We introduce a new text-mining methodology that extracts sentiment information from news articles to predict asset returns. Unlike more common sentiment scores used for stock return prediction (e.g., those sold by commercial vendors or built with dictionary-based methods), our supervised...

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands/U.K. (1629-1812), U.K. (1813-1870) and U.S. (1871-2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for...

A central challenge in asset pricing is the weak connection between stock returns and observable economic fundamentals. We provide evidence that this connection is stronger than previously thought. We use a modified version of the Bry-Boschan algorithm to identify long-run swings in the stock...

A single macroeconomic factor based on growth in the capital share of aggregate income exhibits significant explanatory power for expected returns across a range of equity characteristic portfolios and non-equity asset classes, with risk price estimates that are of the same sign and similar in...

This article examines the performance of various financial variables as predictors of subsequent U.S. recessions. Series such as interest rates and spreads, stock prices, currencies, and monetary aggregates are evaluated singly and in comparison with other financial and non-financial indicators....

This paper uses aggregate Japanese data and sectoral U.S. data to explore the properties of the joint behavior of stock prices and total factor productivity (TFP) with the aim of highlighting data patterns that are useful for evaluating business cycle theories. The approach used follows that...

We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...

A consensus has recently emerged that variables beyond the level, slope, and curvature of the yield curve can help predict bond returns. This paper shows that the statistical tests underlying this evidence are subject to serious small-sample distortions. We propose more robust tests, including a...

We propose that innovative originality (InnOrig) is a valuable organizational resource, and that owing to limited investor attention and skepticism of complexity, firms with greater InnOrig are undervalued. We find that firms' InnOrig strongly predicts higher, more persistent, and less volatile...

We present a dynamic model that links characteristic-based return predictability to systematic factors that determine the evolution of firm fundamentals. In the model, an economy-wide disruption process reallocates profits from existing businesses to new projects and thus generates a source of...