Can mispricing explain the value premium?

• Date: 01 September 2020
• Author: Jeffrey F. Jaffe,Jan Jindra,David J. Pedersen,Torben Voetmann
• DOI: http://doi.org/10.1111/fima.12272
• Published date: 01 September 2020

DOI: 10.1111/fima.12272

ORIGINAL ARTICLE

Can mispricing explain the value premium?

Jeffrey F. Jaffe1Jan Jindra2David J. Pedersen3

TorbenVoetmann4,5

1Finance Department, The Wharton School,

University of Pennsylvania,Philadelphia,

Pennsylvania

2The Securities and ExchangeCommission, San

Francisco,California

3Rutgers School of Business—Camden, Camden,

New Jersey

4University of San Francisco,San Francisco,

California

5The BrattleGroup, San Francisco, California

Correspondence

DavidJ. Pedersen, Rutgers School of Business—

Camden,227 Penn Street, Camden, New Jersey

08102.

Email:David.Pedersen@Rutgers.edu

Fundinginformation

DavidWhitcomb Center for Research in Financial

Servicesof Rutgers University

Abstract

Empirical research finds that stocks with low market-to-book (MTB)

ratiosoutperform stocks with high MTB ratios. Rhodes-Kropf, Robin-

son, and Viswanathan separate the MTB ratio into mispricing and

growth options components. We report that the mispricing com-

ponent, but not the growth options component, predicts abnormal

returns for up to 5 years. We also find that the mispricing compo-

nent, but not the growth options component, provides incremental

information relative to existingasset pricing models. Moreover, after

controlling for mispricing, value no longer beats growth. Overall, our

evidence is consistent with a behavioral explanation of the value

premium.

KEYWORDS

value premium, mispricing, growth options, return predictability

JEL CLASSIFICATIONS

G14

1INTRODUCTION

For over 80 years, investorshave noted the profitability of value strategies, that is, the tendency of stocks with high

value-to-priceratios to outperform stocks with low value-to-price ratios (Graham & Dodd, 1934). The past 25 years has

seen an ongoing debate within the academic community over the source of this value premium. One side argues that

differencesin the book equity-to-market equity (BTM) ratios reflect differences in the systematic risks (Fama & French,

1992). According to this risk-based explanation, high BTM stocks are riskier than low BTM stocks and, consequently,

earn a return premium. The other side offers a behavioralexplanation. High BTM stocks are undervalued, whereas low

BTM stocks are overvalued (Lakonishok, Shleifer,& Vishny, 1994). Thus, the value premium is a manifestation of the

correction of these mispricings.

A challenge in distinguishing between these two alternatives is the identification of mispriced stocks. In this paper,

we rely on the work of Rhodes-Kropf,Robinson, and Viswanathan (RKRV) (2005) to decompose a firm’s market equity-

to-book equity (MTB) ratio into a mispricing component and a growth options component. RKRV’s (2005) model yields

c

2019 Financial Management Association International

Financial Management. 2020;49:615–633. wileyonlinelibrary.com/journal/fima 615

616 JAFFE ETAL.

one of the most common misvaluation measures in the literature.1However, one aspect of the literature using the

RKRV-based (2005) measure is that the studies assume the measure reflects misvaluation. Toour knowledge, no one

has systematically investigated the asset pricing implications of RKRV’s (2005) decomposition.

The goal of this paper is to use RKRV’s (2005) identification of the mispricing and growth options components of

MTB to examinethe value premium. First, we test whether the mispricing and growth options components of MTB pre-

dict future returns. Using a large sample of U.S. stocks, we find that underpriced stocks, according to the RKRV (2005)

model, subsequently outperform overpriced stocks consistent with the hypothesis that the RKRV (2005) model iden-

tifies mispricing. This conclusion holds for excess returns and for abnormal returns based on the capital asset pricing

model (CAPM), the five-factor model of Fama and French (2015) (FF-5), and the M-4 factor model of Stambaugh and

Yuan(2017) (M-4). The mispricing alphas from the factor models range from 24 to 47 basis points per month.

Theability of the growth options component to predict future returns is far less robust. Aportfolio composed of long

positionson firms with low-growth options and short positions on firms with high-growth options generates an insignif-

icantexcess return. The CAPM alpha on this portfolio is also insignificant. However, the alpha is negativeand significant

once we control for the additional risk factors in the FF-5 model. Although the M-4 alpha of the long–short-growth

options portfolio is also negative, the effect is only marginally significant. Thus, even when significant, the alphas from

growth options are negative suggesting a contrarian value strategy.

Next,we determine whether each MTB component adds incremental information to the existing asset pricing mod-

els. Todo so, we follow standard steps in asset pricing and construct factors from the mispricing and growth options

components of MTB. The time series premium on the mispricing factor is roughly equivalent to the premium on the

standard value factor (HML), while the growth options factor does not earn a significant premium. Following Barillas

and Shanken (2017), we then regress each of our two MTB factors on the factors in the existing asset pricing models.

Barillas and Shanken (2017) argue that a significant alpha indicates that the new factor contains information useful to

investors implying that one should augment the existing model with the new factor.For the mispricing factor, we find

a positive and significant alpha, ranging between 17 and 43 basis points per month, relative to the CAPM, FF-5, and

M-4 models. In particular,the FF-5 alpha indicates that an investor who already trades the value factor, along with the

other FF-5 factors, can benefit from the information contained in the mispricing factor.Thus, the value factor does not

subsume the mispricing factor.

Again, the growth options results are less consistent. The CAPM alpha of the growth options factor is positive and

marginally significant. Its FF-5 alpha is negative and significant, and its M-4 alpha is insignificant. Overall, it is unclear

whether the growth options factor adds anything to the existingasset pricing models.

We then consider whether the mispricing factor can explain the well-known value premium. Consistent with the

literature,we find that the Fama-French (2015) book-to-market Value-minus-Growth (Value– Growth) portfolio earns

a significant premium of 43 basis points per month over our sample period. The standard market and size factors are

unable to explain this premium. However, when we also control for the mispricing factor, the alpha on the “Value –

Growth” portfolio is statistically insignificant and falls to –2 basis points per month. In other words, the value premium

disappears. Using the Barillas-Shanken (2017) framework, we next regress the value factor (i.e., HML) on the market

factor, the size factor (i.e., SMB), and the mispricing factor. The alpha from this three-factor model is a statistically

insignificant 6 basis points per month. Because the alpha on HML is a statistically significant 48 basis points per month

in a model that only includes the market and size factors, we conclude that the mispricing factor subsumes the value

factor.Overall, the evidence strongly suggests that mispricing explains the value premium.

There is little evidence that growth options explainthe value premium. The alpha on the “ Value– Growth” portfolio

is positive and significant based on a model that includes the market factor, the size factor, and the growth options

1As of December 2017, there are 101 citations of RKRV (2005) in the following journals: Journal of Finance,Review of Financial Studies,Journal of Financial

Economics,Journalof Financial and Quantitative Analysis,Management Science,Journal of Corporate Finance,andFinancialManagement. By our count, 31 of these

articlesuse the RKRV-based (2005) measure as an independent variable, and five articles use it as a dependent variable.