Dynamic relationship between stock return, trading volume, and volatility in the Stock Exchange of Thailand: does the US subprime crisis matter?

Transcription

1 MPRA Munich Personal RePEc Archive Dynamic relaionship beween sock reurn, rading volume, and volailiy in he Sock Exchange of Thailand: does he US subprime crisis maer? Komain Jiranyakul Naional Insiue of Developmen Adminisraion Sepember 216 Online a hps://mpra.ub.uni-muenchen.de/73791/ MPRA Paper No , posed 18 Sepember 216 9:16 UTC

2 Dynamic relaionship beween sock reurn, rading volume, and volailiy in he Sock Exchange of Thailand: does he US subprime crisis maer? Komain Jiranyakul School of Developmen Economics Naional Insiue of Developmen Adminisraion Bangkok, Thailand Absrac: Using daily daa from 24 o 215, his paper aemps o examine he relaionship beween reurn, volume and volailiy in he Thai sock marke. The main findings are ha rading volume plays a dominan role in he dynamic relaionships. Specifically, rading volume causes boh reurn and reurn volailiy when he US subprime crisis is aken ino accoun. The resuls may give undersanding on how invesors make heir rading decisions ha can affec porfolio adjusmen. Keywords: Sock reurn, rading volume, volailiy, VAR, subprime crisis JEL Classificaion: G15, G14 1. Inroducion In previous empirical sudies, he relaionship beween reurn and rading volume has been widely invesigaed in boh well-developed and emerging sock markes. 1 Earlier sudies emphasize he conemporaneous relaionship beween price changes and rading volume in he sock markes (Gallan e al., 1992, among ohers). In addiion, here is an asserion ha here is causal relaionship beween price changes and rading volume. Theoreically, here are compeing models ha explain why his noion exiss. The sequenial informaion arrival model assers ha he new informaion does no disseminae o all marke paricipans a he same ime. Therefore, lagged rading volume conains informaion ha is useful in predicing curren sock reurn and lagged sock reurn conains informaion ha is useful in predicing curren rading volume (Copeland, 1976, Jennings e al, 1981). Therefore, here should be a leas a unidirecional causaliy beween sock reurn and rading volume. The mixure of disribuion model assers ha here should be a unidirecional causaliy running from rading volume o sock reurn (Epps and Epps, 1976). According o his model, rading volume is an imporan measure of disagreemen among paricipans in he sock marke. When new informaion arrives he sock marke, he widening of disagreemen occurs. Black (1976) indicaes ha reurns of socks lised in he Dow Jones indusrial average are negaively correlaed wih volailiy. Wang (1994) proposes a raional expecaions model ha links rading volume o sock price volailiy under asymmeric informaion. Therefore, empirical sudies emphasize he dynamic relaionship beween reurn and rading volume, rading volume and reurn volailiy, and reurn and is volailiy. For volume-reurn relaionship, Saacioglu and Sarks (1998) find ha rading volume causes sock reurns, bu sock reurns do no cause rading volume. Chen e al. (21) examine he relaion beween reurns, volume and volailiy of sock indexes of nine inernaional sock markes. They find evidence of posiive correlaion beween rading volume and he absolue value of sock price change. 1 Karpoff (1987) gives a horough review of boh heoreical and empirical works peraining his relaionship. 1

3 Furhermore, here is bidirecional causaliy beween rading volume and sock reurns. Their resuls also show ha volailiy is persisen even afer accouning for curren and lagged volume effecs. Chuang e al. (29) find bidirecional causaliy beween rading volume and sock reurn wih he dominan role of rading volume. For he relaion beween rading volume, reurn and volailiy, earlier empirical work of Chrisie (1982) finds evidence of a negaive correlaion beween volume and volailiy. Gallan e al. (1992) find he dominan role of rading volume in he reurn-volailiy relaionship. Using boh linear and nonlinear causaliy ess, Brooks (1998) finds evidence of bidirecional causaliy beween rading volume and volailiy. Carroll and Kearney (212) examine he role of rading volumes in a GARCH-based ess of he mixure of disribuion hypohesis on firm-level daa for 2 larges Forune 5 socks. They find ha rading volumes and reurn volailiy are posiively correlaed, and hus he evidence suppors his hypohesis. Ong (215) employs alernaive approach raher han radiional linear and nonlinear causaliy ess, and finds ha rading volume plays a dominan role in he dynamic relaionship beween reurn and volailiy, and beween rading volume and volailiy for S&P5 socks. Some previous sudies focus on Asian sock markes. Moosa and Al-Loughani (1995) employ monhly daa o examine he price volume relaionship in Malaysia, Philippines, Singapore and Thailand. They find evidence of causaliy running from rading volume o absolue price changes and from price changes o rading volume in hese sock markes. In addiion, nonlinear and linear causaliy ess seem o produce he similar resuls. Using daily daa during 199 and 24, Pisedasalasai and Gunasekarage (27) examine he dynamic relaionships among sock reurns, reurn volailiy and rading volume for Indonesia, Malaysia, Philippines, Singapore and Thailand. They find ha sock reurns in hese economies are imporan in predicing heir fuure dynamics as well as hose of he rading volume, bu rading volume has a very limied impac on fuure dynamics of sock reurns. The rading volume in some markes seems o conain informaion for predicing fuure dynamics of reurn volailiy. Gebka (212) employs daily and weekly daa from January 199 o November 23 o examine he dynamic relaionship beween reurns, rading volume, and volailiy in Hong Kong, Indonesia, Japan, Souh Korea, Malaysia, Singapore, Taiwan and Thailand, and finds weak evidence indicaing ha rading volume plays dominan role on reurn and volailiy. Using daily daa from January 199 o June 28, Lin (213) invesigaes he dynamic relaionship beween reurns and rading volume in Indonesia, Malaysia, Singapore, Souh Korea, Taiwan and Thailand and finds evidence showing ha rading volume conains informaion o predic sock reurns in mos of he markes, excep he case of Singapore. Using daily daa of he Culcaa Sock Exchange in India, Bose and Rahman (215) find ha he conemporaneous or lagged rading volume as a proxy for laen informaion arrival o he marke do no adequaely convey informaion o induce raders view of he desirabiliy o rade. The presen sudy employs daily daa during 24 and 215 o examine he dynamic relaionship beween sock reurn, rading volume and reurn volailiy in he Thai sock marke. The main finding is ha rading volume plays an imporan par in he relaionship beween volume, reurn and volailiy in he Sock Exchange of Thailand. 2. Daa and Preliminary Resuls 2.1 Daa The daase comprises he series of daily marke and secoral sock indexes and respecive rading volume in he Thai sock marke. The daa are rerieved from SETSMART websie. The period of sudy ranges from January 3, 24 o December 3, 215. There are 2,932 observaions. The sock marke index is a marke capializaion-weighed index while he secoral sock indexes are he capializaion- 2

4 weighed equiy secor indexes. The reurn series are he price changes. The rading volumes are expressed in millions of shares. The descripive saisics are repored in Table 1. Table 1 Descripive saisics. Panel A: Reurn series. Mean S. D. Skewness Kurosis Marke Agro-indusry Consumpion Financials Indusrials Prop & Cons Resources Services Technology Panel B: Trading volume series. Mean S. D. Skewness Kurosis Marke Agro-indusry Consumpion Financials Indusrials Prop & Cons Resources Services Technology Noe: Prop & Cons sands for propery and consrucion secor. The descripive saisics of he sock marke reurn and hose of eigh secors show ha mos of he reurns are negaively skewed wih excess kurosis. The kurosis values indicae ha he reurns are no normally disribued. For he rading volume, he high rading volumes compared wih he marke rading volume are hose of propery and consrucion, echnology, services, indusrials and financials. All rading volumes are posiively skewed wih excess kurosis. 2.2 Trend and Uni Roo Tess Following Gallan e al. (1992), he rend saionary in rading volume is esed by regressing he series on a ime rend and a nonlinear ime rend. The es equaion is expressed as: TV a b c 2 e (1) where TV is he raw rading volume and is a linear ime rend and 2 is a nonlinear ime rend. The resuls of his regression show ha Eq. (1) performed quie well since he esimaed coefficiens of boh linear and quadraic ime rends are mosly significan a he 1 percen level. 2 As a resul, he derended rading volume is obained for he marke and each equiy secor. 2 The esimaed coefficiens of he quadraic ime rend are no significan for he agriculure and propery and consrucion secors. 3

5 In esing for saionary propery of he series, he augmened Dickey-Fuller (ADF) es and he Phillips and Perron (PP) es wih consan are used. The resuls of uni roo ess are repored in Table 2. Table 2 Resuls of uni roo ess. Panel A: Reurn series. ADF saisic p-value PP saisic p-value Marke [25] [563]. Agro-indusry [22] [492]. Consumpion [22] [31]. Financials [25] [24]. Indusrials [22] [346]. Prop & Cons [25] [293]. Resources [22] [353]. Services [25] [448]. Technology [25] [33]. Panel B. Derended rading volume series. ADF saisic p-value PP saisic p-value Marke [23] [28]. Agro-indusry [23] [27]. Consumpion [27] [35]. Financials [2] [28]. Indusrials [19] [19]. Prop & Cons [27] [28]. Resources [2] [26]. Services [26] [29]. Technology [27] [31]. Noe: Prop & Cons sands for propery and consrucion secor. The number in bracke is he opimal lag lengh for he ADF es deermined by Akaike Informaion Crierion (AIC) and he opimal bandwidh for he PP es. The daa for reurns and derended rading volume exhibi saionariy propery because he null hypohesis of uni roo is rejeced a he 1 percen level by boh he ADF and PP ess. This is he necessary condiion for he specified regression o obain he conemporaneous relaionships explained in he nex sub-secion. 2.3 Conemporaneous Relaionships The relaionship beween reurn and rading volume can be esimaed by he following regression: V a b R e (2) where V denoes derended rading volume, and R denoes equiy reurn. Eq. (2) is a simple regression. French (198) and Hui (25), among ohers, find evidence supporing he Monday effec. Therefore, he dummy variable ha capures he impac of he Monday effec can be included in Eq. (2). However, he esimaed coefficien of his dummy variable is insignifican in he relaionship. The esimaed coefficien b in Eq. (2) should be posiive. The iniial resuls of reurn-volume relaionship are shown in Table 3. 4

6 Table 3 Conemporaneous reurn-volume relaionship a b Marke (-.19) 6.771*** (5.725) Agro-indusry -.54 (-.32).582*** (5.679) Consumpion -.3 (-.16) 1.77*** (5.571) Financials (-.22) 5.514*** (8.358) Indusrials -.4 (-.1) 2.894** (2.362) Prop & Cons (-.12) *** (5.177) Resources -.25 (-.8) 1.716*** (5.975) Services (-.47) 4.3*** (5.98) Technology -.36 (-.2) 2.97 (1.16) Noe: Prop & Cons sands for propery and consrucion secor. The number in parenhesis is - saisic. *** and ** indicae significance a he 1 and 5 percen, respecively. The resuls in Table 3 show ha all coefficiens of he inercep are insignificanly negaive. The slope coefficiens of mos equiy secors are posiive and significan a he 1 percen level, excep for he coefficien of he indusrial secor ha is posiive and significan a he 5 percen level. The echnology secor is he only one secor ha exhibis insignifican posiive coefficien. For he overall marke, he slope coefficien is posiive and significan a he 1 percen level. Therefore, i can be argued ha here is a significan conemporaneous correlaion beween reurn and rading volume in he Thai sock marke. 3. Dynamic relaionship beween reurns, volailiy and rading volumes 3.1 Marke analysis Empirically, he error disribuion of sock reurns migh no exhibi a consan variance. Therefore, he GARCH model of Bollerslev (1986) ha encompasses heeroskedasiciy should be suiable. If he posiive conemporaneous relaionship beween rading volume and sock reurn exiss afer conrolling for nonlineariy of error disribuion, he GARCH (1,1) model can be esimaed. The model is expressed as: R c c, 1V N, h ), (3) ( 2 h 1 1h 1 1 D 5

7 where D is he US subprime crisis dummy variable. This dummy variable akes he value of 1 during he crisis and zero oherwise. 3 The crisis is assumed o impose he immediae impac on he Thai sock marke. Eq. (3) can deec he posiive relaionship beween reurn and rading volume along wih he reurn volailiy series. The GARCH (1,1) model expressed in Eq. (3) is firs esimaed for he sock marke and he resuls are repored in Table 4. Table 4 GARCH es of conemporaneous relaionship Variable Esimaed coefficien -saisic c -.34*** c 1.3*** α *** α 1.428*** β 1.27*** δ *** Q(2) = 4.5 (p-value =.132) Q 2 (2) = 4.67 (p-value =.131) LR saisic = Noe: *** indicaes significance a he 1 percen level. As repored in Table 3, he coefficien of regressing sock marke reurn on rading volume is posiive and significan a he 1 percen level. This resul confirms conemporaneous reurn-volume relaionship even hough he size of he esimaed coefficien is much smaller. The resul of GARCH model esimaion in Table 4 shows ha he LR saisic is very large in absolue value. The Ljung-Box saisics reveal ha here are no serial correlaion and furher ARCH effec up o 2 lags. The coefficiens of boh ARCH and GARCH erms are posiive and significan a he 1 percen level. The coefficien of he inercep is posiive and significan a he 1 percen level. Furhermore, he sum of boh coefficiens is.698, which is less han 1. This indicaes ha he reurn volailiy series is saionary. Therefore, he symmeric GARCH (1,1) model is an aracive represenaion of daily sock reurn behavior. 4 The coefficien of he US subprime crisis dummy variable is significanly posiive and very large, which implies ha he US subprime crisis imposes a posiive impac on sock reurn volailiy. The plo of he series of reurn volailiy is shown in Fig. 1. In Fig. 1, he volailiy is low before he crisis and significanly increased during he crisis. Afer he crisis, he volailiy is decreased, bu sill larger han he volailiy before he crisis. 3 According o Dooley and Huchison (29), he range of he crisis is from February 27, 27 o he end February The asymmeric GARCH model of Nelson (1991) is also esimaed, bu here is serial correlaion in he error erm of he mean equaion. 6

8 GARCH1 1, 8, 6, 4, 2, /1/24 28/3/25 24/8/25 18/1/26 19/6/26 13/11/ /11/28 24/4/29 22/9/29 18/2/21 27/7/21 17/12/21 25/5/211 13/1/ /5/213 3/1/213 24/3/214 2/8/214 22/1/215 23/6/215 13/11/215 Fig. 1 Sock marke reurn volailiy. The casual relaionships among reurn, volailiy and rading volume can be conduced using Granger causaliy es proposed by Granger (1969). Since all series are saionary, he es is conduced using he leas squares mehod ha includes he crisis dummy variable. In addiion, he VAR (p) model can be used o examine he relaionships among variables. The resuls of pairwise Granger causaliy es wih he US subprime crisis dummy variable are repored in Table 5. Table 5 Resuls of Granger causaliy es. Null hypohesis F-saisic Coefficien of dummy R V (.252) (.966) V R 3.669*** (.) (.52) V VOL 3.156*** (.3) (.) VOL V (.29) (.438) R VOL 3.574*** (.) (.) VOL R * (.312) (.78) Noe: VOL denoes reurn volailiy. ***, ** and * indicae significance a he 1, 5 and 1 percen, respecively. The null hypohesis is ha one variable does no cause anoher variable. The resuls in Table 5 show causaliy beween each pair of variables. The firs pairwise causaliy is ha sock marke reurn does no Granger causes rading volume, bu rading volume Granger causes sock marke reurn. This implies ha sock reurn does no precede rading volume, bu rading volume precedes sock marke reurn. 5 However, he US subprime crisis does no affec hese causal relaionships. For he pairwise causaliy beween rading volume and reurn volailiy, reurn volailiy does no Granger cause rading volume, bu rading volume causes reurn volailiy. The US subprime crisis srongly affec his pairwise causaliy in one direcion, i.e., causaliy ha runs from rading volume o reurn volailiy. For he pair of reurn and is volailiy, reurn volailiy does no cause 5 In spie of he exisence of conemporaneous relaionship beween rading volume and sock reurn, sock reurn does no cause rading volume in Granger causaliy sense. 7

9 reurn, bu reurn causes is own volailiy. The subprime crisis srongly srenghens he unidirecional causaliy running from reurn o reurn volailiy. I should be noed ha rading volume causes sock reurn a a 1 percen significance level. This resul is compaible wih he exisence of conemporaneous relaionship repored in Table 4. In addiion, rading volume also significanly causes reurn volailiy. Therefore, i can be argued ha rading volume helps predic boh reurn and reurn volailiy. In his sense, rading volume conains informaion abou reurn and has he abiliy o predic reurn volailiy a he same ime. The hird finding is ha reurn helps predic volailiy, bu volailiy does no help predic reurn. Using he VAR (p) model proposed by Sim (198), he relaionships among variables can be examined. The opimal lag lengh, p, can be deermined by informaion crierion. The VAR (8) is esimaed using AIC o deermine he order of lag lengh. The esimaion of he VAR (8) model allows for an analysis of impulse response funcions and variance decomposiions. The resuls of impulse response analysis are shown in Fig. 2. Response o Cholesky One S.D. Innovaions ± 2 S.E. Response of of R R o o R Response of R o V Response of R o VOL Response of V o R Response of V o V Response of V o VOL 3, 3, 3, 2, 2, 2, 1, 1, 1, -1, , , Response of VOL o R Response of VOL o V Response of VOL o VOL 6, 6, 6, 4, 4, 4, 2, 2, 2, -2, , , Fig. 2 Impulse response funcions Fig. 2 shows he impulse response funcions and he Mone Carlo simulaed a 95 percen inervals. The response of sock marke reurn (R) o a shock of rading volume (V) shows boh posiive and negaive impacs. Sock marke reurn begins o rise on he nex day following he conemporaneous effec of ha shock and lass for en days. The response of sock marke reurn o a shock of reurn volailiy is emporary because his response dissipaes quickly. The response of rading volume o a shock in reurn decreases wihin 6 days following he effec of ha shock. However, rading volume does no respond o a shock in sock reurn a all. For he response of volailiy o a shock in reurn, 8

10 he volailiy decreases he nex day afer he shock and increases he nex day and dissipaes wihin wo days. Finally, he response of rading volume o a shock in sock marke reurn dissipaes wihin six days. I can be concluded ha rading volume plays a more imporan role compared o oher variables. Variance decomposiions ha are used o ascerain how imporan he innovaions of oher variables are in explaining he fracion of each variable a differen sep-ahead-forecas variance. The resuls of variance decomposiions analysis are illusraed in Fig. 3 Variance Decomposiion ± 2 S.E. Percen R variance due o R Percen R variance due o V Percen R variance due o VOL Percen V variance due o R Percen V variance due o V Percen V variance due o VOL Percen VOL variance due o R Percen VOL variance due o V Percen VOL variance due o VOL Fig. 3 Variance decomposiions The dashed lines in Fig. 3 represen he Mone Carlo simulaed a he 95 percen confidence inervals. The resuls provide evidence for he independency of rading volume because is variance is mainly caused by is own innovaions. The impac of sock reurn on rading volume is small while he impac of reurn volailiy on rading volume is negligible. In addiion, sock reurn has no impac on reurn volailiy. Finally, reurn volailiy imposes no impac on rading volume. 3.2 Secor analysis The resuls in Table 3 show ha only one secor does no exhibi conemporaneous relaionship. However, he causal relaionship beween rading volume and secor reurn can be analyzed using he causaliy es. 6 The resuls are repored in Table 6. 6 The impac of he subprime crisis is also included in each es equaion. 9

11 Table 6 Resuls of Granger causaliy es for equiy secors. Secor R V V R Agro-indusry 5.973*** (.) 3.363*** (.1) Consumpion 6.623*** (.) (.159) Financials 2.182** (.26) 4.62*** (.) Indusrials 1.14 (.357) (.315) Prop & Cons 1.94* (.55) 4.889*** (.) Resources 2.56*** (.1) (.145) Services 3.74*** (.) 2.647*** (.7) Technology.797 (.65) (.26) Noe: ***, ** and * indicae significance a he 1, 5 and 1 percen, respecively. P-value is in parenhesis. There are only hree secors (consumpion, financials and resources) are affeced by he subprime crisis. Therefore, he subprime crisis does no affec he marke. The dynamic or causal relaionship beween volume and reurn are observed in mos secors. Bidirecional causaliy is found in hree secors (agro-indusry, financials, and services) while no causaliy is found in wo secors (indusrials and echnology. The overall resuls seem o suppor he resuls from he marke analysis. 3.3 Discussion Some poins are worh discussing. Firsly, here is conemporaneous relaionship beween rading volume and reurn in he Thai sock marke even hough one ou of eigh equiy secors does no exhibi his relaionship. The resuls of causaliy es indicae ha rading volume significanly causes sock reurn. This finding is conradicory o he resuls found by Lee and Rui (22) for some advanced sock markes and Pisedasalasai and Gunasekarage (27) for five emerging sock markes in Souheas Asia. This finding is also consisen wih some heoreical models ha here is informaion conen of rading volume for fuure reurns, e. g. he resul of bidirecional causaliy found by Chuang e al (29) and Lin (213). The second finding reveals ha here is a dynamic or causal causaion from rading volume o reurn volailiy is no compaible wih he resul found by Gebka (212), which shows only weak evidence of he role of rading volume on reurn. Specifically, rading volume helps predic boh reurn volailiy and sock marke reurn. Finally, he finding ha reurn negaively causes reurn volailiy is in line wih he find by Chrisie (1982) and Black (1976). 4. Concluding Remarks In his paper, empirical dynamic or causal relaionship beween rading volume, reurn and volailiy is invesigaed by using daily daa during 24 and 215. The resuls found in his paper are compaible wih some heoreical models ha asser ha rading volume play a dominan role, i.e., rading volume Granger causes sock marke reurn in he Thai sock marke. In addiion, he iner-linkages 1

12 among sock reurn, reurn volailiy, and rading volume are observed. Specifically, rading volume seems o conain informaion abou reurn and has he abiliy o predic reurn volailiy a he same ime. This sudy also akes ino accoun of he impac of he US subprime crisis on socks lised in he sock exchange of Thailand. The US subprime crisis srongly affec his pairwise causaliy in one direcion, i.e., causaliy ha runs from rading volume o reurn volailiy. For he pair of reurn and is volailiy, reurn volailiy does no cause reurn, bu reurn causes is own volailiy. The subprime crisis srongly srenghens he unidirecional causaliy running from reurn o reurn volailiy. The findings in his paper may give some insigh o how invesors will make rading decisions, which can affec porfolio adjusmen. References Black, F., Sudies in sock price volailiy changes, In Proceedings of he 1976 Business Meeing of he Business and Economic Secion, American Economic Associaion, Bollerslev, T., Generalized auoregressive condiional heeroskedasiciy, Economerica, 31(2), Bose, S., and Rahman, H., 215. Examining he relaionship beween sock reurn volailiy and rading volume: new evidence from an emerging economy, Applied Economics, 47(18), Brooks, C, Predicing sock index volailiy: can marke volume help?, Journal of Forecasing, 17(1), Carroll, R. and Kearney, C., 212. Do rading volumes explain he persisence of GARCH effecs?, Applied Financial Economics, 22(23), Chen, G., Firh, M. and Rui, O. M., 21. The dynamic relaionship beween sock reurns, rading volume and volailiy, Financial Review, 36(3), Chrisie, A., The sochasic behavior of common sock variances-value, leverage and ineres rae effecs, Journal of Financial Economics, 1(4), Chuang, C.-C., Kuan, C.-M., and Lin, H.-Y., 29. Causaliy in quaniles and dynamic sock reurnvolume relaions, Journal of Banking and Finance, 33(7), Copeland, T. E., A model of asse rading under he assumpion of sequenial informaion arrival, Journal of Finance, 31(4), Dooley, M. and Huchison, M., 29. Transmission of he U. S. subprime crisis o emerging markes: evidence on he decoupling-recoupling hypohesis, Journal of Inernaional Money and Finance, 28(8), Epps, T. W., and Epps, M. L., The sochasic dependence of securiy price changes and ransacion volumes: implicaions for he mixure-of-disribuion hypohesis, Economerica, 44(2), French, K. R., 198. Sock reurns and he weekend effec, Journal of Financial Economics, 8(1), Gallan, R., Rossi, P., and Tauchen, G., Sock prices and volume, Review of Financial Sudies, 5(2),

13 Gebka, B., 212. The dynamic relaion beween reurns, rading volume, and volailiy: lessons from spillover beween Asia and he Unied Saes, Bullein of Economic Research, 64(1), Granger, C. W. J., Invesigaing causal relaions by economeric models and cross-specral mehods, Economerica, 37(4), Hui, T-K., 25. Day-of-he-week effecs in US and Asia-Pacific sock markes during he Asian financial crisis: a non-parameric approach, Omega-The Inernaional Journal of Managemen Science, 33(3), Jennings, R., Sarks, L. and Fellingham, J., An equilibrium model of asse rading wih sequenial informaion arrival, Journal of Finance, 36(1), Karpoff, J. M., The relaions beween price changes and rading volume: a survey, Journal of Financial and Quaniaive Analysis, 22(1), Lee, B-S., and Rui, O. M., 22. The dynamic relaionship beween sock reurns and rading volume: domesic and cross-counry evidence, Journal of Banking and Finance, 26(1), Lin, H.-Y., 213. Dynamic sock reurn-volume relaion: evidence from emerging Asian markes, Bullein of Economic Research, 62(2), Moosa, I. A., and Al-Loughani, N. E., Tesing he price-volume relaion in emerging Asian sock markes, Journal of Asian Economics, 6(3), Nelson, D., Condiional heeroskedasiciy in asse reurns: a new approach, Economerica, 59(2), Ong, M. A., 215. An informaion heoreic analysis of sock reurns, volailiy and rading volumes, Applied Economics, 47(36), Pisedasalasai, A., and Gunasekarage, A., 27. Causal and dynamic relaionships among sock reurns, reurn volailiy and rading volume: evidence from emerging markes in Souh-Eas Asia, Asia-Pacific Financial Markes, 14(4), Saacioglu, K., and Sarks, L. T., The sock price-volume relaionship in emerging sock markes: he case of Lain America, Inernaional Journal of Forecasing, 14(2), Sim, C., 198. Macroeconomics and realiy, Economerica, 48(1), Wang, J., A model of compeiive sock rading volume, Journal of Poliical Economy, 12(1),