MCMC Bayesian Estimation in FIEGARCH Models

DOI10.1080/03610918.2014.932800zbMath1349.62426arXiv1304.1733OpenAlexW1996378294MaRDI QIDQ2828706

Sílvia R. C. Lopes, Taiane Schaedler Prass, Jorge Alberto Achcar

Publication date: 26 October 2016

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

Full work available at URL: https://arxiv.org/abs/1304.1733

zbMATH Keywords

long-range dependenceBayesian inferenceMCMCFIEGARCH processes

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)

Related Items (1)

A Bayesian approach for estimating the parameters of an α-stable distribution

Cites Work

• Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH
• Fractionally integrated generalized autoregressive conditional heteroskedasticity
• Time series: theory and methods.
• The detection and estimation of long memory in stochastic volatility
• Inference from iterative simulation using multiple sequences
• Theoretical results on fractionally integrated exponential generalized autoregressive conditional heteroskedastic processes
• Generalized autoregressive conditional heteroscedasticity
• Modeling and pricing long memory in stock market volatility
• BUGS for a Bayesian analysis of stochastic volatility models
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Simulation Run Length Control in the Presence of an Initial Transient
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Monte Carlo sampling methods using Markov chains and their applications

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