Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

DOI10.1016/j.csda.2009.06.011zbMath1284.91579OpenAlexW2136186200WikidataQ34072988 ScholiaQ34072988MaRDI QIDQ2445744

I. Enriquez, Dipankar Bandyopadhyay, Victor Hugo Lachos, Carlos A. Abanto-Valle

Publication date: 14 April 2014

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2923593

Mathematics Subject Classification ID

Statistical methods; risk measures (91G70) Bayesian inference (62F15) Robustness and adaptive procedures (parametric inference) (62F35) Stochastic models in economics (91B70)

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Uses Software

• Scythe

Cites Work

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• On leverage in a stochastic volatility model
• Stochastic volatility with leverage: fast and efficient likelihood inference
• Bayesian analysis of stochastic volatility models with fat-tails and correlated errors
• Leverage, heavy-tails and correlated jumps in stochastic volatility models
• Block sampler and posterior mode estimation for asymmetric stochastic volatility models
• Generalized autoregressive conditional heteroscedasticity
• Markov chain Monte Carlo methods for stochastic volatility models.
• Markov chains for exploring posterior distributions. (With discussion)
• The multivariate skew-slash distribution
• Marginal Likelihood from the Gibbs Output
• Bayesian Inference for Nonlinear and Non-Gaussian Stochastic Volatility Model with Leverage Effect
• SCALE MIXTURES DISTRIBUTIONS IN STATISTICAL MODELLING
• Robust Estimation of the Mean and Covariance Matrix from Data with Missing Values
• The Price Variability-Volume Relationship on Speculative Markets
• Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• On Gibbs sampling for state space models
• Likelihood analysis of non-Gaussian measurement time series
• Filtering via Simulation: Auxiliary Particle Filters
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• The simulation smoother for time series models
• BAYESIAN REGRESSION ANALYSIS WITH SCALE MIXTURES OF NORMALS
• Robust Linear Mixed Models with Normal/Independent Distributions and Bayesian MCMC Implementation
• Portfolio Analysis in a Stable Paretian Market
• Bayesian modeling of financial returns: A relationship between volatility and trading volume
• Bayesian predictive information criterion for the evaluation of hierarchical Bayesian and empirical Bayes models
• A multi-move sampler for estimating non-Gaussian time series models: Comments on Shephard & Pitt (1997)
• Robust Estimates of Location: Survey and Advances
• Deviance information criteria for missing data models