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Characteristics of Conditional Volatility of BSE SENSEX:The Impact of Information Asymmetry and Leverage


Affiliations
1 Department of Commerce, Rabindra Mahavidyalaya, Champadanga, Hooghly, West Bengal, Pin 712401, India
2 The University of Burdwan, West Bengal, India
     

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Stock market volatility has attracted growing attentions from scholars, policy makers and practitioners due to its impact on decision making. Present study in this context tries to explore the features of daily returns of BSE SENSEX and the conditional volatility of the same. Highly significant large JB-statistic confirms that the return series is not normally distributed. The return series is leptokurtic and returns are serially correlated. It appears that volatility clustering is present during the study period. Furthermore, GARCH (1, 1) model has been applied to compute conditional variance of the sample data. The empirical results show that above model is a good fit and it has also been established that volatility in this market persists over a long period of time. A large sum of coefficients implies that a large positive or a large negative return leads future forecasts of the variance to be high for a prolonged period. To capture the leverage effect present study has applied TARCH(1,1) model. From the empirical result it appears that news asymmetry and leverage effect are present in the market.
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  • Characteristics of Conditional Volatility of BSE SENSEX:The Impact of Information Asymmetry and Leverage

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Authors

Som Sankar Sen
Department of Commerce, Rabindra Mahavidyalaya, Champadanga, Hooghly, West Bengal, Pin 712401, India
Tanmay Bandyopadhyay
The University of Burdwan, West Bengal, India

Abstract


Stock market volatility has attracted growing attentions from scholars, policy makers and practitioners due to its impact on decision making. Present study in this context tries to explore the features of daily returns of BSE SENSEX and the conditional volatility of the same. Highly significant large JB-statistic confirms that the return series is not normally distributed. The return series is leptokurtic and returns are serially correlated. It appears that volatility clustering is present during the study period. Furthermore, GARCH (1, 1) model has been applied to compute conditional variance of the sample data. The empirical results show that above model is a good fit and it has also been established that volatility in this market persists over a long period of time. A large sum of coefficients implies that a large positive or a large negative return leads future forecasts of the variance to be high for a prolonged period. To capture the leverage effect present study has applied TARCH(1,1) model. From the empirical result it appears that news asymmetry and leverage effect are present in the market.