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Luc Bauwens

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.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Michel Lubrano & Luc Bauwens & Alan Kirman & Camelia Protopopescu, 2003. "Ranking Economics Departments in Europe: A Statistical Approach," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1367-1401, December.

    Mentioned in:

    1. > Economics Profession > Ranking in Economics > Ranking Institutions

Working papers

  1. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2022. "We modeled long memory with just one lag!," LIDAM Discussion Papers CORE 2022016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.

  2. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  3. Maciej Augustyniak & Luc Bauwens & Arnaud Dufays, 2019. "A new approach: the factorial hidden Markov volatility model," LIDAM Reprints CORE 3066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
    2. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.

  4. Bauwens, Luc & Xu, Yongdeng, 2019. "DCC and DECO-HEAVY: a multivariate GARCH model based on realized variances and correlations," Cardiff Economics Working Papers E2019/5, Cardiff University, Cardiff Business School, Economics Section, revised Aug 2021.

    Cited by:

    1. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  5. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with A New Approach to Nonlinear Filtering," CREATES Research Papers 2018-30, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    2. Yang, Yuhong, 2000. "Combining Different Procedures for Adaptive Regression," Journal of Multivariate Analysis, Elsevier, vol. 74(1), pages 135-161, July.

  6. L. Bauwens & E. Otrando, 2018. "Nonlinearities and Regimes in Conditional Correlations with Different Dynamics," Working Paper CRENoS 201803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Mariagrazia Fallanca & Antonio Fabio Forgione & Edoardo Otranto, 2021. "Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach," JRFM, MDPI, vol. 14(1), pages 1-15, January.
    3. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    4. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  7. AUGUSTYNIAK, Maciej & BAUWENS, Luc & DUFAYS, Arnaud, 2016. "A New Approach to Volatility Modeling : The High-Dimensional Markov Model," LIDAM Discussion Papers CORE 2016042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.

  8. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Discussion Papers CORE 2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    2. 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.
    3. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    4. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    5. Jin, Xin & Maheu, John M & Yang, Qiao, 2017. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," MPRA Paper 81920, University Library of Munich, Germany.
    6. BRAIONE, Manuela, 2016. "A time-varying long run HEAVY model," LIDAM Discussion Papers CORE 2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    8. Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
    9. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    10. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    11. 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.
    12. 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.
    13. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
    14. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.

  9. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Vogler, Jan & Golosnoy, Vasyl, 2023. "Unrestricted maximum likelihood estimation of multivariate realized volatility models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1063-1074.
    2. 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.
    3. 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.
    4. 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.
    5. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    6. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
    7. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.

  10. Luc Bauwens & Edoardo Otranto, 2016. "Modeling the dependence of conditional correlations on market volatility," LIDAM Reprints CORE 2924, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    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. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    3. Gao, Lingbo & Ye, Wuyi & Guo, Ranran, 2022. "Jointly forecasting the value-at-risk and expected shortfall of Bitcoin with a regime-switching CAViaR model," Finance Research Letters, Elsevier, vol. 48(C).
    4. Mariagrazia Fallanca & Antonio Fabio Forgione & Edoardo Otranto, 2021. "Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach," JRFM, MDPI, vol. 14(1), pages 1-15, January.
    5. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    6. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    7. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    8. Gu, Huaying & Liu, Zhixue & Weng, Yingliang, 2017. "Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 460-472.
    9. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    10. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. 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).
    12. 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).
    13. L. Bauwens & E. Otrando, 2018. "Nonlinearities and Regimes in Conditional Correlations with Different Dynamics," Working Paper CRENoS 201803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    14. Shumi Akhtar & Farida Akhtar & Maria Jahromi & Kose John, 2023. "Volatility linkages and value gains from diversifying with Islamic assets," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(8), pages 1495-1528, October.
    15. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    16. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.

  11. Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," LIDAM Discussion Papers CORE 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jean HINDRIKS & Yukihiro NISHIMURA, 2016. "Equilibrium Leadership in Tax Competiton Models with Capital Ownership: A Rejoinder," LIDAM Reprints CORE 2758, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    3. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.
    4. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    5. Balandraud, Eric & Queyranne, Maurice & Tardella, Fabio, 2015. "Largest minimally inversion-complete and pair-complete sets of permutations," LIDAM Discussion Papers CORE 2015009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Didier Nibbering, 2019. "A High-dimensional Multinomial Choice Model," Monash Econometrics and Business Statistics Working Papers 19/19, Monash University, Department of Econometrics and Business Statistics.
    7. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    8. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    9. Chiara Lattanzi & Manuele Leonelli, 2019. "A changepoint approach for the identification of financial extreme regimes," Papers 1902.09205, arXiv.org.
    10. DESCHAMPS, Philippe J., 2016. "Bayesian Semiparametric Forecasts of Real Interest Rate Data," LIDAM Discussion Papers CORE 2016050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Didier Nibbering, 2023. "A High-dimensional Multinomial Logit Model," Monash Econometrics and Business Statistics Working Papers 19/23, Monash University, Department of Econometrics and Business Statistics.
    12. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    13. Vrins, F. & Jeanblanc, M., 2015. "The [phi]-Martingale," LIDAM Discussion Papers CORE 2015022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    15. Graziano Moramarco, 2021. "Regime-Switching Density Forecasts Using Economists' Scenarios," Papers 2110.13761, arXiv.org, revised Feb 2024.
    16. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
    17. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    19. I. G. Ukpong & K. G. Balcombe & I. M. Fraser & F. J. Areal, 2019. "Preferences for Mitigation of the Negative Impacts of the Oil and Gas Industry in the Niger Delta Region of Nigeria," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 811-843, October.

  12. BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen, 2015. "The Contribution of Structural Break Models to Forecating Macroeconomic Series," LIDAM Reprints CORE 2651, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    2. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    3. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    4. 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.
    5. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    6. Gary Koop & Dimitris Korobilis, 2023. "Bayesian Dynamic Variable Selection In High Dimensions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1047-1074, August.
    7. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    8. Arnaud Dufays & Jeroen V.K. Rombouts, 2016. "Sparse Change-point HAR Models for Realized Variance," Cahiers de recherche 1607, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    9. Davide Pettenuzzo & Allan Timmermann, 2017. "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 183-201, April.
    10. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
    11. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org.
    12. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    13. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    14. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    15. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    16. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    17. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    18. Elena Afanasyeva, 2020. "Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap," Finance and Economics Discussion Series 2020-045, Board of Governors of the Federal Reserve System (U.S.).
    19. Franz Ruch & Mehmet Balcilar & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 201543, University of Pretoria, Department of Economics.
    20. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Working Papers 201482, University of Pretoria, Department of Economics.
    21. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    22. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Koop, Gary & Korobilis, Dimitris, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2009-40, Scottish Institute for Research in Economics (SIRE).
    24. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    25. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pinter, Gabor, 2015. "Forecasting with VAR models: fat tails and stochastic volatility," Bank of England working papers 528, Bank of England.
    26. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    27. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    28. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    29. Eo Yunjong, 2016. "Structural changes in inflation dynamics: multiple breaks at different dates for different parameters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 211-231, June.
    30. Kirsten Thompson & Renee van Eyden & Rangan Gupta, 2013. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Working Papers 201383, University of Pretoria, Department of Economics.
    31. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    32. Wensheng Kang & Jing Wang, 2018. "Oil shocks, policy uncertainty and earnings surprises," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 375-388, August.
    33. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    34. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    35. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    36. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    37. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    38. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    39. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    40. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    41. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    42. Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
    43. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    44. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
    45. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    46. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    47. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    48. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    49. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    50. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    51. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  13. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2014. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Discussion Papers CORE 2014053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    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. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," MPRA Paper 93802, University Library of Munich, Germany.
    3. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    4. 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.
    5. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    6. Jin, Xin & Maheu, John M & Yang, Qiao, 2017. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," MPRA Paper 81920, University Library of Munich, Germany.
    7. BRAIONE, Manuela, 2016. "A time-varying long run HEAVY model," LIDAM Discussion Papers CORE 2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. 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).
    10. 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.
    11. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    12. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.
    13. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
    14. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.

  14. BAUWENS, Luc & GRIGORYEVA, Lyudmila & ORTEGA, Juan-Pablo, 2014. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," LIDAM Discussion Papers CORE 2014012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    2. Gu, Huaying & Liu, Zhixue & Weng, Yingliang, 2017. "Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 460-472.
    3. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    4. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Gian Piero Aielli & Davide Pirino, 2023. "Funding Liquidity and Stocks’ Market Liquidity: Structural Estimation From High-Frequency Data," CEIS Research Paper 568, Tor Vergata University, CEIS, revised 28 Nov 2023.
    6. Grigoryeva, Lyudmila & Ortega, Juan-Pablo & Peresetsky, Anatoly, 2018. "Volatility forecasting using global stochastic financial trends extracted from non-synchronous data," Econometrics and Statistics, Elsevier, vol. 5(C), pages 67-82.
    7. L. Bauwens & E. Otrando, 2018. "Nonlinearities and Regimes in Conditional Correlations with Different Dynamics," Working Paper CRENoS 201803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    8. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    9. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.

  15. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    2. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2019. "Non-Linearities, Cyber Attacks and Cryptocurrencies," CESifo Working Paper Series 7692, CESifo.
    4. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    5. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    6. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    7. Thabani Ndlovu & Delson Chikobvu, 2023. "A Wavelet-Decomposed WD-ARMA-GARCH-EVT Model Approach to Comparing the Riskiness of the BitCoin and South African Rand Exchange Rates," Data, MDPI, vol. 8(7), pages 1-24, July.
    8. Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
    9. Thanasis Stengos & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "On the volatility of cryptocurrencies," Working Papers 2202, University of Guelph, Department of Economics and Finance.
    10. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    11. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    12. BenSaïda, Ahmed, 2015. "The frequency of regime switching in financial market volatility," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 63-79.
    13. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    14. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    15. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.
    16. Wang, Hanjie & Feil, Jan-Henning & Yu, Xiaohua, 2021. "Disagreement on sunspots and soybeans futures price," Economic Modelling, Elsevier, vol. 95(C), pages 385-393.
    17. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.
    18. 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.
    19. Nick James & Roman Marchant & Richard Gerlach & Sally Cripps, 2019. "Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series," Papers 1902.03350, arXiv.org.
    20. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.

  16. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Jean J. Gabszewicz & Skerdilajda Zanaj, 2015. "(Un)stable vertical collusive agreements," Canadian Journal of Economics, Canadian Economics Association, vol. 48(3), pages 924-939, August.
    3. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    4. MAULEON, Ana & MOLIS, Elena & VANNETELBOSCH, Vincent & VERGOTE , Wouter, 2013. "Dominance invariant one-to-one matching problems," LIDAM Discussion Papers CORE 2013052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2016. "Volatility Dependent Dynamic Equicorrelation," NCER Working Paper Series 111, National Centre for Econometric Research.
    6. MANIQUET, François & MORELLI, Massimo, 2015. "Approval quorums dominate participation quorums," LIDAM Reprints CORE 2666, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    8. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    9. Dudek, Jérémy, 2013. "Illiquidité, contagion et risque systémique," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/13236 edited by Le Fol, Gaëlle.
    10. Becker, Christoph & Schmidt, Wolfgang M., 2015. "How past market movements affect correlation and volatility," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 78-107.
    11. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.
    12. P. Bertuccelli & M. Mucciardi & E. Otranto, 2014. "Spatial Effects in Dynamic Conditional Correlations," Working Paper CRENoS 201406, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    13. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.

  17. Bauwens, Luc & Hafner, Christian & Pierret, Diane, 2013. "Modelling multivariate volatility of electricity futures," LIDAM Reprints ISBA 2013030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    3. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    4. Escribano, Alvaro & Sucarrat, Genaro, 2018. "Equation-by-equation estimation of multivariate periodic electricity price volatility," Energy Economics, Elsevier, vol. 74(C), pages 287-298.

  18. BAUWENS, Luc & STORTI, Giuseppe, 2012. "Computationally efficient inference procedures for vast dimensional realized covariance models," LIDAM Discussion Papers CORE 2012028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    2. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. CREMER, Helmuth & PESTIEAU, Pierre & PONTHIERE, Grégory, 2012. "The economics of long-term care: a survey," LIDAM Reprints CORE 2466, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  19. BAUWENS, Luc & STORTI, Giuseppe & VIOLANTE, Francesco, 2012. "Dynamic conditional correlation models for realized covariance matrices," LIDAM Discussion Papers CORE 2012060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    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. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    3. 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.
    4. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Roxana Halbleib & Valeri Voev, 2012. "Forecasting Covariance Matrices: A Mixed Frequency Approach," Working Paper Series of the Department of Economics, University of Konstanz 2012-30, Department of Economics, University of Konstanz.
    6. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Ilya Archakov & Peter Reinhard Hansen, 2021. "A New Parametrization of Correlation Matrices," Econometrica, Econometric Society, vol. 89(4), pages 1699-1715, July.
    8. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    9. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    10. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    12. Hartl, Tobias & Weigand, Roland, 2019. "Multivariate Fractional Components Analysis," University of Regensburg Working Papers in Business, Economics and Management Information Systems 38283, University of Regensburg, Department of Economics.
    13. 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).
    14. BAUWENS, Luc & STORTI, Giuseppe, 2013. "Computationally efficient inference procedures for vast dimensional realized covariance models," LIDAM Reprints CORE 2469, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    16. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.
    17. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    18. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    19. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.

  20. WANG, Shin-Huei & BAUWENS, Luc & HSIAO, Cheng, 2012. "Forecasting long memory processes subject to structural breaks," LIDAM Discussion Papers CORE 2012048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    2. Gong, Xu & Lin, Boqiang, 2018. "Structural changes and out-of-sample prediction of realized range-based variance in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 27-39.
    3. 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.
    4. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    5. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    6. Erdenebat Bataa & Marwan Izzeldin & Denise Osborn, 2015. "Changes in the global oil market," Working Papers 75761696, Lancaster University Management School, Economics Department.
    7. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
    8. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    9. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
    10. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.

  21. BAUWENS, Luc & KOROBILIS, Dimitris, 2011. "Bayesian methods," LIDAM Discussion Papers CORE 2011061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.

  22. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models," CIRANO Working Papers 2011s-13, CIRANO.

    Cited by:

    1. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    2. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    3. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    4. 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.
    5. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    6. Gary Koop & Dimitris Korobilis, 2023. "Bayesian Dynamic Variable Selection In High Dimensions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1047-1074, August.
    7. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    8. Arnaud Dufays & Jeroen V.K. Rombouts, 2016. "Sparse Change-point HAR Models for Realized Variance," Cahiers de recherche 1607, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    9. Davide Pettenuzzo & Allan Timmermann, 2017. "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 183-201, April.
    10. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
    11. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org.
    12. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    13. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    14. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    15. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    16. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    17. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
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    20. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Working Papers 201482, University of Pretoria, Department of Economics.
    21. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    22. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Koop, Gary & Korobilis, Dimitris, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2009-40, Scottish Institute for Research in Economics (SIRE).
    24. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    25. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pinter, Gabor, 2015. "Forecasting with VAR models: fat tails and stochastic volatility," Bank of England working papers 528, Bank of England.
    26. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Research Working Paper RWP 11-16, Federal Reserve Bank of Kansas City.
    27. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    28. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    29. Eo Yunjong, 2016. "Structural changes in inflation dynamics: multiple breaks at different dates for different parameters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 211-231, June.
    30. Kirsten Thompson & Renee van Eyden & Rangan Gupta, 2013. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Working Papers 201383, University of Pretoria, Department of Economics.
    31. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    32. Wensheng Kang & Jing Wang, 2018. "Oil shocks, policy uncertainty and earnings surprises," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 375-388, August.
    33. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
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    35. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    36. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    37. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    38. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    39. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    40. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    41. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    42. Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
    43. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    44. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
    45. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    46. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    47. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    48. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    49. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    50. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    51. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  23. Bauwens, L. & Hafner, C. & Pierret, D., 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers ISBA 2011013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    4. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    6. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    7. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. 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).
    9. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    11. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    12. Escribano, Alvaro & Sucarrat, Genaro, 2018. "Equation-by-equation estimation of multivariate periodic electricity price volatility," Energy Economics, Elsevier, vol. 74(C), pages 287-298.
    13. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    14. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Reprints CORE 2923, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Francisco Ortiz Arango & Alma Nelly Montiel Guzmán, 2017. "Transmission of future prices of corn of the Chicago Board of Trade to the Mexican spot market," Contaduría y Administración, Accounting and Management, vol. 62(3), pages 941-957, Julio-Sep.
    16. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Xiao, Binqing & Yang, Ye & Peng, Xuerong & Fang, Libing, 2019. "Measuring the connectedness of European electricity markets using the network topology of variance decompositions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    18. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    20. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    21. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    22. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Scholarly Articles 34650305, Harvard University Department of Economics.
    23. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    24. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    26. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    28. Proietti, Tommaso, 2014. "Exponential Smoothing, Long Memory and Volatility Prediction," MPRA Paper 57230, University Library of Munich, Germany.
    29. Asger Lunde & Kasper V. Olesen, 2014. "Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange," CREATES Research Papers 2013-19, Department of Economics and Business Economics, Aarhus University.
    30. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.
    32. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    33. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    34. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    35. Palzer, Andreas & Westner, Günther & Madlener, Reinhard, 2012. "Evaluation of Different Hedging Strategies for Commodity Price Risks of Industrial Cogeneration Plants," FCN Working Papers 2/2012, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Mar 2013.
    36. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    37. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    38. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    39. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    40. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  24. Luc Luc & Arnaud Dufays & Jeroen V.K. Rombouts, 2011. "Marginal Likelihood for Markov-switching and Change-point Garch Models," CREATES Research Papers 2011-41, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Monica Billio & Roberto Casarin & Anthony Osuntuyi, 2012. "Efficient Gibbs Sampling for Markov Switching GARCH Models," Working Papers 2012:35, Department of Economics, University of Venice "Ca' Foscari".
    2. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    3. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    4. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    5. Nima Nonejad, 2019. "Modeling Persistence and Parameter Instability in Historical Crude Oil Price Data Using a Gibbs Sampling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1687-1710, April.
    6. Arnaud Dufays, 2016. "Evolutionary Sequential Monte Carlo Samplers for Change-Point Models," Econometrics, MDPI, vol. 4(1), pages 1-33, March.
    7. Maciej Augustyniak & Mathieu Boudreault & Manuel Morales, 2018. "Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 165-188, March.
    8. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    9. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    11. Aknouche Abdelhakim & Demmouche Nacer & Dimitrakopoulos Stefanos & Touche Nassim, 2020. "Bayesian analysis of periodic asymmetric power GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-24, September.
    12. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    13. Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
    14. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    15. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    16. Aknouche, Abdelhakim & Demmouche, Nacer & Touche, Nassim, 2018. "Bayesian MCMC analysis of periodic asymmetric power GARCH models," MPRA Paper 91136, University Library of Munich, Germany.
    17. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Monica Billio & Lorenzo Frattarolo & Hayette Gatfaoui & Philippe de Peretti, 2016. "Clustering in Dynamic Causal Networks as a Measure of Systemic Risk on the Euro Zone," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01339826, HAL.
    19. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    20. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    21. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    22. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    23. Seuk Wai Phoong & Seuk Yen Phoong & Shi Ling Khek, 2022. "Systematic Literature Review With Bibliometric Analysis on Markov Switching Model: Methods and Applications," SAGE Open, , vol. 12(2), pages 21582440221, April.
    24. Menelaos Karanasos & Alexandros Paraskevopoulos & Faek Menla Ali & Michail Karoglou & Stavroula Yfanti, 2014. "Modelling Returns and Volatilities During Financial Crises: a Time Varying Coefficient Approach," Papers 1403.7179, arXiv.org.
    25. Wee, Damien C.H. & Chen, Feng & Dunsmuir, William T.M., 2022. "Likelihood inference for Markov switching GARCH(1,1) models using sequential Monte Carlo," Econometrics and Statistics, Elsevier, vol. 21(C), pages 50-68.
    26. Thanasis Stengos & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "On the volatility of cryptocurrencies," Working Papers 2202, University of Guelph, Department of Economics and Finance.
    27. Luc BAUWENS & Jean-François CARPENTIER & Arnaud DUFAYS, 2017. "Autoregressive moving average infinite hidden Markov-switching models," LIDAM Reprints CORE 2836, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    29. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    30. Dohyun Chun & Donggyu Kim, 2022. "State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 105-124, January.
    31. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    32. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
    33. Monica Billio & Maddalena Cavicchioli, 2013. "�Markov Switching Models for Volatility: Filtering, Approximation and Duality�," Working Papers 2013:24, Department of Economics, University of Venice "Ca' Foscari".
    34. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Ardia, David & Dufays, Arnaud & Ordás Criado, Carlos, 2023. "Linking Frequentist and Bayesian Change-Point Methods," MPRA Paper 119486, University Library of Munich, Germany.
    36. Jean-François Carpantier & Arnaud Dufays, 2014. "Specific Markov-switching behaviour for ARMA parameters," Working Papers hal-01821134, HAL.
    37. Arnaud Dufays & Maciej Augustyniak & Luc Bauwens, 2016. "A new approach to volatility modeling: the High-Dimensional Markov model," Cahiers de recherche 1609, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    38. D’Amato, Valeria & Levantesi, Susanna & Piscopo, Gabriella, 2022. "Deep learning in predicting cryptocurrency volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    39. Donggyu Kim & Minseok Shin, 2023. "Volatility models for stylized facts of high‐frequency financial data," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 262-279, May.
    40. Griffin, Jim E. & Mitrodima, Gelly, 2020. "A Bayesian quantile time series model for asset returns," LSE Research Online Documents on Economics 105610, London School of Economics and Political Science, LSE Library.
    41. Gustavo Cabrera González, 2019. "Modeling and Projection of the Mexican Exchange Rate (Peso/Dollar): a Bayesian Approach for Model Selection," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(2), pages 203-219, Abril-Jun.
    42. Xiaoping Zhan & Tiefeng Ma & Shuangzhe Liu & Kunio Shimizu, 2018. "Markov-Switching Linked Autoregressive Model for Non-continuous Wind Direction Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 410-425, September.
    43. Gerrit Reher & Bernd Wilfling, 2016. "A nesting framework for Markov-switching GARCH modelling with an application to the German stock market," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 411-426, March.
    44. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    45. 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.
    46. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    47. Pappas, Vasileios & Ingham, Hilary & Izzeldin, Marwan & Steele, Gerry, 2016. "Will the crisis “tear us apart”? Evidence from the EU," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 346-360.

  25. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    3. Chia-Lin Chang & Juan-à ngel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," KIER Working Papers 795, Kyoto University, Institute of Economic Research.
    4. Paulo Araújo Santos & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies," Working Papers in Economics 11/28, University of Canterbury, Department of Economics and Finance.
    5. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    8. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    9. Jean-François Carpantier & Arnaud Dufays, 2013. "Commodities Inventory Effect," DEM Discussion Paper Series 13-07, Department of Economics at the University of Luxembourg.
    10. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "Intra-daily volatility spillovers between the US and German stock markets," Economics Working Papers 2012-06, Christian-Albrechts-University of Kiel, Department of Economics.
    11. Yuta Kurose & Yasuhiro Omori, 2014. "Dynamic Equicorrelation Stochastic Volatility," CIRJE F-Series CIRJE-F-941, CIRJE, Faculty of Economics, University of Tokyo.
    12. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    14. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    16. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    17. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Documentos de Trabajo del ICAE 2011-32, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    18. Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
    19. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. 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.
    21. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    22. Yaya, OlaOluwa S. & Tumala, Mohammed M. & Udomboso, Christopher G., 2016. "Volatility persistence and returns spillovers between oil and gold prices: Analysis before and after the global financial crisis," Resources Policy, Elsevier, vol. 49(C), pages 273-281.
    23. Gianluca Cubadda & Barbara Guardabascio & Alain Hecq, 2016. "A Vector Heterogeneous Autoregressive Index Model for Realized Volatily Measures," CEIS Research Paper 391, Tor Vergata University, CEIS, revised 23 Jul 2016.
    24. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  26. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Arnaud Dufays, 2016. "Evolutionary Sequential Monte Carlo Samplers for Change-Point Models," Econometrics, MDPI, vol. 4(1), pages 1-33, March.
    2. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    4. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.

  27. BAUWENS, Luc & ROMBOUTS, Jeroen, 2009. "On marginal likelihood computation in change-point models," LIDAM Discussion Papers CORE 2009061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    2. Philip Liu & Konstantinos Theodoridis & Haroon Mumtaz & Francesco Zanetti, 2019. "Changing Macroeconomic Dynamics at the Zero Lower Bound," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 391-404, July.
    3. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model," OECD Statistics Working Papers 2020/01, OECD Publishing.
    4. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    5. Soosung Hwang & Alexandre Rubesam, 2015. "The disappearance of momentum," The European Journal of Finance, Taylor & Francis Journals, vol. 21(7), pages 584-607, May.
    6. Gebrenegus Ghilagaber & Parfait Munezero, 2020. "Bayesian change-point modelling of the effects of 3-points-for-a-win rule in football," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(2), pages 248-264, January.
    7. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. van den Hout, Ardo & Muniz-Terrera, Graciela & Matthews, Fiona E., 2013. "Change point models for cognitive tests using semi-parametric maximum likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 684-698.
    9. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    10. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.

  28. BAUWENS, Luc & PREMINGER, Arie & ROMBOUTS, Jeroen V.K., 2007. "Theory and inference for a Markov switching GARCH model," LIDAM Discussion Papers CORE 2007055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Monica Billio & Roberto Casarin & Anthony Osuntuyi, 2012. "Efficient Gibbs Sampling for Markov Switching GARCH Models," Working Papers 2012:35, Department of Economics, University of Venice "Ca' Foscari".
    2. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    3. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    5. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2019. "Non-Linearities, Cyber Attacks and Cryptocurrencies," CESifo Working Paper Series 7692, CESifo.
    6. Bergsli, Lykke Øverland & Lind, Andrea Falk & Molnár, Peter & Polasik, Michał, 2022. "Forecasting volatility of Bitcoin," Research in International Business and Finance, Elsevier, vol. 59(C).
    7. Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
    8. Maciej Augustyniak & Mathieu Boudreault & Manuel Morales, 2018. "Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 165-188, March.
    9. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    10. 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.
    11. 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).
    12. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    13. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    15. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    16. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    17. Giuseppe Storti & Luc Bauwens, 2006. "A component GARCH model with time varying weights," Computing in Economics and Finance 2006 388, Society for Computational Economics.
    18. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    19. Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
    20. Aknouche, Abdelhakim & Demouche, Nacer, 2018. "Ergodicity conditions for a double mixed Poisson autoregression," MPRA Paper 88843, University Library of Munich, Germany.
    21. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    22. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    23. Thomas Chuffart, 2015. "Selection Criteria in Regime Switching Conditional Volatility Models," Econometrics, MDPI, vol. 3(2), pages 1-28, May.
    24. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    26. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.
    27. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    28. Martin T. Bohl & Badye Essid & Pierre L. Siklos, 2011. "Do Short Selling Restrictions Destabilize Stock Markets? Lessons from Taiwan," Working Papers 112011, Hong Kong Institute for Monetary Research.
    29. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    30. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1682-1700, August.
    31. Aknouche, Abdelhakim & Demmouche, Nacer, 2019. "Ergodicity conditions for a double mixed Poisson autoregression," Statistics & Probability Letters, Elsevier, vol. 147(C), pages 6-11.
    32. Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
    33. Samuel Tabot Enow, 2023. "Stock Market Liquidity during Periods of Distress and its Implications: Evidence from International Financial Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 13(1), pages 1-6, January.
    34. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    35. Wee, Damien C.H. & Chen, Feng & Dunsmuir, William T.M., 2022. "Likelihood inference for Markov switching GARCH(1,1) models using sequential Monte Carlo," Econometrics and Statistics, Elsevier, vol. 21(C), pages 50-68.
    36. Thanasis Stengos & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "On the volatility of cryptocurrencies," Working Papers 2202, University of Guelph, Department of Economics and Finance.
    37. Szabolcs Blazsek & Anna Downarowicz, 2008. "Regime switching models of hedge fund returns," Faculty Working Papers 12/08, School of Economics and Business Administration, University of Navarra.
    38. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    39. Maddalena Cavicchioli, 2021. "Statistical inference for mixture GARCH models with financial application," Computational Statistics, Springer, vol. 36(4), pages 2615-2642, December.
    40. Shen, Zhiwei & Ritter, Matthias, 2016. "Forecasting volatility of wind power production," Applied Energy, Elsevier, vol. 176(C), pages 295-308.
    41. Pierre-Julien Trombe & Pierre Pinson & Henrik Madsen, 2012. "A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations," Energies, MDPI, vol. 5(3), pages 1-37, March.
    42. Colletaz, Gilbert & Hurlin, Christophe & Pérignon, Christophe, 2013. "The Risk Map: A new tool for validating risk models," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3843-3854.
    43. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    44. Kim, Yujin & Hwang, Eunju, 2018. "A dynamic Markov regime-switching GARCH model and its cumulative impulse response function," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 20-30.
    45. Dohyun Chun & Donggyu Kim, 2022. "State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 105-124, January.
    46. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, 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.
    47. Monica Billio & Maddalena Cavicchioli, 2013. "�Markov Switching Models for Volatility: Filtering, Approximation and Duality�," Working Papers 2013:24, Department of Economics, University of Venice "Ca' Foscari".
    48. Liu, Xiaochun, 2017. "Measuring systemic risk with regime switching in tails," Economic Modelling, Elsevier, vol. 67(C), pages 55-72.
    49. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    50. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    51. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    52. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
    53. Shuang Lin & Minke Wang & Zhihong Cheng & Fan He & Jiuhao Chen & Chuanhui Liao & Shengda Zhang, 2022. "Risk Management of Fuel Hedging Strategy Based on CVaR and Markov Switching GARCH in Airline Company," Sustainability, MDPI, vol. 14(22), pages 1-9, November.
    54. 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.
    55. Jean-François Carpantier & Arnaud Dufays, 2014. "Specific Markov-switching behaviour for ARMA parameters," Working Papers hal-01821134, HAL.
    56. Ojea Ferreiro, Javier, 2019. "Disentangling the role of the exchange rate in oil-related scenarios for the European stock market," Working Paper Series 2296, European Central Bank.
    57. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    58. Zhu, Junjun & Xie, Shiyu, 2010. "Bayesian Analysis of a Triple-Threshold GARCH Model with Application in Chinese Stock Market," MPRA Paper 28235, University Library of Munich, Germany.
    59. He, Yongda & Lin, Boqiang, 2018. "Forecasting China's total energy demand and its structure using ADL-MIDAS model," Energy, Elsevier, vol. 151(C), pages 420-429.
    60. Donggyu Kim & Minseok Shin, 2023. "Volatility models for stylized facts of high‐frequency financial data," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 262-279, May.
    61. Zhang, Dayong & Dickinson, David & Barassi, Marco, 2008. "Volatility Switching in Shanghai Stock Exchange: Does regulation help reduce volatility?," MPRA Paper 70352, University Library of Munich, Germany.
    62. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    63. Accolley, Delali, 2021. "Some Markov-Switching Models for the Toronto Stock Exchange," MPRA Paper 108072, University Library of Munich, Germany.
    64. Gelman, Sergey & Wilfling, Bernd, 2009. "Markov-switching in target stocks during takeover bids," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 745-758, December.
    65. Gerrit Reher & Bernd Wilfling, 2016. "A nesting framework for Markov-switching GARCH modelling with an application to the German stock market," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 411-426, March.
    66. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    67. de Bruijn, L.P. & Franses, Ph.H.B.F., 2015. "Stochastic levels and duration dependence in US unemployment," Econometric Institute Research Papers EI2015-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    68. 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.
    69. N. Alemohammad & S. Rezakhah & S. H. Alizadeh, 2020. "Markov switching asymmetric GARCH model: stability and forecasting," Statistical Papers, Springer, vol. 61(3), pages 1309-1333, June.
    70. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    71. 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).
    72. Pappas, Vasileios & Ingham, Hilary & Izzeldin, Marwan & Steele, Gerry, 2016. "Will the crisis “tear us apart”? Evidence from the EU," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 346-360.

  29. Winfried Pohlmeier & Luc Bauwens & David Veredas, 2007. "High frequency financial econometrics. Recent developments," ULB Institutional Repository 2013/136223, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Juan D. Moreno-Ternero, 2010. "Voting over piece-wise linear tax methods," Working Papers 10.02, Universidad Pablo de Olavide, Department of Economics.
    2. GAUTIER, Axel & WAUTHY, Xavier Yves, 2012. "Competitively neutral universal service obligations," LIDAM Reprints CORE 2455, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. NESTEROV, Yurii, 2011. "Random gradient-free minimization of convex functions," LIDAM Discussion Papers CORE 2011001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    5. MANZI, Jorge & SAN MARTIN, Ernesto & VAN BELLEGEM, Sébastien, 2010. "School system evaluation by value-added analysis under endogeneity," LIDAM Discussion Papers CORE 2010046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. CREMER, Helmuth & GAHVARI, Firouz & PESTIEAU, Pierre, 2011. "Fertility, human capital accumulation, and the pension system," LIDAM Reprints CORE 2366, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Bouezmarni, Taoufik & Van Bellegem, Sébastien, 2009. "Nonparametric Beta Kernel Estimator for Long Memory Time Series," TSE Working Papers 09-082, Toulouse School of Economics (TSE).
    8. GILLIS, Nicolas & GLINEUR, François, 2011. "A multilevel approach for nonnegative matrix factorization," LIDAM Reprints CORE 2381, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Marie-Louise Leroux & Grégory Ponthière, 2013. "Utilitarianism and unequal longevities: A remedy?," PSE - Labex "OSE-Ouvrir la Science Economique" hal-00813226, HAL.
    10. Pierre Pestieau & Maria Racionero, 2015. "Tagging with leisure needs," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 45(4), pages 687-706, December.
    11. DI SUMMA, Marco & WOLSEY, Laurence, 2010. "Mixing sets linked by bidirected paths," LIDAM Discussion Papers CORE 2010063, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    13. GRANDJEAN, Gilles, 2011. "Risk-sharing networks and farsighted stability," LIDAM Discussion Papers CORE 2011014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Vandenbussche, Hylke & Song, Huasheng & ,, 2010. "Innovation, antidumping, and retaliation," CEPR Discussion Papers 7916, C.E.P.R. Discussion Papers.
    15. Jacques-François Thisse, 2011. "Geographical Economics: A Historical Perspective," Recherches économiques de Louvain, De Boeck Université, vol. 77(2), pages 141-168.
    16. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A comparison of Forecasting Procedures for Macroeconomic Series: The Contribution of Structural Break Models," Working Papers 1113, University of Strathclyde Business School, Department of Economics.
    17. Bréchet, Thierry & Jouvet, Pierre-André & Rotillon, Gilles, 2013. "Tradable pollution permits in dynamic general equilibrium: Can optimality and acceptability be reconciled?," Ecological Economics, Elsevier, vol. 91(C), pages 89-97.
    18. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2014. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Reprints CORE 2594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. CALCIANO, Filippo L., 2011. "The complementarity foundations of industrial organization," LIDAM Discussion Papers CORE 2011005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. LUTTENS, Roland Iwan, 2010. "Lower bounds rule!," LIDAM Discussion Papers CORE 2010069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. LEROUX, Marie-Louise & PESTIEAU, Pierre, 2012. "The political economy of derived pension rights," LIDAM Reprints CORE 2444, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    23. MAULEON, Ana & VANNETELBOSCH, Vincent & VERGARI, Cecilia, 2010. "Unions' relative concerns and strikes in wage bargaining," LIDAM Discussion Papers CORE 2010076, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    24. GILLIS, Nicolas & GLINEUR, François, 2012. "On the geometric interpretation of the nonnegative rank," LIDAM Reprints CORE 2439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    26. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
    27. Axel Gautier & Per J. Agrell, 2011. "A Theory of Soft Capture," CREPP Working Papers 1107, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    28. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2010. "Iterative Regularization in Nonparametric Instrumental Regression," IDEI Working Papers 630, Institut d'Économie Industrielle (IDEI), Toulouse.
    29. RAMAEKERS, Eve, 2010. "Fair allocation of indivisible goods among two agents," LIDAM Discussion Papers CORE 2010087, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. LEBRETON, Michel & MORENO-TERNERO, Juan D. & SAVVATEEV, Alexei & Weber, Shlomo, 2013. "Stability and fairness in models with a multiple membership," LIDAM Reprints CORE 2540, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    32. DENUIT, Michel & EECKHOUDT, Louis & TSETLIN, Ilia & WINKLER, Robert L., 2010. "Multivariate concave and convex stochastic dominance," LIDAM Discussion Papers CORE 2010044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    33. HINDRIKS, Jean & VERSCHELDE, Marijn & RAYP, Glenn & SCHOORS, Koen, 2010. "School autonomy and educational performance: within-country evidence," LIDAM Discussion Papers CORE 2010082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    34. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    36. GILLIS, Nicolas & GLINEUR, François, 2010. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Discussion Papers CORE 2010075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    37. Katarzyna Bień-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 117-142, June.
    38. STEPHAN, Rüdiger, 2010. "An extension of disjunctive programming and its impact for compact tree formulations," LIDAM Discussion Papers CORE 2010045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    39. GABSZEWICZ, Jean & TAROLA, Ornella, 2010. "Product innovation and market acquisition of firms," LIDAM Discussion Papers CORE 2010078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    40. UNO, Hiroshi, 2011. "Nested potentials and robust equilibria," LIDAM Discussion Papers CORE 2011009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    41. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    42. AGRELL, Per & KASPERZEC, Roman, 2010. "Dynamic joint investments in supply chains under information asymmetry," LIDAM Discussion Papers CORE 2010085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  30. BAUWENS, Luc & MION, Giordano & THISSE, Jacques-François, 2007. "The resistible decline of European science," LIDAM Discussion Papers CORE 2007092, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Daraio, Cinzia & Moed, Henk F., 2011. "Is Italian science declining?," Research Policy, Elsevier, vol. 40(10), pages 1380-1392.
    2. Carillo, Maria Rosaria & Papagni, Erasmo & Sapio, Alessandro, 2013. "Do collaborations enhance the high-quality output of scientific institutions? Evidence from the Italian Research Assessment Exercise," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 47(C), pages 25-36.
    3. Conti, Annamaria & Gaule, Patrick, 2011. "Is the US outperforming Europe in university technology licensing? A new perspective on the European Paradox," Research Policy, Elsevier, vol. 40(1), pages 123-135, February.
    4. Stelios Katranidis & Theodore Panagiotidis & Kostas Zontanos, 2022. "A note on the relative productivity drivers of economists: a probit/logit approach for six European countries," Economic Change and Restructuring, Springer, vol. 55(4), pages 2171-2178, November.
    5. Panaretos, John & Malesios, Chrisovalandis, 2012. "Influential Mathematicians: Birth, Education and Affiliation," MPRA Paper 68046, University Library of Munich, Germany.
    6. Maria Rosaria Carillo & Erasmo Papagni & Alessandro Sapio, 2012. "Do collaborations enhance the high-quality output of scientific institutions? Evidence from the Italian Research Assessment Exercise (2001-2003)," Discussion Papers 4_2012, CRISEI, University of Naples "Parthenope", Italy.
    7. David Emanuel Andersson & Åke E. Andersson & Björn Hårsman & Xiyi Yang, 2020. "The geography of science in 12 European countries: a NUTS2-level analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1099-1125, August.
    8. Quentin Max David, 2013. "Determinants of Research Production at Top Universities," Working Papers TIMES² 2014-007, ULB -- Universite Libre de Bruxelles.
    9. Sonia M. R. Vasconcelos & Martha M. Sorenson & Jacqueline Leta, 2009. "A new input indicator for the assessment of science & technology research?," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 217-230, July.
    10. Raquel Carrasco & Javier Ruiz-Castillo, 2019. "Spatial mobility in elite academic institutions in economics: the case of Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 141-172, June.
    11. Mathieu Goudard & Michel Lubrano, 2011. "Human capital, social capital and scientific research in Europe: an application of linear hierarchical models," Working Papers halshs-00601033, HAL.
    12. Stelios Katranidis & Theodore Panagiotidis & Costas Zontanos, 2016. "Economists, research performance and national inbreeding:North versus South," Discussion Paper Series 2016_01, Department of Economics, University of Macedonia, revised Oct 2016.
    13. Argyropoulou, Maria & Soderquist, Klas Eric & Ioannou, George, 2019. "Getting out of the European Paradox trap: Making European research agile and challenge driven," European Management Journal, Elsevier, vol. 37(1), pages 1-5.
    14. Shahid Yusuf & Kaoru Nabeshima, 2009. "Growth through Innovation : An Industrial Strategy for Shanghai," World Bank Publications - Reports 18613, The World Bank Group.
    15. Polt, Wolfgang & Berger, Martin & Boekholt, Patries & Cremers, Katrin & Egeln, Jürgen & Gassler, Helmut & Hofer, Reinhold & Rammer, Christian & Deuten, Jasper & Good, Barbara & Warta, Katharina, 2010. "Das deutsche Forschungs- und Innovationssystem: Ein internationaler Sytemvergleich zur Rolle von Wissenschaft, Interaktionen und Governance für die technologische Leistungsfähigkeit," Studien zum deutschen Innovationssystem 11-2010, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    16. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Geographic mobility and research productivity in a selection of top world economics departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 241-265, April.
    17. Christian Reiner, 2010. "Brain competition policy as a new paradigm of regional policy: A European perspective," Papers in Regional Science, Wiley Blackwell, vol. 89(2), pages 449-461, June.

  31. BAUWENS, Luc & GALLI, Fausto, 2007. "Efficient importance sampling for ML estimation of SCD models," LIDAM Discussion Papers CORE 2007053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Tore Selland KLEPPE & Jun YU & Hans J. SKAUG, 2009. "Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models," Working Papers 20-2009, Singapore Management University, School of Economics.
    2. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Bekierman Jeremias & Gribisch Bastian, 2016. "Estimating stochastic volatility models using realized measures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 279-300, June.
    4. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
    5. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
    6. 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.
    7. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    8. 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.
    9. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
    10. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
    11. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
    12. 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.
    13. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    14. Kleppe, Tore Selland & Liesenfeld, Roman, 2011. "Efficient high-dimensional importance sampling in mixture frameworks," Economics Working Papers 2011-11, Christian-Albrechts-University of Kiel, Department of Economics.
    15. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
    16. Skaug, Hans J. & Yu, Jun, 2014. "A flexible and automated likelihood based framework for inference in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 642-654.
    17. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.

  32. BAUWENS, Luc & STORTI, Giuseppe, 2007. "A component GARCH model with time varying weights," LIDAM Discussion Papers CORE 2007019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2016. "Macro-Finance Determinants of the Long-Run Stock–Bond Correlation: The DCC-MIDAS Specification," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 617-642.
    2. Bouoiyour, Jamal & Selmi, Refk, 2013. "Nonlinearities and the nexus between inflation and inflation uncertainty in Egypt: New evidence from wavelets transform framework," MPRA Paper 52414, University Library of Munich, Germany.
    3. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    4. Amendola, Alessandra & Candila, Vincenzo & Scognamillo, Antonio, 2015. "On the influence of the U.S. monetary policy on the crude oil price volatility," 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy 207860, Italian Association of Agricultural and Applied Economics (AIEAA).
    5. Bouoiyour, Jamal & Selmi, Refk, 2015. "Bitcoin Price: Is it really that New Round of Volatility can be on way?," MPRA Paper 65580, University Library of Munich, Germany.
    6. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. 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.
    8. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    9. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    10. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    11. Jamal Bouoiyour & Refk Selmi, 2016. "Bitcoin: a beginning of a new phase?," Economics Bulletin, AccessEcon, vol. 36(3), pages 1430-1440.
    12. Tong Fang & Tae-Hwy Lee & Zhi Su, 2020. "Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection," Working Papers 202009, University of California at Riverside, Department of Economics.
    13. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    14. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    15. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    17. Bouoiyour, Jamal & Selmi, Refk, 2013. "The controversial link between exchange rate volatility and exports: Evidence from Tunisian case," MPRA Paper 49133, University Library of Munich, Germany, revised Mar 2013.
    18. Henryk Gurgul & Roland Mestel & Robert Syrek, 2017. "MIDAS models in banking sector – systemic risk comparison," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 18(2), pages 165-181.
    19. Bouoiyour, Jamal & Miftah, Amal & Selmi, Refk, 2014. "Do Financial Flows raise or reduce Economic growth Volatility? Some Lessons from Moroccan case," MPRA Paper 57258, University Library of Munich, Germany.
    20. Bouoiyour, Jamal & Selmi, Refk, 2013. "Commodity Price Uncertainty and Manufactured Exports in Morocco and Tunisia: Some Insights from a Novel GARCH Model," MPRA Paper 53412, University Library of Munich, Germany, revised Nov 2013.
    21. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    22. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    23. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    24. Mobarek, Asma & Muradoglu, Gulnur & Mollah, Sabur & Hou, Ai Jun, 2016. "Determinants of time varying co-movements among international stock markets during crisis and non-crisis periods," Journal of Financial Stability, Elsevier, vol. 24(C), pages 1-11.
    25. N. Alemohammad & S. Rezakhah & S. H. Alizadeh, 2020. "Markov switching asymmetric GARCH model: stability and forecasting," Statistical Papers, Springer, vol. 61(3), pages 1309-1333, June.

  33. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    2. Braione, Manuela & Scholtes, Nicolas K., 2014. "Construction of value-at-risk forecasts under different distributional assumptions within a BEKK framework," LIDAM Discussion Papers CORE 2014059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Bonga-Bonga, Lumengo & Nleya, Lebogang, 2016. "Assessing portfolio market risk in the BRICS economies: use of multivariate GARCH models," MPRA Paper 75809, University Library of Munich, Germany.

  34. BAUWENS, Luc, 2006. "Econometric analysis of intra-daily trading activity on the Tokyo Stock Exchange," LIDAM Reprints CORE 1862, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. 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.
    2. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    3. 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.
    4. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.

  35. BAUWENS, Luc & HAFNER, Christian & ROMBOUTS, Jeroen, 2006. "Multivariate mixed normal conditional heteroskedasticity," LIDAM Discussion Papers CORE 2006012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    2. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    3. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    4. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
    5. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    6. Rombouts, Jeroen V.K. & Stentoft, Lars, 2011. "Multivariate option pricing with time varying volatility and correlations," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2267-2281, September.
    7. Rossi, E. & Spazzini, F., 2010. "Model and distribution uncertainty in multivariate GARCH estimation: A Monte Carlo analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2786-2800, November.
    8. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    9. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    10. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    11. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    12. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    13. Abdelhakim Aknouche & Nadia Rabehi, 2010. "On an independent and identically distributed mixture bilinear time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 113-131, March.
    14. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    15. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    16. Maddalena Cavicchioli, 2021. "Statistical inference for mixture GARCH models with financial application," Computational Statistics, Springer, vol. 36(4), pages 2615-2642, December.
    17. Rombouts Jeroen V. K. & Bouaddi Mohammed, 2009. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-32, May.
    18. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    19. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Mitica Pepi, 2022. "The Impact of the Global Pandemic Crisis on East and Central EU Stock Markets," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 963-968, September.
    21. Tanattrin Bunnag, 2015. "Hedging Petroleum Futures with Multivariate GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 105-120.
    22. 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.
    23. Anghelache, Gabriela Victoria & Kralik, Lorand Istvan & Acatrinei, Marius & Pete, Stefan, 2014. "Influence of the EU Accession Process and the Global Crisis on the CEE Stock Markets: A Multivariate Correlation Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 35-52, June.
    24. Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.
    25. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    26. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    27. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    28. Bentarzi, M. & Hamdi, F., 2008. "Mixture periodic autoregressive conditional heteroskedastic models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 1-16, September.
    29. Mohamed Osman, 2015. "Dynamic Asymmetries in the Electric Consumption of the GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 461-467.

  36. BAUWENS, Luc & LUBRANO, Michel, 2006. "Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market," LIDAM Discussion Papers CORE 2006050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Baird, Matthew & Daugherty, Lindsay & Kumar, Krishna B., 2019. "Improving Estimation of Labor Market Disequilibrium Using Shortage Indicators, with an Application to the Market for Anesthesiologists," IZA Discussion Papers 12129, Institute of Labor Economics (IZA).
    2. Matthew Baird & Lindsay Daugherty & Krishna Kumar, 2017. "Improving Estimation of Labor Market Disequilibrium through Inclusion of Shortage Indicators," CINCH Working Paper Series 1701, Universitaet Duisburg-Essen, Competent in Competition and Health.
    3. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.
    4. Karmelavičius, Jaunius & Mikaliūnaitė-Jouvanceau, Ieva & Petrokaitė, Austėja Petrokaitė, 2022. "Housing and credit misalignments in a two-market disequilibrium framework," ESRB Working Paper Series 135, European Systemic Risk Board.
    5. Claessens, Stijn & Sakho, Yaye Seynabou, 2013. "Assessing firms'financing constraints in Brazil," Policy Research Working Paper Series 6624, The World Bank.
    6. Carpenter, Seth & Demiralp, Selva & Eisenschmidt, Jens, 2014. "The effectiveness of non-standard monetary policy in addressing liquidity risk during the financial crisis: The experiences of the Federal Reserve and the European Central Bank," Journal of Economic Dynamics and Control, Elsevier, vol. 43(C), pages 107-129.
    7. Aloysius Deno Hervino, 2011. "Avoiding risk in working capital credit distribution in Indonesia," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 3(2), pages 199-210, April.
    8. Paolo Del Giovane & Andrea Nobili & Federico Maria Signoretti, 2013. "Supply tightening or lack of demand? An analysis of credit developments during the Lehman Brothers and the sovereign debt crises," Temi di discussione (Economic working papers) 942, Bank of Italy, Economic Research and International Relations Area.
    9. Bofinger, Peter & Maas, Daniel & Ries, Mathias, 2017. "A model of the market for bank credit: The case of Germany," W.E.P. - Würzburg Economic Papers 98, University of Würzburg, Department of Economics.
    10. Tamini, Arnaud & Petey, Joël, 2021. "Hoarding of reserves in the banking industry: Explaining the African paradox," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 214-225.
    11. Schmidt, Torsten & Zwick, Lina, 2012. "In Search for a Credit Crunch in Germany," Ruhr Economic Papers 361, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  37. BAUWENS, Luc & SUCARRAT, Genaro, 2006. "General to specific modelling of exchange rate volatility: a forecast evaluation," LIDAM Discussion Papers CORE 2006021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Cairns, Andrew J.G. & Blake, David & Dowd, Kevin & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2011. "Mortality density forecasts: An analysis of six stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 48(3), pages 355-367, May.
    2. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    3. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    4. Panday, Anjan, 2015. "Impact of monetary policy on exchange market pressure: The case of Nepal," Journal of Asian Economics, Elsevier, vol. 37(C), pages 59-71.
    5. J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
    6. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
    7. Sucarrat, Genaro, 2009. "Econometric reduction theory and philosophy," UC3M Working papers. Economics we091005, Universidad Carlos III de Madrid. Departamento de Economía.
    8. Carlisle E. Moody & Thomas B. Marvell, 2010. "On the Choice of Control Variables in the Crime Equation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 696-715, October.
    9. Alvaro Escribano & Genaro Sucarrat, 2011. "Automated model selection in finance: General-to-speci c modelling of the mean and volatility speci cations," Working Papers 2011-09, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    10. Sucarrat, Genaro & Escribano, Álvaro, 2009. "Automated financial multi-path GETS modelling," UC3M Working papers. Economics we093620, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    12. Philipp Otto, 2022. "A Multivariate Spatial and Spatiotemporal ARCH Model," Papers 2204.12472, arXiv.org.
    13. Holger Fink & Andreas Fuest & Henry Port, 2018. "The Impact of Sovereign Yield Curve Differentials on Value-at-Risk Forecasts for Foreign Exchange Rates," Risks, MDPI, vol. 6(3), pages 1-19, August.
    14. Clavero, Borja, 2017. "A contribution to the Quantity Theory of Disaggregated Credit," MPRA Paper 76657, University Library of Munich, Germany.
    15. Lyonnet, Victor & Werner, Richard, 2012. "Lessons from the Bank of England on ‘quantitative easing’ and other ‘unconventional’ monetary policies," International Review of Financial Analysis, Elsevier, vol. 25(C), pages 94-105.
    16. Tennant, David, 2011. "Why do people risk exposure to Ponzi schemes? Econometric evidence from Jamaica," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 328-346, July.
    17. Genaro Sucarrat & Alvaro Escribano, 2012. "Automated Model Selection in Finance: General-to-Specific Modelling of the Mean and Volatility Specifications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 716-735, October.
    18. Sucarrat, Genaro & Escribano, Álvaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    19. Cui, Jin & In, Francis & Maharaj, Elizabeth Ann, 2016. "What drives the Libor–OIS spread? Evidence from five major currency Libor–OIS spreads," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 358-375.

  38. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime Switching Garch Models," Working Papers 0605, Ben-Gurion University of the Negev, Department of Economics.

    Cited by:

    1. Nagaraj Naik & Biju R. Mohan, 2021. "Stock Price Volatility Estimation Using Regime Switching Technique-Empirical Study on the Indian Stock Market," Mathematics, MDPI, vol. 9(14), pages 1-18, July.
    2. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    3. Michail Karoglou, 2010. "Breaking down the non-normality of stock returns," The European Journal of Finance, Taylor & Francis Journals, vol. 16(1), pages 79-95.
    4. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.

  39. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    2. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    3. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    4. Marco Minozzo & Silvia Centanni, 2012. "Monte Carlo likelihood inference for marked doubly stochastic Poisson processes with intensity driven by marked point processes," Working Papers 11/2012, University of Verona, Department of Economics.
    5. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    6. Nolte, Ingmar & Voev, Valeri, 2007. "Panel intensity models with latent factors: An application to the trading dynamics on the foreign exchange market," CoFE Discussion Papers 07/02, University of Konstanz, Center of Finance and Econometrics (CoFE).
    7. Herrera, Rodrigo, 2013. "Energy risk management through self-exciting marked point process," Energy Economics, Elsevier, vol. 38(C), pages 64-76.
    8. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    9. 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.
    10. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    11. 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).
    12. 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.
    13. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    14. Blazsek, Szabolcs & Escribano, Álvaro, 2009. "Knowledge spillovers in U.S. patents: a dynamic patent intensity model with secret common innovation factors," UC3M Working papers. Economics we098951, Universidad Carlos III de Madrid. Departamento de Economía.
    15. 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.
    16. 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).
    17. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    18. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    19. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    20. Blazsek, Szabolcs & Escribano, Alvaro, 2016. "Patent propensity, R&D and market competition: Dynamic spillovers of innovation leaders and followers," Journal of Econometrics, Elsevier, vol. 191(1), pages 145-163.
    21. Kehrle, Kerstin & Peter, Franziska J., 2013. "Who moves first? An intensity-based measure for information flows across stock exchanges," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1629-1642.
    22. 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.
    23. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    24. 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.
    25. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    26. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    27. Jean-Francois Richard, 2007. "Efficient High-Dimensional Importance Sampling," Working Paper 321, Department of Economics, University of Pittsburgh, revised Jan 2007.
    28. Richard, Jean-Francois & Zhang, Wei, 2007. "Efficient high-dimensional importance sampling," Journal of Econometrics, Elsevier, vol. 141(2), pages 1385-1411, December.
    29. Aneta Hryckiewicz & Piotr Mielus & Karolina Skorulska & Malgorzata Snarska, 2018. "Does a bank levy increase frictions on the interbank market?," KAE Working Papers 2018-033, Warsaw School of Economics, Collegium of Economic Analysis.
    30. Kohler, Alexander & von Wyss, Rico, 2012. "Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID," Working Papers on Finance 1209, University of St. Gallen, School of Finance.
    31. 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.
    32. 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.
    33. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos & Touche, Nassim, 2019. "Integer-valued stochastic volatility," MPRA Paper 91962, University Library of Munich, Germany, revised 04 Feb 2019.
    34. 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.
    35. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    36. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    37. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    38. Rodrigo Herrera & Bernhard Schipp, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers SFB649DP2011-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    39. Giampaoli, Iacopo & Ng, Wing Lon & Constantinou, Nick, 2009. "Analysis of ultra-high-frequency financial data using advanced Fourier transforms," Finance Research Letters, Elsevier, vol. 6(1), pages 47-53, March.
    40. Blazsek, Szabolcs & Escribano, Álvaro, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.
    41. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    42. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.
    43. Renault, Eric & van der Heijden, Thijs & Werker, Bas J.M., 2014. "The dynamic mixed hitting-time model for multiple transaction prices and times," Journal of Econometrics, Elsevier, vol. 180(2), pages 233-250.
    44. Blazsek, Szabolcs & Escribano, Álvaro, 2014. "Propensity to patent, R&D and market competition : dynamic spillovers of innovation leaders and followers," UC3M Working papers. Economics we1412, Universidad Carlos III de Madrid. Departamento de Economía.

  40. 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).

    Cited by:

    1. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," Papers 1809.08060, arXiv.org, revised Sep 2021.
    2. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Risks, MDPI, vol. 8(3), pages 1-20, September.
    3. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    4. Emmanuel Bacry & Jean-Francois Muzy, 2014. "Second order statistics characterization of Hawkes processes and non-parametric estimation," Papers 1401.0903, arXiv.org, revised Feb 2015.
    5. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org.
    6. Angelos Dassios & Xin Dong, 2014. "Stationarity of Bivariate Dynamic Contagion Processes," Papers 1405.5842, arXiv.org.
    7. Monira Essa Aloud, 2016. "Time Series Analysis Indicators under Directional Changes: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 55-64.
    8. Ketelbuters, John John & Hainaut, Donatien, 2021. "Time-Consistent Evaluation of Credit Risk with Contagion," LIDAM Discussion Papers ISBA 2021004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 91-114, March.
    10. Anatoliy Swishchuk & Aiden Huffman, 2020. "General Compound Hawkes Processes in Limit Order Books," Risks, MDPI, vol. 8(1), pages 1-25, March.
    11. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    12. Steffen Volkenand & Günther Filler & Martin Odening, 2020. "Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities," Risks, MDPI, vol. 8(3), pages 1-17, July.
    13. Álvaro Cartea, 2013. "Derivatives pricing with marked point processes using tick-by-tick data," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 111-123, January.
    14. Dungey, Mardi & Long, Xiangdong & Ullah, Aman & Wang, Yun, 2014. "A semiparametric conditional duration model," Economics Letters, Elsevier, vol. 124(3), pages 362-366.
    15. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    16. Dassios, Angelos & Jang, Jiwook & Zhao, Hongbiao, 2019. "A generalised CIR process with externally-exciting and self-exciting jumps and its applications in insurance and finance," LSE Research Online Documents on Economics 102043, London School of Economics and Political Science, LSE Library.
    17. Ioane Muni Toke, 2010. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Papers 1003.3796, arXiv.org, revised Jun 2010.
    18. 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).
    19. Marcello Rambaldi & Emmanuel Bacry & Fabrizio Lillo, 2016. "The role of volume in order book dynamics: a multivariate Hawkes process analysis," Papers 1602.07663, arXiv.org.
    20. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2013. "Modelling systemic price cojumps with Hawkes factor models," Papers 1301.6141, arXiv.org, revised Mar 2013.
    21. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2011. "Modeling microstructure noise with mutually exciting point processes," Papers 1101.3422, arXiv.org.
    22. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
    23. Li, Jie & Li, Guangzhong & Zhou, Yinggang, 2015. "Do securitized real estate markets jump? International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 31(C), pages 13-35.
    24. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    25. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    26. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    27. 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.
    28. Anatoliy Swishchuk, 2021. "Modelling of Limit Order Books by General Compound Hawkes Processes with Implementations," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 399-428, March.
    29. V. Filimonov & D. Sornette, 2015. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1293-1314, August.
    30. Hainaut, Donatien, 2016. "A bivariate Hawkes process for interest rate modeling," Economic Modelling, Elsevier, vol. 57(C), pages 180-196.
    31. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    32. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    33. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    34. Hainaut, Donatien, 2019. "Fractional Hawkes processes," LIDAM Discussion Papers ISBA 2019016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    35. Lucio Maria Calcagnile & Giacomo Bormetti & Michele Treccani & Stefano Marmi & Fabrizio Lillo, 2015. "Collective synchronization and high frequency systemic instabilities in financial markets," Papers 1505.00704, arXiv.org.
    36. Adam Clements & Yin Liao, 2013. "The dynamics of co-jumps, volatility and correlation," NCER Working Paper Series 91, National Centre for Econometric Research.
    37. Vladimir Filimonov & David Bicchetti & Nicolas Maystre, 2013. "Quantification of the High Level of Endogeneity and of Structural Regime Shifts in Commodity Markets," UNCTAD Discussion Papers 212, United Nations Conference on Trade and Development.
    38. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    39. Bacry, E. & Delattre, S. & Hoffmann, M. & Muzy, J.F., 2013. "Some limit theorems for Hawkes processes and application to financial statistics," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2475-2499.
    40. Pietro Fodra & Huy^en Pham, 2013. "High frequency trading and asymptotics for small risk aversion in a Markov renewal model," Papers 1310.1756, arXiv.org, revised Jan 2015.
    41. Roueff, Francois & von Sachs, Rainer & Sansonnet, Laure, 2015. "Time-frequency analysis of locally stationary Hawkes processes," LIDAM Discussion Papers ISBA 2015011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    42. Zhang, Yaohua & Zou, Jian & Ravishanker, Nalini & Thavaneswaran, Aerambamoorthy, 2019. "Modeling financial durations using penalized estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 145-158.
    43. Alessio Sancetta, 2017. "Estimation for the Prediction of Point Processes with Many Covariates," Papers 1702.05315, arXiv.org.
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    45. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
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  41. BAUWENS, Luc & PREMINGER, Arie & ROMBOUTS, Jeroen, 2006. "Regime switching GARCH models," LIDAM Discussion Papers CORE 2006011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Chunming Yuan, 2008. "The Exchange Rate and Macroeconomic Determinants: Time-Varying Transitional Dynamics," UMBC Economics Department Working Papers 09-114, UMBC Department of Economics, revised 01 Nov 2009.
    2. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    3. Robert J. Elliott & John W. Lau & Hong Miao & Tak Kuen Siu, 2012. "Viterbi-Based Estimation for Markov Switching GARCH Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(3), pages 219-231, August.
    4. Giuseppe Storti & Luc Bauwens, 2006. "A component GARCH model with time varying weights," Computing in Economics and Finance 2006 388, Society for Computational Economics.
    5. BAUWENS, Luc & HAFNER, Christian M. & ROMBOUTS, Jeroen VK, 2007. "Multivariate mixed normal conditional heteroskedasticity," LIDAM Reprints CORE 1906, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Markus Haas & Jochen Krause & Marc S. Paolella & Sven C. Steude, 2013. "Time-Varying Mixture GARCH Models and Asymmetric Volatility," Swiss Finance Institute Research Paper Series 13-04, Swiss Finance Institute.
    7. Nagaraj Naik & Biju R. Mohan, 2021. "Stock Price Volatility Estimation Using Regime Switching Technique-Empirical Study on the Indian Stock Market," Mathematics, MDPI, vol. 9(14), pages 1-18, July.
    8. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    9. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    10. Nyberg, Henri, 2010. "QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles," MPRA Paper 23724, University Library of Munich, Germany.
    11. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    12. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    13. 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).
    14. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    15. Chunming Yuan, 2008. "Forecasting Exchange Rates: The Multi-State Markov-Switching Model with Smoothing," UMBC Economics Department Working Papers 09-115, UMBC Department of Economics, revised 01 Nov 2009.
    16. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    17. Michail Karoglou, 2010. "Breaking down the non-normality of stock returns," The European Journal of Finance, Taylor & Francis Journals, vol. 16(1), pages 79-95.
    18. Michail Karoglou & Panicos Demetriades & Siong Law, 2011. "One date, one break?," Empirical Economics, Springer, vol. 41(1), pages 7-24, August.
    19. Aloui, Chaker & Jammazi, Rania, 2009. "The effects of crude oil shocks on stock market shifts behaviour: A regime switching approach," Energy Economics, Elsevier, vol. 31(5), pages 789-799, September.
    20. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.

  42. Luc Bauwens & David Veredas & Winfried Pohlmeier, 2005. "High frequency finance," ULB Institutional Repository 2013/136220, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    2. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Working Papers hal-00603385, HAL.
    4. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Papers 1106.5040, arXiv.org.
    5. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
    6. Lillie Lam & Laurence Fung & Ip-wing Yu, 2009. "Forecasting a Large Dimensional Covariance Matrix of a Portfolio of Different Asset Classes," Working Papers 0901, Hong Kong Monetary Authority.
    7. Yuanhua Feng & Sarah Forstinger & Christian Peitz, 2013. "On the iterative plug-in algorithm for estimating diurnal patterns of financial trade durations," Working Papers CIE 66, Paderborn University, CIE Center for International Economics.

  43. BAUWENS, Luc & LAURENT, Sébastien, 2005. "A new class of multivariate skew densities, with application to generalized autoregressive conditional heteroscedasticity models," LIDAM Reprints CORE 1793, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
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    3. Kinateder, Harald & Campbell, Ross & Choudhury, Tonmoy, 2021. "Safe haven in GFC versus COVID-19: 100 turbulent days in the financial markets," Finance Research Letters, Elsevier, vol. 43(C).
    4. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    5. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    6. Luca Merlo & Lea Petrella & Valentina Raponi, 2021. "Forecasting VaR and ES using a joint quantile regression and implications in portfolio allocation," Papers 2106.06518, arXiv.org.
    7. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    8. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    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. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2021. "Hedging stocks with oil," Energy Economics, Elsevier, vol. 93(C).
    11. Anatolyev Stanislav, 2009. "Multi-Market Direction-of-Change Modeling Using Dependence Ratios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    12. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
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    21. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    22. Guangyang Chen & Kai Dong & Shaonan Wang & Xiuli Du & Ronghua Zhou & Zhongwei Yang, 2022. "The Dynamic Relationship among Bank Credit, House Prices and Carbon Dioxide Emissions in China," IJERPH, MDPI, vol. 19(16), pages 1-18, August.
    23. Javier Mencía & Enrique Sentana, 2012. "Distributional Tests in Multivariate Dynamic Models with Normal and Student-t Innovations," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 133-152, February.
    24. Alexey Balaev, 2011. "Modeling multivariate parametric densities of financial returns (in Russian)," Quantile, Quantile, issue 9, pages 39-60, July.
    25. Zouheir Mighri & Faysal Mansouri, 2013. "Dynamic Conditional Correlation Analysis of Stock Market Contagion: Evidence from the 2007-2010 Financial Crises," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 637-661.
    26. Balaev , Alexey, 2011. "Multivariate skewed t-distribution with degrees of freedom vector and its application to financial modeling," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 23(3), pages 79-97.
    27. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    28. 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.
    29. Mori Kogid & Jaratin Lily & Rozilee Asid & James M. Alin & Dullah Mulok, 2022. "Volatility spillover and dynamic co-movement of foreign direct investment between Malaysia and China and developed countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 131-148, February.
    30. Schwaab, Bernd & Lucas, André & Zhang, Xin, 2013. "Conditional and joint credit risk," Working Paper Series 1621, European Central Bank.
    31. Shimizu, Katsutoshi & Ly, Kim Cuong, 2017. "Were regulatory interventions effective in lowering systemic risk during the financial crisis in Japan?," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 80-91.
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    34. Yu, Honghai & Du, Donglei & Fang, Libing & Yan, Panpan, 2018. "Risk contribution of crude oil to industry stock returns," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 179-199.
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    37. Javier Mencía & Enrique Sentana, 2008. "Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
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    42. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    43. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    44. Deschamps, Philippe J., 2012. "Bayesian estimation of generalized hyperbolic skewed student GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3035-3054.
    45. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
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    47. Zhu, Ke & Li, Wai Keung, 2014. "A new Pearson-type QMLE for conditionally heteroskedastic models," MPRA Paper 52732, University Library of Munich, Germany.
    48. Jón Daníelsson & Kevin James & Marcela Valenzuela & Ilknur Zer, 2014. "Model Risk of Risk Models," Finance and Economics Discussion Series 2014-34, Board of Governors of the Federal Reserve System (U.S.).
    49. Storti, Giuseppe & Wang, Chao, 2022. "A multivariate semi-parametric portfolio risk optimization and forecasting framework," MPRA Paper 115266, University Library of Munich, Germany.
    50. Tshikalange, Mulanga & Bonga-Bonga, Lumengo, 2023. "The determinants of the dynamic correlation between foreign exchange and equity markets: Cross-Country comparisons," MPRA Paper 118401, University Library of Munich, Germany.
    51. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility," CIRJE F-Series CIRJE-F-488, CIRJE, Faculty of Economics, University of Tokyo.
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    62. Luis García-Álvarez & Richard Luger, 2011. "Dynamic Correlations, Estimation Risk, and Porfolio Management During the Financial Crisis," Working Papers wp2011_1103, CEMFI, revised Sep 2011.
    63. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    64. Zouheir Mighri & Faysal Mansouri, 2014. "Modeling international stock market contagion using multivariate fractionally integrated APARCH approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-25, December.
    65. Hassan, M. Kabir & Djajadikerta, Hadrian Geri & Choudhury, Tonmoy & Kamran, Muhammad, 2022. "Safe havens in Islamic financial markets: COVID-19 versus GFC," Global Finance Journal, Elsevier, vol. 54(C).
    66. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    67. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    68. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    69. Karanasos, M. & Kartsaklas, A., 2009. "Dual long-memory, structural breaks and the link between turnover and the range-based volatility," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 838-851, December.
    70. Fantazzini, Dean & Zimin, Stephan, 2019. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," MPRA Paper 95988, University Library of Munich, Germany.
    71. Fang, Libing & Chen, Baizhu & Yu, Honghai & Qian, Yichuo, 2018. "Identifying systemic important markets from a global perspective: Using the ADCC ΔCoVaR approach with skewed-t distribution," Finance Research Letters, Elsevier, vol. 24(C), pages 137-144.
    72. Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
    73. Lucas, André & Schwaab, Bernd & Zhang, Xin, 2013. "Conditional euro area sovereign default risk," Working Paper Series 269, Sveriges Riksbank (Central Bank of Sweden).
    74. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    75. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
    76. Siddhartha Chib & Yasuhiro Omori & Manabu Asai, 2007. "Multivariate stochastic volatility (Revised in May 2007, Handbook of Financial Time Series (Published in "Handbook of Financial Time Series" (eds T.G. Andersen, R.A. Davis, Jens-Peter Kreiss," CARF F-Series CARF-F-094, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    77. Emmanuel Afuecheta & Artur Semeyutin & Stephen Chan & Saralees Nadarajah & Diego Andrés Pérez Ruiz, 2020. "Compound distributions for financial returns," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-25, October.
    78. Valeriane Jokhadze & Wolfgang M. Schmidt, 2020. "Measuring Model Risk In Financial Risk Management And Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-37, April.
    79. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    80. Donghang Luo & Ke Zhu & Huan Gong & Dong Li, 2020. "Testing error distribution by kernelized Stein discrepancy in multivariate time series models," Papers 2008.00747, arXiv.org.
    81. Tsuji, Chikashi, 2018. "Return transmission and asymmetric volatility spillovers between oil futures and oil equities: New DCC-MEGARCH analyses," Economic Modelling, Elsevier, vol. 74(C), pages 167-185.
    82. Arellano-Valle, Reinaldo B. & Azzalini, Adelchi & Ferreira, Clécio S. & Santoro, Karol, 2020. "A two-piece normal measurement error model," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    83. Carol Alexander & Michael Coulon & Yang Han & Xiaochun Meng, 2021. "Evaluating the Discrimination Ability of Proper Multivariate Scoring Rules," Papers 2101.12693, arXiv.org.
    84. Canan G. Corlu & Alper Corlu, 2015. "Modelling exchange rate returns: which flexible distribution to use?," Quantitative Finance, Taylor & Francis Journals, vol. 15(11), pages 1851-1864, November.
    85. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    86. Rainer Jobst & Daniel Rösch & Harald Scheule & Martin Schmelzle, 2015. "A Simple Econometric Approach for Modeling Stress Event Intensities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 300-320, April.
    87. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    88. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    89. 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.
    90. Mun, Kyung-Chun, 2016. "Hedging bank market risk with futures and forwards," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 112-125.
    91. Tsuji, Chikashi, 2018. "New DCC analyses of return transmission, volatility spillovers, and optimal hedging among oil futures and oil equities in oil-producing countries," Applied Energy, Elsevier, vol. 229(C), pages 1202-1217.
    92. Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).
    93. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    94. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    95. 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.
    96. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    97. Al-Nassar, Nassar S. & Boubaker, Sabri & Chaibi, Anis & Makram, Beljid, 2023. "In search of hedges and safe havens during the COVID─19 pandemic: Gold versus Bitcoin, oil, and oil uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 318-332.
    98. Ogata, Hiroaki, 2013. "Estimation for multivariate stable distributions with generalized empirical likelihood," Journal of Econometrics, Elsevier, vol. 172(2), pages 248-254.
    99. Ryo Kinoshita, 2015. "Asset allocation under higher moments with the GARCH filter," Empirical Economics, Springer, vol. 49(1), pages 235-254, August.
    100. Josip Arneric & Elza Jurun & Snježana Pivac, 2008. "Multivariate Risk-Return Decision Making Within Dynamic Estimation," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 7, pages 1-11, October.
    101. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.
    102. Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
    103. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.
    104. Cao, Yufei, 2022. "Extreme risk spillovers across financial markets under different crises," Economic Modelling, Elsevier, vol. 116(C).
    105. Li, Xindan & Yu, Honghai & Fang, Libing & Xiong, Cheng, 2019. "Do firm-level factors play forward-looking role for financial systemic risk: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    106. Yu, Honghai & Fang, Libing & Sun, Boyang & Du, Donglei, 2018. "Risk contribution of the Chinese stock market to developed markets in the post-crisis period," Emerging Markets Review, Elsevier, vol. 34(C), pages 87-97.
    107. Merlo, Luca & Petrella, Lea & Raponi, Valentina, 2021. "Forecasting VaR and ES using a joint quantile regression and its implications in portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 133(C).

  44. BAUWENS, Luc & RIME, Dagfinn & SUCARRAT, Genaro, 2005. "Exchange rate volatility and the mixture of distribution hypothesis," LIDAM Discussion Papers CORE 2005058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. M. Frömmel & A. Mende & L. Menkhoff, 2007. "Order Flows, News, and Exchange Rate Volatility," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/474, Ghent University, Faculty of Economics and Business Administration.
    2. Olivier Damette, 2016. "Mixture distribution hypothesis and the impact of a Tobin tax on exchange rate volatility : a reassessment," Post-Print hal-01601393, HAL.
    3. Jakree Koosakul & Ilhyock Shim, 2017. "The beneficial aspect of FX volatility for market liquidity," BIS Working Papers 629, Bank for International Settlements.
    4. Francis Bismans & Olivier Damette, 2012. "La taxe Tobin : une synthèse des travaux basés sur la théorie des jeux et l’économétrie," Working Papers of BETA 2012-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    5. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
    6. Suleyman Serdengecti & Ahmet Sensoy, 2019. "Intraday Volume-Volatility Nexus in the FX Markets: Evidence from an Emerging Market," Working Papers 1928, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Angelo Ranaldo & Paolo Santucci de Magistris, 2018. "Trading Volume, Illiquidity and Commonalities in FX Markets," Working Papers on Finance 1823, University of St. Gallen, School of Finance, revised Oct 2019.
    8. Saïd Souam & Faycal Hamdi, 2018. "Mixture Periodic GARCH Models: Theory and Applications," Post-Print hal-01589209, HAL.
    9. Olivier Damette & Stéphane Goutte, 2015. "Tobin tax and trading volume tightening: a reassessment," Post-Print hal-01203841, HAL.
    10. Olivier Damette & Beum-Jo Park, 2015. "Tobin Tax and Volatility: A Threshold Quantile Autoregressive Regression Framework," Review of International Economics, Wiley Blackwell, vol. 23(5), pages 996-1022, November.
    11. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Ewa M. Syczewska, 2014. "The EURPLN, DAX and WIG20: the Granger causality tests before and during the crisis," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 14, pages 93-104.
    13. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    14. Francq, Christian & Sucarrat, Genaro, 2015. "Equation-by-Equation Estimation of a Multivariate Log-GARCH-X Model of Financial Returns," MPRA Paper 67140, University Library of Munich, Germany.
    15. POPOVICI, Oana Cristina, 2015. "A Volatility Analysis Of The Euro Currency And The Bond Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 67-79.
    16. Rime, Dagfinn & Sucarrat, Genaro, 2007. "Exchange rate variability, market activity and heterogeneity," UC3M Working papers. Economics we077039, Universidad Carlos III de Madrid. Departamento de Economía.
    17. Michael Frömmel & Eyup Kadioglu, 2023. "Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    18. Munazza Jabeen & Saud Ahmad Khan, 2014. "Modelling Exchange Rate Volatility by Macroeconomic Fundamentals in Pakistan," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 58-76, September.
    19. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2018. "Public information arrival, price discovery and dynamic correlations in the Chinese renminbi markets," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 168-186.
    20. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    21. Sucarrat, Genaro & Escribano, Álvaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.

  45. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2005. "Bayesian inference for the mixed conditional heteroskedasticity model," LIDAM Discussion Papers CORE 2005085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    2. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    3. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    4. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    5. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    7. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    8. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    9. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.

  46. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," LIDAM Reprints CORE 1731, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Tsionas, Mike G., 2019. "Multi-objective optimization using statistical models," European Journal of Operational Research, Elsevier, vol. 276(1), pages 364-378.
    2. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Explaining Adaptive Radial-Based Direction Sampling," Econometric Institute Research Papers EI 2003-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2005. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," Econometric Institute Research Papers EI 2005-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Hoogerheide, L.F. & van Dijk, H.K. & van Oest, R.D., 2007. "Simulation based bayesian econometric inference: principles and some recent computational advances," Econometric Institute Research Papers EI 2007-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    6. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2005. "Bayesian inference for the mixed conditional heteroskedasticity model," LIDAM Discussion Papers CORE 2005085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Rodney Strachan & Herman K. van Dijk, "undated". "Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan," MRG Discussion Paper Series 1407, School of Economics, University of Queensland, Australia.
    8. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    9. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.
    10. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2004. "Neural network based approximations to posterior densities: a class of flexible sampling methods with applications to reduced rank models," Econometric Institute Research Papers EI 2004-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Waggoner, Daniel F. & Wu, Hongwei & Zha, Tao, 2016. "Striated Metropolis–Hastings sampler for high-dimensional models," Journal of Econometrics, Elsevier, vol. 192(2), pages 406-420.
    12. McCausland, William J., 2008. "On Bayesian analysis and computation for functions with monotonicity and curvature restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 484-507, January.
    13. Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012. "A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
    14. Hoogerheide, L.F. & van Dijk, H.K., 2007. "Note on neural network sampling for Bayesian inference of mixture processes," Econometric Institute Research Papers EI 2007-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. David Ardia & Lennart Hoogerheide & Herman K. van Dijk, 2009. "To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods," Tinbergen Institute Discussion Papers 09-017/4, Tinbergen Institute.

  47. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2004. "Econometrics," LIDAM Reprints CORE 1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    Cited by:

    1. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
    2. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    3. Ciaian, Pavel & Kancs, d'Artis & Pokrivcak, Jan, 2008. "Comparative Advantages, Transaction Costs and Factor Content in Agricultural Trade: Empirical Evidence from the CEE," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44135, European Association of Agricultural Economists.
    4. Veredas, David & Rodríguez Poo, Juan M. & Espasa, Antoni, 2001. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," DES - Working Papers. Statistics and Econometrics. WS ws013321, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    7. Sule Akkoyunlu & Konstantin A. Kholodilin & Boriss Siliverstovs, 2006. "The Effect of Economic Reforms of 1980s and of the Customs Union 1996 upon the Turkish Intra-Industry Trade," Discussion Papers of DIW Berlin 649, DIW Berlin, German Institute for Economic Research.
    8. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Miriam Hein, 2005. "Wie hat sich die universitaere volkswirtschaftliche Forschung in der Schweiz seit Beginn der 90er Jahre entwickelt?�," TWI Research Paper Series 11, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    10. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    11. Iheb FRIJA, 2008. "La compétitivité de l'industrie d'habillement tunisienne. Atouts et limites (The tunisian clothing industry competitiveness : assets and limits)," Working Papers 200, Laboratoire de Recherche sur l'Industrie et l'Innovation. ULCO / Research Unit on Industry and Innovation.
    12. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.
    13. Catherine L. Mann, 1990. "Towards the next generation of newly industrializing economies: the roles for macroeconomic policy and the manufacturing sector," International Finance Discussion Papers 376, Board of Governors of the Federal Reserve System (U.S.).
    14. Alfred Steinherr, 1995. "The Pivotal Role of the European Union for Central and Eastern Europe," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 131(III), pages 303-327, September.
    15. 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).
    16. Ola Simonsen, 2007. "An empirical model for durations in stocks," Annals of Finance, Springer, vol. 3(2), pages 241-255, March.
    17. Fatima Sol Murta, 2007. "The Money Market Daily Session :an UHF-GARCH Model Applied to the Portuguese Case Before and After the Introduction Of the Minimum Reserve System of the Single Monetary Policy," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 50(3), pages 285-314.
    18. Kulan Ranasinghe & Mervyn J. Silvapulle, 2008. "Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown," Monash Econometrics and Business Statistics Working Papers 1/08, Monash University, Department of Econometrics and Business Statistics.
    19. Roel C.A. Oomen, 2004. "Statistical Models for High Frequency Security Prices," Econometric Society 2004 North American Winter Meetings 77, Econometric Society.
    20. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    21. David L. Anderson & John Tressler, 2010. "The Merits of Using Citation-Based Journal Weighting Schemes to Measure Research Performance in Economics: The Case of New Zealand," Working Papers in Economics 10/03, University of Waikato.
    22. Kulan Ranasinghe & Mervyn J. Silvapulle, 2008. "Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown," Monash Econometrics and Business Statistics Working Papers 5/08, Monash University, Department of Econometrics and Business Statistics.
    23. Helena Beltran & Albert J. Menkveld, 2004. "Understanding limit order book depth: conditioning on trade informativeness," Econometric Society 2004 Latin American Meetings 142, Econometric Society.
    24. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
    25. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    26. J. David Richardson & Chi Zhang, 1999. "Revealing Comparative Advantage: Chaotic or Coherent Patterns Across Time and Sector and U.S. Trading Partner?," NBER Working Papers 7212, National Bureau of Economic Research, Inc.
    27. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2005. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Working Papers 05-9, HEC Montreal, Canada Research Chair in Risk Management.
    28. Vinokurov, Evgeny, 2007. "L’enclave russe de Kaliningrad : spécificité territoriale et intégration à l’économie mondiale [The Russian Enclave of Kaliningrad: Territorial Specificity and Integration with the World Economy]," MPRA Paper 20939, University Library of Munich, Germany.
    29. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.

  48. BAUWENS, Luc & VEREDAS, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," LIDAM Reprints CORE 1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    2. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    3. Wen Cao & Clifford Hurvich & Philippe Soulier, 2012. "Drift in Transaction-Level Asset Price Models," Working Papers hal-00756372, HAL.
    4. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Nolte, Ingmar & Voev, Valeri, 2007. "Panel intensity models with latent factors: An application to the trading dynamics on the foreign exchange market," CoFE Discussion Papers 07/02, University of Konstanz, Center of Finance and Econometrics (CoFE).
    7. Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
    8. Giovanni De Luca & Giampiero M. Gallo, 2005. "Time-varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometrics Working Papers Archive wp2005_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    9. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    10. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
    11. Zikes, Filip & Barunik, Jozef & Shenai, Nikhil, 2015. "Modeling and forecasting persistent financial durations," FinMaP-Working Papers 36, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    12. Arie Preminger & Christian M. Hafner, 2006. "Deciding Between Garch And Stochastic Volatility Via Strong Decision Rules," Working Papers 0603, Ben-Gurion University of the Negev, Department of Economics.
    13. Allen, David & Ng, K.H. & Peiris, Shelton, 2013. "The efficient modelling of high frequency transaction data: A new application of estimating functions in financial economics," Economics Letters, Elsevier, vol. 120(1), pages 117-122.
    14. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
    15. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. 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.
    17. Alexander Aue & Lajos Horváth & Clifford M. Hurvich & Philippe Soulier, 2014. "Limit Laws in Transaction-Level Asset Price Models," Post-Print hal-00583372, HAL.
    18. Adriana Bortoluzzo & Pedro Morettin & Clelia Toloi, 2010. "Time-varying autoregressive conditional duration model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 847-864.
    19. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    20. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2008. "Scaling in the distribution of intertrade durations of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5818-5825.
    21. Zhou, Weijie & Wang, Zhengxin & Guo, Haiming, 2016. "Modelling volatility recurrence intervals in the Chinese commodity futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 514-525.
    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. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    24. N. Balakrishna & Hira L. Koul, 2017. "Varying kernel marginal density estimator for a positive time series," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(3), pages 531-552, July.
    25. 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).
    26. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    27. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    28. Nikolaus Hautsch & Vahidin Jeleskovic, 2008. "Modelling High-Frequency Volatility and Liquidity Using Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2008-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    30. Bhatti, Chad R., 2009. "Intraday trade and quote dynamics: A Cox regression analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2240-2249.
    31. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    32. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    33. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    34. Pooi AH-HIN & Ng KOK-HAUR & Soo HUEI-CHING, 2016. "Modelling and Forecasting with Financial Duration Data Using Non-linear Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 79-92.
    35. Keith Freeland & Brendan McCabe & Gael Martin, 2004. "Testing for Dependence in Non-Gaussian Time Series Data," Econometric Society 2004 Australasian Meetings 313, Econometric Society.
    36. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
    37. 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.
    38. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    39. Willa Chen & Rohit Deo, 2005. "GMM Estimation for Long Memory Latent Variable Volatility and Duration Models," Econometrics 0501006, University Library of Munich, Germany.
    40. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    41. 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).
    42. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    43. 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.
    44. Chun Liu & John M Maheu, 2010. "Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market," Working Papers tecipa-401, University of Toronto, Department of Economics.
    45. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    46. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
    47. Wei Wei & Denis Pelletier, 2015. "A Jump-Diffusion Model with Stochastic Volatility and Durations," CREATES Research Papers 2015-34, Department of Economics and Business Economics, Aarhus University.
    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. Aerambamoorthy Thavaneswaran & Nalini Ravishanker & You Liang, 2015. "Generalized duration models and optimal estimation using estimating functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 129-156, February.
    50. Rohit Deo & Mengchen Hsieh & Clifford Hurvich, 2005. "Tracing the Source of Long Memory in Volatility," Econometrics 0501005, University Library of Munich, Germany.
    51. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.
    52. Katarzyna Bien-Barkowska, 2011. "Distribution Choice for the Asymmetric ACD Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 55-72.
    53. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 469-488, Summer.
    54. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    55. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
    56. Zhi-Qiang Jiang & Wei Chen & Wei-Xing Zhou, 2008. "Detrended fluctuation analysis of intertrade durations," Papers 0806.2444, arXiv.org.
    57. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    58. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
    59. Katarzyna Bien-Barkowska, 2012. ""Does it take volume to move fx rates?" Evidence from quantile regressions," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 35-52.
    60. 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.
    61. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    62. Gómez-Déniz, E. & Pérez-Rodríguez, J.V., 2019. "Modelling bimodality of length of tourist stay," Annals of Tourism Research, Elsevier, vol. 75(C), pages 131-151.
    63. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    64. Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    65. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Finance Working Papers 22483, East Asian Bureau of Economic Research.
    66. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    67. Roman Huptas, 2009. "Intraday Seasonality in Analysis of UHF Financial Data: Models and Their Empirical Verification," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 128-138.
    68. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    69. Hujer, Reinhard & Vuletic, Sandra, 2007. "Econometric analysis of financial trade processes by discrete mixture duration models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 635-667, February.
    70. Simos G. Meintanis & Bojana Milošević & Marko Obradović, 2020. "Goodness-of-fit tests in conditional duration models," Statistical Papers, Springer, vol. 61(1), pages 123-140, February.
    71. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
    72. Fernandes, Marcelo & Grammig, Joachim, 2002. "A family of autoregressive conditional duration models," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 440, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    73. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2019. "Threshold Stochastic Conditional Duration Model for Financial Transaction Data," JRFM, MDPI, vol. 12(2), pages 1-21, May.
    74. Katarzyna Bień-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 117-142, June.
    75. 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.
    76. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    77. Tomoki Toyabe & Teruo Nakatsuma, 2022. "Stochastic Conditional Duration Model with Intraday Seasonality and Limit Order Book Information," JRFM, MDPI, vol. 15(10), pages 1-25, October.
    78. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
    79. 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.
    80. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    81. 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.
    82. Dungey, Mardi & Jeyasreedharan, Nagaratnam & Li, Tuo, 2010. "Modelling the Time Between Trades in the After-Hours Electronic Equity Futures Market," Working Papers 10451, University of Tasmania, Tasmanian School of Business and Economics, revised 30 May 2012.
    83. 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.
    84. Isuru Ratnayake & V. A. Samaranayake, 2022. "Threshold Asymmetric Conditional Autoregressive Range (TACARR) Model," Papers 2202.03351, arXiv.org, revised Mar 2022.
    85. Dimitrakopoulos, Stefanos & Tsionas, Mike G. & Aknouche, Abdelhakim, 2020. "Ordinal-response models for irregularly spaced transactions: A forecasting exercise," MPRA Paper 103250, University Library of Munich, Germany, revised 01 Oct 2020.
    86. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    87. Dingan Feng & Peter X.-K. Song & Tony S. Wirjanto, 2008. "Time-Deformation Modeling Of Stock Returns Directed By Duration Processes," Working Papers 08010, University of Waterloo, Department of Economics.
    88. DOLADO , Juan J. & RODRIGUEZ-POO, Juan & VEREDAS, David, 2004. "Testing weak exogeneity in the exponential family : an application to financial point processes," LIDAM Discussion Papers CORE 2004049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    89. Katarzyna Bień-Barkowska, 2011. "Multistate asymmetric ACD model: an application to order dynamics in the EUR/PLN spot market," NBP Working Papers 104, Narodowy Bank Polski.
    90. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    91. Patrick Leung & Catherine S. Forbes & Gael M Martin & Brendan McCabe, 2019. "Forecasting Observables with Particle Filters: Any Filter Will Do!," Monash Econometrics and Business Statistics Working Papers 22/19, Monash University, Department of Econometrics and Business Statistics.
    92. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    93. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
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    95. Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
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  49. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    2. Liesenfeld, Roman & Richard, Jean-François, 2004. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Economics Working Papers 2004-12, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    4. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    5. GRAMMIG, Joachim & HEINEN, Andréas & RENGIFO, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market," LIDAM Discussion Papers CORE 2004058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. 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.
    7. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.
    8. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    9. Jean-Francois Richard & Roman Liesenfeld, 2007. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Working Paper 322, Department of Economics, University of Pittsburgh, revised Jan 2004.
    10. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
    11. Omar Euch & Masaaki Fukasawa & Mathieu Rosenbaum, 2018. "The microstructural foundations of leverage effect and rough volatility," Finance and Stochastics, Springer, vol. 22(2), pages 241-280, April.
    12. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Gilles Zumbach, 2015. "Cross-sectional universalities in financial time series," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1901-1912, December.
    14. Ban Zheng & Franc{c}ois Roueff & Fr'ed'eric Abergel, 2013. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Papers 1301.5007, arXiv.org, revised Feb 2014.
    15. Grammig, Joachin & Heinen, Andreas & Rengifo, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market: An empirical analysis using a multivariate count data model," MPRA Paper 8115, University Library of Munich, Germany.

  50. BAUWENS, Luc & BEN OMRANE, Walid & GIOT, Pierre, 2003. "News announcements, market activity and volatility in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2003029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jieun Lee & Doojin Ryu, 2019. "The impacts of public news announcements on intraday implied volatility dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(6), pages 656-685, June.
    2. Evans, Kevin P. & Speight, Alan E.H., 2010. "Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility," Research in International Business and Finance, Elsevier, vol. 24(1), pages 82-101, January.
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  51. BAUWENS, Luc & ROMBOUTS, Jeroen, 2003. "Bayesian clustering of many GARCH models," LIDAM Discussion Papers CORE 2003087, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," OFRC Working Papers Series 2009fe03, Oxford Financial Research Centre.
    2. Francq, Christian & Horvath, Lajos & Zakoian, Jean-Michel, 2009. "Merits and drawbacks of variance targeting in GARCH models," MPRA Paper 15143, University Library of Munich, Germany.
    3. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    4. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    5. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2013. "Risk spillovers in international equity portfolios," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 121-137.
    6. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    8. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    9. Jane L. Harvill & Priya Kohli & Nalini Ravishanker, 2017. "Clustering Nonlinear, Nonstationary Time Series Using BSLEX," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 935-955, September.
    10. Rombouts Jeroen V. K. & Bouaddi Mohammed, 2009. "Mixed Exponential Power Asymmetric Conditional Heteroskedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-32, May.
    11. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Robert Darkins & Emma J Cooke & Zoubin Ghahramani & Paul D W Kirk & David L Wild & Richard S Savage, 2013. "Accelerating Bayesian Hierarchical Clustering of Time Series Data with a Randomised Algorithm," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    13. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Model-based Clustering of non-Gaussian Panel Data," MPRA Paper 880, University Library of Munich, Germany.
    14. Sylvia Frühwirth-Schnatter, 2011. "Panel data analysis: a survey on model-based clustering of time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 251-280, December.
    15. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    16. Brownlees, Christian T., 2019. "Hierarchical GARCH," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 17-27.

  52. BAUWENS, Luc & GALLI, Fausto & GIOT, Pierre, 2003. "The moments of Log-ACD models," LIDAM Discussion Papers CORE 2003011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    2. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    3. Helton Saulo & Narayanaswamy Balakrishnan & Roberto Vila, 2021. "On a quantile autoregressive conditional duration model applied to high-frequency financial data," Papers 2109.03844, arXiv.org.
    4. 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).
    5. Feng, Yuanhua & Zhou, Chen, 2015. "Forecasting financial market activity using a semiparametric fractionally integrated Log-ACD," International Journal of Forecasting, Elsevier, vol. 31(2), pages 349-363.
    6. Simonsen, Ola, 2006. "The Impact of News Releases on Trade Durations in Stocks -Empirical Evidence from Sweden," Umeå Economic Studies 688, Umeå University, Department of Economics.
    7. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2019. "Realized variance modeling: decoupling forecasting from estimation," Econometrics Working Papers Archive 2019_05, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    8. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 122, Paderborn University, CIE Center for International Economics.
    9. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    10. Ola Simonsen, 2007. "An empirical model for durations in stocks," Annals of Finance, Springer, vol. 3(2), pages 241-255, March.
    11. Allen, David & Chan, Felix & McAleer, Michael & Peiris, Shelton, 2008. "Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks," Journal of Econometrics, Elsevier, vol. 147(1), pages 163-185, November.
    12. Aerambamoorthy Thavaneswaran & Nalini Ravishanker & You Liang, 2015. "Generalized duration models and optimal estimation using estimating functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 129-156, February.
    13. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.
    14. Simonsen, Ola, 2006. "Stock Data, Trade Durations, And Limit Order Book Information," Umeå Economic Studies 689, Umeå University, Department of Economics.
    15. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 125, Paderborn University, CIE Center for International Economics.
    16. Katarzyna Bień-Barkowska, 2011. "Multistate asymmetric ACD model: an application to order dynamics in the EUR/PLN spot market," NBP Working Papers 104, Narodowy Bank Polski.
    17. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Jan Beran & Yuanhua Feng & Sucharita Ghosh, 2015. "Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models," Statistical Papers, Springer, vol. 56(2), pages 431-451, May.
    19. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    20. Yuanhua Feng & Jan Beran & Sebastian Letmathe & Sucharita Ghosh, 2020. "Fractionally integrated Log-GARCH with application to value at risk and expected shortfall," Working Papers CIE 137, Paderborn University, CIE Center for International Economics.

  53. BAUWENS, Luc & KIRMAN, Alan & LUBRANO, Michel & PROTOPOPESCU, Camelia, 2003. "Ranking economics departments in Europe: a statistical approach," LIDAM Discussion Papers CORE 2003050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Ruiz-Castillo, Javier, 2006. "Economics research in Spain during the 1990's : a literature review," UC3M Working papers. Economics we063609, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Tombazos, Christis G., 2005. "A revisionist perspective of European research in economics," European Economic Review, Elsevier, vol. 49(2), pages 251-277, February.
    3. Raul Ramos & Vicente Royuela & Jordi Suriñach, 2006. "An analysis of the determinants in economics and business publications by spanish universities between 1994 and 2004," IREA Working Papers 200602, University of Barcelona, Research Institute of Applied Economics, revised Dec 2006.
    4. van Dalen, Hendrik Peter, 2021. "How the publish-or-perish principle divides a science: The case of economists," Other publications TiSEM a6a5a855-bb5a-4d52-a841-3, Tilburg University, School of Economics and Management.
    5. Frank Neri & Joan Rodgers, 2012. "Human capital externalities, departmental co-authorship and research productivity," Economics Working Papers wp12-05, School of Economics, University of Wollongong, NSW, Australia.
    6. Püttmann, Vitus & Thomsen, Stephan L. & Trunzer, Johannes, 2020. "Zur Relevanz von Ausstattungsunterschieden für Forschungsleistungsvergleiche: Ein Diskussionsbeitrag für die Wirtschaftswissenschaften in Deutschland," Hannover Economic Papers (HEP) dp-679, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Mar 2021.
    7. Chih-Sheng Hsieh & Michael D. König & Xiaodong Liu & Christian Zimmermann, 2018. "Superstar Economists: Coauthorship networks and research output," Working Papers 2018-28, Federal Reserve Bank of St. Louis.
    8. Mustafa Kadir DOĞAN & Tolga YURET, 2013. "Publication Performance and Student Quality of Turkish Economics Departments," Sosyoekonomi Journal, Sosyoekonomi Society, issue 19(19).
    9. Frances Ruane & Richard S.J. Tol, 2007. "Centres of Research Excellence in Economics in the Republic of Ireland," Papers WP180, Economic and Social Research Institute (ESRI).
    10. Henrekson, Magnus & Waldenström, Daniel, 2008. "How Should Research Performance Be Measured? A Study of Swedish Economists," SSE/EFI Working Paper Series in Economics and Finance 693, Stockholm School of Economics.
    11. Miriam Hein, 2005. "Wie hat sich die universitaere volkswirtschaftliche Forschung in der Schweiz seit Beginn der 90er Jahre entwickelt?�," TWI Research Paper Series 11, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    12. Chokri Dridi & Wiktor L. Adamowicz & Alfons Weersink, 2010. "Ranking of Research Output of Agricultural Economics Departments in Canada and Selected U.S. Universities," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(3), pages 273-282, September.
    13. Haucap Justus & Mödl Michael, 2013. "Zum Verhältnis von Spitzenforschung und Politikberatung: Eine empirische Analyse vor dem Hintergrund des Ökonomenstreits," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 14(3-4), pages 346-378, August.
    14. Miguel sarmiento, 2009. "Central Bank Economic Research: Output, Demand, Productivity, and Relevance," Borradores de Economia 5935, Banco de la Republica.
    15. Stephen Bazen & Patrick Moyes, 2011. "Elitism and Stochastic Dominance," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00576585, HAL.
    16. Mark J. McCabe & Christopher M. Snyder, 2015. "Does Online Availability Increase Citations? Theory and Evidence from a Panel of Economics and Business Journals," The Review of Economics and Statistics, MIT Press, vol. 97(1), pages 144-165, March.
    17. Stelios Katranidis & Theodore Panagiotidis & Kostas Zontanos, 2022. "A note on the relative productivity drivers of economists: a probit/logit approach for six European countries," Economic Change and Restructuring, Springer, vol. 55(4), pages 2171-2178, November.
    18. Rabah Amir & Malgorzata Knauff, 2008. "Ranking Economics Departments Worldwide on the Basis of PhD Placement," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 185-190, August.
    19. Giannias Dimitris A. & Sfakianaki Eleni, 2012. "University Rankings of Different Academic Positions for the Present and the Future: The Case of Greek Departments of Economics," Scientific Annals of Economics and Business, Sciendo, vol. 59(2), pages 43-66, December.
    20. Tom Coupé, 2003. "Revealed Performances: Worldwide Rankings of Economists and Economics Departments, 1990-2000," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1309-1345, December.
    21. Carrasco, Raquel & Ruiz-Castillo, Javier, 2012. "The evolution of the scientific productivity of highly productive economist," UC3M Working papers. Economics we1216, Universidad Carlos III de Madrid. Departamento de Economía.
    22. Badi H. Baltagi, 2007. "Worldwide Econometrics Rankings: 1989-2005," Center for Policy Research Working Papers 94, Center for Policy Research, Maxwell School, Syracuse University.
    23. Hendrik P. van Dalen, 2019. "Values of Economists Matter in the Art and Science of Economics," Kyklos, Wiley Blackwell, vol. 72(3), pages 472-499, August.
    24. Esteban Colla De Robertis, 2010. "Monetary policy committees and the decision to publish voting records," Documentos de Investigación - Research Papers 1, CEMLA.
    25. van Ours, J.C. & Vermeulen, F.M.P., 2007. "Ranking Dutch economists," Other publications TiSEM 22ef61f4-2610-4223-a75b-7, Tilburg University, School of Economics and Management.
    26. Angelina Keil & Peter Huber, 2004. "„Wo die Luft dünn wird…”– Zur Publikationstätigkeit der Wirtschaftsforschungsinstitute Österreichs und Deutschlands," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 5(3), pages 363-375, August.
    27. Mladen Djuric & Jovan Filipovic & Stefan Komazec, 2020. "Reshaping the Future of Social Metrology: Utilizing Quality Indicators to Develop Complexity-Based Scientific Human and Social Capital Measurement Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(2), pages 535-567, April.
    28. Michael Graber & Andrey Launov & Klaus Waelde, 2007. "How to get tenured," Working Papers 030, Bavarian Graduate Program in Economics (BGPE).
    29. Azar, Ofer H. & Brock, David M., 2007. "A Citation-Based Ranking of Strategic Management Journals," MPRA Paper 7066, University Library of Munich, Germany.
    30. Michael Graber & Andrey Launov & Klaus Wälde, 2008. "Publish or Perish? The Increasing Importance of Publications for Prospective Economics Professors in Austria, Germany and Switzerland," German Economic Review, Verein für Socialpolitik, vol. 9(4), pages 457-472, November.
    31. Angelini, Paolo, 2003. "Small is beautiful but large is not to be belittled: a comment on Eijffinger et al. [Eur. J. Political Economy 18 (2002) 365-374]," European Journal of Political Economy, Elsevier, vol. 19(4), pages 901-903, November.
    32. Fredrick M. Wamalwa & Justine Burns, 2018. "Teacher Human Capital, Teacher Effort and Student Achievements in Kenya," Working Papers 150, Economic Research Southern Africa.
    33. Albarrán, Pedro & Carrasco, Raquel & Ruiz-Castillo, Javier, 2016. "Are migrants more productive than stayers? Some evidence for a set of highly productive academic economists," UC3M Working papers. Economics 23424, Universidad Carlos III de Madrid. Departamento de Economía.
    34. Azar, Ofer H., 2006. "Behavioral economics and socio-economics journals: A citation-based ranking," MPRA Paper 4377, University Library of Munich, Germany.
    35. James B. Davies & Martin G. Kocher & Matthias Sutter, 2008. "Economics research in Canada: a long‐run assessment of journal publications," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 22-45, February.
    36. Nicolas CARAYOL & Agenor LAHATTE, 2014. "Dominance relations and ranking when quantity and quality both matter: Applications to US universities and econ. departments worldwide," Cahiers du GREThA (2007-2019) 2014-14, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    37. Raquel Carrasco & Javier Ruiz-Castillo, 2019. "Spatial mobility in elite academic institutions in economics: the case of Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 141-172, June.
    38. José M. Merigó & Jian-Bo Yang, 2017. "Accounting Research: A Bibliometric Analysis," Australian Accounting Review, CPA Australia, vol. 27(1), pages 71-100, March.
    39. J. Barkley Rosser Jr & Richard P.F. Holt & David Colander, 2010. "European Economics at a Crossroads," Books, Edward Elgar Publishing, number 13585.
    40. Jang C. Jin, 2009. "Publications in mathematical economics and econometrics: ranking of Asian universities and an application of Zipf's law," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 23(2), pages 116-122, November.
    41. Mathieu Goudard & Michel Lubrano, 2011. "Human capital, social capital and scientific research in Europe: an application of linear hierarchical models," Working Papers halshs-00601033, HAL.
    42. Néstor Garza & Gisell Pugliese, 2009. "Elección teórica en economía: el caso de las teorías de crecimiento de Solow, Romer y Ramsey," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, June.
    43. Libman, A., 2010. "Economics in Germany – from National to Global," Journal of the New Economic Association, New Economic Association, issue 8, pages 155-158.
    44. David L. Anderson & John Tressler, 2008. "Research Output in New Zealand Economics Department 2000-2006," Working Papers in Economics 08/05, University of Waikato.
    45. Stelios Katranidis & Theodore Panagiotidis & Costas Zontanos, 2016. "Economists, research performance and national inbreeding:North versus South," Discussion Paper Series 2016_01, Department of Economics, University of Macedonia, revised Oct 2016.
    46. David I. Stern & Richard S. J. Tol, 2021. "Depth and breadth relevance in citation metrics," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 961-977, July.
    47. Susanne Warning & Christian Wiermann & Günther G. Schulze, 2008. "Zeitschriftenrankings für die Wirtschaftswissenschaften Konstruktion eines umfassenden Metaindexes," Discussion Paper Series 3, Department of International Economic Policy, University of Freiburg, revised Mar 2008.
    48. Stelios Katranidis & Theodore Panagiotidis & Costas Zontanos, 2012. "An Evaluation of the Greek Universities Economics Departments," Working Paper series 03_12, Rimini Centre for Economic Analysis.
    49. Ritzberger Klaus, 2008. "A Ranking of Journals in Economics and Related Fields," German Economic Review, De Gruyter, vol. 9(4), pages 402-430, December.
    50. Dolado, Juan José & García-Romero, Antonio & Zamarro, Gema, 2002. "Research in economics in Spain: rankings of institutions and authors," UC3M Working papers. Economics we023112, Universidad Carlos III de Madrid. Departamento de Economía.
    51. murat cokgezen, 2005. "Publication Performance Of Economists And Economics Departments In Turkey (1999-2003)," General Economics and Teaching 0503007, University Library of Munich, Germany, revised 17 Jan 2006.
    52. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2012. "A comparison of top economics departments in the US and EU on the basis of the multidimensional prestige of influential articles in 2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 681-698, December.
    53. Teodora Diana Corsatea, 2010. "Measuring science: Spatial investigation of academic opportunities in Belgium," Papers in Regional Science, Wiley Blackwell, vol. 89(2), pages 373-387, June.
    54. Peter Huber & Angelina Keil, 2007. "Ach wie gut, dass niemand weiß ...? Anmerkungen zur Methodenwahl bei Institutsrankings," WIFO Working Papers 287, WIFO.
    55. Rodgers, Joan R. & Valadkhani, Abbas, 2005. "Ranking of Australian Economics Departments Based on Their Total and Per Academic Staff Research Output," Economics Working Papers wp05-18, School of Economics, University of Wollongong, NSW, Australia.
    56. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia & Nicolas Robinson-García & Daniel Torres-Salinas, 2013. "Benchmarking research performance at the university level with information theoretic measures," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 435-452, April.
    57. Stefano Benati & Silvana Stefani, 2011. "The Academic Journal Ranking Problem: A Fuzzy-Clustering Approach," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 7-20, April.
    58. Kevin Greenidge & Lisa Drakes, 2010. "Tax Policy and Macroeconomic Activity in Barbados," Money Affairs, CEMLA, vol. 0(2), pages 182-210, July-Dece.
    59. van Dalen, Hendrik Peter, 2020. "How the Publish-or-Perish Principle Divides a Science : The Case of Academic Economists," Other publications TiSEM 6fbb6b92-0e06-4271-b6e7-3, Tilburg University, School of Economics and Management.
    60. Laurens Cherchye & Frederic Vermeulen, 2004. "Robust rankings of multi-dimensional performances: An application to Tour de France racing cyclists," Public Economics Working Paper Series wptourf, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
    61. Michael Graber & Andrey Launov & Klaus Wälde, 2007. "How to Get Tenured (in Germany, in Economics)," Working Papers 2007_32, Business School - Economics, University of Glasgow.
    62. Marcella Corsi & Carlo D'Ippoliti & Federico Lucidi, 2011. "On the Evaluation of Economic Research: The Case of Italy," Economia politica, Società editrice il Mulino, issue 3, pages 369-402.
    63. Ruiz-Castillo, Javier, 2006. "La investigación en economía en España durante los años 90 : una revisión de la literatura," DE - Documentos de Trabajo. Economía. DE de060201, Universidad Carlos III de Madrid. Departamento de Economía.
    64. Justus Haucap, 2020. "Wirtschaftswissenschaftliche Politikberatung in Deutschland: Stärken, Schwächen, Optimierungspotenzial," Springer Books, in: Dirk Loerwald (ed.), Ökonomische Erkenntnisse verständlich vermitteln, pages 45-78, Springer.
    65. Vicente Royuela & Juan Carlos Duque & Raul Ramos, 2005. "Regional and Urban Research in Italy during the Nineties: Evidence from Publications in Nine Top International Journals," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2005(3).
    66. Jorge Ponce, 2010. "A Normative Analysis of Banking Supervision: Independence, Legal Protection and Accountability," Money Affairs, CEMLA, vol. 0(2), pages 141-181, July-Dece.
    67. Klaus Ritzberger, 2008. "Eine invariante Bewertung wirtschaftswissenschaftlicher Fachzeitschriften," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 9(3), pages 267-285, August.
    68. Johan Lyhagen & Per Ahlgren, 2020. "Uncertainty and the ranking of economics journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2545-2560, December.
    69. Derek Yu & Atoko Kasongo & Mariana Moses, 2016. "Examining the performance of the South African economics departments, 2005-2014," Working Papers 13/2016, Stellenbosch University, Department of Economics.
    70. Laurens Cherchye & Frederic Vermeulen, 2006. "Robust Rankings of Multidimensional Performances," Journal of Sports Economics, , vol. 7(4), pages 359-373, November.
    71. Jin, Jang C., 2005. "Economics departmental rankings in Korea: A decade later," Journal of Asian Economics, Elsevier, vol. 16(2), pages 223-237, April.
    72. Martin Gregor & Ondrej Schneider, 2005. "The World is Watching: Rankings of Czech and Slovak Economics Departments (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 55(11-12), pages 518-530, November.
    73. Joan R. Rodgers & Abbas Valadkhani, 2006. "A Multidimensional Ranking of Australian Economics Departments," The Economic Record, The Economic Society of Australia, vol. 82(256), pages 30-43, March.
    74. Aziz Kutlar & Ali Kabasakal & Mehmet Sena Ekici, 2013. "Contributions of Turkish academicians supervising PhD dissertations and their universities to economics: an evaluation of the 1990–2011 period," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 639-658, December.
    75. Murat Çokgezen, 2019. "Research Performance of Turkish Economists and Economics Departments: Another Update and a Review of the 2000s," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(1), pages 133-149, January.
    76. Murat Çokgezen, 2006. "Publication Performance of Economists and Economics Departments in Turkey (1999–2003)," Bulletin of Economic Research, Wiley Blackwell, vol. 58(3), pages 253-265, July.
    77. Martin Gregor, 2006. "Hodnocení ekonomických pracovišť a ekonomů: Koho, proč, čím a jak [A survey of rankings of economic departments: Global, american, european and national]," Politická ekonomie, Prague University of Economics and Business, vol. 2006(3), pages 394-414.
    78. Jang C. Jin, 2009. "Asian University Rankings in International and Development Economics: An Application of Zipf's Law," Review of International Economics, Wiley Blackwell, vol. 17(1), pages 137-143, February.
    79. Frank Neri & Joan R. Rodgers, 2013. "Eagles and Turkeys: Human Capital Externalities, Departmental Co-authorship and Research Productivity," Australian Economic Papers, Wiley Blackwell, vol. 52(3-4), pages 171-189, December.
    80. Maria Racionero, 2009. "Susanne Warning, The Economic Analysis of Universities: Strategic Groups and Positioning (Edward Elgar Publishing, 2007)," Agenda - A Journal of Policy Analysis and Reform, Australian National University, College of Business and Economics, School of Economics, vol. 16(1), pages 83-86.
    81. Hendrik P. Dalen, 2021. "How the publish-or-perish principle divides a science: the case of economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1675-1694, February.
    82. Pierre St-Amant & Greg Tkacz & Annie Guérard-Langlois & Louis Morel, 2005. "Quantity, Quality, and Relevance: Central Bank Research, 1990-2003," Staff Working Papers 05-37, Bank of Canada.
    83. Barbara Dluhosch, 2011. "European Economics at a Crossroads, by J. Barkley Rosser, Jr., Richard P. F. Holt, and David Colander," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 629-631, August.
    84. Frank Neri & Joan R. Rodgers, 2006. "Ranking Australian Economics Departments by Research Productivity," The Economic Record, The Economic Society of Australia, vol. 82(s1), pages 74-84, September.
    85. Silvia Ferrini, 2007. "L’Impact Factor: luci e ombre," Department of Economic Policy, Finance and Development (DEPFID) University of Siena 002, Department of Economic Policy, Finance and Development (DEPFID), University of Siena.
    86. Jin, Jang C. & Hong, Jin-Heon, 2008. "East Asian rankings of economics departments," Journal of Asian Economics, Elsevier, vol. 19(1), pages 74-82, February.
    87. James Foster & Joel Greer & Erik Thorbecke, 2010. "The Foster–Greer–Thorbecke (FGT) poverty measures: 25 years later," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 8(4), pages 491-524, December.
    88. James E. Foster & Joel Greer & Erik Thorbecke, 2010. "The Foster-Greer-Thorbecke (FGT) Poverty Measures: Twenty-Five Years Later," Working Papers 2010-14, The George Washington University, Institute for International Economic Policy.
    89. David Anderson & John Tressler, 2008. "Research output in New Zealand economics departments 2000-2006: A stock approach," New Zealand Economic Papers, Taylor & Francis Journals, vol. 42(2), pages 155-189.
    90. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Geographic mobility and research productivity in a selection of top world economics departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 241-265, April.

  54. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen, 2003. "Multivariate GARCH models: a survey," LIDAM Discussion Papers CORE 2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Rasmus Søndergaard Pedersen & Anders Rahbek, 2012. "Multivariate Variance Targeting in the BEKK-GARCH Model," Discussion Papers 12-23, University of Copenhagen. Department of Economics.
    2. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    3. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    4. Joanna Olbrys, 2013. "Asymmetric impact of innovations on volatility in the case of the US and CEEC-3 markets: EGARCH based approach," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 33-50.
    5. Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," OFRC Working Papers Series 2009fe03, Oxford Financial Research Centre.
    6. 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.
    7. Gianluca Cubadda & Alain Hecq, 2021. "Reduced Rank Regression Models in Economics and Finance," CEIS Research Paper 525, Tor Vergata University, CEIS, revised 08 Nov 2021.
    8. Ariana Paola Cortés Ángel & Mustafa Hakan Eratalay, 2022. "Deep diving into the S&P Europe 350 index network and its reaction to COVID-19," Journal of Computational Social Science, Springer, vol. 5(2), pages 1343-1408, November.
    9. Piotr Fiszeder, 2011. "Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 87-98.
    10. Julyerme M. Tonin & Carlos M. R. Vieira & Rui M. de Sousa Fragoso & João G. Martines Filho, 2020. "Conditional correlation and volatility between spot and futures markets for soybean and corn," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 707-724, October.
    11. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    12. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.
    13. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    14. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    15. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
    16. Pierre O. De souza & Tiago P. Filomena & João F. Caldeira & Denis Borenstein & Marcelo B. Righi, 2017. "Risk parity in the brazilian market," Economics Bulletin, AccessEcon, vol. 37(3), pages 1555-1566.
    17. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    18. Olessia Caillé & Daria Onori, 2019. "Conditional Risk-Based Portfolio," Finance, Presses universitaires de Grenoble, vol. 40(2), pages 77-117.
    19. Roberto Pascual & David Veredas, 2009. "Does the open limit order book matter in explaining informational volatility?," ULB Institutional Repository 2013/183777, ULB -- Universite Libre de Bruxelles.
    20. Raddant, Matthias & Wagner, Friedrich, 2016. "Multivariate GARCH for a large number of stocks," Kiel Working Papers 2049, Kiel Institute for the World Economy (IfW Kiel).
    21. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques) 2005044, Université catholique de Louvain, Département des Sciences Economiques.
    22. Chamizo, Álvaro & Novales, Alfonso, 2021. "Evaluation of market risk associated with hedging a credit derivative portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 411-430.
    23. Santos, André A.P. & Nogales, Francisco J. & Ruiz, Esther & Dijk, Dick Van, 2012. "Optimal portfolios with minimum capital requirements," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1928-1942.
    24. Yu-Pin Hu & Ruey S. Tsay, 2014. "Principal Volatility Component Analysis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 153-164, April.
    25. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    26. Horvath, Roman & Poldauf, Petr, 2011. "International stock market comovements: what happened during the financial crisis?," MPRA Paper 35317, University Library of Munich, Germany.
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  55. BAUWENS, Luc & GIOT, Pierre, 2003. "Asymmetric ACD models: Introducing price information in ACD models," LIDAM Reprints CORE 1670, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Nowak, Sylwia & Anderson, Heather M., 2014. "How does public information affect the frequency of trading in airline stocks?," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 26-38.
    2. Saulo, Helton & Balakrishnan, Narayanaswamy & Vila, Roberto, 2023. "On a quantile autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 425-448.
    3. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    4. A. Durre & H. Beltran & P. Giot, 2006. "Volatility regimes and the provision of liquidity in order book markets," Post-Print hal-00260870, HAL.
    5. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    6. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    7. Helena Beltran & Alain Durré & Pierre Giot, 2004. "How does liquidity react to stress periods in a limit order market?," Working Paper Research 49, National Bank of Belgium.
    8. Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
    9. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
    11. Christian M. Hafner, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1363-1379, December.
    12. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006.
    13. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    14. Paola Zuccolotto, 2002. "Modelling the impact of open volume on inter-trade autoregressive durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 49-63.
    15. Pooi AH-HIN & Ng KOK-HAUR & Soo HUEI-CHING, 2016. "Modelling and Forecasting with Financial Duration Data Using Non-linear Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 79-92.
    16. Giot, Pierre & Schwienbacher, Armin, 2007. "IPOs, trade sales and liquidations: Modelling venture capital exits using survival analysis," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 679-702, March.
    17. Ahmed M. Khalid & Gulasekaran Rajaguru, 2004. "Financial Market Linkages in South Asia: Evidence Using a Multivariate GARCH Model," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 43(4), pages 585-603.
    18. Christian Hafner, 2005. "Durations, volume and the prediction of financial returns in transaction time," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 145-152.
    19. 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).
    20. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    21. Aerambamoorthy Thavaneswaran & Nalini Ravishanker & You Liang, 2015. "Generalized duration models and optimal estimation using estimating functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 129-156, February.
    22. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.
    23. Katarzyna Bien-Barkowska, 2011. "Distribution Choice for the Asymmetric ACD Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 55-72.
    24. M. Dolores Jiménez-Gamero & Sangyeol Lee & Simos G. Meintanis, 2020. "Goodness-of-fit tests for parametric specifications of conditionally heteroscedastic models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 682-703, September.
    25. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 469-488, Summer.
    26. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.
    27. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    28. Yiing Fei Tan & Kok Haur Ng & You Beng Koh & Shelton Peiris, 2022. "Modelling Trade Durations Using Dynamic Logarithmic Component ACD Model with Extended Generalised Inverse Gaussian Distribution," Mathematics, MDPI, vol. 10(10), pages 1-20, May.
    29. Liu, Shouwei & Tse, Yiu-Kuen, 2015. "Intraday Value-at-Risk: An asymmetric autoregressive conditional duration approach," Journal of Econometrics, Elsevier, vol. 189(2), pages 437-446.
    30. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Finance Working Papers 22483, East Asian Bureau of Economic Research.
    31. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    32. Charlie X. Cai & Qi Zhang, 2016. "High†Frequency Exchange Rate Forecasting," European Financial Management, European Financial Management Association, vol. 22(1), pages 120-141, January.
    33. Danúbia R. Cunha & Roberto Vila & Helton Saulo & Rodrigo N. Fernandez, 2020. "A General Family of Autoregressive Conditional Duration Models Applied to High-Frequency Financial Data," JRFM, MDPI, vol. 13(3), pages 1-20, March.
    34. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    35. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
    36. Pérez-Rodríguez, Jorge V. & Sosvilla-Rivero, Simón & Andrada-Felix, Julián & Gómez-Déniz, Emilio, 2022. "Searching for informed traders in stock markets: The case of Banco Popular," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    37. Pyrlik, Vladimir, 2013. "Autoregressive conditional duration as a model for financial market crashes prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6041-6051.
    38. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    39. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    40. Petchey, James & Wee, Marvin & Yang, Joey, 2016. "Pinning down an effective measure for probability of informed trading," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 456-475.
    41. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
    42. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
    43. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Improved ACD-based financial trade durations prediction leveraging LSTM networks and Attention Mechanism," Papers 2101.02736, arXiv.org.
    44. Qi Zhang & Charlie X Cai & Kevin Keasey, 2009. "Forecasting using high-frequency data: a comparison of asymmetric financial duration models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 371-386.
    45. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    46. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.

  56. Luc Bauwens & Charles S. Bos & Herman K. van Dijk & Rutger D. van Oest, 2002. "Adaptive Polar Sampling," Computing in Economics and Finance 2002 307, Society for Computational Economics.

    Cited by:

    1. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Adaptive radial-based direction sampling; Some flexible and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2003-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    3. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.
    4. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    5. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, University Library of Munich, Germany.

  57. BAUWENS, Luc & LAURENT, Sébastien, 2002. "A new class of multivariate skew densities, with application to GARCH models," LIDAM Discussion Papers CORE 2002020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    2. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    3. Jondeau, E. & Rockinger, M., 2004. "Optimal Portfolio Allocation Under Higher Moments," Working papers 108, Banque de France.
    4. 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".
    5. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Michal Kaut & Stein Wallace, 2011. "Shape-based scenario generation using copulas," Computational Management Science, Springer, vol. 8(1), pages 181-199, April.
    7. GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    9. Vincenzo Candila, 2013. "A Comparison of the Forecasting Performances of Multivariate Volatility Models," Working Papers 3_228, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    10. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    11. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    12. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    13. Giuseppe Storti & Luc Bauwens, 2006. "A component GARCH model with time varying weights," Computing in Economics and Finance 2006 388, Society for Computational Economics.
    14. LOMBARDI, Marco & VEREDAS, David, 2007. "Indirect estimation of elliptical stable distributions," LIDAM Discussion Papers CORE 2007018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Mencia, Javier F. & Sentana, Enrique, 2004. "Estimation and testing of dynamic models with generalised hyperbolic innovations," LSE Research Online Documents on Economics 24742, London School of Economics and Political Science, LSE Library.
    16. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    17. Kai-Li Wang & Mei-Ling Chen, 2007. "The dynamics in the spot, futures, and call options with basis asymmetries: an intraday analysis in a generalized multivariate GARCH-M MSKST framework," Review of Quantitative Finance and Accounting, Springer, vol. 29(4), pages 371-394, November.
    18. Eric Jondeau & Michael Rockinger, 2005. "Conditional Asset Allocation under Non-Normality: How Costly is the Mean-Variance Criterion?," FAME Research Paper Series rp132, International Center for Financial Asset Management and Engineering.
    19. Bal??zs ??gert & Ev??en Kocenda, 2007. "Time-Varying Comovements in Developed and Emerging European Stock Markets: Evidence from Intraday Data," William Davidson Institute Working Papers Series wp861, William Davidson Institute at the University of Michigan.
    20. Zhu, Dongming & Galbraith, John W., 2010. "A generalized asymmetric Student-t distribution with application to financial econometrics," Journal of Econometrics, Elsevier, vol. 157(2), pages 297-305, August.
    21. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2009. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working Papers 0905, University of Nevada, Las Vegas , Department of Economics.
    22. Deniz Erdemlioglu & Sebastien Laurent & Christopher J. Neely, 2012. "Econometric modeling of exchange rate volatility and jumps," Working Papers 2012-008, Federal Reserve Bank of St. Louis.
    23. 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.
    24. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    25. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
    26. Boswijk, H.P. & Weide, R. van der, 2006. "Wake me up before you GO-GARCH," CeNDEF Working Papers 06-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    27. Choi, Pilsun & Nam, Kiseok, 2008. "Asymmetric and leptokurtic distribution for heteroscedastic asset returns: The SU-normal distribution," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 41-63, January.
    28. John Galbraith & Dongming Zhu, 2009. "Forecasting Expected Shortfall With A Generalized Asymmetric Student-T Distribution," Departmental Working Papers 2009-01, McGill University, Department of Economics.
    29. Fantazzini, Dean, 2008. "An Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 10(2), pages 91-137.
    30. Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, University Library of Munich, Germany.
    31. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    32. Eric Jondeau & Michael Rockinger, 2002. "Conditional Dependency of Financial Series: The Copula-GARCH Model," FAME Research Paper Series rp69, International Center for Financial Asset Management and Engineering.
    33. Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.

  58. BAUWENS , Luc & LUBRANO, Michel, 2002. "Bayesian option pricing using asymmetric GARCH models," LIDAM Reprints CORE 1569, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    2. Martin, G.M. & Forbes, C.S. & Martin, V.L., 2000. "Implicit Bayesian Inference Using Option Prices," Monash Econometrics and Business Statistics Working Papers 5/00, Monash University, Department of Econometrics and Business Statistics.
    3. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    4. G.C. Lim & G.M. Martin & V.L. Martin, 2002. "Parametric Pricing of Higher Order Moments in S&P500 Options," Monash Econometrics and Business Statistics Working Papers 1/02, Monash University, Department of Econometrics and Business Statistics.
    5. Ausin, Maria Concepcion & Galeano, Pedro, 2007. "Bayesian estimation of the Gaussian mixture GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2636-2652, February.
    6. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    8. Chiang, Min-Hsien & Huang, Hsin-Yi, 2011. "Stock market momentum, business conditions, and GARCH option pricing models," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 488-505, June.
    9. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 387-418.
    10. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Yuzhi Cai, 2021. "Estimating expected shortfall using a quantile function model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4332-4360, July.
    12. Abel Rodr�guez & Enrique ter Horst, 2011. "Measuring expectations in options markets: an application to the S&P500 index," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1393-1405, July.
    13. Eirini Konstantinidi & Gkaren Papazian & George Skiadopoulos, 2015. "Modeling the Dynamics of Temperature with a View to Weather Derivatives," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 17, pages 511-544, World Scientific Publishing Co. Pte. Ltd..
    14. Ehlers, Ricardo S., 2012. "Computational tools for comparing asymmetric GARCH models via Bayes factors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 858-867.
    15. Lisha Lin & Yaqiong Li & Rui Gao & Jianhong Wu, 2019. "The Numerical Simulation of Quanto Option Prices Using Bayesian Statistical Methods," Papers 1910.04075, arXiv.org.
    16. Kiyotaka Satoyoshi & Hidetoshi Mitsui, 2011. "Empirical Study of Nikkei 225 Options with the Markov Switching GARCH Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(1), pages 55-68, March.
    17. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    18. Tunaru, Radu & Zheng, Teng, 2017. "Parameter estimation risk in asset pricing and risk management: A Bayesian approach," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 80-93.
    19. Anna Pajor, 2009. "Bayesian Analysis of the Box-Cox Transformation in Stochastic Volatility Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 81-90.
    20. Lin, Lisha & Li, Yaqiong & Gao, Rui & Wu, Jianhong, 2021. "The numerical simulation of Quanto option prices using Bayesian statistical methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    21. Chen, Yufeng & Xu, Jing & Miao, Jiafeng, 2023. "Dynamic volatility contagion across the Baltic dry index, iron ore price and crude oil price under the COVID-19: A copula-VAR-BEKK-GARCH-X approach," Resources Policy, Elsevier, vol. 81(C).
    22. Darsinos, T. & Satchell, S.E., 2001. "Bayesian Forecasting of Options Prices: A Natural Framework for Pooling Historical and Implied Volatiltiy Information," Cambridge Working Papers in Economics 0116, Faculty of Economics, University of Cambridge.
    23. Fonseca, Thais C O & Cerqueira, Vinicius S & Migon, Helio S & Torres, Christian A C, 2021. "Evaluating the performance of degrees of freedom estimation in asymmetric GARCH models with t-student innovations," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(2), April.
    24. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," JRFM, MDPI, vol. 4(1), pages 1-23, December.
    25. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    26. Li, Chao & Shang, Pengjian, 2018. "Complexity analysis based on generalized deviation for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 118-128.

  59. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2002. "Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2002-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Adaptive radial-based direction sampling; Some flexible and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2003-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.
    3. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, University Library of Munich, Germany.

  60. BAUWENS, Luc & HUNTER, John, 2000. "Identifying long-run behaviour with non-stationary data," LIDAM Discussion Papers CORE 2000043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Tabaghdehi, Seyedeh Asieh H. & Hunter, John, 2020. "Long-run price behaviour in the gasoline market - The role of exogeneity," Journal of Business Research, Elsevier, vol. 116(C), pages 620-627.

  61. BAUWENS, Luc & GINSBURGH, Victor, 2000. "Art experts and auctions are pre-sale estimates unbiased and fully informative?," LIDAM Reprints CORE 1485, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michel Clement & Anke Lepthien & Tim Schulze, 2016. "Erfolgsfaktoren bei der Vermarktung von Kunst [Success Factors for Marketing of Arts]," Schmalenbach Journal of Business Research, Springer, vol. 68(4), pages 377-400, December.
    2. Melissa Boyle & Justin Svec, 2022. "The Roundness of Antiquity Valuations from Auction Houses and Sales," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(4), pages 602-630, October.
    3. David Chambers & Elroy Dimson & Christophe Spaenjers, 0. "Art as an Asset: Evidence from Keynes the Collector," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(3), pages 490-520.
    4. Patrick Georges & Aylin Seçkin, 2013. "Black notes and white noise: a hedonic approach to auction prices of classical music manuscripts," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(1), pages 33-60, February.
    5. G. Candela & P. Figini & A. E. Scorcu, 2003. "Price indices for artists - A proposal," Working Papers 491, Dipartimento Scienze Economiche, Universita' di Bologna.
    6. Victor Ginsburgh & Sheila Weyers, 2008. "Quantitative approaches to valuation in the arts, with an application to movies," ULB Institutional Repository 2013/7292, ULB -- Universite Libre de Bruxelles.
    7. Calin Valsan & Robert Sproule, 2006. "Hedonic Models and Pre-Auction Estimates: Abstract Art Revisited," Economics Bulletin, AccessEcon, vol. 26(5), pages 1-10.
    8. Jun-ichi Itaya & Heinrich Ursprung, 2008. "Price and Death," CESifo Working Paper Series 2213, CESifo.
    9. GINSBURGH, Victor, 2003. "Awards, success and aesthetic quality in the arts," LIDAM Reprints CORE 1616, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Hadj Ali H. & Lecocq S. & Visser M., 2007. "The impact of gurus: Parker grades and en primeur wine prices¤," Working Papers ERMES 0718, ERMES, University Paris 2.
    11. Stuart Kells, 2003. "Explaining The Breadth Of Expert Estimate Ranges In Auctions Of Rare Books," Department of Economics - Working Papers Series 873, The University of Melbourne.
    12. Brunella Bruno & Emilia Garcia‐Appendini & Giacomo Nocera, 2018. "Experience and Brokerage in Asset Markets: Evidence from Art Auctions," Financial Management, Financial Management Association International, vol. 47(4), pages 833-864, December.
    13. Patrick Georges & Aylin Seçkin, 2012. "Auction Prices of Classical Music Manuscripts – A Hedonic Approach," Working Papers 1202E, University of Ottawa, Department of Economics.
    14. Nicoletta MARINELLI & Giulio PALOMBA, 2008. "A Model for Pricing the Italian Contemporary Art Paintings at Auction," Working Papers 316, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    15. Aubry, Mathieu & Kräussl, Roman & Manso, Gustavo & Spaenjers, Christophe, 2019. "Machine learning, human experts, and the valuation of real assets," CFS Working Paper Series 635, Center for Financial Studies (CFS).
    16. Lisa Farrell & Tim R.L. Fry, 2017. "Pre-sale information and hammer prices for Australian Indigenous art," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(5), pages 483-500, November.
    17. Orley Ashenfelter & Kathryn Graddy, 2003. "Auctions and the Price of Art," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 763-787, September.
    18. Graddy, Kathryn & Hamilton, Jonathan, 2017. "Auction guarantees for works of art," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 303-312.
    19. Ünsal Özdilek, 2013. "Visual autocorrelation of prices," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(2), pages 203-223, May.
    20. Spaenjers, Christophe & Goetzmann, William N. & Mamonova, Elena, 2015. "The economics of aesthetics and record prices for art since 1701," Explorations in Economic History, Elsevier, vol. 57(C), pages 79-94.
    21. Tim R. L. Fry, 2020. "Heterogeneity in Auction Price Distributions for Australian Indigenous Artists," The Economic Record, The Economic Society of Australia, vol. 96(313), pages 177-186, June.
    22. Calin Valsan & Robert Sproule, 2008. "Reservation Prices And Pre-Auction Estimates: A Study In Abstract Art," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 10(24), pages 257-272, June.
    23. Alan Beggs & Kathryn Graddy, 2006. "Failure to Meet the Reserve Price: The Impact on Returns to Art," Economics Series Working Papers 272, University of Oxford, Department of Economics.
    24. Menival, David & Charters, Steve, 2014. "The impact of geographic reputation on the value created in Champagne," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    25. Ashenfelter, Orley C & Graddy, Kathryn, 2002. "Art Auctions: A Survey of Empirical Studies," CEPR Discussion Papers 3387, C.E.P.R. Discussion Papers.
    26. Draper, Paul & Duboisée de Ricquebourg, Alan & Clacher, Iain, 2018. "Auctions, market efficiency, and the trade in second-hand and antique silver," Economics Letters, Elsevier, vol. 162(C), pages 45-48.
    27. Seçkin Aylin & Atukeren Erdal, 2012. "A Heckit Model of Sales Dynamics in Turkish Art Auctions: 2005-2008," Review of Middle East Economics and Finance, De Gruyter, vol. 7(3), pages 1-32, May.
    28. Lucio Picci & Antonello Scorcu, 2003. "Bidders' and Sellers' Strategies in Sequential Auctions. New Evidence about the Afternoon Effect," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 30(2), pages 163-178, June.
    29. Bronwyn Coate & Tim R.L. Fry, 2012. "Better off Dead? Prices Realised for Australian Paintings Sold at Auction," ACEI Working Paper Series AWP-02-2012, Association for Cultural Economics International, revised Feb 2012.
    30. Michael Beckmann, 2004. "Art Auctions and Bidding Rings: Empirical Evidence from German Auction Data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 28(2), pages 125-141, May.
    31. Shailendra Gurjar & Usha Ananthakumar, 2023. "Presale Estimates and Auction Prices in Indian Art Market: Accuracy, Determinants and Motivations," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 555-567, September.

  62. BAUWENS , Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2000. "A comparison of financial duration models via density forecasts," LIDAM Discussion Papers CORE 2000060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bhatti, Chad R., 2009. "On the interday homogeneity in the intraday rate of trading," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2250-2257.
    2. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," LIDAM Discussion Papers CORE 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Artur Sokolovsky & Luca Arnaboldi, 2020. "A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components," Papers 2009.09993, arXiv.org, revised Jun 2022.
    4. Veredas, David & Rodríguez Poo, Juan M. & Espasa, Antoni, 2001. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," DES - Working Papers. Statistics and Econometrics. WS ws013321, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Helton Saulo & Jeremias Leão & Víctor Leiva & Robert G. Aykroyd, 2019. "Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data," Statistical Papers, Springer, vol. 60(5), pages 1605-1629, October.
    7. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    8. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    9. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    10. Allen, David & Lazarov, Zdravetz & McAleer, Michael & Peiris, Shelton, 2009. "Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2535-2555.
    11. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    12. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
    13. Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
    14. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    15. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    16. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    17. Allen, David & Ng, K.H. & Peiris, Shelton, 2013. "The efficient modelling of high frequency transaction data: A new application of estimating functions in financial economics," Economics Letters, Elsevier, vol. 120(1), pages 117-122.
    18. GIOT, Pierre & PETITJEAN, Mikael, 2007. "The information content of the Bond-Equity Yield Ratio: Better than a random walk?," LIDAM Reprints CORE 1982, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Dungey, Mardi & Long, Xiangdong & Ullah, Aman & Wang, Yun, 2014. "A semiparametric conditional duration model," Economics Letters, Elsevier, vol. 124(3), pages 362-366.
    21. 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.
    22. Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
    23. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    24. Marcello Rambaldi & Emmanuel Bacry & Fabrizio Lillo, 2016. "The role of volume in order book dynamics: a multivariate Hawkes process analysis," Papers 1602.07663, arXiv.org.
    25. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    26. Stanislav Anatolyev & Grigory Kosenok, 2006. "Tests in contingency tables as regression tests," Working Papers w0075, New Economic School (NES).
    27. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    28. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    29. Nikolaus Hautsch & Vahidin Jeleskovic, 2008. "Modelling High-Frequency Volatility and Liquidity Using Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2008-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    31. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    32. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.
    33. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    34. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    35. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    36. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Economics Working Papers ECO2006/3, European University Institute.
    37. 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).
    38. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
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    Cited by:

    1. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
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    4. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
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    6. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Allen, David & Lazarov, Zdravetz & McAleer, Michael & Peiris, Shelton, 2009. "Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2535-2555.
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    11. Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
    12. Hautsch, Nikolaus & Pohlmeier, Winfried, 2001. "Econometric Analysis of Financial Transaction Data: Pitfalls and Opportunities," CoFE Discussion Papers 01/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    13. Giovanni De Luca & Giampiero M. Gallo, 2005. "Time-varying Mixing Weights in Mixture Autoregressive Conditional Duration Models," Econometrics Working Papers Archive wp2005_11, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
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    17. Gerhard, Frank & Hautsch, Nikolaus, 1999. "Volatility Estimation on the Basis of Price Intensities," CoFE Discussion Papers 99/19, University of Konstanz, Center of Finance and Econometrics (CoFE).
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    20. COSMA, Antonio & GALLI, Fausto, 2006. "A nonparametric ACD model," LIDAM Discussion Papers CORE 2006067, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    23. Adriana Bortoluzzo & Pedro Morettin & Clelia Toloi, 2010. "Time-varying autoregressive conditional duration model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 847-864.
    24. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    25. Jiang, Zhi-Qiang & Chen, Wei & Zhou, Wei-Xing, 2008. "Scaling in the distribution of intertrade durations of Chinese stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5818-5825.
    26. Zhou, Weijie & Wang, Zhengxin & Guo, Haiming, 2016. "Modelling volatility recurrence intervals in the Chinese commodity futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 514-525.
    27. 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.
    28. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    29. N. Balakrishna & Hira L. Koul, 2017. "Varying kernel marginal density estimator for a positive time series," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(3), pages 531-552, July.
    30. 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).
    31. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    32. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    33. Nikolaus Hautsch & Vahidin Jeleskovic, 2008. "Modelling High-Frequency Volatility and Liquidity Using Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2008-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    35. Bhatti, Chad R., 2009. "Intraday trade and quote dynamics: A Cox regression analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2240-2249.
    36. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
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    38. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
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  65. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K., 1999. "Adaptive polar sampling with an application to a Bayes measure of value-at-risk," LIDAM Discussion Papers CORE 1999057, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.
    2. Ausin, Maria Concepcion & Galeano, Pedro, 2007. "Bayesian estimation of the Gaussian mixture GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2636-2652, February.
    3. Carol Alexander & Emese Lazar, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336, April.
    4. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
    5. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    6. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    7. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    8. Qiang Xia & Heung Wong & Jinshan Liu & Rubing Liang, 2017. "Bayesian Analysis of Power-Transformed and Threshold GARCH Models: A Griddy-Gibbs Sampler Approach," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 353-372, October.
    9. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime Switching Garch Models," Working Papers 0605, Ben-Gurion University of the Negev, Department of Economics.
    10. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    11. Badescu Alex & Kulperger Reg & Lazar Emese, 2008. "Option Valuation with Normal Mixture GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-42, May.
    12. Mohamed Saidane & Christian Lavergne, 2009. "Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 323-364, November.
    13. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 2000. "On the variation of hedging decisions in daily currency risk management," Econometric Institute Research Papers EI 2000-20/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  66. BAUWENS, Luc & GIOT, Pierre, 1998. "Asymmetric ACD models: introducing price information in ACD models with a two state transition model," LIDAM Discussion Papers CORE 1998044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Florian Ielpo & Dominique Gúegan, 2009. "Understanding the Importance of the Duration and Size of the Variations of Fed’s Target Rate," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(3-4), pages 44-72, August.
    2. Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
    3. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006.
    4. GIOT, Pierre, 2001. "Time transformations, intraday data, and volatility models," LIDAM Reprints CORE 1500, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Sylwia Nowak, 2008. "How Do Public Announcements Affect The Frequency Of Trading In U.S. Airline Stocks?," CAMA Working Papers 2008-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

  67. BAUWENS, LUC & GIOT, Pierre, 1997. "The logarithmic ACD model: an application to market microstructure and NASDAQ," LIDAM Discussion Papers CORE 1997089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Hujer Reinhard & Grammig Joachim & Kokot Stefan, 2000. "Time Varying Trade Intensities and the Deutsche Telekom IPO / Zeitvariable Handelsintensitaten und die Deutsche Telekom IPO," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 220(6), pages 689-714, December.
    2. Gerhard, Frank & Hautsch, Nikolaus, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Papers 00/20, University of Konstanz, Center of Finance and Econometrics (CoFE).

  68. BAUWENS, Luc & DEPRINS, Dominique & VANDEUREN, Jean-Pierre, 1997. "Modelling interest rates with a cointegrated VAR-GARCH model," LIDAM Discussion Papers CORE 1997080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
    2. Stefano Puddu, 2013. "Real Sector and Banking System: Real and Feedback Effects. A Non-Linear VAR Approach," IRENE Working Papers 13-01, IRENE Institute of Economic Research.
    3. Röthig, Andreas, 2004. "Currency Futures and Currency Crises," Darmstadt Discussion Papers in Economics 136, Darmstadt University of Technology, Department of Law and Economics.
    4. J. Isaac Miller & Yoosoon Chang & Joon Y. Park, 2005. "Extracting a Common Stochastic Trend:Theories with Some Applications," Working Papers 0507, Department of Economics, University of Missouri, revised 18 Aug 2005.
    5. Ge, Yuanlong & Wang, H. Holly & Ahn, Sung K., 2008. "Implication of Cotton Price Behavior on Market Integration," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37623, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    6. Hui, Cho-Hoi & Fong, Tom Pak-Wing, 2015. "Price cointegration between sovereign CDS and currency option markets in the financial crises of 2007–2013," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 174-190.
    7. Yvan Lengwiler & Prof. Dr. Carlos Lenz, 2008. "Intelligible Factors for the Yield Curve," Working Papers 2008-02, Swiss National Bank.
    8. Röthig, Andreas, 2004. "Currency futures and currency crises," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 4022, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

  69. BAUWENS, Luc & GIOT, Pierre, 1997. "A Gibbs sampling approach to cointegration," LIDAM Discussion Papers CORE 1997016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Gareth W. Peters & Balakrishnan Kannan & Ben Lasscock & Chris Mellen, 2010. "Model Selection and Adaptive Markov chain Monte Carlo for Bayesian Cointegrated VAR model," Papers 1004.3830, arXiv.org.
    2. Andrea Silvestrini, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," Empirical Economics, Springer, vol. 39(1), pages 241-274, August.
    3. Sugita, Katsuhiro, 2002. "Testing For Cointegration Rank Using Bayes Factors," The Warwick Economics Research Paper Series (TWERPS) 654, University of Warwick, Department of Economics.
    4. Sugita, Katsuhiro, 2002. "Testing for Cointegration Rank Using Bayes Factors," Economic Research Papers 269467, University of Warwick - Department of Economics.
    5. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Strachan, Rodney W. & Inder, Brett, 2004. "Bayesian analysis of the error correction model," Journal of Econometrics, Elsevier, vol. 123(2), pages 307-325, December.
    7. Chew Lian Chua & Peter Summers, 2004. "Structural Error Correction Model: A Bayesian Perspective," Econometric Society 2004 Far Eastern Meetings 702, Econometric Society.
    8. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.

  70. BAUWENS, LUC & LUBRANO, Michel, 1997. "Bayesian option pricing using asymmetric GARCH," LIDAM Discussion Papers CORE 1997059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    2. Abel Rodríguez & Enrique ter Horst & Samuel Malone, 2015. "Bayesian Inference for a Structural Credit Risk Model with Stochastic Volatility and Stochastic Interest Rates," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 839-867.
    3. HAFNER, Christian & HERWARTZ, Helmut, 1998. "Volatility impulse response functions for multivariate GARCH models," LIDAM Discussion Papers CORE 1998047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  71. BAUWENs, Luc & LUBRANO , Michel, 1996. "Bayesian Inference on GARCH Models using the Gibbs Sampler," LIDAM Discussion Papers CORE 1996027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Mathias Silva & Michel Lubrano, 2023. "Bayesian correction for missing rich using a Pareto II tail with unknown threshold: Combining EU-SILC and WID data," Working Papers hal-04231661, HAL.
    2. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    3. Miazhynskaia, Tatiana & Fruhwirth-Schnatter, Sylvia & Dorffner, Georg, 2006. "Bayesian testing for non-linearity in volatility modeling," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2029-2042, December.
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    1. LUBRANO, Michel, 1998. "Smooth transition GARCH models: a Bayesian perspective," LIDAM Discussion Papers CORE 1998066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Lee, Grace H.Y. & Azali, M., 2012. "Is East Asia an optimum currency area?," Economic Modelling, Elsevier, vol. 29(2), pages 87-95.

  78. Bauwens, L. & Dijk, H. K., 1989. "Bayesian Limited Information Analysis Revisited," Econometric Institute Archives 272386, Erasmus University Rotterdam.

    Cited by:

    1. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.
    2. Kleibergen, F.R. & van Dijk, H.K., 1997. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Econometric Institute Research Papers EI 9714/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. van Dijk, H.K., 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Research Papers EI 2002-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  79. ZELLNER, A. & BAUWENS, Luc & VAN DIJK, H., 1987. "Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods," LIDAM Discussion Papers CORE 1987056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
    2. Chuanming Gao & Kajal Lahiri, 2000. "A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Econometric Society World Congress 2000 Contributed Papers 0230, Econometric Society.
    3. Steel, M.F.J., 1991. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Other publications TiSEM 029ee64f-b5a0-4787-9f5e-0, Tilburg University, School of Economics and Management.
    4. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    5. John C. Chao & Peter C.B. Phillips, 1996. "Bayesian Posterior Distributions in Limited Information Analysis of the Simultaneous Equations Model Using the Jeffreys Prior," Cowles Foundation Discussion Papers 1137, Cowles Foundation for Research in Economics, Yale University.
    6. Hoogerheide, L.F. & Kleibergen, F.R. & van Dijk, H.K., 2006. "Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data," Econometric Institute Research Papers EI 2006-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2005. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," Econometric Institute Research Papers EI 2005-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Chuanming Gao & Kajal Lahiri, 2019. "A Comparison of Some Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    9. Bauwens, L. & Dijk, H. K., 1989. "Bayesian Limited Information Analysis Revisited," Econometric Institute Archives 272386, Erasmus University Rotterdam.
    10. Gary Koop & Robert Leon Gonzalez & Rodney Strachan, 2011. "Bayesian Model Averaging in the Instrumental Variable Regression Model," GRIPS Discussion Papers 10-32, National Graduate Institute for Policy Studies.
    11. Hop, J. P. & van Duk, H. K., 1990. "Two Algorithms For The Computation Of Posterior Moments And Densities Using Monte Carlo Integration," Econometric Institute Archives 272483, Erasmus University Rotterdam.
    12. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    13. Chao, J. C. & Phillips, P. C. B., 1998. "Posterior distributions in limited information analysis of the simultaneous equations model using the Jeffreys prior," Journal of Econometrics, Elsevier, vol. 87(1), pages 49-86, August.
    14. Kleibergen, F.R. & Zivot, E., 1998. "Bayesian and classical approaches to instrumental variable regression," Econometric Institute Research Papers EI 9835, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Dorfman, Jeffrey H., 1995. "A numerical bayesian test for cointegration of AR processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 289-324.
    16. Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 185-212.
    17. Pholo Bala, Alain, 2009. "Urban concentration and economic growth: checking for specific regional effects," LIDAM Discussion Papers CORE 2009038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. van Dijk, H.K., 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Research Papers EI 2002-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Kwan, Yum K., 1998. "Asymptotic Bayesian analysis based on a limited information estimator," Journal of Econometrics, Elsevier, vol. 88(1), pages 99-121, November.
    20. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    21. Steel, M.F.J., 1988. "Seemingly unrelated regression equation systems under diffuse stochastic prior information : A recursive analytical approach," Discussion Paper 1988-5, Tilburg University, Center for Economic Research.
    22. Stanislav Radchenko, 2004. "Limited Information Bayesian Analysis of a Simultaneous Equation with an Autocorrelated Error Term and its Application to the U.S. Gasoline Market," Econometrics 0408001, University Library of Munich, Germany.
    23. Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.
    24. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    25. Li, Mingliang & Mumford, Kevin J. & Tobias, Justin L., 2012. "A Bayesian analysis of payday loans and their regulation," Journal of Econometrics, Elsevier, vol. 171(2), pages 205-216.
    26. Kien C. Tran & Mike G. Tsionas, 2022. "Instrumental Variables Estimation without Outside Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 489-506, September.
    27. Nascimento, Marcus Gerardus Lavagnole & Abanto-Valle, Carlos Antonio & Mendonça, Mario Jorge, 2019. "Multivariate Spatial IV Regression," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(2), January.
    28. Zellner, Arnold & Ando, Tomohiro, 2010. "A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model," Journal of Econometrics, Elsevier, vol. 159(1), pages 33-45, November.
    29. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
    30. Heckelei, Thomas & Mittelhammer, Ron C., 2003. "Bayesian bootstrap multivariate regression," Journal of Econometrics, Elsevier, vol. 112(2), pages 241-264, February.

  80. BAUWENS, Luc & RICHARD, Jean-François, 1985. "A 1-1 poly-t random variable generator with application to Monte Carlo integration," LIDAM Reprints CORE 644, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Steel, M.F.J., 1991. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Other publications TiSEM 029ee64f-b5a0-4787-9f5e-0, Tilburg University, School of Economics and Management.
    2. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    3. Andrea Silvestrini, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," Empirical Economics, Springer, vol. 39(1), pages 241-274, August.
    4. Bauwens, L. & Dijk, H. K., 1989. "Bayesian Limited Information Analysis Revisited," Econometric Institute Archives 272386, Erasmus University Rotterdam.
    5. Hop, J. P. & van Duk, H. K., 1990. "Two Algorithms For The Computation Of Posterior Moments And Densities Using Monte Carlo Integration," Econometric Institute Archives 272483, Erasmus University Rotterdam.
    6. Steel, Mark F. J. & Richard, Jean-Francois, 1991. "Bayesian multivariate exogeneity analysis : An application to a UK money demand equation," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 239-274.
    7. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. W.E. Griffiths & Ma. Rebecca Valenzuela, 2004. "Gibbs Samplers for a Set of Seemingly Unrelated Regressions," Department of Economics - Working Papers Series 912, The University of Melbourne.
    9. Müller-Plantenberg, Nikolas, 2012. "Long swings in Japan’s current account and in the yen," Working Papers in Economic Theory 2012/08, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    10. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.
    11. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.

  81. BAUWENS, Luc & d'ALCANTARA, Gonzague, 1983. "An export model for the Belgian industry," LIDAM Reprints CORE 533, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bradley, John & Fanning, Connell & Prendergast, Canice & Wynne, Mark, 1985. "Medium-Term Analysis of Fiscal Policy in Ireland: A Macroeconometric Study of the Period 1967-1980," Research Series, Economic and Social Research Institute (ESRI), number GRS122, June.
    2. Bradley, John & Modesto, Leonor & Sosvilla-Rivero, Simon, 1995. "HERMIN : A macroeconometric modelling framework for the EU periphery," Economic Modelling, Elsevier, vol. 12(3), pages 221-247, July.

Articles

  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.
    See citations under working paper version above.
  2. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    See citations under working paper version above.
  3. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," Journal of Econometrics, Elsevier, vol. 217(2), pages 496-522.
    See citations under working paper version above.
  4. Maciej Augustyniak & Luc Bauwens & Arnaud Dufays, 2019. "A New Approach to Volatility Modeling: The Factorial Hidden Markov Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 696-709, October.

    Cited by:

    1. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    2. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
    3. Zhang, Xiaoyuan & Zhang, Tianqi, 2023. "On pricing double-barrier options with Markov regime switching," Finance Research Letters, Elsevier, vol. 51(C).
    4. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.
    5. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    6. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.

  5. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering," Econometrics, MDPI, vol. 6(4), pages 1-22, December.
    See citations under working paper version above.
  6. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    See citations under working paper version above.
  7. Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
    See citations under working paper version above.
  8. Bauwens, Luc & Grigoryeva, Lyudmila & Ortega, Juan-Pablo, 2016. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 17-36.
    See citations under working paper version above.
  9. Luc Bauwens & Edoardo Otranto, 2016. "Modeling the Dependence of Conditional Correlations on Market Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 254-268, April.
    See citations under working paper version above.
  10. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
    See citations under working paper version above.
  11. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2015. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 596-620, June.
    See citations under working paper version above.
  12. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    See citations under working paper version above.
  13. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    See citations under working paper version above.
  14. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    See citations under working paper version above.
  15. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
    See citations under working paper version above.
  16. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    See citations under working paper version above.
  17. Luc Bauwens & Giordano Mion & Jacques-François Thisse, 2011. "The Resistible Decline of European Science," Recherches économiques de Louvain, De Boeck Université, vol. 77(4), pages 5-31.
    See citations under working paper version above.
  18. Luc Bauwens & Arie Preminger & Jeroen V. K. Rombouts, 2010. "Theory and inference for a Markov switching GARCH model," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 218-244, July.
    See citations under working paper version above.
  19. Bauwens, Luc & Ben Omrane, Walid & Rengifo, Erick, 2010. "Intradaily dynamic portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2400-2418, November.

    Cited by:

    1. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    2. Rachidi Kotchoni, 2012. "Applications of the Characteristic Function Based Continuum GMM in Finance," Post-Print hal-00867795, HAL.
    3. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.

  20. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
    See citations under working paper version above.
  21. Bauwens Luc & Storti Giuseppe, 2009. "A Component GARCH Model with Time Varying Weights," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-33, May.
    See citations under working paper version above.
  22. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    See citations under working paper version above.
  23. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    See citations under working paper version above.
  24. Luc Bauwens & Alvaro Escribano & Michel Lubrano, 2007. "The Econometrics of Industrial Organization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1153-1156.

    Cited by:

    1. Ooms, M., 2008. "Trends in Applied Econometrics Software Development 1985-2008, an analysis of Journal of Applied Econometrics research articles, software reviews, data and code," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

  25. L. Bauwens & J.V.K. Rombouts, 2007. "Bayesian inference for the mixed conditional heteroskedasticity model," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 408-425, July.
    See citations under working paper version above.
  26. Luc Bauwens & Michel Lubrano, 2007. "Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 469-486.
    See citations under working paper version above.
  27. L. Bauwens & J. V. K. Rombouts, 2007. "Bayesian Clustering of Many Garch Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 365-386.
    See citations under working paper version above.
  28. Bauwens, Luc, 2006. "Econometric Analysis of Intra-daily Trading Activity on the Tokyo Stock Exchange," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 24(1), pages 1-23, March.
    See citations under working paper version above.
  29. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 450-493.
    See citations under working paper version above.
  30. Luc Bauwens & Winfried Pohlmeier & David Veredas, 2006. "Editor’s introduction," Empirical Economics, Springer, vol. 30(4), pages 791-794, January.

    Cited by:

    1. Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).

  31. Bauwens, Luc & Peter Boswijk, H. & Urbain, Jean-Pierre, 2006. "Causality and exogeneity in econometrics," Journal of Econometrics, Elsevier, vol. 132(2), pages 305-309, June.

    Cited by:

    1. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in quantiles and dynamic relations in energy markets: (De)tails matter," Energy Policy, Elsevier, vol. 133(C).
    2. Genaro, SUCARRAT, 2006. "The First Stage in Hendry’s Reduction Theory Revisited," Discussion Papers (ECON - Département des Sciences Economiques) 2006041, Université catholique de Louvain, Département des Sciences Economiques.
    3. White, Halbert, 2006. "Time-series estimation of the effects of natural experiments," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 527-566.
    4. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in Quantiles and Dynamic Relations in Energy Markets," Working Papers 116, VATT Institute for Economic Research.

  32. Luc Bauwens & Dagfinn Rime & Genaro Sucarrat, 2006. "Exchange rate volatility and the mixture of distribution hypothesis," Empirical Economics, Springer, vol. 30(4), pages 889-911, January.
    See citations under working paper version above.
  33. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    See citations under working paper version above.
  34. Bauwens, Luc & Laurent, Sebastien, 2005. "A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 346-354, July.
    See citations under working paper version above.
  35. Bauwens, Luc & Ben Omrane, Walid & Giot, Pierre, 2005. "News announcements, market activity and volatility in the euro/dollar foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1108-1125, November.
    See citations under working paper version above.
  36. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    See citations under working paper version above.
  37. Bauwens, Luc & Lubrano, Michel & van Dijk, Herman K., 2004. "Recent advances in Bayesian econometrics," Journal of Econometrics, Elsevier, vol. 123(2), pages 197-199, December.

    Cited by:

    1. Majda Benzidia & Michel Lubrano, 2016. "A Bayesian Look at American Academic Wages: The Case of Michigan State University," Working Papers halshs-01358882, HAL.

  38. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    See citations under working paper version above.
  39. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    See citations under working paper version above.
  40. Luc Bauwens & Pierre Giot, 2003. "Asymmetric ACD models: Introducing price information in ACD models," Empirical Economics, Springer, vol. 28(4), pages 709-731, November.
    See citations under working paper version above.
  41. Michel Lubrano & Luc Bauwens & Alan Kirman & Camelia Protopopescu, 2003. "Ranking Economics Departments in Europe: A Statistical Approach," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1367-1401, December.
    See citations under working paper version above.
  42. Bauwens, Luc & Lubrano, Michel, 2002. "Bayesian option pricing using asymmetric GARCH models," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 321-342, August.
    See citations under working paper version above.
  43. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    See citations under working paper version above.
  44. Luc Bauwens & Michel Lubrano, 1998. "Bayesian inference on GARCH models using the Gibbs sampler," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 23-46.
    See citations under working paper version above.
  45. Bauwens, Luc & Polasek, Wolfgang & van Dijk, Herman K., 1996. "Editor's introduction," Journal of Econometrics, Elsevier, vol. 75(1), pages 1-5, November.

    Cited by:

    1. Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).

  46. Bauwens, Luc & Fiebig, Denzil G & Steel, Mark F J, 1994. "Estimating End-Use Demand: A Bayesian Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 221-231, April.
    See citations under working paper version above.
  47. Luc Bauwens & Michel Lubrano, 1991. "Bayesian Diagnostics for Heterogeneity," Annals of Economics and Statistics, GENES, issue 20-21, pages 17-40.
    See citations under working paper version above.
  48. Luc Bauwens, 1991. "The 'pathologie' of the Natural Conjugate Prior Density in the Regression Model," Annals of Economics and Statistics, GENES, issue 23, pages 49-64.
    See citations under working paper version above.
  49. Balassa, Bela & Bauwens, Luc, 1988. "The determinants of intra-European trade in manufactured goods," European Economic Review, Elsevier, vol. 32(7), pages 1421-1437, September.

    Cited by:

    1. Kwanho Shin & Yunjong Wang, 2003. "Monetary Integration Ahead of Trade Integration in East Asia?," ISER Discussion Paper 0572, Institute of Social and Economic Research, Osaka University.
    2. Kwanho Shin & Yunjong Wang, 2003. "Trade Integration and Business Cycle Synchronization in East Asia," ISER Discussion Paper 0574, Institute of Social and Economic Research, Osaka University.
    3. Venables Anthony J. & Rice Patricia G. & Stewart Martin, 2003. "The Geography of Intra-Industry Trade: empirics," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 3(1), pages 1-25, September.
    4. Das, Gouranga G., 2002. "Cross-Country Analysis of Empirical Evidences of Intra-industry Trade in Manufactures for Dynamic Asian and Other Developing Economies: Implications for Economic Growth and Development," MPRA Paper 37916, University Library of Munich, Germany, revised 2002.
    5. Fedoseeva, Svetlana & Zeidan, Rodrigo, 2016. "A dead-end tunnel or the light at the end of it: The role of BRICs in European exports," Economic Modelling, Elsevier, vol. 59(C), pages 237-248.
    6. Justyna Lapinska, 2016. "Determinant Factors Of Intra-Industry Trade: The Case Of Poland And Its European Union Trading Partners," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(2), pages 251-264, June.
    7. Martin Andresen, 2010. "A cross-industry analysis of intra-industry trade measurement thresholds: Canada and the United States, 1988–1999," Empirical Economics, Springer, vol. 38(3), pages 793-808, June.
    8. Das, Gouranga G., 2007. "Intra-Industry Trade and Development: Revisiting Theory, Measurement and New Evidences," MPRA Paper 37260, University Library of Munich, Germany, revised 01 Sep 2008.
    9. Dilip Nachane & Amlendu Dubey, 2018. "India in the globalized economy : Growth spillovers & business cycle synchronization," International Economics and Economic Policy, Springer, vol. 15(1), pages 89-115, January.
    10. Mary Lovely & Douglas Nelson, 2002. "Intra-industry trade as an indicator of labor market adjustment," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(2), pages 179-206, June.
    11. Fischer, Manfred M. & Johannson, Börje, 1994. "Opening Up International Trade in Eastern European Countries. Consequences for Aggregate Trade Flows in the Rhine-Main-Danube Area," MPRA Paper 77812, University Library of Munich, Germany.
    12. Béatrice Colin-Sédillot, 1994. "Les échanges industriels entre la France et les pays d'Europe centrale et orientale : premières tendances de la spécialisation," Économie et Statistique, Programme National Persée, vol. 279(1), pages 69-80.

  50. Bela Balassa & Luc Bauwens, 1988. "Inter-industry and intra-industry specialization in manufactured goods," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 124(1), pages 1-13, March.

    Cited by:

    1. Maylene Y. Damoense-Azevedo & André C. Jordaan, 2012. "Factors influencing bilateral intra-industry trade in the auto industry: the case of South Africa," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 63-82.
    2. Venables Anthony J. & Rice Patricia G. & Stewart Martin, 2003. "The Geography of Intra-Industry Trade: empirics," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 3(1), pages 1-25, September.
    3. Das, Gouranga G., 2002. "Cross-Country Analysis of Empirical Evidences of Intra-industry Trade in Manufactures for Dynamic Asian and Other Developing Economies: Implications for Economic Growth and Development," MPRA Paper 37916, University Library of Munich, Germany, revised 2002.
    4. Das, Gouranga G., 2007. "Intra-Industry Trade and Development: Revisiting Theory, Measurement and New Evidences," MPRA Paper 37260, University Library of Munich, Germany, revised 01 Sep 2008.
    5. Jianhong Zhang & Arjen van Witteloostuijn & Chaohong Zhou, 2005. "Chinese Bilateral Intra-Industry Trade: A Panel Data Study for 50 Countries in the 1992–2001 Period," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 141(3), pages 510-540, October.

  51. Zellner, Arnold & Bauwens, Luc & Van Dijk, Herman K., 1988. "Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 39-72.
    See citations under working paper version above.
  52. Balassa, Bela & Bauwens, Luc, 1987. "Intra-industry Specialisation in a Multi-country and Multi-industry Framework," Economic Journal, Royal Economic Society, vol. 97(388), pages 923-939, December.

    Cited by:

    1. Kemal Türkcan, 2009. "Vertical Intra-Industry Trade: An Empirical Examination of the Austria’s Auto-Parts Industry," FIW Working Paper series 030, FIW.
    2. Soumyananda Dinda, 2014. "Climate Change: An Emerging Trade Opportunity in South Asia," South Asian Journal of Macroeconomics and Public Finance, , vol. 3(2), pages 221-239, December.
    3. Hanna, Joseph & Lévi, Loïc & Petit, Sylvain, 2015. "Intra-tourism trade, income distribution and tourism endowment: an econometric investigation," MPRA Paper 62235, University Library of Munich, Germany.
    4. Veeramani C, 2001. "India's intra-industry trade under economic liberalization: Trends and country specific factors," Centre for Development Studies, Trivendrum Working Papers 313, Centre for Development Studies, Trivendrum, India.
    5. Nuno Carlos Leit o & Muhammad Shahbaz, 2012. "Liberalization and United States' Intra-Industry Trade," International Journal of Economics and Financial Issues, Econjournals, vol. 2(4), pages 505-512.
    6. Fukao, Kyoji & 深尾, 京司 & フカオ, キョウジ & Ishido, Hikari & 石戸, 光 & イシド, ヒカリ & Ito, Keiko & 伊藤, 恵子, 2003. "Vertical Intra-Industry Trade and Foreign Direct Investment in East Asia," Discussion Paper Series a434, Institute of Economic Research, Hitotsubashi University.
    7. Snježana Brkić & Radovan Kastratović & Mirela Abidović Salkica, 2021. "Patterns And Determinants Of Intra-Industry Trade In Agri-Food Products Between Bosnia And Herzegovina And Cefta 2006," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 66(229), pages 7-36, April – J.
    8. E.M. Ekanayake & Mihalis Halkides & Robin Rance & Iliana Filyanova, 2007. "Intra-Industry Trade Between The United States And Latin American Countries," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 109-124.
    9. Dutta, Sourish, 2023. "Horizontal and Vertical Differentiation: Approaching Endogenous Measurement in Intra-industry Trade," EconStor Preprints 275680, ZBW - Leibniz Information Centre for Economics.
    10. Shehu U.R. Aliyu & Sani Bawa, 2015. "Gravity model by panel data approach: empirical evidence from Nigeria," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 8(1), pages 42-57.
    11. Joakim Gullstrand, 2002. "Does the measurement of intra-industry trade matter?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(2), pages 317-339, June.
    12. Aturupane, Chonira & Djankov, Simeon & Hoekman, Bernard, 1997. "Determinants of intra-industry trade between East and West Europe," Policy Research Working Paper Series 1850, The World Bank.
    13. Pinar Narin Emirhan, 2005. "Determinants of Vertical Intra-Industry Trade of Turkey: Panel Data Approach," Discussion Paper Series 05/05, Dokuz Eylül University, Faculty of Business, Department of Economics, revised 23 Nov 2005.
    14. David Greenaway & Johan Torstensson,, "undated". "Back to the Future: Taking Stock on Intra-Industry Trade," Discussion Papers 96/14, University of Nottingham, CREDIT.
    15. Shahbaz, Muhammad & Leitão, Nuno Carlos, 2011. "Intra-industry trade: The Pakistan experience," MPRA Paper 28665, University Library of Munich, Germany.
    16. McCorriston, Steve & Sheldon, Ian M., 1990. "Intra-Industry Trade and Specialisation in Processed Agricultural Products: The Case of the US and EC," Occasional Papers 232835, Regional Research Project NC-194: Organization and Performance of World Food Systems.
    17. Maza, Adolfo & Gutiérrez-Portilla, Paula, 2022. "Outward FDI and exports relation: A heterogeneous panel approach dealing with cross-sectional dependence," International Economics, Elsevier, vol. 170(C), pages 174-189.
    18. Brahim Razgallah, 2004. "La théorie des ZMO s'applique-t-elle aux pays en développement?," International Finance 0403003, University Library of Munich, Germany.
    19. Maylene Y. Damoense-Azevedo & André C. Jordaan, 2012. "Factors influencing bilateral intra-industry trade in the auto industry: the case of South Africa," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 63-82.
    20. Robert C. Shelburne, 2002. "Bilateral Intra-Industry Trade in a Multi-Country Helpman-Krugman Model," International Economic Journal, Taylor & Francis Journals, vol. 16(4), pages 53-73.
    21. Rosanna Pittiglio & Filippo Reganati, 2012. "Vertical intra-industry trade in higher and lower quality: a new approach of measuring country-specific determinants," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 44-62.
    22. Moshirian, Fariborz, 2004. "Financial services: Global perspectives," Journal of Banking & Finance, Elsevier, vol. 28(2), pages 269-276, February.
    23. Kwanho Shin & Yunjong Wang, 2003. "Monetary Integration Ahead of Trade Integration in East Asia?," ISER Discussion Paper 0572, Institute of Social and Economic Research, Osaka University.
    24. Mónica Rivera, 2014. "Trade patterns in the process of European integration: Evidence for the intraindustrial exchanges of a Mediterranean peripheral region," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(1), pages 227-249, January.
    25. Gervais, Antoine, 2019. "Indirect measures of trade costs: Limitations and caveats," Economics Letters, Elsevier, vol. 176(C), pages 96-102.
    26. Godwin Odo ONOGWU, 2014. "Determinants of the intra-industry trade in cereal and miscellaneous edible preparations: the evidence for Nigeria and the ECOWAS partners," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(1), pages 21-30.
    27. Filippo Reganati & Rosanna Pittiglio, 2007. "Two-Way International Trade And Production In Italy: A Country/Industry Specific Analysis," Quaderni DSEMS 19-2007, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    28. Gnidchenko, A., 2018. "Structural Transformation in International Trade (2001-2015): Towards a New Classification," Journal of the New Economic Association, New Economic Association, vol. 37(1), pages 62-86.
    29. Saeed Rasekhi & Shideh Shojaee, 2012. "Country-specific Determinants of Intra Industry Trade Types of Agricultural Sector in Selected Developing Countries," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 17(1), pages 85-99, winter.
    30. Robert Ballance & Helmut Forstner & W. Sawyer, 1992. "An empirical examination of the role of vertical product differentiation in north-south trade," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 128(2), pages 330-338, June.
    31. Dutta, Sourish, 2022. "Two Approaches of Measuring Intra-industry Trade," EconStor Preprints 259000, ZBW - Leibniz Information Centre for Economics.
    32. Rosanna Pittiglio, 2008. "The intra-industry trade for a high-income country: new empirical evidence for Italy," Dundee Discussion Papers in Economics 211, Economic Studies, University of Dundee.
    33. Leitão, Nuno Carlos & Tripathi, Sabyasachi, 2013. "Portuguese Trade and European Union: The Gravity Model," MPRA Paper 45994, University Library of Munich, Germany.
    34. Celi, Giuseppe, 2010. "Empirical Explanation of Vertical and Horizontal Intra-industry Trade in the UK: A Comment - Spiegazioni empiriche del commercio intra-industriale verticale ed orizzontale del Regno Unito: un commento," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 63(1), pages 53-90.
    35. Davis, Donald R., 1995. "Intra-industry trade: A Heckscher-Ohlin-Ricardo approach," Journal of International Economics, Elsevier, vol. 39(3-4), pages 201-226, November.
    36. Yener Kandogan, 2005. "Trade Creation and Diversion Effects of Europe???s Regional Liberalization Agreements," William Davidson Institute Working Papers Series wp746, William Davidson Institute at the University of Michigan.
    37. Saeed Rasekhi & Shideh Sadat Shojaee, 2012. "Determinant factors of vertical intra industry trade in agricultural sector: A study of Iran and her main trading partners," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 58(4), pages 180-190.
    38. Nuno Carlos LEITÃO & Marius-Razvan SURUGIU & Camelia SURUGIU, 2014. "Romanian intra-industry trade: a panel data approach," EuroEconomica, Danubius University of Galati, issue 2(33), pages 7-18, November.
    39. Stefanescu, Razvan & Dumitriu, Ramona, 2007. "Impact of the EU adhesion on the indirect taxes for the intra - community imports," MPRA Paper 41779, University Library of Munich, Germany, revised 02 Oct 2007.
    40. Kwok Tong Soo, 2016. "Intra-industry trade: A Krugman–Ricardo Model and Data," Economica, London School of Economics and Political Science, vol. 83(330), pages 338-355, April.
    41. Chonira Aturupane & Simeon Djankov & Bernard Hoekman, 1999. "Horizontal and vertical intra-industry trade between Eastern Europe and the European union," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(1), pages 62-81, March.
    42. Rafika Korti & Sassi Boudemagh Souad, 2018. "Citizen Participation and Sense of Community in the Development of the Permanent Conservation Project Plan," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 4, January -.
    43. Haq, Zahoor Ul & Meilke, Karl D., 2008. "Differentiated Agri-Food Product Trade and the Linder Effect," Working Papers 46629, Canadian Agricultural Trade Policy Research Network.
    44. Sawyer, William C. & Sprinkle, Richard L. & Tochkov, Kiril, 2010. "Patterns and determinants of intra-industry trade in Asia," Journal of Asian Economics, Elsevier, vol. 21(5), pages 485-493, October.
    45. Miria Pigato, 2009. "Strengthening China's and India's Trade and Investment Ties to the Middle East and North Africa," World Bank Publications - Books, The World Bank Group, number 2626, December.
    46. Imre Ferto & Károly Attila Soós, 2012. "Controversial issues in factors determining intra-industry trade," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 132-148.
    47. Venables Anthony J. & Rice Patricia G. & Stewart Martin, 2003. "The Geography of Intra-Industry Trade: empirics," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 3(1), pages 1-25, September.
    48. Sourish Dutta, 2022. "The Problem of Measuring Intra-industry Trade," Working Papers hal-03681243, HAL.
    49. Kwok Tong Soo, 2013. "Intra-industry trade," Working Papers 33867578, Lancaster University Management School, Economics Department.
    50. Dutta, Sourish, 2022. "Measuring Horizontal and Vertical Differentiation in Intra-industry Trade," SocArXiv rudtq, Center for Open Science.
    51. Filippo Reganati & Rosanna Pittiglio, 2005. "Vertical Intra-Industry Trade: Patterns And Determinants In The Italian Case," Quaderni DSEMS 06-2005, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    52. Lars Nilsson, 1999. "Two-way trade between unequal partners: The EU and the developing countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(1), pages 102-127, March.
    53. Joan A. Martín & Vicente Orts, 2001. "A two-stage analysis of monopolistic competition models of intraindustry trade," Investigaciones Economicas, Fundación SEPI, vol. 25(2), pages 315-333, May.
    54. Muhammad Shahbaz & Nuno Carlos Leit o & Muhammad Sabihuddin Butt, 2012. "Pakistan Intra-Industry Trade: A Panel Data Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 225-232.
    55. Matthew A. Cole & Robert J. R. Elliott, 2003. "Do Environmental Regulations Influence Trade Patterns? Testing Old and New Trade Theories," The World Economy, Wiley Blackwell, vol. 26(8), pages 1163-1186, August.
    56. M. Choudhary & Paul Temple & Lei Zhao, 2013. "Taking the measure of things: the role of measurement in EU trade," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(1), pages 75-109, February.
    57. Sheldon, Ian, 1989. "Intra-Industry Trade and Specialisation in Processed Agricultural Products: Theory and Issues," Occasional Papers 232829, Regional Research Project NC-194: Organization and Performance of World Food Systems.
    58. Martin Andresen, 2010. "A cross-industry analysis of intra-industry trade measurement thresholds: Canada and the United States, 1988–1999," Empirical Economics, Springer, vol. 38(3), pages 793-808, June.
    59. Sagnik Bagchi & Surajit Bhattacharyya, 2019. "Country-Specific Determinants of Intra-Industry Trade in India," Foreign Trade Review, , vol. 54(3), pages 129-158, August.
    60. Ruhul Salim & Amirul Islam & Harry Bloch, 2018. "Patterns And Determinants Of Intra-Industry Trade In Southeast Asia: Evidence From The Automotive And Electrical Appliances Sectors," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(03), pages 647-665, June.
    61. J. Vicente Blanes Cristobal, 1997. "Comercio intra-industrial y presencia de capital extranjero en España," Working Papers wpdea9705, Department of Applied Economics at Universitat Autonoma of Barcelona.
    62. Ecochard, Pierre & Fontagné, Lionel & Gaulier, Guillaume & Zignago, Soledad, 2005. "Intra-industry trade and regional integration," MPRA Paper 44182, University Library of Munich, Germany.
    63. Don Clark & Denise Stanley, 2003. "Determinants of Intraindustry Trade Between the United States and Industrial Nations," International Economic Journal, Taylor & Francis Journals, vol. 17(3), pages 1-18.
    64. Hirschberg, Joseph G. & Sheldon, Ian M. & Dayton, James R., 1992. "An Analysis of Bilateral Intra-Industry Trade in the Food Processing Sector," Occasional Papers 233083, Regional Research Project NC-194: Organization and Performance of World Food Systems.
    65. Antonella Bellino & Giuseppe Celi, 2016. "The Role of Migration in the Variety and Quality of Trade: Evidence from Germany," German Economic Review, Verein für Socialpolitik, vol. 17(1), pages 1-25, February.
    66. Jarko Fidrmuc & Daniela Grozea-Helmenstein & Andreas Wörgötter, 1999. "East-west intra-industry trade dynamics," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(2), pages 332-346, June.
    67. Tsang, Cheuk Yan & Shakur, Shamim, 2017. "New Zealand’s Trade Prospects in an Uncertain Trans-Pacific Partnership (TPP) Environment: Results from Gravity Model," 2017 Conference, October 19-20, Rotorua, New Zealand 269528, New Zealand Agricultural and Resource Economics Society.
    68. Frahan, Bruno Henry de & Tharakan, Joe, 1998. "Horizontal And Vertical Intra-Industry Trade In The Processed Food Sector," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20903, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    69. Clark, Don P., 2010. "Scale economies and intra-industry trade," Economics Letters, Elsevier, vol. 108(2), pages 190-192, August.
    70. Seyed-Rohollah Ahmadi, 2016. "The Impact of Sanction on Bilateral Intra-Industry Trade between Iran and SCO Countries," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 20(3), pages 277-293, Summer.
    71. Tripathi, Sabyasachi & Leitão, Nuno Carlos, 2013. "India’s Trade and Gravity Model: A Static and Dynamic Panel Data," MPRA Paper 45502, University Library of Munich, Germany.
    72. BELLINO, Antonella & CELI, Giuseppe, 2016. "The Migration-Trade Nexus in the Presence of Vertical and Horizontal Product Differentiation," CELPE Discussion Papers 137, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    73. Volodymyr Toryanyk & Vladimir Dzhyndzhoian & Yevhen Namliyev, 2018. "Competitiveness Of Ukrainian Export-Oriented Fields," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 4(3).
    74. Kandogan, Yener, 2009. "A Gravity Model for Components of Imports," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 5(1-2), pages 1-17, April.
    75. Andriamananjara, Shuby & Nash, John, 1997. "Have trade policy reforms led to greater openness in developing countries : evidence from readily available trade data," Policy Research Working Paper Series 1730, The World Bank.
    76. Jeremiás Máté Balogh & Nuno Carlos Leitão, 2019. "A gravity approach of agricultural trade: The nexus of the EU and African, Caribbean and Pacific countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(11), pages 509-519.
    77. Orszaghova, Lucia & Schudel, Willem & Dautović, Ernest, 2014. "Intra-industry trade between CESEE countries and the EU15," Working Paper Series 1719, European Central Bank.
    78. Ernest Dautović & Lucia Orszaghova & Willem Schudel, 2017. "Converging in divergent ways," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 25(4), pages 625-662, October.
    79. Yener Kandogan, 2009. "Trade Creation and Diversion Effects of Europe's Regional Liberalization Agreements," International Economic Journal, Taylor & Francis Journals, vol. 23(4), pages 591-615.
    80. Moshirian, Fariborz & Li, Donghui & Sim, Ah-Boon, 2005. "Intra-industry trade in financial services," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1090-1107, November.
    81. Amadeo Navarro Zapata & María Arrazola & José Hevia, 2023. "Technological intensity in manufacturing trade between ASEAN and the EU: challenges and opportunities," Asia Europe Journal, Springer, vol. 21(1), pages 23-42, March.
    82. Joan Martín-Montaner & Vicente Ríos, 2002. "Vertical specialization and intra-industry trade: The role of factor endowments," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(2), pages 340-365, June.
    83. Dutta, Sourish, 2023. "Endogenous Horizontal and Vertical Differentiation: Measuring Value Added in Intra-industry Trade," SocArXiv zqb9n, Center for Open Science.
    84. Moshirian, Fariborz, 2006. "Aspects of international financial services," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1057-1064, April.
    85. Justyna Lapinska, 2014. "Determinants of Intra-Industry Trade in Agricultural and Food Products between Poland and EU Countries," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 3, pages 159-172, September.
    86. M A Cole & R J R Elliott, 2003. "Do Environmental Regulations Influence Trade Patterns? Testing New and Old Trade Theories," Economics Discussion Paper Series 0310, Economics, The University of Manchester.
    87. Nuno Leitão & Horácio Faustino & Yushi Yoshida, 2009. "Determinants of Vertical Intra-Industry Trade in the Automobile Manufacturing Sector: globalization and fragmentation," Working Papers Department of Economics 2009/06, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    88. Sagnik Bagchi & Surajit Bhattacharyya, 2021. "Industry-level determinants of India’s vertical and horizontal IIT," Indian Economic Review, Springer, vol. 56(1), pages 113-145, June.
    89. J. Vicente Blanes Cristobal, 1997. "El comercio intra-industrial de España con los países de la comunidad europea(1982-1990):determinantes y efectos de su integración," Working Papers wpdea9704, Department of Applied Economics at Universitat Autonoma of Barcelona.
    90. Bo Carlsson, 1991. "Flexible manufacturing and U.S. trade performance," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 127(2), pages 300-322, June.

  53. Bauwens, Luc & Richard, Jean-Francois, 1985. "A 1-1 poly-t random variable generator with application to Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 19-46.
    See citations under working paper version above.
  54. Bauwens, Luc & d'Alcantara, Gonzague, 1983. "An export model for the Belgian industry," European Economic Review, Elsevier, vol. 22(3), pages 265-276.
    See citations under working paper version above.

Chapters

  1. Luc Bauwens & Dimitris Korobilis, 2013. "Bayesian methods," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 16, pages 363-380, Edward Elgar Publishing.
    See citations under working paper version above.
  2. Luc Bauwens & Dagfinn Rime & Genaro Sucarrat, 2008. "Exchange rate volatility and the mixture of distribution hypothesis," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 7-29, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), 2008. "High Frequency Financial Econometrics," Studies in Empirical Economics, Springer, number 978-3-7908-1992-2, July.

    Cited by:

    1. Juan D. Moreno-Ternero, 2010. "Voting over piece-wise linear tax methods," Working Papers 10.02, Universidad Pablo de Olavide, Department of Economics.
    2. GAUTIER, Axel & WAUTHY, Xavier Yves, 2012. "Competitively neutral universal service obligations," LIDAM Reprints CORE 2455, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. NESTEROV, Yurii, 2011. "Random gradient-free minimization of convex functions," LIDAM Discussion Papers CORE 2011001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. MANZI, Jorge & SAN MARTIN, Ernesto & VAN BELLEGEM, Sébastien, 2010. "School system evaluation by value-added analysis under endogeneity," LIDAM Discussion Papers CORE 2010046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. CREMER, Helmuth & GAHVARI, Firouz & PESTIEAU, Pierre, 2011. "Fertility, human capital accumulation, and the pension system," LIDAM Reprints CORE 2366, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Bouezmarni, Taoufik & Van Bellegem, Sébastien, 2009. "Nonparametric Beta Kernel Estimator for Long Memory Time Series," TSE Working Papers 09-082, Toulouse School of Economics (TSE).
    7. GILLIS, Nicolas & GLINEUR, François, 2011. "A multilevel approach for nonnegative matrix factorization," LIDAM Reprints CORE 2381, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Marie-Louise Leroux & Grégory Ponthière, 2013. "Utilitarianism and unequal longevities: A remedy?," PSE - Labex "OSE-Ouvrir la Science Economique" hal-00813226, HAL.
    9. Pierre Pestieau & Maria Racionero, 2015. "Tagging with leisure needs," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 45(4), pages 687-706, December.
    10. DI SUMMA, Marco & WOLSEY, Laurence, 2010. "Mixing sets linked by bidirected paths," LIDAM Discussion Papers CORE 2010063, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. GRANDJEAN, Gilles, 2011. "Risk-sharing networks and farsighted stability," LIDAM Discussion Papers CORE 2011014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Vandenbussche, Hylke & Song, Huasheng & ,, 2010. "Innovation, antidumping, and retaliation," CEPR Discussion Papers 7916, C.E.P.R. Discussion Papers.
    13. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    14. Jacques-François Thisse, 2011. "Geographical Economics: A Historical Perspective," Recherches économiques de Louvain, De Boeck Université, vol. 77(2), pages 141-168.
    15. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A comparison of Forecasting Procedures for Macroeconomic Series: The Contribution of Structural Break Models," Working Papers 1113, University of Strathclyde Business School, Department of Economics.
    16. Bréchet, Thierry & Jouvet, Pierre-André & Rotillon, Gilles, 2013. "Tradable pollution permits in dynamic general equilibrium: Can optimality and acceptability be reconciled?," Ecological Economics, Elsevier, vol. 91(C), pages 89-97.
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