Long Memory in Stock Market Volatility: Indian Evidences

Artha Vijnana, Vol. 52, No. 4, pp. 332-345, December, 2010

14 Pages Posted: 22 Jun 2011

See all articles by Gourishankar S. Hiremath

Gourishankar S. Hiremath

Indian Institute of Technology (IIT), Kharagpur - Department of Humanities and Social Sciences

Bandi Kamaiah

University of Hyderabad

Date Written: December 31, 2010

Abstract

Long memory in variance or volatility refers to a slow hyperbolic decay in auto-correlation functions of the squared or log-squared returns. GARCH models extensively used in empirical analysis do not account for long memory in volatility. The present paper examines the issue of long memory in volatility in the context of Indian stock market using the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model. For the purpose, daily values of 38 indices from both National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) are used. The results of the study confirm presence of long memory in volatility of all the index returns. This shows that FIGARCH model better describes the persistence in volatility than the conventional ARCH-GARCH models.

Keywords: Long memory, fractional integration, Volatility, Variance, ARCH-GARCH, FIGARCH, Indian Stock Market, BSE, NSE, Long memory, fractional integration, Volatility, hyperbolic decay, ARCH-GARCH, FIGARCH, Indian Stock Market, BSE, NSE

JEL Classification: G14, C 14, C58

Suggested Citation

Hiremath, Gourishankar S. and Kamaiah, Bandi, Long Memory in Stock Market Volatility: Indian Evidences (December 31, 2010). Artha Vijnana, Vol. 52, No. 4, pp. 332-345, December, 2010, Available at SSRN: https://ssrn.com/abstract=1868832

Gourishankar S. Hiremath (Contact Author)

Indian Institute of Technology (IIT), Kharagpur - Department of Humanities and Social Sciences ( email )

Kharagpur, West Bengal 721302
India

Bandi Kamaiah

University of Hyderabad ( email )

Central University (PO)
Andhra Pradesh
Hyderabad, CA 500 046
India

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