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Large dynamic covariance matrices
Engle, Robert F.; Ledoit, Olivier; Wolf, Michael - 2017
for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH/GARCH …
Persistent link: https://www.econbiz.de/10011663190
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Beyond sorting: A more powerful test for cross-sectional anomalies
Ledoit, Olivier; Wolf, Michael; Zhao, Zhao - 2016
Many researchers seek factors that predict the cross-section of stock returns. The standard methodology sorts stocks according to their factor scores into quantiles and forms a corresponding long-short portfolio. Such a course of action ignores any information on the covariance matrix of stock...
Persistent link: https://www.econbiz.de/10011663197
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Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails
Zhang, Xin; Creal, Drew; Koopman, Siem Jan; Lucas, Andre - 2011
We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...
Persistent link: https://www.econbiz.de/10010326055
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Multivariate volatility modeling of electricity futures
Bauwens, Luc; Hafner, Christian M.; Pierret, Diane - 2011
estimate nonparametrically. For the short-run dynamics, we use a GJR-GARCH model for the conditional variances and augmented …
Persistent link: https://www.econbiz.de/10010330971
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Do we need non-linear models to predict REIT returns?
Case, Brad; Guidolin, Massimo; Yildirim, Yildiray - 2013
model relative to even very complex multivariate GARCH specifications, recently reported in the literature using measures of …-of-sample forecast tests indicate that the four-regime MS model is, indeed, superior to all of the GARCH specifications in forecasting …-asset return covariances, however, the MS model is surprisingly superior to all of the GARCH models. …
Persistent link: https://www.econbiz.de/10010409448
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Modelling Dynamic Conditional Correlations in WTI Oil Forward and Futures Returns
Manera, Matteo; Lanza, Alessandro; McAleer, Michael - 2004
This paper estimates the dynamic conditional correlations in the returns on WTI oil one-month forward prices, and one-, three-, six-, and twelve-month futures prices, using recently developed multivariate conditional volatility models. The dynamic correlations enable a determination of whether...
Persistent link: https://www.econbiz.de/10011324947
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Conditional Correlations in the Returns on Oil Companies Stock Prices and Their Determinants
Manera, Matteo; Giovannini, Massimo; Grasso, Margherita; … - 2004
cointegration techniques in modelling the conditional mean, as well as multivariate GARCH models for the conditional variances. We … specifiy the conditional variances of VECM residuals with the Constant Conditional Correlation (CCC) multivariate GARCH model … of Bollerslev (1990) and the Dynamic Conditional Correlation (DCC) multivariate GARCH model of Engle (2002). The "within …
Persistent link: https://www.econbiz.de/10011324953
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Factor models for portfolio selection in large dimensions: The good, the better and the ugly
De Nard, Gianluca; Ledoit, Olivier; Wolf, Michael - 2018
This paper injects factor structure into the estimation of time-varying, large-dimensional covariance matrices of stock returns. Existing factor models struggle to model the covariance matrix of residuals in the presence of conditional heteroskedasticity in large universes. Conversely,...
Persistent link: https://www.econbiz.de/10011969201
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The power of (non-)linear shrinking: A review and guide to covariance matrix estimation
Ledoit, Olivier; Wolf, Michael - 2019
Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance...
Persistent link: https://www.econbiz.de/10012026512
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The power of (non-)linear shrinking: A review and guide to covariance matrix estimation
Ledoit, Olivier; Wolf, Michael - 2020
Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance...
Persistent link: https://www.econbiz.de/10012166460