Multivariate Stochastic Volatility with Large and Moderate Shocks

Autor:	Panayotis G. Michaelides, Marwan Izzeldin, Mike G. Tsionas
Rok vydání:	2019
Předmět:	Statistics and Probability Economics and Econometrics Multivariate statistics Stochastic volatility Model selection 05 social sciences Bayesian probability MathematicsofComputing_NUMERICALANALYSIS Univariate 0502 economics and business Prior probability Covariate Econometrics Economics 050207 economics Statistics Probability and Uncertainty Volatility (finance) Social Sciences (miscellaneous) 050205 econometrics
Zdroj:	Journal of the Royal Statistical Society Series A: Statistics in Society. 182:887-917
ISSN:	1467-985X 0964-1998
DOI:	10.1111/rssa.12443
Popis:	Summary The paper proposes a multivariate stochastic volatility model where shifts in volatility are endogenously driven by large return shocks. The model proposed generalizes the univariate stochastic volatility model of Dendramis and colleagues to a multivariate context. Allowing for multivariate dependence permits the volatility of common return factors to affect individual stock returns volatility jointly. The model is further extended to allow for endogenous thresholds that depend on covariates. Model selection priors are introduced and the new techniques are applied by using data from the FTSE100-index.
Databáze:	OpenAIRE
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