Forecasting VaR models under Different Volatility Processes and Distributions of Return Innovations

DOI10.1002/FOR.2303zbMath1397.91597OpenAlexW2104122754MaRDI QIDQ4687527

Elias Tzavalis, Yiannis Dendramis, Giles E. Spungin

Publication date: 12 October 2018

Published in: Journal of Forecasting (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/for.2303

zbMATH Keywords

skewed distributionsextreme value theoryrisk measuresregime-switching modelsvalue at riskout-of-sample

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Related Items (6)

Shifts in volatility driven by large stock market shocks ⋮ A new approach to Value-at-Risk: GARCH-TSLx model with inference ⋮ The improved value-at-risk for heteroscedastic processes and their coverage probability ⋮ Augmenting the realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects ⋮ A new generalization of skew-T distribution with volatility models ⋮ Two-sided exponential-geometric distribution: inference and volatility modeling

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