We provide a reduced-rank approach (RRA) to extract a few factors from a large set of factor proxies and apply the extracted factors to model the cross-section of expected stock returns. Empiricall…
This paper proposes a novel supervised learning technique for forecasting: scaled principal component analysis (sPCA). The sPCA improves the traditional principal component analysis (PCA) by scalin…
We propose an optimal combining strategy to mitigate estimation risk for the popular mean-variance portfolio choice problem in the case without a risk-free asset. We find that our strategy performs…
We examine the macro-spanning hypothesis for bond returns in international markets. Based on a large panel of real-time macroeconomic variables that are not subject to revisions, we find that globa…