Probability weighting and equity premium prediction: Investing with optimism

Abstract

Empirically motivated theoretical models of probability weighting which overweight tail events are finding many applications in finance. However, probability weighting has not yet been applied to equity premium prediction or to constructing optimal market timing investment strategies. We show that a measure of market optimism from a representative agent asset pricing model with probability weighting can be used to construct optimal dynamic investment strategies that outperform the buy-and-hold strategy and strategies generated by 17 leading equity premium predictors. We further show that this theory-based measure of market optimism predicts the equity premium and market Sharpe ratio in-sample and out-of-sample. The predictability is not subsumed by disaster probabilities, market sentiment, or market skewness. Our results indicate that our theory-based measure provides a distinct channel for predicting aggregate stock returns.