Abstract:In this paper, we build efficient portfolios using different frameworks proposed in the literature with several datasets containing an increasing number of predictors as conditioning information. We carry an extensive empirical study to investigate several approaches to impose sparsity and dimensionality reduction, as well as possible latent factors driving the returns of the risky assets. In contrast to previous studies that made use of naive OLS and low-dimension information sets, we find that (i) accounting… Show more
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