Showing 1 - 10 of 14
This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter...
Persistent link: https://www.econbiz.de/10010266934
This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter...
Persistent link: https://www.econbiz.de/10005440044
This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the model generates...
Persistent link: https://www.econbiz.de/10008854426
-averse investor, regardless of the type of utility function, would be better-off using our model. -- Forecasting ; Fractional …
Persistent link: https://www.econbiz.de/10003876903
This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. By modelling the Cholesky factors of the covariance matrices, the model generates...
Persistent link: https://www.econbiz.de/10013132544
In this paper we introduce a new method of forecasting covariance matrices of large dimensions by exploiting the … conditions are very general and do not rely on distributional assumptions of the forecasting errors or on a particular model …
Persistent link: https://www.econbiz.de/10013038331
evaluation. An important implication is that forecasting superiority of models using high frequency data is likely to be …
Persistent link: https://www.econbiz.de/10013153598
This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter...
Persistent link: https://www.econbiz.de/10012750115
been proposed. A related strand of literature focuses on dynamic models and covariance forecasting for high-frequency data …, we address, is the relative importance of the quality of the realized measure as an input in a given forecasting model vs …
Persistent link: https://www.econbiz.de/10010608120
evaluation. An important implication is that forecasting superiority of models using high frequency data is likely to be …
Persistent link: https://www.econbiz.de/10008491711