We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

Behavioral finance presented in Finance for Normal People is a second generation behavioral finance. The first generation, starting in the early 1980s, largely accepted standard finance's notion of people's wants as “rational” wants – restricted to the utilitarian benefits of high returns...

There are three fundamental ways of testing the validity of an investment algorithm against historical evidence: a) the walk-forward method; b) the resampling method; and c) the Monte Carlo method. By far the most common approach followed among academics and practitioners is the walk-forward...

A war-related factor model derived from textual analysis of media news reports explains the cross section of expected asset returns. Using a semi-supervised topic model to extract discourse topics from 7,000,000 New York Times stories spanning 160 years, the war factor predicts the cross section...

Using a semi-supervised topic model on 7,000,000 New York Times articles spanning 160 years, we test whether topics of media discourse predict future stock and bond market returns to test rational and behavioral hypotheses about market valuation of disaster risk. Focusing on media discourse...

When the pricing kernel is U-shaped, then expected returns of claims with payout on the upside are negative for strikes beyond a threshold, determined by the slope of the U-shaped kernel in its increasing region, and have negative partial derivative with respect to strike in the increasing...

A growing literature analyzes the cross-section of single stock option returns, virtually always under the (implicit or explicit) assumption of a monotonically decreasing pricing kernel. Using option returns, we non-parametrically provide significant and robust evidence that the pricing kernel...

We build a model of the law of small numbers (LSN)--the incorrect belief that even small samples represent the properties of the underlying population--to study its implications for trading behavior and asset prices. In our model, a belief in the LSN induces investors to expect short-term price...

We estimate a dynamic asset pricing model characterized by heterogeneous boundedly rational agents. The fundamental value of the risky asset is publicly available to all agents, but they have different beliefs about the persistence of deviations of stock prices from the fundamental benchmark. An...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies - momentum. We find that momentum has earned abnormally high risk-adjusted returns - a...