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Andréas Heinen
(Andreas Heinen)

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.

Working papers

  1. M. Hamadi & A. Heinen, 2015. "Firm Performance when Ownership is very Concentrated: Evidence from a Semiparametric Panel," Working Paper CRENoS 201502, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Zouaoui, Haykel & Mazioud, Manel & Ellouz, Nidhal Ziedi, 2018. "A semi-parametric panel data analysis on financial development-economic volatility nexus in developing countries," Economics Letters, Elsevier, vol. 172(C), pages 50-55.
    2. Maria Aluchna & Tomasz Kuszewski, 2021. "Do Financial Investors Mitigate Agency Problems? Evidence from an Emerging Market," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 872-888.
    3. Gopalakrishnan, Balagopal & Mohapatra, Sanket, 2019. "Insolvency Regimes and Firms' Default Risk Under Economic Uncertainty and Shocks," MPRA Paper 96283, University Library of Munich, Germany.
    4. Inmaculada Aguiar-Diaz & María Victoria Ruiz-Mallorquí & Lourdes Trujillo, 2020. "Ownership structure and financial performance of Spanish port service companies," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(4), pages 674-698, December.
    5. Joura, Essam & Xiao, Qin & Ullah, Subhan, 2021. "The impact of Say-on-Pay votes on firms' strategic policies: Insights from the Anglo-Saxon economy," International Review of Financial Analysis, Elsevier, vol. 73(C).
    6. González, Maximiliano & Guzmán, Alexander & Pablo, Eduardo & Trujillo, María-Andrea, 2019. "Is board turnover driven by performance in family firms?," Research in International Business and Finance, Elsevier, vol. 48(C), pages 169-186.
    7. Taylan Mavruk & Conny Overland & Stefan Sjögren, 2020. "Keeping it real or keeping it simple? Ownership concentration measures compared," European Financial Management, European Financial Management Association, vol. 26(4), pages 958-1005, September.
    8. Qichang Xie & Yingkun Yan & Xu Wang, 2023. "Assessing the role of foreign direct investment in environmental sustainability: a spatial semiparametric panel approach," Economic Change and Restructuring, Springer, vol. 56(2), pages 1263-1295, April.
    9. Mohamad Nur Utomo & Sugeng Wahyudi & Harjum Muharam & Maximus Leonardo Taolin, 2018. "Strategy To Improve Firm Performance Through Operational Efficiency Commitment To Environmental Friendliness: Evidence From Indonesia," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 9(1).
    10. Florackis, Chris & Kanas, Angelos & Kostakis, Alexandros & Sainani, Sushil, 2020. "Idiosyncratic risk, risk-taking incentives and the relation between managerial ownership and firm value," European Journal of Operational Research, Elsevier, vol. 283(2), pages 748-766.
    11. Maria Aluchna & Tomasz Kuszewski, 2020. "Does Corporate Governance Compliance Increase Company Value? Evidence from the Best Practice of the Board," JRFM, MDPI, vol. 13(10), pages 1-21, October.
    12. Sami Ben Jabeur & Rabi Belhaj Hassine & Salma Mefteh‐Wali, 2021. "Firm financial performance during the financial crisis: A French case study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2800-2812, April.
    13. Nakabayashi, Masaki, 2019. "Ownership structure and market efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 189-212.

  2. Andréas Heinen & M. Hamadi & Guillermo Baquero, 2013. "Competition, Loan Rates and Information Dispersion in Microcredit Markets," Working Paper CRENoS 201314, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Hailu Abebe Wondirad, 2022. "Interest rates in microfinance: What is a fair interest rate when we lend to the poor?," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4537-4548, December.
    2. Riekhof, Marie-Catherine, 2019. "The insurance premium in the interest rates of interlinked loans in a small-scale fishery," Environment and Development Economics, Cambridge University Press, vol. 24(1), pages 87-112, February.
    3. Jonathan de Quidt & Thiemo Fetzer & Maitreesh Ghatak, 2018. "Market Structure and Borrower Welfare in Microfinance," Economic Journal, Royal Economic Society, vol. 128(610), pages 1019-1046, May.
    4. Tchakoute Tchuigoua, Hubert, 2016. "Buffer capital in microfinance institutions," Journal of Business Research, Elsevier, vol. 69(9), pages 3523-3537.
    5. Abrego, Adriana & Guizar, Isai, 2017. "Resilience of Agricultural Microfinance Institutions to Rainfall Shocks," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258031, Agricultural and Applied Economics Association.
    6. Cull, Robert & Demirgüç-Kunt, Asli & Morduch, Jonathan, 2013. "Banks and Microbanks," CEI Working Paper Series 2013-03, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    7. Cull, Robert & Harten, Sven & Nishida, Ippei & Rusu, Anca Bogdana & Bull, Greta, 2015. "Benchmarking the financial performance, growth, and outreach of greenfield MFIs in Africa," Emerging Markets Review, Elsevier, vol. 25(C), pages 92-124.
    8. Beatriz Cu鬬ar-Fernᮤez & Yolanda Fuertes-Call鮠 & Carlos Serrano-Cinca & Bego uti鲲ez-Nieto, 2016. "Determinants of margin in microfinance institutions," Applied Economics, Taylor & Francis Journals, vol. 48(4), pages 300-311, January.

  3. Malika Hamadi & Andreas Heinen, 2011. "Ownership Structure and Firm Performance : Evidence from a non-parametric panel," DEM Discussion Paper Series 11-16, Department of Economics at the University of Luxembourg.

    Cited by:

    1. Mendy, David & Widodo, Tri, 2018. "Two Stage Markov Switching Model: Identifying the Indonesian Rupiah Per US Dollar Turning Points Post 1997 Financial Crisis," MPRA Paper 86728, University Library of Munich, Germany.
    2. T. G. Saji, 2019. "Can BRICS Form a Currency Union? An Analysis under Markov Regime-Switching Framework," Global Business Review, International Management Institute, vol. 20(1), pages 151-165, February.
    3. Anatoliy Swishchuk & Maksym Tertychnyi & Robert Elliott, 2014. "Pricing Currency Derivatives with Markov-modulated Levy Dynamics," Papers 1402.1953, arXiv.org.
    4. Anatoliy Swishchuk & Maksym Tertychnyi & Winsor Hoang, 2014. "Currency Derivatives Pricing for Markov-modulated Merton Jump-diffusion Spot Forex Rate," Papers 1402.2273, arXiv.org.

  4. HEINEN, Andréas & VALDESOGO, Alfonso, 2009. "Asymmetric CAPM dependence for large dimensions: the Canonical Vine Autoregressive Model," LIDAM Discussion Papers CORE 2009069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    2. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    3. Arreola Hernandez, Jose, 2014. "Are oil and gas stocks from the Australian market riskier than coal and uranium stocks? Dependence risk analysis and portfolio optimization," Energy Economics, Elsevier, vol. 45(C), pages 528-536.
    4. Arreola Hernandez, Jose & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Al Janabi, Mazin A. M. & Reboredo, Juan Carlos, 2014. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," MPRA Paper 73399, University Library of Munich, Germany, revised Aug 2016.
    5. Satish Kumar & Aviral K. Tiwari & Ibrahim D. Raheem & Qiang Ji, 2019. "Dependence risk analysis in energy, agricultural and precious metals commodities: A pair vine copula approach," Research Africa Network Working Papers 19/092, Research Africa Network (RAN).
    6. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    7. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Tinbergen Institute Discussion Papers 13-022/III, Tinbergen Institute.
    8. Maziar Sahamkhadam & Andreas Stephan, 2023. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2139-2166, December.
    9. Jammazi, Rania & Tiwari, Aviral Kr. & Ferrer, Román & Moya, Pablo, 2015. "Time-varying dependence between stock and government bond returns: International evidence with dynamic copulas," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 74-93.
    10. David E. Allen & Michael McAleer & Abhay K. Singh, 2014. "Risk Measurement and Risk Modelling using Applications of Vine Copulas," Tinbergen Institute Discussion Papers 14-054/III, Tinbergen Institute.
    11. Catherine Bruneau & Alexis Flageollet & Zhun Peng, 2020. "Economic and financial risk factors, copula dependence and risk sensitivity of large multi-asset class portfolios," Annals of Operations Research, Springer, vol. 284(1), pages 165-197, January.
    12. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    13. Stelios Bekiros & Shawkat Hammoudeh & Rania Jammazi & Duc Khuong Nguyen, 2018. "Sovereign bond market dependencies and crisis transmission around the eurozone debt crisis: a dynamic copula approach," Applied Economics, Taylor & Francis Journals, vol. 50(47), pages 5031-5049, October.
    14. Waqas Hanif & Jose Arreola Hernandez & Perry Sadorsky & Seong-Min Yoon, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," Post-Print hal-02567429, HAL.
    15. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    16. Luca Riccetti, 2013. "A copula–GARCH model for macro asset allocation of a portfolio with commodities," Empirical Economics, Springer, vol. 44(3), pages 1315-1336, June.
    17. Bekiros, Stelios & Hernandez, Jose Arreola & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2015. "Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios," Resources Policy, Elsevier, vol. 46(P2), pages 1-11.
    18. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    19. Guillaume Arnould & Catherine Bruneau & Zhun Peng, 2015. "Liquidity and Equity Short term fragility: Stress-tests for the European banking system," Post-Print halshs-01254729, HAL.
    20. Brechmann Eike Christain & Czado Claudia, 2013. "Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 307-342, December.
    21. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    22. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    23. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    24. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    25. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    26. Sahamkhadam, Maziar & Stephan, Andreas & Östermark, Ralf, 2022. "Copula-based Black–Litterman portfolio optimization," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1055-1070.
    27. David Walsh-Jones & Daniel Jones & Christoph Reisinger, 2014. "Modelling of dependence in high-dimensional financial time series by cluster-derived canonical vines," Papers 1411.4970, arXiv.org.
    28. Al Janabi, Mazin A.M. & Arreola Hernandez, Jose & Berger, Theo & Nguyen, Duc Khuong, 2017. "Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1121-1131.
    29. Salaheddine El Adlouni, 2018. "Quantile regression C-vine copula model for spatial extremes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(1), pages 299-317, October.
    30. Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    31. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    32. Min, Aleksey & Czado, Claudia, 2014. "SCOMDY models based on pair-copula constructions with application to exchange rates," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 523-535.
    33. Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo & Lacal, Virginia, 2016. "Structure learning in Bayesian Networks using regular vines," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 186-208.
    34. Hans Manner & Olga Reznikova, 2012. "A Survey on Time-Varying Copulas: Specification, Simulations, and Application," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 654-687, November.
    35. Catherine Bruneau & Alexis Flageollet & Zhun Peng, 2015. "Risk Factors, Copula Dependence and Risk Sensitivity of a Large Portfolio," Documents de recherche 15-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    36. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    37. Prayer M. Rikhotso & Beatrice D. Simo-Kengne, 2022. "Dependence Structures between Sovereign Credit Default Swaps and Global Risk Factors in BRICS Countries," JRFM, MDPI, vol. 15(3), pages 1-22, February.

  5. Sophie Chemarin & Andreas Heinen & Eric Strobl, 2008. "Electricity, carbon and weather in France: where do we stand ?," Working Papers hal-00340171, HAL.

    Cited by:

    1. M. Cummins, 2013. "Multiple comparisons problem: Recent advances applied to energy and emissions," Applied Economics Letters, Taylor & Francis Journals, vol. 20(9), pages 903-909, June.
    2. Fatemeh Nazifi, 2016. "The pass-through rates of carbon costs on to electricity prices within the Australian National Electricity Market," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 18(1), pages 41-62, January.
    3. Moutinho, Victor & Vieira, Joel & Carrizo Moreira, António, 2011. "The crucial relationship among energy commodity prices: Evidence from the Spanish electricity market," Energy Policy, Elsevier, vol. 39(10), pages 5898-5908, October.
    4. Freitas, Carlos J. Pereira & Silva, Patrícia Pereira da, 2015. "European Union emissions trading scheme impact on the Spanish electricity price during phase II and phase III implementation," Utilities Policy, Elsevier, vol. 33(C), pages 54-62.

  6. CHOLLETE, Loran & HEINEN, Andréas & VALDESOGO, Alfonso, 2008. "Modeling international financial returns with a multivariate regime switching copula," LIDAM Discussion Papers CORE 2008013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Cathy Ning & Loran Chollete, 2012. "Asymmetric Dependence between Aggregate Consumption and Financial Risk," Working Papers 046, Ryerson University, Department of Economics.
    2. Syed Abul, Basher & Salem, Nechi & Hui, Zhu, 2014. "Dependence patterns across Gulf Arab stock markets: a copula approach," MPRA Paper 56566, University Library of Munich, Germany.
    3. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    4. Arreola Hernandez, Jose & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Al Janabi, Mazin A. M. & Reboredo, Juan Carlos, 2014. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," MPRA Paper 73399, University Library of Munich, Germany, revised Aug 2016.
    5. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.
    6. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    7. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    8. Fei, Fei & Fuertes, Ana-Maria & Kalotychou, Elena, 2017. "Dependence in credit default swap and equity markets: Dynamic copula with Markov-switching," International Journal of Forecasting, Elsevier, vol. 33(3), pages 662-678.
    9. Govindan, Rajesh & Al-Ansari, Tareq, 2019. "Computational decision framework for enhancing resilience of the energy, water and food nexus in risky environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 653-668.
    10. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Tinbergen Institute Discussion Papers 13-022/III, Tinbergen Institute.
    11. Claudiu Albulescu & Aviral Tiwari & Qiang Ji, 2020. "Copula-based local dependence between energy, agriculture and metal commodity markets," Papers 2003.04007, arXiv.org.
    12. Tachibana, Minoru, 2022. "Safe haven assets for international stock markets: A regime-switching factor copula approach," Research in International Business and Finance, Elsevier, vol. 60(C).
    13. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    14. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    15. Donatien Hainaut & Yang Shen & Yan Zeng, 2018. "How do capital structure and economic regime affect fair prices of bank’s equity and liabilities?," Annals of Operations Research, Springer, vol. 262(2), pages 519-545, March.
    16. Yuting Gong & Xueqin Wang & Mo Zhu & Ying‐En Ge & Wenming Shi, 2023. "Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 69-89, January.
    17. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    18. David E. Allen & Michael McAleer & Abhay K. Singh, 2014. "Risk Measurement and Risk Modelling using Applications of Vine Copulas," Tinbergen Institute Discussion Papers 14-054/III, Tinbergen Institute.
    19. Jamal Bouoiyour & Refk Selmi & Shawkat Hammoudeh & Mark E Wohar, 2019. "What are the categories of geopolitical risks that could drive oil prices higher? Acts or threats?," Post-Print hal-02409062, HAL.
    20. Oleg Sokolinskiy & Dick van Dijk, 2011. "Forecasting Volatility with Copula-Based Time Series Models," Tinbergen Institute Discussion Papers 11-125/4, Tinbergen Institute.
    21. Hainaut, Donatien, 2014. "Impulse control of pension fund contributions, in a regime switching economy," European Journal of Operational Research, Elsevier, vol. 239(3), pages 810-819.
    22. Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
    23. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    24. René Garcia & Georges Tsafack, 2009. "Dependence Structure and Extreme Comovements in International Equity and Bond Markets," CIRANO Working Papers 2009s-21, CIRANO.
    25. Yang, Bingduo & Hafner, Christian M. & Liu, Guannan & Long, Wei, 2018. "Semiparametric Estimation and Variable Selection for Single-index Copula Models," IRTG 1792 Discussion Papers 2018-064, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Documents de travail du Centre d'Economie de la Sorbonne 10040, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    27. Henryk Gurgul & Robert Syrek, 2010. "Polish stock market and some foreign markets - dependence analysis by regime-switching copulas," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 8, pages 21-39.
    28. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    29. Waqas Hanif & Jose Arreola Hernandez & Perry Sadorsky & Seong-Min Yoon, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," Post-Print hal-02567429, HAL.
    30. Donatien Hainaut & Renaud MacGilchrist, 2012. "Strategic asset allocation with switching dependence," Annals of Finance, Springer, vol. 8(1), pages 75-96, February.
    31. Cyprian Omari & Peter Mwita & Anthony Waititu, 2019. "Conditional Dependence Modelling with Regular Vine Copulas," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(1), pages 1-5.
    32. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    33. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2013. "Pair Copula Construction based Expected Shortfall estimation," Economics Bulletin, AccessEcon, vol. 33(2), pages 1067-1072.
    34. Chollete, Loran & Ning, Cathy, 2009. "The Dependence Structure of Macroeconomic Variables in the US," UiS Working Papers in Economics and Finance 2009/31, University of Stavanger.
    35. BenMim, Imen & BenSaïda, Ahmed, 2019. "Financial contagion across major stock markets: A study during crisis episodes," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 187-201.
    36. Christoffersen, Peter & Langlois, Hugues, 2013. "The Joint Dynamics of Equity Market Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1371-1404, October.
    37. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    38. Selmi, Refk & Bouoiyour, Jamal & Wohar, Mark E., 2022. "“Digital Gold” and geopolitics," Research in International Business and Finance, Elsevier, vol. 59(C).
    39. Ahmed BenSaïda & Houda Litimi, 2021. "Financial contagion across G10 stock markets: A study during major crises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4798-4821, July.
    40. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    41. Kai Zheng & Weidong Xu & Xili Zhang, 2023. "Multivariate Regime Switching Model Estimation and Asset Allocation," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 165-196, January.
    42. Yang, Bingduo & Cai, Zongwu & Hafner, Christian M. & Liu, Guannan, 2018. "Trending Mixture Copula Models with Copula Selection," IRTG 1792 Discussion Papers 2018-057, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    43. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    44. Xue Deng & Ying Liang, 2023. "Robust Portfolio Optimization Based on Semi-Parametric ARMA-TGARCH-EVT Model with Mixed Copula Using WCVaR," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 267-294, January.
    45. Dominique Guegan & Pierre-André Maugis, 2011. "An econometric Study for Vine Copulas," Post-Print halshs-00645799, HAL.
    46. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    47. Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2021. "The structure and degree of dependence in government bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    48. Zhichao Zhang & Fan Zhang & Zhuang Zhang, 2013. "Strategic Asset Allocation for China's Foreign Reserves: A Copula Approach," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(6), pages 1-21, November.
    49. Chollete, Loran & Pena, Victor de la & Lu, Ching-Chih, 2009. "International Diversification: A Copula Approach," UiS Working Papers in Economics and Finance 2009/27, University of Stavanger.
    50. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    51. Markwat, T.D. & Kole, H.J.W.G. & van Dijk, D.J.C., 2009. "Time Variation in Asset Return Dependence: Strength or Structure?," ERIM Report Series Research in Management ERS-2009-052-F&A, 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.
    52. Peter Christoffersen & Kris Jacobs & Xisong Jin & Hugues Langlois, 2013. "Dynamic Diversification in Corporate Credit," CREATES Research Papers 2013-46, Department of Economics and Business Economics, Aarhus University.
    53. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    54. Chakraborty, Sandip & Kakani, Ram Kumar & Sampath, Aravind, 2022. "Portfolio risk and stress across the business cycle," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    55. 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.
    56. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    57. Hainaut, Donatien & Moraux, Franck, 2019. "A switching self-exciting jump diffusion process for stock prices," LIDAM Reprints ISBA 2019017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    58. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.
    59. Sanjay Sehgal & Piyush Pandey & Florent Deisting, 2018. "Stock Market Integration Dynamics and its Determinants in the East Asian Economic Community Region," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 389-425, June.
    60. Anubha Goel & Aparna Mehra, 2019. "Analyzing Contagion Effect in Markets During Financial Crisis Using Stochastic Autoregressive Canonical Vine Model," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 921-950, March.
    61. Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "On the paradigm shift of asset pricing models, before and after the global financial crisis: a literature review," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 15(29), pages 7-38, Primer se.
    62. Cao, Jin & Chollete, Lorán, 2017. "Monetary policy and financial stability in the long run: A simple game-theoretic approach," Journal of Financial Stability, Elsevier, vol. 28(C), pages 125-142.
    63. Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo, 2010. "On the simplified pair-copula construction -- Simply useful or too simplistic?," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1296-1310, May.
    64. Henryk Gurgul & Artur Machno, 2015. "Regime-Dependent Relationships among Stock Markets in Frankfurt, Vienna and Warsaw," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 13(1 (Spring), pages 3-25.
    65. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    66. Weiß, Gregor N.F., 2011. "Are Copula-GoF-tests of any practical use? Empirical evidence for stocks, commodities and FX futures," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 173-188, May.
    67. Silva Filho, Osvaldo Candido da & Ziegelmann, Flavio Augusto & Dueker, Michael J., 2012. "Modeling dependence dynamics through copulas with regime switching," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 346-356.
    68. Arturo Lorenzo Valdés & Ricardo Massa Roldán, 2013. "Measuring dependence in financial crisis: A copula approach for Mexico and Brazil," Economía Mexicana NUEVA ÉPOCA, CIDE, División de Economía, vol. 0(2), pages 341-355, July-Dece.
    69. Chollete, Loran & Ning, Cathy, 2012. "Asymmetric Dependence in the US Economy: Application to Money and the Phillips Curve," UiS Working Papers in Economics and Finance 2012/1, University of Stavanger.
    70. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    71. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.
    72. Fjærvik, Thomas, 2023. "Crash risk in the Nordic Stock Market - a cross-sectional analysis," Discussion Papers 2023/5, Norwegian School of Economics, Department of Business and Management Science.
    73. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    74. Chong, Terence Tai Leung & Ding, Yue & Pang, Tianxiao, 2017. "Extreme Risk Value and Dependence Structure of the China Securities Index 300," MPRA Paper 80556, University Library of Munich, Germany.
    75. Manner, Hans & Stark, Florian & Wied, Dominik, 2019. "Testing for structural breaks in factor copula models," Journal of Econometrics, Elsevier, vol. 208(2), pages 324-345.
    76. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    77. Takahiro Komatsu & Naoki Makimoto, 2015. "Dynamic Investment Strategy with Factor Models Under Regime Switches," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 22(2), pages 209-237, May.
    78. Youssef, Manel & Mokni, Khaled, 2020. "Modeling the relationship between oil and USD exchange rates: Evidence from a regime-switching-quantile regression approach," Journal of Multinational Financial Management, Elsevier, vol. 55(C).
    79. Supper, Hendrik & Irresberger, Felix & Weiß, Gregor, 2020. "A comparison of tail dependence estimators," European Journal of Operational Research, Elsevier, vol. 284(2), pages 728-742.
    80. Andréas Heinen & Mi Lim Kim & Alfonso Valdesogo, 2015. "Regime switching House price dependence: Evidence from MSAs in the US," ERES eres2015_201, European Real Estate Society (ERES).
    81. Stöber, Jakob & Czado, Claudia, 2014. "Regime switches in the dependence structure of multidimensional financial data," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 672-686.
    82. Canela Miguel-Angel & Pedreira Eduardo, 2012. "Modelling Dependence in Latin American Markets Using Copula Functions," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 11(3), pages 231-270, December.
    83. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    84. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    85. Su, EnDer, 2014. "Measuring Contagion Risk in High Volatility State between Major Banks in Taiwan by Threshold Copula GARCH Model," MPRA Paper 58161, University Library of Munich, Germany.
    86. Chollete, Loran, 2011. "A Model of Endogenous Extreme Events," UiS Working Papers in Economics and Finance 2012/2, University of Stavanger.
    87. Qingfu Liu & Yiuman Tse & Kaixin Zheng, 2021. "The impact of trading behavioral biases on market liquidity under different volatility levels: Evidence from the Chinese commodity futures market," The Financial Review, Eastern Finance Association, vol. 56(4), pages 671-692, November.
    88. Pablo Jose Campos de Carvalho & Aparna Gupta, 2018. "Multivariate Jump Diffusion Model with Markovian Contagion," Working Papers Series 482, Central Bank of Brazil, Research Department.
    89. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    90. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    91. Hendriks, Johannes Jurgens & Bonga-Bonga, Lumengo, 2020. "Sectoral dependence and contagion in the BRICS grouping: an application of the R-Vine copulas," MPRA Paper 102473, University Library of Munich, Germany.
    92. Atenga, Eric Martial Etoundi & Mougoué, Mbodja, 2021. "Return and volatility spillovers to African currencies markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    93. Travkin, Alexandr, 2013. "Pair copula constructions in portfolio optimization ploblem," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 32(4), pages 110-133.
    94. Nathan Lael Joseph & Thi Thuy Anh Vo & Asma Mobarek & Sabur Mollah, 2020. "Volatility and asymmetric dependence in Central and East European stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1241-1303, November.
    95. Minoru Tachibana, 2020. "Flight-to-quality in the stock–bond return relation: a regime-switching copula approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(4), pages 429-470, December.
    96. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    97. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    98. Su, Xiaoshan & Bai, Manying & Han, Yingwei, 2021. "Robust portfolio selection with regime switching and asymmetric dependence," Economic Modelling, Elsevier, vol. 99(C).
    99. Ye, Wuyi & Zhu, Yangguang & Wu, Yuehua & Miao, Baiqi, 2016. "Markov regime-switching quantile regression models and financial contagion detection," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 21-26.
    100. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Post-Print halshs-00492124, HAL.
    101. Donatien Hainaut & Yan Shen & Yan Zeng, 2016. "How do capital structure and economic regime affect fair prices of bank's equity and liabilities?," Post-Print hal-01394133, HAL.
    102. Pan, Zhiyuan & Wang, Yudong & Yang, Li, 2014. "Hedging crude oil using refined product: A regime switching asymmetric DCC approach," Energy Economics, Elsevier, vol. 46(C), pages 472-484.
    103. Maximilian Coblenz & Simon Holz & Hans‐Jörg Bauer & Oliver Grothe & Rainer Koch, 2020. "Modelling fuel injector spray characteristics in jet engines by using vine copulas," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 863-886, August.
    104. Jose Arreola Hernandez & Mazin A.M. Al Janabi, 2020. "Forecasting of dependence, market, and investment risks of a global index portfolio," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 512-532, April.
    105. Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    106. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    107. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    108. Mendoza, Alfonso. & Galvanovskis, Evalds., 2014. "La cópula GED bivariada. Una aplicación en entornos de crisis," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(323), pages .721-746, julio-sep.
    109. 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.
    110. Min, Aleksey & Czado, Claudia, 2014. "SCOMDY models based on pair-copula constructions with application to exchange rates," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 523-535.
    111. Shi, Wenming & Gong, Yuting & Yin, Jingbo & Nguyen, Son & Liu, Qian, 2022. "Determinants of dynamic dependence between the crude oil and tanker freight markets: A mixed-frequency data sampling copula model," Energy, Elsevier, vol. 254(PB).
    112. Philippas, Dionisis & Siriopoulos, Costas, 2013. "Putting the “C” into crisis: Contagion, correlations and copulas on EMU bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 161-176.
    113. Songjiao Chen & William Wilson & Ryan Larsen & Bruce Dahl, 2016. "Risk Management for Grain Processors and “Copulas”," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 365-382, June.
    114. Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo & Lacal, Virginia, 2016. "Structure learning in Bayesian Networks using regular vines," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 186-208.
    115. Wei Huang & Meng-Shiuh Chang, 2021. "Gold and Government Bonds as Safe-Haven Assets Against Stock Market Turbulence in China," SAGE Open, , vol. 11(1), pages 21582440219, January.
    116. Derumigny Alexis & Fermanian Jean-David, 2017. "About tests of the “simplifying” assumption for conditional copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 154-197, August.
    117. Zhou, Chunyang & Qin, Xiao, 2021. "Time-varying asymmetric tail dependence of international equities markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    118. Thijs Markwat, 2014. "The rise of global stock market crash probabilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 557-571, April.
    119. Chollete, Loran & de la Pena , Victor & Lu, Ching-Chih, 2009. "International Diversification: An Extreme Value Approach," UiS Working Papers in Economics and Finance 2009/26, University of Stavanger.
    120. Changqing, Luo & Chi, Xie & Cong, Yu & Yan, Xu, 2015. "Measuring financial market risk contagion using dynamic MRS-Copula models: The case of Chinese and other international stock markets," Economic Modelling, Elsevier, vol. 51(C), pages 657-671.
    121. Chang, Meng-Shiuh & Kung, Chih-Chun & Chen, Meng-Wei & Tian, Yuan, 2021. "Volatility regime, inverted asymmetry, contagion, and flights in the gold market," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    122. Chang, Kuang-Liang, 2017. "Does REIT index hedge inflation risk? New evidence from the tail quantile dependences of the Markov-switching GRG copula," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 56-67.
    123. Michael A. Goldstein & Joseph McCarthy & Alexei G. Orlov, 2019. "The Core, Periphery, and Beyond: Stock Market Comovements among EU and Non‐EU Countries," The Financial Review, Eastern Finance Association, vol. 54(1), pages 5-56, February.
    124. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    125. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
    126. Henryk Gurgul & Artur Machno, 2014. "The optimal portfolio under VaR and ES," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 24(2), pages 59-79.
    127. Longbing Cao, 2021. "AI in Finance: Challenges, Techniques and Opportunities," Papers 2107.09051, arXiv.org.
    128. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    129. Ba Chu & Stephen Satchell, 2016. "Recovering the Most Entropic Copulas from Preliminary Knowledge of Dependence," Econometrics, MDPI, vol. 4(2), pages 1-21, March.
    130. Peter Christoffersen & Kris Jacobs & Xisong Jin & Hugues Langlois, 2018. "Dynamic Dependence and Diversification in Corporate Credit [Asymmetric correlations of equity portfolios]," Review of Finance, European Finance Association, vol. 22(2), pages 521-560.
    131. Chollete, Loran & Ning, Cathy, 2010. "Asymmetric Dependence in US Financial Risk Factors?," UiS Working Papers in Economics and Finance 2011/2, University of Stavanger.
    132. Dominique Guegan & Pierre-André Maugis, 2011. "An econometric Study for Vine Copulas," PSE-Ecole d'économie de Paris (Postprint) halshs-00645799, HAL.
    133. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2013. "Risk prediction management and weak form market efficiency in Eurozone financial crisis," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 384-393.
    134. Krupskii, Pavel & Joe, Harry, 2015. "Structured factor copula models: Theory, inference and computation," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 53-73.
    135. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.
    136. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    137. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    138. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.
    139. Chollete, Loran & Ismailescu, Iuliana & Lu, Ching-Chih, 2014. "Dependence between Extreme Events in the Real and Financial Sectors," UiS Working Papers in Economics and Finance 2014/12, University of Stavanger.

  7. Barrios, Salvador & Bertinelli, Luisito & Heinen, Andreas, 2007. "Exploring The Link Between Local And Global Knowledge Spillovers," MPRA Paper 6239, University Library of Munich, Germany.

    Cited by:

    1. Burgi, Constantin & Gorgulu, Nisan, 2021. "The Impact of the Spatial Population Distribution on Economic Growth," Working Papers 17-2021, Copenhagen Business School, Department of Economics.
    2. Syeda Tamkeen Fatima, 2016. "Productivity spillovers from foreign direct investment: evidence from Turkish micro-level data," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 25(3), pages 291-324, June.
    3. Harald Badinger & Peter Egger, 2010. "Horizontal vs. Vertical Interdependence in Multinational Activity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(6), pages 744-768, December.
    4. Muhammad Ali & Uwe Cantner & Ipsita Roy, 2016. "Knowledge spillovers through FDI and trade: the moderating role of quality-adjusted human capital," Journal of Evolutionary Economics, Springer, vol. 26(4), pages 837-868, October.
    5. Magrini, Stefano & Cheshire, Paul, 2008. "Urban growth drivers in a Europe of sticky people and implicit boundaries," LSE Research Online Documents on Economics 33182, London School of Economics and Political Science, LSE Library.
    6. Constantin Bürgi & Nisan Gorgulu, 2022. "The Impact of the Spatial Population Distribution on Economic Growth: Evidence from the United States," CESifo Working Paper Series 10008, CESifo.
    7. Paul Cheshire & Stefano Magrini, 2008. "Urban Growth Drivers and Spatial Inequalities: Europe - a case with geographically sticky people," Working Papers 2008_32, Department of Economics, University of Venice "Ca' Foscari".
    8. Santos, Eleonora, 2017. "Externalities from FDI on domestic firms’ Productivity: A Literature Review for Developed Countries," MPRA Paper 88958, University Library of Munich, Germany.
    9. Eberhardt, Markus & Helmers, Christian & Strauss, Hubert, 2010. "Do spillovers matter when estimating private returns to R&D?," Economic and Financial Reports 2010/1, European Investment Bank, Economics Department.
    10. Nuno Crespo & Isabel Proença & Maria Paula Fontoura, 2010. "The Spatial Dimension in FDI Spillovers: Evidence at the Regional Level from Portugal," Working Papers Department of Economics 2010/17, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.

  8. Chollete, Lorán & Heinen, Andreas, 2006. "Frequent Turbulence? A Dynamic Copula Approach," Discussion Papers 2006/10, Norwegian School of Economics, Department of Business and Management Science.

    Cited by:

    1. Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 3-36.
    2. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.

  9. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Mike Vuolo, 2017. "Copula Models for Sociology: Measures of Dependence and Probabilities for Joint Distributions," Sociological Methods & Research, , vol. 46(3), pages 604-648, August.
    2. Yee, Thomas W., 2014. "Reduced-rank vector generalized linear models with two linear predictors," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 889-902.
    3. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.

  10. 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).

    Cited by:

    1. Pagliacci, Carolina, 2006. "The Venezuelan Overnight Fund Market: Understanding a Credit Constraint Limit Order Market," MPRA Paper 106541, University Library of Munich, Germany.
    2. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    3. Aitken, Michael & Almeida, Niall & deB. Harris, Frederick H. & McInish, Thomas H., 2007. "Liquidity supply in electronic markets," Journal of Financial Markets, Elsevier, vol. 10(2), pages 144-168, May.
    4. 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.
    5. Kempf, Alexander & Mayston, Daniel, 2006. "Liquidity commonality beyond best prices," CFR Working Papers 06-04, University of Cologne, Centre for Financial Research (CFR).

  11. Erick Rengifo & Andresas Heinen, 2004. "Comovements in Trading activity: A Multivariate Autoregressive Model of Time Series Count Data Using Copulas," Econometric Society 2004 Far Eastern Meetings 755, Econometric Society.

    Cited by:

    1. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.

  12. 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.

    Cited by:

    1. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    2. 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.
    3. Kempf, Alexander & Mayston, Daniel, 2006. "Liquidity commonality beyond best prices," CFR Working Papers 06-04, University of Cologne, Centre for Financial Research (CFR).

  13. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Forecasting transaction counts with integer-valued GARCH models," MPRA Paper 101779, University Library of Munich, Germany, revised 11 Jul 2020.
    2. Aknouche, Abdelhakim & Bendjeddou, Sara, 2016. "Negative binomial quasi-likelihood inference for general integer-valued time series models," MPRA Paper 76574, University Library of Munich, Germany, revised 03 Feb 2017.
    3. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    4. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    6. Daniel L. R. Orozco & Lucas O. F. Sales & Luz M. Z. Fernández & André L. S. Pinho, 2021. "A new mixed first-order integer-valued autoregressive process with Poisson innovations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 559-580, December.
    7. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    8. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    9. Aknouche, Abdelhakim & Scotto, Manuel, 2022. "A multiplicative thinning-based integer-valued GARCH model," MPRA Paper 112475, University Library of Munich, Germany.
    10. Weiß, Christian H., 2010. "INARCH(1) processes: Higher-order moments and jumps," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1771-1780, December.
    11. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    12. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.
    13. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    14. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data: Modelling and Estimation," Economics Working Papers 2005-08, Christian-Albrechts-University of Kiel, Department of Economics.
    15. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    17. 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.
    18. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Naushad Mamode Khan, 2019. "Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework," JRFM, MDPI, vol. 12(2), pages 1-13, April.
    19. 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).
    20. Ghahramani, M. & Thavaneswaran, A., 2009. "On some properties of Autoregressive Conditional Poisson (ACP) models," Economics Letters, Elsevier, vol. 105(3), pages 273-275, December.
    21. Ali Ahmad & Christian Francq, 2015. "Poisson QMLE of Count Time Series Models," Post-Print hal-01533548, HAL.
    22. Weiß, Christian H. & Schweer, Sebastian, 2016. "Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 124-130.
    23. 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.
    24. Christian H. Weiß, 2017. "On Eigenvalues of the Transition Matrix of Some Count-Data Markov Chains," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 997-1007, September.
    25. Luiza S. C. Piancastelli & Wagner Barreto‐Souza & Hernando Ombao, 2023. "Flexible bivariate INGARCH process with a broad range of contemporaneous correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 206-222, March.
    26. Christian Weiß, 2009. "Modelling time series of counts with overdispersion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 507-519, November.
    27. Youngmi Lee & Sangyeol Lee, 2019. "CUSUM test for general nonlinear integer-valued GARCH models: comparison study," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1033-1057, October.
    28. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    29. Xu, Hai-Yan & Xie, Min & Goh, Thong Ngee & Fu, Xiuju, 2012. "A model for integer-valued time series with conditional overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4229-4242.
    30. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    31. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    32. Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
    33. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    34. Juan Dolado, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 442-446, September.
    35. Ivanov, Vladimir & Lewis, Craig M., 2008. "The determinants of market-wide issue cycles for initial public offerings," Journal of Corporate Finance, Elsevier, vol. 14(5), pages 567-583, December.
    36. Quoreshi, Shahiduzzaman, 2005. "Modelling High Frequency Financial Count Data," Umeå Economic Studies 656, Umeå University, Department of Economics.
    37. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    38. Brännäs, Kurt & Quoreshi, Shahiduzzaman, 2004. "Integer-Valued Moving Average Modelling of the Number of Transactions in Stocks," Umeå Economic Studies 637, Umeå University, Department of Economics.
    39. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    40. 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.
    41. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
    42. Christian H. Weiß & Sebastian Schweer, 2015. "Detecting overdispersion in INARCH(1) processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 281-297, August.
    43. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    44. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    45. Youngmi Lee & Sangyeol Lee & Dag Tjøstheim, 2018. "Asymptotic normality and parameter change test for bivariate Poisson INGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 52-69, March.
    46. 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.
    47. Mamode Khan Naushad & Rumjaun Wasseem & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Computing with bivariate COM-Poisson model under different copulas," Monte Carlo Methods and Applications, De Gruyter, vol. 23(2), pages 131-146, June.
    48. Lee, Sangyeol & Kim, Dongwon & Kim, Byungsoo, 2023. "Modeling and inference for multivariate time series of counts based on the INGARCH scheme," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    49. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    50. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    51. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.

  14. BEN OMRANE, Walid & HEINEN, Andréas, 2003. "The response of individual FX dealers'quoting activity to macroeconomic news announcements," LIDAM Discussion Papers CORE 2003070, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Áron Gereben & György Gyomai & Norbert Kiss M., 2005. "The microstructure approach to exchange rates: a survey from a central bank’s viewpoint," MNB Occasional Papers 2005/42, Magyar Nemzeti Bank (Central Bank of Hungary).

  15. HEINEN, Andréas, 2003. "Modelling time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Forecasting transaction counts with integer-valued GARCH models," MPRA Paper 101779, University Library of Munich, Germany, revised 11 Jul 2020.
    2. Aknouche, Abdelhakim & Bendjeddou, Sara, 2016. "Negative binomial quasi-likelihood inference for general integer-valued time series models," MPRA Paper 76574, University Library of Munich, Germany, revised 03 Feb 2017.
    3. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    4. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    6. Daniel L. R. Orozco & Lucas O. F. Sales & Luz M. Z. Fernández & André L. S. Pinho, 2021. "A new mixed first-order integer-valued autoregressive process with Poisson innovations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 559-580, December.
    7. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    8. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    9. Tianqing Liu & Xiaohui Yuan, 2013. "Random rounded integer-valued autoregressive conditional heteroskedastic process," Statistical Papers, Springer, vol. 54(3), pages 645-683, August.
    10. Aknouche, Abdelhakim & Scotto, Manuel, 2022. "A multiplicative thinning-based integer-valued GARCH model," MPRA Paper 112475, University Library of Munich, Germany.
    11. Weiß, Christian H., 2010. "INARCH(1) processes: Higher-order moments and jumps," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1771-1780, December.
    12. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    13. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.
    14. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    15. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.
    16. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data: Modelling and Estimation," Economics Working Papers 2005-08, Christian-Albrechts-University of Kiel, Department of Economics.
    17. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    19. 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.
    20. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Naushad Mamode Khan, 2019. "Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework," JRFM, MDPI, vol. 12(2), pages 1-13, April.
    21. Jung, Robert C. & Liesenfeld, Roman & Richard, Jean-François, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 73-85.
    22. Ben Omrane, Walid & Heinen, Andréas, 2009. "Is there any common knowledge news in the Euro/Dollar market?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 656-670, October.
    23. 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).
    24. Ghahramani, M. & Thavaneswaran, A., 2009. "On some properties of Autoregressive Conditional Poisson (ACP) models," Economics Letters, Elsevier, vol. 105(3), pages 273-275, December.
    25. Ali Ahmad & Christian Francq, 2015. "Poisson QMLE of Count Time Series Models," Post-Print hal-01533548, HAL.
    26. Weiß, Christian H. & Schweer, Sebastian, 2016. "Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 124-130.
    27. BEN OMRANE, Walid & HEINEN, Andréas, 2003. "The response of individual FX dealers'quoting activity to macroeconomic news announcements," LIDAM Discussion Papers CORE 2003070, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. 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.
    29. Christian H. Weiß, 2017. "On Eigenvalues of the Transition Matrix of Some Count-Data Markov Chains," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 997-1007, September.
    30. Luiza S. C. Piancastelli & Wagner Barreto‐Souza & Hernando Ombao, 2023. "Flexible bivariate INGARCH process with a broad range of contemporaneous correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 206-222, March.
    31. Christian Weiß, 2009. "Modelling time series of counts with overdispersion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 507-519, November.
    32. Youngmi Lee & Sangyeol Lee, 2019. "CUSUM test for general nonlinear integer-valued GARCH models: comparison study," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1033-1057, October.
    33. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    34. Xu, Hai-Yan & Xie, Min & Goh, Thong Ngee & Fu, Xiuju, 2012. "A model for integer-valued time series with conditional overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4229-4242.
    35. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    36. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    37. Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
    38. 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.
    39. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    40. Juan Dolado, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 442-446, September.
    41. Quoreshi, Shahiduzzaman, 2005. "Modelling High Frequency Financial Count Data," Umeå Economic Studies 656, Umeå University, Department of Economics.
    42. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    43. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    44. Brännäs, Kurt & Quoreshi, Shahiduzzaman, 2004. "Integer-Valued Moving Average Modelling of the Number of Transactions in Stocks," Umeå Economic Studies 637, Umeå University, Department of Economics.
    45. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    46. Robert C. Jung & Roman Liesenfeld & Jean-François Richard, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 73-85, January.
    47. 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.
    48. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
    49. Christian H. Weiß & Sebastian Schweer, 2015. "Detecting overdispersion in INARCH(1) processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 281-297, August.
    50. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    51. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    52. Youngmi Lee & Sangyeol Lee & Dag Tjøstheim, 2018. "Asymptotic normality and parameter change test for bivariate Poisson INGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 52-69, March.
    53. 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.
    54. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    55. Mamode Khan Naushad & Rumjaun Wasseem & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Computing with bivariate COM-Poisson model under different copulas," Monte Carlo Methods and Applications, De Gruyter, vol. 23(2), pages 131-146, June.
    56. Lee, Sangyeol & Kim, Dongwon & Kim, Byungsoo, 2023. "Modeling and inference for multivariate time series of counts based on the INGARCH scheme," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    57. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    58. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    59. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    60. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.

Articles

  1. Andréas Heinen & James B. Kau & Donald C. Keenan & Mi Lim Kim, 2021. "Spatial Dependence in Subprime Mortgage Defaults," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 1-24, January.

    Cited by:

    1. Arunav Das, 2021. "Visual Analytics approach for finding spatiotemporal patterns from COVID19," Papers 2101.06476, arXiv.org.

  2. Heinen, Andréas & Valdesogo, Alfonso, 2020. "Spearman rank correlation of the bivariate Student t and scale mixtures of normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 179(C).

    Cited by:

    1. Cameron Francis Assadian & Francis Assadian, 2023. "Data-Driven Modeling of Appliance Energy Usage," Energies, MDPI, vol. 16(22), pages 1-12, November.
    2. Andréas Heinen & Alfonso Valdesogo, 2022. "The Kendall and Spearman rank correlations of the bivariate skew normal distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1669-1698, December.

  3. Andréas Heinen & Jeetendra Khadan & Eric Strobl, 2019. "The Price Impact of Extreme Weather in Developing Countries," The Economic Journal, Royal Economic Society, vol. 129(619), pages 1327-1342.

    Cited by:

    1. Maqsood Aslam & Etienne Farvaque & Franck Malan, 2021. "A disaster always rings twice: Early life experiences and central bankers' reactions to natural disasters," Kyklos, Wiley Blackwell, vol. 74(3), pages 301-320, August.
    2. William Ginn, 2022. "Climate Disasters and the Macroeconomy: Does State-Dependence Matter? Evidence for the US," Economics of Disasters and Climate Change, Springer, vol. 6(1), pages 141-161, March.
    3. Xing-Yun Zou & Xin-Yu Peng & Xin-Xin Zhao & Chun-Ping Chang, 2023. "The impact of extreme weather events on water quality: international evidence," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 1-21, January.
    4. Kanika Mahajan & Shekhar Tomar, 2021. "COVID‐19 and Supply Chain Disruption: Evidence from Food Markets in India†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 35-52, January.
    5. Johar, Meliyanni & Johnston, David W. & Shields, Michael A. & Siminski, Peter & Stavrunova, Olena, 2020. "The Economic Impacts of Direct Natural Disaster Exposure," IZA Discussion Papers 13616, Institute of Labor Economics (IZA).
    6. Kanika Mahajan & Shekhar Tomar, 2020. "Here Today, Gone Tomorrow: COVID-19 and Supply Chain Disruptions," Working Papers 28, Ashoka University, Department of Economics.
    7. Alessandro Cantelmo, 2020. "Rare disasters, the natural interest rate and monetary policy," Temi di discussione (Economic working papers) 1309, Bank of Italy, Economic Research and International Relations Area.
    8. Yothin Jinjarak & Ilan Noy & Quy Ta, 2020. "How Shocks Affect International Reserves? A Quasi-Experiment of Earthquakes," CESifo Working Paper Series 8632, CESifo.
    9. Fox, Stephen & Griffy-Brown, Charla & Dabic, Marina, 2020. "From socio-technical systems to biosocial technical systems: New themes and new guidance for the field of technology in society," Technology in Society, Elsevier, vol. 62(C).
    10. K. Mukherjee & B. Ouattara, 2021. "Climate and monetary policy: do temperature shocks lead to inflationary pressures?," Climatic Change, Springer, vol. 167(3), pages 1-21, August.
    11. Ciccarelli, Matteo & Marotta, Fulvia, 2021. "Demand or supply? An empirical exploration of the effects of climate change on the macroeconomy," Working Paper Series 2608, European Central Bank.
    12. Yang, Bixuan & Asche, Frank & Li, Tao, 2021. "Food Price Inflation and Demand Shocks: Evidence from Chinese Cities during the Covid-19 Epidemic," 2021 Annual Meeting, August 1-3, Austin, Texas 314067, Agricultural and Applied Economics Association.
    13. Beuermann, Diether W. & Pecha, Camilo J., 2020. "The effects of weather shocks on early childhood development: Evidence from 25 years of tropical storms in Jamaica," Economics & Human Biology, Elsevier, vol. 37(C).
    14. Cunpu Li & Xuetong Zhang & Jing He, 2023. "Impact of Climate Change on Inflation in 26 Selected Countries," Sustainability, MDPI, vol. 15(17), pages 1-22, August.
    15. Jeroen Klomp & John Sseruyange, 2021. "Earthquakes and Economic Outcomes: Does Central Bank Independence Matter?," Open Economies Review, Springer, vol. 32(2), pages 335-359, April.
    16. Thibault Lemaire & Paul Vertier, 2023. "International Commodity Prices Transmission to Consumer Prices in Africa," Working Papers hal-03944888, HAL.
    17. Christian Bommer & Axel Dreher & Marcello Perez-Alvarez, "undated". "Home bias in humanitarian aid: The role of regional favoritism in the allocation of international disaster relief," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 266, Courant Research Centre PEG.
    18. John Beirne & Yannis Dafermos & Alexander Kriwoluzky & Nuobu Renzhi & Ulrich Volz & Jana Wittich, 2021. "The Effects of Natural Disasters on Price Stability in the Euro Area," Working Papers 244, Department of Economics, SOAS University of London, UK.
    19. Chaitat Jirophat & Pym Manopimoke & Suparit Suwanik, 2022. "The Macroeconomic Effects of Climate Shocks in Thailand," PIER Discussion Papers 188, Puey Ungphakorn Institute for Economic Research.
    20. Faccia, Donata & Parker, Miles & Stracca, Livio, 2021. "Feeling the heat: extreme temperatures and price stability," Working Paper Series 2626, European Central Bank.
    21. Anastasios Evgenidis & Masashige Hamano & Wessel N. Vermeulen, 2021. "Economic consequences of follow-up disasters: lessons from the 2011 Great East Japan Earthquake," Working Papers 2111, Waseda University, Faculty of Political Science and Economics.
    22. P. Figini & S. Cicognani & L. Zirulia, 2019. "Booking in the Rain: Testing the impact of public information on prices," Working Papers wp1137, Dipartimento Scienze Economiche, Universita' di Bologna.
    23. Etienne Espagne, 2018. "Money, Finance and Climate: The Elusive Quest for a Truly Integrated Assessment Model," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(1), pages 131-143, March.
    24. Kunze, Sven, 2020. "Unraveling the effects of tropical cyclones on economic sectors worldwide," Working Papers 0685, University of Heidelberg, Department of Economics.
    25. Serhan Cevik, João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," Working Papers REM 2023/0276, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    26. Alain N. Kabundi & Mr. Montfort Mlachila & Jiaxiong Yao, 2022. "How Persistent are Climate-Related Price Shocks? Implications for Monetary Policy," IMF Working Papers 2022/207, International Monetary Fund.
    27. Pablo Garcia Sanchez, 2022. "Introduction to weather extremes and monetary policy," BCL working papers 163, Central Bank of Luxembourg.
    28. Sven Kunze, 2021. "Unraveling the Effects of Tropical Cyclones on Economic Sectors Worldwide: Direct and Indirect Impacts," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(4), pages 545-569, April.
    29. Mr. Serhan Cevik & João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," IMF Working Papers 2023/087, International Monetary Fund.

  4. Guillermo Baquero & Malika Hamadi & Andréas Heinen, 2018. "Competition, Loan Rates, and Information Dispersion in Nonprofit and For‐Profit Microcredit Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 893-937, August.

    Cited by:

    1. Wang, Bo & Yu, Yunjun & Yang, Ziying & Zhang, Xiaomei, 2021. "Microfinance institutions and Peer-to-Peer lending: What does microfinance competition bring?," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    2. Quidt, Jonathan de & Fetzer, Thiemo & Ghatak, Maitreesh, 2016. "Commercialization and the Decline of Joint Liability Microcredit," CAGE Online Working Paper Series 272, Competitive Advantage in the Global Economy (CAGE).
    3. Giovanna Aguilar Andía & Jhonatan Portilla Goicochea, 2020. "Competencia, alcance social y sostenibilidad financiera en las microfinanzas reguladas peruanas," Documentos de Trabajo / Working Papers 2020-493, Departamento de Economía - Pontificia Universidad Católica del Perú.
    4. Ahmad, Syedah & Lensink, Robert & Mueller, Annika, 2020. "The double bottom line of microfinance: A global comparison between conventional and Islamic microfinance," World Development, Elsevier, vol. 136(C).
    5. Djibril Faye & Zaka Ratsimalahelo, 2022. "Dynamic analysis of the interest rate determinant in microfinance institutions," Working Papers 2022-09, CRESE.
    6. François-Seck Fall & Hubert Tchakoute Tchuigoua & Anne Vanhems & Léopold Simar, 2021. "Gender effect on microfinance social efficiency: A robust nonparametric approach," Post-Print hal-03200582, HAL.
    7. Pignatel, Isabelle & Tchakoute Tchuigoua, Hubert, 2020. "Microfinance institutions and International Financial Reporting Standards: An exploratory analysis," Research in International Business and Finance, Elsevier, vol. 54(C).
    8. Christoph Sommer, 2022. "Unintended consequences of microfinance: Effects on credit access for small‐ and medium‐sized enterprises," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(3), pages 564-586, April.
    9. Magloire Nya Tchatchoua & Isabelle Pignatel & Hubert Tchakoute Tchuigoua, 2019. "What type of microfinance institutions comply with International Financial Reporting Standards?," Working Papers CEB 19-012, ULB -- Universite Libre de Bruxelles.
    10. Tchakoute-Tchuigoua, Hubert & Soumaré, Issouf, 2019. "The effect of loan approval decentralization on microfinance institutions' outreach and loan portfolio quality," Journal of Business Research, Elsevier, vol. 94(C), pages 1-17.

  5. Hamadi, Malika & Heinen, Andréas & Linder, Stefan & Porumb, Vlad-Andrei, 2016. "Does Basel II affect the market valuation of discretionary loan loss provisions?," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 177-192.

    Cited by:

    1. Hamdi Ben-Nasr & Sabri Boubaker & Syrine Sassi, 2021. "Board reforms and debt choice," Post-Print hal-04455596, HAL.
    2. Hou, Xiaohui & Wang, Bo & Lian, Jiale & Li, Wanli, 2021. "Bank executive pay limits and discretionary loan loss provisions: Evidence from China," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Walter Amedzro St-Hilaire & Patrick Boisselier, 2018. "Evaluating profitability strategies and the determinants of the risk performance of sectoral and banking institutions," Post-Print hal-03220229, HAL.
    4. Bakkar, Yassine & De Jonghe, Olivier & Tarazi, Amine, 2023. "Does banks’ systemic importance affect their capital structure and balance sheet adjustment processes?," Journal of Banking & Finance, Elsevier, vol. 151(C).
    5. Sanzid A. Haq & Dung Viet Tran & M. Kabir Hassan, 2019. "Discretionary Loan Loss Provision Behaviour and Banks' Liquidity Creation," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(2), pages 119-154.
    6. Konstantinos Vasilakopoulos & Christos Tzovas & Apostolos Ballas, 2021. "Banks’ Risk and The Impact of Audit Quality on Income Smoothing," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 20(3), pages 425-453, September.
    7. Mohamed A. Elbannan, 2016. "Accounting Discretion and the Market Disciplining of Bank Risk-taking Behavior: An Assessment of the Effectiveness of Egyptian Banking Reforms from an Accounting Perspective," Accounting and Finance Research, Sciedu Press, vol. 5(4), pages 1-1, November.
    8. Jutasompakorn, Pearpilai & Lim, Chu Yeong & Ranasinghe, Tharindra & Ow Yong, Kevin, 2021. "Impact of Basel III on the discretion and timeliness of Banks’ loan loss provisions," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(2).
    9. Lartey, Theophilus & James, Gregory A. & Danso, Albert & Boateng, Agyenim, 2022. "Bank business models, failure risk and earnings opacity: A short- versus long-term perspective," International Review of Financial Analysis, Elsevier, vol. 80(C).
    10. Pandey, Ashish & Guhathakurta, Kousik, 2022. "Value relevance of loan loss provision components and the choice of model specification," Advances in accounting, Elsevier, vol. 58(C).
    11. Degryse, Hans & Huylebroek, Cédric, 2023. "Fiscal support and banks’ loan loss provisions during the COVID-19 crisis," Journal of Financial Stability, Elsevier, vol. 67(C).
    12. Yassine Bakkar & Olivier de Jonghe & Amine Tarazi, 2017. "Does banks' systemic importance affect their capital structure adjustment process?," Working Papers hal-01546995, HAL.
    13. Hegde, Shantaram P. & Kozlowski, Steven E., 2021. "Discretionary loan loss provisioning and bank stock returns: The Role of economic booms and busts," Journal of Banking & Finance, Elsevier, vol. 130(C).

  6. Hamadi, Malika & Heinen, Andréas, 2015. "Firm performance when ownership is very concentrated: Evidence from a semiparametric panel," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 172-194.
    See citations under working paper version above.
  7. Salvador Barrios & Luisito Bertinelli & Andreas Heinen & Eric Strobl, 2012. "Exploring the Existence of Local and Global Knowledge Spillovers: Evidence from Plant-Level Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 856-880, September.

    Cited by:

    1. Görg, Holger & Mulyukova, Alina, 2022. "Place-Based Policies and Agglomeration Economies: Firm-Level Evidence from Special Economic Zones in India," IZA Discussion Papers 15123, Institute of Labor Economics (IZA).
    2. Stephan Kyburz, Huong Quynh Nguyen, 2017. "Does Proximity to Foreign Invested Firms Stimulate Productivity Growth of Domestic Firms? Firmlevel Evidence from Vietnam," Diskussionsschriften credresearchpaper16, Universitaet Bern, Departement Volkswirtschaft - CRED.
    3. Nguyen, Huong, 2016. "Does Proximity to Foreign Invested Firms Stimulate Productivity Growth of Domestic Firms? Firm-level Evidence from Vietnam," Papers 1001, World Trade Institute.

  8. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.

    Cited by:

    1. Aymen Belgacem & Anna Creti & Khaled Guesmi & Amine Lahiani, 2015. "Volatility spillovers and macroeconomic announcements: evidence from crude oil markets," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2974-2984, June.
    2. Walid Ben Omrane & Christian Hafner, 2015. "Macroeconomic news surprises and volatility spillover in foreign exchange markets," Empirical Economics, Springer, vol. 48(2), pages 577-607, March.
    3. Walid Ben Omrane & Robert Welch & Xinyao Zhou, 2020. "The dynamic effect of macroeconomic news on the euro/US dollar exchange rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 84-103, January.
    4. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    5. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    6. Aymen Belgacem & Amine Lahiani, 2012. "More on the impact of US macroeconomic announcements: Evidence from French and German stock markets' volatility," Economics Bulletin, AccessEcon, vol. 32(2), pages 1509-1526.

  9. Ben Omrane, Walid & Heinen, Andréas, 2009. "Is there any common knowledge news in the Euro/Dollar market?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 656-670, October.

    Cited by:

    1. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
    2. Müller, Christian, 2015. "Radical uncertainty: Sources, manifestations and implications," Economics Discussion Papers 2015-41, Kiel Institute for the World Economy (IfW Kiel).

  10. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    See citations under working paper version above.
  11. Heinen, Andréas & Rengifo, Erick, 2008. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2931-2944, February.
    See citations under working paper version above.
  12. 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.

    Cited by:

    1. Mike Vuolo, 2017. "Copula Models for Sociology: Measures of Dependence and Probabilities for Joint Distributions," Sociological Methods & Research, , vol. 46(3), pages 604-648, August.
    2. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Luc Bauwens & Nikolaus Hautsch, 2007. "Modelling Financial High Frequency Data Using Point Processes," SFB 649 Discussion Papers SFB649DP2007-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    5. Escribano, Ana & Maggi, Mario, 2019. "Intersectoral default contagion: A multivariate Poisson autoregression analysis," Economic Modelling, Elsevier, vol. 82(C), pages 376-400.
    6. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    7. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2021. "Goodness–of–Fit Tests for Bivariate Time Series of Counts," Econometrics, MDPI, vol. 9(1), pages 1-20, March.
    8. 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).
    9. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    11. Yan Cui & Qi Li & Fukang Zhu, 2020. "Flexible bivariate Poisson integer-valued GARCH model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1449-1477, December.
    12. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.
    13. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Filtering the intensity of public concern from social media count data with jumps," Papers 2012.13267, arXiv.org.
    15. Arianna Agosto & Paolo Giudici, 2023. "Cyber Risk Contagion," Risks, MDPI, vol. 11(9), pages 1-10, September.
    16. Jung, Robert C. & Liesenfeld, Roman & Richard, Jean-François, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 73-85.
    17. Paul Doukhan, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 447-450, September.
    18. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    19. Yang Lu & Christian Gourieroux, 2018. "Negative Binomial Autoregressive Process," Working Papers hal-01730050, HAL.
    20. Fantazzini, Dean, 2020. "Discussing copulas with Sergey Aivazian: a memoir," MPRA Paper 102317, University Library of Munich, Germany.
    21. Gloria Gonzalez-Rivera & Yingying Sun, 2014. "Generalized Autocontours: Evaluation of Multivariate Density Models," Working Papers 201431, University of California at Riverside, Department of Economics.
    22. Popovic, Gordana C. & Hui, Francis K.C. & Warton, David I., 2018. "A general algorithm for covariance modeling of discrete data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 86-100.
    23. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    24. Yan Cui & Fukang Zhu, 2018. "A new bivariate integer-valued GARCH model allowing for negative cross-correlation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 428-452, June.
    25. 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.
    26. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    27. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    28. Christian Gouriéroux & Yang Lu, 2018. "Negative Binomial Autoregressive Process," Working Papers 2018-03, Center for Research in Economics and Statistics.
    29. Robert C. Jung & Roman Liesenfeld & Jean-François Richard, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 73-85, January.
    30. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    31. Eugenio J. Miravete, 2009. "Competing with Menus of Tariff Options," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 188-205, March.
    32. Youngmi Lee & Sangyeol Lee & Dag Tjøstheim, 2018. "Asymptotic normality and parameter change test for bivariate Poisson INGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 52-69, March.
    33. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    34. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.
    35. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
    36. Scotto, Manuel G. & Weiß, Christian H. & Silva, Maria Eduarda & Pereira, Isabel, 2014. "Bivariate binomial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 233-251.
    37. Yicheng Song & Nachiketa Sahoo & Shuba Srinivasan & Chrysanthos Dellarocas, 2022. "Uncovering Characteristic Response Paths of a Population," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1661-1680, May.
    38. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    39. Bracher, Johannes & Held, Leonhard, 2022. "Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1221-1233.

Chapters

  1. Andréas Heinen & Alfonso Valdesogo, 2010. "Dynamic D-Vine Model," World Scientific Book Chapters, in: Dorota Kurowicka & Harry Joe (ed.), Dependence Modeling Vine Copula Handbook, chapter 16, pages 329-353, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. GRIGORIADIS, Vasilis & EMMANOUILIDES, Christos & FOUSEKIS, Panos, 2016. "The Integration Of Pigmeat Markets In The Eu. Evidence From A Regular Mixed Vine Copula," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 19(1), pages 1-10, March.

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