This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...

We present an alternative expectation formation mechanism that helps rationalize well known asset pricing anomalies, such as the predictability of excess returns, excess volatility, and the equity-premium puzzle. As with rational expectations (RE), the expectation formation mechanism we consider...

This paper is an investigation into the determinants of asymmetries in stock returns. We develop a series of cross-sectional regression specifications which attempt to forecast skewness in the daily returns of individual stocks. Negative skewness is most pronounced in stocks that have...

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...

Recent studies have used the value spread to predict aggregate stock returns to construct cash-flow betas that appear to explain the size and value anomalies. We show that two related variables, the book-to-market spread (the book-to-market of value stocks minus that of growth stocks) and the...

We ask whether stock returns in France, Germany, Japan, the UK and the US are predictable by three instruments: the dividend yield, the earnings yield and the short rate. The predictability regression is suggested by a present value model with earnings growth, payout ratios and the short rate as...

The aggregate dividend payout ratio forecasts aggregate excess returns on both stocks and corporate bonds in post-war US data. Both high corporate profits and high stock prices forecast low excess returns on equities. When the payout ratio is high, expected returns are high. The payout ratio's...

We construct portfolios of stocks and of bonds that are maximally predictable with respect to a set of ex ante observable economic variables, and show that these levels of predictability are statistically significant, even after controlling for data-snooping biases. We disaggregate the sources...

The predictability of monthly stock returns is investigated from the perspective of a risk-averse investor who uses the data to update initially vague beliefs about the conditional distribution of returns. The optimal stocks-versus-cash allocation of the investor can depend importantly on the...

Recent research suggests that stock returns are predictable from fundamentals such as dividend yield, and that the degree of predictability rises with the length of the horizon over which return is measured. This paper investigates the magnitude of two sources of small simple bias in these...