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The topic of extreme events is becoming ever more important for risk management. Stress testing is a technique that is explicitly designed to deal with extreme shocks; however, its methodology and place in the risk process is often unclear to risk managers. This paper, written by a FactSet researcher (link below), will address some common misconceptions about stress testing and provide methodology for its incorporation into the risk process as a supplement to risk measures such as VaR and tracking error. Two stress testing methodologies are presented and empirically tested on actual extreme periods. Both are based on multivariate normal distributions conditional on a factor shock, differing only in the way that covariances are estimated. One of the two methods uses temporal weighting commonly used in the risk model construction; the other uses event weighting, which assigns a higher weight to extreme events that are similar to the factor shock specified. The key conclusion is that the Time Weighted method performs better in moderate or semi-expected shocks, while the Event Weighted method performs better in more extreme and unexpected shocks like the LTCM crisis, 9/11 terrorist attacks, and Fall 2008 financials-led meltdown. As expected, the Event Weighted method, which is designed to model the rise in correlations and variances during extreme markets, produces a more conservative estimate of return impacts. Our results support the conclusion that stress testing can be a very valuable addition to standard risk measures.

Link to white paper:
http://www.factset.com/products/directions/qim/stresstestingpaper

Please contact Taryn Levine at TLevine@factset.com with any questions.


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