IDEAS home Printed from https://ideas.repec.org/f/pbo842.html
   My authors  Follow this author

Eric Bouyé
(Eric Bouye)

Personal Details

First Name:Eric
Middle Name:
Last Name:Bouye
Suffix:
RePEc Short-ID:pbo842
[This author has chosen not to make the email address public]

Affiliation

World Bank Group

Washington, District of Columbia (United States)
http://www.worldbank.org/
RePEc:edi:wrldbus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Bouye, Eric & Durlleman, Valdo & Nikeghbali, Ashkan & Riboulet, Gaël & Roncalli, Thierry, 2000. "Copulas for finance," MPRA Paper 37359, University Library of Munich, Germany.

Articles

  1. Eric Bouye & Mark Salmon, 2009. "Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 721-750.

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. Bouye, Eric & Durlleman, Valdo & Nikeghbali, Ashkan & Riboulet, Gaël & Roncalli, Thierry, 2000. "Copulas for finance," MPRA Paper 37359, University Library of Munich, Germany.

    Cited by:

    1. MICHIELS, Frederik & DE SCHEPPER, Ann, 2007. "A copula test space model: How to avoid the wrong copula choice," Working Papers 2007027, University of Antwerp, Faculty of Business and Economics.
    2. Bedendo, Mascia & Campolongo, Francesca & Joossens, Elisabeth & Saita, Francesco, 2010. "Pricing multiasset equity options: How relevant is the dependence function?," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 788-801, April.
    3. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Joshua V. Rosenberg, 2003. "Nonparametric pricing of multivariate contingent claims," Staff Reports 162, Federal Reserve Bank of New York.
    5. Zhichao Zhang & Li Ding & Fan Zhang & Zhuang Zhang, 2015. "Optimal Currency Composition for China's Foreign Reserves: A Copula Approach," The World Economy, Wiley Blackwell, vol. 38(12), pages 1947-1965, December.
    6. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    7. Beatriz Vaz de Melo Mendes & Cecília Aíube, 2011. "Copula based models for serial dependence," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 7(1), pages 68-82, February.
    8. Kole, H.J.W.G. & Koedijk, C.G. & Verbeek, M.J.C.M., 2003. "Stress Testing with Student's t Dependence," ERIM Report Series Research in Management ERS-2003-056-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.
    9. Michal Kaut & Stein Wallace, 2011. "Shape-based scenario generation using copulas," Computational Management Science, Springer, vol. 8(1), pages 181-199, April.
    10. Domino, Krzysztof & Błachowicz, Tomasz, 2014. "The use of copula functions for modeling the risk of investment in shares traded on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 77-85.
    11. Szego, Giorgio, 2002. "Measures of risk," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1253-1272, July.
    12. Cooper, Joseph & Delbecq, Benoit, 2014. "A Multi-Region Approach to Assessing Fiscal and Farm Level Consequences of Government Support for Farm Risk Management," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173108, Italian Association of Agricultural and Applied Economics (AIEAA).
    13. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," NBER Technical Working Papers 0331, National Bureau of Economic Research, Inc.
    14. Artem Prokhorov & Peter Schmidt, 2009. "Likelihood Based Estimation in a Panel Setting: Robustness, Redundancy and Validity of Copulas," Working Papers 09002, Concordia University, Department of Economics.
    15. Xisong Jin & Francisco Nadal De Simone, 2013. "Banking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach," BCL working papers 82, Central Bank of Luxembourg.
    16. Giacomini, Enzo & Härdle, Wolfgang & Spokoiny, Vladimir, 2009. "Inhomogeneous Dependence Modeling with Time-Varying Copulae," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 224-234.
    17. Huard, David & Evin, Guillaume & Favre, Anne-Catherine, 2006. "Bayesian copula selection," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 809-822, November.
    18. Long Kang, 2011. "Asset allocation in a Bayesian copula-GARCH framework: An application to the ‘passive funds versus active funds’ problem," Journal of Asset Management, Palgrave Macmillan, vol. 12(1), pages 45-66, April.
    19. Xisong Jin & Francisco Nadal De Simone, 2017. "Systemic Financial Sector and Sovereign Risks," BCL working papers 109, Central Bank of Luxembourg.
    20. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    21. Zhu, Xiaoqian & Xie, Yongjia & Li, Jianping & Wu, Dengsheng, 2015. "Change point detection for subprime crisis in American banking: From the perspective of risk dependence," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 18-28.
    22. Yuri Salazar & Wing Ng, 2015. "Nonparametric estimation of general multivariate tail dependence and applications to financial time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(1), pages 121-158, March.
    23. Vaz de Melo Mendes, Beatriz & Martins de Souza, Rafael, 2004. "Measuring financial risks with copulas," International Review of Financial Analysis, Elsevier, vol. 13(1), pages 27-45.
    24. Yanqin Fan & Xiaohong Chen & Andrew Patton, 2004. "(IAM Series No 003) Simple Tests for Models of Dependence Between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates," FMG Discussion Papers dp483, Financial Markets Group.
    25. José M. R. Murteira & Óscar D. Lourenço, 2007. "Health Care Utilization and Self-Assessed Health Specification of Bivariate Models Using Copulas," Health, Econometrics and Data Group (HEDG) Working Papers 07/27, HEDG, c/o Department of Economics, University of York.
    26. Boubaker, Heni & Sghaier, Nadia, 2013. "Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 361-377.
    27. Fathi, Abid & Nader, Naifar, 2007. "Price Calibration of basket default swap: Evidence from Japanese market," MPRA Paper 6013, University Library of Munich, Germany.
    28. 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.
    29. Zhang, Ming-Heng, 2008. "Modelling total tail dependence along diagonals," Insurance: Mathematics and Economics, Elsevier, vol. 42(1), pages 73-80, February.
    30. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data," Papers 1307.5981, arXiv.org, revised Feb 2015.
    31. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
    32. Michal Kaut, 2014. "A copula-based heuristic for scenario generation," Computational Management Science, Springer, vol. 11(4), pages 503-516, October.
    33. Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Automated Variable Selection in Vector Multiplicative Error Models," Econometrics Working Papers Archive wp2009_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    34. Panchenko, Valentyn, 2005. "Goodness-of-fit test for copulas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 176-182.
    35. Fantazzini, Dean, 2010. "Three-stage semi-parametric estimation of T-copulas: Asymptotics, finite-sample properties and computational aspects," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2562-2579, November.
    36. Henryk Gurgul & Roland Mestel & Robert Syrek, 2008. "Polish Stock Market and some foreign markets - dependence analysis by copulas," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 18(2), pages 17-35.
    37. Abel Elizalde, 2006. "Credit Risk Models I: Default Correlation in Intensity Models," Working Papers wp2006_0605, CEMFI.
    38. Zhang, Chen & Yang, Yu & Yun, Po, 2020. "Risk measurement of international carbon market based on multiple risk factors heterogeneous dependence," Finance Research Letters, Elsevier, vol. 32(C).
    39. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    40. Xisong Jin & Francisco Nadal De Simone, 2016. "Tracking Changes in the Intensity of Financial Sector's Systemic Risk," BCL working papers 102, Central Bank of Luxembourg.
    41. Param Silvapulle & Gunky Kim & Mervyn J. Silvapulle, 2004. "Robustness of a semiparametric estimator of a copula," Econometric Society 2004 Australasian Meetings 317, Econometric Society.
    42. Song, Zhe & Zhang, Zijun & Jiang, Yu & Zhu, Jin, 2018. "Wind turbine health state monitoring based on a Bayesian data-driven approach," Renewable Energy, Elsevier, vol. 125(C), pages 172-181.
    43. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula–Based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics, MDPI, vol. 5(2), pages 1-24, April.
    44. Cossette, Hélène & Marceau, Etienne & Marri, Fouad, 2008. "On the compound Poisson risk model with dependence based on a generalized Farlie-Gumbel-Morgenstern copula," Insurance: Mathematics and Economics, Elsevier, vol. 43(3), pages 444-455, December.
    45. Cooper, Joseph & Hungerford, Ashley & O'Donoghue, Erik, 2015. "Interactions of Shallow Loss Support and Traditional Federal Crop Insurance: Building a Framework for Assessing Commodity Support Issues for the Next Farm Act," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205310, Agricultural and Applied Economics Association.
    46. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "To the problem of evaluation of market risk of global equity index portfolio in global capital markets," MPRA Paper 47708, University Library of Munich, Germany, revised 20 Jun 2013.
    47. Chen, Xiaohong & Fan, Yanqin & Patton, Andrew J., 2004. "Simple tests for models of dependence between multiple financial time series, with applications to U.S. equity returns and exchange rates," LSE Research Online Documents on Economics 24681, London School of Economics and Political Science, LSE Library.
    48. Damiano Brigo & Kyriakos Chourdakis, 2012. "Consistent single- and multi-step sampling of multivariate arrival times: A characterization of self-chaining copulas," Papers 1204.2090, arXiv.org, revised Apr 2012.
    49. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    50. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 22(2), pages 98-134.
    51. Lan-Ya Ma & Zi-Yu Li, 2017. "Research on the Effect of Chinese Margin Trading on Market Risk: Based on GJR Model and Filtered Historical Simulation," Applied Economics and Finance, Redfame publishing, vol. 4(4), pages 84-93, July.
    52. Yan, Jun, 2007. "Enjoy the Joy of Copulas: With a Package copula," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i04).
    53. Hurlimann, Werner, 2004. "Fitting bivariate cumulative returns with copulas," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 355-372, March.
    54. Evis Këllezi & Nick Webber, 2004. "Valuing Bermudan options when asset returns are Levy processes," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 87-100.
    55. Cumming, Fergus & Noss, Joseph, 2013. "Financial Stability Paper No 26: Assessing the adequacy of CCPs' default resources," Bank of England Financial Stability Papers 26, Bank of England.
    56. Jadran Dobric & Friedrich Schmid, 2005. "Nonparametric estimation of the lower tail dependence λL in bivariate copulas," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(4), pages 387-407.
    57. Penikas, Henry, 2011. "Copula-Based Price Risk Hedging Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 22(2), pages 3-21.
    58. Sukcharoen, Kunlapath & Zohrabyan, Tatevik & Leatham, David & Wu, Ximing, 2014. "Interdependence of oil prices and stock market indices: A copula approach," Energy Economics, Elsevier, vol. 44(C), pages 331-339.
    59. Alejandro García & Ramazan Gençay, 2007. "Managing Adverse Dependence for Portfolios of Collateral in Financial Infrastructures," Staff Working Papers 07-25, Bank of Canada.
    60. Alexandru Stanga, 2008. "Measuring market risk: a copula and extreme value approach," Advances in Economic and Financial Research - DOFIN Working Paper Series 13, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
    61. Patton, Andrew J, 2001. "Estimation of Copula Models for Time Series of Possibly Different Length," University of California at San Diego, Economics Working Paper Series qt3fc1c8hw, Department of Economics, UC San Diego.

Articles

  1. Eric Bouye & Mark Salmon, 2009. "Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 721-750.

    Cited by:

    1. Tae-Hwy Lee & Weiping Yang, 2014. "Granger-Causality in Quantiles between Financial Markets: Using Copula Approach," Working Papers 201406, University of California at Riverside, Department of Economics.
    2. Wang, Bo & Xiao, Yang, 2023. "Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    3. Beare, Brendan K., 2012. "Archimedean Copulas And Temporal Dependence," Econometric Theory, Cambridge University Press, vol. 28(6), pages 1165-1185, December.
    4. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    5. Khalid Almeshal & Nader Naifar, 2016. "A quantile regression approach and nonlinear analysis with Archimedean copulas to explain the movements of residential real estate prices," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 6(4), pages 374-395.
    6. Kraus, Daniel & Czado, Claudia, 2017. "D-vine copula based quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 1-18.
    7. Beare, Brendan K. & Seo, Juwon, 2014. "Time Irreversible Copula-Based Markov Models," Econometric Theory, Cambridge University Press, vol. 30(5), pages 923-960, October.
    8. Sim, Nicholas, 2016. "Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 31-45.
    9. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
    10. Tian, Maoxi & Ji, Hao, 2022. "GARCH copula quantile regression model for risk spillover analysis," Finance Research Letters, Elsevier, vol. 44(C).
    11. Chang, Bo & Joe, Harry, 2019. "Prediction based on conditional distributions of vine copulas," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 45-63.
    12. M. Mesfioui & T. Bouezmarni & M. Belalia, 2023. "Copula-based link functions in binary regression models," Statistical Papers, Springer, vol. 64(2), pages 557-585, April.
    13. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    14. David E. Allen & Abhay K. Singh & Robert J. Powell & Michael McAleer & James Taylor & Lyn Thomas, 2013. "Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression," Tinbergen Institute Discussion Papers 13-020/III, Tinbergen Institute.
    15. Terence D. Agbeyegbe, 2015. "An inverted U‐shaped crude oil price return‐implied volatility relationship," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 28-45, November.
    16. Reboredo, Juan C. & Ugolini, Andrea, 2016. "Quantile dependence of oil price movements and stock returns," Energy Economics, Elsevier, vol. 54(C), pages 33-49.
    17. Rémillard, Bruno & Nasri, Bouchra & Bouezmarni, Taoufik, 2017. "On copula-based conditional quantile estimators," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 14-20.
    18. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    19. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    20. David E Allen & Abhay K Singh & Robert J Powell & Michael McAleer & James Taylor & Lyn Thomas, 2012. "The Volatility-Return Relationship:Insights from Linear and Non-Linear Quantile Regressions," KIER Working Papers 831, Kyoto University, Institute of Economic Research.
    21. Walid Mensi & Debasish Maitra & Refk Selmi & Xuan Vinh Vo, 2023. "Extreme dependencies and spillovers between gold and stock markets: evidence from MENA countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    22. Avdulaj Krenar & Barunik Jozef, 2017. "A semiparametric nonlinear quantile regression model for financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 81-97, February.
    23. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    24. Yanqin Fan & Xiaohong Chen, 2004. "Estimation of Copula-Based Semiparametric Time Series Models," Econometric Society 2004 Far Eastern Meetings 559, Econometric Society.
    25. Giovanni De Luca & Giorgia Rivieccio & Paola Zuccolotto, 2010. "Combining random forest and copula functions: A heuristic approach for selecting assets from a financial crisis perspective," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(2), pages 91-109, April.
    26. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    27. Limin Wu, 2020. "Tuning the Bivariate Meta-Gaussian Distribution Conditionally in Quantifying Precipitation Prediction Uncertainty," Forecasting, MDPI, vol. 2(1), pages 1-19, January.
    28. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    29. Shanglei Chai, 2015. "Dependence Structure and Hedging of U.S. Spot and Futures Markets in Financial Crisis," Accounting and Finance Research, Sciedu Press, vol. 4(3), pages 1-77, August.
    30. Wattanawongwan, Suttisak & Mues, Christophe & Okhrati, Ramin & Choudhry, Taufiq & So, Mee Chi, 2023. "Modelling credit card exposure at default using vine copula quantile regression," European Journal of Operational Research, Elsevier, vol. 311(1), pages 387-399.
    31. CORONEO, Laura & VEREDAS, David, 2006. "Intradaily seasonality of returns distribution. A quantile regression approach and intradaily VaR estimation," LIDAM Discussion Papers CORE 2006077, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    32. Xiaohong Chen & Wei Biao Wu & Yanping Yi, 2009. "Efficient Estimation of Copula-based Semiparametric Markov Models," Cowles Foundation Discussion Papers 1691, Cowles Foundation for Research in Economics, Yale University, revised Mar 2009.
    33. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024.
    34. Xianling Ren & Xinping Yu, 2024. "Hedging performance analysis of energy markets: Evidence from copula quantile regression," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 432-450, March.
    35. Huo, Lijuan & Kim, Tae-Hwan & Kim, Yunmi, 2012. "Robust estimation of covariance and its application to portfolio optimization," Finance Research Letters, Elsevier, vol. 9(3), pages 121-134.
    36. Arunanondchai, Panit & Sukcharoen, Kunlapath & Leatham, David J., 2020. "Dealing with tail risk in energy commodity markets: Futures contracts versus exchange-traded funds," Journal of Commodity Markets, Elsevier, vol. 20(C).
    37. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
    38. Fabrizio Cipollini & Giampiero Gallo & Andrea Ugolini, 2016. "Median Response to Shocks: A Model for VaR Spillovers in East Asia," Econometrics Working Papers Archive 2016_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    39. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    40. Li, Danyang & Zhang, Zhekai & Cerrato, Mario, 2023. "Factor investing and currency portfolio management," International Review of Financial Analysis, Elsevier, vol. 87(C).
    41. Benlagha, Noureddine, 2020. "Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade," Research in International Business and Finance, Elsevier, vol. 54(C).
    42. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Maitra, Debasish & Al-Jarrah, Idries Mohammad Wanas, 2019. "Portfolio management and dependencies among precious metal markets: Evidence from a Copula quantile-on-quantile approach," Resources Policy, Elsevier, vol. 64(C).
    43. Harry Joe, 2018. "Dependence Properties of Conditional Distributions of some Copula Models," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 975-1001, September.
    44. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    45. Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Eric Bouye
(Eric Bouye) should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.