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Volatility Clustering, New Heavy-Tailed Distribution and the Stock Market Returns in South Korea

Author

Listed:
  • Yoon Hong

    (Hanyang University, South Korea)

  • Ji-chul Lee

    (Dongseo University, South Korea)

  • Guoping Ding

    (Nanjing University, China)

Abstract

As other developed economies over the world, the stock market plays a crucial role in facilitating the economic growth. In this paper, we compare two different types of heavy-tailed distribution, the Student’s t distribution and the normal reciprocal inverse Gaussian distribution, within the generalized autoregressive conditional heteroskedasticity (GARCH) framework for the daily stock market returns of South Korea (KOSPI). Our results show two important findings: i) the daily KOSPI returns exhibit conditional heavy tails even after volatility clustering effect has been accounted for; and ii) the NRIG distribution has a better in-sample performance than the Student’s t distribution.

Suggested Citation

  • Yoon Hong & Ji-chul Lee & Guoping Ding, 2017. "Volatility Clustering, New Heavy-Tailed Distribution and the Stock Market Returns in South Korea," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 6(3), pages 164-169, September.
  • Handle: RePEc:ods:journl:v:6:y:2017:i:3:p:164-169
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    References listed on IDEAS

    as
    1. Sola, Martin & Spagnolo, Fabio & Spagnolo, Nicola, 2002. "A test for volatility spillovers," Economics Letters, Elsevier, vol. 76(1), pages 77-84, June.
    2. Taufiq Choudhry, 2000. "Day of the week effect in emerging Asian stock markets: evidence from the GARCH model," Applied Financial Economics, Taylor & Francis Journals, vol. 10(3), pages 235-242.
    3. Wenshwo Fang, 2002. "The effects of currency depreciation on stock returns: evidence from five East Asian economies," Applied Economics Letters, Taylor & Francis Journals, vol. 9(3), pages 195-199.
    4. Dimitris N. Politis, 2004. "A Heavy-Tailed Distribution for ARCH Residuals with Application to Volatility Prediction," Annals of Economics and Finance, Society for AEF, vol. 5(2), pages 283-298, November.
    5. Su, Jung-Bin & Hung, Jui-Cheng, 2011. "Empirical analysis of jump dynamics, heavy-tails and skewness on value-at-risk estimation," Economic Modelling, Elsevier, vol. 28(3), pages 1117-1130, May.
    6. Sang Jin Lee, 2009. "Volatility spillover effects amongsix Asian countries," Applied Economics Letters, Taylor & Francis Journals, vol. 16(5), pages 501-508.
    7. Politis, Dimitris N., 2004. "A heavy-tailed distribution for ARCH residuals with application to volatility prediction," University of California at San Diego, Economics Working Paper Series qt7r89639x, Department of Economics, UC San Diego.
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