The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model

DOI10.1111/1368-423X.00070zbMath1048.91065OpenAlexW2024726293MaRDI QIDQ4549742

Morten B. Jensen, Asger Lunde

Publication date: 31 October 2002

Published in: The Econometrics Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1368-423x.00070

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70)

Related Items (11)

Option valuation with conditional skewness ⋮ Practical implications of higher moments in risk management ⋮ Augmenting the realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects ⋮ Tail behavior and dependence structure in the APARCH model ⋮ A Markov-switching regression model with non-Gaussian innovations: estimation and testing ⋮ Value at Risk with time varying variance, skewness and kurtosis-the NIG-ACD model ⋮ An empirical evaluation of fat-tailed distributions in modeling financial time series ⋮ Bayesian estimation of NIG models via Markov chain Monte Carlo methods ⋮ On the stationary version of the generalized hyperbolic ARCH model ⋮ Simulation and Estimation of the Meixner Distribution ⋮ A COMPARISON OF PRICING KERNELS FOR GARCH OPTION PRICING WITH GENERALIZED HYPERBOLIC DISTRIBUTIONS

This page was built for publication: The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model