Time Series of Return and Volatility

Raj S. Dhankar ()
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Raj S. Dhankar: University of Delhi

Chapter Chapter 10 in Risk-Return Relationship and Portfolio Management, 2019, pp 165-177 from Springer

Abstract: Abstract The study 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 analyses the relationship between stock returns and conditional volatilityConditional volatility , and standard residuals. The daily opening and closing prices of the S&P 500 and NASDAQ 100NASDAQ 100 are used for the period January 1990–December 2007. The study applies GARCHGeneralized Autoregressive Conditional Heteroscedasticity (GARCH) (1, 1) and T-GARCHT-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, analysing the relationship, the study reports a negative significant relationship between stock returns and conditional volatilityConditional volatility . However, the relationship between stock returns and standardized residuals is found to be significant. This study provides a robustness test of the conditional volatilityConditional volatility and asymmetric impact of good and bad news. These findings bring out that investors adjust their investment decisions with regard to expected volatilityExpected volatility , however, they expect extra riskRisk premium for unexpected volatilityUnexpected volatility .

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isbchp:978-81-322-3950-5_10

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DOI: 10.1007/978-81-322-3950-5_10

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