An analytic approach to credit risk of large corporate bond and loan portfolios," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1635-1664, September.
    See citations under working paper version above.
  70. Lucas, Andre, 2001. "Evaluating the Basle Guidelines for Backtesting Banks' Internal Risk Management Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 33(3), pages 826-846, August.

    Cited by:

    1. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2013. "A comparison of the original and revised Basel market risk frameworks for regulating bank capital," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 249-268.
    2. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "When more is less: Using multiple constraints to reduce tail risk," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2693-2716.
    3. Colliard, Jean-Edouard, 2017. "Strategic Selection of Risk Models and Bank Capital Regulation," HEC Research Papers Series 1229, HEC Paris, revised 29 Nov 2017.
    4. Gordon J. Alexander & Alexandre M. Baptista & Shu Yan, 2015. "On Regulatory Responses to the Recent Crisis: An Assessment of the Basel Market Risk Framework and the Volcker Rule," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 24(2-3), pages 87-125, May.
    5. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2014. "Bank regulation and international financial stability: A case against the 2006 Basel framework for controlling tail risk in trading books," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 107-130.
    6. Bernardo da Veiga & Felix Chan & Michael McAleer, 2009. "It Pays to Violate: How Effective are the Basel Accord Penalties?," CIRJE F-Series CIRJE-F-683, CIRJE, Faculty of Economics, University of Tokyo.
    7. Christophe Pérignon & Zi Yin Deng & Zhi Jun Wang, 2008. "Do banks overstate their Value-at-Risk?," Post-Print hal-00461046, HAL.
    8. Sabiwalsky, Ralf, 2012. "Does Basel II pillar 3 risk exposure data help to identify risky banks?," SFB 649 Discussion Papers 2012-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "Bank regulation and stability: An examination of the Basel market risk framework," Discussion Papers 09/2012, Deutsche Bundesbank.
    10. Gyöngyi Bugár & Anita Ratting, 2016. "Revision of the quantification of market risk in the Basel III regulatory framework," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(1), pages 33-50.
    11. Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
    12. Orla Mccullagh & Mark Cummins & Sheila Killian, 2023. "The Fundamental Review of the Trading Book: Implications for Portfolio and Risk Management in the Banking Sector," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(7), pages 1785-1816, October.
    13. Dal Borgo, Mariela, 2022. "Internal models for deposits: Effects on banks' capital and interest rate risk of assets," Journal of Banking & Finance, Elsevier, vol. 135(C).
    14. Darius Palia & Robert Porter, 2003. "Contemporary Issues in Regulatory Risk Management of Commercial Banks," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 12(4), pages 223-256, September.
    15. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2021. "Regulation of bank proprietary trading post 2007–09 crisis: An examination of the Basel framework and Volcker rule," Journal of International Money and Finance, Elsevier, vol. 119(C).
    16. Gordon J. Alexander & Alexandre M. Baptista, 2017. "Bank Capital Regulation of Trading Portfolios: An Assessment of the Basel Framework," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 603-634, June.
    17. Al-Hadi, Ahmed & Al-Yahyaee, Khamis Hamed & Hussain, Syed Mujahid & Taylor, Grantley, 2019. "Market risk disclosures and corporate governance structure: Evidence from GCC financial firms," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 136-150.
    18. Erik Larson, 2017. "Demand for credit, international financial legitimacy, and vulnerability to crises: Regulatory change and the social origins of Iceland's collapse," Regulation & Governance, John Wiley & Sons, vol. 11(2), pages 185-202, June.

  71. Taylor, Nick & Dijk, Dick van & Franses, Philip Hans & Lucas, Andre, 2000. "SETS, arbitrage activity, and stock price dynamics," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1289-1306, August.
    See citations under working paper version above.
  72. Abadir, Karim M. & Lucas, Andre, 2000. "Quantiles for t-statistics based on M-estimators of unit roots," Economics Letters, Elsevier, vol. 67(2), pages 131-137, May.

    Cited by:

    1. Carsten Colombier, 2011. "Does the composition of public expenditure affect economic growth? Evidence from the Swiss case," Applied Economics Letters, Taylor & Francis Journals, vol. 18(16), pages 1583-1589.
    2. Carstensen, Kai, 2003. "The finite-sample performance of robust unit root tests," Munich Reprints in Economics 19943, University of Munich, Department of Economics.
    3. Christis Katsouris, 2022. "Asymptotic Theory for Unit Root Moderate Deviations in Quantile Autoregressions and Predictive Regressions," Papers 2204.02073, arXiv.org, revised Aug 2023.
    4. Abadir, Karim M. & Lucas, Andre, 2004. "A comparison of minimum MSE and maximum power for the nearly integrated non-Gaussian model," Journal of Econometrics, Elsevier, vol. 119(1), pages 45-71, March.
    5. H. Peter Boswijk & Jurgen A. Doornik, 1999. "Distribution Approximations for Cointegration Tests with Stationary Exogenous Regressors," Tinbergen Institute Discussion Papers 99-013/4, Tinbergen Institute.

  73. Lucas, Andre, 2000. "A Note on Optimal Estimation from a Risk-Management Perspective under Possibly Misspecified Tail Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 31-39, January.
    See citations under working paper version above.
  74. Van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(2), pages 217-235, April.
    See citations under working paper version above.
  75. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.
    See citations under working paper version above.
  76. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.

    Cited by:

    1. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. van Heerde, H.J. & Dekimpe, M.G. & Putsis, W.P., 2004. "Marketing Models and the Lucas Critique," ERIM Report Series Research in Management ERS-2004-080-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Trost, Robert & Silk, Julian, 2003. "Quantitative Models in Marketing Research,: Philip Hans Franses and Richard Paap (Eds.), Cambridge University Press, Cambridge, UK. (2001), 206 pp. - ISBN 0-521-80166-4, [UK pound]30.00," International Journal of Forecasting, Elsevier, vol. 19(3), pages 535-538.
    4. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    6. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "The European Consumer: United In Diversity?," ERIM Report Series Research in Management ERS-2005-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Harald Van Heerde & Kristiaan Helsen & Marnik G. Dekimpe, 2007. "The Impact of a Product-Harm Crisis on Marketing Effectiveness," Marketing Science, INFORMS, vol. 26(2), pages 230-245, 03-04.
    8. Dekimpe, M.G. & Hanssens, D.M. & Nijs, V.R. & Steenkamp, J-B.E.M., 2003. "Measuring Short- and Long-run Promotional Effectiveness on Scanner Data Using Persistence Modeling," ERIM Report Series Research in Management ERS-2003-087-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    9. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    10. Janghyeok Yoon & Kwangsoo Kim, 2012. "Detecting signals of new technological opportunities using semantic patent analysis and outlier detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 445-461, February.
    11. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2006. "Robust Artificial Neural Networks for Pricing of European Options," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 329-351, May.
    13. Dekimpe, M.G. & Hanssens, D.M., 2003. "Persistence Modeling for Assessing Marketing Strategy Performance," ERIM Report Series Research in Management ERS-2003-088-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2007. "Consumer confidence in Europe : United in diversity," Other publications TiSEM ea8c3268-2c0b-4fcc-9d4a-6, Tilburg University, School of Economics and Management.

  77. Franses, Philip Hans & Lucas, Andre, 1998. "Outlier Detection in Cointegration Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 459-468, October.

    Cited by:

    1. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Georgiev, Iliyan, 2010. "Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables," Journal of Econometrics, Elsevier, vol. 158(1), pages 37-50, September.
    3. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    4. Winkelried, Diego, 2012. "Traspaso del tipo de cambio y metas de inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 23, pages 9-24.
    5. Alfred A. Haug, 2002. "Temporal Aggregation and the Power of Cointegration Tests: a Monte Carlo Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 399-412, September.
    6. Diego Winkelried, 2014. "Exchange rate pass-through and inflation targeting in Peru," Empirical Economics, Springer, vol. 46(4), pages 1181-1196, June.
    7. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    9. Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
    10. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    11. Hong Li & Yanlin Shi, 2022. "Robust information share measures with an application on the international crude oil markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 555-579, April.
    12. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    13. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, Enero-Abr.
    14. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
    15. Andreas Benedictow & Pål Boug, 2013. "Trade liberalisation and exchange rate pass-through: the case of textiles and wearing apparels," Empirical Economics, Springer, vol. 45(2), pages 757-788, October.
    16. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    17. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    18. Miguel Arranz & Alvaro Escribano, 2004. "Outliers - robust ECM cointegration tests based on the trend components," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(4), pages 243-266, December.
    19. Borbély, Dóra & Meier, Carsten-Patrick, 2003. "Macroeconomic interval forecasting: the case of assessing the risk of deflation in Germany," Kiel Working Papers 1153, Kiel Institute for the World Economy (IfW Kiel).
    20. Barry Falk & Chun-Hsuan Wang, 2003. "Testing long-run PPP with infinite-variance returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 471-484.
    21. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    22. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    23. Francisco Blasques & Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2024. "Robust Multivariate Observation-Driven Filtering for a Common Stochastic Trend: Theory and Application," Tinbergen Institute Discussion Papers 24-062/III, Tinbergen Institute.
    24. Carlos Andrés Perilla Castro, 2001. "Capitales mínimos de los establecimientos de crédito," Monetaria, CEMLA, vol. 0(3), pages 271-353, julio-sep.
    25. Katarzyna Rosiak-Lada, 2008. "Stylized Facts of Macroeconomics: the Polish Experience," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 20.
    26. Eser, Fabian & Schwaab, Bernd, 2016. "Evaluating the impact of unconventional monetary policy measures: Empirical evidence from the ECB׳s Securities Markets Programme," Journal of Financial Economics, Elsevier, vol. 119(1), pages 147-167.
    27. Luis A. Rivas & José de Jesús Rojas, 2001. "Precios relativos, inflación subyacente y metas de inflación: un análisis para Nicaragua," Monetaria, CEMLA, vol. 0(3), pages 355-380, julio-sep.
    28. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    29. Benner Joachim & Meier Carsten-Patrick, 2004. "Prognosegüte alternativer Früh Indikatoren für die Konjunktur in Deutschland / Forecasting Performance of Alternative Indicators for the German Economy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 639-652, December.
    30. Meier, Carsten-Patrick, 2004. "Investigating the impact of an appreciation of the euro in a small macroeconometric model of Germany and the euro area," Kiel Working Papers 1204, Kiel Institute for the World Economy (IfW Kiel).
    31. Daniel G. Garcés Díaz, 2001. "Determinación del nivel de precios y la dinámica inflacionaria en México," Monetaria, CEMLA, vol. 0(3), pages 241-269, julio-sep.
    32. Mosab I. Tabash & Mujeeb Saif Mohsen Al-Absy & Azzam Hannoon, 2024. "Modeling the Nexus between European Carbon Emission Trading and Financial Market Returns: Practical Implications for Carbon Risk Reduction and Hedging," JRFM, MDPI, vol. 17(4), pages 1-29, April.

  78. Andre Lucas, 1998. "Inference on cointegrating ranks using lr and lm tests based on pseudo-likelihoods," Econometric Reviews, Taylor & Francis Journals, vol. 17(2), pages 185-214.

    Cited by:

    1. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Georgiev, Iliyan, 2010. "Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables," Journal of Econometrics, Elsevier, vol. 158(1), pages 37-50, September.
    3. Anil K. Bera & Yannis Bilias, 2024. "Three Scores and 15 Years (1948-2023) of Rao's Score Test: A Brief History," Papers 2406.19956, arXiv.org, revised Oct 2024.
    4. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    5. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    6. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    7. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    8. Al-Sadoon, Majid M., 2017. "A unifying theory of tests of rank," Journal of Econometrics, Elsevier, vol. 199(1), pages 49-62.
    9. Bera Anil K. & Bilias Yannis & Yoon Mann J. & Taşpınar Süleyman & Doğan Osman, 2020. "Adjustments of Rao’s Score Test for Distributional and Local Parametric Misspecifications," Journal of Econometric Methods, De Gruyter, vol. 9(1), pages 1-29, January.
    10. Martin Wagner, 2004. "A Comparison of Johansen's, Bierens’ and the Subspace Algorithm Method for Cointegration Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 399-424, July.
    11. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Juhl, Ted, 2001. "Cointegration analysis using M estimators," Economics Letters, Elsevier, vol. 71(2), pages 149-154, May.
    13. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    14. Boswijk, H. Peter & Lucas, Andre, 2002. "Semi-nonparametric cointegration testing," Journal of Econometrics, Elsevier, vol. 108(2), pages 253-280, June.
    15. Juhl, Ted & Xiao, Zhijie, 2005. "Testing for cointegration using partially linear models," Journal of Econometrics, Elsevier, vol. 124(2), pages 363-394, February.
    16. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.

  79. Lucas, André, 1997. "Cointegration Testing Using Pseudolikelihood Ratio Tests," Econometric Theory, Cambridge University Press, vol. 13(2), pages 149-169, April.

    Cited by:

    1. Carlomagno, Guillermo & Espasa, Antoni, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Georgiev, Iliyan, 2010. "Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables," Journal of Econometrics, Elsevier, vol. 158(1), pages 37-50, September.
    3. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    4. Lorenzo Camponovo & Olivier Scaillet & Fabio Trojani, 2016. "Predictability Hidden by Anomalous Observations," Papers 1612.05072, arXiv.org.
    5. Vlaar, Peter J. G., 2000. "Value at risk models for Dutch bond portfolios," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1131-1154, July.
    6. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    7. Carstensen, Kai, 2003. "Nonstationary term premia and cointegration of the term structure," Economics Letters, Elsevier, vol. 80(3), pages 409-413, September.
    8. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    9. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    10. Helmut Herwartz & Helmut Lütkepohl, 2000. "Multivariate volatility analysis of VW stock prices," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(1), pages 35-54, March.
    11. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    12. H. Peter Boswijk & Jurgen A. Doornik, 1999. "Distribution Approximations for Cointegration Tests with Stationary Exogenous Regressors," Tinbergen Institute Discussion Papers 99-013/4, Tinbergen Institute.
    13. Arranz, Miguel A. & Escribano, Álvaro, 1998. "Detrending procedures and cointegration testing: ECM tests under structural breaks," DES - Working Papers. Statistics and Econometrics. WS 4551, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Al-Sadoon, Majid M., 2017. "A unifying theory of tests of rank," Journal of Econometrics, Elsevier, vol. 199(1), pages 49-62.
    15. H. Peter Boswijk, 2000. "Testing for a Unit Root with Near-Integrated Volatility," Econometric Society World Congress 2000 Contributed Papers 1101, Econometric Society.
    16. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    17. Miguel Arranz & Alvaro Escribano, 2004. "Outliers - robust ECM cointegration tests based on the trend components," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(4), pages 243-266, December.
    18. Hubrich, Kirstin & Lütkepohl, Helmut & Saikkonen, Pentti, 1998. "A review of systemscointegration tests," SFB 373 Discussion Papers 1998,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    19. Barry Falk & Chun-Hsuan Wang, 2003. "Testing long-run PPP with infinite-variance returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 471-484.
    20. Juhl, Ted, 2001. "Cointegration analysis using M estimators," Economics Letters, Elsevier, vol. 71(2), pages 149-154, May.
    21. H. Peter Boswijk & Franc Klaassen, 2005. "Why Frequency Matters for Unit Root Testing," Tinbergen Institute Discussion Papers 04-119/4, Tinbergen Institute.
    22. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    23. Francisco Blasques & Janneke van Brummelen & Paolo Gorgi & Siem Jan Koopman, 2024. "Robust Multivariate Observation-Driven Filtering for a Common Stochastic Trend: Theory and Application," Tinbergen Institute Discussion Papers 24-062/III, Tinbergen Institute.
    24. Boswijk, H. Peter & Lucas, Andre, 2002. "Semi-nonparametric cointegration testing," Journal of Econometrics, Elsevier, vol. 108(2), pages 253-280, June.
    25. Juhl, Ted & Xiao, Zhijie, 2005. "Testing for cointegration using partially linear models," Journal of Econometrics, Elsevier, vol. 124(2), pages 363-394, February.
    26. Franses, Philip Hans & Lucas, André, 1997. "Outlier robust cointegration analysis," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    27. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    28. Lucia Parisio & Matteo Pelagatti, 2019. "Market coupling between electricity markets: theory and empirical evidence for the Italian–Slovenian interconnection," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 36(2), pages 527-548, July.

  80. Lucas, Andre, 1995. "An outlier robust unit root test with an application to the extended Nelson-Plosser data," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 153-173.

    Cited by:

    1. So, Beong Soo & Shin, Dong Wan, 2001. "An invariant sign test for random walks based on recursive median adjustment," Journal of Econometrics, Elsevier, vol. 102(2), pages 197-229, June.
    2. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    3. Franses, Philip Hans & Kleibergen, Frank, 1996. "Unit roots in the Nelson-Plosser data: Do they matter for forecasting?," International Journal of Forecasting, Elsevier, vol. 12(2), pages 283-288, June.
    4. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    5. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    6. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Discussion Paper 2006-20, Tilburg University, Center for Economic Research.
    7. Carstensen, Kai, 2003. "The finite-sample performance of robust unit root tests," Munich Reprints in Economics 19943, University of Munich, Department of Economics.
    8. Shin, Dong Wan & So, Beong Soo, 1999. "New tests for unit roots in autoregressive processes with possibly infinite variance errors," Statistics & Probability Letters, Elsevier, vol. 44(4), pages 387-397, October.
    9. Falk, Barry, 1995. "A Comparison of OLS and WS unit Root Test Results," ISU General Staff Papers 199506010700001268, Iowa State University, Department of Economics.
    10. Susan Sunila Sharma & Lutzardo Tobing & Prayudhi Azwar, 2018. "Understanding Indonesia’S Macroeconomic Data: What Do We Know And What Are The Implications?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 21(2), pages 217-250, October.
    11. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    12. Gabriel Rodriguez & Dionisio Ramirez, 2014. "A Note on the Size of the ADF Test with Additive Outliers and Fractional Errors. A Reappraisal about the (Non)Stationarity of the Latin-American Inflation Series," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 37(73), pages 113-132.
    13. Dias, Daniel A. & Marques, Carlos Robalo, 2010. "Using mean reversion as a measure of persistence," Economic Modelling, Elsevier, vol. 27(1), pages 262-273, January.
    14. V. A. Reisen & C. Lévy-Leduc & M. Bourguignon & H. Boistard, 2017. "Robust Dickey–Fuller tests based on ranks for time series with additive outliers," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 115-131, January.
    15. Natalia Bailey & Liudas Giraitis, 2015. "Spectral Approach to Parameter-Free Unit Root Testing," Working Papers 746, Queen Mary University of London, School of Economics and Finance.
    16. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    17. Arranz, Miguel A. & Escribano, Álvaro, 1998. "Detrending procedures and cointegration testing: ECM tests under structural breaks," DES - Working Papers. Statistics and Econometrics. WS 4551, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Rothenberg, Thomas J. & Stock, James H., 1997. "Inference in a nearly integrated autoregressive model with nonnormal innovations," Journal of Econometrics, Elsevier, vol. 80(2), pages 269-286, October.
    19. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, Enero-Abr.
    20. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    21. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
    22. Arranz, Miguel A. & Escribano, Álvaro & Mármol, Francesc, 2002. "Effects of Applying Linear and Nonlinear Filters on Tests for Unit Roots with Additive Outliers," UC3M Working papers. Economics we20091101, Universidad Carlos III de Madrid. Departamento de Economía.
    23. Miguel Arranz & Alvaro Escribano, 2004. "Outliers - robust ECM cointegration tests based on the trend components," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(4), pages 243-266, December.
    24. Xiao, Zhijie, 2004. "Estimating average economic growth in time series data with persistency," Journal of Macroeconomics, Elsevier, vol. 26(4), pages 699-724, December.
    25. PREMINGER, Arie & SAKATA, Shinichi, 2005. "A model selection method for S-estimation," LIDAM Discussion Papers CORE 2005073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Aparicio, Felipe M. & Escribano, Álvaro & García, Ana, 2004. "A range unit root test," DES - Working Papers. Statistics and Econometrics. WS ws041104, Universidad Carlos III de Madrid. Departamento de Estadística.
    27. Saban Nazlioglu & Dogukan Tarakci & Emre Kilic, 2024. "Nelson and Plosser revisited: macroeconomic and financial stability of Turkey," Empirical Economics, Springer, vol. 66(6), pages 2557-2592, June.
    28. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    29. Abadir, Karim M. & Lucas, Andre, 2000. "Quantiles for t-statistics based on M-estimators of unit roots," Economics Letters, Elsevier, vol. 67(2), pages 131-137, May.
    30. Čίžek, Pavel & Härdle, Wolfgang Karl, 2006. "Robust econometrics," SFB 649 Discussion Papers 2006-050, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    31. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    32. Hoek, Henk & Lucas, Andre & van Dijk, Herman K., 1995. "Classical and Bayesian aspects of robust unit root inference," Journal of Econometrics, Elsevier, vol. 69(1), pages 27-59, September.
    33. Lima Luiz Renato & Xiao Zhijie, 2010. "Testing Unit Root Based on Partially Adaptive Estimation," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-34, June.
    34. Dong Wan Shin & Oesook Lee, 2004. "M‐Estimation for regressions with integrated regressors and arma errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 283-299, March.
    35. Franses, Philip Hans & Lucas, André, 1997. "Outlier robust cointegration analysis," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    36. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    37. Gabriel Rodriguez & Dionisio Ramirez, 2013. "A comparison between Tau-d and the procedure TRAMO-SEATS is also included," Documentos de Trabajo / Working Papers 2013-355, Departamento de Economía - Pontificia Universidad Católica del Perú.
    38. Luiz Lima & Jaime de Jesus Filho, 2008. "Further investigation of the uncertain trend in US GDP," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1207-1216.
    39. Hella, Heikki, 2003. "On robust ESACF identification of mixed ARIMA models," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2003_027, December.

  81. Groenendijk, Patrick A. & Lucas, Andre & de Vries, Casper G., 1995. "A note on the relationship between GARCH and symmetric stable processes," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 253-264, September.

    Cited by:

    1. Iglesias, Emma M. & Linton, Oliver, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," UC3M Working papers. Economics we094726, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2002. "Stationarity of stable power-GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 97-107, January.
    3. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2000. "Diagnosing and treating the fat tails in financial returns data," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 389-416, November.
    4. Degiannakis, Stavros & Livada, Alexandra & Panas, Epaminondas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," MPRA Paper 80464, University Library of Munich, Germany.
    5. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    6. Roman Horváth & Boril Sopov, 2015. "GARCH Models, Tail Indexes and Error Distributions: An Empirical Investigation," Working Papers IES 2015/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2015.
    7. Broussard, John Paul, 2001. "Extreme-value and margin setting with and without price limits," The Quarterly Review of Economics and Finance, Elsevier, vol. 41(3), pages 365-385.
    8. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    9. Paolella, Marc S., 2017. "Asymmetric stable Paretian distribution testing," Econometrics and Statistics, Elsevier, vol. 1(C), pages 19-39.
    10. J. Huston McCulloch & Prasad V. Bidarkota, 2003. "Signal Extraction can Generate Volatility Clusters," Computing in Economics and Finance 2003 59, Society for Computational Economics.
    11. J. Huston McCulloch & Prasad V. Bidarkota, 2002. "Signal Extraction Can Generate Volatility Clusters From IID Shocks," Working Papers 02-04, Ohio State University, Department of Economics.

  82. Hoek, Henk & Lucas, Andre & van Dijk, Herman K., 1995. "Classical and Bayesian aspects of robust unit root inference," Journal of Econometrics, Elsevier, vol. 69(1), pages 27-59, September.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    2. Carstensen, Kai, 2003. "The finite-sample performance of robust unit root tests," Munich Reprints in Economics 19943, University of Munich, Department of Economics.
    3. Marriott, John & Newbold, Paul, 2000. "The strength of evidence for unit autoregressive roots and structural breaks: A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 98(1), pages 1-25, September.
    4. Jussi Tolvi, 2001. "Outliers in eleven Finnish macroeconomic time series," Finnish Economic Papers, Finnish Economic Association, vol. 14(1), pages 14-32, Spring.
    5. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    6. César Eduardo Tamayo T. & Andr�s Mauricio Vargas P., 2007. "Flujos de capital y frenazos súbitos: teoría, historia y una nueva estimación," Coyuntura Económica, Fedesarrollo.
    7. Franses, Philip Hans & Kloek, Teun & Lucas, Andre, 1998. "Outlier robust analysis of long-run marketing effects for weekly scanning data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 293-315, November.
    8. Bibiana Lanzilotta & Adrián Fernández & Gonzalo Zunino, 2008. "Evaluación de las proyecciones de analistas: la encuesta de expectativas de inflación del banco central," Monetaria, CEMLA, vol. 0(1), pages 1-25, enero-mar.
    9. Aparicio, Felipe M. & Escribano, Álvaro & García, Ana, 2004. "A range unit root test," DES - Working Papers. Statistics and Econometrics. WS ws041104, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Abadir, Karim M. & Lucas, Andre, 2000. "Quantiles for t-statistics based on M-estimators of unit roots," Economics Letters, Elsevier, vol. 67(2), pages 131-137, May.
    11. Palandri, Alessandro, 2024. "Reconciling interest rates evidence with theory: Rejecting unit roots when the HD(1) is a competing alternative," Journal of Banking & Finance, Elsevier, vol. 161(C).
    12. Valeria C. Castellanos, 2008. "Comisiones en cajeros automáticos y su relación con el tamaño de la red en México," Monetaria, CEMLA, vol. 0(1), pages 57-92, enero-mar.
    13. Franses, Philip Hans & Lucas, André, 1997. "Outlier robust cointegration analysis," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    14. Enrique Cuervo Guzmán, 2008. "Bayesian analysis of the unit root in real exchange rates: the NAFTA case," Monetaria, CEMLA, vol. 0(1), pages 93-144, enero-mar.
    15. van Dijk, D.J.C. & Franses, Ph.H.B.F. & Lucas, A., 1996. "Testing for Smooth Transition Nonlinearity in the Presence of Outliers," Econometric Institute Research Papers EI 9622-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Luiz Lima & Jaime de Jesus Filho, 2008. "Further investigation of the uncertain trend in US GDP," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1207-1216.
    17. Hella, Heikki, 2003. "On robust ESACF identification of mixed ARIMA models," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2003_027, December.

  83. Lucas, André, 1995. "Unit Root Tests Based on M Estimators," Econometric Theory, Cambridge University Press, vol. 11(2), pages 331-346, February.

    Cited by:

    1. So, Beong Soo & Shin, Dong Wan, 2001. "An invariant sign test for random walks based on recursive median adjustment," Journal of Econometrics, Elsevier, vol. 102(2), pages 197-229, June.
    2. Avdoulas, Christos & Bekiros, Stelios & Boubaker, Sabri, 2016. "Detecting nonlinear dependencies in eurozone peripheral equity markets: A multistep filtering approach," Economic Modelling, Elsevier, vol. 58(C), pages 580-587.
    3. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    4. Ted Juhl & Zhijie Xiao, 2000. "N-Consistent Semiparametric Regression: Partially Linear Models with Unit Roots," Econometric Society World Congress 2000 Contributed Papers 1532, Econometric Society.
    5. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    6. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    7. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    8. Lorenzo Camponovo & Olivier Scaillet & Fabio Trojani, 2016. "Predictability Hidden by Anomalous Observations," Papers 1612.05072, arXiv.org.
    9. Carstensen, Kai, 2003. "The finite-sample performance of robust unit root tests," Munich Reprints in Economics 19943, University of Munich, Department of Economics.
    10. Shin, Dong Wan & So, Beong Soo, 1999. "New tests for unit roots in autoregressive processes with possibly infinite variance errors," Statistics & Probability Letters, Elsevier, vol. 44(4), pages 387-397, October.
    11. Christis Katsouris, 2022. "Asymptotic Theory for Unit Root Moderate Deviations in Quantile Autoregressions and Predictive Regressions," Papers 2204.02073, arXiv.org, revised Aug 2023.
    12. Olivier Darné & Amélie Charles, 2012. "A note on the uncertain trend in US real GNP: Evidence from robust unit root tests," Economics Bulletin, AccessEcon, vol. 32(3), pages 2399-2406.
    13. Ling, S. & McAleer, M., 2001. "Regression Quantiles for Unstable Autoregressive Models," ISER Discussion Paper 0526, Institute of Social and Economic Research, The University of Osaka.
    14. Xiao, Zhijie, 2012. "Robust inference in nonstationary time series models," Journal of Econometrics, Elsevier, vol. 169(2), pages 211-223.
    15. Xuedong Wu & Jeffrey H. Dorfman & Berna Karali, 2018. "The impact of data frequency on market efficiency tests of commodity futures prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 696-714, June.
    16. Abadir, Karim M. & Lucas, Andre, 2004. "A comparison of minimum MSE and maximum power for the nearly integrated non-Gaussian model," Journal of Econometrics, Elsevier, vol. 119(1), pages 45-71, March.
    17. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    18. Arranz, Miguel A. & Escribano, Álvaro, 1998. "Detrending procedures and cointegration testing: ECM tests under structural breaks," DES - Working Papers. Statistics and Econometrics. WS 4551, Universidad Carlos III de Madrid. Departamento de Estadística.
    19. Rothenberg, Thomas J. & Stock, James H., 1997. "Inference in a nearly integrated autoregressive model with nonnormal innovations," Journal of Econometrics, Elsevier, vol. 80(2), pages 269-286, October.
    20. Ke Zhu & Shiqing Ling, 2015. "LADE-Based Inference for ARMA Models With Unspecified and Heavy-Tailed Heteroscedastic Noises," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 784-794, June.
    21. Kai Carstensen & Julia Hawellek, 2003. "Forecasting inflation from the term structure," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 139(2), pages 306-323, June.
    22. Ziping Zhao & Daniel P. Palomar, 2017. "Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model," Papers 1710.05513, arXiv.org.
    23. Miguel Arranz & Alvaro Escribano, 2004. "Outliers - robust ECM cointegration tests based on the trend components," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(4), pages 243-266, December.
    24. Guodong Li & Chenlei Leng & Chih-Ling Tsai, 2014. "A Hybrid Bootstrap Approach To Unit Root Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(4), pages 299-321, July.
    25. Xiao, Zhijie, 2004. "Estimating average economic growth in time series data with persistency," Journal of Macroeconomics, Elsevier, vol. 26(4), pages 699-724, December.
    26. Aparicio, Felipe M. & Escribano, Álvaro & García, Ana, 2004. "A range unit root test," DES - Working Papers. Statistics and Econometrics. WS ws041104, Universidad Carlos III de Madrid. Departamento de Estadística.
    27. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    28. Narayan, Paresh Kumar & Liu, Ruipeng & Westerlund, Joakim, 2016. "A GARCH model for testing market efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 121-138.
    29. Rickard Sandberg, 2015. "M-estimator based unit root tests in the ESTAR framework," Statistical Papers, Springer, vol. 56(4), pages 1115-1135, November.
    30. Abadir, Karim M. & Lucas, Andre, 2000. "Quantiles for t-statistics based on M-estimators of unit roots," Economics Letters, Elsevier, vol. 67(2), pages 131-137, May.
    31. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Co-integration and common trends analysis with score-driven models : an application to the federal funds effective rate and US inflation rate," UC3M Working papers. Economics 28451, Universidad Carlos III de Madrid. Departamento de Economía.
    32. Hoek, Henk & Lucas, Andre & van Dijk, Herman K., 1995. "Classical and Bayesian aspects of robust unit root inference," Journal of Econometrics, Elsevier, vol. 69(1), pages 27-59, September.
    33. Lima Luiz Renato & Xiao Zhijie, 2010. "Testing Unit Root Based on Partially Adaptive Estimation," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-34, June.
    34. Shin, Dong Wan & Park, Soo Jung & Oh, Man-Suk, 2009. "A robust sign test for panel unit roots under cross sectional dependence," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1312-1327, February.
    35. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    36. Dong Wan Shin & Oesook Lee, 2004. "M‐Estimation for regressions with integrated regressors and arma errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 283-299, March.
    37. Franses, Philip Hans & Lucas, André, 1997. "Outlier robust cointegration analysis," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    38. Rickard Sandberg, 2017. "Sample Moments and Weak Convergence to Multivariate Stochastic Power Integrals," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1000-1009, November.
    39. Demetrescu, Matei & Roling, Christoph, 2025. "Testing the Predictive Ability of Possibly Persistent Variables under Asymmetric Loss," Econometrics and Statistics, Elsevier, vol. 33(C), pages 80-104.
    40. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    41. Shin, Dong Wan & Park, Sangun, 2010. "Robust panel unit root tests for cross-sectionally dependent multiple time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2801-2813, November.
    42. Luiz Lima & Jaime de Jesus Filho, 2008. "Further investigation of the uncertain trend in US GDP," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1207-1216.
    43. Hella, Heikki, 2003. "On robust ESACF identification of mixed ARIMA models," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2003_027, December.

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