Work detail

Predictive Accuracy of Competing Value-at Risk Specifications during Crisis: An Application to CEE Financial Markets

Author: Mgr. Kroutil Tomáš
Year: 2011 - summer
Work type: Doctoral
Finance, Financial Markets and Banking
Language: English
Pages: 126
Awards and prizes:
Abstract: The recent worldwide Financial Crisis has increased the need for reliable financial
risk measurement and management. In this thesis we evaluate and compare the
accuracy of one-day-ahead out-of-sample forecasts of various Value-at-Risk models
through a comprehensive assessment framework using crisis data of three CEE
stock market indices (PX, WIG20 and BUX) and two benchmark stock indices (S&P
500, DAX). For building the VaR specifications we employ several GARCH
extensions allowing either for asymmetry in volatility such as EGARCH, TGARCH
and APARCH or long memory like FIGARCH and HYGARCH. Apart from conditional
heteroscedasticity models, we also utilize realized volatility estimated by long
memory ARFIMA and HAR. Individual volatility models are combined with full
parametric approach, filtered historical simulation or filtered extreme value theory.
This thesis shows that while VaR specifications based on logarithmic realized
volatility, TGARCH and APARCH perform best overall, the benchmark - RiskMetrics
model - is not significantly outperformed. The best performing model proves to be the
TGARCH-t FHS, which is a combination of asymmetric and heavy-tailed GARCH
filter with a historical simulation based approach.
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