Regular Variation and Extremal Dependence of GARCH Residuals with Application to Market Risk Measures
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Publication:3615082
DOI10.1080/07474930802387985zbMath1161.62072OpenAlexW2081252940MaRDI QIDQ3615082
Jonathan A. Tawn, Fabrizio Laurini
Publication date: 17 March 2009
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07474930802387985
regular variationvalue-at-riskgeneralized Pareto distributionextremal dependencedeclusteringexpected shortfalls
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistics of extreme values; tail inference (62G32)
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Cites Work
- Unnamed Item
- Extremes and related properties of random sequences and processes
- Extreme values for stationary and Markov sequences
- Random difference equations and renewal theory for products of random matrices
- A simple general approach to inference about the tail of a distribution
- ARCH models and financial applications
- Generalized autoregressive conditional heteroscedasticity
- Limit theory for the sample autocorrelations and extremes of a GARCH \((1,1)\) process.
- New estimators for the extremal index and other cluster characteristics
- Coherent Measures of Risk
- Clusters of Extreme Observations and Extremal Index Estimate in GARCH Processes
- Statistics for near independence in multivariate extreme values
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Concomitant tail behaviour for extremes
- Diagnostics for Dependence within Time Series Extremes
- Inference for Clusters of Extreme Values
- Extremes of Markov Chains with Tail Switching Potential
- Extremes and local dependence in stationary sequences
- A Conditional Approach for Multivariate Extreme Values (with Discussion)
- Estimation of value at risk by extreme value methods
- An introduction to statistical modeling of extreme values
- Dependence measures for extreme value analyses