How to mitigate the impact of inappropriate distributional settings when the parametric value-at-risk approach is used

DOI10.1080/14697688.2012.738934zbMath1294.91198OpenAlexW2027763458MaRDI QIDQ2879030

Jung-Bin Su

Publication date: 5 September 2014

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

Full work available at URL: https://doi.org/10.1080/14697688.2012.738934

zbMATH Keywords

value at risk (VaR)parametric approachautoregressive jump intensity (ARJI)filter historical simulationskewed generalized error distribution

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Related Items (1)

How does the choice of Value-at-Risk estimator influence asset allocation decisions?

Uses Software

• RiskMetrics

Cites Work

• Bootstrap methods: another look at the jackknife
• Estimation of stochastic volatility models with diagnostics
• Financial Data and the Skewed Generalized T Distribution
• A Test for Normality of Observations and Regression Residuals

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