Modelling and Forecasting Volatility of Stock Index Return Using GARCH Models: an Empirical Evidence of Argentina
Xenofontos, Andreas (2014) Modelling and Forecasting Volatility of Stock Index Return Using GARCH Models: an Empirical Evidence of Argentina. [Dissertation (University of Nottingham only)] (Unpublished)
Modelling and forecasting stock market volatility has been one of the most important topics in financial econometrics during the last years. In an attempt to contribute to empirical literature, this thesis examines stock return volatility in Argentine stock market and evaluates the forecasting performance of GARCH-type models in terms of their out-of-sample forecasting accuracy. Both symmetric and asymmetric models are applied, using both daily and weekly frequency data of Merval Index over the twelve year period from January 2002 to August 2014. The models are estimated using three distributions which are Student’s-t Distribution, Generalized Error Distribution and Gaussian Distribution.
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