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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

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    Cited by:

    1. Dash, M., 2019. "Testing the Random Walk Hypothesis in the Indian Stock Market Using ARIMA Modelling," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 8(2), pages 71-77, May.
    2. Dash, M., 2019. "A Study on Commodity Market Behaviour, Price Discovery and its Factors," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 8(3), pages 125-134, September.
    3. Yensen Ni & Min-Yuh Day & Yirung Cheng & Paoyu Huang, 2022. "Can investors profit by utilizing technical trading strategies? Evidence from the Korean and Chinese stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    4. Mihir Dash, 2020. "Testing the Binomial Model in the Indian Stock Market," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 9(1), pages 22-27, March.

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