GARCH and SV Models with Application of Extreme Value Theory
In the scientific research as well as in everyday life we can see a tendency to averaging many of the observed values. However, we could point out many cases where centrality measures are improper. In the case of events with extreme size the Extreme Value Theory (EVT) is appropriate. The methods of estimation in the EVT can be divided into two groups: nonparametric and parametric ones. The subject of further analysis in this paper is the Peaks over Threshold (POT) method, which belongs to the parametric group of the methods. The main aim of this paper is to present the application of the Extreme Value Theory in a risk analysis. We put forward a thesis that GARCH and SV models with application of the EVT can provide better estimation of the risk measures for financial time series, then standard volatility models. (fragment of text)
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