Stock Returns: Characteristics and Factors

Paper Session

Sunday, Jan. 8, 2017 1:00 PM – 3:00 PM

Sheraton Grand Chicago, Sheraton Ballroom V
Hosted By: American Finance Association
  • Chair: Jonathan Lewellen, Dartmouth College

Why Do Discount Rates Vary?

Serhiy Kozak
,
University of Michigan
Shrihari Santosh
,
University of Maryland

Abstract

We argue that the price of “discount-rate” risk reveals whether increases in equity risk premia represent “good” or “bad” news to rational investors. We employ a new empirical methodology and find that the price is negative, contrary to previous estimates. This finding supports equilibrium models with stochastic technology or preferences as the drivers of time-varying expected returns, but is inconsistent with canonical models of sentiment. Our approach relies on using future realized market returns to consistently estimate covariances of asset returns with the market risk premium. Covariances drive observed patterns in the broad cross-sections of stock and bond expected returns.

Mispricing Factors

Robert Stambaugh
,
University of Pennsylvania
Yu Yuan
,
Shanghai Advanced Institute of Finance

Abstract

A four-factor model with two “mispricing” factors, in addition to market and size factors, accommodates a large set of anomalies better than notable four- and five-factor alternative models. Moreover, our size factor reveals a small-firm premium nearly twice usual estimates. The mispricing factors aggregate information across 11 prominent anomalies by averaging rankings within two clusters exhibiting the greatest return comovement. Investor sentiment predicts the mispricing factors, especially their short legs, consistent with a mispricing interpretation and the asymmetry in ease of buying versus shorting. A three-factor model with a single mispricing factor also performs well, especially in Bayesian model comparisons.

The History of the Cross Section of Stock Returns

Juhani Linnainmaa
,
University of Chicago
Michael Roberts
,
University of Pennsylvania

Abstract

Using data spanning the 20th century, we show that most accounting-based return anomalies are spurious. When examined out-of-sample by moving either backward or forward in time, anomalies' average returns decrease, and volatilities and correlations with other anomalies increase. The data-snooping problem is so severe that even the true asset pricing model is expected to be rejected when tested using in-sample data. Our results suggest that asset pricing models should be tested using out-of-sample data or, when not feasible, by whether a model is able to explain half of the in-sample alpha.
Discussant(s)
Christopher Polk
,
London School of Economics and Political Science
Tobias Moskowitz
,
Yale University
Christopher Hrdlicka
,
University of Washington
JEL Classifications
  • G1 - Asset Markets and Pricing