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Estimating Volatility Pattern in Stock Markets: The Indian Case

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  • Saheli Das
  • Archana Kulkarni
  • Bandi Kamaiah

Abstract

This paper examines the volatility pattern in Indian stock markets during the time period January 1, 2011 to March 31, 2014 using the daily closing prices of two stock indices, S&P BSE Sensex and CNX Nifty. This paper uses asymmetric GARCH models like Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH) to explain the volatility. Considering the minimum values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), TGARCH model is found to be a superior model for return volatility over EGARCH. The findings suggest that there is no volatility persistence as well as leverage effect in the data during the period under consideration.

Suggested Citation

  • Saheli Das & Archana Kulkarni & Bandi Kamaiah, 2014. "Estimating Volatility Pattern in Stock Markets: The Indian Case," The IUP Journal of Applied Economics, IUP Publications, vol. 0(4), pages 42-51, October.
    • Handle: RePEc:icf:icfjae:v:13:y:2014:i:4:p:42-51
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