On conditional risk estimation considering model risk

DOI10.1080/02664763.2015.1100595OpenAlexW1911597977MaRDI QIDQ5138086

Fedya Telmoudi, Mohamed Limam, Mohamed El Ghourabi

Publication date: 3 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2015.1100595

zbMATH Keywords

model riskGARCH modelsconditional value at riskartificial intelligence modelsLS-SVRspareness

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Value-at-risk estimation by LS-SVR and FS-LS-SVR based on GAS model ⋮ Nonparametric predictive inference for American option pricing based on the binomial tree model

Uses Software

• Wiener-Hammerstein Benchmark

Cites Work

• Benchmarking least squares support vector machine classifiers
• Asymptotic normality of support vector machine variants and other regularized kernel methods
• Financial forecasting using support vector machines
• Generalized autoregressive conditional heteroscedasticity
• Weighted least squares support vector machines: robustness and sparse approximation
• Support vector machine as an efficient framework for stock market volatility forecasting
• Support Vector Machines
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation