Swings in Sentiment and Stock Returns: Evidence from a Frontier Market

Transcription

1 Inernaional Journal of Trade, Economics and Finance, Vol. 4, No. 6, December 3 Swings in Senimen and Sock Reurns: Evidence from a Fronier Marke M. Arifur Rahman, Lim Kok Shien, and M. Shibley Sadique Absrac We invesigae he impac of noise rader senimen on he formaion of expeced reurns and volailiy in he conex of he fronier sock marke of Bangladesh. Empirical resuls based on a GARCH-in-mean framework show ha shifs in invesor senimen are significanly posiively correlaed wih excess marke reurns. Evidence of his direc impac of changes in senimen on expeced reurns is robus across sample periods and alernaive measures of senimen we use in he analysis. In addiion, we find ha he magniude of bullish or bearish senimen changes also exers an indirec effec on expeced reurns hrough is asymmeric influence on he condiional volailiy process. Overall, our resuls sugges ha shifs in invesor senimen in he marke represen a sysemaic risk facor ha is priced in equilibrium. Index Terms Invesor senimen, volailiy, excess reurns. I. INTRODUCTION We underake an empirical invesigaion ino he poenial impac of rading behavior of uninformed invesors on he sock price dynamics of a fronier sock marke. Unlike ha of informed invesors, rading decisions of uninformed invesors are driven by senimen which is no jusified by currenly available fundamenal informaion abou fuure cash flows and invesmen risk. A leas since John Maynard Keynes [] use of he analogy of a beauy cones o illusrae invesor behavior, economiss have pondered he ways in which agen senimen can play ou in he financial markes o move asse price away from fundamenal value. Decades laer, DeLong, Shleifer, Summers, and Waldmann [] formalize he role of senimen in a financial marke which is populaed by wo caegories of invesors: informed raders who raionally anicipae asse value, and uninformed noise raders who experience waves of opimisic or pessimisic senimen ha is no fully jusified by he facs abou fundamenals a hand. They demonsrae how, aggregae demand shifs on he par of noise raders (as a resul of heir acing in concer) riggered by changes in senimen can induce a sysemaic risk ha is priced in equilibrium. In heir model, noise rader senimen is sochasic and he deviaions in price from fundamenal value creaed by changes in senimen are unpredicable. As a Manuscrip received June, 3; revised Augus 9, 3. This work was suppored by he he Universii Brunei Darussalam research gran UBD/PNC//RG/(6) in financial par. M. A. Rahman and L. K. Shien are wih he Faculy of Business, Economics & Policy Sudies, Universii Brunei Darussalam, Gadong BE4, Brunei Darussalam ( arifur.rahman@ubd.edu.bn, kokshien.lim@ ubd.edu.bn). M. S. Sadique is wih he School of Business, Curin Universiy, Sarawak, Malaysia ( shibley@curin.edu.my). resul, now informed invesors have o ake ino accoun no only fundamenal risk of invesmen bu also he risk ha invesor senimen becomes even more exreme and prices move furher away from fundamenal values over he holding period. This addiional risk, known as he noise rader risk, renders arbirage aciviy risky and prevens risk-averse informed raders from aking fully offseing posiions o correc mispricing induced by noise rading. Consequenly, noise rader risk represens an addiional source of sysemaic risk ha is priced in he marke. So far a number of sudies, mosly done in he conex of US markes using a variey of senimen proxies, have largely len suppor o he implicaion of he DSSW model for asse pricing. Alhough conradicory, a very few recen papers provide some emerging marke evidence in he conex of he rapidly growing sock markes of China. We are no aware of any published research o dae ha has ried o undersand he implicaions of noise rader risk in he conex of a fronier sock marke. In his research plan, we propose o es he asse pricing implicaion of DSSW model a he marke level using daa from Dhaka Sock Exchange (DSE), Bangladesh. We choose a fronier marke like DSE because we consider i o be an ideal plaform o es he DSSW proposiion for a couple of reasons. Firs, compared o developed sock markes, and even some emerging markes like China and India, Bangladesh capial marke is no as well organized and managed. Marke regulaions ofen fail o proec invesor righs and regulae he aciviies of erran lised companies and marke paricipans. The marke is largely driven by unsophisicaed individual reail invesors who are generally informaion consrained, ofen lack he abiliy o shif hrough informaion due o heir poor educaional background, and do no have access o exper advice of financial analyss. As a resul, he invesmen decisions of an average invesor are more likely o be swayed by he swings of senimen in response o, for example, sheer rumors and hearsay, advice of sock brokers or financial gurus, or rend chasing behavior [3]. Recenly, Schmeling [4] presens evidence ha he impac of on sock reurns is higher for counries which have less marke inegriy and which are culurally more prone o herd-like behavior and overreacion. Second, unlike developed markes and many emerging markes, arbirage opporuniies for he raional invesors are exremely limied in Bangladesh sock marke. I operaes under a complee shor sale ban and here is no derivaive There is no sandards definiion of fronier sock markes. These markes generally, as defined by he MSCI and S&P, are considered o have low liquidiy, low ransparency, low level of foreign invesmens, high corrupion and a weak regulaory framework. Compared wih emerging markes, fronier markes are less financially and insiuionally developed. Boh MSCI and S&P caegorize Bangladesh as a fronier sock marke. DOI:.7763/IJTEF.3.V

2 Inernaional Journal of Trade, Economics and Finance, Vol. 4, No. 6, December 3 marke for arbirageurs o creae arificial posiions. II. A BRIEF REVIEW OF LITERATURE The efficien marke hypohesis [5] is he cornersone of classical finance heories on asse pricing. Based on he assumpion of invesor raionaliy, he efficien marke hypohesis posis ha prices reac only o informaion abou changes in fundamens and considers noise as a non-fundamenal facor ha should no have any influence on asse pricing. The argumen was ha an invesor rading on anyhing bu fundamenal informaion will fall prey o raional arbirageurs and evenually be driven ou of he marke. However, over he pas decades relenless evidence has surfaced calling he assumpion of invesor raionaliy in quesion. Therefore, he noise rader model of DSSW has araced remendous aenion of boh he academics and praciioners. Invesigaing he impac of invesor senimen on asse reurns and volailiy is essenial o appreciae he implicaions of heir model for asse pricing. The predicive power of senimen for reurns has been explored in a number of papers. Neal and Whealey [6] examine he forecas power of hree measures of individual invesor senimen: he level of discouns on closed-end funds, he ne muual fund redempions and he raio of odd-lo sales o purchases. They find ha fund discoun predics small firm reurns (bu unrelaed o fuure large firm reurns), and ha ne fund redempions capure he invesor senimen in fund discouns. However, hey find only lile indicaion ha odd-lo raio has reurn predicabiliy. Brown and Cliff [7], by examining various direc (survey based) and indirec measures (marke daa derived) of senimen, find ha alhough senimen levels and changes are srongly correlaed wih conemporaneous marke reurns, senimen indicaors have lile predicive power for near-erm fuure sock reurns. Their evidence suggess ha senimen effec is limied o small firm reurns and reurns exer mush sronger influence on senimen indicaors. However, in heir follow up research [8], hey esablish ha he lack of effec predicabiliy of senimen in he shor run does no preven i from affecing asse values in he long run. They show ha high senimen is followed by low cumulaive long run reurns as asse prices rever o heir fundamenal value. Baker and Wurgler [9] find ha he predicabiliy of US invesor senimen is more pronounced for firms ha are hard o price and hus difficul o arbirage (e.g., growh socks and small socks). More recenly, Schmeling [4] examine wheher consumer confidence as a proxy of individual invesor senimen - affecs expeced sock reurns in 8 indusrialized counries. He finds ha senimen negaively forecass aggregae sock marke reurns on average across counries. In line wih recen evidence for he US, his relaion also holds for reurns of value socks, growh socks, small socks, and for differen forecasing horizons. Ineresingly, he repors some empirical evidence suggesing he impac of senimen on sock reurns is higher for counries which have less marke inegriy and which are culurally more prone o herd-like behavior and overreacion. A few papers have also invesigaed he relaionship beween senimen and volailiy of reurns since senimen may affec expeced reurns hrough is impac on he marke s formaion of risk. Brown [] finds ha deviaions from he mean level of individual invesor senimen are associaed wih greaer volailiy in closed-end fund reurns. Lee, Jiang and Indro [], using a survey based senimen indicaor, es he impac of noise rader risk on he formaion of condiional volailiy and expeced reurns and find ha shifs in senimen are negaively correlaed wih condiional marke volailiy. Using a differen senimen measure based on daily muual fund flow daa, [] also repor similar finding on senimen on volailiy relaionship. As we have noed earlier, some recen research sheds some ligh on he asse pricing implicaion of invesor senimen in he conex of emerging sock markes of China. Using marke urnover, closed-end fund discoun and growh in he number of invesor accoun as senimen indicaors, [3] repor significan effec of changes in Chinese invesor senimen on reurns and noe ha he volailiy of reurns caused by invesor senimen changes is a sysemaic risk. Ng and Wu [4] however find ha neiher he volume of rade of insiuional nor individual invesors demonsraes price predicabiliy. Using a survey based measure of insiuional invesor senimen, [5] repor ha senimen does no predic fuure marke movemens, bu a drop in senimen increases marke volailiy and desabilizes markes. In summary herefore he empirical lieraure ells us ha invesor senimen may indeed have asse pricing implicaion and i is worh invesigaing furher especially in he conex of a differen marke organizaion which is markedly differen from he well developed sock markes. III. THE FRAMEWORK OF ANALYSIS The main objecive of he paper is o assess he asse pricing implicaion of he DSSW model using a fronier marke daa. DSSW predic ha he influence of noise raders senimen on expeced reurns can be boh ransiory and permanen. The direcion of he direc influence is deermined hrough he ineracion of wha DSSW erm as he price-pressure effec and he hold-more effec. Similarly, hey sugges ha he direcion of he indirec influence resuls from he relaive srengh of he Friedman effec and he creae-space effec. The price-pressure effec implies ha, when noise raders are on average bullish (bearish), heir rading pushes up (down) prices when hey purchase (sale) as asse. Consequenly, higher (lower) purchase (sale) prices ranslae ino lower expeced reurns. The effec of price pressure is herefore always negaive; no maer wheher noise rader senimen is bullish or bearish. The hold-more effec, on he oher hand, implies ha when noise raders become more bullish (bearish) such ha hey demand more (less) of risky asses, heir rading increases (decreases) he level of marke risk and hereby leads o higher (lower) expeced reurns. Therefore, noise rading increase expeced reurns only when noise raders are more bullish and he hold-more effec dominaes he price-pressure effec. However, he ne effec of bearish noise rader senimen on expeced reurn is always negaive since hese wo effecs become muually reinforcing. 348

3 Inernaional Journal of Trade, Economics and Finance, Vol. 4, No. 6, December 3 In addiion, he variabiliy of mispercepions abou asse s value on he par of noise raders increases price uncerainy in he marke and discourage risk-averse smar money invesors o confron noise raders in rading risky asses. The creae-space effec refers o a siuaion where noise induced increased volailiy end o crowed ou smar invesors and creae more space for noise raders o rade only among hemselves and hereby help increase heir reurns. Therefore, his siuaion implies higher volailiy and higher expeced reurns for he noise raders. The Friedman effec, on he oher hand, refers o a siuaion where noise induced increased volailiy does no preven smar money invesors from being agains and exploiing he noise raders. Since noise raders end o herd in heir invesmen decision, hey are usually very poor marke imers; meaning ha hey end o buy high and sell low. As a resul, if higher price uncerainy due o noise rading fail o preven smar money from being agains he noise raders, higher volailiy may also mean higher losses for he noise raders. The join influence of he creae-space effec and he Friedman effec on expeced reurn may eiher be posiive or negaive depending on heir relaive imporance a a paricular ime. Clearly, unlike he price-pressure and hold-more effecs, he creae-space and Friedman effecs influence asse prices no direcly bu hrough an increase in volailiy of reurns. To invesigae he role of senimen in DSE price process we follow [], who employ a generalized condiional heerokedasiciy (GARCH) in-mean framework and joinly es he impac of senimen boh on he formaion of condiional volailiy and expeced reurns. Specifically, we esimae an asymmeric GARCH in-mean model ha includes conemporaneous shifs in invesor senimen in he mean equaion and lagged shifs in senimen indicaor in he condiional volailiy equaion. The model akes he following form: r - r f = α +ασ +α ΔS +ε () where r is monhly reurn on he marke, r f is he risk-free rae, S is he shif in he measure of senimen indicaor, and h.capures he condiional volailiy of marke reurns. In addiion, in equaion () N(, h ) and I h 3 ( S ) D ( S ) ( D ) 4 5 where I if and zero oherwise, and D when and zero oherwise. S While he coefficien in equaion () measures he impac on senimen changes on marke reurns, coefficiens 4 and 5 gauge he impac of senimen shifs on condiional volailiy. Wheher his volailiy in urn affecs excess reurns is measured by he GARCH in-mean erm [7]. () Asymmeric GARCH in-mean specificaion is moivaed by [6] and in equaion (). In order o accoun for ypical auocorrelaion propery of excess marke reurn, we include firs four lags of he series in equaion (). The equaion is furher augmened o accoun for poenial day-of-he-week effec in marke reurns. IV. SENTIMENT MEASURES Our primary measure of senimen shif is a modified rading index (TRIN) a measure of relaive srengh of rading volume in relaion o advancing socks agains ha of declining socks. The original measure of TRIN, as inroduced by Richard Arms in an aricle in Barron s in 967, is given by A / D DV / D TRIN AV / DV AV / A where A ( D ) is he number of advancing (declining) socks and AV ( DV ) is advancing (declining) volume measured in number of shares. TRIN can herefore be inerpreed as he raio of he average daily volume of declining socks o he average daily volume of he advancing socks. Clearly, TRIN will have a neural value of when he average declining volume is exacly equal o he average rising volume on a day. Naurally, a TRIN value greaer (smaller) han can herefore be inerpreed as represening a bearish (bullish) rading behavior of he marke paricipans. Since he bullish (bearish) aciviy causes he raio o decline (rise), TRIN in is original form acually sounds couner inuiive. In addiion, as a closer look would however reveal, he lowes possible TRIN value is zero and hence i can never be more han one uni below he neural value. In conras, here is effecively no cap on is highes possible value. TRIN in is basic form herefore is also asymmeric by consrucion. In order o his asymmeric propery, we use he following modified TRIN (MTRIN) measure, which is also increasing in bullish marke aciviy: MTRIN (3) ln(/ TRIN) (4) In addiion, in order o es he robusness of our resuls based on our inuiive MTRIN measure, we use anoher senimen proxy based on a recen heoreical work [8]. They argue ha, in he presence of shor-sale consrain, marke liquidiy can be used as an indicaor of invesor senimen. Alhough here are several differen measures of liquidiy, considering limied availabiliy of a broad range of daa ses on fronier markes, we find he liquidiy measure proposed by Amihud [9] mos suiable for use in a fronier marke like he DSE. His measure is essenially an illiquidiy measure ha follows [] concep of illiquidiy he price response o order flows, and requires only daily reurn and value of rades as is inpus o calculaion. In order o conver he marke level Amihud illiquidiy measure o a liquidiy measure (which in increasing in senimen), we muliply is normalized log values by -. The firs difference of his ransformed Amihud measure represens our measure of senimen shifs. 349

4 Inernaional Journal of Trade, Economics and Finance, Vol. 4, No. 6, December 3 V. DATA AND DESCRIPTIVE STATISTICS In order o consruc our marke-wide senimen proxies and conduc furher analysis we use sock-level daily daa over he period from Jan hrough 8 Dec. Our sample of 3 socks includes dead and delised common socks, which helps alleviae poenial survivorship bias in our resuls. To check he sabiliy of resuls of he analysis, we spli he full sample period ino wo sub-samples one ranging from o 6 and he oher from 7 o. Reurns are calculaed as he logarihmic differences of prices imes. Capializaion weighed reurns on he porfolio of sample socks is considered o represen he marke reurn. Daily excess reurn on he marke is hen calculaed by deducing he call money rae from he marke reurn. TABLE I: DESCRIPTIVE STATISTICS OF EXCESS MARKET RETURNS AND SENTIMENT PROXIES Panel-A: Excess marke reurn Full Smpl s SS nd SS Mean Median Maximum Minimum Sd. Dev Skewness Kurosis Observaions Panel-B: MTRIN Full Smpl s SS nd SS Mean Median Maximum Minimum Sd. Dev Skewness Kurosis Observaions Panel-C: Amihud Full Smpl s SS nd SS Mean... Median..3.5 Maximum Minimum Sd. Dev Skewness Kurosis Observaions Table I provides some descripive saisics of excess reurns (Panel A) and our senimen proxies MTRIN (Panel B) and Amihud (Panel C), over he full sample and wo sub-sample periods. Excess reurns show ypical characerisics of significan non-normaliy. Sub-sample comparison reveals ha reurns in he second sub-sample is much more volaile, which conains boh he exreme reurn values (min and max) of he full sample period. Like ha of reurns, our senimen shif measures also display significan non-normaliy. In comparison o he firs sub-sample period, higher kurosis values of alernaive senimen shif measures in he second sub-period may have resuled from some frequen large swings in senimen values during he period. VI. EMPIRICAL RESULTS Table II repors he resuls of esimaing he GARCH specificaions of equaion () and () wih and wihou he senimen shif measures over he full sample and sub-sample periods. All GARCH specificaions are esimaed using he quasi-maximum likelihood mehod and sandard errors of esimaes are adjused for heeroskedasiciy []. To faciliae comparison, Panel A of he able repors he resuls of esimaing he benchmark specificaion wihou he senimen shif indicaors. Ineresingly, a negaive and significan GARCH-in-mean erm for he second sub-sample appears o conradic he CAPM predicion and implies a negaive price for ime-varying risk for he period. Esimaes of he mean equaion also suppor he presence of auocorrelaion and he day-of-he-week effec in daily excess reurns. Esimaes of he variance equaion highligh he difference in volailiy dynamics in wo sub-periods of analysis while he asymmeric effec of negaive reurn shocks is eviden in he second sub-sample, we find no such evidence for earlier sub-sample period. Panel B and C of he able presen he effec of senimen shifs on reurn and volailiy dynamics where senimen shifs are measured in erms of MTRIN and Amihud, respecively. The direc effec of senimen shifs on excess reurns is mos clearly eviden across measures and sub-periods of analysis. Judging by he size of he coefficiens, senimen shifs play a greaer role affecing excess reurns in periods when he marke is more volaile. Focusing on he mean equaion esimaes, i is eviden ha he hold-more effec dominaes he price-pressure effec in DSE and herefore he bullish (bearish) senimen of noise raders leads o an increase (decrease) in expeced reurns. Using boh of our senimen proxies we also find some evidence, paricularly wih reference o he firs sub-sample of daa, ha he magniude of senimen shif may significanly affec he formaion of condiional volailiy in he marke. Ineresingly, our sub-period analysis suggess ha he effec of senimen shif on condiional volailiy may be differen depending on he overall marke condiions. Specifically, using he MTRIN measure we find ha a bearish shif in senimen exer a negaive effec on he volailiy of fuure reurns in a relaively ranquil period, he effec however urns posiive during a relaively urbulen period of marke aciviy. In addiion, we find evidence ha he inroducion of senimen in our GARCH-in-mean framework has he poenial o urn he previously observed insignifican or negaive expeced reurn-volailiy relaionship ino posiive or only insignificanly negaive one. Using MTRIN as he senimen proxy for he full sample and he firs sub-sample, we find evidence ha as he magniude of he bullish (bearish) shif in senimen increases, here is an upward (a downward) revision in condiional volailiy, which, given a posiive expeced reurn-volailiy relaionship, leads o an upward revision in expeced reurns. 35

5 Inernaional Journal of Trade, Economics and Finance, Vol. 4, No. 6, December 3 This resul implies ha he creae-space effec of noise rading dominaes is Friedman effec in he conex of DSE. TABLE II: GARCH IN-MEAN MODEL OF EXCESS RETURNS WITH AND WITHOUT THE EFFECT OF SENTIMENT Panel-A: Full Smpl. s SS nd SS -.3 ** -.64 ** ** AR().9 ***.37 ***.69 ** AR() * AR(3).47 **.4.48 * AR(4).43 **.84 *** -.5 DAY DAY.97 ***.5 **.74 ** DAY3.4 *..97 DAY4.3 ***.46 **.383 ***.3 ***.4 ***.93 ***.9 ***.58 ***.69 ***.7 * *** ***.857 ***.8 *** N Log Like Skw Kur Q(5) 9.4 * Q (5) Panel-B: Full Smpl. s SS nd SS *** -.36 *** -.66 *.83 *.3 * ***.335 ***.79 *** AR(). ***.3 ***.75 *** AR() AR(3).4 **.3.4 * AR(4).3 *.85 *** -.8 DAY.9 *.9 *.5 DAY.94 ***.59 ***.36 *** DAY3.49 **.4 **.7 DAY4.3 ***.54 **.359 ***. ***.9.66 ***.9 ***.4 ***.65 ***.77 *.4.4 *** ***.853 ***.8 *** 4..7 * * -.9 **.66 ** N Log Like Skw Kur Q(5) Q (5) Panel-C : Full Smpl. s SS nd SS -.95 * -.65 ***.34 **.47.3 ** -.7 **.39 ***.44 *.358 *** AR(). ***.37 ***.6 ** AR() * AR(3).49 **..47 * AR(4).44 **.98 *** -.8 DAY DAY.5 **. *.77 DAY DAY4.7 ***.85.7 **.8 ***.3 **.88 ***.7 ***.58 ***.74 ***.89 ** *** ***.857 ***.84 *** ** ***.3 N Log Like Skw Kur Q(5) Q (5) * Noe: ***, ** and * indicae significance a, 5 and percen, respecively. VII. CONCLUSION We invesigae he impac of changes in noise rader senimen on sock prices in he conex of a fronier sock marke he Dhaka Sock Exchange, Bangladesh. We assess he effec of swings in senimen on boh he formaion of condiional volailiy and expeced reurns using daily sock daa over he period from January o 8 December in a generalized auoregressive condiional heeroskedasiciy (GARCH) in-mean framework. Our primary measure of senimen shifs is a modified rading index (TRIN) a measure of he relaive srengh of he rading volume in relaion o advancing socks agains ha of declining socks. We find ha, irrespecive of wheher he marke is in a relaively urbulen or ranquil sae, daily excess reurns are conemporaneously posiively relaed o shifs in invesor senimen. In addiion, depending on he marke saes, we uncover an asymmeric effec of he magniude of bullish or bearish changes in senimen on condiional volailiy of fuure excess reurns. While in a relaively volaile marke condiions, he magniude of only bearish change in senimen leads o an upward revision in volailiy, in a relaively sable marke condiions, he magniude of bullish (bearish) changes in senimen leads o upward (downward) revisions in volailiy. These resuls remain largely unalered o he effec of ouliers and an alernaive measure of senimen shif based on he changes in aggregae marke liquidiy. Overall, our empirical resuls show ha he changes in invesor senimen in a fronier sock marke like Bangladesh represen a sysemaic risk facor, which is priced in equilibrium. REFERENCES [] J. M. Keynes, The General Theory of Employmen, Ineres and Money, London, Melbourne, Torono: Macmillan, 936, ch.. [] J. B. D. Long, A. Shleifer, L. H. Summers, and R. Waldmann, Noise rader risk in financial markes, Journal of Poliical Economy, vol. 98, pp , 99. [3] A. Shleifer and L. H. Summers, The noise rader approach o finance, Journal of Economic Perspecives, vol. 4, pp. 9-33,

6 Inernaional Journal of Trade, Economics and Finance, Vol. 4, No. 6, December 3 [4] M. Schmeling, Invesor senimen and sock reurns: Some inernaional evidence, Journal of Empirical Finance, vol. 6, pp , 9. [5] E. F. Fama, Efficien capial markes: A review of heory and empirical work, Journal of Finance, vol. 5, pp , 97. [6] R. Neal and M. S. Whealey, Do measures of invesor senimen predic reurns? Journal of Financial and Quaniaive Analysis, vol. 33, pp , 998. [7] G. W. Brown and M. T. Cliff, Invesor senimen and he near-erm sock marke, Journal of Empirical Finance, vol., pp. -7, 4. [8] G. W. Brown and M. T. Cliff, Invesor senimen and asse valuaion, Journal of Business, vol. 78, pp , 5. [9] M. Baker and J. Wurgler, Invesor senimen and he cross-secion of sock reurns, Journal of Finance, vol. 6, pp , 6. [] G. W. Brown, Volailiy, senimen, and noise raders, Financial Analyss Journal, vol. 55, pp. 8-9, 999. [] W. Y. Lee, C. X. Jiang, and D. C. Indro, Sock marke volailiy, excess reurns, and he role of invesor senimen, Journal of Banking & Finance, vol. 6, pp ,. [] R. Beaumon, M.-V. Daele, B. Frijns, T. Lehner, and A. Muller, Invesor senimen, muual fund flows and is impac on reurns and volailiy, Managerial Finance, vol. 34, pp , 8. [3] Q. Zhang and S.-E. Yang, Noise rading, invesor senimen volailiy, and sock reurns, Sysems Engineering-Theory and Pracice, vol. 9, pp. 4-47, 9. [4] F. Wu e al., The rading behaviour of insiuions and individuals in Chinese equiy markes, Journal of Banking & Finance, vol. 3, pp , 7. [5] G. Kling and L. Gao, Chinese insiuional invesors senimen, Journal of Inernaional Financial Markes & Money, vol. 8, pp , 8. [6] D. B. Nelson, Condiional heeroscedasiciy in asse reurns: A new approach, Economerica, vol. 59, pp , 99. [7] L. R. Glosen, R. Jagannahan, and D. A. Runkle, On he relaion beween he expeced value and he volailiy of he nominal excess reurn on socks, Journal of Finance, vol. 48, pp , 993. [8] M. Baker and J. C. Sein, Marke liquidiy as a senimen indicaor, Journal of Financial Markes, vol. 7, pp. 7-99, 4. [9] Y. Amihud, Illiquidiy and sock reurns: cross-secion and ime series effecs, Journal of Financial Markes, vol. 5, pp. 3-56,. [] A. S. Kyle, Coninuous aucions and insider rading, Economerica, vol. 53, pp , 985. [] T. Bollerslev and J. M. Wooldridge, Quasi-maximum likelihood esimaion and inference in dynamic models wih ime varying covariances, Economerics Review, vol., pp. 43-7, 99. M. Arifur Rahman is a senior lecurer a he Universii Brunei Darussalam. He obained his Ph.D. in Finance from he Universiy of Wesern Sydney in Ausralia. His research ineress are accouning informaion and asse prices, issue in behavioral finance and emerging sock marke behavior. He has published in inernaionally refereed journals including he Review of Quaniaive Finance and Accouning, Applied Financial Economics and Froniers in Finance and Economics. Recenly, he has also reviewed papers for he Quarerly Review of Economics and Finance. Lim Kok Shien is a lecurer a Universii Brunei Darussalam. He obained his maser in Inernaional Finance from Universiy of New Souh Wales in Ausralia. His research ineress are reiremen planning and invesmens. He has provided numerous workshops for enrepreneurs and senior governmen officials on financial planning and reiremen. He has also done consulancy work on deermining conribuion raes for reiremen for he Brunei reiremen providen fund. M. Shibley Sadique is a senior lecurer a Curin Universiy, Malaysia. He obained his Ph.D. in Finance from Monash Universiy in Ausralia. His research ineress are exual informaion and marke behavior, nonlineariy in asse prices and behavioral finance. He has published in inernaionally refereed journals including Journal of Macroeconomics, Inernaional Journal of Finance & Economics and Asian Economic Review. He has been reviewer in differen inernaional journals such as Economics Leers, Communicaions in Saisics-Simulaion and Compuaion, Economic Noes - Review of Banking, Finance and Moneary Economics. 35