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 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...

Contrary to conventional wisdom in nance, return prediction R2 and optimal portfolio Sharpe ratio generally increase with model parameterization, even when minimal regularization is used. We theoretically characterize the behavior of return prediction models in the high complexity regime, i.e....

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 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 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 study the market price of risk, the stock volatility and the hedging behavior in equilibrium of heterogeneous agents with arbitrary utility functions, consuming only at the end of the time horizon, and with the state variable following an arbitrary homogeneous diffusion process. We introduce...

We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading...