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Application of GARCH Models to Forecast Financial Volatility of Daily Returns:An Empirical Study on the Indian Stock Market


Affiliations
1 Department of Business Management, Bharathi Institute of Business Management, Warangal, Telangana, India
     

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The present study attempts to modelling and forecasting the volatility of the S&P BSE 500 Index returns of Indian stock market, using daily data covering a period from sep. 17. 2007 till Dec. 30. 2016. This study applies GARCH, EGARCH and GARCH-M models to investigate the behavior of stock return volatility for Indian stock market. This study aims to examine the volatility characteristics on Indian stock market that include; clustering volatility, leverage effect and risk premium. This paper shows that the Indian stock market experiences volatility clustering and hence GARCH-type models predict the market volatility better than simple volatility models, like historical average, moving average etc. This study shows volatility forecasted for period of 200 days by using GARCH family models. The study concludes that there is a presence of volatility clustering, evidence of asymmetric and leverage effect on volatility and non-existence of risk premium in the Indian stock market.

Keywords

GARCH, EGARCH, GARCH-M, Volatility Clustering, Leverage Effect.
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  • Application of GARCH Models to Forecast Financial Volatility of Daily Returns:An Empirical Study on the Indian Stock Market

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Authors

Mulukalapally Susruth
Department of Business Management, Bharathi Institute of Business Management, Warangal, Telangana, India

Abstract


The present study attempts to modelling and forecasting the volatility of the S&P BSE 500 Index returns of Indian stock market, using daily data covering a period from sep. 17. 2007 till Dec. 30. 2016. This study applies GARCH, EGARCH and GARCH-M models to investigate the behavior of stock return volatility for Indian stock market. This study aims to examine the volatility characteristics on Indian stock market that include; clustering volatility, leverage effect and risk premium. This paper shows that the Indian stock market experiences volatility clustering and hence GARCH-type models predict the market volatility better than simple volatility models, like historical average, moving average etc. This study shows volatility forecasted for period of 200 days by using GARCH family models. The study concludes that there is a presence of volatility clustering, evidence of asymmetric and leverage effect on volatility and non-existence of risk premium in the Indian stock market.

Keywords


GARCH, EGARCH, GARCH-M, Volatility Clustering, Leverage Effect.