Abstract
The purpose of this paper is to evaluate performance of value-at-risk (VaR) produced by two risk models: historical simulation and Risk Metrics. We perform three backtest: unconditional coverage, independence and conditional coverage. We present results on both VaR 1% and VaR 5% on a one-day horizon for the following indices: S&P 500, DAX, SAX, PX and Belex 15. Our results show that Historical simulation 500 days rolling window approach satisfies unconditional coverage for all tested indices, while Risk Metrics has many rejection cases. On the other hand Risk Metrics model satisfies independence backtest for three indices, while Historical simulation has rejected more times. Based on our strong criteria to accept accuracy of VaR models only if both unconditional coverage and independence properties are satisfied, results indicate that during the crisis period all tested VaR models underestimate the true level of market risk exposure.
Highlights
Risk is an integral part of human existence and wherever there is a human activity the risks are present
In this paper we investigated the performance of value at risk (VaR) models that are widely used in the developed capital markets on daily indices returns from Serbia, Germany, Slovakia, Czech Republic and USA
As a result of this event VaR models that are applied in the work not properly predict market risk, even in the most efficient capital markets such as the NYSE
Summary
Risk is an integral part of human existence and wherever there is a human activity the risks are present. The idea that risk, from a scientific point of view, may be important to the economy is dating back from 1921 in the paper Frank H. Financial risk includes situations where there is uncertainty and opportunity for achievement's financial loss or in other words, this risk is related to the money that can be lost in the financial markets. The main measure of market risk is value at risk (VaR) methodology, which measures the worst loss potential when holding a financial asset over specific time period with a certain probability, and which is in practice used with other techniques to minimize the risks in order to achieve good results in business
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