# Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach

@article{McNeil2000EstimationOT, title={Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach}, author={Alexander J. McNeil and R{\"u}diger Frey}, journal={Journal of Empirical Finance}, year={2000}, volume={7}, pages={271-300} }

We propose a method for estimating Value at Risk VaR and related risk measures describing the tail of the conditional distribution of a heteroscedastic financial return series. Our approach combines pseudo-maximum-likelihood fitting of GARCH models to estimate . the current volatility and extreme value theory EVT for estimating the tail of the innovation distribution of the GARCH model. We use our method to estimate conditional . quantiles VaR and conditional expected shortfalls the expected…

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