Publication: Factor models for portfolio selection in large dimensions: the good, the better and the ugly
Factor models for portfolio selection in large dimensions: the good, the better and the ugly
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De Nard, G., Ledoit, O., & Wolf, M. (2021). Factor models for portfolio selection in large dimensions: the good, the better and the ugly. Journal of Financial Econometrics, 19(2), 236–257. https://doi.org/10.1093/jjfinec/nby033
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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 time-varying conditional heteroskedasticity in large universes. Conversely, rotation-equivariant estimators of large-dimensional time-varying covariance matrices forsake directional information embedded in market-wide risk factors. We introduce a new covariance matrix estimator that blends factor structure with tim
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De Nard, G., Ledoit, O., & Wolf, M. (2021). Factor models for portfolio selection in large dimensions: the good, the better and the ugly. Journal of Financial Econometrics, 19(2), 236–257. https://doi.org/10.1093/jjfinec/nby033
