Copula-based models provide a great deal of flexibility in modeling multivariate
distributions, allowing the researcher to specify the models for the marginal distributions …

This paper makes three contributions to the literature on forecasting stock returns. First,
unlike the extant literature on oil price and stock returns, we focus on out-of-sample …

This paper constructs a manager sentiment index based on the aggregated textual tone of
corporate financial disclosures. We find that manager sentiment is a strong negative …

Our paper reexamines whether 29 variables from 26 papers published after, as well as the
original 17 variables, were useful in predicting the equity premium in-sample and out-of …

We propose a new investor sentiment index that is aligned with the purpose of predicting the
aggregate stock market. By eliminating a common noise component in sentiment proxies …

We show that short interest is arguably the strongest known predictor of aggregate stock
returns. It outperforms a host of popular return predictors both in and out of sample, with …

We survey the literature on stock return forecasting, highlighting the challenges faced by
forecasters as well as strategies for improving return forecasts. We focus on US equity …

This paper contributes to the debate on the role of oil prices in predicting stock returns. The
novelty of the paper is that it considers monthly time-series historical data that span over 150 …

Academic research relies extensively on macroeconomic variables to forecast the US equity
risk premium, with relatively little attention paid to the technical indicators widely employed …

Our article comprehensively reexamines the performance of variables that have been
suggested by the academic literature to be good predictors of the equity premium. We find …