I apply a disciplined dimension reduction technique called Partial Least Square (PLS) to construct a new quality factor by aggregating... Show moreI apply a disciplined dimension reduction technique called Partial Least Square (PLS) to construct a new quality factor by aggregating information from 16 individual signals. It earns significant risk-adjusted returns and outperforms quality factors constructed by alternative techniques, namely, PCA, Fama-Macbeth regression, a combination of PCA and Fama-Mabeth regression and a Rank-based approach. I show that my quality factor performs even better during rough economic patches and thus appears to hedge periods of market distress. I further show adding our quality factor to an opportunity set consisting of the other classical factors increases the maximum Sharpe ratio. Show less
