Technical supplement to Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory
نویسندگان
چکیده
منابع مشابه
Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory
Abstract. We propose nonparametric estimators for conditional value-at-risk (VaR) and expected shortfall (ES) associated with conditional distributions of a series of returns on a financial asset. The return series and the conditioning covariates, which may include lagged returns and other exogenous variables, are assumed to be strong mixing and follow a fully nonparametric conditional location...
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We propose an estimation procedure for value at risk (VaR) and expected shortfall (TailVaR) for conditional distributions of a time series of returns on a ̄nancial asset. Our approach combines a local polynomial estimator of conditional mean and volatility functions in a conditional heterocedastic autoregressive nonlinear (CHARN) model with Extreme Value Theory for estimating quantiles of the c...
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