Economic uncertainty: Mispricing and ambiguity premium

• Published date: 01 November 2023
• Author: Charlie X. Cai,Xi Fu,Semih Kerestecioglu
• Date: 01 November 2023
• DOI: http://doi.org/10.1111/eufm.12403

DOI: 10.1111/eufm.12403

ORIGINAL ARTICLE

Economic uncertainty: Mispricing

and ambiguity premium

Charlie X. Cai |Xi Fu |Semih Kerestecioglu

Accounting and Finance, University of

Liverpool Management School,

Liverpool, Merseyside, UK

Correspondence

Charlie X. Cai, Accounting and Finance,

University of Liverpool Management

School, Chatham Street, Merseyside,

Liverpool L69 7ZH, UK.

Email: x.cai7@liverpool.ac.uk

Abstract

We uncover two channels of effect in the financial market

when investors face macroeconomic uncertainty. Condi-

tional on a common mispricing index, we find that

economic uncertainty exposure (EUE) induces dis-

agreement, which amplifies mispricing. The highest EUE

quintile produces an annualised mispricing alpha of 9.96%,

more than double the unconditional mispricing effect. An

ambiguity premium of 3.84% alpha is documented in the

“non‐mispricing”quintile. The EUE‐induced mispricing

effect is different from the existing limits of arbitrage

explanations. The ambiguity premium is predictably

observed during the unfolding of shocks of COVID‐19 to

the market.

KEYWORDS

ambiguity aversion, cross‐section of stock returns, economic

uncertainty, mispricing, return predictability, risk premium

JEL CLASSIFICATION

G11, G12, E30, C13

Eur Financ Manag. 2023;29:1702–1751.1702

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This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and

reproduction in any medium, provided the original work is properly cited.

© 2022 The Authors. European Financial Management published by John Wiley & Sons Ltd.

We are grateful for constructive comments from the editor (John A. Doukas), two anonymous referees, Shamim

Ahmed (University of Liverpool), Turan Bali (Georgetown University), Steven Davis (University of Chicago), Robert

Faff (University of Queensland), Weikai Li (Singapore Management University, Singapore), Sydney Ludvigson (New

York University), Brent Meyer (Federal Reserved Board), David Sraer (University of California, Berkeley), Chardin

Wese Simen (University of Liverpool), Jianfeng Yu (Tsinghua University), Hao Zhou (Tsinghua University),

participants in the seminars at the University of Liverpool and University of Birmingham, and participants in 52nd

Money Macro and Finance Annual Conference, Cambridge and The 3rd International Conference on Financial

Regulation and Financial Stability, Taiyuan. Errors are ours.

1|INTRODUCTION

Macroeconomic uncertainty (MEU) has become an accustomed reality for policy, business and

investment decision‐makers. One recent and ongoing example is the heightened economic

uncertainty caused by the COVID‐19 pandemic. During this period, we have observed two

phenomena in financial markets. First, the tug of war between optimists and pessimists in the market

is intensified. This is exemplified by the record‐breaking daily gains and losses closely clustered in the

leading equity benchmark indices around the world.

1

Second, some investors prefer to watch from

the sidelines by moving their money out of the equity market temporarily and looking for bargains

for their long‐term investments.

2

These phenomena aforementioned represent two different

responses from investors to economic uncertainty. While both of these phenomena have been

studied separately, existing studies have not been able to present a coherent framework to study both

of these effects. This leads to inconclusive findings on the impact of MEU on asset pricing.

These two responses are broadly related to studies on how economic uncertainty affects

investors' beliefs and preferences. First, MEU amplifies biases in individuals' beliefs by making

optimists more optimistic and pessimists more pessimistic. Hirshleifer (2001) argues that

uncertainty leaves more room for investors to follow their own subjective estimations and

ignore objective valuations. Investors' heterogeneous beliefs about the fundamental value can

be a source of mispricing (Hong & Stein, 2007). When there are contrasting beliefs among

investors, Miller (1977) shows that stocks will be in general overpriced as this is more likely to

reflect optimists' views than pessimists' in light of short‐sale constraints. Therefore, these stocks

will be more likely to experience overpricing and have lower expected returns. We refer to this

effect as the mispricing effect of economic uncertainty, which amplifies the tension between

optimists and pessimists.

Second, people prefer certain over uncertain outcomes. Uncertain outcomes have been

classified into two groups by Knight (1921): one referred to as risk, which is defined as an event

with a known distribution; and the other as uncertainty, which is an event with an unknown

distribution. Knight (1921) contends that people are more averse to uncertainty than risk. In

this regard, stocks' exposures to economic uncertainty will affect investors' preferences for these

stocks. Anderson et al. (2009) show that macro uncertainty carries a positive premium in

equilibrium in a dynamic model, and they find supportive empirical evidence using dispersion

in the Survey of Professional Forecasters (SPFs) as a measure of uncertainty. In a nutshell, this

line of literature predicts that investors would demand a premium from stocks with high

exposure to economic uncertainty. We refer to this effect as the ambiguity‐premium effect, and

it applies to uncertainty‐averse investors who would prefer to stay on the sidelines unless the

expected compensation is high enough.

These two explanations regarding investors' behaviour in response to economic uncertainty

have conflicting predictions on the relationship between firms' economic uncertainty exposure

1

For example, in March 2020, the S&P 500 index experienced two of the top 20 historical best daily performances and

three of the worst 20 daily performances since its introduction in 1923. In fact, two of these large episodes are next to

each other: on March 12, 2020 with a return of −9.51% and March 13, 2020 with a return of 9.29%. See https://en.

wikipedia.org/wiki/List_of_largest_daily_changes_in_the_S%26P_500_Index (accessed June 29, 2020). If we look at the

oil price during the period, a similar extreme volatility can be observed.

2

There is anecdotal evidence suggesting that investors first fall back to cash and move to safe assets, such as gold during

this period. See https://www.cnbc.com/2020/04/20/coronavirus-why-gold-is-seen-as-a-safe-haven-investment-in-a-

crisis.html?__source=newsletter%7Cmakeit (accessed June 29, 2020).

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(EUE) and cross‐sectional returns.

3

The ambiguity‐premium effect predicts a positive

correlation between EUE and expected returns, while the mispricing effect predicts a negative

one. It is not surprising that existing studies provide mixed evidence on the relationship

between EUE and expected returns.

4

The challenge of obtaining a clear inference from the studies mentioned above is that both the

ambiguity premium and mispricing mechanisms are at work. A clear conclusion can only be drawn

when these two effects can be disentangled. The mispricing argument suggests that disagreement is

a general source of mispricing (Hong & Stein, 2007). However, what information sources investors

use to form their optimistic or pessimistic beliefsaboutthecompanyarenotspecifiedinthese

models. It is, therefore, a useful identification strategy to study the effect of economic uncertainty

when investors already have heterogeneous beliefs in the first place. To this end, the mispricing

score (MIS) proposed by Stambaugh et al. (2012,2015)usingfirm‐level characteristics provides a

measure of cross‐sectional variation for overpricing and underpricing stocks.

5

If the disagreement is

a source of mispricing, higher exposure to economic uncertainty will induce la rger disagreement in

investors' assessment of those firm‐level value relevant characteristics and will lead to more apparent

mispricing. In other words, high firm‐level exposure to economic uncertainty will exacerbate

investors' mispricing of other firm characteristics, making optimists more optimistic and pessimists

more pessimistic. In addition, stocks in the non‐mispricing group (neither overpriced nor

underpriced) according to MIS can be used to study a “pure”ambiguity‐premium effect since this

subset of stocks is not influenced by these known mispricing characteristics.

6

We develop the following two main hypotheses in Section 2:(1)IfEUE‐induced disagreement is

a common source of mispricing, we expect that the mispricing effect (measured by the long–short

portfolio sorted by MIS) will be the strongest in the group of stocks with the highest EUE; and (2)

For stocks experiencing the least influence of mispricing measured by the MIS (i.e., those in the

middle portfolio sorted by MIS), the ambiguity‐premium effect of EUE will be the dominant effect,

and therefore a positive relationship between EUE and expected return is expected.

In our empirical analysis, we measure EUE by estimating the absolute sensitivity of stock

return to log changes of economic uncertainty proposed by Jurado et al. (2015, hereafter JLN).

7

3

We define EUE as the absolute sensitivity of the return to the log change of economic uncertainty. Empirically, it is

estimated by the absolute value of the regression coefficient from a time series regression of a stock's returns on log

changes of economic uncertainty index while controlling for other risk factors, such as Fama–French market factors.

More detailed discussion can be found in Section 3.2.

4

Li (2016) finds that stocks with higher exposures to macro‐disagreement earn lower future returns, which provides

support to the mispricing effect as proposed by Hong and Sraer (2016). Bali et al. (2017) also find a negative relationship

between the uncertainty beta estimated using the uncertainty index in Jurado et al. (2015) and the expected return.

These results are consistent with the mispricing argument under the hedging argument in the context of Merton's

(1973) intertemporal capital asset pricing model (ICAPM). By contrast, Anderson et al. (2009) and Bali and Zhou (2016)

provide evidence supporting a positive uncertainty premium. Brenner and Izhakian (2018) find that the ambiguity

premium is positive when the expected probability of a positive outcome is high, while the ambiguity premium is

negative when the expected probability of a negative outcome is high. The mixed findings in those studies may also be

due to the use of different economic uncertainty proxies.

5

Eleven firm characteristics are taken into account for MIS construction. Please see Section 3.1 for details.

6

A similar approach is adopted by Stambaugh and Yuan (2017) when they construct their size factor using stocks least

likely to be mispriced, that is, those in the middle mispricing group. They show that when controlling for the

mispricing effect, a much clearer and strong size premium that is nearly twice that implied by the familiar

Fama–French version of small‐minus‐big is documented.

7

They define economic uncertainty as the conditional volatility of a disturbance that is unforecastable from the

perspective of economic agents. They show that such a measure is better at capturing quantitively important

uncertainty episodes than other popular financial market‐based proxies, such as the volatility index.

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