Abstract
Characteristic-sorted portfolios are the workhorses of modern empirical finance, deployed widely to evaluate anomalies and construct asset pricing models. We propose a new method for their estimation that is simple to compute; makes no ex-ante assumption on the nature of the relationship between the characteristic and returns; and does not require ad hoc selections of percentile breakpoints or portfolio weighting schemes. Characteristic portfolio weights are implied directly from data, through maximizing the expected value of a mean-variance utility function estimated non-parametrically over the cross section of the assets. To illustrate the method we use it to evaluate the size, value and momentum anomalies.
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