University of Khartoum

Forecasting Volatility in GCC Emerging Markets: The Predictive Power of Alternative Models

Forecasting Volatility in GCC Emerging Markets: The Predictive Power of Alternative Models

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dc.contributor.author Onour, Ibrahim A.
dc.date.accessioned 2016-06-21T09:27:19Z
dc.date.available 2016-06-21T09:27:19Z
dc.date.issued 2011
dc.identifier.uri http://khartoumspace.uofk.edu/123456789/22039
dc.description.abstract In this paper forecast of conditional volatility in Saudi, Kuwait, and Abu-Dhabi markets is performed. To capture skewness and excess kurtosis that characterize asset returns in GCC markets, conditional volatility of asset returns estimated using skewed t-distribution, symmetric student t-distribution, and the Normal distribution specifications. Prediction performance results indicate the Normal and symmetric t-distribution models outperform the skewed t-distribution model. en_US
dc.language.iso en en_US
dc.publisher University of Khartoum en_US
dc.subject GARCH en_US
dc.subject Volatility en_US
dc.subject Asymmetry en_US
dc.subject skewness en_US
dc.subject Forecast en_US
dc.title Forecasting Volatility in GCC Emerging Markets: The Predictive Power of Alternative Models en_US
dc.type Publication en_US

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