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

Yoon Hong, Ji-chul Lee and Guoping Ding
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Yoon Hong: Hanyang University, South Korea
Ji-chul Lee: Dongseo University, South Korea
Guoping Ding: Nanjing University, China

Journal of Applied Management and Investments, 2017, vol. 6, issue 3, 164-169

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.

Keywords: stock market; GARCH model; heavy-tailed distribution; KOSPI (search for similar items in EconPapers)
Date: 2017
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Handle: RePEc:ods:journl:v:6:y:2017:i:3:p:164-169