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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...
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Portfolio managers are rarely able to express views on expected returns in a quantitative way. This paper tackles this issue by proposing a simple framework which allows these views to be part of an efficient portfolio construction process. This approach accommodates both a wide range of...
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This chapter surveys recent econometric methodologies for inference in large dimensional conditional factor models in finance. Changes in the business cycle and asset characteristics induce time variation in factor loadings and risk premia to be accounted for. The growing trend in the use of...
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Testing procedures for predictive regressions with lagged autoregressive variables imply a suboptimal inference in presence of small violations of ideal assumptions. We propose a novel testing framework resistant to such violations, which is consistent with nearly integrated regressors and...
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