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FORECASTING STOCK MARKET VOLITILITY- EVIDENCE FROM MUSCAT SECURITY MARKET USING GARCH MODELS

Journal Name:

  • International Journal of Commerce And Finance

Publication Year:

  • 2016

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Author Name
Abstract (2. Language): 
Engle (1982) introduced the autoregressive conditionally heteroskedastic model for quantifying the conditional volatility and by Boollerslev (1986), Engle, Lilien and Robins (1987) and Glosten, Jaganathan and Runkle (1993) extended the class asymmetric model. Amongst many others, Bollerslev, Chou and Kroner (1992) or (1994) are considered to be the précis of ARCH family models. In this direction the paper forecasts the stock market volatility of four actively trading indices from Muscat security market by using daily observations of indices over the period of January 2001 to November 2015 using GARCH(1,1), EGARCH(1,1) and TGARCH (1,1) models. The study reveals the positive relationship between risk and return. The analysis exhibits that the volatility shocks are quite persistent. Further the asymmetric GARCH models find a significance evidence of asymmetry in stock returns. The study discloses that the volatility is highly persistent and there is asymmetrical relationship between return shocks and volatility adjustments and the leverage effect is found across all flour indices. Hence the investors are advised to formulate investment strategies by analyzing recent and historical news and forecast the future market movement while selecting portfolio for efficient management of financial risks to reap benefit in the stock market.
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