Empirical Analysis of Conditional Heteroskedasticity in Time Series of Stock Returns and Asymmetric Effect on Volatility

Abstract

This article investigates the presence of conditional heteroskedasticity in time series of US stock market returns, and the asymmetric effect of good and bad news on volatility. Further, the study also analyzes the relationship between stock returns and conditional volatility, and standard residuals. The daily opening and closing prices of S&P 500 and NASDAQ 100 are used for the period January 1990 to December 2007. The study applies GARCH (1, 1) and T-GARCH (1, 1) to examine the heteroskedasticity and the asymmetric nature of stock returns respectively. The results of the study suggest the presence of the heteroskedasticity effect and the asymmetric nature of stock returns. Further, analyzing the relationship, the study reports a negative significant relationship between stock returns and conditional volatility. However, the relationship between stock returns and standardized residuals is found to be significant. This study provides a robustness test of the conditional volatility and asymmetric impact of good and bad news. These findings bring out that investors adjust their investment decisions with regard to expected volatility, however, they expect extra risk premium for unexpected volatility.