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Extreme Value Theory

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Extreme Value Theory
In statistics, any way to estimate or measure the likelihood of an extremely unlikely event. That is, extreme value theory measures the probability that a data point that deviates significantly from the mean will occur. It is useful in insurance to measure the risk of catastrophic events, such as tornados and wildfires.


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ABSTRACT The purpose of this paper is to use the extreme value theory to analyze ten Asian stock markets, identifying which type of extreme value asymptotic distribution better fits historical extreme market events.
CHAPTER 8: Importance Sampling Techniques for Large Quantile Estimation in the Advanced Measurement Approach CHAPTER 9: One-Sided Cross-Validation for Density Estimation with an Application to Operational Risk CHAPTER 10: Multivariate Models for Operational Risk: A Copula Approach Using Extreme Value Theory and Poisson Shock Models CHAPTER 11: First-Order Approximations to Operational Risk: Dependence and Consequences PART THREE: Operational Risk Management and Mitigation.
Key areas discussed include: Defining VaR and where and why it is used; The pros and cons of VaR measurements; Alternative risk measures and why they are not popular; Volatility modeling, in particular multivariate volatility; State-of-the-art methods such as extreme value theory and copulas.
 
 
 
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