Abstract

This paper discusses assumptions behind market risk measures and models. Using a sample period that includes the 2008 international financial crisis, we run a case study with four market risk models: Riskmetics(TM), Historical Simulation, Mixture of Normal with Monte Carlo Simulation and an approach based on Extreme Value Theory. We argue that the trend in the industry is for more sophisticated models, but the necessary degree of complexity is not so clear. We also conclude that the appropriate approach is not to rely only in a single model or measure for market risk management. In fact, as market participants know all the assumptions behind market risk models and measures, the challenge is to build a risk management strategy that takes into account a framework more complex than relying on a single number.

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