In this paper, we document evidence that downside betas tend to comove more than upside betas during a financial crisis, but upside betas tend to comove more than the downside betas during financial booms. We find that the asymmetry between Downside-Beta Comovement and Upside-Beta Comovement is...

We present a new theory of asset pricing and portfolio choices under asymmetric reasoning, contrast the predictions with those under asymmetric information, and present experimental evidence in favor of our theory. The Efficient Markets Hypothesis and its formal foundation, the Rational...

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...

A growing literature uses portfolio holdings data to quantify the impact of investor demand on equilibrium prices via counterfactual experiments. The key parameter in relating demand and equilibrium prices is investors’ elasticity of demand with respect to the price. Unlike previous studies,...

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 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...

Empirical studies investigate various causes and effects of sustainable investments. While some attempts have been made to describe the results found by theoretical models, these are relatively complex and idiosyncratic. We relate to existing studies and use a parsimonious CAPM in which we model...

We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...

Many bond portfolio managers argue that bond laddering tends to outperform other bond investment strategies because it reduces both market price risk and reinvestment risk for a bond portfolio in the presence of interest rate uncertainty. Despite the popularity of bond ladders as a strategy for...

A random variable dominates another random variable with respect to the covariance order if the covariance of any two monotone increasing functions of this variable is smaller. We characterize completely the covariance order, give strong sufficient conditions for it, present a number of examples...