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Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets

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  • Chun-Pin Hsu

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  • Chin-Wen Huang

    ()

  • Wan-Jiun Chiou

    ()

Abstract

A traditional Monte Carlo simulation using linear correlations induces estimation bias in measuring portfolio value-at-risk (VaR), due to the well-documented existence of fat-tail, skewness, truncations, and non-linear relations in return distributions. In this paper, we consider the above issues in modeling VaR and evaluate the effectiveness of using copula-extreme-value-based semiparametric approaches. To assess portfolio risk in six Asian markets, we incorporate a combination of extreme value theory (EVT) and various copulas to build joint distributions of returns. A backtesting analysis using a Monte Carlo VaR simulation suggests that the Clayton copula-EVT evinces the best performance regardless of the shapes of the return distributions, and that in general the copulas with the EVT provide better estimations of VaRs than the copulas with conventionally employed empirical distributions. These findings still hold in conditional-coverage-based backtesting. These findings indicate the economic significance of incorporating the down-side shock in risk management. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Chun-Pin Hsu & Chin-Wen Huang & Wan-Jiun Chiou, 2012. "Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets," Review of Quantitative Finance and Accounting, Springer, vol. 39(4), pages 447-468, November.
  • Handle: RePEc:kap:rqfnac:v:39:y:2012:i:4:p:447-468 DOI: 10.1007/s11156-011-0261-0
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    References listed on IDEAS

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    1. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," Journal of Financial Econometrics, Society for Financial Econometrics, pages 373-411.
    2. Aggarwal, Raj & Mougoue, Mbodja, 1998. "Common Stochastic Trends among Asian Currencies: Evidence for Japan, ASEANs, and the Asian Tigers," Review of Quantitative Finance and Accounting, Springer, pages 193-206.
    3. Ho, Lan-Chih & Burridge, Peter & Cadle, John & Theobald, Michael, 2000. "Value-at-risk: Applying the extreme value approach to Asian markets in the recent financial turmoil," Pacific-Basin Finance Journal, Elsevier, pages 249-275.
    4. François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    5. Isabelle Huault & V. Perret & S. Charreire-Petit, 2007. "Management," Post-Print halshs-00337676, HAL.
    6. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, pages 187-201.
    7. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    8. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    9. Tastan, Hüseyin, 2006. "Estimating time-varying conditional correlations between stock and foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 445-458.
    10. Patro, Dilip K. & Wald, John K. & Wu, Yangru, 2002. "Explaining exchange rate risk in world stock markets: A panel approach," Journal of Banking & Finance, Elsevier, vol. 26(10), pages 1951-1972, October.
    11. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    12. L. K. Hotta & E. C. Lucas & H. P Palaro, 2008. "Estimation of VaR Using Copula and Extreme Value Theory," Multinational Finance Journal, Multinational Finance Journal, vol. 12(3-4), pages 205-218, September.
    13. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
    14. Doidge, Craig & Griffin, John & Williamson, Rohan, 2006. "Measuring the economic importance of exchange rate exposure," Journal of Empirical Finance, Elsevier, pages 550-576.
    15. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, pages 271-300.
    16. Bartram, Sohnke M. & Taylor, Stephen J. & Wang, Yaw-Huei, 2007. "The Euro and European financial market dependence," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1461-1481, May.
    17. S. T. M. Straetmans & W. F. C. Verschoor & C. C. P. Wolff, 2008. "Extreme US stock market fluctuations in the wake of 9|11," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 17-42.
    18. Turan G. Bali, 2007. "A Generalized Extreme Value Approach to Financial Risk Measurement," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1613-1649, October.
    19. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, pages 307-335.
    20. Engle, Robert & Colacito, Riccardo, 2006. "Testing and Valuing Dynamic Correlations for Asset Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 238-253, April.
    21. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, pages 401-423.
    22. Kolari, James W. & Moorman, Ted C. & Sorescu, Sorin M., 2008. "Foreign exchange risk and the cross-section of stock returns," Journal of International Money and Finance, Elsevier, vol. 27(7), pages 1074-1097, November.
    23. Okimoto, Tatsuyoshi, 2008. "New Evidence of Asymmetric Dependence Structures in International Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(03), pages 787-815, September.
    24. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
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    Cited by:

    1. Shahzad, Syed Jawad Hussain & Kumar, Ronald Ravinesh & Ali, Sajid & Ameer, Saba, 2016. "Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 8-33.
    2. Meichi Huang & Chih-Chiang Wu, 2015. "Economic benefits and determinants of extreme dependences between REIT and stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 299-327, February.
    3. Siburg, Karl Friedrich & Stoimenov, Pavel & Weiß, Gregor N.F., 2015. "Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 129-140.
    4. Jing-Rung Yu & Wan-Jiun Paul Chiou & Jian-Hong Yang, 2017. "Diversification benefits of risk portfolio models: a case of Taiwan’s stock market," Review of Quantitative Finance and Accounting, Springer, pages 467-502.

    More about this item

    Keywords

    Copulas; Dependence; Emerging markets; EVT; GARCH; Backtesting; G15; F31; C46;

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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