Rational or Intuitive : Are Behavioral Biases Correlated Across Stock Market Investors?

Transcription

1 31 Prmary submsson: Fnal acceptance: Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? Andrey Kudryavtsev 1, Gl Cohen 1, Shlomt Hon-Snr 1 ABSTRACT Human judgments are systematcally affected by varous bases and dstortons. The man goal of our study s to analyze the effects of fve well-documented behavoral bases namely, the dsposton effect, herd behavor, avalablty heurstc, gambler s fallacy and hot hand fallacy on the mechansms of stock market decson makng and, n partcular, the correlatons between the magntudes of the bases n the cross-secton of market nvestors. Employng an extensve onlne survey, we demonstrate that, on average, actve captal market nvestors exhbt moderate degrees of behavoral bases. We then calculate the cross-sectonal correlaton coeffcents between the bases and fnd that all of them are postve and hghly sgnfcant for both professonal and non-professonal nvestors and for all categores of nvestors, as classfed by ther experence levels, genders, and ages. Ths fndng suggests that an nvestor who s more nclned to employ a certan ntutve decson-makng technque wll most lkely accept other technques as well. Furthermore, we determne that the correlaton coeffcents between the bases are hgher for more experenced nvestors and male nvestors, ndcatng that these categores of nvestors are lkely to behave more consstently, or, n other words, are more lkely to decde for themselves whether to rely on smplfyng decson-makng technques n general or to reject all of them. Alternatvely, ths fndng may suggest that these nvestors develop more sophstcated adaptve toolboxes, or collectons of heurstcs, and apply them more systematcally. KEY WORDS: JEL Classfcaton: avalablty heurstc; dsposton effect; gambler s fallacy; herd behavor; hot hand fallacy D81, D84, G11, G14, G19 1 The Max Stern Academc College of Emek Yezreel, Israel Introducton People are not ratonal utlty-optmzaton machnes. Our decsons are affected by a varety of systematc bases and dstortons that may result n ncorrect patterns of behavor and nferor performance (for an overvew, see, for example, Kahneman et al., 1982; Stracca, In ths study, we analyze the effects of Correspondence concernng ths artcle should be addressed to: Andrey Kudryavtsev, Economcs and Management Department, The Max Stern Academc College of Emek Yezreel, Emek Yezreel 19300, Israel, e-mal: andreyk@yvc.ac.l fve well-documented behavoral bases on market nvestors decson-makng: Dsposton effect (Shefrn, & Statman, 1985 an nvestor s tendency to sell stocks that ganed value and to hold on to stocks that lost value. Herd behavor (for a recent survey, see, e.g., Hrshlefer, & Teoh, 2003 the behavor of an nvestor mtatng the observed actons of others or the movements of the market nstead of followng her own belefs and nformaton. Avalablty heurstc (Tversky, & Kahneman, 1973 the phenomenon of determnng the lkelhood Vzja Press&IT

2 32 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr of an event accordng to the easness of recallng smlar nstances. Gambler s fallacy (Laplace, 1796 the ncorrect belef n the negatve autocorrelaton of non-autocorrelated random sequences. Hot hand fallacy (Glovch et al., 1985 the ncorrect belef that certan random sequences may n fact be non-random (human-related and therefore postvely autocorrelated. A contnuously growng body of contemporaneous fnancal lterature clearly demonstrates that nvestors behavors are nfluenced by all of these bases (see, for example, Barber, & Odean, 2008; Hon-Snr et al., 2012; Klger, & Kudryavtsev, 2008; Park, & Sabouran, 2011; Sundal, & Croson, However, s an nvestor who s affected by one of the bases more lkely to be affected by others? Formally, are the magntudes of behavoral bases correlated n the cross-secton? To the best of our knowledge, ths queston s not addressed by prevous lterature, and the major goal of the present paper s to fll ths gap. We perform an onlne survey askng stock market nvestors, both professonal and non-professonal, a number of questons concernng ther personal ways of makng nvestment decsons. The questons are formulated to detect whether the partcpants are affected by the above-mentoned bases. For each partcpant, we calculate her personal bas grades, each of whch s hgher the more her reported behavor, as dscerned from her answers, s consstent wth the respectve behavoral effect. On average, our survey partcpants exhbt moderate degrees of behavoral bases. The major focus of our research s calculatng the cross-sectonal correlaton coeffcents between the bas grades. All of the correlatons are postve (n fact, close to one and hghly sgnfcant for both professonal and non-professonal nvestors. Therefore, we nfer that f an nvestor accepts a certan ntutve decson-makng technque, she wll lkely accept other technques as well. Furthermore, we perform a subsample analyss of the correlatons. We document that the correlaton coeffcents between the bases are hgher for more experenced nvestors and male nvestors, ndcatng that these categores of nvestors lkely behave more consstently, or, n other words, are more lkely to decde for themselves whether to rely on smplfyng decson-makng technques n general or to reject all of them. Alternatvely, ths fndng may suggest that more experenced nvestors manage to develop (everyone for herself a more sophstcated adaptve toolbox or collecton of heurstcs (Ggerenzer, & Selten, 2001 and apply t more systematcally, possbly arrvng at better nvestment results. We also fnd that the correlaton coeffcents for the most experenced non-professonal nvestors are lower than those for the professonal nvestors, lkely suggestng that the latter group, though not necessarly more ratonal (as shown by Hon-Snr et al., 2012, at least behaves more consstently, or based on a more ample collecton of decsonmakng rules. Conversely, the correlatons appear to be ndependent from nvestors ages. Importantly, all of the correlaton coeffcents we obtan for all of the subsamples and categores of partcpants are postve and hghly sgnfcant, provdng a strong robustness check for our major fndng. The rest of the paper s structured as follows. In Secton 2, we revew the lterature on behavoral bases, featurng both psychologcal aspects and economc applcatons. In Secton 3, we descrbe our survey desgn and research approach. Secton 4 defnes our hypotheses and provdes the emprcal tests and the results. Secton 5 concludes and provdes a bref dscusson. Psychologcal bases n fnance: Lterature revew Recent lterature demonstrates that economc and fnancal behavor and decson makng may be affected by varous psychologcal effects. These effects, often referred to as bases or fallaces, are based on feelngs, emotons and ntuton, rather than ratonal consderatons, and often result n nferor fnancal performance. In the present research, we concentrate on fve well-documented effects. Dsposton effect One of the most strkng behavoral patterns s the tendency of nvestors to sell wnners (stocks that ganed value and to hold on to losers (stocks that lost value. The term dsposton effect was frst dubbed by Shefrn and Statman (1985, who also offer a behavoral explanaton for t, based on the combnaton of loss averson (Kahneman, & Tversky, 1979 and mental accountng (Thaler, In essence, the dsposton ef- CONTEMPORARY ECONOMICS DOI: /ce

3 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 33 fect s a reflecton of nvestors keepng a separate mental account for each stock and, accordng to prospect theory, maxmzng an S-shaped (concave for gans and convex for losses, reference-level-based, value functon wthn that account. Three dfferent types of data are appled for studyng the dsposton effect: aggregate (on the level of stock exchanges, ndvdual (on the level of ndvdual nvestors and expermental. The frst to employ aggregate data are Lakonshok and Smdt (1986. Usng hstorcal stock prces as possble reference ponts, they fnd that wnners tend to have a hgher abnormal volume than losers. A smlar technque s employed by Ferrs et al. (1988 and Bremer and Cato (1996, yeldng comparable results. Huddart et al. (2007 fnd a sgnfcantly hgher volume when stock prces are above (below ther ffty-two week hghs (lows. Kausta (2004 uses the prce and volume nformaton on US ntal publc offerngs (IPOs and fnds that for negatve ntal return IPOs, tradng below the offer prce (whch s assumed to be the reference pont s suppressed n comparson to tradng above the offer prce and there s an ncrease n tradng volume as ther stock prces reach new record hghs. The second major group of papers studyng the dsposton effect s based on ndvdual data. The reference pont n these studes s taken to be the stocks purchase prces. In a comprehensve study, Odean (1998 takes the average purchase prce (for each nvestor and stock as a reference pont and then dstngushes between paper and realzed gans and losses. For each day and nvestor, he calculates the Proporton of Gans Realzed (PGR and the Proporton of Losses Realzed (PLR, takng the rato of PGR to PLR as a measure of the dsposton effect. Odean s man fndngs nclude the observaton that ndvdual nvestors demonstrate sgnfcant preferences for sellng wnners and holdng losers. Dhar and Zhu (2002 fnd that the dsposton effect s manly pronounced by lowncome and non-professonal nvestors. Goetzmann and Massa (2003 argue that nvestors dsposton bases affect frms returns. Grnblatt and Han (2005 were the frst to connect the dsposton effect and momentum, showng, both theoretcally and emprcally, that the dsposton effect may account for the tendency of past wnnng stocks to subsequently outperform past losng stocks. Frazzn (2006 fnds that n the presence of dsposton-prone nvestors, prces under-react to news, thereby generatng a post-event prce drft. Locke and Mann (2005 fnd that the average holdng perod for losng trades s longer than for wnnng trades. They argue that whle all traders hold losers longer than wnners, the least successful traders hold losers the longest, whereas the most successful hold losers for the shortest amount of tme. Shapra and Veneza (2000 compare the duratons of wnnng and losng round trps and document the dsposton effect for all groups of accounts, fndng that t s less pronounced for managed accounts than for ndependent ones. Klger and Kudryavtsev (2008 dscover that nvestors update ther reference ponts on stocks based on the percepton of stock exchange-lsted frms quarterly earnngs announcements as good or bad surprses and subsequently exhbt the dsposton effect wth respect to these reference ponts. The thrd group of papers that sheds lght on the dsposton effect conssts of papers employng expermental desgn. Weber and Camerer (1998 conduct a mult-stage experment examnng dfferent characterstcs and determnants of the dsposton effect and fnd that subjects tend to sell fewer shares when the prce falls than when t rses and also sell less when the prce s below the purchase prce than when t s above. Smlarly to Weber and Camerer (1998, Oehler et al. (2002 use the purchase prce and the last perod prce as alternatve reference ponts. The dsposton effect s found to be stronger when the purchase prce s taken as a reference pont. Herd behavor (herdng In fnancal markets, herdng s usually termed as the behavor of an nvestor mtatng the observed actons of others or the movements of the market nstead of followng her own belefs and nformaton. Herd behavor s possbly among the most mentoned but least understood terms n the fnancal lexcon. Dffcultes n measurng and quantfyng the exstence of the behavor form obstacles to extensve research. Even so, there are at least two ponts people tend to unanmously agree upon. Frst, as one of the foundng pllars n the newly developed behavoral asset prcng area, herd behavor helps explan market-wde anomales. Because ndvdual bases are not nfluental enough to move market prces and returns, they only have real anomalous effects f they create socal contamnaton Vzja Press&IT

4 34 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr wth a strong emotonal content, leadng to more wdespread phenomena such as herd behavor. Second, t s generally accepted that the flood of herdng may lead to a stuaton n whch the market prce fals to reflect all relevant nformaton; therefore, the market becomes unstable and moves towards neffcency. Theoretcal and emprcal research on herd behavor has been conducted n an solated manner. The theoretcal work (e.g., Avery, & Zemsky, 1998; Cpran, & Guarno 2008; Lee, 1998; Park, & Sabouran, 2011 tres to dentfy the mechansms that can lead traders to herd. Papers n ths strand of lterature emphasze that n fnancal markets, the fact that prces adjust to the order flow makes t more dffcult for herd behavor to arse than n the other setups studed n socal learnng lterature n whch there are no prce mechansms. Nevertheless, t s possble that ratonal traders herd because there are dfferent sources of uncertanty n the market, traders have nformatonal and non-nformatonal (e.g., lqudty or hedgng motves to trade or tradng actvty s affected by reputaton concerns. Emprcal studes of herd behavor employ ether laboratory or market data. In all the models, herdng means makng the same decson ndependently of the prvate nformaton that one receves. The problem for the emprcst s that there are no data on the prvate nformaton avalable to traders; therefore, t s dffcult to understand whether traders make smlar decsons because they dsregard ther own nformaton and mtate (as opposed, for nstance, to reactng to the same pece of publc nformaton. To overcome ths problem, some authors (e.g., Cpran, & Guarno, 2005; 2009; Drehman et al., 2005 test herd behavors n laboratory fnancal markets and document the types of behavor consstent wth herd motves. A seres of emprcal studes make an effort to detect and measure herd behavor n real market stuatons. Lakonshok et al. (1992 measure herd behavor as the average tendency of a group of money managers to buy or sell partcular stocks at the same tme, relatve to what could be expected f the managers made ther decsons ndependently. Wermers (1995 proposes a portfolo-change measure, by whch herd behavor s measured by the extent to whch portfolo weghts assgned to the varous stocks by dfferent money managers move n the same drecton. Chrste and Huang (1995 document lower volatlty of ndvdual securty returns n the perods of extremely postve and extremely negatve market returns, whch s n lne wth herdng behavor and contradcts ratonal asset prcng. Hwang and Salmon (2004 and Wang and Canela (2006 employ cross-sectonal varance of the betas to study herd behavor towards market ndces n major developed and emergng fnancal markets. They fnd hgher levels of herdng n emergng markets than n developed markets and hgher correlatons of herdng between two markets from the same group compared to those between two markets from dfferent groups. They also argue that herd behavor shows sgnfcant movements and persstence ndependently from market condtons. Avalablty heurstc The avalablty heurstc (Tversky, & Kahneman, 1973 refers to the phenomenon of determnng the lkelhood of an event accordng to the easness of recallng smlar nstances. In other words, the avalablty heurstc may be descrbed as a rule of thumb, whch occurs when people estmate the probablty of an outcome based on how easy that outcome s to magne. As such, vvdly descrbed, emotonally charged possbltes wll be perceved as beng more lkely than those that are harder to pcture or dffcult to understand. Tversky and Kahneman (1974, provde examples of ways avalablty may provde practcal clues for assessng frequences and probabltes. They argue that recent occurrences are lkely to be relatvely more avalable than earler experences (p and thus conclude that people assess probabltes by overweghtng current nformaton, as opposed to processng all relevant nformaton. A number of papers dscuss the nfluence of the avalablty heurstc on market nvestors. Shller (1998 argues that nvestors attenton to nvestment categores (e.g., stocks versus bonds or real estate; nvestng abroad versus nvestng at home may be affected by alternatng waves of publc attenton and nattenton. Smlarly, Barber and Odean (2008 fnd that when choosng whch stock to buy, nvestors tend to consder only those stocks that have recently caught ther attenton (stocks n the news, stocks experencng hgh abnormal tradng volume, stocks wth extreme one day returns. Danel et al. (2002 conclude that nvestors and analysts are, on average, too credulous. CONTEMPORARY ECONOMICS DOI: /ce

5 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 35 That s, when examnng an nformatve event or a value ndcator, they do not dscount adequately for the ncentves of others to manpulate ths sgnal. Credulty may be explaned by lmted attenton and the fact that avalablty of a stmulus causes t to be more heavly weghted. Freder (2004 fnds that stock traders seek to buy after large postve earnngs surprses and sell after large negatve earnngs surprses and explans ths tendency by the avalablty heurstc, assumng that the salence of an earnngs surprse ncreases n ts magntude. Ganzach (2001 brngs support for a model n whch analysts base ther judgments of rsk and return for unfamlar stocks upon a global atttude. If stocks are perceved as good, they are judged to have hgh return and low rsk, whereas f they are perceved as bad, they are judged to be low n return and hgh n rsk. Lee et al. (2007 dscuss the recency bas, whch s the tendency of people to make judgments about the lkelhood of events based on ther recent experence. They fnd that analysts forecasts of frms long-term growth n earnngs per share tend to be relatvely optmstc when the economy s expandng and relatvely pessmstc when the economy s contractng. Ths fndng s consstent wth the avalablty heurstc, ndcatng that forecasters overweght the current state of the economy n makng long-term growth predctons. Klger and Kudryavtsev (2010 fnd that postve stock prce reactons to analyst recommendaton upgrades are stronger when accompaned by postve stock market ndex returns and negatve stock prce reactons to analyst recommendaton downgrades are stronger when accompaned by negatve stock market ndex returns. They dub ths fndng outcome avalablty effect and explan t by hgher avalablty of postve (negatve outcomes on days of market ndex rses (declnes. Moreover, Klger and Kudryavtsev (2010 document weaker (stronger reactons to recommendaton upgrades (downgrades on days of substantal stock market moves. They dub ths fndng the rsk avalablty effect and explan t by hgher avalablty of rsky outcomes on such hghly volatle days. Gambler s fallacy The gambler s fallacy s defned as an (ncorrect belef n the negatve autocorrelaton of a non-autocorrelated random sequence. For example, ndvduals who beleve n the gambler s fallacy beleve that after three red numbers appearng on the roulette wheel, a black number s due, or, n other words, s more lkely to appear than a red number. The frst publshed account of the gambler s fallacy s from Laplace (1951. Gambler s fallacy-type belefs are frst observed n the laboratory (under controlled condtons n the lterature on probablty matchng. In these experments, subjects are asked to guess whch of two colored lghts wll next llumnate. After seeng a strng of one outcome, subjects are sgnfcantly more lkely to guess the other, an effect referred to n that lterature as negatve recency (see Estes, 1964; Lee, 1971, for revews. Ayton and Fscher (2004 also demonstrate the exstence of gambler s fallacy belefs n the lab when subjects choose whch of two colors wll appear next on a smulated roulette wheel. Gal and Baron (1996 show that gambler s fallacy behavor s not smply caused by boredom. They ask partcpants n ther experments how they would best maxmze ther earnngs and receve responses based on gambler s fallacy-type logc. The gambler s fallacy s usually thought to be caused by the representatveness heurstc (Kahneman, & Tversky, 1972; Tversky, & Kahneman, Here, chance s perceved as a self-correctng process n whch a devaton n one drecton nduces a devaton n the opposte drecton to restore the equlbrum (Tversky, & Kahneman, 1974, p Thus, after a sequence of three red numbers appears on the roulette wheel, black s more lkely to occur than red because a sequence red-red-red-black s more representatve of the underlyng dstrbuton than a sequence redred-red-red. Recently, a number of alternatve explanatons for ths bas have been proposed. For example, Hahn and Warren (2009 suggest that the gambler s fallacy may reflect the subjectve experence of a fnte data stream for an agent wth a lmted short-term memory capacty. In other words, ths effect may result not from the lmtatons of people s ntutve statstcs, but rather from the extent to whch the human cogntve system s fnely attuned to the statstcs of the envronment. In lne wth Hahn and Warren (2009, Sun and Wang (2010 demonstrate that n fnte data streams, streak patterns have longer watng tmes that s, tmes t takes them to frst occur from the tme at whch montorng begns than the patterns wth reversals, makng the former seem more probable n Vzja Press&IT

6 36 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr the eyes of people, whose personal experence s naturally lmted. A number of researchers demonstrate the exstence of the gambler s fallacy emprcally, n lottery and horse and dog racng settngs. For example, Clotfelter and Cook (1991; 1993 and Terrell (1994 show that soon after a lottery number wns, ndvduals are sgnfcantly less lkely to bet on t. Ths effect dmnshes over tme; months later, the wnnng number s as popular as the average number. Papachrstou and Karamans (1998 demonstrate that the partcpants n the Greek Natonal Lottery bet sgnfcantly more on overdue numbers, that s, on the numbers that have not been drawn durng some relatvely long perods of tme. Subsequently, Papachrstou (2004 reports a weaker evdence of the same type for the Brtsh Lotto. Hauser-Rethaller and Kong (2002 and Roger and Bronanne (2007 also present evdence that people takng part n the Austran and French Lotto, respectvely, appear not to choose lottery numbers randomly. Metzger (1984, Terrell and Farmer (1996 and Terrell (1998 show the gambler s fallacy n horse and dog racng. Croson and Sundal (2005 and Sundal and Croson (2006 use vdeotapes of play of a roulette table n the casno and document a sgnfcant gambler s fallacy n bettng. That s, followng a sequence of one color outcome, people are more lkely to place ther bets on the other color. Zelonka (2004 asks a group of stock market professonals a number of questons amed at detectng ther ways of makng decsons and fnds that market sgnals consdered by techncal analysts are consstent wth a number of behavoral bases, ncludng the gambler s fallacy. Overall, the gambler s fallacy s well-documented both n the laboratory and n the real world, ncludng money-related behavor. However, there seems to be lttle evdence of ths pattern n fnancng, ncludng stock market decson makng. Hot hand fallacy As people exhbt the gambler s fallacy, whch s a tendency to predct the opposte of the last event (negatve recency, they may also express belefs that certan events wll be repeated (postve recency. The latter tendency s known as the hot hand fallacy, and unlke the gambler s fallacy, t refers to people s belef that a partcular person, rather than a partcular outcome, s hot. For example, f an ndvdual has won n the past, whatever numbers she chooses to bet on are lkely to wn n the future, not only the numbers she had won wth prevously. Glovch, Vallone and Tversky (1985 were the frst to use the term hot hand. They demonstrate that ndvduals beleve n the hot hand n basketball shootng and that these belefs are not correct (.e., basketball shooters probablty of success s serally uncorrelated. They suggest that the hot hand also arses out of the representatveness heurstc just as the gambler s fallacy. They wrte, A concepton of chance based on representatveness produces two related bases. Frst, t nduces a belef that the probablty of heads s greater after a long sequence of tals than after a long sequence of heads ths s the notorous gambler s fallacy. Second, t leads people to reject the randomness of sequences that contan the expected number of runs because even the occurrence of, say, four heads n a row whch s qute lkely n a sequence of 20 tosses makes the sequence appear non-representatve. Another potental explanaton for the hot hand fallacy may be related to Langer (1975 dealng wth the lluson of control, or people s tendency to beleve that they (or others exert control over events that are n fact randomly determned. Rabn and Vayanos (2010 develop a theoretcal model to examne the lnk between the gambler s fallacy and the hot-hand fallacy. They show that because of the gambler s fallacy, an ndvdual who observes a sequence of sgnals that depend on an unobservable underlyng state s prone to exaggerate the magntudes of changes n the state but underestmate ther duraton. By contrast, they demonstrate that long sequences of smlar sgnals may cause people to beleve that a type of momentum s present n the underlyng state tself and, n lne wth the hot-hand fallacy, to expect sequence contnuaton. Other expermental evdence shows that subjects n a smulated blackjack game bet more after a seres of wns than they do after a seres of losses, both when bettng on ther own play and on the plays of others (Chau, & Phllps, Further evdence of the hot hand n a laboratory experment comes from Ayton and Fscher (2004, who document both the gambler s fallacy and the Hot hand fallacy and conclude that the former s attrbuted to randomly lookng processes CONTEMPORARY ECONOMICS DOI: /ce

7 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 37 and to nanmate chance mechansms, whereas the latter refers to processes that seem to be non-random and related to human sklled performance. Feld evdence for the hot hand s weaker. Camerer (1989 compares odds n the bettng market for basketball teams wth ther actual performance and fnds that bettors do appear to beleve n the hot team. Croson and Sundal (2005 and Sundal and Croson (2006 document hot hand-consstent behavor n casnos. Clotfelter and Cook (1989 note the tendency of gamblers to redeem wnnng lottery tckets for more tckets rather than for cash. Ths behavor s also consstent wth hot hand belefs because the ndvduals who have recently won seem to beleve they are more lkely to wn agan. Overall, smlarly to the gambler s fallacy, the hot fallacy s wdely dscussed n dfferent branches of lterature but s not suffcently documented n fnancal research, possbly because t s qute dffcult to establsh the hot hand feelngs partcular nvestors may have at certan moments of tme. In the present study, we frst wsh to shed addtonal lght on the effects of the above-dscussed psychologcal patterns on fnancal decson-makng. Ths understandng may be especally valuable for the case of the gambler s fallacy and the hot hand fallacy, whose potental effects on the feld of fnance are not suffcently studed n prevous lterature. However, the major goal of ths study s to analyze the cross-sectonal correlatons between the magntudes of dfferent behavoral bases n stock market decson-makng, a matter that s, to our best knowledge, not at all dscussed n prevous lterature. Survey desgn and research approach We gathered the data for ths study n the framework of a computerzed survey, consstng of two stages: Frst, we asked a group of professonal portfolo managers (41 managers at one of the major Israel nvestment houses to fll out a short questonnare. Ths stage of the survey took place n January Second, we conducted onlne surveys va one of the leadng fnancal webstes n Israel - the Bzportal ( Ths webste s wdely recognzed for beng regularly vsted by market nvestors, not necessarly professonal. Ths stage of the survey took place n March-Aprl We receved responses from 305 users. We asked all of the respondents to ndcate ther gender, age, and number of years of actve experence n the captal market. Table 1 (n Appendx 1 reports the basc descrptve statstcs of our sample. The majorty of our partcpants were males (78.05% and 74.10% n the professonals and non-professonals groups, respectvely, 30 to 40 years old (53.66% and 55.08%, respectvely, and had more than 10 years of experence n stock market nvestments (39.02% and 40.98%, respectvely. Our survey questonnare conssted of 10 questons, whch are presented n Appendx 2. In each queston, partcpants were asked to rate the approprateness of a statement on a Lkert scale between 1 (strongly dsagree and 5 (strongly agree. The goal of the questonnare was to detect f stock market nvestors were affected by dfferent psychologcal bases. In ths respect, the statements were formulated so that questons 1 and 2 referred to the dsposton effect, questons 3 and 4 to the gambler s fallacy, questons 5 and 6 to the hot hand fallacy, questons 7 and 8 to herd behavor, and questons 9 and 10 to the avalablty heurstc. Nether the names of the behavoral effects nor any type of descrpton were ncluded n the questonnare. The questons were n fact formulated n the form of a dalogue allowng the partcpants to express ther general belefs wth respect to the stock markets, n general, and ther tradng phlosophes, n partcular. Includng two questons for each of the bases allowed the questonnare to better capture the partcpants actual opnon about each of them. 1 Accordng to the defnton of the bases and the formulaton of the questons, for all of our questons, except queston 2, a hgher grade provded by a partcpant would be consstent wth a stronger effect of the respectve bas on her. To capture the effect of each of the behavoral bases on each of our partcpants, we calculate ther personal bas grades. To do so, we frst control for the crosssectonal correlatons of grades gven by the partcpants wthn the pars of the questons we employed for each of the bases. The correlaton coeffcents between the grades wthn the pars are reported n Table 2. The table clearly demonstrates that the correlatons wthn all of the pars are hghly sgnfcant for both the professonal and non-professonal partcpants. We also note that the sgn of the correlaton between Vzja Press&IT

8 38 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr the grades on questons 1 and 2 s negatve, whch s because nvestment behavor consstent wth the dsposton effect requres a hgh grade on queston 1 and a low grade on queston 2. Strong correlatons wthn the pars of questons allow us to aggregate the bas grades for each partcpant and for each of the bases n the followng way: ( D G: D G = G _ G _ 2 (1 2 where G _ N s the grade (answer gven by partcpant for queston (statement N. Gambler s grade ( G G : G G = G _ 2 + G _ 3 (2 ( H G : H G = G _ 5 + G _ 6 (3 Herd (behavor grade ( B G : B G = G _ 7 + G _ 8 (4 ( A G : A G = G _ 9 + G _ 10 (5 Accordng to ths approach, the resultng personal bas grades we attan for each partcpant and for each queston N range from 2, meanng that the respectve bas has vrtually no effect on the respectve partcpant, or, n other words, that the partcpant s behavor s fully ratonal, to 10, meanng that the respectve partcpant tends to make decsons that are completely based on the respectve smplfyng decson-makng rule (bas, or, n other words, that the partcpant s behavor s completely ntutve. Testable hypotheses and results Frst, we look at the general pcture of the bas grades n our sample. Table 3 concentrates the descrptve statstcs n ths respect, and shows some general results: All of the bas grades for both groups range from 2 (mnmal possble grade to 9-10 (maxmal possble grade. In other words, n our sample, we have both partcpants who seem to be fully affected and those who seem to be completely unaffected by the respectve behavoral patterns. The mean bas grades range from to 5.646, and the majorty of the partcpants have bas grades lower than 6. Therefore, we may nfer that our partcpants are, on average, moderately affected by behavoral bases. However, the major goal of our paper s to analyze the cross-sectonal correlatons between the magntudes of dfferent psychologcal bases n stock market behavor, a matter that s, to our best knowledge, not dscussed at all n prevous fnancal lterature. Cross-sectonal correlatons between the behavoral bases: Total sample A consderable number of psychologcal effects n stock market behavors have been already documented n the lterature, as dscussed above. A relatvely small number of studes address the ndvdual dfferences n the magntudes of these effects (see Hon-Snr et al., (2012 for a seres of results, short lterature revew, and dscusson 3. However, there are no studes that analyze f there exst cross-sectonal correlatons between the effects, or, n other words, f an nvestor who s affected by one of the bases s more lkely to be affected by others. The present study makes an effort to fll ths gap. We suggest that nvestors tend to rely ether on purely ratonal consderatons or on ther feelngs and ntuton. That s, we expect ratonal nvestors to reman ratonal n all of the decsons they make and ntutve nvestors to employ not smply one or two, but varous smplfyng decson-makng rules. Therefore, we hypothesze that: Hypothess 1: The magntudes of the behavoral effects are postvely correlated n the cross-secton. Table 4 presents cross-sectonal correlaton coeffcents between the personal bas grades for the professonal portfolo managers (Panel A and for the nonprofessonal nvestors (Panel B. The results strongly support Hypothess 1. All of the correlatons are postve (n fact, close to 1 and hghly sgnfcant. That s, we may conclude that f an nvestor accepts a certan ntutve decson-makng technque, she wll most lkely accept others as well. Ths result may be especally valuable because the matter of cross-sectonal correlatons between dfferent behavoral bases s, to our best knowledge, not dscussed n prevous economc and fnancal lterature. Ths fndng mples that nvestors tend to behave n a consstently ratonal or ntutve way. Based on ths, one may be able to better predct future decsons to be made by an nvestor, or even a group of nvestors, wth relatvely scarce nformaton about ther past decsons. We may also note that at frst glance, the fact that the Gambler s grades and the s are postvely correlated n CONTEMPORARY ECONOMICS DOI: /ce

9 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 39 the cross-secton mght seem puzzlng. However, as we have noted n Secton 2, these two behavoral bases do not contradct each other and may well co-exst wthn one person because they refer to people s belefs wth respect to dfferent types of processes. For example, Ayton and Fscher (2004 expermentally document both the gambler s fallacy and the hot hand fallacy and conclude that the former s attrbuted to randomly lookng processes and to nanmate chance mechansms, whereas the latter refers to processes that seem to be non-random and related to human sklled performances. Fnally, we may note that personal bas grades seem to be equally strongly correlated for both professonal and non-professonal nvestors, as demonstrated by the two panels of Table 4. 4 Subsample analyss Havng documented hgh correlatons between the behavoral bases wthn both major groups of our partcpants, we now proceed to analyzng the nature of the correlatons wthn dfferent subsamples. We classfy our survey partcpants by a number of personal characterstcs. Tradng experence s a characterstc one should obvously address n ths respect. Ths aspect clearly has strong effects on the ways nvestors make decsons. In Hon-Snr et al. (2012, we fnd that nvestors tradng experence makes them less nfluenced by behavoral bases. Now, we are nterested n establshng f the correlatons between the bases also change wth experence. We expect more experenced nvestors to behave more consstently, n any case. In other words, we suggest that more experenced nvestors are more lkely to decde for themselves whether to rely on smplfyng decson-makng technques n general or to reject all of them. Moreover, we may consder the same matter from a dfferent angle. Studes by Ggerenzer and Selten, systematzed n Ggerenzer and Selten (2001, put forward the concept of bounded ratonalty and suggest that heurstcs do not represent systematc devatons from ratonal behavor, but rather a collecton of useful rules of decson-makng developed durng the process of evoluton and people makng rapd and, though not mathematcally calculated and proven, usually correct decsons. They dub ths collecton of heurstcs an adaptve toolbox and menton that t s not unversal but rather developed and amplfed durng each of our lves dependng on the types of stuatons and problems we face. In ths context, we may expect more experenced nvestors to possess more ample adaptve toolboxes and to employ the heurstcs (or the ratonal crtera for nvestment decsons n a more systematc way. In other words, we (agan expect that more experenced nvestors are more lkely to decde whether to employ ratonal or ntutve decsonmakng technques. Thus, we hypothesze the followng: Hypothess 2: The correlatons between the behavoral effects are hgher for more experenced nvestors. To test ths hypothess, we calculate correlaton coeffcents between the bases separately by the categores of nvestors reported market experences. Because the subsample of professonal nvestors s relatvely small, we employ only the subsample of webste vstors for ths analyss. Table 5 reports the correlaton coeffcents by categores of experence and for each of the bases and also compares (n Panel D the correlaton coeffcents for the most and least experenced nvestors. 5 The results n general support Hypothess 2. Though the correlatons between the bases do not ncrease contnuously wth stock tradng experence, the clearly lowest correlaton coeffcents for all the bases are obtaned wthn the category of the least experenced nvestors (wth reported experence of less than 3 years. We perform a statstcal comparson of the correlatons between the extreme experence categores, employng the Fsher r-to-z transformaton to convert correlaton coeffcents (Pearson s correlatons to normally dstrbuted varables (z and compare the latter between the subsamples. Ths comparson reveals that 8 out of 10 coeffcents are hgher for the most experenced nvestors, 6 of them sgnfcantly at the 5% level, ncludng 5 at the 1% level. In other words, as expected, non-experenced traders are more lkely to behave nconsstently or possess more lmted adaptve toolboxes, that s, to rely on certan smplfyng behavoral technques whle rejectng others. We may also note that the correlaton coeffcents for the most experenced non-professonal nvestors are stll lower than those we obtaned n the prevous subsecton for the group of professonal nvestors 6, ndcatng that t s lkely that the latter group, though not nec- Vzja Press&IT

10 40 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr essarly more ratonal (as shown by Hon-Snr et al., 2012, at least behaves more consstently, or, n other words, has more professonal experence and employs more ample sets of decson-makng rules. Fnally, we should menton that all of the correlaton coeffcents for all of the nvestor categores are stll sgnfcantly postve, provdng an mportant robustness check for Hypothess 1. Furthermore, we wsh to analyze the correlatons between the behavoral effects separately for male and female nvestors. Psychologcal dfferences between men and women are evdent and well-documented n prevous lterature (see, for example, Fengold, 1994; Frtz, & Helgeson, 1998; Helgeson, 1994; Helgeson, 2003; Hyde, In Hon-Snr et al (2012, we document that male nvestors are less lkely to employ smplfyng decson-makng rules. In the framework of the present study, we expect male nvestors to employ more sophstcated sets of decson-makng technques, and therefore, hypothesze the followng: Hypothess 3: The correlatons between the behavoral effects are hgher for male nvestors. To test the hypothess, we once agan employ only the non-professonal nvestors responses. Table 6 comprses the correlaton coeffcents and ther averages, separately for male and female nvestors. The results support Hypothess 3. As reported n Panel B, 9 out of 10 coeffcents are hgher for male nvestors (or lower for female nvestors, 6 of them sgnfcantly at the 5% level, ncludng 3 at the 1% level. These fndngs ndcate that t s lkely that male nvestors are more consstent n employng behavoral decson-makng technques or, alternatvely, possess more ample adaptve toolboxes. Fnally, we compare the correlatons between the bases for dfferent groups of ages. Agan, the lterature dealng wth age dfferences n the magntudes of behavoral bases s rather scarce. Kudryavtsev and Cohen (2010, 2011a, 2011b report that younger people are slghtly less affected by anchorng bas 7 and hndsght bas 8 when recallng fnancal nformaton. Therefore, we mght expect them, n general, to use more ample collectons of decson-makng rules. That s, we hypothesze the followng: Hypothess 4: The correlatons between the behavoral effects are hgher for younger nvestors. In Table 7, we dvde the subsample of non-professonal nvestors nto three categores of age years old, years old, and older than 40 9 and calculate the correlatons between the bases for each of the categores. The results do not support Hypothess 4. The correlaton coeffcents are very smlar for all of the age categores, and the dfferences between the correlatons for the youngest and the oldest nvestors are of dfferent sgns, the majorty of them beng nonsgnfcant, as demonstrated by Panel C. Therefore, nvestors ages most lkely do not sgnfcantly affect the consstency of the decsons. However, the very hgh and strongly sgnfcant correlaton coeffcents we obtan for all of the age categores serve as mportant robustness checks for our general Hypothess 1. Conclusons and Dscusson Our paper explores the effects of behavoral bases namely, the dsposton effect, herd behavor, avalablty heurstc, gambler s fallacy and hot hand fallacy on the mechansm of stock market decson-makng and, n partcular, the cross-sectonal correlatons between the magntudes of the bases. Employng an extensve onlne survey, we demonstrate that on average, actve stock market nvestors exhbt moderate degrees of behavoral bases. We then calculate cross-sectonal correlaton coeffcents between the bases, and as a major contrbuton of our study, confrm that all of them are postve and hghly sgnfcant for both professonal and non-professonal nvestors. Ths fndng shows that f an nvestor accepts certan ntutve decson-makng technque, she wll most lkely accept others as well. Furthermore, we perform a subsample analyss of the correlatons and determne that the correlaton coeffcents between the bases are hgher for more experenced nvestors and male nvestors, ndcatng that these categores lkely behave more consstently, or, n other words, are more lkely to decde for themselves whether to rely on smplfyng decson-makng technques n general or reject all of them. Alternatvely, ths fndng may suggest that the more experenced nvestors manage to develop (everyone for herself more sophstcated adaptve toolboxes, or collectons of heurstcs, and apply them more systematcally, possbly arrvng at better nvestment results. We also fnd that the correlaton coeffcents for the most experenced non-professonal nvestors are lower than those for the professonal n- CONTEMPORARY ECONOMICS DOI: /ce

11 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 41 vestors, suggestng that t s lkely that the latter group, though not necessarly more ratonal, at least makes more consstent decsons, or possesses more ample adaptve toolboxes. However, the correlatons appear to be ndependent from nvestors ages. Importantly, all of the correlaton coeffcents we obtan for all of the subsamples and categores of partcpants are postve and hghly sgnfcant, provdng a strong robustness check for our major fndng. Our results may have a number of nterestng mplcatons. Frst of all, accordng to our man fndng, stock market nvestors are lkely to run to extremes, that s, to ether be skeptcal towards behavoral decsonmakng technques n general or follow at least a few of them. Ths result may be applcable for both academc researchers and stock market practtoners. From the research pont of vew, t makes nvestors behavors more predctable. That s, f the real market, survey, or even expermental data one employs ndcate that an nvestor or group of nvestors exhbts one or several behavoral bases, one mght assume that these specfc nvestors are affected by other bases as well. Fnancal consultants, n ther turn, mght fnd t smpler to convnce an nvestor who appears to be affected by one of the bases to make a decson consstent wth another bas or bases 10 or, on the contrary, to convnce a ratonal nvestor to reman ratonal all along the way. Both sdes of the game mght pay attenton to ths fndng. Wth regards to the hgher correlatons between the bases for more experenced nvestors and for male nvestors, ths fndng mples that the latter group, beng n general less nclned to employ ntutve decsonmakng technques, may also fnd t easer to heal themselves of all the behavoral bases knowng that one of them may result n nferor nvestment performances. They, and actually all the nvestors, smply have to be aware of as many known bases as possble to avod them and choose approprate nvestment strateges. References Avery, C., & Zemsky, P. (1998. Multdmensonal Uncertanty and Herd Behavor n Fnancal Markets. Amercan Economc Revew, 88(4, Ayton, P., & Fscher, I. (2004. The Hot Hand Fallacy and the Gambler s Fallacy: Two Faces of Subjectve Randomness? Memory and Cognton, 32(8, Barber, B. M., & Odean, T. (2008. All that Gltters: The Effect of Attenton and News on the Buyng behavor of Indvdual and Insttutonal Investors. Revew of Fnancal Studes, 21(2, Bremer, M., & Kato K. (1996. Tradng Volume for Wnners and Losers on the Tokyo Stock Exchange. Journal of Fnancal and Quanttatve Analyss, 31(1, Camerer, C. (1989. Does the Basketball Market Beleve n the Hot Hand? Amercan Economc Revew, 79(5, Chau, A., & Phllps, J. (1995. Effects of Perceved Control upon Wagerng and Attrbutons n Computer Blackjack. The Journal of General Psychology, 122(3, Chrste, W. G., & Huang, R. D. (1995. Followng the Ped Pper: Do Indvdual Returns Herd Around the Market? Fnancal Analysts Journal, 51(4, Cpran, M., & Guarno, A. (2005. Herd Behavor n a Laboratory Fnancal Market. Amercan Economc Revew, 95(5, Cpran, M., & Guarno, A. (2008. Herd Behavor and Contagon n Fnancal Markets. The B.E. Journal of Theoretcal Economcs (Contrbutons, 8(1, Retreved from: vew/j/bejte /bejte /bejte xml Cpran, M., & Guarno, A. (2009. Herd Behavor n Fnancal Markets: A Feld Experment wth Fnancal Market Professonals. Journal of the European Economc Assocaton, 7(1, Clotfelter, C. T., & Cook, P. J. (1989. Sellng Hope: State Lotteres n Amerca. Cambrdge, MA: Harvard Unversty Press. Clotfelter, C. T., & Cook, P. J. (1991. Lotteres n the Real World. Journal of Rsk and Uncertanty, 4(3, Clotfelter, C. T., & Cook, P. J. (1993. The Gambler s Fallacy n Lottery Play. Management Scence, 39(12, Croson, R., & Sundal, J. (2005. The Gambler s Fallacy and the Hot Hand: Emprcal Data from Casnos. Journal of Rsk and Uncertanty, 30(3, Danel, K., Hrshlefer, D. &, Teoh, S. H. (2002. Investor Psychology n Captal Markets: Evdence and Polcy Implcatons. Journal of Monetary Economcs, 49(1, Vzja Press&IT

12 42 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr Dhar, R., & Zhu, N. (2002. Up Close and Personal: An Indvdual Level Analyss of the Dsposton Effect (ICF Workng Paper No Yale School of Management. Drehmann, M., Oechssler, J., & Rder, A. (2005. Herdng and Contraran Behavor n Fnancal Markets - An Internet Experment. Amercan Economc Revew, 95(5, Estes, W. (1964. Probablty Learnng. In A. W. Melton (Ed., Categores of Human Learnng (pp New York, NY: Academc Press. Fengold, A. (1994. Gender Dfferences n Personalty: A Meta-Analyss. Psychologcal Bulletn, 116(3, Ferrs, S. P, Haugen, R. A. & Makhja, A. K. (1988. Predctng Contemporary Volume wth Hstorc Volume at Dfferental Prce Levels: Evdence Supportng the Dsposton Effect. Journal of Fnance, 43(3, Frazzn, A. (2006. The Dsposton Effect and Underreacton to News. Journal of Fnance, 61(4, Freder, L. (2004. Evdence on Behavoral Bases n Tradng Actvty (EFA 2004 Maastrcht Meetngs Paper No Retreved from SSRN: ssrn.com/abstract= Frtz, H. L. & Helgeson, V. S. (1998. Dstnctons of Unmtgated Communon from Communon: Self- Neglect and Overnvolvement wth Others. Journal of Personalty and Socal Psychology, 75(1, Gal, I. & Baron, J. (1996. Understandng Repeated Smple Choces. Thnkng and Reasonng, 2(1, Ganzach, Y. (2001. Judgng Rsk and Return of Fnancal Assets. Organzatonal Behavor and Human Decson Processes, 83(2, Ggerenzer, G. & Selten, R. (Eds.. (2001. Bounded Ratonalty: The Adaptve Toolbox. Cambrdge, MA: MIT Press. Glovch, T., Vallone, R. & Tversky, A. (1985. The Hot Hand n Basketball: On the Mspercepton of Random Sequences. Cogntve Psychology, 17(3, Goetzmann, W. N., & Massa, M. (2003. Dsposton Matters: Volume, Volatlty and Prce Impact of a Behavoral Bas (Workng Paper, No Retreved from NBER webste: papers/w9499.pdf Grnblatt, M. & Han, B. (2005. Prospect Theory, Mental Accountng and Momentum. Journal of Fnancal Economcs, 78(2, Hahn, U. & Warren, P. A. (2009. Perceptons of Randomness: Why Three Heads are Better than Four. Psychologcal Revew, 116(2, Hauser-Rethaller, U. & Kong, U. (2002. Parmutuel Lotteres: Gamblers Behavor and the Demand for Tckets. German Economc Revew, 3(2, Helgeson, V. S. (1994. Relaton of Agency and Communon to Well-Beng: Evdence and Potental Explanatons. Psychologcal Bulletn, 116(3, Helgeson, V. S. (2003. Unmtgated Communon and Adjustment to Breast Cancer: Assocatons and Explanatons. Journal of Appled Socal Psychology, 33(8, Hrshlefer D. & Teoh, S. H. (2003. Herd Behavor and Cascadng n Captal Markets: A Revew and Synthess. European Fnancal Management, 9(1, Hon-Snr, S., Kudryavtsev, A. & Cohen, G. (2012. Stock Market Investors: Who Is More Ratonal, and Who Reles on Intuton? Internatonal Journal of Economcs and Fnance, 4(5, Huddart, S., Lang, M. & Yetman, M. (2007. Psychologcal Factors, Stock Prce Paths, and Tradng Volume. (Unpublshed Paper. Hwang, S. & Salmon, M. (2004. Market Stress and Herdng. Journal of Emprcal Fnance, 11(4, Hyde, J. S. (2005. The Gender Smlartes Hypothess. Amercan Psychologst, 60(6, Kahneman, D. & Tversky, A. (1972. Subjectve Probablty: A Judgment of Representatveness. Cogntve Psychology, 3(3, Kahneman, D. & Tversky, A. (1979. Prospect Theory: An Analyss of Decson under Rsk. Econometrca, 46(2, Kahneman, D., Slovc, P. & Tversky, A. (Eds.. (1982. Judgment under Uncertanty: Heurstcs and Bases. New York, NY: Cambrdge Unversty Press. Kausta, M. (2004. Market-Wde Impact of the Dsposton Effect: Evdence from IPO Tradng Volume. Journal of Fnancal Markets, 7(2, Klger, D. & Kudryavtsev, A. (2008. Reference Pont Formaton by Market Investors. Journal of Bankng and Fnance, 32(9, CONTEMPORARY ECONOMICS DOI: /ce

13 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 43 Klger, D. & Kudryavtsev, A. (2010. The Avalablty Heurstc and Investors Reacton to Company-Specfc Events. Journal of Behavoral Fnance, 11(1, Kudryavtsev, A. & Cohen, G. (2010. Anchorng and Pre-Exstng Knowledge n Economc and Fnancal Settngs. Amercan Journal of Socal and Management Scences, 1(2, Kudryavtsev, A. & Cohen, G. (2011a. The Less I Remember, the More Confdent I Feel: Hndsght Bas n Economc and Fnancal Knowledge. Internatonal Research Journal of Appled Fnance, 2(2, Kudryavtsev, A. & Cohen, G. (2011b. Behavoral Bases n Economc and Fnancal Knowledge: Are They the Same for Men and Women? Advances n Management and Appled Economcs, 1(1, Lakonshok, J. & Smdt, S. (1986. Volume for Wnners and Losers: Taxaton and Other Motves for Stock Tradng. Journal of Fnance, 41(4, Lakonshok, J. Shlefer, A., & Vshny, R. W. (1992. The Impact of Insttutonal Tradng on Stock Prces. Journal of Fnancal Economcs, 32(1, Langer, E. J. (1975. The Illuson of Control. Journal of Personalty and Socal Psychology, 32(2, Laplace, P. S. (1951. A Phlosophcal Essay on Probabltes. New York, NY: Dover Lee, W. (1971. Decson Theory and Human Behavor. New York, NY: Wley. Lee, I. H. (1998. Market Crashes and Informatonal Avalanches. Revew of Economc Studes, 65(4, Lee, B., O Bren, J., & Svaramakrshnan, K. (2007. An Analyss of Fnancal Analysts Optmsm n Long-term Growth Forecasts. Journal of Behavoral Fnance, 9(3, Locke, P. R., & Mann, S. C. (2005. Professonal Trader Dscplne and Trade Dsposton. Journal of Fnancal Economcs, 76(2, Metzger, M. (1984. Bases n Bettng: An Applcaton of Laboratory Fndngs. Psychologcal Reports, 56(3, Odean, T. (1998. Are Investors Reluctant to Realze Ther Losses? Journal of Fnance, 53(5, Oehler, A., Helmann, K., Lager, V., & Oberlander, M. (2002. Dyng Out or Dyng Hard? Dsposton Investors n Stock Markets EFA 2002 Berln Meetngs Presented Paper. Retreved from SSRN: or org/ /ssrn Papachrstou, G. (2004. The Brtsh Gambler s Fallacy. Appled economcs, 36(18, Papachrstou, G., & Karamans, D. (1998. Investgatng Effcency of Bettng Markets: Evdence from the Greek 6/49 Lotto. Journal of Bankng and Fnance, 22(12, Park, A., & Sabouran, H. (2011. Herdng and Contraran Behavor n Fnancal Markets. Econometrca, 79(4, Rabn, M., & Vayanos, D. (2010. The gambler s and hot-hand fallaces: Theory and applcatons. Revew of Economc Studes, 77(2, Roger, P., & Brohanne, M. H. (2007. Effcency of Bettng Markets and Ratonalty of Players: Evdence from the French 6/49 Lotto. Journal of Appled statstcs, 34(6, Shapra, Z., & Veneza, I. (2001. Patterns of Behavor of Professonally Managed and Independent Investors. Journal of Bankng and Fnance, 25(8, Shefrn, H. & Statman, M. (1985. The Dsposton to Sell Wnners Too Early and Rde Losers Too Long. Journal of Fnance, 40(3, Shller, R. J. (1998. Human Behavor and the Effcency of the Fnancal System (NBER Workng Paper No Natonal Bureau of Economc Research. Stracca, L. (2004. Behavoral Fnance and Asset Prces: Where Do We Stand? Journal of Economc Psychology, 25(3, Sun, Y. & Wang, H. (2010. Gambler s Fallacy, Hot Hand Belef, and the Tme of Patterns. Judgment and Decson Makng, 5(2, Sundal, J. & Croson, R. (2006. Bases n Casno Bettng: The Hot Hand and the Gambler s Fallacy. Judgment and Decson Makng, 1(1, Terrell, D. (1994. A Test of the Gambler s Fallacy: Evdence from Par-Mutuel Games. Journal of Rsk and Uncertanty, 8(3, Terrell, D. (1998. Bases n Assessments of Probabltes: New Evdence from Greyhound Races. Journal of Rsk and Uncertanty, 17(2, Terrell, D., & Farmer, A. (1996. Optmal Bettng and Effcency n Parmutuel Bettng Markets wth Informaton Costs. The Economc Journal, 106(437, Thaler, R. (1985. Mental Accountng and Consumer Choce. Marketng Scence, 4(3, Vzja Press&IT

14 44 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr Tversky, A., & Kahneman, D. (1971. Belef n the Law of Small Numbers. Psychologcal Bulletn, 76(2, Tversky, A., & Kahneman, D. (1973. Avalablty: A Heurstc for Judgng Frequency and Probablty. Cogntve Psychology, 5(2, Tversky, A., & Kahneman, D. (1974. Judgment under Uncertanty: Heurstcs and Bases. Scence, 185(4157, Wang, D., & Canela, M. (2006. Herd Behavor towards the Market Index: Evdence from 21 Fnancal Markets (Workng Paper No IESE Busness School. Weber, M., & Camerer, C. F. (1998. The Dsposton Effect n Securtes Tradng: An Expermental Analyss. Journal of Economc Behavor and Organzaton, 33(2, Wermers, R. (1995. Herdng, Trade Reversals, and Cascadng by Insttutonal Investors. (Unpublshed Paper, Unversty of Colorado, Boulder. Zelonka, P. (2004. Techncal Analyss as the Representaton of Typcal Cogntve Bases. Internatonal Revew of Fnancal Analyss, 13(2, Endnotes 1. There was one more reason for lmtng the number of questons referrng to each of the bases to two. Our goal was to refer to a relatvely large number of bases whle not makng the questonnare too long (resultng n potentally unnformatve answers. Makng our questonnare relatvely short (we have explctly stated that t was gong to take no more than 3-4 mnutes most lkely allowed us to recrut more partcpants among the webste vstors. 2. We subtract the grade on queston 2 because t s negatvely correlated wth the magntude of the dsposton effect exhbted by the respectve partcpants. The number 6 s added to reduce the dsposton grade to the same 2-to-10 scale as the rest of the bas grades. 3. In Hon-Snr, Kudryavtsev, and Cohen (2011, we dscuss ndvdual dfferences n the magntudes of these fve behavoral bases. We observe that all the effects are sgnfcantly more weakly pronounced for more experenced nvestors and for male nvestors. However, the magntudes of the effects do not sgnfcantly dffer between the professonal portfolo managers and non-professonal nvestors. Moreover, the latter appear to be sgnfcantly more strongly affected by the behavoral bases than the most experenced non-professonal nvestors. 4. Sx out of 10 correlaton coeffcents are hgher for the non-professonal nvestors, and the other 4 are lower. None of the dfferences are sgnfcant. The detaled results are avalable upon request from the authors. 5. We employ the Fsher r-to-z transformaton to convert correlaton coeffcents (Pearson s correlatons to normally dstrbuted varables (z and compare the latter between the subsamples. 6. All of the 10 correlaton coeffcents are hgher for the professonal nvestors, 7 of them sgnfcantly at the 1% level. The detaled results are avalable upon request from the authors. 7. Anchorng bas refers to people s tendency to form ther estmates for dfferent categores, startng from a partcular avalable, and often rrelevant, value and nsuffcently adjustng ther fnal judgments from ths startng value. 8. Hndsght bas denotes people s tendency to overestmate n hndsght how predctable an outcome was n foresght. 9. Due to the small number of partcpants n the last three age categores accordng to Table 1, we combne them nto one category older than If, for some reason, that s what certan fnancal consultants are nterested n dong. 11. Index that tracks the prces of the shares of the 100 companes wth the hghest market captalzaton on the Tel Avv Stock Exchange. CONTEMPORARY ECONOMICS DOI: /ce

15 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 45 Appendx 1: Tables Table 1. Sample descrptve statstcs Panel A: Portfolo managers (41 respondents Category Number Percent of total 1. Gender: Men Women Age: Captal market nvestor for: Less than 3 years to 5 years to 10 years More than 10 years Panel B: Market nvestors (305 respondents Category Number Percent of total 1. Gender: Men Women Age: Captal market nvestor for: Less than 3 years to 5 years to 10 years More than 10 years Vzja Press&IT

16 46 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr Table 2. Cross-sectonal correlaton coeffcents of grades wthn the bas-related pars of questons Par of questons Panel A: Portfolo managers (41 respondents Cross-sectonal correlaton coeffcent between the queston grades Questons 1 & 2 (Dsposton effect *** Questons 3 & 4 (Gambler's fallacy 0.928*** Questons 5 & 6 (Hot hand fallacy 0.877*** Questons 7 & 8 (Herd behavor 0.827*** Questons 9 & 10 (Avalablty heurstc 0.842*** Par of questons Panel B: Market nvestors (305 respondents Cross-sectonal correlaton coeffcent between the queston grades Questons 1 & 2 (Dsposton effect *** Questons 3 & 4 (Gambler's fallacy 0.917*** Questons 5 & 6 (Hot hand fallacy 0.862*** Questons 7 & 8 (Herd behavor 0.841*** Questons 9 & 10 (Avalablty heurstc 0.842*** Note Astersks denote 1-taled p-values: *p<0.10; **p<0.05; ***p<0.01 Table 3. Basc descrptve statstcs of bas grades The table reports, by groups of partcpants, basc statstcs of the bas grades calculated as follows: D G = G _ G _ 2 ; G G = G _ 2 + G _ 3 ; H G = G _ 5 + G _ 6 ; B G = G _ 7 + G _ 8 ; A G = G _ 9 + G _ 10 where: G _ N s the grade (answer gven by partcpant for queston (statement N. Panel A: Portfolo managers (41 partcpants Statstcs Herd (behavor Mean Medan Standard Devaton Maxmum Mnmum Grade [6,10], percent Statstcs Panel B: Market nvestors (305 partcpants Herd (behavor Mean Medan Standard Devaton Maxmum Mnmum Grade [6,10], percent CONTEMPORARY ECONOMICS DOI: /ce

17 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 47 Table 4. Cross-sectonal correlatons between behavoral bases: Total sample The table reports, by groups of partcpants, correlaton coeffcents between the bas grades. Last column reports average correlaton coeffcents for each bas grade wth other grades, by groups of partcpants. Panel A: Portfolo managers (41 partcpants Correlaton coeffcents between bas grades Herd (behavor Gambler s grade Herd (behavor 0.904*** 0.901*** 0.906*** 0.891*** 0.948*** 0.932*** 0.934*** 0.936*** 0.942*** 0.932*** Panel B: Non-professonal nvestors (305 partcpants Correlaton coeffcents between bas grades Herd (behavor Gambler s grade Herd (behavor 0.903*** 0.907*** 0.905*** 0.889*** 0.949*** 0.936*** 0.938*** 0.948*** 0.943*** 0.935*** Note Astersks denote 1-taled p-values: *p<0.10; **p<0.05; ***p< Vzja Press&IT

18 48 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr Table 5. Cross-sectonal correlatons between behavoral bases: Subsample analyss by categores of reported stock market experence. The table compares the correlaton coeffcents between the bas grades for dfferent categores of nvestors accordng to ther reported nvestment experence. In Panel D, the second row n each square reports the z-statstc accordng to the Fsher r-to-z transformaton for the comparson of correlaton coeffcents between nvestors wth more than 10 years of experence and those wth less than 3 years of experence (n ths order. Panel A: Reported stock market nvestment experence of less than 3 years (107 partcpants Correlaton coeffcents between bas grades Herd (behavor Gambler s grade Herd (behavor 0.312*** 0.392*** 0.405*** 0.253*** 0.850*** 0.750*** 0.808*** 0.761*** 0.770*** 0.691*** Panel B: Reported stock market nvestment experence of 3 to 5 years (29 partcpants Correlaton coeffcents between bas grades Herd (behavor Gambler s grade Herd (behavor 0.873*** 0.863*** 0.835*** 0.878*** 0.903*** 0.887*** 0.907*** 0.909*** 0.943*** 0.940*** CONTEMPORARY ECONOMICS DOI: /ce

19 Ratonal or Intutve : Are Behavoral Bases Correlated Across Stock Market Investors? 49 Table 5. (contnued Panel C: Reported stock market nvestment experence of 5 to 10 years (44 partcpants Correlaton coeffcents between bas grades Herd (behavor Gambler s grade Herd (behavor 0.745*** 0.774*** 0.761*** 0.730*** 0.911*** 0.892*** 0.852*** 0.882*** 0.891*** 0.860*** Panel D: Reported stock market nvestment experence of more than 10 years (125 partcpants Correlaton coeffcents between bas grades Comparson of correlatons: Investors wth experence of more than 10 years versus nvestors wth experence of less than 3 years: z-statstc accordng to the Fsher r-to-z transformaton Herd (behavor 0.743*** 4.75*** 0.764*** 4.43*** 0.760*** 4.25*** 0.753*** 5.40*** Gambler s grade 0.794*** *** *** *** 2.57*** 0.804*** 0.67 Herd (behavor 0.816*** 2.21** Note Astersks denote 1-taled p-values: *p<0.10; **p<0.05; ***p< Vzja Press&IT

20 50 Vol. 7 Issue Andrey Kudryavtsev, Gl Cohen, Shlomt Hon-Snr Table 6. Cross-sectonal correlatons between behavoral bases: Male versus female nvestors The table compares the correlaton coeffcents between the bas grades for male and female nvestors. In Panel B, the second row n each square reports the z-statstc accordng to the Fsher r-to-z transformaton for the comparson of correlaton coeffcents between women and men (n ths order. Panel A: Male nvestors (226 partcpants Correlaton coeffcents between bas grades Herd (behavor Gambler s grade Herd (behavor 0.874*** 0.881*** 0.874*** 0.857*** 0.931*** 0.925*** 0.912*** 0.934*** 0.924*** 0.924*** Panel B: Female nvestors (79 partcpants Correlaton coeffcents between bas grades Comparson of correlatons: Female versus Male: z-statstc accordng to the Fsher r-to-z transformaton Herd (behavor 0.842*** *** -2.44*** 0.790*** -2.10** 0.778*** -1.82** Gambler s grade 0.929*** *** -2.48*** 0.931*** *** -2.05** 0.909*** Herd (behavor 0.839*** -3.00*** Note Astersks denote 1-taled p-values: *p<0.10; **p<0.05; ***p<0.01 CONTEMPORARY ECONOMICS DOI: /ce