This paper proposes that leverage aversion be introduced into portfolio theory, and that leverage aversion be considered along with volatility aversion in determining optimal portfolios. Mean-variance-leverage optimization results in a three-dimensional mean-variance-leverage efficient surface,...

We propose that portfolio theory and mean-variance optimization be augmented to incorporate investor aversion to leverage and suggest a specification for leverage aversion that captures the unique risks of leverage. We also introduce mean-variance-leverage efficient frontiers, compare them with...

An asynchronous discrete-time model run in "dynamic mode" can model the effects on market prices of changes in strategies, leverage, and regulations, or the effects of different return estimation procedures and different trading rules. Run in "equilibrium mode," it can be used to arrive at...

The mean-variance-leverage (MVL) optimization model (Jacobs and Levy 2012, 2013a) tackles an issue not dealt with by the mean-variance optimization inherent in the general mean-variance portfolio selection model (GPSM) — that is, the impact on investor utility of the risks that are unique to...

Optimization of long-short portfolios through the use of fast algorithms takes advantage of models of covariance to simplify the equations that determine optimality. Fast algorithms exist for widely applied factor and scenario analysis for long-only portfolios. To allow their use in factor and...

Smart beta strategies aim to outperform the capitalization-weighted market through relatively simple alternative weighting methods that emphasize a handful of factors such as size, value, momentum, or low volatility. Because of their simplicity, smart beta strategies bear a resemblance to...