Through extending a standard Grossman and Stiglitz (1980) noisy rational expectations economy by a heterogeneous signal structure with signal-specific differences in uncertainty, we show that price momentum as well as reversal are not intrinsically at odds with rational behavior. Differences in...

Three concepts: stochastic discount factors, multi-beta pricing and mean-variance efficiency, are at the core of modern empirical asset pricing. This chapter reviews these paradigms and the relations among them, concentrating on conditional asset-pricing models where lagged variables serve as...

We consider a canonical asset pricing model, where agents with quadratic preferences are allowed to retrade a limited set of securities over multiple periods, after which these securities expire, and agents consume their liquidation values. A key assumption in this model is that agents have...

We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...

We investigate intermediary asset pricing theories empirically and find strong support for models that have intermediary leverage as the relevant state variable. A parsimonious model that uses detrended dealer leverage as a price-of-risk variable, and innovations to dealer leverage as a pricing...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form Efficient Market Hypothesis). We do...

We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the Efficient Market Hypothesis). We do not...

We show empirically that survey-based measures of expected inflation are significant and strong predictors of future aggregate stock returns in several industrialized countries both in-sample and out-of-sample. By empirically discriminating between competing sources of this return predictability...

We propose a novel reinforcement learning approach to extract high-frequency aggregate growth expectations from asset prices. While much expectations-based research in macroeconomics and finance relies on low-frequency surveys, the multitude of events that pass between survey dates renders...