"It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns,...

It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns,...

It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns,...

This paper analyzes the effect of non-constant elasticity of the pricing kernel on asset return characteristics in a rational expectations model. It is shown that declining elasticity of the pricing kernel can lead to predictability of asset returns and high and persistent volatility. Also,...

I generalize the long-run risks (LRR) model of Bansal and Yaron (2004) by incorporating recursive smooth ambiguity aversion preferences from Klibanoff et al. (2005, 2009) and time-varying ambiguity. Relative to the Bansal-Yaron model, the generalized LRR model is as tractable but more flexible...