Munich Personal RePEc Archive
Behavioral Finance
Hirshleifer, David
Merage School of Business, UC Irvine
14 August 2014
Online at https://mpra.ub.uni-muenchen.de/59028/
MPRA Paper No. 59028, posted 02 Oct 2014 18:50 UTC
1 8/ 5/ 2014
Behavioral Finance
David Hirshleifer M erage School of Business Universit y of California, Irvine
david.h@uci.edu (614) 214-4304
W hen citing this paper, please use the follow ing: Hirshleifer D, 2014. Title. Annu. Rev. Econ.
7,: Submitted. Doi: 10.1146/ annurev-financial-092214-043752
Keywords: Invest or psychology, heurist ics, overconfidence, at t ent ion, feelings, reference dependence, social finance
JEL code: G02 - Behavioral Finance: Underlying Principles Abstract:
Behavioral finance st udies t he applicat ion of psychology t o finance, w it h a f ocus on individual- level cognit ive biases. I describe here t he sources of judgment and decision biases, how t hey affect t rading and market prices, t he role of arbit rage and flow s of w ealt h bet w een more rat ional and less rat ional invest ors, how firms exploit inefficient prices and incit e m isvaluat ion, and t he effect s of managerial judgment biases. There is need for m ore t heory and t est ing of t he effect s of feelings on financial decisions and aggregat e out comes. Especially, t he t ime has come t o move beyond behavioral finance t o social finance, w hich st udies t he st ruct ure of social int eract ions, how financial ideas spread and evolve, and how social processes affect financial out comes.
I t hank Nicholas Barberis, Jam es Choi, Bing Han, Gilles Hilary, Narasimhan Jegadeesh, Danling Jiang, Sonya Lim , Siew Hong Teoh, Anjan Thakor, Ivo Welch, Wei Xiong, and Liyan Yang for helpful com ment s, and Lin Sun and Qiguang Wang for excellent research assist ance and comment s.
2 Cont ent s
1. Introduction
2. M arket mispricing, arbitrage, and financial agents a. Arbit rage
b. Financial agent s 3. Psychological foundations
4. Overconfidence and self-esteem maintenance a. Psychology of overconfidence
b. Invest or overconfidence and self-est eem maint enance c. M anagerial and advisor overconfidence and overopt im ism 5. Limited attention and cognitive processing
a. Failure t o process signals and feat ures of t he decision environment b. Neglect ing basic feat ures of t he decision environment
c. Financial t heories of cat egory t hinking d. Reference-dependence and framing
e. Concept ual discret izing, loss aversion, and probabilit y weight ing f. M ent al account ing and realizat ion preference
g. Heurist ic learning 6. Feelings
a. Familiarit y and liking
b. Financial t heories based on feelings
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c. Evidence on financial effect s of fam iliarit y and in-group bias d. Sent iment , shift ing opt imism and risk t olerance
7. Firm behavior: Exploiting versus inciting misvaluation a. Theories of exploit ive advisors and firms b. Evidence on exploit ive advisors and firms
c. M isvaluat ion, new issues and repurchase, and post -event ret urns 8. Conclusion: Behavioral finance versus social finance
4 1. Introduction
The st ock price of Ent reM ed jum ped about 600% in one w eekend upon t he
republicat ion of informat ion t hat w as already publicly available five m ont hs earlier about a new cancer drug (Huberman & Regev (2001)). This violat ed t he Efficient M arket Hypot hesis, w hich assert s t hat prices accurat ely ref lect publicly available informat ion. The Efficient M arket
Hypot hesis is based on t he idea t hat most , or at least t he m ost import ant , invest ors are rat ional in processing informat ion. Behavioral finance, in cont rast , st udies how people fall short of t his ideal in t heir decisions, and how market s are, t o some degree, inefficient .
The rise of behavioral finance over t he last t hree decades has been felt t hroughout finance and econom ics. M any scholars are now ready t o ent ert ain t he consequences of eit her rat ional or irrat ional aspect s of human judgment , as relevant for t he part icular applicat ion at hand. This readiness is great est for errors by individual m arket part icipant s; vigorous debat e cont inues about how psychological bias af fect s price det erminat ion in large and liquid market s.
Nevert heless, a modern underst anding of t he finance field requires grounding in psychological as w ell as rat ional approaches. Today many of t he leading t heories about such fundam ent al t opics as invest or behavior, t he cross-sect ion of ret urns, corporat e invest m ent , and money managem ent , derive f rom psychological fact ors.
Psychology has ident ified various judgment biases t hat can affect financial decision- making. Since psychological bias is t he dist inct ive feat ure of behavioral finance, I organize t his review by t he t ype of bias (see also Shiller (1999)). Also, rat her t han view ing t he psychology of judgment and decisions as a congeries of inexplicable fact s, I organize t he discussion of biases
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around a relat ively small number of underlying evolut ionary and psychological root s. Then, I discuss financial t heories founded upon each t ype of bias, and t he evidence bearing upon t hem .
Some fundament als of behavioral finance do not inherent ly depend on t he specific psychological source of bias. So I discuss separat ely t he t opics of how arbit rage and flow s of wealt h prom ot e market efficiency, how firms induce or react t o m ispricing, and how invest or sent iment affect s securit y market s.
The m ain focus of t his review is on t he effect s, individual or aggregat e, of individual- level bias. The t opic of social processes, discussed in t he conclusion, deserve great er at t ent ion in finance, and a separat e review . Also, I do not go deeply here int o dist inguishing t he effect s of psychological bias from rat ional risk effect s (see, e.g., t he review of Daniel et al. (2002)).
Som e surveys focus more heavily on issues t hat cut across different psychological biases, such as limit s t o arbit rage (Gromb & Vayanos (2010)), noise t rading (Shleifer (2000)), and how valuat ions affect corporat e behavior (Baker (2009)). For a great er focus on prospect t heory, see t he excellent survey of Barberis & Thaler (2003); neurofinance, Bernheim (2009);
experiment al economics and asset market s, Smit h (2008); invest ment s and asset pricing, Hirshleifer (2001); behavioral corporat e finance, Baker & Wurgler (2012); behavioral
account ing, Libby et al. (2002) and Hirshleifer & Teoh (2009a); and policy, regulat ion, or f ield experim ent s, Thaler & Sunst ein (2008), Hirshleifer (2008), and Card et al. (2011).
2. M arket mispricing, arbitrage, and financial agents
a. Arbit rage
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Arbit rage is t he purchase or sale of goods t o profit from differences in effect ive prices across t rading venues. The t erm is used broadly t o refer t o t he exploit at ion of profit
opport unit ies w henever some asset s are overpriced relat ive t o ot hers, based on t he idea t hat buying cheap asset s and selling similar but expensive ones can yield a relat ively low-risk ret urn.
In perfect m arket s, arbit rage opport unit ies are lim it ed by t he risk aversion of invest ors and t he riskiness of t rading t he m ispriced asset (DeLong et al. (1991)).
An oft -neglect ed fact is t hat arbit rage is a double-edged blade t hat can make prices eit her more or less efficient . In asset market equilibrium under disagreement , price reflect s a weight ed average of beliefs. So bot h t he irrat ional impellers of mispricing and t he m ore rat ional correct ors of it believe t hat t hey are performing profit able arbit rage against inefficient market prices. Whet her great er arbit rage capit al reduces mispricing t herefore depends on whet her t his capit al is w ielded by `sm art ’ invest ors—t hose w ho are bot h rat ional and, if m oney managers, not pandering t o t he mist aken beliefs of irrat ional invest ors about what is a profit opport unit y.
A pow erful argum ent for w hy market s are oft en highly eff icient is t hat in t he long run w ealt h t ends t o flow t o sm art arbit rageurs, w ho end up dom inat ing t he market . How ever, irrat ional invest ors can earn higher expect ed profit s t han rat ional ones by bearing higher risk (DeLong et al. (1991)), or by inducing self-validat ing feedback int o fundam ent als (Hirshleifer et al. (2006)). Alt ernat ively, rat ionalit y can falt er if invest ing success increases subsequent bias (Daniel et al. (1998); Gervais & Odean (2001)).
If w ealt h does f low t o sm art invest ors, t heir influence on prices increases, owing eit her t o credit const raint s or decreasing risk aversion. How ever, t his process is oft en slow , as st rat egy
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performance is t ypically a very noisy indicat or of abilit y (Yan (2008)). M eanw hile, new naïve money flow s int o market s each day; t he succession of generat ions reshuffles w ealt h and t alent .
If irrat ional invest ors misvalue t he idiosyncrat ic component s of t he fundament al payoffs of many securit ies, if m arket s are frict ionless, and if rat ional and irrat ional invest ors all bet on many securit ies, t hen ow ing t o t he large number of bet s, t he flow of w ealt h becom es sw ift and alm ost sure. This causes rat ional invest ors t o acquire all t he wealt h very quickly. How ever, if most invest ors only place act ive bet s on subset s of securit ies, t he rat e of w ealt h flow can be modest , accom modat ing relat ively subst ant ial and persist ent m ispricing (Daniel et al. (2001)).
b. Financial agent s
It is usually supposed t hat inst it ut ional money managers and professional invest ment advisors are smart ar bit rageurs, act ing on behalf of less sophist icat ed individual invest ors.
Sophist icat ed invest ors perf orm careful analysis t o lear n about biases of invest ors or
consequent m ispricing, and t he insight der ived t hereby can be used t o educat e client s or t o deploy client funds t o achieve high ret urns. How ever, ow ing t o conflict of int erest , or t o
imperfect rat ionalit y of invest m ent professionals, em ploying agent s is an imperfect rem edy for ignorance and folly. M oney managers oft en pander t o invest or irrat ionalit y, in order t o at t ract inflow s.
This does not m ake financial advice and delegat ion pure evils. For example, in t he model of Gennaioli et al. (2014), `money doct ors’ skim off som e of t he gains from invest ment , but st ill increase w elfare by encouraging ot herw ise-dist rust ful individuals t o part icipat e in t he market .
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As for whet her t he abilit y of irrat ional invest ors t o hire exploit ive agent s im proves t he efficiency of prices, t here is no general unam biguous answ er. So opt imism about t he
inevit abilit y of reaching alm ost perfect market efficiency must be t empered by recognit ion t hat agent s may exacerbat e invest or bias. Furt hermore, w hen, by chance, m ispricing get s w orse, smart arbs lose money on t heir exist ing posit ions and have more t rouble raising funds. So correct ive arbit rage pressure on price is w eakest w hen it is needed t he most (Shleifer & Vishny (1997)).
Ow ing t o heavier t ot al pressure from irrat ional invest ors speculat ing about syst emat ic fact ors, w e t ypically expect great er m ispricing of fact ors t han of idiosyncrat ic payoff
component s, except for idiosyncrat ic opport unit ies t hat arbs simply do not not ice (Daniel et al.
(2001)). For exam ple, t he book-t o-market and accrual charact erist ics are associat ed w it h ret urn comovem ent (Fama & French (1993); Hirshleifer et al. (2012)), so if t he value and accrual anom alies (bot h discussed lat er) represent mispricing, t hey are probably relat ively hard t o arbit rage aw ay.
3. Psychological foundations
Since people need t o make judgm ent s and decisions quickly using limit ed cognit ive resources, t hey necessarily use short cut s (Simon (1956); Kahneman et al. (1982)), oft en called
“ heurist ics.” All t hinking builds upon cognit ive algorit hm s t hat operat e aut omat ically below t he level of consciousness. The t erm “ heurist ics” encompasses bot h innat e and aut omat ic
processes, and learned or consciously select ed rules of t hum b.
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Heurist ics oft en w ork w ell w it hin some domains and for some t ypes of problems, but badly in ot hers. Heurist ic simplificat ion implies more errors for decision problem s t hat range fart her from t he t ypes of problems t hat t he hum an mind evolved t o deal w it h in t he ancest ral past .
In dual process t heories of cognit ion, an aut omat ic, non-deliberat ive syst em quickly generat es percept ions and judgment s; a slow er, more effort ful syst em monit ors and revises such judgment s as t ime and circumst ances permit (St anovich (1999); Kahneman (2011)).
Follow ing Haidt and Kesebir (2010), I refer t o t he fast process as t he int uit ive syst em, and t he slow process as t he reasoning syst em.
Kahneman (2011) describes hum an t hinking as largely int uit ive, and heavily influenced by t he associat ions t hat are t riggered by t he present at ion of a decision problem . People are overconf ident t hat t heir int uit ive w ay of t hinking about a problem is cor rect ; inf ormat ion t hat does not immediat ely come t o mind t ends t o be complet ely neglect ed, a phenomenon t hat Kahnem an calls WYSIATI (What You See Is All There Is).
Feelings provide t he value w eight s assigned t o possible out com es t o m ot ivat e decisions and act ions. Affect ive react ions can also facilit at e making fast use of urgent inf ormat ion about t he environment (as in t he affect heurist ic; Slovic et al. (2002)). For exam ple, a risky invest m ent opport unit y m ay t rigger fear and, t hereby, useful hesit at ion.
How ever, feelings oft en short -circuit useful analysis, as w it h exit ing t he st ock m arket in sudden panic, or buying a hot st ock based on ent husiasm rat her t han crit ical evaluat ion. Such
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affect ive short -circuit ing can also creat e self-discipline problem s, such as not saving for ret irement .
In modern financial market s, t here are great benefit s t o m aking decisions analyt ically rat her t han relying solely upon feelings and int uit ion. Int uit ion-generat ing m echanism s suit ed t o t he human ancest ral environment provide poor guidance for decisions in modern market s and large econom ies.
Beliefs have a social-signaling as well as a decision-making role. In t he t heory of Trivers (1991), people overest imat e t heir personal merit s so as t o be more persuasive t o ot hers about t hem. Such self-decept ion comes at t he cost of errors deriving from overconfident beliefs.
The t hree abovement ioned element s—heurist ic simplificat ion, affect ive short -circuit ing, and self-decept ion—explain most of t he psychological biases st udied in behavioral finance.
These elem ent s also underlie t he dynam ic psychological updat ing processes t hat m aint ain biases despit e having opport unit ies t o learn from past errors.
4. Overconfidence and self-esteem maintenance
a. Psychology of overconfidence
An immediat e consequence of self-decept ion is t hat people w ill be overconfident about t heir m erit s of various sort s. In overprecision, people t hink t hat t heir judgment s are more accurat e t han t hey really are. Overconfidence t ends t o be st ronger w hen correct judgm ent s are hard t o form, such as w hen uncert aint y is high. The difficult y effect is t he finding t hat
overprecision is st ronger for challenging judgment t asks.
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Recent st udies bot h of overplacement (overest im at ion of one’s rank in t he populat ion) in t he psychological laborat ory (Benoit et al. (2014)) and t he field (M erkle & Weber (2011)), and of overprecision in financial field set t ings, confirm t hat overconfidence is very st rong (Ben- David et al. (2013)).
Since high abilit y cont r ibut es t o good out comes, overest im at ion of one’s merit s
promot es overopt imism about one’s prospect s. People do t end t o be overopt imist ic about t heir life prospect s (Weinst ein (1980)), which af fect s t heir economic and financial decisions (Puri &
Robinson (2007)).
If overconf idence is t o persist as new informat ion about abilit y arrives, t here must be biases in updat ing processes t hat favor a posit ive self-assessm ent . Such self-enhancing at t ribut ion bias is w ell docum ent ed (Langer & Rot h (1975)).
People t end t o shift t heir at t it udes in favor of act ions t hey have chosen or have been induced t o engage in w it hout compensat ion, a phenomenon t hat m ot ivat es t he t heory of cognit ive dissonance (Fest inger & Carlsmit h (1959)). Such shift s help people reconcile t heir past choices w it h t he percept ion t hat t hey are good decision-makers. Self-enhancing updat ing promot es escalat ion of commit ment (st icking t oo st ubbornly t o a choice despit e opposing informat ion, St aw (1976)), including t he sunk cost effect (reluct ance t o t erm inat e cost ly act ivit ies aft er expending resources on t hem ; Thaler (1980)); and rat ionalizat ion of one’s past behaviors (Nisbet t & W ilson (1977)).
b. Invest or overconfidence and self-est eem maint enance
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i. Overconfidence and t rading aggressiveness in st at ic set t ings
Overconfidence causes invest ors t o t rade more aggressively, w hich t ends t o reduce t heir w elfare (Odean (1998)). Overconfidence t herefore helps solve t he act ive invest ing puzzle:
t hat individual invest ors t rade individual st ocks despit e losing money doing so (Barber & Odean (2000)), and invest in act ive funds inst ead of indexing t o obt ain bet t er net performance.
Consist ent w it h overconfidence, in experiment al market s, some invest ors overest imat e t he precision of t heir signals, are m ore subject t o t he w inner’s curse, and do w orse in t rading (Biais et al. (2005)).
By promot ing bet s on individual securit ies, overconfidence reduces diversificat ion.
How ever, as discussed lat er, underdiversificat ion has ot her sources as well. So great er confidence, by encouraging part icipat ion in ot herw ise-neglect ed asset classes, can also promot e diversif icat ion. Indeed, great er feeling of compet ence about invest ing is associat ed wit h w eaker home bias in invest ing (discussed lat er; Graham et al. (2009)).
ii. Overconfidence and price overreact ion in st at ic set t ings
Overconfidence about some value-relevant infor mat ion signal causes overreact ion in prices, and t herefore long-run correct ion (Odean (1998)). This im plies negat ive ret urn aut ocorrelat ions.
Any psychological force t hat causes overreact ion t o informat ion w ill t end t o make high price be a proxy for overvaluat ion and low price for undervaluat ion. This leads nat urally t o t he
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size (market value) effect . For example, overext rapolat ion of fundament als or prices can cause such effect s (Lakonishok et al. (1994)).
Scaling by a proxy for fundament als, such as book value, cleanses market price of variat ion not derived from mispricing. So in t he overconf idence-based capit al asset pricing model of Daniel et al. (2001), fundament al-t o-price rat ios predict ret urns even m ore st rongly, if t he fundam ent al proxy is not t oo noisy. Bot h bet a and scaled price variables such as book-t o- market predict ret urns. Since scaled price variables capt ure bot h risk and m ispricing effect s, t hey can somet im es dom inat e bet a in ret urn predict ion regressions even w hen risk is priced.
Empirically, high bet a-st ocks do underperform (Frazzini & Pedersen (2014)).
Book-t o-market is an example of how mispricing can be proxied by t he deviat ion of market price from a benchm ark t hat is less subject t o misvaluat ion. Empirically, st ocks w it h low price relat ive t o fundament al proxies on average experience high subsequent ret urns. Such proxies include book value, earnings or cash flow (t he value effect ), past price (t he w inner/ loser effect ), or a const ant (t he size effect ). The value effect has been confirmed in many market s and asset classes (Asness et al. (2013)).
Short -t erm int erest rat es can act as a fundam ent al scaling for long-t erm rat es. So overconfidence furt her im plies t hat t he forw ard premium f or bonds denom inat ed in different currencies can negat ively predict exchange rat e shift s, t he forw ard premium puzzle (Burnside et al. (2011)).
Furt her implicat ions of overconfidence derive from com parat ive st at ics on it s det erminant s. For example, t he difficult y effect implies st ronger overconfidence effect s for
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hard-t o-value st ocks. Consist ent w it h t his, t he value effect is st ronger am ong high R& D st ocks (Chan et al. (2001)); m oment um is also st ronger for hard-t o-evaluat e st ocks (as indicat ed by uncert aint y proxies; Jiang et al. (2005)).
iii. Bias in self-at t ribut ion and t rading aggressiveness in dynamic set t ings
In m odels of t he dynam ics of overconfidence, profit s on an invest or’s exist ing long or short posit ion increase confidence, result ing in great er subsequent t rading aggressiveness (Daniel et al. (1998)). It follow s t hat for securit ies t hat are in posit ive net supply, high past ret urns should be associat ed w it h great er subsequent t rading (Gervais & Odean (2001)).
Consist ent wit h bias in self-at t ribut ion, t rading act ivit y by individual invest ors increases aft er t hey experience high ret urns (Barber & Odean (2002)). Similarly, invest or t rading and market t rading volume increase aft er high ret urns (St at man et al. (2006); Griffin et al. (2007)).
iv. Overconfidence, biased self-at t ribut ion, and price under- vs. over-react ions
Bias in self-at t ribut ion im plies short -run cont inuat ion of st ock ret urns and long-run reversal. When a st ock has risen, for exam ple, relat ive t o ot her st ocks, in t he short run t his overreact ion t ends t o cont inue; and, on average, it lat er falls, but t his correct ion is hindered, so t he decline also t ends t o cont inue. So short -run ret urn cont inuat ion and long-run reversal t oget her are consist ent wit h a process of cont inuing overreact ion and t hen correct ion (Daniel et al. (1998)). This m odel also im plies post -event ret urn cont inuat ion (post -event abnormal ret urns of t he sam e sign on average as t he event -dat e react ion) if firms t end t o select good
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new s act ions in response t o underpricing (as w it h issuing overpriced shares and repurchasing underpriced shares); and cont inuat ion aft er earnings surprises.
Empirically, a cont rast ing pair of st ylized fact s is t he t endency of st ock ret urns t o
cont inue in t he short run (posit ive aut ocorrelat ions w it h condit ioning period of several m ont hs- - Jegadeesh & Tit m an (1993)) versus a t endency t o reverse in t he long run (negat ive
aut ocorrelat ions w it h a condit ioning period of several years; DeBondt & Thaler (1985)). The short -run effect is called moment um, w hich is present in many asset classes in t he t im e series (M oskow it z et al. (2012)) and t he cross-sect ion. The long-run reversal of ret urns is called t he w inner/ loser effect .
Event st udies t ypically report post -event ret urn cont inuat ion, i.e., average post -event abnormal ret urns of t he sam e sign as t he event -dat e react ion, as summarized in Hirshleifer (2001). For example, seasoned equit y issues (and IPOs, and debt issues) t end t o be follow ed by negat ive abnormal ret urns (t he new issues puzzle; Loughran & Rit t er (1995); Spiess & Affleck- Graves (1995)), and repurchase by high ret urns (Ikenberry et al. (1995)).
Equit y issuance is followed by low average market ret urns in many count ries
(Henderson et al. (2006)). At t he aggregat e level as w ell, t he share of equit y issues in t ot al new equit y and debt issues has been a negat ive predict or of U.S. market ret urns (Baker & Wurgler (2000)).
Also consist ent wit h overconfidence and bias in self-at t ribut ion, earnings surprises are associat ed w it h subsequent abnormal ret urns of t he same sign (post -earnings announcem ent drift , discussed in Sect ion 5).
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The abilit y of overconfidence and it s dynam ic count erpart , self-at t ribut ion bias, t o explain a w ide range of major pat t erns of ret urn predict abilit y is not able, but does not prove t hat overconf idence is t he cause. Indeed, lat er sect ions discuss alt ernat ive possible
psychological explanat ions f or several of t hese effect s. Dist inguishing t heories requires hom ing in on t heir dist inct ive im plicat ions.
v. Overconfidence, short -sales const raint s, and overpricing
In t he model of M iller (1977), owing t o short -sale const raint s, only relat ively opt imist ic beliefs are impounded int o price, result ing in overvaluat ion. Invest ors st ubbornly disagree, alt hough rat ionally opt im ist s should updat e pessimist ically based on t he knowledge t hat t here are sidelined pessim ist s. Such disagreement can be explained by overconfidence on t he part of opt imist s t hat t heir ow n analysis is superior, or t hat disagreeing invest ors are rare (as in
WYSIATI).
Empirically, dispersion of analyst forecast s is negat ively associat ed w it h subsequent abnormal ret urns (Diet her et al. (2002)). Clear examples of overpricing derived from disagreement and short -selling const raint s occurred during t he m illennial high-t ech boom , w hen t he m arket value of a parent f irm w as somet imes subst ant ially less t han t he value of it s holdings in one of it s publicly-t raded divisions (Lamont & Thaler (2003)). Also consist ent wit h t he M iller t heory, st ocks wit h t ight er short -sale const raint s have st ronger ret urn predict abilit y anom alies (Nagel (2005)), and great er long-short asym met ry in t he accrual anomaly (Hirshleifer et al. (2011)).
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Volat ilit y increases t he scope for disagreement , implying great er overvaluat ion.
Empirically, st ocks wit h high idiosyncrat ic risk (Ang et al. (2006)) do under perform.
In m arket s w it h short sale const raint s, invest ors may buy overvalued st ocks in t he expect at ion of selling at an even higher price t o overconfident invest ors. Low er available float should exacerbat e such bubbles (Hong et al. (2006)), as confirmed for a bubble in Chinese w arrant s (Xiong & Yu (2011)).
c. M anagerial and advisor overconfidence and overopt im ism
A manager who is overconfident of his abilit y will t end t o be opt im ist ic about his firm ’s prospect s as w ell. In t he m odel of Bernardo & Welch (2001), overconf idence has a bright side, as it encourages ent repreneurs t o engage in socially desirable experiment at ion. Survey
evidence confirms t hat ent repreneurs t end t o be overopt im ist ic about t heir fut ure success.
Overconfidence and overopt imism have obvious cost s, but can also help shareholders by encouraging risk averse m anagers t o t ake good risky or innovat ive project s (Cam pbell et al.
(2011)). This leads t o a benef it t o mat ching managerial opt im ism or confidence appropriat ely t o firms (Goel & Thakor (2008)). Different degrees of opt im ism bet w een ent repreneurs and
out side invest ors can result in inefficient screening of project s, creat ing a role for rat ional banks t o act as a bridge bet w een t hese t w o groups (Coval & Thakor (2005).
i. Evidence on overconfidence, opt imism, and invest ment and financing decisions
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Several st rands of evidence display bot h t he bright and dark sides of managerial overconfidence and overopt im ism suggest ed by t heoret ical models. On t he dark side, bidders on average earn low ret urns from t akeovers, more opt imist ic managers are more likely t o make acquisit ions, and t he market react s more negat ively t o t heir bids (M almendier & Tat e (2008)).
Opt imist ic CEOs also use less ext ernal finance, especially equit y (M alm endier et al.
(2011)), and finance relat ively m ore w it h short -t erm debt (Graham et al. (2013)). The
invest m ent of firms wit h overopt im ist ic managers (as proxied by volunt arily ret aining equit y- like claims in t he f irm), is m ore sensit ive t o cash flow (M almendier & Tat e (2005)). This suggest s t hat such managers view t heir firm as undervalued, making ext ernal capit al seem expensive t o t hem.
Bot h overconfidence and overopt imism are associat ed w it h great er corporat e invest m ent (Ben-David et al. (2013)). Pot ent ially on t he bright side, overopt imist ic managers spend more on R& D, and obt ain m ore pat ent s relat ive t o t heir R& D spending, perhaps because of great er willingness t o bear risk (Hirshleifer et al. (2012)).
The opt imism of analyst forecast s at long horizons suggest s eit her t hat analyst s are overopt im ist ic, or t hat t hey forecast opt imist ically for agency reasons (Richardson et al. (2004)).
The associat ion of analyst polit ical at t it udes wit h forecast opt im ism suggest s t hat psychological fact ors play a role (Jiang et al. (2014)).
ii. Dynamics of managerial and analyst confidence
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Turning t o t he dynamics of managerial bias, t here is evidence suggest ing t hat managers t end t o at t ribut e good perf ormance excessively t o t heir ow n abilit ies rat her t han luck. Bias in managerial self -at t ribut ion has been found in t he cont ext s of repeat ed acquisit ions (Billet t &
Qian (2008)) and in t he issuance of management earnings forecast s aft er past successes (Hilary
& Hsu (2011)).
5. Limited attention and cognitive processing
Ow ing t o limit ed at t ent ion and processing pow er, people t end t o neglect relevant informat ion signals and st rat egic feat ures of t he decision environment . This is manifest ed in a variet y of more specific effect s t o be described, such as evaluat ion based on cat egories, t he influence of framing and reference point s on judgment s, concept ual discret izing of cont inuous quant it ies, flaw ed t racking of cost s and benefit s in ment al account ing, and t he heurist ic updat ing of beliefs.
a. Failure t o process signals and feat ures of t he decision environment
People t end t o neglect low salience signals and overreact t o salient or recent new s.
Ow ing t o WYSIATI, t hey also t end t o be unaw are of such errors, and hence do oft en not correct t hem. People also neglect import ant feat ures of t heir decision environment s, such as st rat egic mot ives for t he act ions of ot hers. Such neglect is reflect ed in cognit ive hierarchy m odels and evidence in t he experiment al game t heory lit erat ure (Camerer et al. (2004)), and ot her models of neglect of st rat egic mot ives (Hirshleifer & Teoh (2003); Eyst er & Rabin (2005)).
i. Financial t heories of informat ion neglect
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Informat ion sources can be biased because of inherent psychological bias, infect ion by public excit ement , or conflict of int erest . When invest ors do not adjust appropriat ely for biased signal pr ovision, t rading mist akes and mispricing follow (see Sect ion 7.b).
In t he m odels of Hirshleifer & Teoh (2003), Peng & Xiong (2006), and Hirshleifer et al.
(2011), a subset of invest ors neglect a value-relevant informat ion signal, result ing in ret urn predict abilit y. Exam ples of such signals include t he deviat ion bet w een GAAP and pro forma earnings, f oot not es in financial st at ement s about opt ion com pensat ion t o managers, t he breakdow n of earnings bet w een component s w it h different value relevance (cash flow s versus accruals), and earnings surprises.
Limit ed at t ent ion t heories imply posit ive abnormal ret urns aft er neglect ed good new s and negat ive abnormal ret urns aft er neglect ed bad new s. Firms can t emporarily increase t heir st ock prices t hrough earnings management , and presumably do so w hen t he gains fr om having a high st ock price are large.
For t wo reasons, limit ed at t ent ion causes overreact ions as well as underreact ions. First , invest ors overreact t o salient new s. Second, neglect of earnings component s implies
overreact ion t o t he less predict ive com ponent , accruals (Sloan (1996); Hirshleifer et al. (2011)).
Hong & St ein (1999) st udy t he int eract ion bet w een “ new s-w at chers” w ho condit ion only on signals about fut ure cash flows and “ m oment um t raders” who condit ion only on a part ial hist ory of prices. The informat ion possessed by news-wat chers is gradually incorporat ed int o prices, and naïve m oment um t rading causes t rends t o overshoot and lat er correct . This generat es ret urn under- and overreact ions. M oment um is st rongest am ong low -at t ent ion
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st ocks owing t o slower diffusion of informat ion. Consist ent wit h t his predict ion, Hong et al.
(2000) find t hat mom ent um is st ronger f or sm all st ocks and st ocks wit h low analyst coverage.
ii. Financial evidence on informat ion neglect , salience, and dist ract ion
A. Invest or naivet é
M any invest ors are naïve in t heir financial beliefs, and do not underst and basic concept s such as equit y or diversificat ion (Lusardi & M it chell (2011)). Not ably, t here are (short -lived) episodes of ext rem e t rading in response t o egregious confusions bet w een t he abbreviat ed nam es of firm s and t he t icker sym bols of ot her firm s (Rashes (2001)). Such episodes suggest t hat more subt le confusions are rife.
B. Evidence of pricing effect s of signal neglect and neglect of st rat egic mot ives
The int roduct ion gave an example of high influence of salient new s announcem ent s. At t he opposit e ext reme, t here is severe neglect of non-salient informat ion, such as t hat cont ained in demographic predict ors of shift s in product demand (DellaVigna & Pollet (2007)).
A venerable anomaly is t he sluggish react ion of st ock prices t o earnings surprises and revisions in analyst forecast s of earnings, post -earnings announcement drift or PEAD (Fost er et al. (1984); Bernard & Thomas (1989)). The fact t hat subsequent ret urns associat ed w it h
earnings surprises are concent rat ed at lat er earnings announcem ent s, and t hat market react ions reflect naïve seasonal random w alk expect at ions, support a lim it ed at t ent ion explanat ion.
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Accruals, t he account ing adjust m ent s m ade t o cash flow s t o obt ain ear nings, are less posit ive t han cash flow as a predict or of pr ofit abilit y. Neglect of t he dist inct ion bet w een t hese earnings com ponent s, and of t he incent ives of managers t o manage earnings, cause accruals and t heir abnormal `m anaged’ com ponent t o be negat ive predict ors of ret urns, t he accrual anomaly (Sloan (1996); Teoh et al. (1998a,b)). Accruals are also associat ed w it h bias in analyst forecast s (Teoh & Wong (2002)).
The accrual anomaly is based on a compar ison of t w o non-parallel quant it ies, earnings and cash f low . The cash analog t o earnings is Free Cash Flow , w hich is net of invest ment expendit ures (just as earnings is net of depreciat ion). So t he deviat ion bet w een cash and account ing profit abilit y should be a bet t er indicat or t han accruals of misvaluat ion. Cumulat ing t he deviat ions over t ime yields Net Operat ing Asset s, w hich t urns out t o be a m uch st ronger ret urn predict or t han accruals (Hirshleifer et al. (2004)).
Salience and dist ract ion, by modulat ing invest or at t ent ion, affect t rading and mispricing.
Several dat a confirm t hat informat ion t hat is m ore salient or easier t o process is incorporat ed more sharply int o prices. The prices of count ry funds underreact t o changes in t he value of underlying asset s, except w hen t he new s appears in t he f ront page of The New York Times (Klibanoff et al. (1998)). Indust ry informat ion is im pounded int o prices more rapidly in simple pure-play firms t han in conglom erat es t hat operat e across indust ries (Cohen & Lou (2012)).
Consist ent w it h high salience of new s m edia coverage and t he M iller (1977)
disagreement model, individual invest ors are net buyers of st ocks t hat have recent ly gained media at t ent ion, as w ell as st ocks w it h high abnormal t rading volume or ext reme one-day
23
ret urns (Barber & Odean (2008)). Suggest ive of gradual grow t h in net dem and for st ocks t hat have become t he focus of invest or at t ent ion, st ocks w it h unusually high t rading volum e over a day or a w eek on average earn a ret urn prem ium during t he next mont h (Gervais et al. (2001)).
There should generally be great er resort t o int uit ive, heurist ic t hinking w hen an invest or’s at t ent ional resources are deplet ed, such as w hen t here is great er decision pressure or dist ract ing new s. The sensit ivit y of t he m arket react ion t o earnings surprises is w eaker on Fridays w hen at t ent ion should be low (DellaVigna & Pollet (2009)), and w hen t he number of dist ract ing sam e-day earnings announcement s is large (Hirshleifer et al. (2009)), result ing in correspondingly larger post -earnings announcem ent drift .
b. Neglect ing basic feat ures of t he decision environment
Even professionals have cognit ive const raint s and rely on heur ist ics. For exam ple, a survey of CFOs found use of naïve capit al budget ing approaches such as t he payback crit erion, and t he use of a single discount rat e t o evaluat e very different kinds of project s (Graham &
Harvey (2001)).
In narrow framing (Kahneman & Lovallo (1993)), a decision problem is view ed in isolat ion from some of t he fact ors t hat are relevant for it . For exam ple, in Choi et al. (2009), individuals neglect ed t he employer mat ching feat ure of cont ribut ions t o t heir ret irem ent plans, unless t he decision problem w as designed t o force t hem t o m ake int egrat ed decisions. Under narrow fram ing, t he addit ion of each asset t o a port folio is evaluat ed based upon w het her it is viewed as inherent ly good or bad inst ead of in t erms of it s diversifying cont ribut ion t o t he overall port folio.
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In fact , people do t end t o invest in excessively narrow set s of asset s and asset classes. A not able st ylized fact is t hat invest ors t end t o eschew foreign securit ies, home bias (French &
Pot erba (1991); Tesar & Werner (1995)). This ef fect is st ronger for invest ors wit h lower cognit ive abilit ies and f inancial lit eracy (Grinblat t et al. (2011)). Sect ions 4 and 6 discuss ot her reasons for underdiversificat ion.
c. Financial t heories of cat egory t hinking
Behavioral explanat ions for comovem ent involve eit her irrat ional amplificat ion of fundament al com ovement , or ot her kinds of mispercept ions. In t he first approach,
overconfident invest ors w ho overreact t o informat ion about f undam ent al fact ors induce ret urn comovement (Daniel et al. (2001)).
In t he model of Hirshleifer & Jiang (2010), a fact or port folio is built by going long and short on misvalued firms, and a st ock’s fact or loading m easures t he ext ent t o w hich t he firm inherit s invest or overreact ion t o f undam ent al fact ors. Such loadings are t herefore proxies for firm-level m isvaluat ion. Em pirically, t here is comovem ent in st ock ret urns associat ed w it h a misvaluat ion fact or based upon debt and equit y issuance and repurchase; loadings on t his fact or are st rong ret urn predict ors.
An alt ernat ive explanat ion for comovement in excess of fundam ent als is t hat invest ors t hink heurist ically about securit y cat egories. A basic mechanism of t hought is classificat ion, so t hat inst ances can be evaluat ed based on feat ures of t heir cat egor ies (see, e.g., Ashby &
M addox (2005)). Such a heurist ic is pow erful, but flaw ed w hen cat egories are non-uniform.
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In t he st yle invest ing model of Barberis & Shleifer (2003), asset s t hat share a st yle comove more t han w ould be im plied by f undam ent als. Shift ing t he cat egory of an asset raises it s correlat ion wit h it s new st yle. Ow ing t o st yle-based t rading, st yle-level mom ent um and value st rat egies are predict ed t o be more profit able t han t heir asset -level count erpart s. Relat ed implicat ions can be derived in a model t hat f ocuses explicit ly on const raint s on invest or’s at t ent ion (Peng & Xiong (2006)).
St yle invest ing can explain t he t emporary high ret urns of st ocks upon S& P inclusion (Harris & Gurel (1986); Shleifer (1986)), comovem ent of st ocks t hat share st yles such as size and book-t o-market , and increased com ovement of st ocks t hat are added t o t he S& P 500 w it h exist ing index members (Barberis et al. (2005)).
Bot h overreact ion t o fundament al fact or signals, and st yle invest ing, im ply comovement in excess of w hat w ould be expect ed rat ionally. Consist ent w it h t his im plicat ion, presumably- naïve ret ail invest or t rading is associat ed w it h ret urn comovement (Kumar & Lee (2006)).
d. Reference-dependence and framing
Cognit ive processes are t o some ext ent specific t o t he domain of t he decision problem (Cosm ides & Tooby (2013)), and t o t he modalit y of present at ion (graphical, numerical, or verbal; probabilit ies versus frequencies; see, e.g., Gigerenzer & Hoffrage (1995)). Even for given t ype of decision problem and modalit y, alt ernat ive descript ions of logically ident ical decision problems, such as t he highlight ing of a different reference for com parison of out comes, have large effect s on choices, a phenomenon know n as framing (Tversky & Kahnem an (1981)).
Opt im izing based on deviat ions of payoffs from reference point s (a key feat ure of pr ospect
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t heory, discussed lat er in t his sect ion) implies framing effect s, and t herefore choices t hat become inconsist ent as changing present at ions or circumst ances cause t he reference point t o shift .
There is ext ensive evidence t hat seemingly irrelevant reference point s mat t er t o invest ors and firms. Firm s manage earnings t o meet salient t hresholds (forecast s or past
earnings; DeGeorge et al. (1999)), and st ock prices react sharply t o even a small short fall. Firms’
borrow ing rat es seem unduly influenced by previous rat es (Dougal et al. (2014)). Past st ock price highs affect firm and invest or behavior and predict fut ure st ock and market ret urns (George & Hw ang (2004); Baker et al. (2012)).
When individuals do not have an answ er t o a decision problem, t hey oft en subst it ut e t he solut ion t o a relat ed simpler problem , at t ribut e subst it ut ion (Kahneman & Frederick (2002)). This can explain money illusion (Fisher (1928)), wherein nominal inst ead of real prices are used for invest m ent decisions. In t his spirit , Rit t er & Warr (2002) argue t hat m ist aken discount ing at nom inal int erest rat es induced long U.S. bear and bull market s as inflat ionary t rends shift ed.
e. Concept ual discret izing, loss aversion, and probabilit y weight ing
Expect ed ut ilit y t heory cannot explain, wit h plausible levels of aversion t o large risks, t he degree t o w hich people avoid small gambles (Rabin (2000)). This phenomenon, called loss aversion (Kahneman & Tversky (1979)), has been modeled as a dist ast e for gambles w hose payoffs somet imes fall slight ly short of a reference point . This suggest s a kink in t he value funct ion at t he reference point (as in prospect t heory, discussed lat er; but see also Gal (2006)).
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Empirically, loss aversion affect s t he t rading decisions of professional invest ors (Coval &
Shum w ay (2005)). Econom ist s have long st rived t o underst and t he high est imat ed prem ium of equit y expect ed ret urns over bonds (\ cit eN{mehr a/ prescot t :85}). By increasing effect ive risk aversion, loss aversion offers a possible explanat ion for t he equit y prem ium and
nonpart icipat ion puzzles; shift s in loss aversion owing t o t he house m oney effect addit ionally can explain high equit y ret urn volat ilit y and t he value effect in t he cross-sect ion of ret urns (Benart zi & Thaler (1995) and Barberis & Huang (2001), but see also Beshears et al. (2012)). The equit y prem ium over long-t erm bond yields has, how ever, been sm all for t he last four decades (Welch & Levi (2013)), which is consist ent wit h t his explanat ion if invest ors over t im e have st art ed t o underst and t hat t heir loss aversion w as excessive.
Loss aversion may reflect t he use of a heurist ic of discret izing cont inuous variables so t hat even a small loss is perceived t o be essent ially different from a small gain. I call t his phenomenon concept ual discret izing.
Concept ual discret izing can also explain why individuals overw eight fairly unlikely event s yet underw eight ext remely unlikely ones (t reat ed as “ virt ually impossible” ); such probabilit y w eight ing is a key ingredient of prospect t heory. In t he m odel of Barberis & Huang (2008), probabilit y weight ing induces a demand for posit ively skewed “ lot t ery st ocks.” Alt ernat ively, social int eract ions can induce such a dem and even if invest ors have no direct preference for skew ness (Han & Hirshleifer (2014)). These approaches can explain t he high invest or demand for, and low fut ure ret urns experienced by posit ively skew ed st ocks (Boyer et al. (2010); Eraker
& Ready (2014)).
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f. M ent al account ing and realizat ion preference
M ent al account ing is t he syst em t hat people use t o t rack t heir gains and losses relat ive t o a reference point , and feel rew arded or punished for t hem. It involves narrow framing, wherein people separat ely opt imize different kinds of gains and losses t hat are placed in different ment al account s. Invest ors reexamine each account int ermit t ent ly for occasional act ion. Under ment al account ing, people care about t he labeling of payoffs by account , even w hen complet ely fungible across account s, as t his affect s at t ribut ion as a gain or a loss.
Narrow fram ing, reference-dependence, loss aversion, and ment al account ing are efficient ly modeled as nont radit ional preferences. However, all can be view ed as reflect ing mist akes of analysis or belief , as w it h an invest or w ho decides w het her t o sell a st ock by focusing on it s marginal ret urn dist ribut ion w it hout t hinking about w hy he should care about covariance w it h his port folio.
i. Realizat ion preference
If selling a st ock m akes t he increment al payoff in it s ment al account m ore salient ,
invest ors should become more w illing t o realize as t he net gain increases realizat ion preference.
Under loss aversion, t his applies even t o sm all gains and losses, implying a jump at zero, sign realizat ion preference. Such behavior can enhance self-est eem , if it is easier t o pret end t hat mere “ paper” losses w ill be regained.
In t he model of Grinblat t & Han (2005), a great er w illingness t o sell above t han below t he purchase price causes price underreact ion t o new s. Em pirically t his effect helps explain
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ret urn m oment um. How ever, pure underreact ion t heories do not explain t he evidence t hat moment um reverses in t he long-run (Griffin et al. (2003); Jegadeesh & Tit man (2011)).
In a t est focusing direct ly on realizat ions, Lim (2006) finds t hat individual invest ors are more likely t o sell losers on t he same day t han w inners on t he same day. This is consist ent w it h t he dual risk at t it udes of prospect t heory (risk loving in t he loss domain, risk averse in t he gain domain) t oget her wit h realizat ion preference.
A. The disposit ion effect
The disposit ion effect is t he st rong and w idespread regularit y t hat t he probabilit y of an invest or selling an asset condit ional upon a gain is great er t han condit ional upon a loss (Shefrin
& St at man (1985)). The disposit ion effect is oft en appealed t o as st rong evidence t hat psychological bias affect s t rading, yet it is not know n w hat bias causes it .
Experiment al and field evidence reveals a reverse disposit ion effect (selling losers) for delegat ed holdings in m ut ual funds. The reversal of t he disposit ion effect w hen invest ors can assign blame t o ot hers suggest s t hat t he urge t o maint ain self-est eem is a key driver of t he effect (Chang et al. (2014)).
A direct realizat ion preference explanat ion for t he disposit ion effect w as suggest ed by Shefrin & St at m an (1985) and modeled by Barberis & Xiong (2012). Ot her possible explanat ions derive from t he dual risk preference feat ure of prospect t heory; Barberis & Xiong (2009) point out limit at ions of t his approach, w hereas Henderson (2012) and Li & Yang (2013) describe condit ions under w hich t he prospect t heory explanat ion can w ork.
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There is evidence of neurological processes associat ed w it h realizat ion preference (Frydman et al. (2014)). How ever, discont inuit y t est s on U.S. invest or t rades do not support sign realizat ion preference, and show t hat it is not t he source of t he disposit ion ef fect . Furt hermore, t he empirical V-shape in probabilit y of bot h selling and buying as funct ions of gains or losses suggest s t hat realizat ion preference is not t he dominant m ot ive f or selling decisions in general (Ben-David & Hirshleifer (2012)).
Cont rary t o comm on discussions, t here is current ly no st rong em pirical indicat ion as t o w het her preference-based m odels or explicit belief bias models w ill offer a bet t er explanat ion for t he disposit ion effect . In em pirical papers, explanat ions have t ypically been discussed in a st at ic fashion; recent m odels derive predict ions t hat reflect t he dynam ics of t rading w it h realizat ion preference (Barberis & Xiong (2012), Ingersoll & Jin (2013)).
ii. Prospect t heory
Reference dependence and loss aversion are ingredient s of prospect t heory (Kahneman
& Tversky (1979); Tversky & Kahneman (1992)), w herein individuals maximize a w eight ed sum across st at es of t he w orld of value f unct ions (ut ilit ies), value depends on gains or losses rat her t han levels, and where t he weight s are funct ions of probabilit ies (in a fashion discussed earlier) . Value is an S-shaped funct ion of gain/ loss (dual risk at t it udes), result ing in risk aversion in t he gain domain and risk seeking in t he loss domain. Loss aversion is reflect ed in a kink in t he value funct ion at zero gain or loss. Financial t heories and evidence based upon t he different ingredient s of prospect t heory w ere discussed in earlier sect ions.
g. Heurist ic learning
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i. Represent at iveness, hyperact ive pat t ern-recognit ion, and overext rapolat ion
According t o t he represent at iveness heurist ic (Kahnem an & Tversky (1973)), people assess t he probabilit y of a st at e of t he w orld based on how t ypical of t hat st at e t he evidence seems t o be. This is reasonable if t ypicalit y proxies for t he condit ional probabilit y of t he evidence given t he st at e of t he w orld. How ever, rat ionally one should adjust f or t he prior probabilit ies of t he out com es. In realit y people t end t o underw eight verbal st at ement s about uncondit ional populat ion frequencies in updat ing beliefs— base-rat e underw eight ing. This is anot her sym pt om of W YSIATI.
Furt hermore, percept ions of how t ypical a piece of evidence is of a st at e of t he w orld oft en ref lect it s condit ional probabilit y poorly. For exam ple, error management t heory holds t hat t he hum an m ind evolved t o overw eight t he probabilit ies of opport unit ies or dangers w hen t he pot ent ial cost of neglect is high (Haselt on & Net t le (2006)). This suggest s t hat people are subject t o w hat m ay be called hyperact ive pat t ern recognit ion. For example, people t end t o overw eight small samples in draw ing inferences about dist ribut ions (t he law of small numbers, Tversky & Kahneman (1971)). How ever, t hey also rely t oo lit t le on large sam ples.
In financial market s, overext rapolat ion of securit y ret urns im plies posit ive feedback t rading. In t he model of DeLong et al. (1990b), exogenous posit ive feedback t rading causes overreact ion and long-run ret urn reversal, and pot ent ially short -run moment um as well.
In t he m odel of Barberis et al. (1998), conservat ism bias (Edw ards (1968)), in w hich individuals hold t oo t ight ly t o est im at es based upon early observat ions, causes short -t erm underreact ion t o earnings new s (consist ent w it h t he PEAD anomaly). Ow ing t o t he
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represent at iveness heurist ic, if sequences of good earnings new s occur, invest ors fixat e on t his pat t ern and overreact . This combinat ion of effect s generat es ret urn moment um and reversal, and an overreact ion/ reversal pat t ern in response t o t rends in public value signals (e.g., earnings new s sequences).
Empirically, invest ors do naïvely ext rapolat e in experim ent al market s, survey, and field st udies; and in various kinds of invest ment s (e.g., Smit h et al. (1988)). There is less support f or overreact ion t o t rends in public financial signals (Chan et al. (2004); Daniel & Tit m an (2006)).
ii. Reinforcement learning
Under reinforcement learning, an individual only ext rapolat es from his own direct experience, and wit hout properly reflect ing t he informat iveness of t he dat a. There is financial evidence t hat invest ors learn t o make financial decisions by naïve reinforcem ent . Invest ors overext rapolat e t heir own past perf ormance in making invest m ent choices (Choi et al. (2009);
Chiang et al. (2011)). Furt herm ore, past life experiences also affect bot h invest or and managerial decisions (Greenw ood & Nagel (2009), M almendier, Tat e & Yan (2011)).
iii. Inert ia and habit s
People easily lock int o habit s, and rely on t hem wit h lit t le t hought . This leads t o big mist akes w hen circumst ances change. When t here is m emory loss about t he reasons for past decisions, and if t he environment is reasonably st able, it is, nevert heless, const rained-opt im al t o rely on habit s (Hirshleifer & Welch (2002)). Act ion-induced at t it ude changes, as w it h
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cognit ive dissonance and t he sunk cost fallacy, can also induce inert ia. Em pirically, ret irement invest ors seldom updat e t heir port folios as condit ions change (Choi et al. (2004)).
The st at us quo bias (Sam uelson & Zeckhauser (1988)), a preference for t he default choice among a set of opt ions, also economizes on t he reasoning syst em’s slow , effort f ul cognit ion. For example, default s f or pension plan cont ribut ions and allocat ions have large effect s on invest m ent decisions (e.g., M adrian & Shea (2001)).
6. Feelings
Feelings are a key source of t he quick assessm ent s provided by t he int uit ive syst em, and can overw helm cooler analysis. For exam ple, people w ho plan t o consume sparingly are lat er t empt ed t o consume heavily, result ing in t ime-inconsist ent choices. This show s how immediacy can int ensify t he effect s of feelings. People w ho foresee t his can gain by imposing consum pt ion rules upon t hemselves (Ainslie (1975)).
Present -biased decision-making (quasi-hyperbolic discount ing; Laibson (1997)) has been applied in models of savings, liquidit y prem ia and t he equit y prem ium puzzle. To resolve t he t ime-inconsist ency of such preferences in favor of saving more, people impose personal rules such as consuming only out of int erest and dividends, not principal (Thaler & Shef rin (1981)).
This can explain t he preference of invest ors for cash dividends (Shefrin & St at man (1984)).
People oft en misat t ribut e arousal and ot her t ransient feelings t o ot her sources, biasing t heir judgment s (Schw arz & Clore (1983)). Good mood increases opt im ism and risk-t aking (Kuhnen & Knut son (2011)). The kind of feeling mat t ers, not just it s valence. For example,
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when fearful, people t end t o be m ore pessimist ic and risk averse; w hen angry, m ore opt imist ic and risk t olerant (Lerner & Kelt ner (2001)).
a. Familiarit y and liking
Exposure t o an unreinforced st imulus t ends t o make people like it more, t he mere exposure effect (Bornst ein & D'Agost ino (1992)). The evolut ionary basis f or t his m ay be t hat w hat is fam iliar t ends t o be underst ood bet t er, reducing risk; or t hat experience of a st im ulus wit hout adverse consequences indicat es low risk. Indeed, fam iliarit y reduces feelings of risk (Weber et al. (2005)). How ever, t he fam iliarit y heurist ic can go ast ray, as when people prefer t o bet on a m at t er about w hich t hey feel expert over anot her precisely equivalent gamble (Heat h
& Tversky (1991)).
The endow ment effect (Kahneman et al. (1990)) is a preference f or ret aining w hat one has over exchanging for a bet t er alt ernat ive (as w it h refusing t o sw ap a lot t ery t icket for an equivalent one plus cash). A possible explanat ion is loss aversion. Alt ernat ively, an already- ow ned good may be affect ively at t ract ive by virt ue of sense of ow nership.
Am biguit y aversion is a dist ast e for layered gambles relat ive t o single-st age gambles wit h ident ical payoff dist ribut ions (Ellsberg (1961); Bossaert s et al. (2010)). For exam ple, invest ors may dislike uncert aint y about t he st ruct ure of a f inancial market , as dist inguished from t he effect of t he f ut ure st at e realizat ion given t hat st ruct ure.
b. Financial t heories based on feelings
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Financial t heorizing about feelings has been most ly informal (but see M ehra & Sah (2002)), w hich is surprising given t heir psychological import ance. A basic t heme is t hat mood swings affect opt imism, risk t olerance, and market prices. Owing t o misat t ribut ion of t ransient mood t o long-t erm prospect s, mood sw ings associat ed w it h w eat her or sport s event s can affect prices (as document ed by Saunders (1993); Hirshleifer & Shum w ay (2003); Edm ans et al.
(2007)). Seasonal shift s in lengt h of day can induce Seasonal Affect ive Disorder, and are correlat ed w it h m arket ret urns (Kamst ra et al. (2003)).
Skept icism about t he foreign and unfamiliar offers an explanat ion for t he failure of invest ors t o part icipat e in import ant asset classes. M odels of am biguit y aversion can help explain non-part icipat ion, fam iliarit y bias, and t heir effect s on asset pricing (Chen & Epst ein (2002); Cao et al. (2011)). Such models pot ent ially have an affect ive int erpret at ion.
Feelings of envy m ay help explain t he at t ract iveness of invest ment s w it h lot t ery payoffs, as individuals hear about high payoffs obt ained by ot hers. In t he model of Goel & Thakor
(2010), t he t akeovers decisions of managers are influenced by feelings of envy t ow ard ot her managers, result ing in merger w aves.
c. Evidence on financial effect s of fam iliarit y and in-group bias
People prefer local invest ment s and familiar ones, such as firms t hat t hey are cust omers of (Grinblat t & Keloharju (2001); Huberman (2001)). One reason is t hat invest ors m ay have superior informat ion about local or fam iliar firms (Coval & M oskow it z (1999)). How ever, t his does not seem t o be t he only reason for local bias. For exam ple, at t he cost of poor
diversificat ion, employees invest in t heir own f irm s w it hout show ing signs of super ior
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informat ion (Benart zi (2001)). Furt hermore, informat ional superiorit y seems an unlikely explanat ion for hom e bias exhibit ed by great masses of unsophist icat ed invest ors.
In-group bias (belief in t he superior merit s of one’s ow n group), which is relat ively neglect ed in analyt ical modeling, implies bias in financial invest ing and economic exchange in favor of own-cult ure. Several st udies provide support ing evidence (Grinblat t & Keloharju (2001)).
Consist ent w it h in-group bias and w it h t heories based on aversion t o uncert aint y or unfamiliarit y, dist rust is an import ant bar rier t o part icipat ion in t he st ock market (Guiso et al.
(2008)) and exchange and invest ment bet w een count ries (Guiso et al. (2009)). M ore generally, fam iliarit y and in-group biases are sources of underdiversificat ion, a problem t o w hich
unsophist icat ed invest ors are especially subject (Goet zmann & Kumar (2008)).
d. Sent iment , shift ing opt imism and risk t olerance
Invest or sent iment is t he fluct uat ing general at t it ude t ow ard invest ment cat egories, such as grow t h st ocks or long-t erm bonds. It can be associat ed w it h shift s in assessments of expect ed ret urns or of risk. Waves of irrat ional ent husiasm for , or abhorrence of, cert ain
invest m ent charact erist ics derive from shift s in t he salience of emot ional or cognit ive t riggers in t he econom ic environment . Such shift s can be m agnified by self-reinforcing social processes induced by m edia bias or conform it y effect s.
In t he model of DeLong et al. (1990a), irrat ional noise t rading induces fluct uat ions in t he price of an asset wit h riskfree dividends. Short horizons of rat ional risk averse invest ors prevent
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full arbit rage bet w een t his asset and an asset w it h ident ical dividends t hat is not subject t o noise t rading. The t heory im plies t hat on average t he speculat ive asset t rades at a discount relat ive t o f undament als as compensat ion for it s excess volat ilit y.
Lee et al. (1991) m ore broadly suggest t hat closed-end funds, like ot her sm all st ocks, are subject t o noise t rading, so t hat irrat ional t rading induces prem ia or discount s relat ive t o t he price of t heir underlying asset s. Consist ent wit h a risk discount for st ochast ic fund prem ia, on average funds t rade at discount s relat ive t o t heir holdings. Furt hermore, discount s and prem ia comove across funds and w it h t he ret urns on sm all st ocks in general, w hich suggest s a comm on influence of sent iment among naïve individual invest ors.
If sent iment induces mispricing, t hen sent iment m easures should predict fut ure
abnorm al ret urns. Em pirically, U.S. closed end funds discount s and prem ia predict fut ure small st ock ret urns (Sw aminat han (1996)). How ever, in dist inguishing t he pricing effect s of sent iment from ot her hypot heses, it is useful t o employ measures of sent iment t hat are not based on market prices (Qiu & Welch (2006)). When several sent iment proxies are low , st ocks t hat are hard t o value and arbit rage earn high subsequent ret urns (Baker & W urgler (2006)). High sent iment increases t he profit abilit y of t he short legs but not t he long legs of cross-sect ional ret urn anomalies (St ambaugh et al. (2012)).
M easures of global sent im ent negat ively predict count ry-level ret urns. Bot h global and local sent iment are st ronger ret urn predict ors for st ocks t hat are hard t o value and t o arbit rage (Baker et al. (2012)).
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Shift s in market sent iment creat e incent ives for int erest ed part ies t o incit e misvaluat ion.
In t he t heory of Baker & Wurgler (2004), managers cat er t o invest or preferences for or against dividends. W hen t he st ock price prem ium on payers is high, firms st art paying dividends in order t o incit e higher valuat ion. Consist ent wit h t his predict ion, w hen sent iment favors dividends m ore, nonpayers t end t o init iat e dividends.
7. Firm behavior: Exploiting versus inciting misvaluation
A dist inct ion t hat is fundament al for firm behavior in inefficient m arket s is bet w een exploit ing mispricing, defined as an act ion t aken in response t o a preexist ing level of mispricing, and incit ing, an act ion designed t o shift t he level of mispricing (Hirshleifer (2001)). Incit ing t akes advant age of t he funct ion describing t he relat ion bet w een m arket price and t he firm’s act ion.1
1Incit ing encom passes act ions t aken t o shift mispricing eit her upw ard or dow nw ard. In cont rast ,
“ cat ering” (Baker & Wurgler (2012)) is def ined as an act ion t aken t o increase price above fundament al value.
Also, it is comm on t o dist inguish incit ing or cat ering from t iming, wherein t he f irm is sure t o undert ake t he act ion, but uses discret ion as t o w hen. How ever, t his is not an exhaust ive part it ion of cases; a firm can exploit in it s choice of w het her rat her t han w hen t o t ake an act ion.
Post -event ret urn drift is oft en int erpret ed as t im ing w it hout considerat ion of t his very plausible possibilit y. M ore import ant ly, t he possibilit y of incit em ent of misvaluat ion is oft en ignored in favor of t iming in response t o preexist ing misvaluat ion.
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To illust rat e t his dist inct ion, consider a firm t hat issues equit y t o exploit preexist ing overvaluat ion. Ow ing t o t he negat ive average react ion t o t he announcement , t here t ends t o be a reduct ion in overvaluat ion, but t his w ill normally be an unavoidable adverse side-effect f rom t he firm ’s view point , in w hich case t his is not incit ement . In cont rast , a repurchase can be incit ement if it s purpose is t o induce higher valuat ion (rat her t han merely dist ribut ing cash, or profit ing from purchasing underpriced shares).
Upw ard earnings management designed t o induce overvaluat ion (or eliminat e
undervaluat ion) is also incit ement . M ost financial execut ives in one survey report ed t hat t hey would sacrifice economic value in order t o avoid missing quart erly earnings forecast s (Graham et al. (2005)). Sim ilarly, managing earnings dow nward w it h t he purpose of reducing t he st ock price (e.g., t o persuade pot ent ial com pet it ors t hat t he business is unprofit able, or t o reduce t he cost of share repurchase), is dow nw ard incit em ent . Verbal communicat ion can also be used t o incit e m isvaluat ion, as wit h m isleading disclosures, and discussions w it h m edia and analyst s (t ypically upward “ hype” ).
a. Theories of exploit ive advisors and firms
Sect ion 5 point s out t hat neglect of public signals result s in ret urn predict abilit y based upon t he account ing informat ion, and t herefore t hat m anipulat ion of disclosures can incit e over- or undervaluat ion (Hirshleifer & Teoh (2003); Hirshleifer et al. (2011)).
St ein (1996) models t he exploit at ion of exogenous st ock m arket mispricing by f irms in t heir financing and invest ment decisions. In St ein’s model, misvaluat ion affect s real invest m ent decisions m ore w hen managers have short t ime horizons, and firms should somet imes
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pat ernalist ically discount using bet a even w hen bet a is not a ret urn predict or. In Daniel et al.
(1998), new issues and repurchase am ount s are select ed by a firm as a funct ion of m ispricing t o exploit invest or overconfidence. This im plies posit ive abnorm al ret urns aft er repurchase and negat ive aft er new issues.
Ljungqvist et al. (2006) model t he exploit at ion of individual invest or opt im ism in init ial public offerings. Cornelli et al. (2006) provide evidence t hat inst it ut ional invest ors and
underwrit ers exploit m isvaluat ion of IPOs by individual invest ors.
Invest ors wit h limit ed at t ent ion w ill somet im es overlook opport unism. One way t o exploit cust om ers is t o add com plexit y; in t he m odel of Carlin (2009), int ent ionally added complexit y of financial product s result s in equilibrium price dispersion am ong compet ing providers.
Exploit at ion and incit ement can have adverse macroeconomic effect s as w ell. In t he t heory of Gennaioli et al. (2012a), int ermediaries design securit ies t hat seem nearly riskfree t o t ake advant age of invest or neglect of nonsalient risks. This result s in booms and crashes.
b. Evidence on exploit ive advisors and firms
Evidence suggest s t hat invest ors are overly credulous about t he st rat egic incent ives of informat ion sources, leaving t hem vulnerable t o manipulat ion by f irms, advisors, and
int ermediaries (such as analyst s, brokers, and m oney managers). Daniel et al. (2002) argue t hat credulit y derives from lim it ed at t ent ion and overconfidence, and t hat it explains a w ide range
