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

Similar documents
Market Liquidity and the Impacts of the Computerized Trading System: Evidence from the Stock Exchange of Thailand

Market Efficiency or Not? The Behaviour of China s Stock Prices in Response to the Announcement of Bonus Issues

Contrarian insider trading and earnings management around seasoned equity offerings; SEOs

Can Individual Investors Use Technical Trading Rules to Beat the Asian Markets?

Chapter 8: Regression with Lagged Explanatory Variables

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya.

Morningstar Investor Return

Duration and Convexity ( ) 20 = Bond B has a maturity of 5 years and also has a required rate of return of 10%. Its price is $613.

How To Calculate Price Elasiciy Per Capia Per Capi

Ownership structure, liquidity, and trade informativeness

The Behavior of China s Stock Prices in Response to the Proposal and Approval of Bonus Issues

BALANCE OF PAYMENTS. First quarter Balance of payments

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR

VALUE BASED FINANCIAL PERFORMANCE MEASURES: AN EVALUATION OF RELATIVE AND INCREMENTAL INFORMATION CONTENT

4. International Parity Conditions

Small and Large Trades Around Earnings Announcements: Does Trading Behavior Explain Post-Earnings-Announcement Drift?

Anticipating the future from the past: the valuation implication of mergers and acquisitions 1

Predicting Stock Market Index Trading Signals Using Neural Networks

Short selling and margin trading: Evidence from Chinese intra-day data

The Information Content of Implied Skewness and Kurtosis Changes Prior to Earnings Announcements for Stock and Option Returns

MSCI Index Calculation Methodology

Does the Market Detect Firms Real Earnings Management? Wei Li. Department of Accounting University of Melbourne

GUIDE GOVERNING SMI RISK CONTROL INDICES

Journal Of Business & Economics Research September 2005 Volume 3, Number 9

Measuring macroeconomic volatility Applications to export revenue data,

DNB W o r k i n g P a p e r. Stock market performance and pension fund investment policy: rebalancing, free f loat, or market timing?

I. Basic Concepts (Ch. 1-4)

A Note on Using the Svensson procedure to estimate the risk free rate in corporate valuation

An Empirical Study on Capital Structure and Financing Decision- Evidences from East Asian Tigers

SURVEYING THE RELATIONSHIP BETWEEN STOCK MARKET MAKER AND LIQUIDITY IN TEHRAN STOCK EXCHANGE COMPANIES

Supplementary Appendix for Depression Babies: Do Macroeconomic Experiences Affect Risk-Taking?

When Do TIPS Prices Adjust to Inflation Information?

WORKING CAPITAL ACCRUALS AND EARNINGS MANAGEMENT 1

Investor sentiment of lottery stock evidence from the Taiwan stock market

Journal of Financial and Strategic Decisions Volume 12 Number 1 Spring 1999

The Grantor Retained Annuity Trust (GRAT)

Journal Of Business & Economics Research Volume 1, Number 11

Day Trading Index Research - He Ingeria and Sock Marke

Impact of scripless trading on business practices of Sub-brokers.

Earnings Timeliness and Seasoned Equity Offering Announcement Effect

Hedging with Forwards and Futures

The Greek financial crisis: growing imbalances and sovereign spreads. Heather D. Gibson, Stephan G. Hall and George S. Tavlas

Relationships between Stock Prices and Accounting Information: A Review of the Residual Income and Ohlson Models. Scott Pirie* and Malcolm Smith**

Efficiency of the Mutual Fund Industry: an Examination of U.S. Domestic Equity Funds:

Do Investors Overreact or Underreact to Accruals? A Reexamination of the Accrual Anomaly

USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES

SPEC model selection algorithm for ARCH models: an options pricing evaluation framework

Does Stock Price Synchronicity Represent Firm-Specific Information? The International Evidence

Accruals and cash flows anomalies: evidence from the Indian stock market

CALCULATION OF OMX TALLINN

DO FUNDS FOLLOW POST-EARNINGS ANNOUNCEMENT DRIFT? RACT. Abstract

Monetary Policy & Real Estate Investment Trusts *

Premium Income of Indian Life Insurance Industry

Florida State University Libraries

expressed here and the approaches suggested are of the author and not necessarily of NSEIL.

An Empirical Comparison of Asset Pricing Models for the Tokyo Stock Exchange

Estimating Time-Varying Equity Risk Premium The Japanese Stock Market

Commission Costs, Illiquidity and Stock Returns

Nikkei Stock Average Volatility Index Real-time Version Index Guidebook

Does informed trading occur in the options market? Some revealing clues

Long-Run Stock Returns: Participating in the Real Economy

JEL classifications: Q43;E44 Keywords: Oil shocks, Stock market reaction.

How Useful are the Various Volatility Estimators for Improving GARCH-based Volatility Forecasts? Evidence from the Nasdaq-100 Stock Index

BALANCE OF PAYMENTS AND FINANCIAL MA REPORT All officiell statistik finns på: Statistikservice: tfn

International Business & Economics Research Journal March 2007 Volume 6, Number 3

LEASING VERSUSBUYING

Vector Autoregressions (VARs): Operational Perspectives

Chapter 6: Business Valuation (Income Approach)

Article The determinants of cash flows in Greek bond mutual funds. International Journal of Economic Sciences and Applied Research

Macroeconomic functions of the Russian stock market

Markit Excess Return Credit Indices Guide for price based indices

Does Option Trading Have a Pervasive Impact on Underlying Stock Prices? *

PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE

Option Put-Call Parity Relations When the Underlying Security Pays Dividends

Chapter 1.6 Financial Management

Description of the CBOE S&P 500 BuyWrite Index (BXM SM )

The Real Business Cycle paradigm. The RBC model emphasizes supply (technology) disturbances as the main source of

Price Formation and Liquidity Provision in Short-Term Fixed Income Markets 1

Does Option Trading Have a Pervasive Impact on Underlying Stock Prices? *

The Transmission of Pricing Information of Dually-Listed Stocks

Evidence from the Stock Market

THE IMPACT OF CUBES ON THE MARKET QUALITY OF NASDAQ 100 INDEX FUTURES

Market Misvaluation and Merger Activity: Evidence from Managerial Insider Trading

On Overnight Return Premiums of International Stock Markets

How Does the Corporate Bond Market Value Capital Investments and Accruals?

Option Trading Costs Are Lower Than You Think

ABSTRACT: Key words: real options; corporate valuation; abnormal returns, case study; capital budgeting. JEL: G31

Default Risk in Equity Returns

Migration, Spillovers, and Trade Diversion: The Impact of Internationalization on Domestic Stock Market Activity

The information content of directors trades: empirical analysis of the Australian market

ANOMALIES IN INDIAN STOCK MARKET AN EMPIRICAL EVIDENCE FROM SEASONALITY EFFECT ON BSEIT INDEX

11/6/2013. Chapter 14: Dynamic AD-AS. Introduction. Introduction. Keeping track of time. The model s elements

Measuring the Downside Risk of the Exchange-Traded Funds: Do the Volatility Estimators Matter?

The impact of short selling on the volatility and liquidity of stock markets: evidence from Hong Kong market

Performance Center Overview. Performance Center Overview 1

He equiy Risk Premium And The Supply Side Model

Copyright Undertaking

Methodology brief Introducing the J.P. Morgan Emerging Markets Bond Index Global (EMBI Global)

How Fast Do Tokyo and New York Stock Exchanges. Respond to Each Other?: An Analysis with. High-Frequency Data

THE INTERPLAY BETWEEN DIRECTOR COMPENSATION AND CEO COMPENSATION

Transcription:

AN EMPIRICAL TEST OF INDIAN STOCK MARKET EFFICIENCY IN RESPECT OF BONUS ANNOUNCEMENT M. Raja 1 Bharahidasan Universiy College (Lalgudi), India. E-mail: rajacommerce@yahoo.co.in J. Clemen Sudhahar 2 Karunya Universiy, India. E-mail: 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

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

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 (2000-2007). 3

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://www.bseindia.com/), 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 1 1 100 4

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

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

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, -7-4 -2, 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 1.23. 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 1.11. I is ineresing o noe ha he value of ASRV exceeded one he day afer he announcemen day (day +1) wih a value of 1.23. 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

(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 -15 1.53 1.27 @ -5 0.96-0.09 5 1.17 1.21-14 1.37 1.32 @ -4 1.33 1.41 @ 6 0.53-0.57-13 1.01 0.04-3 0.95-0.09 7 0.40-0.69-12 0.77-1.01-2 1.48 1.42 @ 8 0.59-0.46-11 0.94-0.19-1 1.11 1.08 9 0.49-0.55-10 1.14 0.48 0 2.01 1.48 @ 10 0.58-0.43-9 1.06 0.16 1 1.23 1.35 @ 11 0.53-0.46-8 0.83-0.46 2 0.99-0.01 12 0.77-0.22-7 1.29 1.43 @ 3 0.81-0.27 13 0.47-0.49-6 1.75 1.72 ** 4 1.17 1.23 @ 14 1.38 1.30 @ *-1% **-5%@-10% 15 1.44 1.37 @ Source: Compued from PROWESS daa base 8

Figure 1. Average Securiy Reurn Variabiliy of Bonus Issue Announcemen 2.50 2.00 ASRV 1.50 1.00 0.50 0.00-15-14-13-12-11-10-9 -8-7 -6-5 -4-3 -2-1 0 1 2 3 4 5 6 7 8 9 10 1112 13 14 15 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 +15 1.04 FROM DAY -15 TO DAY -1 1.17 FROM DAY 0 TO DAY +15 0.91 FORM DAY -3 TO DAY +3 1.22 FROM DAY -7 TO DAY +7 1.14 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 -15 0.21 0.31-5 1.43 1.35@ 5 0.56 0.37-14 1.33 1.15-4 1.88 1.71** 6 0.22 0.11-13 0.52 0.49-3 1.57 1.54@ 7 1.05 1.02-12 0.20 0.10-2 3.66 2.35* 8 1.91 1.61@ -11 1.29 1.10-1 2.58 2.14** 9 2.30 2.12** -10 0.43 0.40 0 2.06 1.93** 10 1.94 1.85** -9 0.96 0.73 1 0.45 0.52 11 2.33 2.19** -8 0.41 0.38 2 2.25 2.02** 12 2.12 2.08** -7 1.28 1.20 3 0.28 0.16 13 0.58 0.50-6 0.31 0.25 4 2.20 2.03** 14 0.42 0.37 *-1% **-5% @-10% 15 2.41 2.36* Source: Compued from PROWESS a corporae daabase 9

Figure 2. Average Abnormal Reurn of Bonus Announcemen 4 Average Abnormal Reurn of Bonus Announcemen 3.5 3 2.5 ARR 2 1.5 1 0.5 0-15 -14-13 -12-11 -10-9 -8-7 -6-5 -4-3 -2-1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 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 +15 1.33 FROM DAY -15 TO DAY +15 FROM DAY -15 TO DAY -1 1.20 FROM DAY -15 TO DAY -1 FROM DAY 0 TO DAY +15 1.44 FROM DAY 0 TO DAY +15 FORM DAY -3 TO DAY +3 1.84 FORM DAY -3 TO DAY +3 FROM DAY -7 TO DAY +7 1.45 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 -2.11 o 12.4. On he day of announcemen (day 0), he CAAR for bonus announcemen was 14.46 and i increased o 17.16 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

Table 5. Cumulaive Average Abnormal Reurns for Bonus Announcemen Day CAAR Day CAAR Day CAAR -15-0.21-5 2.71 5 15.24-14 -1.54-4 4.59 6 15.46-13 -1.02-3 6.16 7 14.41-12 -0.82-2 9.82 8 12.5-11 -2.11-1 12.4 9 10.2-10 -1.68 0 14.46 10 8.26-9 -0.72 1 14.91 11 5.93-8 -0.31 2 17.16 12 3.81-7 0.97 3 16.88 13 4.39-6 1.28 4 14.68 14 4.81 Source: Compued from PROWESS a corporae daabase 15 2.4 Figure 3. Cumulaive Average Abnormal Reurn of Bonus Announcemen Cumulaive Average Abnormal Reurn of Bonus Announcemen 25.00 20.00 15.00 CAAR 10.00 5.00 0.00-15 -14-13 -12-11 -10-9 -8-7 -6-5 -4-3 -2-1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 (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 +15 6.61 FROM DAY -15 TO DAY -1 1.97 FROM DAY 0 TO DAY +15 10.97 FORM DAY -3 TO DAY +3 13.11 FROM DAY -7 TO DAY +7 10.74 Source: Compued for Table 5 11

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. 67-92. [2] George E. Pinches (1970), The Random Walk Hypohesis and Technical Analysis, Financial Analyss Journal, March-April, 104-110. [3] Edward M. Millar (1979), A Simple Couner Example o he Random Walk Theory, Financial Analyss Journal, June-Augus, 55-67. [4] Obaidullah, M (1990), Sock Prices Adjusmen o Half-Yearly Earnings Announcemens A Tes of Marke Efficiency, Charered Accounan, Vol. 38, pp. 922-924. [5] Eugene F. Fama (1995), Random Walks in Sock Marke Prices, Financial Analyss journal, January - February, 75-80. [6] Elroy Dimson and Massoud Mussavian (1998), A brief hisory of marke efficiency, European Financial Managemen, Volume 4, March, 91-103. [7] Srinivasan. R (1997), Securiy Prices Behaviour Associaed wih Righ Issue Relaed Evens, The ICFAI journal of Applied Finance, 3, pp.50-62. [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.26-40. [9] Ajay Pandey (2001), Take Over Announcemens, Open Offers, and Shareholders Reurn in Targe Firms, Vikalpa, 26,.3, 2001. [10] Bachelier, Louis (1900) Trans. James Boness, Theory of Speculaion, in Cooner, 17-78. [11] Ball, Ray and Philip Brown (1968), An Empirical Evaluaion of Accouning Income Numbers, Journal of Accouning Research, 160. 12

[12] Beaver, W. H. (1968), The Informaion conen of Annual earnings announcemens, Journal of Accouning Research, Supplemen, 6, 67-97. [13] Dillip Kumar Sen, Sugan C. J ain, Swapan Kumar Bala (2002), The Impac of Dividends and Reained Earnings on he Marke Prices of Shares: A Sudy of Seleced Enerprises of he Pharmaceuical Indusry in India, The Journal of Accouning & Finance, 16, 43-49. 14] Dua, Abhiji (2001), Invesors Reacion o he Good and Bad News in Secondary Marke: A sudy relaing o invesors behaviour, Finance India, 567-576. [15] Elroy Dimson and Massoud Mussavian (1998), A brief hisory of marke efficiency, European Financial Managemen, 4, 91-103. [16] Fischer Black (1971), Implicaions of he Random Walk Hypohesis for Porfolio Managemen, Financial Analyss Journal, March April, 16-22. [17] John C. Handley (1995), The Pricing of Underwriing Risk in Relaion o Ausralian Righs Issues, Ausralian Journal of Managemen, 1, 43-75. [18] Jeffrey E. Jarre and Eric Kyper (2006), Capial Marke Efficiency and he Predicabiliy of Daily Reurn, Applied Economics, 38, 631-636 [19] Julie, Walf, (2001), Trumps for Mergers & Acquisiion CEOs Serve Themselves Firs in Mergers of Equals, Effecive Execuive, 3(10), 24-26. [20] Kakai, M (2001), price performance of Bonus issue, Finance India, XV, 1183-1190. [21] Kahleen M. Kahle (2002), When a buyback is no a buyback: Open marke repurchases and employee opions, Journal of Financial Economics, 15, 1, 112-127. [22] Keane. S. M (1983), Sock Marke Efficiency Theory, Evidence, Implicaions. Philip Allan Publishers Ld., Oxford. [23] Lukose Jijo. P. J and Narayanan Rao. S. (2002), Marke reacion o sock splis- An Empirical Sudy, The ICFAI Journal of Applied Finance, 8, 2, 26-40. [24] Michael. C. Jensen (1978), Some Anomalous Evidence Regarding Marke Efficiency, Journal of Financial Economics, 6, 2/3, 95-101. [25] Michad, Hi A, S Harrison Jeffrey and R Ireland Duane (2001), Mergers and Acquisiion, Oxford Universiy Press, Inc, New York 13

[26] Mishra A. K (2005), An Empirical Analysis of Marke Reacion around he Bonus Issues in India, The ICFAI Journal of Applied Financial, 11, 7, 21-39. [27] Mishra A. K (2005), An Empirical Analysis of Share Buybacks in India, The ICFAI journal of Applied Finance, 11,.4, 7-24. [28] Nickolaos V. Tsangarakis (1996), Equiy righs issues: Signaling vs. issue price irrelevance hypohesis, European Financial Managemen.2, 3, 299-310. [29] Peer Walon (2000), Financial Saemen Analysis, Business Press, Thomson Learning, Publishing Company Ld, New Delhi. [30] Parrick Dennis (2003), Sock Splis and Liquidiy: The case of he Nasdaq-100 Index Tracking Sock,.38,.1, 415-433. [31] Samson Ekanayaka (2004), Informaion Signalling of Share Buy-back Announcemen Recen Ausralia Evidence, School of Accouning, Economics and Finance, Deaking Universiy, Vicoria, School working papers- Series 2004, SWP 2004/16. [32] Srinivasan, R. (1997), Securiy Prices Behavior Associaed wih Righ-Issue relaed Evens, The ICFAI Journal of Applied Finance, 3, 3, 71-81. [33] Tirumalvalavan, P. and Suniha. K., 2006, Share Price Behaviour around buy backs in India, Journal of Managemen Research, 1, 4, 27-37. WEBSITES 1. www.sebi.gov.in 2. www.googlefinance.com 3. www.bseindia.com 4. www.indiainfoline.com 5. www.ssrn.org 6. www.cmie.org 7. www.invesopedia.com 14