Journal of Applied Statistics · 2010 · 34 citations · 11 references
BusinessEconomicsFinanceFinancial EconomicsQuantitative FinanceRisk AnalysisExtreme Value TheoryFinancial RiskForeign Exchange RiskRisk MeasurementRisk-return AnalysisValue At RiskCurrency Risk MeasurementExtreme Value AnalysisForeign Currency Risk AssessmentForeign Exchange Risk AnalysisForeign Exchange Risk ModelingTail RiskTail Risk AssessmentTail Risk Modeling
This paper applies extreme value theory (EVT) to estimate the tails of return series of Chinese yuan (CNY) exchange rates. We find that the degree of fitting Pareto distribution to the data of the tail of return series is extremely high. The empirical results indicate that expected shortfall cannot improve the tail risk problem of value-at-risk (VaR). The evidence of back testing indicates that EVT-based VaR values underestimate the risks of exchange rates such as USD/CNY and HKD/CNY, which may be caused by the continuous appreciation of CNY against USD and HKD. However, compared with VaR values calculated by historical simulation and variance–covariance method, VaR values calculated by EVT can measure the risk more accurately for the exchange rates of JPY/CNY and EUR/CNY.
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Philippe Artzner, Freddy Delbaen, Jean‐Marc Eber et al. · Mathematical Finance · 1999 · 9K citations · Full text
Business, Finance, Risk Management +14
Statistical Inference Using Extreme Order Statistics
James Pickands · The Annals of Statistics · 1975 · 3.6K citations