I introduce dynamic option trading and non-linear views into the classical portfolio selection problem. The optimal dynamic option portfolio is characterized explicitly in terms of its expected sensitivities (Greeks) and the role of the mean-variance effi cient portfolio is played by the "Greek...

We derive representations for the stock price drift and volatility in the equilibrium of agents with arbitrary, heterogeneous utility functions and with the aggregate dividend following an arbitrary Markov diffusion. We introduce a new, intrinsic characteristic of the aggregate dividend process...

This paper presents an equilibrium model in a pure exchange economy when investors have three possible sources of heterogeneity. Investors may differ in their beliefs, in their level of risk aversion and in their time preference rate. We study the impact of investors heterogeneity on the...

We study survival, price impact and portfolio impact in heterogeneous economies. We show that, under the equilibrium risk-neutral measure, long-run price impact is in fact equivalent to survival, whereas longrun portfolio impact is equivalent to survival under an agent-specific, wealth-forward...

We provide a representation for the nonmyopic optimal portfolio of an agent consuming only at the terminal horizon when the single state variable follows a general di usion process and the market consists of one risky asset and a risk-free asset. The key term of our representation is a new...

We introduce a new class of momentum strategies, the risk-adjusted time series momentum (RAMOM) strategies, which are based on averages of past futures returns, normalized by their volatility. We test these strategies on a universe of 64 liquid futures contracts and show that RAMOM strategies...

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

We solve the problem of optimal risk management for an investor holding an illiquid, alpha generating fund and hedging his position with a liquid futures contract. When the investor is subject to a drawdown constraint, he is forced to reduce the total risk of his portfolio after a drawdown. In...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance—in terms of SDF Sharpe ratio and average pricing errors—is improving in model parameterization (or “complexity”). Our results predict that the best...

We investigate the performance of non-linear return prediction models in the high complexity regime, i.e., when the number of model parameters exceeds the number of observations. We document a "virtue of complexity" in all asset classes that we study (US equities, international equities, bonds,...