Alternative Approach to Quantitative Risk Analysis
Application of Extreme Value Theory based measurement of Value at Risk and its comparison to conventional risk measures
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The role of Risk Management has grown dramatically after recent financial crisis, triggered by a liquidity shortfall in the United States banking system. Among various proposed risk measures the Value at Risk (VaR) is probably the most essential part of the modern Risk Management architecture. VaR is the response to the lessons of disasters, which caused Lehman Brothers to file bankruptcy in 2008. It is a forward-looking risk measurement, which is widely used to quantify and control market risks. Conventional methods tend to underestimate the risks, since prediction of tail behavior is the pri...
The role of Risk Management has grown dramatically after recent financial crisis, triggered by a liquidity shortfall in the United States banking system. Among various proposed risk measures the Value at Risk (VaR) is probably the most essential part of the modern Risk Management architecture. VaR is the response to the lessons of disasters, which caused Lehman Brothers to file bankruptcy in 2008. It is a forward-looking risk measurement, which is widely used to quantify and control market risks. Conventional methods tend to underestimate the risks, since prediction of tail behavior is the primary goal of any VaR model. Hence, the biggest challenge in VaR modeling is actually the extreme returns specification. The Extreme Value Theory (EVT) has appeared in the academic literature as an alternative to the conventional measures for VaR. The EVT is free from many of the flaws of conventional approaches, since it focuses on extreme values, rather than mean values. The purpose of the paper is to provide an analysis of the theoretical foundations of the EVT compared to the conventional models as well as its practical implications on VaR.
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