Abstract
We present a stock selection methodology that maximizes the expected returns of equity portfolios by efficiently managing their exposures to a given ensemble of risk premia, also known as factors. Our approach is mathematically grounded, robust in its design, and applicable in practice. It addresses several issues specific to factor-investing, such as cross-sectional interactions between factors, the mismatch between the factors performance cycles and typical rebalancing periods, or the mitigation of interactions between the capital allocation schemes and factor exposures.
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