AN EMPIRICAL TEST OF INDIAN STOCK MARKET EFFICIENCY IN RESPECT OF BONUS ANNOUNCEMENT

Transcription

1 AN EMPIRICAL TEST OF INDIAN STOCK MARKET EFFICIENCY IN RESPECT OF BONUS ANNOUNCEMENT M. Raja 1 Bharahidasan Universiy College (Lalgudi), India. rajacommerce@yahoo.co.in J. Clemen Sudhahar 2 Karunya Universiy, India. Clemen@karunya.edu I. ABSTRACT A capial marke is said o be efficien wih respec o an informaion iem if he prices of securiies fully impound he reurn implicaions of ha iem. The efficiency wih which he capial formaion is carried ou depends on he efficiency of he capial markes and financial insiuions. A capial marke is said o be efficien wih respec o corporae even announcemen (sock spli, buyback, righ issue, bonus announcemen, merger & acquisiion, dividend ec) conained informaion and is disseminaions. How quickly and correcly he securiy prices reflec hese even conained informaion show he efficiency of sock markes. Presen sudy is an aemp o es he efficiency of Indian sock marke wih respec o bonus issue announcemen by IT companies. Key words: Marke Reacion/Sock Price Reacion, Abnormal Reurns, Announcemen Period, Efficien Marke, bonus announcemen. JEL codes: G14, G15 II. INTRODUCTION The economic developmen of any counry depends upon he exisence of a well organized financial sysem. An efficien funcioning of he financial sysem faciliaes he free flow of funds o more producive aciviies and hus promoes invesmen. The financial sysem may be viewed as a mulisoried srucure consising mainly of financial insiuions and financial markes. Indian capial markes have undergone ransformaion raher dramaically in he las decade. The number and variey of 1 Dr. M. Raja, M. Com., M. Phil., Ph.D., Assis. Professor, Bharahidasan Universiy College (Lalgudi), Tiruchirapalli, India. 2 Dr. J. Clemen Sudhahar, MBA., M. Phil., Ph.D., Associae Professor, Head-Markeing Area, School of Managemen, Karunya Universiy, Coimbaore-114, India. 1

2 players have increased. The growh in he foreign insiuional invesors, muual funds and he privaizaion of insurance secor, have faciliaed he inducion of more insiuional players in he markes. Furher, i is ineresing o sae ha focus on higher level of accounabiliy, informaion disclosure, corporae governance and shareholder value has also gone up on par wih world sandards. A capial marke is said o be efficien wih respec o an informaion iem if he prices of securiies fully impound he reurns implicaions of ha iem. In an efficien marke, when a new informaion iem is added o he marke, is revaluaion implicaions for securiy reurns are insananeously and unbiasedly impounded in he curren marke price. Several sudies have empirically esed he reacion of securiy prices o he release of differen informaion. Eugene Fama (1960) classifies he marke efficiency ino he following hree caegories depending on he informaion se ha is fully refleced in he securiy prices. a. Weak Form of efficiency, popularly known as Random Walk Theory, is he caegory in which he curren sock prices reflec all he informaion ha is conained in he hisorical sequence of prices. b. Semi Srong Form of efficiency is he caegory in which curren marke prices no only reflec all informaion conen of hisorical prices bu also reflec all he informaion, which are publicly available abou he companies being sudied. c. Srong Form of efficiency, is he caegory in which curren marke prices reflec all informaion wheher i is publicly available or privae informaion (insiders informaion). III. LITERATURE SURVEY Beaver (1968) examined he reacion of he Trading Volume Aciviy (TVA) and Securiy Reurns Variabiliy (SRV) o annual earnings announcemen wih a sample of 143 New York Sock Exchange (NYSE) firms. The resul indicaed 33 percenage increases in TVA and 61 percen increase in SRV in earnings announcemen week over he non-announcemen weeks. A sudy by George E. Pinches (1970) found ha he random walk hypohesis implies ha he price movemens are virually independen of pas price movemen. The sudy reveals ha he random walk hypohesis may be incorrec or, a leas incomplee. McEnally (1971) and Beaver, Clarke and Wrigh (1979) repor significan conemporaneous correlaions beween he magniude and sign of unexpeced annual earnings changes and he magniude and sign of abnormal reurns in he period preceding he annual earnings release. Edward M. Miller (1979) in his sudy argues ha any non-random flucuaion in price (oher han a seady upward drif approximaing he risk adjused rae of reurns) would be exploied by speculaors who would buy before an expeced fall, eliminaing any predicable funcions and making all price changes random. Obaidullah (1990) sudied 33 securiies which performed well. The auhor has repored ha earnings showed an increasing rend much before he announcemen week. The sudy eniled Random Walks in Sock 2

3 Marke Prices by Eugene F. Fama (1995) found ha random walks in sock marke prices presen imporan challenges o boh he charis and proponen of fundamenal analysis. Elroy Dimson and Massoud Mussavian (1998), in heir sudy narraed ha he efficien markes hypohesis is simple in principle bu remains elusive. I is hard o profi from even he mos exreme violaions of marke efficiency. Abhiji Dua (2001) has examined he invesors reacion o informaion using primary daa colleced from 600 individual invesors and observes ha he individual invesors are less reacive o bad news as hey inves for longer period. Hari Om Chaurvedi (2000), in his docoral hesis, observed ha he cumulaive abnormal reurns (CAR) beween he porfolios wih posiive and negaive unexpeced half-yearly earnings were significan. Prabina Das, S. Srinivasan and A. K. Dua (2000) have sudied he reacion of GDR prices and he underlying share prices o he announcemen of dividends and found ha he CAR for he GDR is mosly negaive irrespecive of he rae of dividend whereas he domesic share prices reac in a more synchronous manner. An aemp was made by Kun Shin Im, Kevin E. Dow and Varun Grover (2001) in heir sudy, examined he changes in he marke value of he firm as refleced in he sock price in response o IT invesmen announcemens. Reacions of price and volume were negaively relaed o firm size and became more posiive over ime. Jijo Lukose and Narayan Rao (2002) examined he securiy price behaviour around he announcemen of sock splis and around ex-spli dae. They find ha here are 7.69 percen abnormal reurns during he wo days (i.e. he day of announcemen of sock spli and he nex day). IV. RESEARCHMTHODOLOGY A. Saemen of he Problem Capial marke, being a vial insiuion, faciliaes economic developmen. I is rue ha so many paries are ineresed in knowing he efficiency of he capial marke. The small and medium invesors can be moivaed o save and inves in he capial marke only if heir securiies in he marke are appropriaely priced. The informaion conen of evens and is disseminaion deermine he efficiency of he capial marke. Tha is how quickly and correcly securiy prices reflec hese informaion show he efficiency of he capial marke. In he developed counries, many research sudies have been conduced o es he efficiency of he capial marke wih respec o informaion conen of evens. Whereas in India, very few sudies have been conduced o es he efficiency of he capial marke wih respec o sock spli announcemens, even afer hese sudies have been conduced wih differen indusries wih differen period. Hence presen sudy is an aemp o es he efficiency of he Indian sock marke wih respec o informaion conen of bonus issue announcemens by IT (Informaion Technology) companies for paricular period ( ). 3

4 B. Objecives of he sudy 1) To examine he informaion conen of bonus issue announcemen made by he Informaion Technology (IT) companies 2) To es he speed wih which he bonus issue announcemen conained informaion impounded in he share prices of IT companies. 3) To sugges invesmen sraegies for he invesors, fund managers and analyss. C. Hypoheses of he sudy 1) Bonus issue announcemen conained informaion s are no relevan for he valuaion of socks. 2) Bonus issue announcemen has no significanly influence in he sock prices of IT companies. 3) The Indian sock marke is informaionally no efficien where he Bonus issue announcemen conained informaion s are no impounded insananeously and righly in he sock prices of IT companies D. Sample Selecion The sudy inends o cover he all he IT companies lised in Bombay Sock Exchange (BSE). Ou of all he companies brough under Informaion Technology lised in he BSE as on 30 December 2007 (as per he PROWESS daabase), only 43 companies, which saisfy he following crieria were seleced. i. The companies, which find a place in he lis A and B1 of he Bombay Sock Exchange (BSE), are seleced. The reason for selecing he lis A and B1 is o ensure acive rading, ii. Availabiliy of he daes of announcemen of bonus issue, and iii. Availabiliy of Bonus issue announcemen informaion The informaion regarding adjused share price, bonus issue informaion, daes of bonus issue announcemens, and values of BSE 500 were obained from PROWESS published by CMIE. Oher relevan informaion is obained from he BSE websie (hp:// books, and journals. E. Tools used for he Analysis: i. Daily reurns The daily reurns were calculaed for boh individual securiies as well as Marke Index using he following equaion R i, Where, P P P... (1.0) Ri, = Reurns on Securiy i on ime. = Price of he securiy a ime P

5 P-1 = Price of he securiy a ime -1 ii. Securiy Reurns Variabiliy SRV model is used o know he reacion of he marke. Symbolically, he model is SRV Where, i, 2 AR.. (1.1) i, V ( AR) SRVi, = Securiy Reurns Variabiliy of securiy i in ime AR 2 i, = Abnormal reurns on securiy i on day V (AR) = Variance of Abnormal Reurns during he announcemen period Abnormal Reurns (AR) under marke-adjused abnormal reurns is calculaed using by he equaion as below; AR..... (1.2) i, Ri, Rm, Where, ARi, = Abnormal reurns on securiy i a ime Ri, = Acual reurns on securiy I a ime Ri,m = Acual reurns on marke index, which is proxied by BSE 500, a weighed average index of 500 companies published by BSE, a ime. Thus daily acual reurns over he announcemen period (31days) were adjused agains heir corresponding marke reurns. iii. Average Securiy Reurns Variabiliy (ASRV) The SRVi, so calculaed for he enire bonus issue announcemen are averaged o find he Average Securiy Reurns Variabiliy (ASRV) by using he following equaion.... (1.3) ASRV Where, ASRV = Average Securiy Reurns Variabiliy a ime SRVi, = Securiy Reurns Variabiliy i securiy a ime n = Number of Bonus issue in he sample iv. Average Abnormal Reurns: The Average Abnormal Reurns is calculaed by he equaion given below Where, SRV, (1/ n) i AAR 1 n AR i, n 1. (1.5) AAR = Average Abnormal Reurns on day 5

6 ARi, = Abnormal Reurns on securiy i a ime which is calculaed by using he equaion (1.2) v. Cumulaive Abnormal Reurns (CAR) The CAR is calculaed a CAAR k AAR 1 Where, k.. (1.7) CAARk=Cumulaive Average Abnormal Reurns for he k h period. AAR = Average Abnormal Reurns of sample bonus issue a ime which is calculaed by using he equaion (1.5) T-Tes i). The significance of reacion in securiy prices (ASRV) is esed by using he T- saisics as follows: sa ( ASRV 1) n / s.. (1.4) Where, n is he number of bonus issue in he sample and s is he Sandard Deviaion of abnormal reurns. ii). The significance of he AAR is esed using he -es as follows; AAR n sa /... (1.6) s Where, AAR is he Average Abnormal Reurns on ime, n is he number of bonus issue in sample and s is he Sandard Deviaion of Average Abnormal Reurns. Limiaions of he Sudy 1) The presen sudy is confined o only one even announcemen 2) This sudy is resriced wih only IT indusry 3) All he limiaions of he ools used are applicable o his sudy V. RESULTS AND DISCUSSION The analysis has been done in he following way o empirically es he informaional efficiency of he Indian capial marke wih special reference o he shares of seleced IT Companies. a. Analysis of Average Securiy Reurns Variabiliy (ASRV) 6

7 b. Analysis of Abnormal Reurns (AAR) c. Analysis of Cumulaive Abnormal Reurns (CAR) A. Securiy Reurn Variabiliy One of he major objecives of his sudy is o examine he informaion conen of corporae evens announced by sample IT (Informaion Technology) companies. If corporae evens conain informaion relevan for he valuaion of securiies, he sock marke may use ha informaion o revise he prices of securiies. According o he semi-srong form of efficien marke hypohesis, he marke is said o be efficien if prices reflec all he publicly available informaion insananeously and unabashedly. One of he imporan mehods used o examine he relevance of evens announcemen informaion o valuing he securiy prices is Securiy Reurn Variabiliy (SRV). The variabiliy of securiy reurns during he announcemen period (15 days before he announcemen, he day of announcemen, and 15 days following he announcemen) were calculaed using he equaion 1.1. Analysis of ASRV for Bonus Issue The resuls of ASRV and value for bonus issue announcemen are given in Table 1. I is clearly undersood from he above analysis ha IT socks capured he bonus announcemen conained informaion on day 1, 4, 5, 14 and 15. The values of ASRV during hese days were 1.23, 1.17, 1.17, 1.38 and 1.44 respecively. The ASRV was significan a 10 percen level on day -15, -14, , 0, 1, 4, 14 and day 15. Furher, i was significan a 5 percen level only on day -6. The highes value of ASRV during he 31 days of announcemen was recorded on day -6 wih a value of 1.75, followed by day -15, -2, 15, 14 and 1 wih ASRV value of 1.53, 1.48, 1.44, 1.38 and Furher, he value of ASRV gained greaer han one consisenly during pre announcemen period for five days (day -7 o day -1), excep day -5 and -3, wih ASRV value of 1.29, 1.75, 1.33, 1.48, and I is ineresing o noe ha he value of ASRV exceeded one he day afer he announcemen day (day +1) wih a value of Therefore, i is presumed ha he marke capured he bonus announcemen conained informaion immediaely afer is announcemen. I is inferred ha he bonus announcemen conained informaion relevan for valuaion IT companies securiies. From he above analysis, invesors are advised ha when he company comes up wih he bonus issue, he invesor should ake immediae invesmen decision (buy or sell) in order o benefi from he bonus issue announcemen. The resuls of ASRV for bonus announcemen are presened in Figure 1. The figure clearly shows ha he marke posiively absorbed he bonus issue conained informaion during he pre announcemen period. The analysis of average value of ASRV for bonus announcemen is given in he Table 2. The foregoing discussion reflecs he following: (i) Bonus issue announcemen by IT companies conain informaion s are useful for valuing he securiies. 7

8 (ii) Capial marke for IT companies socks reaced heavily only on he day of he bonus announcemen (day 0) and also on he nex day of he announcemen (day 1). (iii) However, he reacion on day 0 is much greaer han on day 1. B. Average Abnormal Reurn Securiy Reurns Variabiliy (SRV) model was used o find ou wheher bonus issue announcemen informaion is useful or no for valuing securiy prices of sample IT companies. Table 3 shows he analysis of abnormal reurns for bonus announcemen of IT companies. Figure 2 depics he fac ha he marke gained significan reacions in he securiy prices during he pre and pos announcemen periods. The resul of average AAR for bonus announcemen is given in Table 4. The following are he oucome of he discussion presened in he able. (i) IT companies posiively received he bonus announcemen informaion before he announcemen came up and from day -5 o day -1, he securiy prices significanly reaced. (ii) The bonus announcemen conained informaion made by he sample IT companies are useful for valuing he securiies (iii) For bonus announcemen he marke was reac quickly during pos announcemen period (iv) The reacion was exended o up o +15 days for bonus announcemen by IT companies (v) Informaion of Bonus announcemen can be used by he invesors for making abnormal reurns a any poin of he announcemen period, hrough he sraegy of shor selling. Table 1. Resul of ASRV and Value for Bonus Announcemen Day ASRV value Day ASRV value Day ASRV value ** *-1% **-5%@-10% Source: Compued from PROWESS daa base 8

9 Figure 1. Average Securiy Reurn Variabiliy of Bonus Issue Announcemen ASRV Day relaive o he day of he Announcemen ASRV Table 2. Average Value of ASRV for Bonus Announcemen PERIOD ASRV FROM DAY -15 TO DAY FROM DAY -15 TO DAY FROM DAY 0 TO DAY FORM DAY -3 TO DAY FROM DAY -7 TO DAY Source: Compued from Table1 Table 3. Average Abnormal Reurn and -value for Bonus Announcemen Day AAR T value Day AAR T value Day AAR T value @ ** @ * @ ** ** ** ** ** ** ** ** *-1% * Source: Compued from PROWESS a corporae daabase 9

10 Figure 2. Average Abnormal Reurn of Bonus Announcemen 4 Average Abnormal Reurn of Bonus Announcemen ARR Day he day of announcemen ARR Table 4. Average Value of Average Abnormal Reurns for Bonus Announcemen PERIOD AAR PERIOD FROM DAY -15 TO DAY FROM DAY -15 TO DAY +15 FROM DAY -15 TO DAY FROM DAY -15 TO DAY -1 FROM DAY 0 TO DAY FROM DAY 0 TO DAY +15 FORM DAY -3 TO DAY FORM DAY -3 TO DAY +3 FROM DAY -7 TO DAY FROM DAY -7 TO DAY +7 Source: Compued from Table-3 C. Analysis of Cumulaive Average Abnormal Reurn for Bonus Announcemen The resul of cumulaive average abnormal reurns (CAAR) for bonus announcemen is exhibied in he Table 5. The value of cumulaive average abnormal reurns during he pre announcemen period ranged from o On he day of announcemen (day 0), he CAAR for bonus announcemen was and i increased o on day 2. This shows ha marke immediaely reaced o he bonus announcemen conained informaion. The resuls of CAAR for bonus announcemen are graphically represened in he Figure-3 and he average values of CAAR in respec of bonus issue are depiced in Table 6. 10

11 Table 5. Cumulaive Average Abnormal Reurns for Bonus Announcemen Day CAAR Day CAAR Day CAAR Source: Compued from PROWESS a corporae daabase Figure 3. Cumulaive Average Abnormal Reurn of Bonus Announcemen Cumulaive Average Abnormal Reurn of Bonus Announcemen CAAR (5.00) Day relaive o he day of Annoucemne CAAR Table 6 Average Value of Cumulaive Average Abnormal Reurns for Bonus Announcemen PERIOD AAR FROM DAY -15 TO DAY FROM DAY -15 TO DAY FROM DAY 0 TO DAY FORM DAY -3 TO DAY FROM DAY -7 TO DAY Source: Compued for Table 5 11

12 VI. CONCLUSION This sudy has empirically examined he informaional efficiency of capial marke wih regard o bonus issue announcemen released by he IT companies. The resuls of he sudy showed ha he securiy prices reaced o he announcemen of bonus issue. Thus one can safely conclude from he foregoing discussions ha he Indian capial marke for he IT secor, in general, are efficien, bu no perfecly efficien, o he announcemen of bonus issue. This informaional inefficiency can be used by he invesors for making abnormal reurns a any poin of he announcemen period. REFERENCES [1] Beaver, W. H. (1968), The Informaion Conen of Annual Earnings Announcemens, Journal of Accouning Research, Supplemen, Vol. 6, pp [2] George E. Pinches (1970), The Random Walk Hypohesis and Technical Analysis, Financial Analyss Journal, March-April, [3] Edward M. Millar (1979), A Simple Couner Example o he Random Walk Theory, Financial Analyss Journal, June-Augus, [4] Obaidullah, M (1990), Sock Prices Adjusmen o Half-Yearly Earnings Announcemens A Tes of Marke Efficiency, Charered Accounan, Vol. 38, pp [5] Eugene F. Fama (1995), Random Walks in Sock Marke Prices, Financial Analyss journal, January - February, [6] Elroy Dimson and Massoud Mussavian (1998), A brief hisory of marke efficiency, European Financial Managemen, Volume 4, March, [7] Srinivasan. R (1997), Securiy Prices Behaviour Associaed wih Righ Issue Relaed Evens, The ICFAI journal of Applied Finance, 3, pp [8] Lukose, Jijo P. J., and S. Narayan Rao (2002), Marke Reacion o Sock Splis- An Empirical Sudy, The ICFAI Journal of Applied Finance, Vol.8, No.2, pp [9] Ajay Pandey (2001), Take Over Announcemens, Open Offers, and Shareholders Reurn in Targe Firms, Vikalpa, 26,.3, [10] Bachelier, Louis (1900) Trans. James Boness, Theory of Speculaion, in Cooner, [11] Ball, Ray and Philip Brown (1968), An Empirical Evaluaion of Accouning Income Numbers, Journal of Accouning Research,

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