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A Study on the Volatility of the Bangladesh Stock Market — Based on GARCH Type Models

Author

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  • Roni Bhowmik
  • Wu Chao
  • Wang Shouyang

    (Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing100190, China)

  • Jewel Roy Kumar

    (Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, Bangladesh)

Abstract

The generalized autoregressive conditional heteroskedasticity (GARCH) type models are used to investigate the volatility of Bangladesh stock market. The findings of the study demonstrate that the index volatility characteristics changes over time. The article shows that the data are divided into three sub-periods: pre crisis, crisis, and post crisis. Accordingly, the results of the findings indicate changes in the GARCH-type models parameter, risk premium and persistence of volatility in different periods. A significant “low-yield associated with high-risk” phenomenon is detected in the crisis period and the “leverage effect” occurs in each periods. The investors are irrational which is based on assumption of risk and return characteristics of assets. Consequently, the market is not as mature as developed market. It is found in the article that the threshold generalized autoregressive conditional heteroskedasticity (TGARCH) model is more accurate for the model accuracy. Additionally, statistic error measurements indicate that GARCH model is more efficient than others and it has also more forecasting ability.

Suggested Citation

  • Roni Bhowmik & Wu Chao & Wang Shouyang & Jewel Roy Kumar, 2017. "A Study on the Volatility of the Bangladesh Stock Market — Based on GARCH Type Models," Journal of Systems Science and Information, De Gruyter, vol. 5(3), pages 193-215, June.
    • Handle: RePEc:bpj:jossai:v:5:y:2017:i:3:p:193-215:n:1
    DOI: 10.21078/JSSI-2017-193-23
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    References listed on IDEAS

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