Working Paper: NBER ID: w10996
Authors: Michael W. Brandt; Pedro Santa-Clara; Rossen Valkanov
Abstract: We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies.
Keywords: No keywords provided
JEL Codes: G0; G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| firm characteristics (L20) | optimal portfolio weights (G11) |
| smaller firms (L25) | overrepresentation in optimal portfolio (G11) |
| high book-to-market ratios (G32) | overrepresentation in optimal portfolio (G11) |
| high lagged returns (G17) | overrepresentation in optimal portfolio (G11) |
| deviations from market capitalization weights (G19) | function of firm characteristics (D21) |
| optimal deviations from market cap weights (G11) | investor preferences not aligned with market equilibrium (G19) |