Abstract
Alpha modelling typically refers to the selection and weighting of various information sources, which when combined are used by active portfolio managers to forecast security returns. It is traditionally seen as an exogenous input in the construction of the investment portfolio. Instead, a growing number of authors have recently argued that alpha modelling should be integrated within the portfolio-construction process, to account for the active manager’s objective, constraints and transaction costs. Building in particular upon the frameworks of Sneddon (2008) and Qian et al (2007), we present a parsimonious and analytically tractable alpha modelling approach that aims at maximising the typical objective function of an active manager. Our modelling scheme combines several salient features of previous methodologies and explicitly identifies three critical components necessary in achieving the manager’s portfolio objectives: (i) the predictability of alpha factors as captured by their information decay; (ii) the contribution of alpha factors to portfolio risk; and (iii) the autocorrelations of alpha factors in their contribution to portfolio turnover. Our methodology is able to provide various prescriptions relevant to the portfolio manager. For instance, as transaction costs increase, allocating more weight to signals with lower information decay is shown to improve portfolio value added. Factors with higher return-to-risk ratios are also given a higher prominence as they help allocate strategy risk more efficiently.
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