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  5. Asset Pricing: Cross-section of Returns (Other)
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Asset Pricing: Cross-section of Returns (Other)

Paper Session

Sunday, Jan. 8, 2023 1:00 PM - 3:00 PM (CST)

Sheraton New Orleans, Napoleon D
Hosted By: American Finance Association
  • Chair: Bryan Kelly, Yale University

Dynamic Asset (Mis)Pricing: Build-up Versus Resolution Anomalies

Martijn Boons
,
Tilburg University
Christian Opp
,
University of Rochester
Andrea Tamoni
,
Rutgers University
Jules van Binsbergen
,
University of Pennsylvania

Abstract

We classify asset pricing anomalies into those that exacerbate mispricing (build-up
anomalies) and those that resolve it (resolution anomalies). To this end, we estimate
the dynamics of price wedges for a large number of well-known anomaly portfolios in
the factor zoo and map them to firm-level mispricings. We find that several prominent
anomalies like momentum and profitability further dislocate prices. While mispricing
buildup is often quick, the subsequent resolution tends to be slow, suggesting the
potential for material real economic consequences. Our results suggest that financial
intermediaries chasing build-up anomalies in fact negatively affect price efficiency and
associated real capital allocation.

Characteristics and the Cross Section of Covariances

Charles Clarke
,
University of Kentucky
Matthew Linn
,
University of Massachusetts

Abstract

We model firm-level, stock return covariances as a function of firm characteristics. Flexible panel regressions allow us to estimate the marginal predictive power associated with characteristics in a multi-dimensional setting where portfolio sorts are infeasible. We use the model to identify characteristics that proxy for priced factors, unpriced factors, and near-arbitrages while circumventing the need to identify underlying risk factors. Cyclical variation in how characteristics are related to covariances shows that many well-known characteristics proxy for exposure to business cycle risk while few proxy for market sentiment.

Competition and Expected Returns

Ilona Babenko
,
Arizona State University
Oliver Boguth
,
Arizona State University
Yuri Tserlukevich
,
Arizona State University

Abstract

We build a dynamic model of heterogeneous industries to study how firm competition
affects systematic risk. Within an industry, firms invest when the underlying demand
is high and divest when it is low, resulting in a bell-shaped relation between industry
profi tability and systematic risk. Fixing profi tability, industries with more irreversible
investment are less competitive and more risky. Finally, systematic risk is path-dependent
because prior demand shocks a ect installed industry capital. These results imply that
tests that use simple competition measures, such as industry concentration or markups,
can produce conflicting results. Our empirical approach exploits changes in oil prices to
show the dynamic effect of competition on systematic risk within industry and uses a
measure of trade flows between economic sectors to show the cross-industry effect.

What Does Residual Momentum Tell Us About Firm-Specific Momentum?

Sina Ehsani
,
Northern Illinois University
Juhani Linnainmaa
,
Dartmouth College

Abstract

Residual momentum strategies earn significant alphas. The common interpretation for this result - that momentum resides in firm-specific returns - is unwarranted: even in the absence of firm-specific momentum, a strategy sorted on residuals is profitable because it is also a bet against betas. A UMD-like factor that removes these bets to capture true firm-specific momentum earns an alpha of 63 basis points per month ($t$-value = 9.20). Firm-specific momentum strategies, unlike residual momentum strategies, are almost uncorrelated across regions. Our results indicate that there was a strong firm-specific momentum effect in stock returns until 2002, after which it has been almost fully arbitraged away.

Discussant(s)
Johnathan Loudis
,
University of Notre Dame
Seth Pruitt
,
Arizona State University
Yinan Su
,
Johns Hopkins University
Kuntara Pukthuanthong
,
University of Missouri
JEL Classifications
  • G1 - Asset Markets and Pricing