Generalized EGARCH Random Effect Models Application to Financial Time Series

DOI10.1080/03610918.2010.503016zbMath1205.62127OpenAlexW1973584122MaRDI QIDQ3072385

Edilberto Cepeda-Cuervo

Publication date: 3 February 2011

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

Full work available at URL: https://doi.org/10.1080/03610918.2010.503016

zbMATH Keywords

MCMC methodsBayesian methodologyfinancial time seriesGARCH modelsvolatility modelsEGARCH 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) Bayesian inference (62F15)

Cites Work

• ARCH modeling in finance. A review of the theory and empirical evidence
• Generalized autoregressive conditional heteroscedasticity
• BUGS for a Bayesian analysis of stochastic volatility models
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• The Price Variability-Volume Relationship on Speculative Markets
• MODELING STOCHASTIC VOLATILITY: A REVIEW AND COMPARATIVE STUDY

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