Multivariate stochastic volatility with Bayesian dynamic linear models

DOI10.1016/j.jspi.2007.03.057zbMath1130.62105arXiv0802.0214OpenAlexW2053621553MaRDI QIDQ2474386

Kostas Triantafyllopoulos

Publication date: 6 March 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0802.0214

zbMATH Keywords

time seriesKalman filterGARCHforecastingvolatilitystate spaceBayesianmultivariatedynamic linear modelLondon metal exchange

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) 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

Parsimony inducing priors for large scale state-space models ⋮ A new filtering inference procedure for a GED state-space volatility model ⋮ Multi-variate stochastic volatility modelling using Wishart autoregressive processes ⋮ A tractable state-space model for symmetric positive-definite matrices ⋮ Hellinger distance and non-informative priors ⋮ Bound and convergence of the non-constant dynamic linear model ⋮ Multivariate Stochastic Volatility Estimation Using Particle Filters

Uses Software

• RiskMetrics

Cites Work

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