JUMP, NON-NORMAL ERROR DISTRIBUTION AND STOCK PRICE VOLATILITY — A NONPARAMETRIC SPECIFICATION TEST

Mohammad Masudur Rahman (), Laila Arjuman Ara () and Zhenlong Zheng ()
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Mohammad Masudur Rahman: United Nations University-Institute of Advanced Studies (UNU-IAS), 6F, International Organization Centre, Pacifico-Yokohama, Minatomirai, Nishi-ku, Yokohama 220-8502, Japan
Laila Arjuman Ara: WTO Research Centre, Aoyama Gakuin University, Tokyo, Japan
Zhenlong Zheng: Department of Finance, Xiamen University, Fujian, China

The Singapore Economic Review (SER), 2009, vol. 54, issue 01, 101-121

Abstract: This paper examines a wide variety of popular volatility models for stock index return, including Random Walk model, Autoregressive model, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, and extensive GARCH model, GARCH-jump model with Normal, and Studentt-distribution assumption as well as nonparametric specification test of these models. We fit these models to Dhaka stock return index from 20 November 1999 to 9 October 2004. There has been empirical evidence of volatility clustering, alike to findings in previous studies. Each market contains different GARCH models, which fit well. From the estimation, we find that the volatility of the return and the jump probability were significantly higher after 27 November 2001. The model introducing GARCH jump effect with normal and Studentt-distribution assumption can better fit the volatility characteristics. We find that RW-GARCH-t, RW-AGARCH-t RW-IGARCH-t and RW-GARCH-M-t can pass the nonparametric specification test at 5% significance level. It is suggested that these four models can capture the main characteristics of Dhaka stock return index.

Keywords: GARCH-jump; nonparametric specification test; t-distribution (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1142/S0217590809003203

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