BACKTESTING VALUE AT RISK MODELS IN THE PRESENCE OF STRUCTURAL BREAK ON THE ROMANIAN AND HUNGARIAN STOCK MARKETS

Cociuba Mihail Ioan (), Zapodeanu Daniela and Kulcsar Edina
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Cociuba Mihail Ioan: University of Oradea, FSE

Annals of Faculty of Economics, 2014, vol. 1, issue 1, 802-812

Abstract: Transactions on financial markets are associated with variability, risk and uncertainty, so quantification of risk has a great importance. Beside Standard Deviation and Variance, one of the most involved risk measure methods is Value-at-Risk (VaR). In this study, we use daily return for the stock index from Romania (BET) and Hungary (BUX) for the 01:2007 - 02:2013 periods in order to test the influence of structural breaks on the VaR metrics. We find out that the ARCH phenomenon is present, so we use the GARCH family models. The structural breaks in the series mean and variance are identified using the Zivot-Andrews test and PELT algorithm, the structural break dates are captured using dummy variables in the GARCH models (struc-GARCH), the selection of models is done using the informational criterion [Akaike, Schwarz, Log-likelihood]. The results of present research show a greater volatility associated with a higher risk level in case of Romanian stock index. The stock market indices return follows a negatively skewed and leptokurtic distributions forms either in two cases, so is unspecific a normal distribution. After applying above mentioned tests we can conclude that there are eight structural breaks in BET index returns variance and there are five breakpoints in case of BUX. The breakpoints in mean show very closely results in time, for BET in February 2009 and for BUX March 2009. Backtesting VaR models are done by measuring the number of times the loss is greater than the VaR forecast. The first step for unconditional coverage testing consists in comparing of fraction of VaR violation for a particular risk model. The independence testing it is very important tool in back-testing, because it is not the same that the VaR violations are differentiated in time or there are clustered in some certain period. By checking the independence test, we have the possibility to discover and reject the model with clustered hit sequence. Testing the influence of structural breaks on VaR we find that incorporating structural breaks in the GJR-GARCH models generates lower violations when comparing with the plain GJR-GARCH or RiskMetrics methodology.

Keywords: stock market; structural break; Value at Risk; GARCH (search for similar items in EconPapers)
JEL-codes: G17 (search for similar items in EconPapers)
Date: 2014
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