GARCH-UGH: a bias-reduced approach for dynamic extreme Value-at-Risk estimation in financial time series

DOI10.1080/14697688.2022.2048061zbMath1497.91343arXiv2104.09879OpenAlexW3153582124MaRDI QIDQ5092644

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Publication date: 22 July 2022

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2104.09879

zbMATH Keywords

financial time seriesHill estimatorbias correctionGARCH modelvalue-at-risk (VaR)extreme value theory (EVT)

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical methods; risk measures (91G70) Extreme value theory; extremal stochastic processes (60G70)

Cites Work

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• Making and Evaluating Point Forecasts
• Adapting extreme value statistics to financial time series: dealing with bias and serial dependence
• Asymmetric Least Squares Estimation and Testing
• Estimation of extreme value-at-risk: an EVT approach for quantile GARCH model
• Kernel estimators for the second order parameter in extreme value statistics
• A note on the asymptotic variance at optimal levels of a bias-corrected Hill estimator
• A simple general approach to inference about the tail of a distribution
• Semi-parametric estimation of the second order parameter in statistics of extremes
• Extreme quantile estimation for \(\beta\)-mixing time series and applications
• Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
• Generalized autoregressive conditional heteroscedasticity
• Tail expectile process and risk assessment
• Bias correction in extreme value statistics with index around zero
• Coherent Measures of Risk
• COHERENCE AND ELICITABILITY
• Tail Index Estimation for a Filtered Dependent Time Series
• Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
• Estimation of Tail Risk Based on Extreme Expectiles
• Two-step methods in VaR prediction and the importance of fat tails
• Statistics of Extremes
• Backtesting expected shortfall and beyond
• Heavy-Tail Phenomena
• Estimating value-at-risk: a point process approach
• Extreme value theory versus traditional GARCH approaches applied to financial data: a comparative evaluation
• Alternatives to a semi-parametric estimator of parameters of rare events -- the jackknife methodology