A new approach to Value-at-Risk: GARCH-TSLx model with inference

DOI10.1080/03610918.2018.1535069zbMath1489.62324OpenAlexW2908005434WikidataQ128680694 ScholiaQ128680694MaRDI QIDQ5083929

Emrah Altun

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1535069

zbMATH Keywords

GARCHvalue-at-riskvolatilityLomax distributionGJR-GARCH

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) Reliability and life testing (62N05)

Uses Software

• StFinMetrics

Cites Work

• Unnamed Item
• Generalized autoregressive conditional heteroscedasticity
• The use of GARCH models in VaR estimation
• An extended Lomax distribution
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Forecasting VaR models under Different Volatility Processes and Distributions of Return Innovations
• A new generalization of skew-T distribution with volatility models
• The gamma-Lomax distribution
• Marshall–Olkin Extended Lomax Distribution and Its Application to Censored Data
• Business Failures: Another Example of the Analysis of Failure Data

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