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On portfolio optimization : forecasting covariances and choosing the risk model
Chan, Louis K. C.; Karceski, Jason; Lakonishok, Josef - 1999
Persistent link: https://www.econbiz.de/10001378371
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Time-varying betas and asymmetric effects of news : empirical analysis of blue chip stocks
Cho, Young-hye; Engle, Robert F. - 1999
Persistent link: https://www.econbiz.de/10001417230
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Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2021 - This version: June 2021
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how...
Persistent link: https://www.econbiz.de/10012584099
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Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2022 - This version: January 2022
Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how...
Persistent link: https://www.econbiz.de/10013040932
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Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2020
Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did not perform well in large dimensions due to the...
Persistent link: https://www.econbiz.de/10012253083