We show that the introduction of a leverage constraint improves the practical implementation of characteristics-based portfolios. The addition of the constraint leads to significantly lower transaction costs, to a reduction of negative portfolio weights, and to a decrease in volatility and misspecification risk. Furthermore, it allows investors to implement any desired level of leverage. In this study, we include 12 characteristics, thereby extending the classical size, book-to-market and momentum paradigm. We report several key indicators such as the proportion of negative weights, Sharpe ratio, volatility, transaction costs, the transaction cost-adjusted certainty equivalent returns, and the Herfindahl–Hirschman index. Analyzing the sensitivity of these key indicators to the choice of multiple combinations of the 12 characteristics, to risk aversion, and to estimation sample size, we show that constrained policies are much less sensitive to these parameters than their unconstrained counterparts. Finally, for quadratic utility, we derive a semi-closed analytical form for the portfolio weights. Overall, we provide a comprehensive extension of characteristics-based portfolio choice and contribute to a better understanding and implementation of the allocation process.

We examine the asset pricing implications of sustainability in commodity markets. We focus on metals and agricultural goods, for which we collect production-based environmental footprint data, namely greenhouse gas emissions and water consumption. We then build green-minus-brown portfolios and find no evidence that sustainability is priced in the cross-section of metals’ and agricultural commodities’ returns. We also document strong welfare benefits when diversifying equity and bond allocations with low-carbon commodities. Investor welfare, measured by the certainty equivalent return, increases by 22% when the commodity share is 20%. These results reveal the dual opportunities, both financial and environmental, brought by low footprint commodities.