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Sessi Tokpavi

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. Sessi Tokpavi & Christophe Boucher, 2018. "Stocks and Bonds: Flight-to-Safety for Ever?," EconomiX Working Papers 2018-39, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Yadav, Jayant, 2020. "Flight to Safety in Business cycles," MPRA Paper 104093, University Library of Munich, Germany.

  2. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018, January-A.

  3. Bertrand Caudelon & Sessi Tokpavi, 2014. "A Nonparametric Test for Granger-causality in Distribution with Application to Financial Contagion," EconomiX Working Papers 2014-18, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Chia-Lin Chang & Michael McAleer, 2016. "A Simple Test for Causality in Volatility," Tinbergen Institute Discussion Papers 16-094/III, Tinbergen Institute.
    2. Belkhir, Mohamed & Naceur, Sami Ben & Candelon, Bertrand & Wijnandts, Jean-Charles, 2022. "Macroprudential policies, economic growth and banking crises," Emerging Markets Review, Elsevier, vol. 53(C).
    3. Candelon, Bertrand & Luisi , Angelo & Roccazzella, Francesco, 2022. "Fragmentation in the European Monetary Union: Is it really over?," LIDAM Reprints LFIN 2022001, Université catholique de Louvain, Louvain Finance (LFIN).
    4. Li, Jianping & Li, Jingyu & Zhu, Xiaoqian & Yao, Yinhong & Casu, Barbara, 2020. "Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S," International Review of Financial Analysis, Elsevier, vol. 71(C).
    5. Leong, Soon Heng, 2021. "Global crude oil and the Chinese oil-intensive sectors: A comprehensive causality study," Energy Economics, Elsevier, vol. 103(C).
    6. Salma Gallas & Houssam Bouzgarrou & Montassar Zayati, 2024. "Balancing financial stability and economic growth: a comprehensive analysis of macroprudential regulation," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(4), pages 1005-1033, December.
    7. Dibooglu, Sel & Cevik, Emrah I. & Gillman, Max, 2022. "Gold, silver, and the US dollar as harbingers of financial calm and distress," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 200-210.
    8. Erdoğan, Seyfettin & Gedikli, Ayfer & Çevik, Emrah İsmail & Erdoğan, Fatma & Çevik, Emre, 2022. "Precious metals as safe-haven for clean energy stock investment: Evidence from nonparametric Granger causality in distribution test," Resources Policy, Elsevier, vol. 79(C).
    9. Matteo Farnè & Angela Montanari, 2022. "A Bootstrap Method to Test Granger-Causality in the Frequency Domain," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 935-966, March.
    10. Alexander Mayer & Dominik Wied & Victor Troster, 2024. "Quantile Granger Causality in the Presence of Instability," Papers 2402.09744, arXiv.org, revised Dec 2024.
    11. Emre Cevik & Emrah I Cevik & Sel Dibooglu & Raif Cergibozan & Mehmet Fatih Bugan & Mehmet Akif Destek, 2024. "Connectedness and risk spillovers between crude oil and clean energy stock markets," Energy & Environment, , vol. 35(7), pages 3319-3339, November.
    12. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    13. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2024. "Temporal networks and financial contagion," Journal of Financial Stability, Elsevier, vol. 71(C).
    14. Peng, Cheng & Zhu, Huiming & Guo, Yawei & Chen, Xiuyun, 2018. "Risk spillover of international crude oil to China's firms: Evidence from granger causality across quantile," Energy Economics, Elsevier, vol. 72(C), pages 188-199.
    15. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    16. Meng-Shiuh Chang & Meng-Wei Chen & Peijie Ju, 2023. "Asymmetry in Hedges, Safe Havens, Flights and Contagion: Unconditional Quantile Regression Approach," SAGE Open, , vol. 13(4), pages 21582440231, November.
    17. Zheng, Yingfei & Shen, Anran & Li, Ruihai & Yang, Yuhong & Wang, Shengjin & Cheng, Lee-Young, 2023. "Spillover effects between internet financial industry and traditional financial industry: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    18. Qiao, Xingzhi & Zhu, Huiming & Tang, Yiding & Peng, Cheng, 2023. "Time-frequency extreme risk spillover network of cryptocurrency coins, DeFi tokens and NFTs," Finance Research Letters, Elsevier, vol. 51(C).
    19. Deng, Chao & Li, Shiyu & Hong, Yun, 2024. "When local and foreign investors meet the Chinese government's risk perception about COVID-19," Journal of Multinational Financial Management, Elsevier, vol. 74(C).
    20. Roberto Fuentes M. & Irene Crimaldi & Armando Rungi, 2024. "Non-linear dependence and Granger causality: A vine copula approach," Papers 2409.15070, arXiv.org.
    21. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    22. Gunay, Samet & Altınkeski, Buket Kırcı & Ismail Çevik, Emrah & Goodell, John W., 2023. "Quantifying systemic risk in the cryptocurrency market: A sectoral analysis," Finance Research Letters, Elsevier, vol. 58(PC).
    23. Cevik, Emrah Ismail & Gunay, Samet & Zafar, Muhammad Wasif & Destek, Mehmet Akif & Bugan, Mehmet Fatih & Tuna, Fatih, 2022. "The impact of digital finance on the natural resource market: Evidence from DeFi, oil, and gold," Resources Policy, Elsevier, vol. 79(C).
    24. Kakran, Shubham & Kumari, Vineeta & Bajaj, Parminder Kaur & Sidhu, Arpit, 2024. "Exploring crisis-driven return spillovers in APEC stock markets: A frequency dynamics analysis," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    25. Deng, Chao & Su, Xiaojian & Wang, Gangjin & Peng, Cheng, 2022. "The existence of flight-to-quality under extreme conditions: Evidence from a nonlinear perspective in Chinese stocks and bonds' sectors," Economic Modelling, Elsevier, vol. 113(C).
    26. Kliber, Agata & Łęt, Blanka & Řezáč, Pavel, 2024. "Can a boost in oil prices suspend the evolution of the green transportation market? Relationships between green indices and Brent oil," Energy, Elsevier, vol. 295(C).
    27. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    28. Wu, Fei & Zhang, Dayong & Zhang, Zhiwei, 2019. "Connectedness and risk spillovers in China’s stock market: A sectoral analysis," Economic Systems, Elsevier, vol. 43(3).
    29. Altınkeski, Buket Kırcı & Cevik, Emrah Ismail & Dibooglu, Sel & Kutan, Ali M., 2022. "Financial stress transmission between the U.S. and the Euro Area," Journal of Financial Stability, Elsevier, vol. 60(C).
    30. Duan, Kun & Liu, Yang & Yan, Cheng & Huang, Yingying, 2023. "Differences in carbon risk spillovers with green versus traditional assets: Evidence from a full distributional analysis," Energy Economics, Elsevier, vol. 127(PA).
    31. Yajie Qi & Huajiao Li & Sui Guo & Sida Feng, 2019. "Dynamic Transmission of Correlation between Investor Attention and Stock Price: Evidence from China’s Energy Industry Typical Stocks," Complexity, Hindawi, vol. 2019, pages 1-15, December.
    32. Bei, Zeyun & Lin, Juan & Zhou, Yinggang, 2024. "No safe haven, only diversification and contagion — Intraday evidence around the COVID-19 pandemic," Journal of International Money and Finance, Elsevier, vol. 143(C).
    33. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    34. Bouri, Elie & Gök, Remzi & Gemi̇ci̇, Eray & Kara, Erkan, 2024. "Do geopolitical risk, economic policy uncertainty, and oil implied volatility drive assets across quantiles and time-horizons?," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 137-154.
    35. Sewraj, Deeya & Gebka, Bartosz & Anderson, Robert D.J., 2018. "Identifying contagion: A unifying approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 224-240.
    36. Hong, Yun & Jiang, Yanhui & Su, Xiaojian & Deng, Chao, 2024. "Extreme state media reporting and the extreme stock market during COVID-19: A multi-quantile VaR Granger causality approach in China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    37. Deng, Chao & Zhou, Xiaoying & Peng, Cheng & Zhu, Huiming, 2022. "Going green: Insight from asymmetric risk spillover between investor attention and pro-environmental investment," Finance Research Letters, Elsevier, vol. 47(PA).
    38. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    39. McIver, Ron P. & Kang, Sang Hoon, 2020. "Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 54(C).
    40. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    41. Pacelli, Vincenzo & Miglietta, Federica & Foglia, Matteo, 2022. "The extreme risk connectedness of the new financial system: European evidence," International Review of Financial Analysis, Elsevier, vol. 84(C).

  4. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," EconomiX Working Papers 2012-28, University of Paris Nanterre, EconomiX.

    Cited by:

    1. Kaufmann, Robert K. & Banerjee, Shayan, 2014. "A unified world oil market: Regions in physical, economic, geographic, and political space," Energy Policy, Elsevier, vol. 74(C), pages 235-242.
    2. Marc Joëts, 2013. "Energy price transmissions during extreme movements," Working Papers 2013-28, Department of Research, Ipag Business School.
    3. Kaufmann, Robert K., 2016. "Price differences among crude oils: The private costs of supply disruptions," Energy Economics, Elsevier, vol. 56(C), pages 1-8.
    4. Marc Joëts, 2012. "Energy price transmissions during extreme movements," Working Papers hal-04141047, HAL.

  5. Candelon, B. & Hurlin, C. & Tokpavi, S., 2011. "Sampling error and double shrinkage estimation of minimum variance portfolios," Research Memorandum 002, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. Sarah Perrin & Thierry Roncalli, 2019. "Machine Learning Optimization Algorithms & Portfolio Allocation," Papers 1909.10233, arXiv.org.
    2. Olivier Ledoit & Michael Wolf, 2018. "Robust performance hypothesis testing with smooth functions of population moments," ECON - Working Papers 305, Department of Economics - University of Zurich.
    3. Bertrand Maillet & Sessi Tokpavi & Benoit Vaucher, 2013. "Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach," EconomiX Working Papers 2013-28, University of Paris Nanterre, EconomiX.
    4. Michele Costola & Bertrand Maillet & Zhining Yuan & Xiang Zhang, 2024. "Mean-Variance Efficient Large Portfolios : A Simple Machine Learning Heuristic Technique based on the Two-Fund Separation Theorem," Post-Print hal-04514343, HAL.
    5. Hafner, Christian & Wang, Linqi, 2020. "Dynamic portfolio selection with sector-specific regularization," LIDAM Discussion Papers ISBA 2020032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.
    7. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    8. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    9. Bertrand Maillet & Sessi Tokpavi & Benoit Vaucher, 2013. "Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach," Working Papers hal-04141193, HAL.
    10. Marco Neffelli, 2018. "Target Matrix Estimators in Risk-Based Portfolios," Risks, MDPI, vol. 6(4), pages 1-20, November.
    11. Hafner, Christian M. & Wang, Linqi, 2024. "Dynamic portfolio selection with sector-specific regularization," Econometrics and Statistics, Elsevier, vol. 32(C), pages 17-33.
    12. Thibault Bourgeron & Edmond Lezmi & Thierry Roncalli, 2019. "Robust Asset Allocation for Robo-Advisors," Papers 1902.07449, arXiv.org.
    13. Xing, Xin & Hu, Jinjin & Yang, Yaning, 2014. "Robust minimum variance portfolio with L-infinity constraints," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 107-117.
    14. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    15. Simaan, Majeed & Simaan, Yusif & Tang, Yi, 2018. "Estimation error in mean returns and the mean-variance efficient frontier," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 109-124.
    16. Lassance, Nathan, 2021. "Maximizing the Out-of-Sample Sharpe Ratio," LIDAM Discussion Papers LFIN 2021013, Université catholique de Louvain, Louvain Finance (LFIN).

  6. Borghans, L. & Cörvers, F., 2009. "The Americanization of European higher education and research," Research Memorandum 051, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    2. Asai, M. & McAleer, M.J. & Medeiros, M.C., 2010. "Asymmetry and Long Memory in Volatility Modelling," Econometric Institute Research Papers EI 2010-60, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Dixon, Keith, 2013. "Growth and dispersion of accounting research about New Zealand before and during a National Research Assessment Exercise: Five decades of academic journals bibliometrics," MPRA Paper 51100, University Library of Munich, Germany.
    4. Elena-Ivona DUMITRESCU & Christophe HURLIN & Jaouad MADKOUR, 2011. "Testing Interval Forecasts: A New GMM-based Test," LEO Working Papers / DR LEO 1549, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    5. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Paulo Guimarães & Klaus F. Zimmermann & Ana Rute Cardoso, 2015. "Trends in Economic Research: An International Perspective," Working Papers 463, Barcelona School of Economics.
    7. Elena Ivona Dumitrescu & Christophe Hurlin & Jaouad Madkour, 2013. "Testing Interval Forecasts: a GMM-Based Approach," Post-Print hal-01385898, HAL.
    8. Bertrand-Cloodt, D.A.M. & Cörvers, F. & Heijke, J.A.M., 2014. "Ability, academic climate, and going abroad for work or pursuing a PhD," Research Memorandum 024, Maastricht University, Graduate School of Business and Economics (GSBE).
    9. Thomas Bolli & Mehdi Farsi, 2015. "The dynamics of productivity in Swiss universities," Journal of Productivity Analysis, Springer, vol. 44(1), pages 21-38, August.
    10. Manabu Asai, 2013. "Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 469-480, August.

  7. Christophe Hurlin & Gilbert Colletaz & Sessi Tokpavi & Bertrand Candelon, 2008. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Working Papers halshs-00329495, HAL.

    Cited by:

    1. Asai Manabu & So Mike K.P., 2015. "Long Memory and Asymmetry for Matrix-Exponential Dynamic Correlation Processes," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 69-94, January.
    2. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    3. Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
    4. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.
    5. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    6. Mawuli Segnon & Mark Trede, 2017. "Forecasting Market Risk of Portfolios: Copula-Markov Switching Multifractal Approach," CQE Working Papers 6617, Center for Quantitative Economics (CQE), University of Muenster.
    7. Sullivan Hu'e & Christophe Hurlin & Yang Lu, 2024. "Backtesting Expected Shortfall: Accounting for both duration and severity with bivariate orthogonal polynomials," Papers 2405.02012, arXiv.org, revised May 2024.
    8. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    9. Shelton Peiris & Manabu Asai & Michael McAleer, 2017. "Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models," JRFM, MDPI, vol. 10(4), pages 1-16, December.
    10. Wied, Dominik & Weiß, Gregor N.F. & Ziggel, Daniel, 2016. "Evaluating Value-at-Risk forecasts: A new set of multivariate backtests," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 121-132.
    11. Theo Berger & Christina Uffmann, 2021. "Assessing liquidity‐adjusted risk forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1179-1189, November.
    12. Elena-Ivona DUMITRESCU & Christophe HURLIN & Jaouad MADKOUR, 2011. "Testing Interval Forecasts: A New GMM-based Test," LEO Working Papers / DR LEO 1549, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    13. Christophe Hurlin & Christophe Pérignon, 2012. "Margin Backtesting," Working Papers halshs-00746274, HAL.
    14. Wang, Keli & Liu, Xiaoquan & Ye, Wuyi, 2023. "Intraday VaR: A copula-based approach," Journal of Empirical Finance, Elsevier, vol. 74(C).
    15. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," Post-Print hal-01386081, HAL.
    16. Liu, Shouwei & Tse, Yiu-Kuen, 2015. "Intraday Value-at-Risk: An asymmetric autoregressive conditional duration approach," Journal of Econometrics, Elsevier, vol. 189(2), pages 437-446.
    17. 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.
    18. Samet Günay, 2017. "Value at risk (VaR) analysis for fat tails and long memory in returns," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 215-230, August.
    19. Emese Lazar & Ning Zhang, 2017. "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance icma-dp2017-10, Henley Business School, University of Reading.
    20. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    21. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    22. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. 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.
    24. Marta Małecka & Radosław Pietrzyk, 2024. "A spectral approach to evaluating VaR forecasts: stock market evidence from the subprime mortgage crisis, through COVID-19, to the Russo–Ukrainian war," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4533-4567, October.
    25. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    26. 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.
    27. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    28. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    29. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    30. Bontemps, Christian, 2014. "Simple moment-based tests for value-at-risk models and discrete distribution," TSE Working Papers 14-535, Toulouse School of Economics (TSE).
    31. Song, Yuping & Huang, Jiefei & Zhang, Qichao & Xu, Yang, 2024. "Heterogeneity effect of positive and negative jumps on the realized volatility: Evidence from China," Economic Modelling, Elsevier, vol. 136(C).
    32. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
    33. Slim, Skander & Dahmene, Meriam & Boughrara, Adel, 2020. "How informative are variance risk premium and implied volatility for Value-at-Risk prediction? International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 22-37.
    34. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    35. Elena Ivona Dumitrescu & Christophe Hurlin & Jaouad Madkour, 2013. "Testing Interval Forecasts: a GMM-Based Approach," Post-Print hal-01385898, HAL.
    36. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2019. "Range-based DCC models for covariance and value-at-risk forecasting," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 58-76.
    37. Nikola Radivojevic & Milena Cvjetkovic & Saša Stepanov, 2016. "The new hybrid value at risk approach based on the extreme value theory," Estudios de Economia, University of Chile, Department of Economics, vol. 43(1 Year 20), pages 29-52, June.
    38. Powell, Robert J. & Vo, Duc H. & Pham, Thach N. & Singh, Abhay K., 2017. "The long and short of commodity tails and their relationship to Asian equity markets," Journal of Asian Economics, Elsevier, vol. 52(C), pages 32-44.
    39. Ludwig, Alexander, 2014. "A unified approach to investigate pure and wake-up-call contagion: Evidence from the Eurozone's first financial crisis," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 125-146.
    40. Christian Bontemps, 2019. "Moment-Based Tests under Parameter Uncertainty," Post-Print hal-02004687, HAL.
    41. El Bouhadi, Abdelhamid & Achibane, Khalid, 2009. "The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?," MPRA Paper 19482, University Library of Munich, Germany.
    42. Walther, Thomas & Klein, Tony & Thu, Hien Pham & Piontek, Krzysztof, 2017. "True or spurious long memory in European non-EMU currencies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 217-230.
    43. Manabu Asai, 2013. "Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 469-480, August.
    44. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    45. D. Th. Vezeris & C. J. Schinas & Th. S. Kyrgos & V. A. Bizergianidou & I. P. Karkanis, 2020. "Optimization of Backtesting Techniques in Automated High Frequency Trading Systems Using the d-Backtest PS Method," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 975-1054, December.
    46. Bontemps, Christian, 2013. "Moment-Based Tests for Discrete Distributions," IDEI Working Papers 772, Institut d'Économie Industrielle (IDEI), Toulouse, revised Oct 2014.
    47. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    48. Małecka Marta, 2021. "Testing for a serial correlation in VaR failures through the exponential autoregressive conditional duration model," Statistics in Transition New Series, Statistics Poland, vol. 22(1), pages 145-162, March.
    49. Krämer, Walter & Wied, Dominik, 2015. "A simple and focused backtest of value at risk," Economics Letters, Elsevier, vol. 137(C), pages 29-31.
    50. Yannick Hoga & Matei Demetrescu, 2023. "Monitoring Value-at-Risk and Expected Shortfall Forecasts," Management Science, INFORMS, vol. 69(5), pages 2954-2971, May.
    51. Araújo Santos, P. & Fraga Alves, M.I., 2012. "A new class of independence tests for interval forecasts evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3366-3380.
    52. Thor Pajhede, 2015. "Backtesting Value-at-Risk: A Generalized Markov Framework," Discussion Papers 15-18, University of Copenhagen. Department of Economics.
    53. Ziggel, Daniel & Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2014. "A new set of improved Value-at-Risk backtests," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 29-41.
    54. Leccadito, Arturo & Boffelli, Simona & Urga, Giovanni, 2014. "Evaluating the accuracy of value-at-risk forecasts: New multilevel tests," International Journal of Forecasting, Elsevier, vol. 30(2), pages 206-216.
    55. Evers, Corinna & Rohde, Johannes, 2014. "Model Risk in Backtesting Risk Measures," Hannover Economic Papers (HEP) dp-529, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    56. Rachida Hennani, 2015. "Can the Lasota(1977)’s model compete with the Mackey-Glass(1977)’s model in nonlinear modelling of financial time series?," Working Papers 15-09, LAMETA, Universtiy of Montpellier, revised Jun 2015.
    57. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    58. Guoli Mo & Chunzhi Tan & Weiguo Zhang & Xuezeng Yu, 2023. "Dynamic spatiotemporal correlation coefficient based on adaptive weight," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-43, December.
    59. Ludwig, Alexander, 2013. "Sovereign risk contagion in the Eurozone: A time-varying coefficient approach," Dresden Discussion Paper Series in Economics 02/13, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    60. Metiu, Norbert, 2012. "Sovereign risk contagion in the Eurozone," Economics Letters, Elsevier, vol. 117(1), pages 35-38.
    61. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    62. Ahmed BenSaïda & Sabri Boubaker & Duc Khuong Nguyen & Skander Slim, 2018. "Value‐at‐risk under market shifts through highly flexible models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(8), pages 790-804, December.

  8. Christophe Hurlin & Sessi Tokpavi, 2007. "Une Evaluation des Procédures de Backtesting," Working Papers halshs-00159846, HAL.

    Cited by:

    1. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    2. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
    4. Jean-François Carpantier & Arnaud Dufays, 2012. "Commodities volatility and the theory of storage," Working Papers hal-01821149, HAL.
    5. El Bouhadi, Abdelhamid & Achibane, Khalid, 2009. "The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?," MPRA Paper 19482, University Library of Munich, Germany.

  9. Christophe Hurlin & Gilbert Colletaz & Sessi Tokpavi, 2007. "Irregularly Spaced Intraday Value at Risk (ISIVaR) Models : Forecasting and Predictive Abilities," Working Papers halshs-00162440, HAL.

    Cited by:

    1. Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.

  10. Christophe Hurlin & Sessi Tokpavi, 2006. "Backtesting VaR Accuracy: A New Simple Test," Working Papers halshs-00068384, HAL.

    Cited by:

    1. Herwartz, Helmut, 2009. "Exact inference in diagnosing Value-at-Risk estimates -- A Monte Carlo device," Economics Letters, Elsevier, vol. 103(3), pages 160-162, June.
    2. Sajjad Rasoul & Coakley Jerry & Nankervis John C, 2008. "Markov-Switching GARCH Modelling of Value-at-Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-31, September.
    3. Herwartz, Helmut, 2008. "Exact inference in diagnosing value-at-risk estimates: A Monte Carlo device," Economics Working Papers 2008-16, Christian-Albrechts-University of Kiel, Department of Economics.

  11. Christophe HURLIN & Sessi TOKPAVI, 2006. "Backtesting VaR Accuracy: A Simple and Powerful Test," LEO Working Papers / DR LEO 268, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.

    Cited by:

    1. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.

Articles

  1. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.

    Cited by:

    1. Ki-Hong Choi & Ron P. McIver & Salvatore Ferraro & Lei Xu & Sang Hoon Kang, 2021. "Dynamic volatility spillover and network connectedness across ASX sector markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 677-691, October.
    2. Laleh Tafakori & Armin Pourkhanali & Riccardo Rastelli, 2022. "Measuring systemic risk and contagion in the European financial network," Empirical Economics, Springer, vol. 63(1), pages 345-389, July.
    3. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost, Tomáš, 2020. "Increasing systemic risk during the Covid-19 pandemic: A cross-quantilogram analysis of the banking sector," EconStor Preprints 222580, ZBW - Leibniz Information Centre for Economics.
    4. Andrieş, Alin Marius & Ongena, Steven & Sprincean, Nicu & Tunaru, Radu, 2022. "Risk spillovers and interconnectedness between systemically important institutions," Journal of Financial Stability, Elsevier, vol. 58(C).
    5. Ouyang, Zisheng & Zhou, Xuewei & Wang, Gang-jin & Liu, Shuwen & Lu, Min, 2024. "Multilayer networks in the frequency domain: Measuring volatility connectedness among Chinese financial institutions," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 909-928.
    6. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Interconnected networks: Measuring extreme risk connectedness between China’s financial sector and real estate sector," International Review of Financial Analysis, Elsevier, vol. 90(C).
    7. Denisa Banulescu & Christophe Hurlin & Jeremy Leymarie & O. Scaillet, 2019. "Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures," Swiss Finance Institute Research Paper Series 19-48, Swiss Finance Institute.
    8. Ouyang, Zisheng & Zhou, Xuewei & Lu, Min & Liu, Ke, 2024. "Imported financial risk in global stock markets: Evidence from the interconnected network," Research in International Business and Finance, Elsevier, vol. 69(C).
    9. Kumar, Sudarshan & Bansal, Avijit & Chakrabarti, Anindya S., 2019. "Ripples on financial networks," IIMA Working Papers WP 2019-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    10. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    11. Jean-Baptiste Hasse, 2020. "Systemic Risk: a Network Approach," AMSE Working Papers 2025, Aix-Marseille School of Economics, France.
    12. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
    13. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
    14. Pham, Thach N. & Powell, Robert & Bannigidadmath, Deepa, 2024. "Tail risk network analysis of Asian banks," Global Finance Journal, Elsevier, vol. 62(C).
    15. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions," Research in International Business and Finance, Elsevier, vol. 65(C).
    16. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    17. Lilit Popoyan & Mauro Napoletano & Andrea Roventini, 2023. "Systemically important banks - emerging risk and policy responses: An agent-based investigation," LEM Papers Series 2023/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    18. Sudarshan Kumar & Tiziana Di Matteo & Anindya S. Chakrabarti, 2020. "Disentangling shock diffusion on complex networks: Identification through graph planarity," Papers 2001.01518, arXiv.org.
    19. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    20. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost,Tomáš, 2020. "From physical to financial contagion: the COVID-19 pandemic and increasing systemic risk among banks," EconStor Preprints 218944, ZBW - Leibniz Information Centre for Economics.
    21. Deyan Radev, 2024. "Dynamic Measures of Sovereign Systemic Risk," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 3-24.
    22. Narayan, Shivani & Kumar, Dilip & Bouri, Elie, 2023. "Systemically important financial institutions and drivers of systemic risk: Evidence from India," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    23. Wu, Baohui & Zhu, Pingheng & Yin, Hua & Wen, Fenghua, 2023. "The risk spillover of high carbon enterprises in China: Evidence from the stock market," Energy Economics, Elsevier, vol. 126(C).

  2. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    See citations under working paper version above.
  3. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.

    Cited by:

    1. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2018. "Estimation of the global minimum variance portfolio in high dimensions," European Journal of Operational Research, Elsevier, vol. 266(1), pages 371-390.
    2. Ding, Wenliang & Shu, Lianjie & Gu, Xinhua, 2023. "A robust Glasso approach to portfolio selection in high dimensions," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 22-37.
    3. Francisco Fernández-Navarro & Luisa Martínez-Nieto & Mariano Carbonero-Ruz & Teresa Montero-Romero, 2021. "Mean Squared Variance Portfolio: A Mixed-Integer Linear Programming Formulation," Mathematics, MDPI, vol. 9(3), pages 1-13, January.
    4. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    5. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Harmful Diversification: Evidence from Alternative Investments," ICMA Centre Discussion Papers in Finance icma-dp2017-09, Henley Business School, University of Reading.
    6. Hongxin Zhao & Lingchen Kong & Hou-Duo Qi, 2021. "Optimal portfolio selections via $$\ell _{1, 2}$$ ℓ 1 , 2 -norm regularization," Computational Optimization and Applications, Springer, vol. 80(3), pages 853-881, December.
    7. Chiu, Wan-Yi & Jiang, Ching-Hai, 2016. "On the weight sign of the global minimum variance portfolio," Finance Research Letters, Elsevier, vol. 19(C), pages 241-246.
    8. Bonaccolto, Giovanni & Caporin, Massimiliano & Maillet, Bertrand B., 2022. "Dynamic large financial networks via conditional expected shortfalls," European Journal of Operational Research, Elsevier, vol. 298(1), pages 322-336.
    9. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    10. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    11. 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.
    12. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    13. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    14. Eric Andr'e & Guillaume Coqueret, 2020. "Dirichlet policies for reinforced factor portfolios," Papers 2011.05381, arXiv.org, revised Jun 2021.
    15. Mörstedt, Torsten & Lutz, Bernhard & Neumann, Dirk, 2024. "Cross validation based transfer learning for cross-sectional non-linear shrinkage: A data-driven approach in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 318(2), pages 670-685.
    16. Philippe Bertrand & Vincent Lapointe, 2018. "Risk-based strategies: the social responsibility of investment universes does matter," Post-Print hal-01833080, HAL.
    17. Melk C. Bucher, 2020. "Conditional currency hedging," Financial Management, Financial Management Association International, vol. 49(4), pages 897-923, December.
    18. Conlon, Thomas & Cotter, John & Gençay, Ramazan, 2018. "Long-run wavelet-based correlation for financial time series," European Journal of Operational Research, Elsevier, vol. 271(2), pages 676-696.
    19. Xidonas, Panos & Hassapis, Christis & Soulis, John & Samitas, Aristeidis, 2017. "Robust minimum variance portfolio optimization modelling under scenario uncertainty," Economic Modelling, Elsevier, vol. 64(C), pages 60-71.
    20. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    21. Luigi Grossi & Fabrizio Laurini, 2020. "Robust asset allocation with conditional value at risk using the forward search," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(3), pages 335-352, May.
    22. Theo Berger & Ramazan Gençay, 2020. "Short‐run wavelet‐based covariance regimes for applied portfolio management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 642-660, July.
    23. Sandra Caçador & Joana Matos Dias & Pedro Godinho, 2020. "Global minimum variance portfolios under uncertainty: a robust optimization approach," Journal of Global Optimization, Springer, vol. 76(2), pages 267-293, February.
    24. Emmanouil Platanakis & Athanasios Sakkas & Charles Sutcliffe, 2017. "Should Portfolio Model Inputs Be Estimated Using One or Two Economic Regimes?," ICMA Centre Discussion Papers in Finance icma-dp2017-07, Henley Business School, University of Reading.
    25. 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.
    26. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    27. Mazin A.M. Al Janabi, 2021. "Is optimum always optimal? A revisit of the mean‐variance method under nonlinear measures of dependence and non‐normal liquidity constraints," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 387-415, April.
    28. Balbás, Alejandro & Balbás, Beatriz & Balbás, Raquel, 2016. "Good deals and benchmarks in robust portfolio selection," European Journal of Operational Research, Elsevier, vol. 250(2), pages 666-678.
    29. Xidonas, Panos & Mavrotas, George & Hassapis, Christis & Zopounidis, Constantin, 2017. "Robust multiobjective portfolio optimization: A minimax regret approach," European Journal of Operational Research, Elsevier, vol. 262(1), pages 299-305.
    30. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.

  4. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.

    Cited by:

    1. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Time-varying energy and stock market integration in Asia," Energy Economics, Elsevier, vol. 80(C), pages 777-792.
    2. Mobeen Ur Rehman, 2020. "Dynamic correlation pattern amongst alternative energy market for diversification opportunities," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-24, December.
    3. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    4. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    5. Mensi, Walid & Brahim, Mariem & Hammoudeh, Shawkat & Tiwari, Aviral Kumar & Kang, Sang Hoon, 2024. "Time-varying causality and correlations between spot and futures prices of natural gas, crude oil, heating oil, and gasoline," Resources Policy, Elsevier, vol. 93(C).
    6. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2017. "Can stock market investors hedge energy risk? Evidence from Asia," Energy Economics, Elsevier, vol. 66(C), pages 559-570.
    7. Soylu, Pınar Kaya & Güloğlu, Bülent, 2019. "Financial contagion and flight to quality between emerging markets and U.S. bond market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    8. Storhas, Dominik P. & De Mello, Lurion & Singh, Abhay Kumar, 2020. "Multiscale lead-lag relationships in oil and refined product return dynamics: A symbolic wavelet transfer entropy approach," Energy Economics, Elsevier, vol. 92(C).
    9. Marc Joëts, 2013. "Energy price transmissions during extreme movements," Working Papers 2013-28, Department of Research, Ipag Business School.
    10. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    11. Song, Yu & Chen, Bo & Hou, Na & Yang, Yi, 2022. "Terrorist attacks and oil prices: A time-varying causal relationship analysis," Energy, Elsevier, vol. 246(C).
    12. Xi, Yue & Zeng, Qing & Lu, Xinjie & Huynh, Toan L.D., 2022. "Oil and renewable energy stock markets: Unique role of extreme shocks," Energy Economics, Elsevier, vol. 109(C).
    13. Kuck, Konstantin & Schweikert, Karsten, 2017. "A Markov regime-switching model of crude oil market integration," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 16-31.
    14. Marcin Faldzinski & Magdalena Osinska, 2016. "Volatility estimators in econometric analysis of risk transfer on capital markets," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 16, pages 21-35.
    15. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    16. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2024. "Volatility spillovers across the spot and futures oil markets after news announcements," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    17. Wang, Lu & Ma, Feng & Niu, Tianjiao & He, Chengting, 2020. "Crude oil and BRICS stock markets under extreme shocks: New evidence," Economic Modelling, Elsevier, vol. 86(C), pages 54-68.
    18. Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Wang, Lijun, 2017. "Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective," Applied Energy, Elsevier, vol. 185(P2), pages 1788-1798.
    19. Mohamed Albaity & Hasan Mustafa, 2018. "International and Macroeconomic Determinants of Oil Price: Evidence from Gulf Cooperation Council Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(1), pages 69-81.
    20. Koch, Nicolas, 2014. "Tail events: A new approach to understanding extreme energy commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 195-205.
    21. Miroslava Zavadska & Lucía Morales & Joseph Coughlan, 2018. "The Lead–Lag Relationship between Oil Futures and Spot Prices—A Literature Review," IJFS, MDPI, vol. 6(4), pages 1-22, October.

  5. Candelon, B. & Hurlin, C. & Tokpavi, S., 2012. "Sampling error and double shrinkage estimation of minimum variance portfolios," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
    See citations under working paper version above.
  6. Bertrand Candelon & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2011. "Backtesting Value-at-Risk: A GMM Duration-Based Test," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 314-343, Spring.
    See citations under working paper version above.
  7. Christophe Hurlin & Sessi Tokpavi, 2008. "Une évaluation des procédures de Backtesting. « Tout va pour le mieux dans le meilleur des mondes »," Finance, Presses universitaires de Grenoble, vol. 29(1), pages 53-80.

    Cited by:

    1. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    2. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
    3. El Bouhadi, Abdelhamid & Achibane, Khalid, 2009. "The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?," MPRA Paper 19482, University Library of Munich, Germany.

  8. Christophe Hurlin & Sessi Tokpavi, 2007. "Un test de validité de la Value at Risk," Revue économique, Presses de Sciences-Po, vol. 58(3), pages 599-608.

    Cited by:

    1. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    2. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.

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