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Ioannis Vrontos

Personal Details

First Name:Ioannis
Middle Name:
Last Name:Vrontos
Suffix:
RePEc Short-ID:pvr10
http://stat-athens.aueb.gr/~vrontos/

Affiliation

Athens University of Economics and Business (AUEB)

Athens, Greece
http://www.aueb.gr/
RePEc:edi:auebugr (more details at EDIRC)

Research output

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Working papers


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Articles

  1. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
  2. P. Dellaportas & I. D. Vrontos, 2007. "Modelling volatility asymmetries: a Bayesian analysis of a class of tree structured multivariate GARCH models," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 503-520, November.
  3. Giamouridis, Daniel & Vrontos, Ioannis D., 2007. "Hedge fund portfolio construction: A comparison of static and dynamic approaches," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 199-217, January.
  4. I. D. Vrontos & P. Dellaportas & D. N. Politis, 2003. "A full-factor multivariate GARCH model," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 312-334, December.
  5. Vrontos, I D & Dellaportas, P & Politis, D N, 2000. "Full Bayesian Inference for GARCH and EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 187-198, April.

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

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Articles

  1. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.

    Cited by:

    1. Stéphane Auray & Aurélien Eyquem & Frédéric Jouneau-Sion, 2014. "Modelling Tails of Aggregated Economic Processes in a Stochastic Growth Model," Post-Print halshs-00995703, HAL.
    2. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    3. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    4. Nomikos, Nikos K. & Pouliasis, Panos K., 2011. "Forecasting petroleum futures markets volatility: The role of regimes and market conditions," Energy Economics, Elsevier, vol. 33(2), pages 321-337, March.
    5. Giannikis, Dimitrios & Vrontos, Ioannis D., 2011. "A Bayesian approach to detecting nonlinear risk exposures in hedge fund strategies," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1399-1414, June.
    6. Yiu‐Kuen Tse & Wai‐Sum Chan, 2010. "The Lead–Lag Relation Between The S&P500 Spot And Futures Markets: An Intraday‐Data Analysis Using A Threshold Regression Model," The Japanese Economic Review, Japanese Economic Association, vol. 61(1), pages 133-144, March.
    7. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    8. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    9. Francq, Christian & ZakoI¨an, Jean-Michel, 2008. "Deriving the autocovariances of powers of Markov-switching GARCH models, with applications to statistical inference," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3027-3046, February.
    10. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.

  2. P. Dellaportas & I. D. Vrontos, 2007. "Modelling volatility asymmetries: a Bayesian analysis of a class of tree structured multivariate GARCH models," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 503-520, November.

    Cited by:

    1. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    2. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    3. Vrontos, Spyridon D. & Vrontos, Ioannis D. & Giamouridis, Daniel, 2008. "Hedge fund pricing and model uncertainty," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 741-753, May.
    4. Burda Martin & Maheu John M., 2013. "Bayesian adaptively updated Hamiltonian Monte Carlo with an application to high-dimensional BEKK GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 345-372, September.
    5. Meligkotsidou, Loukia & Vrontos, Ioannis D. & Vrontos, Spyridon D., 2009. "Quantile regression analysis of hedge fund strategies," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 264-279, March.
    6. Yuzhi Cai, 2021. "Estimating expected shortfall using a quantile function model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4332-4360, July.
    7. Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023. "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers 2308.00913, arXiv.org, revised Oct 2023.
    8. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.
    9. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.

  3. Giamouridis, Daniel & Vrontos, Ioannis D., 2007. "Hedge fund portfolio construction: A comparison of static and dynamic approaches," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 199-217, January.

    Cited by:

    1. Markus Haas, 2018. "A note on the absolute moments of the bivariate normal distribution," Economics Bulletin, AccessEcon, vol. 38(1), pages 650-656.
    2. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    3. Ding, Bill & Shawky, Hany A. & Tian, Jianbo, 2009. "Liquidity shocks, size and the relative performance of hedge fund strategies," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 883-891, May.
    4. Serge Darolles & Jeremy Dudek & Gaëlle Le Fol, 2014. "Liquidity risk and contagion for liquid funds," Post-Print hal-01632776, HAL.
    5. Ricardo Laborda & Ramiro Losada, 2017. "Why is investors'mutual fund market allocation far from the optimum?," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    6. Mei, Bin, 2019. "Timberland investments in the United States: A review and prospects," Forest Policy and Economics, Elsevier, vol. 109(C).
    7. Roumpis, Efthymios & Syriopoulos, Theodore, 2014. "Dynamics and risk factors in hedge funds returns: Implications for portfolio construction and performance evaluation," The Journal of Economic Asymmetries, Elsevier, vol. 11(C), pages 58-77.
    8. Vrontos, Spyridon D. & Vrontos, Ioannis D. & Giamouridis, Daniel, 2008. "Hedge fund pricing and model uncertainty," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 741-753, May.
    9. Meligkotsidou, Loukia & Vrontos, Ioannis D., 2008. "Detecting structural breaks and identifying risk factors in hedge fund returns: A Bayesian approach," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2471-2481, November.
    10. Yao, Haixiang & Huang, Jinbo & Li, Yong & Humphrey, Jacquelyn E., 2021. "A general approach to smooth and convex portfolio optimization using lower partial moments," Journal of Banking & Finance, Elsevier, vol. 129(C).
    11. Andreas Renard Widarto & Harjum Muharam & Sugeng Wahyudi & Irene Rini Demi Pangestuti, 2022. "ASEAN-5 and Crypto Hedge Fund: Dynamic Portfolio Approach," SAGE Open, , vol. 12(2), pages 21582440221, April.
    12. Serge Darolles & Jeremy Dudek & Gaëlle Le Fol, 2012. "Liquidity Contagion. The Emerging Sovereign Debt Markets example," Post-Print hal-01632803, HAL.
    13. Harris, Richard D.F. & Mazibas, Murat, 2013. "Dynamic hedge fund portfolio construction: A semi-parametric approach," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 139-149.
    14. Meligkotsidou, Loukia & Vrontos, Ioannis D. & Vrontos, Spyridon D., 2009. "Quantile regression analysis of hedge fund strategies," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 264-279, March.
    15. Kritski, Oleg & Ulyanova, Marina, 2007. "Assessment of Multivariate Financial Risks of a Stock Share Portfolio," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 8(4), pages 3-17.
    16. Wegener, Christian & von Nitzsch, Rüdiger & Cengiz, Cetin, 2010. "An advanced perspective on the predictability in hedge fund returns," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2694-2708, November.
    17. Wolfgang Karl Härdle & Sergey Nasekin & David Lee Kuo Chuen & Phoon Kok Fai, 2014. "TEDAS - Tail Event Driven ASset Allocation," SFB 649 Discussion Papers SFB649DP2014-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Dudek, Jérémy, 2013. "Illiquidité, contagion et risque systémique," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/13236 edited by Le Fol, Gaëlle.
    19. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    20. Bodnar, Taras & Mazur, Stepan & Podgórski, Krzysztof, 2016. "Singular inverse Wishart distribution and its application to portfolio theory," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 314-326.
    21. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2015. "Regional and global spillovers and diversification opportunities in the GCC equity sectors," Emerging Markets Review, Elsevier, vol. 24(C), pages 160-187.
    22. Spyridon D Vrontos & Ioannis D Vrontos & Loukia Meligkotsidou, 2013. "Asset-liability management for pension funds in a time-varying volatility environment," Journal of Asset Management, Palgrave Macmillan, vol. 14(5), pages 306-333, October.
    23. El Kalak, Izidin & Azevedo, Alcino & Hudson, Robert, 2016. "Reviewing the hedge funds literature I: Hedge funds and hedge funds' managerial characteristics," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 85-97.
    24. Adam, Alexandre & Houkari, Mohamed & Laurent, Jean-Paul, 2008. "Spectral risk measures and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1870-1882, September.
    25. Wan, Yang & Clutter, Michael L. & Mei, Bin & Siry, Jacek P., 2015. "Assessing the role of U.S. timberland assets in a mixed portfolio under the mean-conditional value at risk framework," Forest Policy and Economics, Elsevier, vol. 50(C), pages 118-126.
    26. Wenbo Wu & Jiaqi Chen & Zhibin (Ben) Yang & Michael L. Tindall, 2021. "A Cross-Sectional Machine Learning Approach for Hedge Fund Return Prediction and Selection," Management Science, INFORMS, vol. 67(7), pages 4577-4601, July.
    27. Víctor M. Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, "undated". "Portfolios in the Ibex 35 index: Alternative methods to the traditional framework, a comparative with the naive diversification in a pre- and post- crisis context," Documentos de Trabajo del ICAE 2015-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Jun 2015.
    28. Víctor Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2017. "“Resolution of optimization problems and construction of efficient portfolios: An application to the Euro Stoxx 50 index"," IREA Working Papers 201702, University of Barcelona, Research Institute of Applied Economics, revised Feb 2017.
    29. Harris, Richard D.F. & Mazibas, Murat, 2010. "Dynamic hedge fund portfolio construction," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 351-357, December.
    30. Elyasiani, Elyas & Mansur, Iqbal, 2017. "Hedge fund return, volatility asymmetry, and systemic effects: A higher-moment factor-EGARCH model," Journal of Financial Stability, Elsevier, vol. 28(C), pages 49-65.
    31. Syriopoulos, Theodore & Roumpis, Efthimios, 2009. "Dynamic correlations and volatility effects in the Balkan equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 565-587, October.

  4. I. D. Vrontos & P. Dellaportas & D. N. Politis, 2003. "A full-factor multivariate GARCH model," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 312-334, December.

    Cited by:

    1. Han, Chulwoo & Park, Frank C., 2022. "A geometric framework for covariance dynamics," Journal of Banking & Finance, Elsevier, vol. 134(C).
    2. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Boswijk, H.P. & Weide, R. van der, 2006. "Wake me up before you GO-GARCH," CeNDEF Working Papers 06-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    4. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    5. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    6. Cho, Haeran & Korkas, Karolos K., 2022. "High-dimensional GARCH process segmentation with an application to Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 23(C), pages 187-203.
    7. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    8. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    9. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
    10. Guilherme Valle Moura & João Frois Caldeira & André Santos, 2014. "Seleção De Carteiras Utilizando O Modelofama-French-Carhart," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 117, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    11. Manuel A. Hernandez & Raul Ibarra & Danilo R. Trupkin, 2014. "How far do shocks move across borders? Examining volatility transmission in major agricultural futures markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(2), pages 301-325.
    12. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
    13. Vrontos, Spyridon D. & Vrontos, Ioannis D. & Giamouridis, Daniel, 2008. "Hedge fund pricing and model uncertainty," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 741-753, May.
    14. Vozlyublennaia, Nadia & Meshcheryakov, Artem, 2014. "Dynamic correlation structure and security risk," Journal of Economics and Business, Elsevier, vol. 73(C), pages 48-64.
    15. LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "A Socio-Finance Model: Inference and empirical application," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01215605, HAL.
    17. García de la Fuente, Cristina & Galeano San Miguel, Pedro & Wiper, Michael Peter, 2014. "Bayesian estimation of a dynamic conditional correlation model with multivariate Skew-Slash innovations," DES - Working Papers. Statistics and Econometrics. WS ws141711, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    19. H. J. Turtle & Kainan Wang, 2014. "Modeling Conditional Covariances With Economic Information Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 217-236, April.
    20. Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    21. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    22. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    23. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    24. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    25. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    26. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2020. "Affine multivariate GARCH models," Journal of Banking & Finance, Elsevier, vol. 118(C).
    27. Helmut Lütkepohl & Anton Velinov, 2014. "Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity," SFB 649 Discussion Papers SFB649DP2014-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Jørgen Vitting Andersen & Ioannis D. Vrontos & Petros Dellaportas & Serge Galam, 2015. "A Socio-Finance Model: Inference and empirical application," SciencePo Working papers Main halshs-01242248, HAL.
    29. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "A Socio-Finance Model: Inference and empirical application," SciencePo Working papers Main hal-01215605, HAL.
    30. Duchesne, Pierre, 2006. "Testing for multivariate autoregressive conditional heteroskedasticity using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2142-2163, December.
    31. Meligkotsidou, Loukia & Vrontos, Ioannis D. & Vrontos, Spyridon D., 2009. "Quantile regression analysis of hedge fund strategies," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 264-279, March.
    32. Claudio Morana, 2017. "Semiparametric Estimation of Multivariate GARCH Models," Working Paper series 17-02, Rimini Centre for Economic Analysis.
    33. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    34. Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Working Papers in Economics 11/23, University of Canterbury, Department of Economics and Finance.
    35. Kritski, Oleg & Ulyanova, Marina, 2007. "Assessment of Multivariate Financial Risks of a Stock Share Portfolio," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 8(4), pages 3-17.
    36. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.
    37. So, Mike K.P. & Chan, Thomas W.C. & Chu, Amanda M.Y., 2022. "Efficient estimation of high-dimensional dynamic covariance by risk factor mapping: Applications for financial risk management," Journal of Econometrics, Elsevier, vol. 227(1), pages 151-167.
    38. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    39. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2023. "Covariance dependent kernels, a Q-affine GARCH for multi-asset option pricing," International Review of Financial Analysis, Elsevier, vol. 87(C).
    40. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    41. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    42. Giamouridis, Daniel & Vrontos, Ioannis D., 2007. "Hedge fund portfolio construction: A comparison of static and dynamic approaches," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 199-217, January.
    43. Spyridon D Vrontos & Ioannis D Vrontos & Loukia Meligkotsidou, 2013. "Asset-liability management for pension funds in a time-varying volatility environment," Journal of Asset Management, Palgrave Macmillan, vol. 14(5), pages 306-333, October.
    44. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    45. Kasper Johansson & Mehmet Giray Ogut & Markus Pelger & Thomas Schmelzer & Stephen Boyd, 2023. "A Simple Method for Predicting Covariance Matrices of Financial Returns," Papers 2305.19484, arXiv.org, revised Nov 2023.
    46. K. Diamantopoulos & I. Vrontos, 2010. "A Student-t Full Factor Multivariate GARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 63-83, January.
    47. Helmut Lütkepohl, 2012. "Identifying Structural Vector Autoregressions via Changes in Volatility," Discussion Papers of DIW Berlin 1259, DIW Berlin, German Institute for Economic Research.
    48. Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023. "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers 2308.00913, arXiv.org, revised Oct 2023.
    49. Cody Yu-Ling Hsiao & Weishun Lin & Xinyang Wei & Gaoyun Yan & Siqi Li & Ni Sheng, 2019. "The Impact of International Oil Prices on the Stock Price Fluctuations of China’s Renewable Energy Enterprises," Energies, MDPI, vol. 12(24), pages 1-17, December.
    50. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    51. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2015. "Theoretical Aspects of Modeling of the SVAR [Теоретические Аспекты Моделирования Svar]," Published Papers mak8, Russian Presidential Academy of National Economy and Public Administration.
    52. Lakshina, Valeriya, 2014. "Is it possible to break the «curse of dimensionality»? Spatial specifications of multivariate volatility models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 36(4), pages 61-78.
    53. García-Ferrer, Antonio & González-Prieto, Ester & Peña, Daniel, 2012. "A conditionally heteroskedastic independent factor model with an application to financial stock returns," International Journal of Forecasting, Elsevier, vol. 28(1), pages 70-93.
    54. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    55. Nimitha John & Balakrishna Narayana, 2018. "Cointegration models with non Gaussian GARCH innovations," METRON, Springer;Sapienza Università di Roma, vol. 76(1), pages 83-98, April.
    56. Munir Mahmood & Maxwell L. King, 2016. "On solving bias-corrected non-linear estimation equations with an application to the dynamic linear model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 332-355, November.

  5. Vrontos, I D & Dellaportas, P & Politis, D N, 2000. "Full Bayesian Inference for GARCH and EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 187-198, April.

    Cited by:

    1. Sofia Anyfantaki & Antonis Demos, 2012. "Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model," DEOS Working Papers 1228, Athens University of Economics and Business.
    2. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
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