Local Does as Local Is: Informaion Conen of he Geography of Individual Invesors Common Sock Invesmens Zoran Ivković and Sco Weisbenner Deparmen of Finance Universiy of Illinois a Urbana-Champaign 340 Wohlers Hall 1206 Souh Sixh Sree Champaign, IL 61820 Tel.: (217) 265-5477, 333-0872 Fax: (217) 244-3102 E-mail: ivkovich@uiuc.edu, weisbenn@uiuc.edu Sco Weisbenner is wih he NBER. We would like o exend our graiude o an anonymous reail discoun broker for providing he daa on individual invesors posiions, rades, and demographics. Special hanks go o Terry Odean for his help in obaining and undersanding he daa se. We hank Alok Kumar for useful insighs and helpful discussions. Boh auhors acknowledge he financial suppor from he College Research Board a he Universiy of Illinois a Urbana-Champaign. Finally, we hank seminar paricipans a he Universiy of Illinois for heir commens and consrucive suggesions. All remaining errors are he sole responsibiliy of he auhors.
Local Does as Local Is: Informaion Conen of he Geography of Individual Invesors Common Sock Invesmens Absrac Using a daa se on a large number of reail invesors from 1991-96, we find ha households exhibi a srong preference for local invesmen he average household invess nearly a hird of heir porfolio in firms headquarered wihin 250 miles. We es wheher his localiy bias is driven by informaion or by simple familiariy. The average household generaes an addiional reurn of 3.7% per year from is local holdings relaive o is non-local holdings, suggesing local invesors are able o exploi local knowledge. The excess reurn o invesing locally is even larger among socks no in he S&P 500 index (firms where informaional asymmeries beween local and non-local invesors may be larges), while here is no excess reurn earned by households ha inves in local S&P 500 socks. Moreover, he paerns in urnover, herding, and excess demand across local and non-local rades are suggesive of a gradual disseminaion of informaion. JEL Classificaion: G12; G14; D82; G11 Keywords: Local Bias; Individual Invesors; Informaional Asymmery; Informaion Diffusion 1
Behold, he fool saih, Pu no all hine eggs in he one baske which is bu a manner of saying, Scaer your money and your aenion ; bu he wise man saih, Pu all your eggs in one baske and wach ha baske. Mark Twain 1894 The finance lieraure has yielded a large number of in-deph sudies concerning he invesmens managed by professional money managers, ye, hisorically, relaively lile has been known abou individual invesors money managemen, in no small par because of he shorage of highqualiy daa available for academic research. This, despie he fac ha U.S. individual invesors have been holding around 50% of he sock marke in direc sock invesmens. The key issue we address in his paper is he availabiliy of asymmeric informaion in financial markes, paricularly in he conex of geography of invesmen by individual invesors. While i is well undersood ha here may be a number of deerminans of he availabiliy and qualiy of informaion abou a company, including, for example, company size, number of analyss following i, and he media coverage, i is reasonable o hypohesize ha, ceeris paribus, invesors may be able o gaher value-relevan informaion abou companies local o hem (henceforh local companies) wih greaer ease and accuracy han hey could abou remoe companies (henceforh non-local companies). Indeed, Coval and Moskowiz (2001) demonsrae ha professional managers local invesmens ouperform heir remoe invesmens, a finding ha boh provides a richer characerizaion of professional managers skill and, more imporanly in he conex of his paper, suggess ha proximiy o invesmen opporuniies faciliaes he acquisiion of disproporionaely accurae value-relevan informaion. Using a deailed daa se on he invesmens 78,000 U.S. reail invesors made hrough a large discoun broker over he six-year period from 1991 o 1996, 1 we find ha individual 1 To proec he confidenialiy and anonymiy of invesor daa and he reail broker, all researchers using he daa se mus sign and adhere o an appropriae non-disclosure agreemen. 2
invesors exhibi local bias, ha is, disproporionae preference for local socks, o an even larger degree han U.S. muual fund managers do (see Coval and Moskowiz, 1999). 2 While i appears ha he professional managers preferences for, and especially success in, pursuing local invesmen opporuniies sem from heir abiliy o exploi he ensuing informaion asymmeries (Coval and Moskowiz, 2001), i is no clear wheher he individual invesors local bias is primarily a resul of heir abiliy o exploi asymmeric informaion or heir inclinaion simply o inves ino he companies hey are familiar wih (hough no necessarily paricularly informed abou). On he one hand, if he individual invesors local bias is informaion-driven, we should uncover evidence of superioriy of heir local invesmens, a leas relaive o heir non-local invesmens. Such a finding would shed some ligh no only on he individual invesors abiliy o idenify and exploi informaional asymmeries, bu also on he inerpreaion of he professional managers invesmen skill. Indeed, if individual invesors could generae superior reurns on heir local invesmens, hen such an accomplishmen by professional managers would seem less impressive and should be reinerpreed primarily as he skill firs o realize ha here is invesmen value in uncovering local informaion and hen o collec i, raher han he skill o carry ou paricularly insighful analyses of such informaion. On he oher hand, here is evidence ha people end disproporionaely o inves in he companies hey are relaively familiar wih, be i by virue of heir inclinaion o favor domesic invesmens over invesmens in foreign asses he so-called home bias, 3 or, in he domesic arena, inves disproporionaely ino own-company sock (Benarzi (2001) and Liang & Weisbenner (2002)). If individual invesors local invesmens sem primarily from noninformaion based reasons, as he evidence presened in Huberman (2001), Grinbla and Kelohraju (2001), and Zhu (2002) suggess, hen invesors localiy should be inerpreed primarily as a behavioral phenomenon. We find ha he average share of local invesmens (defined as he invesmens ino companies headquarered wihin 250 miles from he invesor) is around 30%, boh in erms of he number of socks in he household porfolio and heir value. This figure is disproporionaely 2 For exising sudies of individual invesors invesmen see, e.g., Barber and Odean (2000, 2001), Dhar and Kumar (2001), Dhar and Zhu (2002), Goezmann and Kumar (2002), Hong and Kumar (2002), Kumar (2002), and Zhu (2002). 3
high nearly 20 percenage poins higher han he average percen of all firms headquarered wihin 250 miles from he household (boh equally and value-weighed). Afer documening he local bias in household porfolios and he persisence of localiy over ime, we explore in deail he deerminans of sock urnover, herding, and excess demand, boh for all rades and separaely for local and non-local rades. This exen of deailed insigh ino individual invesors rading paerns as hey relae o localiy of invesmen has no been repored in he lieraure, largely because of he lack of appropriae daa. Variables of paricular ineres are he exen of firm relaive local ownership and he S&P 500 saus (proxy for he exen of informaion asymmery). In regard o sock urnover, he key resul is a sharp difference beween he loadings on firm local ownership among non-local and local rades: he effec is posiive for he former, ye negaive for he laer. We inerpre he posiive relaion for non-local rades as indirec evidence of informaion diffusion: non-local invesors may have evenually acquired he value-relevan news abou he sock and are rading in i only afer he local invesors have done so. This resul is also consisen wih local invesors being conen wih heir posiion in he sock afer heir iniial rades, and local invesors ha missed he boa being relucan o buy now, given ha hey had no purchased he sock already. Local and non-local rades generae diamerically opposie herding paerns wih respec o firm local ownership he relaion is posiive (negaive) for non-local (local) rades. As wih urnover, we inerpre his finding as indirec evidence of informaion diffusion, wherein nonlocal invesors may evenually acquire value-relevan informaion and henceforh herd when his previously locally available informaion becomes more widespread, whereas local invesors reaced o he informaion obained locally in a imely fashion: following he period of heir rading on locally available value-relevan informaion, local households are now conen wih heir posiion in he sock and are less likely o join non-local households in laer herding on ha sock. We find a similar paern in resuls when we focus on excess demand (he imbalance beween buying and selling aciviy of a sock) for local and non-local invesors as well. The cenral quesion we address is wheher local invesmens are based on value-relevan informaion, in which case hose invesmens should do well on average, or wheher hey sem 3 For key resuls relaed o home bias see, e.g., French and Poerba (1991), Cooper and Kaplanis (1994), Gehrig (1993), and Tesar and Werner (1997). 4
primarily from households invesing ino he companies hey are familiar wih, hough no necessarily paricularly informed abou, in which case he local invesmens will likely no earn superior reurns on average. Thus, we nex address he relaion beween locaion-driven informaion asymmery and household porfolio reurns. Simply pu, if individual invesors succeed in collecing and processing locally available value-relevan informaion, hen he value of ha informaion should be refleced in he performance of heir household porfolios. In our iniial inquiry, we find ha local invesmens ouperformed non-local ones by 3.7% per year over a one-year horizon. The excess reurn o invesing locally is even larger among socks no in he S&P 500 index (firms where informaional asymmeries beween local and non-local invesors may be larges), while here is no excess reurn earned by households ha inves in local S&P 500 socks (where informaional asymmeries are likely smalles). Moreover, he evidence is robus o he choice of he period of reurns measuremen and adjusmen for risk. Having esablished ha household porfolio performance is posiively relaed wih he exen and naure of localiy in invesors porfolios and ha he bulk of he performance differenial sems from he invesmens in less widely known (non-s&p 500) socks, we explore he benefis of pursuing localiy by mimicking households local invesmens and shying away from heir non-local invesmens. To ha end, we firs dissec common socks in each household porfolio according o wo dimensions, localiy of he socks and heir S&P 500 saus (our proxy for informaion asymmery), and hen form aggregae posiion-weighed porfolios across all households. The resuls suppor he hypohesis ha locally available informaion is valuerelevan. Specifically, he zero-cos porfolio ha akes a long posiion in local invesmens and a shor posiion in non-local invesmens has saisically and economically significan reurns: monhly raw (risk-adjused) reurns are 19 (12) basis poins. This effec sems primarily from he socks ha exhibi more informaion asymmery. Indeed, he corresponding raw reurns and riskadjused reurns are subsanially smaller for S&P 500 socks (12 and 8 basis poins per monh, respecively) han for non-s&p 500 socks (27 and 26 basis poins per monh, respecively). These resuls are sriking, as he only porfolio formaion crieria were relaed o he geography and a basic sock index membership characerisic. Even hese simple breakdowns yielded abnormal performance of 3.2-3.3% per year, and adjusmen for risk characerisics of he porfolios made virually no difference. 5
The final quesion we address is wheher he effec of locally available value-relevan informaion can be compensaed for by simply observing a firm s local ownership, ha is, he collecive opinion of he poenial invesors local o he firm. In oher words, if he invesor is no local, should he join he locals (i.e., follow he acions of he invesors local o he firm)? The resuls sugges ha merely favoring non-local non-s&p 500 socks wih high local ownership goes a long way oward reducing and almos eliminaing he informaion asymmery beween he local and non-local non-s&p 500 socks. Simply pu, mimicking wha locals do is abou as good as being local. The remainder of his paper is organized as follows. Secion I presens he daa and summary saisics. Secion II considers he characerisics, deerminans, and persisence of localiy of invesmen from he perspecive of he household. Secion III focuses on he deerminans and persisence of firm relaive local ownership; i also relaes firm relaive local ownership wih sock urnover, herding, excess demand, and fuure expeced sock reurns. Secion IV seeks o characerize and quanify he informaion asymmery relaed o localiy of invesmen. Finally, Secion V concludes. I. Daa and Descripive Saisics I.A. Daa We compile he daa for his paper from several sources. The primary source is a large daa se, obained from a reail brokerage house, of individual invesors monhly posiions and rades over a six-year period from 1991 o 1996. The daa se covers all he invesmens 78,000 households made hrough he brokerage house, ranging from common socks, muual funds, governmen and corporae bonds, foreign securiies, o derivaives. Each household could have as few as one accoun and as many as 21 accouns (he median is 2). The daa se also provides some informaion abou he households, such as heir zip code, self-repored income, occupaion, and age. For a deailed descripion of he daa se see Barber and Odean (2000). In his paper we focus on he common socks raded on he NYSE, AMEX, and NASDAQ exchanges. Common sock invesmens consiue nearly 2/3 of he oal value of household invesmens in he sample. We use he Cener for Research in Securiy Prices (CRSP) daabase o obain informaion on sock prices and reurns and COMPUSTAT o obain several firm characerisics, including company headquarers locaion (idenified by is sae and couny 6
codes). We use he headquarers locaion as opposed o he sae of incorporaion because firms ofen do no have he majoriy of heir operaions in heir sae of incorporaion. The sample of households used in his sudy is a subse of he enire collecion of households for which we could ascerain heir zip code and hus deermine heir locaion. We idenify around 11,300 disinc zip codes in he daa. We exclude from he sample households ha were no locaed in he coninenal U.S. (ha is, invesors from Hawaii, Alaska, and Puero Rico) and several zip codes corresponding o miliary insallaions. We obained he laiude and longiude for each of he zip codes from he U.S. Census Bureau s Gazeeer Place and Zip Code Daabase. The corresponding company locaion comes from COMPUSTAT Annual Research Files, which conain he informaion regarding he company headquarers couny code. Finally, we idenify he laiude and longiude for each couny from he U.S. Census Bureau s Gazeeer Place and Zip Code Daabase as well. We use he sandard formula for compuing he disance d(a,b) in sauory miles beween wo poins a and b as follows: π d(a,b) = arccos{cos(a 1 )cos(b 1 )cos(a 2 )cos(b 2 )+cos(a 1 )sin(b 1 )cos(a 2 )sin(b 2 )+sin(a 1 )sin(a 2 )} r, (1) 180 where a 1 and b 1 (a 2 and b 2 )are he laiudes (longiudes) of poins a and b (expressed in degrees), respecively, and r denoes he radius of he Earh (approximaely 3,963 sauory miles). We exclude he socks we could no mach wih CRSP and COMPUSTAT; hey were mos likely lised on smaller exchanges. We also exclude socks no headquarered in he coninenal U.S. The resuling marke he universe of socks we could obain he necessary characerisics and informaion abou consiss of 4,827 socks a he end of 1991, which cover 76% of he overall marke capializaion a he end of 1991. In each sample year, we discard he households wih he oal porfolio value under $1,000 as of he end of he previous year. In sum, he resuling sample of households holding a leas one common sock ha we could idenify and characerize in a leas one of heir accoun porfolios consiss of 31,828 households a he end of 1991. This number ends o change somewha over he sample period, reflecing primarily he liquidaion of some accouns (he rades in he las monh sell off he posiions a he end of he previous monh and here are no subsequen posiions or rades recorded for he accoun). 7
I.B. Descripive Saisics Basic household sample characerisics are presened in Table I. The able repors summary saisics of household income and household porfolio saisics a he end of 1991. 4 Panel A presens he income saisics. Households could repor income in nine ranges (0 15, 15 20, 20 30, 30 40, 40 50, 50 75, 75 100, 100 125, and 125+ housands of dollars per year). One eighh of he households (13%) did no provide income informaion. We assume ha he income level for he households in he firs eigh caegories was he midpoin of he income range. Based on calculaions using he 1992 Survey of Consumer Finances (SCF), he average household income in 1991 for households ha had a leas $125,000 of income was $250,000 (see Kennickell and Sarr-McCluer (1994) for a descripion of he SCF daa se). Thus, we assign he income level of $250,000 o he households ha repored income greaer han $125,000. The median household ha acually repored is annual income repored income in he range from $50,000 o $75,000 (he midpoin presened in he able is $63 housand) and he inerquarile range of income range midpoins is $45 $113 housand. Thus, households in he sample are clearly more affluen han he average household in he U.S. Panel B focuses on households porfolios of NYSE, AMEX, and NASDAQ common socks as documened by he posiion files a he end of 1991. The mean value of common socks in household porfolios was $29,643, while he median was $11,201. The average household held relaively few socks (on average 3.0 socks; he median was only 2 socks per household). Around 38% of he households in he sample held asses oher han common socks (mos ofen muual funds). Among such households, around one-hird of he average household porfolio was allocaed o asses oher han common socks (35% average; 29% median). Thus, he commonsock porions of household porfolios in he sample ypically consised of a handful of socks, which precludes he possibiliy of exensive diversificaion among common socks. 5 We focus on hese hree household porfolio characerisics and on household income because we view hem as (admiedly noisy) measures of wo imporan faces of invesmen: propensiy oward 4 Porfolio summary saisics for subsequen years (no repored) are qualiaively similar o hose presened in Table I. Deails are available upon reques. 5 While diversificaion could be more pronounced for he households holding oher asse classes, he summary saisics sugges ha nearly 2/3 of all households in he sample (62%) held only (ypically very few) common socks and were hus largely undiversified. Moreover, Goezmann and Kumar (2002) show ha he invesors porfolios were under-diversified relaive o he exen of diversificaion possible when holding few socks. 8
diversificaion (larger number of socks, presence of asse classes oher han common socks) and availabiliy of resources o collec informaion (larger dollar value of he porfolio and household income). Table I, Panel C furher summarizes household porfolio saisics peraining o he localiy of heir common sock invesmens according o wo merics. The firs is a simple comparison of he disance from he household o is porfolio and he disance from he household o he marke porfolio (he upper hree rows in he panel). The second meric employs household proximiy o company headquarers, where we se he hreshold of localiy a he disance of 250 miles (he lower hree rows in he panel). Household porfolio disance measures were compued by value-weighing he disance measures across individual socks in he porfolio according o heir household porfolio equiy posiion. Panel C of Table I provides evidence of considerable local bias. The average (median) porfolio is closer o he household han he marke by abou 300 miles. Pu differenly, average (median) households were closer o heir porfolios han o he marke porfolio by around 23%, alhough he nonrivial inerquarile range suggess a broad range of localiy, from households subsanially closer o heir porfolio han o he marke (by around 700 miles or more) o hose ha are somewha furher away from heir porfolio han o he marke (by around 150 miles or more). These figures, hough illusraive, do no necessarily rea invesors in an equiable fashion, as invesors in New York, for example, ha hold he marke porfolio would urn ou o be far more local han invesors in Norh Dakoa ha hold he same porfolio. In mos subsequen analyses, we use a more inuiive and less biased approach. We regard 250 miles as a plausible upper bound on he span of local informaion and regard all invesmens ino companies whose headquarers are wihin ha disance as local. The disance of 250 miles is sill reachable via a moderaely srenuous daily roundrip by car; local newspapers, radio, TV, and oher media sill occasionally provide some coverage of he local evens wihin ha disance. This cuoff is admiedly arbirary and i could be argued ha i is on he conservaive side. 6 Neverheless, we idenify srong localiy effecs ha mach economic inuiion based on informaion asymmery. 6 As a robusness check, we replicae he key analyses wih he localiy cuoff se a 100 kilomeers (see Secion IV.F) and he resuls are even sronger, which suggess ha our choice of 250 miles as he cuoff is conservaive. 9
In he sample of households a he end of 1991 he mean (median) percenage of he number of socks in he household porfolio headquarered wihin 250 miles from he invesor is 30.7% (0%). In fac, slighly less han one-half of he households (15,458 of 31,828) inves in a leas one local firm. The inerquarile range furher suggess ha a leas 25% of he households in he sample have more local han non-local socks in heir porfolios (he acual number is 32%), a saisic ha could be driven in par by he geographic disribuion of invesors and companies. As shown in Figure 1, New York and California boas disproporionaely high numbers of boh. We conrol for he geographic disribuion of companies relaive o invesors by subracing from his percenage anoher percenage he fracion of all firms wihin 250 miles (presened in he fifh row of Table I, Panel C). The resuling measure of household localiy, call i H LOC,w, is summarized in he las row of Table I, Panel C. I is similar o he simple disribuion of he percenage of porfolio socks wihin 250 miles. The mean percenage of local firms ha households inves ino exceeds he percenage of all local firms by 18.1% on average. Before proceeding, we provide an illusraion of he properies of H LOC,w. Is range is from 42% o 99.95% a he end of 1991. The firs (low) exreme is ypical of he households ha chose o inves only non-locally, ye live in he area wih many local invesmen opporuniies (large percenage of he oal marke). A prominen example is a compleely nonlocal invesor living in New York Ciy or Silicon Valley. The oher exreme is ypical of invesors living in remoe areas where here are very few local invesmen opporuniies (and all are very small companies), ye heir enire household porfolios are invesed locally. II. Household Localiy II.A. Household Localiy Characerisics Table II explores household porfolio localiy in sill more deail. The firs column repors he disribuion of household invesmens by localiy ha would prevail if invesors invesed in he marke porfolio. The nex five columns presen shares of porfolio value for all households, as well as he subsamples seleced according o cerain characerisics. Finally, he las column presens he fracion of households ha inves only ino one of he caegories lised in he rows of he able in boh panels. 10
The firs wo columns illusrae how he porfolio shares deviae from he shares ha would be found if every household invesed in he marke porfolio. For example, he average household invess 31% of is porfolio locally; however, he local share would be only 13% if each household invesed in he marke. The bulk of his local bias can be aribued o invesmens in local non-s&p 500 socks. These socks consiue on average 15% of he household porfolio, bu would only make up 3% if he household invesed in he marke. Households also end o place disproporionaely more weigh on local S&P 500 socks (16% in acual porfolio versus 9% in he marke porfolio on average), while placing subsanially less weigh on non-local S&P 500 socks (41% in acual porfolio versus 61% in he marke porfolio on average). Finally, he average household porfolio share allocaed o S&P 500 socks is 57%, 14% less han he share if invesing in he marke porfolio. Inuiively, i is his 14% underweighing of he S&P 500 ha allows for he 12% over-weighing of non-local non-s&p 500 socks in he average household porfolio. These endencies may be relaed o informaion asymmery. Simply pu, here are likely companies abou which here is more informaion han he ohers. Poenial deerminans of such informaion asymmery could include he overall size of he company (measured by marke capializaion, number of employees, number of plans, ec.), he number of analyss following he sock, and membership in a major sock index. For example, he poenial for sizeable informaion asymmery is considerably smaller for S&P 500 han for non-s&p 500 companies. Thus, i is likely ha informaion asymmery is he mos pronounced in he case of non-local vs. local invesmen ino non-s&p 500 companies. Inuiively, invesmens ino local S&P 500 socks are unlikely o be driven by he hope o exploi value-relevan informaion available only o local individual invesors. The second column of Table II suggess individual invesors porfolios exhibi greaer disproporion beween S&P 500 and non-s&p 500 non-local invesmens han beween local ones. Across all households, 3/5 of non-local invesmens are in S&P 500 companies on average, while roughly half of local invesmens are in S&P 500 firms. Thus, invesors end o favor he remoe familiariy of non-local S&P 500 socks over he uncerainy of non-local non-s&p 500 socks. The nex four columns of Table II es for robusness of he basic breakdown; hey feaure virually idenical breakdowns for all households exclusive of CA, CA households, households wih porfolio value of a leas $10,000, and a leas $50,000 respecively. Focusing on 11
households from California, who consiue jus over one quarer of he sample, is done o confirm ha localiy in invesmens is no driven by hese CA households. The exen of localiy of households wih larger porfolios is an empirical issue. I could be higher han for smaller porfolios because larger porfolios signal he availabiliy of resources o invesigae and uncover value-relevan local informaion. On he oher hand, i could be lower because larger porfolios are likely o consis of more socks and also be combined wih invesmens oher han common socks, boh of which are suggesive of endencies o achieve beer diversificaion. As i urns ou, wih he increase in porfolio value he presence in local non-s&p 500 socks is gradually subsiued wih non-local S&P 500 socks. Finally, he las column of Table II illusraes ha many households are eiher all local (one-sixh) or all non-local (one-half). This is no oo surprising, given he small number of socks in he average household porfolio. Abou one ou of every welve households only hold non-s&p 500 firms headquarered wihin 250 miles. II.B. Household Localiy Deerminans Table III presens he resuls of fiing cross-secional regressions of four household porfolio localiy measures (HHP_Localiy), compued a he end of 1991 and summarized in Table I, 7 on several explanaory variables as follows: HHP_Localiy = α + β 1 Log(No_socks_in_HHP) + β 2 Log(Value_of_socks_in_HHP) + β 3 Log(HH_Income) + β 4 No_Repor_Income + β 5 Hold_Oher_Asses (2) Each specificaion is fied in boh he OLS and he fixed-effecs regression frameworks. The inen of he fixed-effec regression, carried ou a he zip-code level, is o conrol for poenial biases in he geographic disribuion of households and firms in he sample. The firs wo measures are based on he average disance from he household o is porfolio and hus are negaively relaed o household porfolio localiy. By conras, he oher wo measures are based on he fracion of porfolio value wihin 250 miles from he household and are each posiively relaed o household porfolio localiy. Consisenly across all specificaion, variables Log(No_socks_in_HHP) and Hold_Oher_Asses are saisically significan and are boh negaively relaed o HHP_Localiy. 12
This finding is inuiive, as i suggess ha a larger exen of diversificaion ranslaes ino a smaller exen of household porfolio localiy. On he oher hand, Log(Value_of_socks_in_HHP) is also saisically significan across all specificaions, bu is posiively relaed o localiy. The same is rue of Log(HH_Income), alhough i lacks saisical significance, especially in he fixed effecs regressions. Boh Log(Value_of_socks_in_HHP) and Log(HH_Income) are indicaive of he availabiliy of resources and experise in informaion acquisiion, which appears o be more efficien in he domain of local socks, hus resuling in increasing household porfolio localiy. II.C. Household Localiy Persisence Resuls presened hus far show ha household porfolios on average feaure considerable bias oward local invesmen, hough he cross-secional disribuion of localiy across households conains nonrivial fracions of household porfolios ha hold only local socks and household porfolios ha hold only non-local socks. While in unrepored analyses we find ha hese facs persis from year o year, his does no necessarily imply ha he localiy of household porfolios hemselves is a highly persisen phenomenon. To assess he persisence of household porfolio localiy, a he end of each year in he sample period we rank household porfolios according o heir localiy measure H LOC,w, compued by subracing from he fracion of household porfolio value invesed locally he weigh of he marke porfolio ha is local (wihin 250 miles) o he household, and race ha rank for each household porfolio over he nex wo years. The challenge in inerpreing localiy persisence is o separae persisence hrough inaciviy (accidenal persisence) from persisence despie inense rading aciviy (deliberae persisence). Indeed, he localiy persisence of a household porfolio ha did no rade a all, or raded very lile, is differen from ha of a household porfolio ha had a high annual urnover of 100% or more, hus creaed sufficien rading aciviy o have urned he enire porfolio over in a year and poenially profoundly changed is localiy, bu sill chose o remain a local invesor. The definiion of household porfolio urnover in year +1 ha we use below is he raio of he minimum of dollar values of porfolio buys and sells in year +1 and he oal dollar value of he household porfolio a he end of year. 7 Resuls based on year-end measures of localiy and explanaory variables for he remaining years in he sample (1992 hrough 1995) are qualiaively similar. Resuls are available from auhors upon reques. 13
Table IV summarizes he evidence of household porfolio persisence. Each panel feaures a simple breakdown of household porfolio localiy rank in year +1 and +2 condiional upon he rank in year. The analysis encompasses 81,578 household porfolios ha repored a oal equiy posiion of a leas $1,000 a he beginning of hree consecuive years (pooled over hree-year inervals from 1991 o 1996). A firs glance, focusing on all households suggess srong persisence. For example, 81% of households classified below he median in year remain below he median in boh year +1 and +2. Moreover, 71% of he household porfolios in he op quarile of localiy in year persis in he op quarile in boh year +1 and +2. To accoun for he differences in household porfolio urnover, we spli household porfolios according o heir annual urnover in year +1 (and, where applicable, in boh year +1 and year +2) ino quariles and deciles (he cuoffs are 0% for boh he firs and second quariles, 22% for he hird quarile, and 114% for he ninh decile). As one would expec, he exen of persisence declines as household porfolio urnover increases. However, his analysis idenifies remarkable persisence in localiy among household porfolios wih annual urnover of a leas 114% (Panel B). Under he null hypohesis of no localiy persisence (i.e., wih respec o localiy porfolio composiion is random from year o year), esimaes of he expeced percenages for he high-urnover household porfolios ha remain he mos local (i.e., in he op quarile of household porfolio localiy), given ha household porfolio urnover is a leas 100% per year, are 25% in year +1 and only 6.25% for year +1 and +2. The probabiliy of remaining above/below he localiy median is 50% in year +1 and 25% in boh year +1 and year +2. All he acual raes of persisence among he household in he op decile wih respec o porfolio urnover (Panel B) are remarkably high by comparison. For example, nearly wo-hirds of he high-urnover household porfolios in he op localiy quarile in year (59%) remain in he op quarile he nex year, and around wo-fifhs (41%) are ranked in he op localiy quarile in boh year +1 and +2. III. Firm-Level Localiy In his secion we focus on he deerminans and consequences of local sock ownership. We define RLO j,, he firm relaive local ownership for firm j a he end of year, as follows: 14
L( j) $ own $ ownk, j, k RLO j, = L( j) NL( j) L( k) NL( k) $ own + $ own $ own + $ own j, j, k k, k L( k) k,, (3) where L( j) j, $ own and $ own NL( j) j, denoe he oal value of he posiion in sock j by he households ha had household porfolios of a leas $1,000 and were local and non-local o firm j, respecively. As before, he hreshold for localiy is se o 250 miles. To eliminae he noise semming from hin ownership in he sample, we include in he following analyses only he firms held by a leas five invesors in year. Relaive local ownership, RLO j,, is defined as he fracion of household sock ownership in he firm held by households locaed wihin 250 miles of he firm (he firs fracion) less he fracion of oal naion-wide household porfolio wealh held by households locaed wihin 250 miles of he firm (he second fracion). III.A. Deerminans of Firm-Level Local Ownership A key resul from Secion II is ha households on average inves disproporionaely ino local firms. In his secion we consider he dual quesion of wha characerizes firm relaive local ownership. To ha end, we form a panel of all firm-year observaions in he sample and regress firm relaive local ownership on several firm characerisics. The panel srucure of he daa promps us o accoun for he unobserved year effecs by adding year dummy variables ino he specificaion and o allow for he correlaion of he firm-specific error erms across ime. Table V presens regression resuls for all firms, S&P 500 firms, and non-s&p 500 firms. Aside from he regression approach oulined above (denoed as Mean ), we also repor he resuls of a robus median regression esimaor (denoed as Median ). Regressions fied for all firms highligh ha firm relaive local ownership is relaed negaively o leverage, posiively o he number of employees, and negaively o he firm s S&P 500 membership saus, while i is largely unrelaed o marke value. 8 From he perspecive of informaion asymmery, we inerpre he number of employees as a noisy proxy of he opporuniy o collec value-relevan 8 In unrepored analyses, we compare he disribuions of marke value of local and non-local invesmens and find ha hey are very similar. This robusness check alleviaes he possible concern ha local invesmens are made ino micro-cap socks o a larger exen han non-local invesmens and ha many of he resuls repored in he paper may sem from he exraordinary performance of micro-cap socks in he sample period. We hank Josef Lakonishok for poining ou his issue. 15
informaion locally, or perhaps o simply become aware of he firm s exisence (familiariy), which is gained hrough social ineracions wih he employees (i.e., word-of-mouh). There is also an alernaive explanaion for he posiive effec of he number of employees on relaive local ownership. Oher sudies have documened he effecs of an underlying srong preference for company sock or equiies, showing ha hose who hold a high proporion of equiies in pension savings also hold a high fracion of non-pension asses in equiies (Bodie and Crane (1997) and Weisbenner (2002)), and ha employees for firms ha require he company mach conribuions o he 401(k) plan o be invesed in company sock end o inves more of heir own 401(k) conribuions in company sock (Benarzi (2001) and Liang & Weisbenner (2002)). If employees of firms end o inves par of heir non-pension plan wealh in company sock, his could also explain why local ownership is higher for firms wih more employees. However, hese issues are unlikely o drive localiy in he sample. The majoriy of he accouns in he daabase are non-reiremen accouns. The accouns ha are reiremen accouns are eiher Individual Reiremen Accouns (IRAs) or KEOGH plans, none are reiremen plans sponsored by an invesor s employer. Thus, if a household is invesing in is employer s sock hrough is 401(k) plan, his will no be conained in our daa. The only invesmen in he sock of a company household members work for ha would be refleced in our daa would be invesmens in non-401(k) accouns. We regard he S&P 500 saus as a fairly accurae measure of boh familiariy and he exen of availabiliy of privae, value-relevan informaion ha would be more easily accessible o local invesors. Simply pu, S&P 500 companies are followed by many sock analyss, owned and researched by many insiuional invesors, held by numerous S&P 500 index funds and oher muual funds, and closely followed by he financial press and oher media. Implicaions of such populariy of S&P500 socks are wofold. Firs, here generally is disproporionaely lile value-relevan privae informaion regarding S&P 500 socks o begin wih and localiy is unlikely o help (being from Seale does no likely give a subsanial advanage in acquiring informaion abou Microsof). Second, i does no require localiy o be familiar wih S&P 500 socks. Thus, i is no surprising ha he loading on he S&P 500 saus is significanly negaive. Moreover, he regressions fied for S&P 500 firms did no yield any saisically significan deerminans whose significance would be consisen across he wo regressions (mean and median). I hus appears ha relaive local ownership of S&P 500 firms is no srongly 16
relaed o firm characerisics. On he oher hand, regressions fied only for non-s&p 500 firms resul in he saisical significance, same direcion, and comparable magniude of he impac of leverage and number of employees. This confirms he inuiion ha non-s&p 500 firms were he primary drivers of he resuls from Table V for all firms. III.B. Persisence of Firm-Level Local Ownership A naural quesion is wheher firm local ownership persiss. We explore his quesion using he same mehodology we used for households and repor he resuls in Table VI. Before proceeding, we noe ha persisence in household localiy, hough likely srongly relaed o he persisence in firm local ownership, need no necessarily imply i. 9 Analogously o Table IV, each panel in Table VI feaures a simple breakdown of firm relaive local ownership rank in year +1 and +2 condiional upon he rank in year. The analysis encompasses 8,064 firms ha were held a he beginning of hree consecuive years (pooled over hree-year inervals from 1991 o 1996). We seek o gain perspecive regarding firm relaive local ownership persisence while conrolling for urnover. Here we use he analogous definiion of urnover he firm s sock urnover is he raio of he minimum of dollar values of buys and sells of he firm s sock in he sample in year +1 and he dollar value of he overall posiion of all household porfolios in he sock a he end of year. Naurally, average firm annual urnover based on he rades in he sample is subsanially higher han i was for he average household porfolio urnover: he cuoffs for firm annual urnover quariles in he sample are 14%, 45%, and 111%. The resuls demonsrae srong persisence in firm relaive local ownership, paricularly remarkable among firms wih he annual urnover of a leas 111% (Panel B). Once again, under he null hypohesis of no localiy persisence (i.e., wih respec o localiy he fracion of local invesors holding he sock is random from year o year), conservaive esimaes of he expeced percenages for he high-urnover firms ha remain he mos local (i.e., in he op quarile of firm localiy), given ha he sock urnover is larger han 100%, are 25% in year +1 and only 6.25% for year +1 and +2. The probabiliy of remaining 9 Consider a simple counerexample wherein he economy consiss of wo invesors, X and Y, and a single share, always worh $1, of each of he wo firms, A and B. Boh A and B are local o X and non-local o Y. Suppose ha a he ouse X held A and Y held B. Furher suppose ha X sold A o Y and soon hereafer bough B from Y. Noe 17
above/below he median is 50% in year +1 and 25% in boh year +1 and year +2. Once again, he acual raes of persisence in Panel B are remarkably high by comparison. For example, around 61% of he high-urnover firms in he op localiy quarile in year remain in he op quarile he nex year, and slighly under wo-fifhs (39%) of high-urnover firms (hose wih urnover in he op quarile in boh year +1 and year +2) are ranked in he op localiy quarile in boh year +1 and +2. III.C. Firm-Level Local Ownership and Sock Turnover This secion explores he relaion beween a firm s RLO (relaive local ownership by individuals) and is rading paerns. We consider deerminans of sock urnover for all rades, as well as separaely for local and non-local rades. In he regressions below, we conrol for year effecs and for he correlaion of he firm-specific error erm across ime. As above, we define sock j urnover in year +1 as he raio of he minimum dollar value of all buys and sells in year +1 o he oal posiion held by all invesors a end of year : E E E min($ Buys j, + 1,$ Sells j, + 1) Turnover j, + 1 =, (4) E $ Posiion j, where E denoes eligibiliy of rades and posiions: All (all), L (local), or NL (non-local), respecively. This definiion implies, for example, ha local urnover of sock j is compued wih respec o local holdings and local rades of sock j. Regressions of E j, + Turnover 1on a number of firm characerisics measured a he end of year are presened in Table VII, Panel A. The key resul in he able is a sharp difference beween he loadings on firm relaive local ownership among local and non-local rades ( 250 vs. 196): hough boh are large in absolue value and highly saisically significan, hey have he opposie sign. Firm relaive local ownership has a posiive effec on non-local urnover. We inerpre his finding as indirec evidence of informaion diffusion, wherein non-local invesors may have evenually acquired he value-relevan news abou he sock and are rading in i only afer he local invesors have done so. Unrepored regressions fied separaely for buy urnover and sell ha, alhough household localiy did no change for eiher X or Y, firms A and B had a drasic swing in local ownership from 100% (0%) o 0% (100%), respecively. 18
urnover sugges ha boh direcional urnovers for non-local rades are posiively relaed o RLO j,. By conras, RLO j, has a negaive effec on local urnover. Unrepored regressions fied separaely for buy urnover and sell urnover (only buys and sells in he numeraor, respecively) sugges ha his relaion is driven primarily by he lack of addiional local buying, which we inerpre as imely reacion o he new informaion (possibly available only locally). This resul is consisen wih local invesors being conen wih heir posiion in he sock afer heir iniial rades, and local invesors ha missed he boa being relucan o buy now, given ha hey had no purchased he sock already. Resuls furher sugges ha socks in he S&P 500 index have been raded less frequenly and ha pas winners have been raded more frequenly. Unrepored regressions fied separaely for buy urnover and sell urnover sugges ha he laer effec sems boh from posiive feedback rading (rend-chasing) as well as he endency o sell pas winners (he disposiion effec). Finally, urnover has been higher among high marke-o-book socks, especially among local rades. Moreover, i has been higher for echnology and medical/bioechnology socks, wo indusries ha invesors were paricularly keen on. 10 I also appears ha invesors raded less in highly levered socks (alhough he coefficien on leverage for he local urnover mean regression is somewha shy of saisical significance). III.D. Firm-Level Local Ownership and Herding We nex explore he relaion beween firm relaive local ownership and herding, ha is, he endency o buy (sell) he same socks ha oher individual invesors buy (sell) a he same ime. We define a measure of herding, similar o he herding measure from Lakonishok, Shleifer, and Vishny (1992): Herding E j, + 1 E E # Buyers j, + 1 # Buyers + 1 =, (5) # Buyers + # Sellers # Buyers + # Sellers E j, + 1 E j, + 1 E + 1 E + 1 where E denoes eligibiliy of rades and posiions: All (all), L (local), or NL (non-local), respecively. Herding is defined as he number of households ha buy a paricular sock divided 10 For example, a he end of 1991 he combined weigh of echnology and medical/bioechnology firms in he valueweighed porfolio of all socks held by individual invesors was 34%, whereas heir combined weigh comprised jus over a fourh of oal marke capializaion. 19
by he number households ha eiher buy or sell ha sock, less he same raio consruced for all buying and selling aciviy for households across all socks. The herding measure is in absolue value and is expressed in percenage poins. When his measure is large, his indicaes abnormal movemen owards (away) from his paricular sock by individual invesors, relaive o markewide buying (selling) aciviy by households across all socks. Regressions of E j, + Herding 1on a number of firm characerisics measured a he end of year are presened in Table VII, Panel B. The regression for all rades suggess no relaion beween herding and RLO j,. The regressions for local and non-local rades reveal ha he lack of he effec observed for all rades masks he sharp difference beween he loadings on firm relaive local ownership for local and non-local rades: hey have he opposie sign and are boh saisically significan. As wih urnover, we inerpre his finding as indirec evidence of informaion diffusion, wherein non-local invesors may evenually acquire value-relevan informaion and henceforh herd when his previously locally available informaion becomes more widespread. On he oher hand, he negaive coefficien on relaive local ownership for herding among local rades is consisen wih a imely reacion of local invesors o he informaion obained locally. Following he period of local invesors iniial procuremen of locally available value-relevan informaion and appropriae rading on ha informaion, invesors are now conen wih heir posiion in he sock and are less likely o join non-local households in laer herding on ha sock. Resuls also show ha individual invesors herd more in S&P 500 socks han in non- S&P 500 socks. This finding maches he inuiion ha, compared o non-s&p 500 socks, here is more informaion regarding S&P 500 companies and ha informaion is disseminaed more rapidly, hus resuling in more herding. Finally, he relaion beween herding and firm size is negaive, as is he case for marke-o-book raio, he dummy variable indicaing he membership in echnology and bioechnology socks, pas firm reurns, and pas oal firm risk. The resuls presened in his secion are broadly consisen wih hose ha perain o a very differen group of marke paricipans pension fund managers (Lakonishok, Shleifer, and Vishny, 1992) and muual fund managers (Coval and Moskowiz, 2001). I is perhaps somewha surprising ha he same facors ha appear o moivae urnover and herding among professional money managers affec individual invesors, he larges marke segmen, in a similar fashion. 20
III.E. Firm-Level Local Ownership and Excess Demand In his secion, we sudy individual invesors poenial for desabilizing prices. We define he measure of excess demand in year +1 he imbalance beween buying and selling aciviy of sock j as he raio of he difference beween he value of all buys and sells in year +1 and he sum of he wo: 11 ExcessDemand E j, + 1 E j, + 1 E j, + 1 E j, + 1 E j, + 1 $ Buys $ Sells =, (6) $ Buys + $ Sells where E once again denoes eligibiliy of rades and posiions: All (all), L (local), or NL (nonlocal), respecively. Regressions of E, + ExcessDemand j 1on a number of firm characerisics measured a he end of year are presened in Table VII, Panel C. The regression for all rades suggess a bes a very weak, posiive relaion beween excess demand and RLO j, (he median regression is no saisically significan and saisical significance of he mean regression is marginal). As wih herding, he regressions for local and non-local rades reveal ha he weak effec observed for all rades masks he sharp difference beween he loadings on RLO j, for local and non-local rades: boh are saisically significan and hey have he opposie sign. Once again, his finding provides indirec evidence of he informaion diffusion hypohesis oulined above. The posiive coefficien on relaive local ownership for he non-local rades may reflec ha non-local invesors have evenually acquired he value-relevan informaion abou a firm and are henceforh creaing excess demand for he sock. The negaive coefficien on relaive local ownership for local rades may indicae ha he excess demand creaed by non-local invesors for companies wih high local ownership is accommodaed by a ne supply of shares from local invesors. Resuls furher sugges ha individual invesors excess demand is posiively relaed wih firm size and marke-o-book raio, suggesing more excess demand for large socks and for growh socks. Ineresingly, here is some evidence ha individual invesors chase oal risk, especially among non-local firms. A he same ime, he relaion beween excess demand and 11 Lakonishok, Shleifer, and Vishny (1992) call his measure Draio (dollar raio). 21