We develop an exact and distribution-free procedure to test for quantile predictability at several quantile levels jointly, while allowing for an endogenous predictive regressor with any degree of persistence. The approach proceeds by combining together the quantile regression t-statistics from...

We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances. In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear...

We develop a simulation-based procedure to test for stock return predictability with multiple regressors. The process governing the regressors is left completely free and the test procedure remains valid in small samples even in the presence of non-normalities and GARCH-type effects in the stock...

We find strong evidence of a funding risk premium in the cross-section of asset returns. Our estimate for the price of funding risk is robust across Treasury bonds, corporate bonds, equities, and hedge funds. Funding shocks pose a risk to investors because they exacerbate the illiquidity and...

We propose an asset pricing model featuring both limited participation and heterogeneity, in which agents randomly participate in the bond and stock markets according to a probability that depends on their non-financial income. We develop an indirect inference method to estimate our model on...

We combine high-frequency stock returns with risk-neutralization to extract the daily common component of tail risks perceived by investors in the cross-section of firms. We find that our tail risk measure significantly predicts the equity premium, variance risk premium and realized moments of...