Tail behavior and dependence structure in the APARCH model

DOI10.1515/jtse-2016-0002zbMath1499.62308OpenAlexW2148529599MaRDI QIDQ1695685

Farrukh Javed, Krzysztof Podgórski

Publication date: 7 February 2018

Published in: Journal of Time Series Econometrics (Search for Journal in Brave)

Full work available at URL: https://lup.lub.lu.se/record/8052644

zbMATH Keywords

estimationheavy tailsleverage effecttime series models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Cites Work

• Financial modeling under non-Gaussian distributions.
• Conditional volatility, skewness, and kurtosis: Existence, persistence, and comovements
• Fat tails and asymmetry in financial volatility models.
• Arch model with Box-Cox transformed dependent variable
• Implied volatility and skewness surface
• EGARCH models with fat tails, skewness and leverage
• Leverage effect for volatility with generalized Laplace error
• Analytical derivates of the APARCH model
• Generalized autoregressive conditional heteroscedasticity
• The efficiency of the estimators of the parameters in GARCH processes.
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model
• The Estimation of Leverage Effect With High-Frequency Data
• Inference in Arch and Garch Models with Heavy-Tailed Errors
• Contemporaneous asymmetry in GARCH processes
• Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities

This page was built for publication: Tail behavior and dependence structure in the APARCH model