Merenje vrednosti pri riziku kod tržišta u usponu: empirijska analiza tržišta kapitala u Srbiji
Measuring Value At Risk On Emerging Stock Markets: Empirical Evidence From Serbian Stock Exchange

Summary/Abstract: This paper evaluates the performance of a variety of symmetric and asymmetric GARCH type models based on normal and Student t distribution in estimating and forecasting market risk in Serbian stock market. Using the daily returns of the Serbian stock index BELEX 15 we tested the relative performance of a variety of symmetric and asymmetric GARCH type models based on normal and Student t distribution for period of October 2005 to October 2012, a sufficiently long period which includes tranquil as well as crisis years. For investors, in the current global financial crisis, it is particularly important to accurately measure and allocate risk and efficiently manage their portfolio. The impact of extreme events on changes in the financial markets in emerging countries is even more pronounced, as such markets are characterized by lower levels of liquidity and significantly smaller market capitalization. The possibility of application of VaR methodology, which is basically designed and developed for liquid and developed markets, should be tested on the emerging markets, which are characterized by volatility, illiquidity and shallowness of the market. This motivates us to implement methods that involve time varying volatility and heavy tails of the empirical distribution of returns. We test the hypothesis that using the assumption of heavy tailed distribution it is possible to forecast market risk more precisely, especially in times of crisis, than under assumption of normal distribution. Our empirical results indicate that the most adequate GARCH type model for estimating and forecasting volatility in the Serbian stock market is EGARCH model with assumption that the residuals follow the normal distribution and GARCH (1,1) model with assumption that the residuals follow the Student's t distribution. Our backtesting results for the last 200 observations based on the Kupiec POF test show that EGARCH model with normal distribution and GARCH(1,1) model with Student t distribution of residuals passed Kupiec test with 99% of confidence level, but not with 95% of confidence level, which imply that these models underestimate VaR at 95% confidence level.

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