SHARE MARKET BONUS ISSUES AND STOCK SPLITS IN INDIAN

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International Journal of Management (IJM) Volume 11, Issue 05, 2020, pp. 1612-1630. Article ID: IJM_11_05_152 MayAvailable online at http://iaeme.com/Home/issue/IJM?Volume=11&Issue=5 Journal Impact Factor (2020): 10.1471 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 DOI: 10.34218/IJM.11.5.2020.152

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AN EMPIRICAL STUDY ON EXPECTED RETURN MODELS WITH REFERENCE TO

BONUS ISSUES AND STOCK SPLITS IN INDIAN SHARE MARKET

Nagendra Marisetty Assistant Professor, Siva Sivani Institute of Management, Secunderabad, Telangana, India

Dr. M. Suresh Babu Professor, Sri Venkateswara University, Tirupathi, Andhra Pradesh, India

Dr. S. V. Ramana Rao Director, Siva Sivani Institute of Management, Secunderabad, Telangana, India

ABSTRACT This article will evaluate the Expected Return Models (ERM) in event study

methodology in the Indian share market. Three main return models, namely, Market Model (MM), Market-Adjusted Model (MAAM), and Mean-Adjusted Model (MEAM) use with an intension to know the any variations in Average Abnormal Return (AAR) and Cumulative Average Abnormal Return (CAAR) on event day of the bonus issues and stock split actions. Total 240 bonus issues and 200 stock Samples are selected from S&P

BSE 500 stocks from 2000 to 2019. Sixty – one day’s events window and 252 days estimation window used to calculate the events' returns. Samples are classified into four parts like pure event, periodic, capitalization, and ratio wise to know any changes in the event's abnormal returns. Market Adjusted Model has a slight advantage over other models due to its slightly inflated abnormal returns other than that all models provide the almost same results. Bonus issue events abnormal returns on event day similar in all models, but returns are not the same in all classifications; it means that bonus issue impact on stocks changes based on different classifications. Stock Split issue events abnormal returns on event day similar in all models. Still, returns are not the same in all classifications; it means that split issue impact on stocks changes based on different classifications. It is also concluded that bonus and split events results are the same in all three expected return models but results varied in sample classifications. Keywords: Abnormal returns, Bonus issues, Event study, Expected return models, and Stock splits.

Nagendra Marisetty, Dr. M. Suresh Babu and Dr. S. V. Ramana Rao


Cite this Article: Nagendra Marisetty, Dr. M. Suresh Babu and Dr. S. V. Ramana Rao, An Empirical Study on Expected Return Models with reference to Bonus Issues and

Stock Splits in Indian Share Market, , 11 (5), International Journal of Management2020, pp. 1612-1630.

http://iaeme.com/Home/issue/IJM?Volume=11&Issue=5

1. INTRODUCTION Finance literature says that stock markets show the company's total accessible information in the company’s share price. In this context, researchers can study the company's events to know

its impact on the company’s share price. Eminent people in the finance stream developed the

Event study methodology (Ball & Brown 1968, Fama et al. 1969) to carry out this research with the main concentration on stock market returns. The economic impact of an event is called an abnormal return. The abnormal return has calculated the difference between an actual return of the stock and expected return or normal return of the stock, i.e., if the event wouldn’t have taken

place. Expected return or normal return required to estimate, for this purpose, event study methodology is made use Expected Return Models (ERM), these are common in finance

research. On the other hand, actual returns are observed in the market during the event. Expected return models (ERM) play a crucial role in the finance literature, especially in

event methodology studies. Market Model (MM), Market Adjusted Model (MAAM), Mean Adjusted Model (MEAM), Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), Fama Three and Four Factor Models and many models. Each model has been developed

under different assumptions for different purposes by using different inputs to know the securities' expected return. It is difficult to say which model is superior from finance literature because each model has its advantages and disadvantages. In the event study methodology, most of the researchers used the market model, and some researchers only used more than one model to compare the performance of models. Dyckman et al. (1984) used three models, i.e., MM. MAM and MAAM in event study to compare the abnormal return of events. Barnes &

Ma (2002) and Fernando &Guneratne (2009) also used those three models to measure the abnormal returns around events.

Bonus issues, also known as a stock dividend in the USA, offer additional shares of the company free of cost to existing stockholders. Bonus issues are offered on a pro-rata basis to existing shareholders. Offering bonus issues increases the company's outstanding stocks, but there is no ownership dilution. The announcement of bonus issues increases the paid-up capital, which reduces the reserves and surplus. Still, no change in the company net worth means that it is just an accounting transaction and no economic value changes. Distribution of bonus issues decreases the earnings per share and market price per share proportionately to the rate of issue, but there is no change in shareholders' wealth. Distribution of bonus issues does not directly affect the company's net worth or the wealth of shareholders. Bonus issues are just accounting transaction transferring the cash from reserves and surplus to paid-up capital.

Bonus issues literature suggests that it is a signal of the company's future earnings (Lakonishok& Lev 1987, Mc Nichols &Dravid 1990, Mishra 2005, George et al. 2007).

Stakeholders believe that Bonus issues action may generate abnormal returns to investors, and this is confirmed by many researchers (Grinblatt, Masulis& Titman 1984, Balachandran &

Tanner 2001, George et al. 2007). Bonus issues have a positive psychological effect on stockholders and increase the liquidity hypothesis supported by Adaoglu&Lasfer (2003), but Lakonishok& Lev 1987 argues that trade volume is not going get effected permanently by bonus issue actions. Encourage retail investor participation because the share's market price will decline proportionately to bonus issues action, and it may make price in a trading range.

An Empirical Study on Expected Return Models with reference to Bonus Issues and Stock Splits in Indian Share Market


A stock split is a corporate action used to increase the number of outstanding stocks through a proportional decrease in the stock's face value. Generally, stock split mainly affects the face value of the stock and the number of outstanding stocks, resulting in a decrease of the face value & increase in the number of outstanding stocks proportionately to the split factor. Stock split actions decrease the earnings per share and market price of the share accordingly as per the split rate factor, but there is no change in the company's wealth of shareholders and market capitalization. The important thing is that stock split actions do not affect the firm's assets and

liabilities, and the paid-up capital only affects the face value of the share and number of outstanding shares. Firms’ stock split action does not directly affect either the firm's economic

value or the accounting value. Stock splits action literature also supports the stock splits are signals of the company's future

earnings (Brennan & Copeland 1988, Healy, Asquith & Palepu 1989, Kunz &Majhensek 2007, Kalay & Kronlund 2009). But some other researchers found that stock splits send negative signals to the market about expected earnings (Lukose & Rao 2001, Huang, Liano & Pan 2002; Leledakis, Papaioannou, Travios&Tsangarakis 2005). The other reason for stock split initiation is to bring the market price of the share into a trading range, and this is supported by Leledakis, Papaioannou, Travios&Tsangarakis (2005), but Kunz &Majhensek (2007) found that trading volume mostly unchanged after the split.

Shareholders feel that stock split increases the liquidity in the market price of the share, and literature also supports this reason (Dhar and Goetzmann 2004, Leung, Rui & Wang 2006,

Joshipura 2008, Li, Stork and Zou 2013). Lukose & Rao (2001), Leledakis, Papaioannou, Travios&Tsangarakis (2005) disproves the share price's liquidity increases after the split

announcement. Shareholders believe that stock split decreases the spread between bid-ask (Koski 1998). Researches contradict significant abnormal returns around the stock split

announcement. Lukose & Rao (2001), Leung, Rui & Wang (2006), Kunz &Majhensek (2007), Kalay & Kronlund (2009), Bodhanwala (2010), Chavali & Zahid (2011), Nguyen, Tran

&Zeckhauser (2012), Hua & Ramesh (2013), Kalay &Kronland (2014), Chakrabarti, Gogai, Faiz & Rathod (2017) and Titman, Wei, and Zhao (2017) proved the abnormal returns around stock split announcements. Leledakis, Papaioannou, Travios&Tsangarakis (2005), Jamroz & Koronkiewicz (2013) have not found any significant unusual returns around the stock split announcement.

This article is divided into five parts; part 2 reviewed the previous literature related to event methodology, anomalies, bonus issues, and stock splits. In part 3 explained the sample

collection, selection procedures, and models applied in this study. Data analysis and interpretation are discussed in part 4, and finally, concluding remarks about this article

presented in the final part.

2. LITERATURE REVIEW

2.1. Review of Event Methodology Fama, French, Jensen & Roll (1969) suggest that the stock market is efficient, and the market price of shares adjusts new information very quickly, and they developed a new model Market model. Brown and Warner (1980) find that the market model performs very well based on simple methodology under different situations. .Bastholdy, Olson, and Peare (2005), proves that some adjustments to event methodology can fulfill the requirements. Kothari and Warner (2006) find that event methodology effects may change with different calendar times and also

depend on the sample of company features. Corrodo (2010) studies short term event methodology intending to add new things to some pressing topics.



2.2. Review on Anomalies G William Schwert (2002) finds that anomalies like size effect, weekend effect, valve effect, and dividend yield effect decreased or disappeared after the authors publish their research work. Eugene F. Fama and Kenneth R. French (2007) observes asset growth anomaly in micro-caps and small-cap companies average returns, but this anomaly is not present in big-cap companies. Roni Michaely, Amir Rubin, and Alexander Vedrashko (2012) study Friday announcement

special and prove no less attention to Friday corporate announcements than other day announcements. Joseph Engelberg, R David Mclean, and Jeffrey Pontiff (2017) prove that on corporate announcement days and earnings announcement days, anomalies returns higher than 50%; the reason for this is biased expectations.

2.3. Review on Bonus Issues Foster and Vickrey (1978) conclude that small stock dividends or large stock dividends won’t

generate a good amount of excess value on the ex-date. Grinblatt, Masulis, and Titman (1984) find that the stock market positively reacts to pure stock splits and stock dividends other than contaminated announcements. Balachandra& Tanner (2001), proofs that bonus issue size and pre-announcement of bonus issues impact the market price of the share. Barnes & Ma (2002) study the China equity market and finds that in the bonus share issue announcement, a higher bonus ratio issue company shares rewarded with good returns and, at the same time, lower bonus ratio issue companies rewarded with bad returns. Adaoglu (2002) finds that market price reacts positively, the sweetened effect of bonus issue announcements, and market price reacts negatively to unsweetened effect rights issue announcements.

Adaoglu and Lasfer (2003) argue that stock price reacted positively to the bonus issue announcement day and pre- -bonus issue period, but after ex-ex bonus days’ market price reacted negatively. George, Charles, and Raphael (2007) supports that the bonus issue announcement sends good signals about the company's future results to shareholders and investors. Marisetty, Marsden, and Raghavan (2007) find that share price returns on announcement date are positive, but returns are not statistically significant. Fernando &Guneratne (2009) find that the shares'

market price reacts significantly to the bonus issue announcement with higher price appreciation on the event announcement in Sri Lanka.

Malhotra, Thenmozhi, and Gopalswamy (2012), according to them, in rights issues and bonus issue announcements, they find evidence to support the cash substitution hypothesis and signaling theory but no evidence to support the liquidity hypothesis. Mehta, Jain, and Yadav (2014) find that stock average abnormal returns observed are positive before the announcement period of stock dividends. On announcement day, they then observe negative abnormal returns after the announcement days. Al Mamun (2013) finds that cumulative abnormal returns and

abnormal returns are statistically significant on rights issue announcement day and around announcement days. Muthukamu&Rajamohan (2015) reveals that the size of the bonus issues has an outstanding effect on the Indian stock market share's market price. Marisetty and Suresh

(2018) prove that abnormal returns on bonus issue announcement day are not statistically significant.

2.4. Review on Stock Splits Fama, French, Jensen, and Roll (1969) suggest that the stock market is efficient, and the market price of shares adjust very quickly with new information. Thomas E Copeland (1979) finds that the bid-ask spreads increase significantly as a percentage of the share market value after the

post-split. Ronald W Masulis and Sheridan Titman (1984) prove that market prices react positively to the announcement of splits and bonus issues and support the signaling hypothesis. Paul. M. Healy, Paul Aquith, and Krishna C Palepu (1989) find that companies split their stocks



after a good hike in share prices and company good earnings. Josef Lakonishok and Baruch Lev (1987) find that companies take up stock split announcement because of maintaining share prices at normal range. Paul Schultz (1998) finds that after the stock split announcement, stock transaction charges increase and weak proof that charges of market-making decrease after the stock split. Jennifer Lynch Koski (1998) finds that every day's variance increases significantly around stock split and stock dividend announcements.

Jijo Lukose P.J and S Narayan Rao (2001) studies market reaction to stock splits and finds that abnormal returns are significant around split announcement date and ex-split date. Rodney D Boehme (2001) proved from his study that abnormal returns are significantly positive during

the first year after the stock split announcement for equally weighted portfolios. Jose YagueGuirao and J Carlos Gomez Sala (2002) find a decrease in trading volume and depth and an increase in bid-ask spread after split announcements. Gow-Cheng Huang, Kastono Liano, and Ming-Shiun Pan (2002) proved that stock splits would not provide any positive signals to

the company’s further results expectations. Ravi Dhar and William N Geoetzmann (2004) supports the stock split announcements to attract new investors and hikes the stock's liquidity.

Michael M Grayson (2005) contradicts the efficient market hypothesis that the stock market is not efficient completely within a stipulated period of three months. George Lekedakis,

George J Papaioannou, Nickolaos G Travols, and Nicklaos V Trangarakis (2005) study stock split and finds no proof of stock price responses on split announcement day. Still, they got strong proof for positive share price changes to ex-split day. Tak Yan Leurg, Oliver Meng Rui, and Steven Sheye Wang (2006) prove that companies utilize stock splits announcements to signal in the process to more liquidity purposes. Alon Kalay and Mathias Kronlund (2007)

supports the information hypothesis and liquidity hypothesis at stock split announcements. SrinivasShirur (2008) concludes promoters’ stake plays a crucial role in the announcement of

stock splits. Kavita Chavali and Zaiby Zahid (2011) find that the impact of stock splits is positive on

event day and finds that an Indian stock market is a semi-strong form of an efficient market hypothesis. James J Angel (2012) suggested that idiosyncratic risk, company size, and company visibility impact the share's tick size and market price. Koroniewicz (2013) proves that stock split, split execution, and reverse split execution announcements have no significant reaction on stock markets, but reverse stock splits significantly negatively affect stock markets. Xiaoqi Li, Philip Stork, and Liping Zou (2013) support the positive cumulative average abnormal

returns around stock split event day, and also they support the liquidity improvement hypothesis.

Liu Hua and Skanthavrathur Ramesh (2013) find that abnormal stock returns are significant at the announcement of stock split days and prove that the Sri Lankan stock market is a semi-strong form efficient hypothesis. SatyajitDhar and Sweta Chhaochharia (2014) find stock prices react positively to the announcement of stock splits and bonus issues and find a semi-strong form of India's efficient market. BabithaRohit, Prakash Pinto &Shakila B (2016) studies two corporate actions, namely stock splits and rights issue announcements impact on share price

with evidence in the Indian stock market and observes positive abnormal returns around announcement date for both the actions but abnormal returns are not statistically significant, and also they find that Indian stock market is significant. Ruzbeh J Bodhanwala (2016) finds shareholders' wealth increases positively after stock split announcements but not for reverse stock split announcements.

B.B. Chakrabarthi, DebangaSourav Gogoi, Md. Faiz and Yash Ramesh Rathod (2017) supported the statistically significant positive abnormal returns around stock split

announcements in the Indian stock market, but on the actual stock split day, abnormal returns are not significant. Sheridan Titman, Chisen Wei, and Bin Zhao (2017) argue that fifty



percentage Chinese stock splits are suspicious. Marisetty & Suresh (2018) found that stock split day abnormal returns and cumulative abnormal returns are positive and abnormal returns are statistically significant.

3. RESEARCH METHODOL OGYAfter reviewing the literature, it is understood that in India, expected return models are not tested much in event study, and also anomalies are not studied elaborately in corporate events. This article will study the different expected return models and different anomalies in two main events, i.e., bonus issues and stock splits.

The objectives of this study as follows. To know the impact of bonus issues and stock split impact on shares abnormal returns

and cumulative abnormal returns on event day in Indian share market. To evaluate the various expected return models' influence on the calculation of

abnormal returns and cumulative abnormal returns of the shares on event day in Indian share market.

The hypothesis of the study is as follows H0 = Bonus issues and stock splits events not impact on abnormal returns and

cumulative abnormal returns of the shares on event day in Indian share market.

3.1. Model Selection and Window Selection Three main expected return models Market Model (MM), Market Adjusted Model (MAAM), and Mean Adjusted Model (MEAM), are selected (Dyckman et al. 1984, Barnes & Ma 2002, Fernando &Guneratne 2009 and Rudnicki 2011) for this study. The reason behind this model's selection is that the expected return is calculated either by using previous market return or particular stock return, not any other factors such as risk-free return or any other outside return. Sixty-one days event window is selected for study, in that ‘0’ which is defined as event day (the

date on which event is publically announced), -30 day to 0 days or event day is called pre-announcement period in event window and 0 days to +30 days is called post-announcement period in event window (Bodhanwala 2010, Nguyen, Tran &Zeckhauser 2012, Chakrabarti, Gogai, Faiz & Rathod 2017). The estimation window will be -252 days from -30 days of the event day window to regress the stock and index (Fernando &Guneratne 2009).

3.2. Market Model (MM)

Abnormal returnARi R= i - (αi + βiRm+ εi) Ri = Actual Returns of the Stock αi = Alpha coefficient of security with Index; βi = Beta coefficient of the security with Index Rm= Expected of the return of the Index εi = Residuals

Average Abnormal returns calculated as fallows

AAR =

i = the number of security in the study; n = total number of stocks in the class

3.3. Market Adjusted Model (MAAM)

Abnormal return (ARit ) = Rit R– mt



Rit = Stock return observed on day t Rmt= Market or Index return observed on day t

3.4. Mean Adjusted Model (MEAM)

Abnormal return (ARit) = Rit –

Rit = Stock return observed on day t = Average return on i in the estimation window

3.5. t Testttest used to determine the significance of abnormal returns

t =

AAR = Average abnormal return; σ (AAR) = Standard error of average abnormal return; Standard error is calculated is σ(AAR) =

σ = Standard deviation of the samples

3.6. Sample Selection Bonus issues and stock splits are selected for this study because these two events are not

announced regularly by companies like earnings and cash dividends events or rarely like rights issues, buybacks and mergers. An important feature of these events is that investors will not gain anything monetarily; just simple change is that decrease of the market price according to that event's factor. Another important feature is that these events are announced most of the time, along with the earnings or earnings and cash dividends. So most of the time, bonus issues and stock split events are contaminated with other corporate events.

Samples selected from the S&P BSE 500 (Standard & Poor Bombay Stock Exchange) Index because these index companies have almost 90 percent market capitalization compared to S&P BSE total companies market capitalization. BSE 500 Index companies have chosen which are there in January 2020 because BSE will regularly alter the Index constituents depend on the index requirements and market requirements. 2000 2019 (20 years) period has selected for –

sample selection because many changes happened in the Indian economy in this duration. Stock price information was collected from the S&P BSE website, and events information collected from moneycontrol.com.

3.7. Bonus Issue Samples In India, a total of 1220 bonus issue events were announced during 20 years research period in that 282 events were announced by BSE 500 companies. Two hundred forty events were only selected for study from 282 events because the remaining 42 events either price information is not sufficient or clash with other events during the event window period. Two hundred forty samples are tested for abnormal returns on event day using three expected return models in four sections. In section 1, samples are divided based on standalone bonus issue announcements and bonus issue announcements along with other events (Grinblatt, Masulis& Titman 1984 and Balachandra& Tanner 2001). In section 2, samples divided based on periodical or calendar-wise, a total of 20 years sample period divided into four equal parts (Bondt&Thaler 1985). In section 3, samples were organized based on January 2020 BSE capitalization wise like large-cap, mid-cap, and small-cap. In section 4, samples categorized based on event factor wise, i.e., the ratio of the event (Millar &Fielitz 1973).



Table 1 Classification of Bonus Issue Samples

S. No 1. Description N 2. Calendar N 3. Cap N 4. Factor N 1 Full Sample 240 2000 - 2004 32 Large 88 01:01 140 2 Standalone Bonus 53 2005 - 2009 63 Mid 51 01:02 49 3 Bonus with other events 187 2010 - 2014 53 Small 101 Others 51

4 2015 - 2019 92

Total 240 240 240 240 (Source: moneycontrol.com)

3.8. Stock Split Samples In India, a total of 1259 stock split events were announced during 20 years research period in

that 250 events were announced by BSE 500 companies. Two hundred events were only selected for study from 250 events because the remaining 50 events either price information is not sufficient or clash with other events during the event window period. Two hundred forty samples are tested for abnormal returns on event day using three expected return models in four sections. In section 1, samples are divided based on standalone stock split announcement (Pure events) and stock split announcement along with other events (Healy, Asquith & Palepu 1989). In section 2, samples divided based on periodical or calendar-wise, a total of 20 years sample period divided into four equal parts (Boehme 2001). In section 3, samples were organized based on January 2020 BSE capitalization wise like large-cap, mid-cap, and small-cap. In section 4, samples categorized based on event factor wise, i.e., the event's ratio (Huang, Liano Pan 2002, Li, Stork and Zou 2013).

Table 2 Classification of Stock Split Samples

S. no 1. Description N 2. Calendar N 3. Cap N 4. Factor N 1 Full Sample 200 2000 - 2004 20 Large 88 0.1 times 47 2 Standalone Split 67 2005 - 2009 70 Mid 51 0.2 times 100 3 Split with other events 133 2010 - 2014 70 Small 101 0.5 times 47 4 2015 -2019 40 Others 6 Total 200 200 200 200

(Source: moneycontrol.com)

4 DATA ANALYSIS . In this part, the results are going to analyze in four sections. In section one, Pure and Impure events, in section two events, based on periodic, section three events based on capitalization and final section events based on factor or ratio of the event.

4.1. Pure & Impure Base Classification of the Events Bonus Issue & Stock Split –

Table 3 AAR and CAAR values of Pure and Impure Bonus Issues on Event day from three Expected return models

Action Type N AAR (%)

t (AAR) p Valve

CAAR (%)

t (CAAR) p Valve

Market Model Full Sample 240 1.0143 4.0009 0.0001*** 5.8061 5.7309 0.0000***

Standalone Bonus Issue 57 0.8160 1.3569 0.1802 9.2840 5.0931 0.0000***




t (AAR) p Valve

CAAR (%)

t (CAAR) p Valve

Bonus Issue with other Actions 183 1.0512 3.8103 0.0002*** 4.6413 3.8944 0.0001***

Market Adjusted Model Full Sample 240 1.1677 4.6373 0.0000*** 9.5158 10.1588 0.0000***

Standalone Bonus Issue 57 1.0591 1.7636 0.0833* 13.1473 6.6348 0.0000***


Mean Adjusted Model Full Sample 240 0.8065 2.9855 0.0031*** 5.6785 5.0840 0.0000***

Standalone Bonus Issue 57 0.4159 0.6546 0.5154 6.7747 2.6074 0.0117**


(Source: Author’s Calculation by using price information from bse.com; *** significant @ 1% level, ** significant @ 5% level and * significant @ 10% level)

It is observed from Table 3 that standalone bonus issues are very less when compare to bonus issues with other actions. Full sample and bonus issue with other events abnormal returns are significantly positive at 1 percent level on event day in all three models, and returns are

highest in the market-adjusted model. Standalone bonus issue events abnormal returns are positive in all three models, but the market-adjusted model return only significant at 10 percent level and return are lowest in the mean adjusted model. CAAR values are positive in all three models for three classifications, and all most all returns are significant at 1 percent level except standalone bonus in the mean adjusted model. On event day, standalone abnormal returns are least in all three models compare to the other two classifications, but standalone bonus CAAR values are highest in all three models.

Table 4 AAR and CAAR values of Pure and Impure Stock Splits on Event day from three Expected return models


t (AAR) p Valve CAAR

(%) t

(CAAR) p Valve

Market Model Full Sample 200 0.3033 1.2654 0.2072 3.3697 3.7683 0.0002***

Standalone Stock Split 67 0.3056 1.0265 0.3084 5.1388 3.4226 0.0011***

Stock Split with other Actions 133 0.2618 0.8067 0.4213 2.4785 2.2375 0.0269**

Market Adjusted Model Full Sample 200 0.4610 1.9247 0.0557* 8.5876 9.2912 0.0000***


Stock Split with other Actions 133 0.4983 1.5203 0.1308 8.2656 7.1159 0.0000***

Mean Adjusted Model Full Sample 200 0.1794 0.6962 0.4871 3.4853 3.3872 0.0009***






(%) t

(CAAR) p Valve

Stock Split with other Actions 133 0.1540 0.4429 0.6586 2.5508 1.9716 0.0507*

(Source: Author’s Calculations; ***significant@1%, ** significant@5% &* significant@ 10%)

It is understood from Table 4 that standalone stock splits are very less when compare to stock splits with other actions. Full sample and stock split with other events abnormal returns are positive on event day in all three models, but full sample AAR in market-adjusted model significant at 10 percent level and returns are highest in the market adjusted model. Standalone stock split events abnormal returns are positive in all three models, but returns are not significant in any model, and return is lowest in the mean adjusted model. Standalone AR are lowest in MM, and MAAM models compare to the other two classifications, but in MEAM, standalone AR is highest compare to the other two classifications. CAAR values are positive in all three models for three classifications, and all most all returns are significant at 1 percent level except standalone split in the mean adjusted model. On event day, standalone abnormal returns are least in all three models compare to the other two classifications, but standalone split CAAR values are highest in all three models. Regarding models, here also, the market-adjusted model generates more abnormal returns than the other two models and least returns in the mean adjusted return model.

4.2. Periodically or Calendar Base Classification of the Events Bonus Issue & –

Stock Split

Table 5 AAR and CAAR values of Periodic base Bonus Issues on Event day from three Expected return models



(%) t

(CAAR) p Valve

Market Model 2000 - 2004 Bonus issues 32 1.9001 2.1555 0.0390** 8.3124 1.9244 0.0635*

2005 - 2009 Bonus Issues 63 1.5616 2.8456 0.0060*** 10.0877 4.1973 0.0001***

2010 - 2014 Bonus Issues 53 0.2159 0.6307 0.5310 4.2636 2.5655 0.0132**

2015 - 2019 Bonus Issues 92 0.7187 1.7818 0.0781* 2.9587 3.0555 0.0030***

Market Adjusted Model 2000 - 2004 Bonus issues 32 2.0415 2.2647 0.0307** 13.3362 3.7826 0.0007***

2005 - 2009 Bonus Issues 63 1.9268 3.6727 0.0005*** 14.5329 6.2603 0.0000***

2010 - 2014 Bonus Issues 53 0.4056 1.1513 0.2549 9.1274 5.9753 0.0000***

2015 - 2019 Bonus Issues 92 0.8016 2.0075 0.0477** 5.0101 5.6028 0.0000***

Mean Adjusted Model 2000 - 2004 Bonus issues 32 1.7159 1.9172 0.0645* 6.7665 1.4690 0.1519





(%) t

(CAAR) p Valve

2005 - 2009 Bonus Issues 63 1.3490 2.1663 0.0341** 10.0432 3.5095 0.0008***

2010 - 2014 Bonus Issues 53 -0.0057 -0.0162 0.9871 3.9032 2.2801 0.0267**

2015 - 2019 Bonus Issues 92 0.5890 1.3906 0.1678 3.4601 3.3568 0.0012***


Table 5 says that bonus issues 2000 04 period is very less and highest in the 2015 19 – –

period. AAR is positive on event day in all periods for MM and MAAM models, and returns are highest in the first two periods but lowest in the third period. AAR is significant at 1 percent level in the period 2004 2009 bonus issues for MM and MAAM models. In the period 2010 –– 14, AAR is positive in MM and MAAM and negative in the MEAM model, and also returns are not significant in any model. In 2015 -19, AAR is positive in all models but 5 percent level significant in MAAM, 10 percent level significant in MM, and not significant in MEAM. On event day, CAAR values are highest in 2005 09-period bonus issues and lowest in 2015 19 – –

period bonus issues for all three models. CAAR values are positive in all three models for all four periods, and all most all returns are significant at various levels except 2000 2004 bonu– s issues in the mean adjusted model not significant.

Table 6 AAR and CAAR values of Periodic base Stock Splits on Event day from three Expected return models



(%) t (CAAR) p Valve

Market Model 2000 - 2004 Stock Splits 20 1.4388 1.2914 0.2121 1.7442 0.7459 0.4649

2005 - 2009 Stock Splits 70 0.5880 1.5265 0.1315 7.9755 4.3695 0.0000***

2010 - 2014 Stock Splits 70 -0.0360 -0.1453 0.8849 0.9042 0.8006 0.4261

2015 - 2019 Stock Splits 40 -0.5228 -0.8572 0.3966 1.5105 0.8170 0.4189

Market Adjusted Model 2000 - 2004 Stock Splits 20 1.6878 1.4590 0.1609 6.0465 3.0037 0.0073***

2005 - 2009 Stock Splits 70 0.8006 2.1213 0.0375** 13.6649 7.1407 0.0000***

2010 - 2014 Stock Splits 70 0.2303 0.7657 0.4465 5.3046 4.6612 0.0000***

2015 - 2019 Stock Splits 40 -0.3428 -0.5610 0.5780 6.7181 3.5177 0.0011***

Mean Adjusted Model 2000 - 2004 Stock Splits 20 0.9790 0.7670 0.4525 0.0702 0.0265 0.9792

2005 - 2009 Stock Splits 70 0.7014 1.6268 0.1083 9.7693 4.8418 0.0000***






2010 - 2014 Stock Splits 70 -0.0845 -0.2728 0.7858 -1.1631 -0.8953 0.3737

2015 - 2019 Stock Splits 40 -0.6720 -1.0854 0.2844 2.3304 1.0936 0.2808


Table 6 says that stock splits in the 2000 04 period are very less and highest in 2005 09 – –

and 2010 - 14. AAR is positive on event day in the first two periods and negative for the last periods for all three models, and returns are highest in the 2000 - 2004 period and lowest in the 2015 - 2019 period. AAR is not significant at any percent level in all three models except in the 2005 09 period for the MAAM model. CAAR values are positive in MAAM for all period –

splits and also significant at the 1 percent level. In MM, CAAR values are positive on vent day but very low in all periods except 2005 – 09 period, and also returns are significant at 1 percent level in 2005 09 only. In MEAM, CAAR values are negative in the 2010 14 period, and – –

remaining in other periods values are positive but 2005 09 period CAAR values only –

significant at 1 percent level. Regarding models, here also, the market-adjusted model generates more abnormal returns than the other two models and least returns in the mean adjusted return model.

4.3. Capitalization or Size Base Classification of the Events Bonus Issue & Stock –

Split

Table 7 AAR and CAAR values of Capitalization baseBonus Issues on Event day from three Expected return models




Market Model Large Cap Bonus Actions 88 1.0652 3.0291 0.0032*** 2.7271 2.0253 0.0459**

Mid Cap Bonus Issue Ations 51 0.9855 1.9738 0.0539* 6.6970 3.8890 0.0003***

Small Cap Bonus Issue Actions 101 0.9395 2.0561 0.0424** 7.8914 4.1743 0.0001***

Market Adjusted Model Large Cap Bonus Actions 88 1.2661 3.6149 0.0005*** 5.2115 4.2575 0.0001***

Mid Cap Bonus Issue Ations 51 1.0575 2.0655 0.0441** 9.3494 5.1557 0.0000***

Small Cap Bonus Issue Actions 101 1.1376 2.5388 0.0127** 13.3501 8.1059 0.0000***

Mean Adjusted Model Large Cap Bonus Actions 88 1.0867 2.7851 0.0066*** 2.8237 1.7206 0.0889*

Mid Cap Bonus Issue Ations 51 0.4948 0.9547 0.3443 5.9934 2.8881 0.0057***

Small Cap Bonus Issue Actions 101 0.7199 1.4954 0.1380 8.0069 4.0709 0.0001***




It is observed from Table 7 that small-cap bonus issues are very high, and mid-cap bonus issues are low. Large-cap AAR values are highest, and mid-cap AAR values are lowest on event day in three models. AAR values are positive in all three models for all three capitalization bonus issues, but most of the returns are significant at various levels except mid-cap and small-

cap bonus issues in the MEAM model. AAR values are highest in the MM model for all capitalization bonus issues and lowest in MEAM. Small-cap CAAR values are highest in all models compare to other caps. On event day, large-cap abnormal returns are highest in all three models compare to the other two classifications, but large-cap bonus CAAR values are lowest in all three models. CAAR values are positive in all three models for three classifications, and all most all returns are significant at 1 percent level except large-cap bonus in MM and MEAM. It can be interpreted from above that large-cap bonus issues generate more abnormal returns to investors on event day than other caps. Another important observation is that small caps CAAR values are highest than other caps; they say that these caps bonus issues generate more revenue for investors during the event window. Regarding models, here also, the market-adjusted model

generates more abnormal returns than the other two models and least returns in the mean adjusted return model.

Table 8 AAR and CAAR values of Capitalization base Stock Split on Event day from three Expected return models



(%) t

(CAAR) p Valve

Market Model Large Cap Stock Split Actions 43 0.0883 0.2095 0.8351 0.9646 0.7992 0.4286

Mid Cap Stock Split Actions 40 0.3220 0.6332 0.5303 0.8346 0.4774 0.6358

Small Cap Stock Split Actions 117 0.3633 1.0886 0.2786 5.1203 3.8861 0.0002***

Market Adjusted Model Large Cap Stock Split Actions 43 0.0968 0.2218 0.8256 3.9665 3.3252 0.0018***

Mid Cap Stock Split Actions 40 0.4468 0.8797 0.3844 6.2312 3.8126 0.0005***

Small Cap Stock Split Actions 117 0.5998 1.7867 0.0766* 11.0915 8.1093 0.0000***

Mean Adjusted Model Large Cap Stock Split Actions 43 0.0791 0.1637 0.8708 0.5824 0.3657 0.7164

Mid Cap Stock Split Actions 40 0.1974 0.3841 0.7030 0.4896 0.2545 0.8005

Small Cap Stock Split Actions 117 0.2101 0.5756 0.5660 5.5763 3.7168 0.0003***


It is found from Table 8 that small-cap stock splits are very high, and mid-cap stock splits are low. Small-cap AAR values are highest, and large-cap AAR values are lowest on event day in three models. AAR values are positive in all three models for all three capitalization stock



splits, but most of the returns are not significant except small-cap stock splits in the MAAM model. AAR values are highest in the MAAM model for all capitalization stock splits and lowest in MEAM. Small-cap CAAR values are highest in all models compare to other caps. On event day, large-cap abnormal returns are lowest in all three models compare to the other two classifications, and also large-cap split CAAR values are lowest in all three models. CAAR values are positive in all three models for three classifications, and all classification cap returns are significant at a 1 percent level MEAM model only. Small-cap CAAR values are significant at one percent level in all models, and other cap CAAR values are not significant at any level other than MAAM. It can be interpreted from above that small-cap stock splits generate more abnormal returns to investors on event day than other caps. Another important observation is that small caps CAAR values are highest than other caps; they say that these caps stock splits generate more revenue during the event window. Again, the market-adjusted model generates more abnormal returns than the other two models and least returns in the mean adjusted return model.

4.4. Factor or Ratio Base Classification of the Events Bonus Issue & Stock Split –

Table 9 AAR and CAAR values of Factor or Ratio base Bonus Issues on Event day from three Expected return models



(%) t

(CAAR) p Valve

Market Model Bonus Issue Ratio 1:1 140 1.1129 3.4731 0.0007*** 5.0826 3.4642 0.0007***

Bonus Issue Ratio 1:2 49 1.0531 1.4547 0.1523 5.6011 3.0806 0.0034***

Other Bonus Issue Ratios 51 0.6171 1.4666 0.1438 7.6969 4.1133 0.0001***

Market Adjusted Model Bonus Issue Ratio 1:1 140 1.3133 4.1495 0.0001*** 9.5163 7.2328 0.0000***

Bonus Issue Ratio 1:2 49 1.1223 1.5903 0.1183 8.3955 5.0882 0.0000***

Other Bonus Issue Ratios 51 0.8117 1.8204 0.0699* 10.5909 5.3168 0.0000***

Mean Adjusted Model Bonus Issue Ratio 1:1 140 0.8964 2.5717 0.0112** 5.6828 3.8470 0.0002***

Bonus Issue Ratio 1:2 49 0.9561 1.2507 0.2171 4.3816 1.8941 0.0643*

Other Bonus Issue Ratios 51 0.4164 0.9853 0.3255 6.9128 2.7055 0.0073***


It is understood from Table 9 that factor 1:1 bonus issues are very high, and also it is more than 60 percent bonus issues in the total sample, it means that companies prefer to announce a 1:1 bonus ratio. 1:1 bonus ratio AAR values are highest, and other ratios AAR values are lowest

on event day in three models. AAR values are positive in all three models for all three capitalization bonus issues, but the 1:1 bonus ratio of the returns only significant at various



levels in all models. AAR values are highest in the MAAM model for all classifications and lowest in MEAM. Other factor CAAR values are highest in all models compare to other ratios. On event day, 1:1 ratio abnormal returns are highest in all three models compare to the other two classifications, but 1:1 bonus CAAR values are not highest on event day in all three models. CAAR values are positive in all three models for three classifications, and all most all returns are significant at 1 percent level except 1:2 bonus in MEAM. It can be interpreted from above that 1:1 bonus issues generate more abnormal returns to investors on event day than other ratios. Another important observation is that other ratios CAAR values are highest than other ratios; it says that these ratios bonus issues generate more revenue to investors during the event window. Regarding models, here also, the market-adjusted model generates more abnormal returns than the other two models and least returns in the mean adjusted return model.

Table 10 AAR and CAAR values of Factor or Ratio baseStock Split on Event day from three Expected return models



(%) t

(CAAR) p Valve

Market Model Splitting the Face Value 0.1 times 47 1.1548 2.2128 0.0319** 3.8241 1.8390 0.0724**

Splitting the Face Value 0.2 times 100 0.0460 0.1457 0.8845 3.2642 2.8741 0.0050***

Splitting the Face Value 0.5 times 47 -0.0807 -0.1825 0.8560 1.5115 1.0019 0.3216

Market Adjusted Model Splitting the Face Value 0.1 times 47 1.3613 2.5573 0.0139** 9.9425 4.1873 0.0001***



Mean Adjusted Model Splitting the Face Value 0.1 times 47 1.0500 1.7642 0.0843* 4.4394 1.9894 0.0526*

Splitting the Face Value 0.2 times 100 -0.0520 -0.1537 0.8781 2.7396 2.1021 0.0381**

Splitting the Face Value 0.5 times 47 -0.2933 -0.5973 0.5532 1.9973 1.0129 0.3164


It is proved from Table 10 that factor 0.2 times stock splits are very high and also it is more than 50 percent stock splits in the total sample; it means that companies prefer to announce 0.2 times split ratio. 0.1 times split ratio AAR values are highest, and other ratios AAR values are the lowest on event day in three models, and the values of which are also 0.5 times split AAR values are negative in MM and MEAM. AAR values are positive in all MAAM for all three classification stock splits, but the returns' 0.1 times split ratio is only significant at the 5 percent level. 0.1 times split values only positive and significant in all models. AAR values are highest in the MAAM model for all classifications and lowest in MEAM. 0.1 times CAAR values are highest in all models compared to other ratios. On event day, the 0.1 times ratio, abnormal returns are highest in all three models than the other two classifications. Also, 0.1 times split



CAAR values are highest on event day in all three models. CAAR values are positive in all three models for three classifications, and all most all returns are significant at various percent levels except 0.5 times split in MM and MEAM. It can be interpreted from above that 0.1 times stock splits generate more abnormal returns to investors on event day compare to other ratios. Another important observation is that the ratios of 0.1 times, and CAAR values are higher than those of other ratios; it says that these ratios stock splits generate more revenue to investors during the event window. Regarding models, here also, the market-adjusted model generates more abnormal returns than the other two models and least returns in the mean adjusted return model.

5. CONCLUSION It is concluded from this study that all the three models, i.e., Market Model (MM), Market Adjusted Model (MAAM), and Mean Adjusted Model (MEAM), are going to provide almost the same results in event study, but MAAM abnormal returns on event day little bit inflated compared to other models in all classifications. Another observation is that MEAM abnormal returns on event day a little bit lesser than MM. The reason behind MAAM inflated results maybe, in this model, to calculate expected returns not use the either stock or index previous returns. Whereas in MM, previous stock and index returns were considered, and in MEAM, only previous stock returns were considered to predict the expected return of the stock.

It is also concluded that bonus issues generate positive abnormal returns in all most all classifications. Classification based on pure and impure, only impure and full sample bonus events is significant, which means that stocks do not impact standalone bonuses. Periodical classification also bonus issue results are not similar in the periods, i.e., 2000 04 & 2005 – – 09 abnormal returns are highly positive on event day and also significant. Whereas in later periods, i.e., 2010 14 & 2015 19, returns are slightly positive and not significant in all models. In – –capitalization classification, large-cap bonus issues are highly positive and significant at a one percent level in all models. In contrast, in other caps, results are not similar in all models. In factor classification, bonus issue 1:1 abnormal returns are positively significant in all models compared to other classification. Bonus issue events impact on stocks are not common for all, so its impact change depends on the purity of the event, period, size, and factor or ratio wise.

It is also concluded that split issues generate slightly positive abnormal returns on event day in most classifications. Classification is based on pure and impure; all most all split events are not significant at any level of significance. Periodical classification split issue results are not similar in the periods, i.e., 2000 04 & 2005 09 abnormal returns are positive on event day – –but not significant in most classifications. Whereas in later periods, i.e., 2010 14 & 2015 – –

19, returns are slightly negative and not significant in all models. In capitalization classification, small-cap split issues are slightly positive and not significant at the five percent level in all models, whereas, in other caps, results are not similar in all models. In factor classification, split issue 0.1 times abnormal returns are positively significant in all models compared to other classifications. Split issue events impact on stocks are not common for all, and most of the classifications abnormal returns are not significant on the event day.

Finally, it is concluded that the Market Adjusted Model has a slight advantage over other models due to its slightly inflated abnormal returns. Bonus issue events abnormal returns on event day similar in all models, but returns are not the same in all classifications; it means that

bonus issue impact on stocks change based on different classifications. Split issue events abnormal returns on event day similar in all models, but returns are not the same in all

classifications, it means that split issue impact on stocks change based on different classifications. It is also concluded that bonus and split events results are the same in all three expected return models but results varied in samples classifications.



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SHARE MARKET BONUS ISSUES AND STOCK SPLITS IN INDIAN