Hiremath, Gourishankar S and Bandi, Kamaiah (2010): Long Memory in Stock Market Volatility:Evidence from India. Published in: Artha Vijnana , Vol. 52, No. 4 (2010): pp. 332345.

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Abstract
Long memory in variance or volatility refers to a slow hyperbolic decay in autocorrelation functions of the squared or logsquared 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 ARCHGARCH models.
Item Type:  MPRA Paper 

Original Title:  Long Memory in Stock Market Volatility:Evidence from India 
English Title:  Long Memory in Stock Market Volatility:Evidence from India 
Language:  English 
Keywords:  Fractional integration, Long memory, Volatility, FIGARCH, hyperbolic decay, Indian Stock Market, NSE, BSE. 
Subjects:  G  Financial Economics > G0  General G  Financial Economics > G1  General Financial Markets > G12  Asset Pricing ; Trading Volume ; Bond Interest Rates G  Financial Economics > G1  General Financial Markets > G14  Information and Market Efficiency ; Event Studies ; Insider Trading G  Financial Economics > G1  General Financial Markets > G17  Financial Forecasting and Simulation 
Item ID:  48519 
Depositing User:  Gourishankar S. Hiremath 
Date Deposited:  22. Jul 2013 13:47 
Last Modified:  22. Jul 2013 14:02 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/48519 