Multi-variate stochastic volatility modelling using Wishart autoregressive processes

DOI10.1111/j.1467-9892.2011.00738.xzbMath1300.62083arXiv1311.0530OpenAlexW1792120675MaRDI QIDQ2930900

Kostas Triantafyllopoulos

Publication date: 20 November 2014

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1311.0530

zbMATH Keywords

covariancefinancial time seriesBayesian forecastingWishart processmulti-variate volatility

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) Statistical methods; risk measures (91G70) Bayesian inference (62F15) Economic time series analysis (91B84)

Related Items (5)

A new filtering inference procedure for a GED state-space volatility model ⋮ Comment on article by Windle and Carvalho ⋮ Multivariate Stochastic Volatility Estimation Using Particle Filters ⋮ Bayesian semiparametric modeling of realized covariance matrices ⋮ Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility

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