Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance

DOI10.1016/j.jeconom.2015.03.020zbMath1337.62317OpenAlexW2148364833MaRDI QIDQ888317

Michael McAleer, Manabu Asai

Publication date: 30 October 2015

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10092/10054

zbMATH Keywords

dimension reductionlong memoryfactor modelrealized volatilitymultivariate stochastic volatilityleverage effects

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) 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) Economic time series analysis (91B84)

Related Items (7)

A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio ⋮ Frontiers in time series and financial econometrics: an overview ⋮ Dynamic correlation multivariate stochastic volatility with latent factors ⋮ Modeling realized covariance measures with heterogeneous liquidity: a generalized matrix-variate Wishart state-space model ⋮ Dynamic principal component CAW models for high-dimensional realized covariance matrices ⋮ The impact of jumps and leverage in forecasting covolatility ⋮ Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers

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