Impact study of volatility modelling of Bangladesh stock index using non-normal density

Abstract

This article examines a wide variety of popular volatility models for stock index return, including the random walk (RW), autoregressive, generalized autoregressive conditional heteroscedasticity (GARCH), and asymmetric GARCH models with normal and non-normal (Student's t and generalized error) distributional assumption. Fitting these models to the Chittagong stock index return data from the period 2 January 1999 to 29 December 2005, we found that the asymmetric GARCH/GARCH model fits better under the assumption of non-normal distribution than under normal distribution. Non-parametric specification tests show that the RW-GARCH, RW-TGARCH, RW-EGARCH, and RW-APARCH models under the Student's t-distributional assumption are significant at the 5% level. Finally, the study suggests that these four models are suitable for the Chittagong Stock Exchange of Bangladesh. We believe that this study would be of great benefit to investors and policy makers at home and abroad.

Keywords:

• random walk
• GARCH
• asymmetric GARCH
• non-parametric specification test
• Student's t-distribution
• generalized error distribution

Acknowledgements

The authors are grateful to the editor of the Journal of Applied Statistics and anonymous referees for their helpful comment and suggestions. Mostafizur Rahman is supported by the Ministry of Education of the People's Republic of China's program for New Century Excellent Talents in University (NCET-04-0608).