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Modeling the fat tails in Asian stock markets

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  • Kittiakarasakun, Jullavut
  • Tse, Yiuman

Abstract

We test whether stock returns in the Asian markets are characterized by infinite variance or just large variance, which has an important implication for the applicability of many financial models in Asian market data. Employing the extreme value framework, we find that the Asian index return distributions are fat-tailed but have finite variance. However, the tails of the distributions behave similarly to those in the U.S. and the MSCI World index returns, suggesting that any financial model or risk management tool that incorporates the second moment would work equally well for the Asian market data as it does for developed market data. We apply the Value-at-Risk method using Asian and U.S. data and find no significant difference in performance.

Suggested Citation

  • Kittiakarasakun, Jullavut & Tse, Yiuman, 2011. "Modeling the fat tails in Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 20(3), pages 430-440, June.
  • Handle: RePEc:eee:reveco:v:20:y:2011:i:3:p:430-440
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    References listed on IDEAS

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    Cited by:

    1. Rafik Nazarian & Esmaeil Naderi & Nadiya G. Alikhani & Ashkan Amiri, 2014. "Long Memory Analysis: An Empirical Investigation," International Journal of Economics and Financial Issues, Econjournals, vol. 4(1), pages 16-26.
    2. Karmakar, Madhusudan & Shukla, Girja K., 2015. "Managing extreme risk in some major stock markets: An extreme value approach," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 1-25.
    3. Wang, Chou-Wen & Wu, Chin-Wen & Tzang, Shyh-Weir, 2012. "Implementing option pricing models when asset returns follow an autoregressive moving average process," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 8-25.
    4. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2013. "Does long memory matter in forecasting oil price volatility?," MPRA Paper 46356, University Library of Munich, Germany.
    5. Huang, Hung-Hsi & Lin, Shin-Hung & Wang, Ching-Ping & Chiu, Chia-Yung, 2014. "Adjusting MV-efficient portfolio frontier bias for skewed and non-mesokurtic returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 59-83.
    6. Liu, Qingfu & Tse, Yiuman, 2017. "Overnight returns of stock indexes: Evidence from ETFs and futures," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 440-451.
    7. Jianyu Ma & Mingzhai Geng & Yun Chu, 2016. "Model selection for merger and acquisition analysis in Asian emerging markets," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 9(1), pages 40-56.
    8. Yu, Hao & Nartea, Gilbert V. & Gan, Christopher & Yao, Lee J., 2013. "Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 356-371.
    9. Nazarian, Rafik & Gandali Alikhani, Nadiya & Naderi, Esmaeil & Amiri, Ashkan, 2013. "Forecasting Stock Market Volatility: A Forecast Combination Approach," MPRA Paper 46786, University Library of Munich, Germany.

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