THE IMPACT OF M&A DEALS ON THE STOCKS RETURN OF BIDDER COMPANIES IN THE RUSSIAN MARKET

Опубликовано в журнале: Научный журнал «Интернаука» № 43(266)
Рубрика журнала: 21. Экономика
DOI статьи: 10.32743/26870142.2022.43.266.347532
Библиографическое описание
Резниченко Е.Д. THE IMPACT OF M&A DEALS ON THE STOCKS RETURN OF BIDDER COMPANIES IN THE RUSSIAN MARKET // Интернаука: электрон. научн. журн. 2022. № 43(266). URL: https://internauka.org/journal/science/internauka/266 (дата обращения: 28.03.2024). DOI:10.32743/26870142.2022.43.266.347532

THE IMPACT OF M&A DEALS ON THE STOCKS RETURN OF BIDDER COMPANIES IN THE RUSSIAN MARKET

Ekaterina Reznichenko

Student of BA “International Business and Management”, National Research University Higher School of Economics (HSE),

Russia, St.Petersburg

 

ABSTRACT

This paper studies the impact of merger and acquisition (M&A) deals and determinants on the profitability of shares of companies in Russian capital market. The research problem is worth investigating because the comparative analysis of abnormal returns and determinants for transactions in Russia is outdated, and results of impact of M&A deals are inconsistent.

This paper examines the stock price performance of 53 Russian companies engaged in M&A during 2010–2019. Applying the event studies method, the study observes that the shareholders of acquirer Russian firms on average experience positive abnormal return of 2.2 percent points within 4, 5, and 10-day windows significant at 5% level. The firms, fully acquiring targets, on average experience higher returns in comparison to firms, acquiring minority stakes; the results are statistically significant for 4 and 5-day event windows at 5% and 10% level. Presence of state ownership decreases returns of the acquirer; the results are statistically significant for 4, 5, and 10-day event windows at 5% level.  

The limitations of the paper are related to the lack of data on deals of non-public companies, and omitted variable bias. Overall, this paper updates available scientific knowledge about the M&A transactions in Russian capital market.

 

Keywords: M&A deals, merger and acquisition, Russia, shareholders, event studies, cumulative abnormal returns

 

Introduction

Main goal of each enterprise is maximization of value, which measures how much the firm’s activities will create in the future. This can be done by certain investment activities, one of them is merger and acquisition deals. The term merger and acquisition (M&A) is used to describe investment strategy of buying or selling a business (Phillips & Zhdanov, 2013) considered in this thesis paper.  As in any deal, M&A have two sides of the agreement: a target, business which is sold or bought, and an acquirer or a bidder, a firm which performs the acquisition activity. M&A deals may be performed a as buying either the stocks of a firm or its assets. In case of M&A deals in stocks the acquirer is given the rights of ownership and corporate rights such as right to the right to participate in the management of the company through the right to vote and the right to participate in the distribution of profits, namely, to receive dividends. M&A deals are profitable for the acquiror due to possibility of increasing market share, entering a new market, obtaining new competencies including technologies, data/client bases, patients/licences, controlling and enriching sales and supply channels, eliminating costs, improving credit conditions (Li, 2013; Renneboog & Vansteenkiste, 2019; Risberg, 2003). All mentioned above can be achieved through step-by-step development of the firm, however, such may require much more resources in comparison to M&A deal does.

The increased participation of emerging capital enterprises in global trade and investments has attracted attention of many researchers. Increased globalization has resulted into substantial growth of M&A deals world-wide due to benefits mentioned earlier (e.g., Zhu et al., 2021; Liu & Meyer, 2020; Boehe, 2016). Indeed, data published by United Nations Conference on Trade and Development (UNCTAD) in World Investment Report (2017) have shown that total value of M&A deals world-wide was around $869 billion in comparison to less than $100 billion in 1990. More recently, in Global & Regional M&A Report 1Q21 published by Mergermarket M&A deals already comprised $1,162.4 billion. The majority of M&A deals are from developed markets, consequently, this is the reason why Russian capital market as emerging one is almost unexplored in comparison, for instance, the USA, developed country (Yang & Hyland, 2012). 

The topic of M&A impact on stock returns is widely and deeply discussed for the developed countries, however, there is no up-to-date analysis for the emerging capital markets, especially for Russia (Pereira et al., 2021). According to the theory explained in the paragraphs above, M&A deals as investment strategy should have positive impact on the share returns of bidder companies. However, after conducting empirical research, the authors state that there is a conflicting view whether acquisitions create (e.g., Chikamoto et al., 2016; Danbolt & Maciver, 2012; Mateev, 2017; Pereira et al., 2021; Rani et al., 2012) or destroy (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Erel et al., 2012; Grigorieva & Petrunina, 2015) value.

This paper is aimed at studying the impact of determinants of merger and acquisition deals on the profitability of shares of companies in Russian capital market. The research problem is worth investigating due to several reasons. First, emerging capital markets offer investors great opportunities opting to the rapid growth of the economy and increased rates of return on securities (Hossain, 2021). Second, the absence of the up-to-date comparative analysis of abnormal returns for transactions in emerging capital markets, as well as analysis of determinants. Even the most recent papers are based on the data from no earlier than ten years (e.g., Hossain, 2021; Liu & Meyer, 2020; Mateev, 2017; Renneboog & Vansteenkiste, 2019; Zhu et al., 2021). Thirdly, inconsistent results of evaluation of determinants of additional profitability of returns - the same determinants have distinctive impact on different database (Xie et al., 2017). Therefore, the most common determinants will be analyzed in the Russian market and then the results will be compared with the earlier papers of other emerging capital markets. Fourth, the minority of articles was found to be analyzing Russian case solely. What is more, even not all papers analyzing emerging capital markets included Russia. The main reason behind this situation is that Russian capital market has a comparatively shorter period of development in comparison to China or India. It was identified that the most recent papers start including Russia (Xie et al., 2017). Therefore, exploration of Russian capital market is gaining its importance among researchers. The known results will allow company owners and top managers to develop the further strategy of the company's behavior after the M&A announcement or the completed transaction. The obtained results will be useful to be considered by investors before buying certain stocks of the companies in emerging markets.

The following paper is structured in a way that firstly literature review is presented to highlight the main findings on the impact of M&A deals and determinants on stock prices. The second section is methodology. The research will be based on the data of M&A deals in the emerging markets of the public companies located on the Bureau van Dijk Zephyr and stock price changes published on Yahoo! Finance. The event studies method will be used to analyze obtained data set - cumulative abnormal returns (CARs) will be calculated using capital asset pricing model (CAPM) (MacKinlay, 1997). The main theoretical concepts behind are the efficient market hypothesis and random walk theory. These imply that the actual stock price adjusts due to new information available on the market (Samuelson, 1965). In the efficient market, which is described by many rational participants, whose aim is profit maximization, each participant is attempting to predict future securities’ market values when information is estimated by all participants (Fama, 1970). After that main hypothesis are stated that M&A announcements result into return changes of the acquiror firm and the impact of specific determinants appropriate for Russia is analysed in greater detail. Then, the procedure of data collection is explained. Following that, descriptive statistics is presented. Following that, the results of hypothesis testing are presented. Further, the discussion of obtained results, including the consistency of the results with previous studies, is demonstrated. Finally, in conclusion section main results, limitations, and implications are presented.

Overall, the answer on this research question: “What is the impact of M&A deals on the stocks return of bidder companies in the Russian market,” first, will update available scientific knowledge about the Russian market stock prices changes. Second, will allow company owners and top managers to develop the further strategy of the company’s behaviour after the M&A announcement or the completed transaction. Third, provide ground for the further aggregated and specific analysis of individual determinants of M&A transactions in Russian capital market.

Literature review

The topic of how stock prices reflect to market changes started to be discussed in the middle of 19th century. Fama (1965) discussed the behaviour of stock prices. The author concluded that as the intrinsic value of stock changes, the actual price immediately adjusts due to new information available on the market. New information may include such events as the advancement of research and development practices, modifications in a management team, foreign restrictions on the industry, expansion of the production volume or any other performed or expected event which affects the firm’s prospects and, as a result, intrinsic stock value. The same year Samuelson (1965) concluded that in a well-functioning and competitive market it is expected that the prices will change as investors’ expectations adapt to new information. Then Fama (1965) presented an article which consisted of a summary of past work and an empirical approach of testing a theory of efficient market hypothesis. The author defines market as the “efficient” in which security prices reflect all available information in full. All mentioned above summarizes that in the efficient market the competition among its rational participants aimed to maximize profit occurs in the way that actual security prices, at any given time, reflect the information on the events which have already happened and on the events which are expected to happen sometime later (Fama, 1970). Namely, in the efficient market the actual security prices, at any given time, is a sufficient estimate of the fair value of security.

As it was stated earlier investors are rational market participants aimed at profit maximization, accordingly, main goal of each enterprise is maximization of value, which measures how much value the firm’s activities will create in the future. This can be done by certain strategic investment activities, one of them is merger and acquisition deals (Risberg, 2003). The term “merger and acquisition” is used to describe investment strategy of buying or selling a business (Phillips & Zhdanov, 2013). First, target firm states its minimum reservation cost which target considers as fair price reflecting firm’s net equity value. Then, acquiror calculates possible benefits derived from this investment strategy, namely, strategic and economic incentives mentioned previously and transaction costs which are payment to intermediates such as advocates, banks and other consultants ensuring safe and advantageous operation. Consequently, possible benefits are added to the true value and transaction costs are then subtracted, therefore, reservation cost for the acquiror is found. Finally, both sides negotiate and agree on certain price. The difference between the reservation price and final gives net synergy, profit earned due to M&A deal. Overall, firm’s financial performance impacts stock returns (Fama & French, 2006).

The increased participation of emerging capital enterprises in global trade and investments has attracted attention of many researchers. Increased globalization has resulted into substantial growth of M&A deals world-wide (e.g., Zhu et al., 2021; Liu & Meyer, 2020; Boehe, 2016). Indeed, data published by United Nations Conference on Trade and Development (UNCTAD) in World Investment Report (2017) have shown that total value of M&A deals world-wide was around $869 billion in comparison to less than $100 billion in 1990. More recently, in Global & Regional M&A Report 1Q21 published by Mergermarket M&A deals already comprised $1,162.4 billion. As it can be observed on the map below the majority of M&A deals are from developed markets, consequently, this is the reason why Russian capital market as emerging one is almost unexplored in comparison, for instance, the USA, developed country (Yang & Hyland, 2012). 

Based on the information mentioned above, it was identified that M&A deals influence stock prices (Vermaelen, 2014). This topic is widely and deeply discussed for the developed countries, however, there is little evidence on up-to-date analysis for the emerging capital markets, especially for Russia. In this part of the literature review main findings will be mentioned and compared, further specific determinants will be chosen for the empirical analysis of their effect on the stock prices in the Russian capital market.

According to the theory, M&A deals as investment strategy should have positive impact on the share returns of bidder companies. However, after conducting empirical research, the authors state that there is a conflicting view whether acquisitions create (e.g., Chikamoto et al., 2016; Danbolt & Maciver, 2012; Mateev, 2017; Pereira et al., 2021; Rani et al., 2012) or destroy (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Erel et al., 2012; Grigorieva & Petrunina, 2015) value.

To start with, Aybar and Ficici (2009) investigated into the impact of M&A announcements on the sample collected from Thomson SDC Platinum database consisted of 433 cross-border M&A announcements made by 58 firms from 1991 to 2004 observed on seven event widows. It was identified that the market reacts negatively to the M&A announcements, this finding is consistent with the other authors (e.g., Bertrand & Betschinger, 2012; Erel et al., 2012; Grigorieva & Petrunina, 2015). The average abnormal return on the day of the announcement is -1.38% at a significance level of 5%. In addition, cumulative abnormal returns on a three and two-day event widows before and after the announcement are negative and statistically significant at 10% level showed that M&A announcements in emerging capital markets are, on average, regarded by the investors as value destructive. It appeared to be that size of the target, bids of privately owned targets and diversified structure of the bidder are statistically significant and have positive influence on the abnormal returns. On the contrary, acquisition announcement of high-tech and related targets is considered value destructive to the stock price of the bidder company. What is more interesting, it was expected that cultural proximity would have a positive influence, however, this determinant had the opposite, namely negative, impact on CAR. As expected, level of control obtained by the bidder has positive influence on the return. Other factors, such as international experience and prior presence in the target market appeared to be statistically insignificant. One of the limitations mentioned is that results obtained for the emerging markets are based on the regional concentration of the Latin America companies and inclusion in the sample such influential emerging capital markets as China, India, Russia might offer a more comprehensive overall picture. Third, in this article is analysed only the effect on the bidder, however, combined value of the bidder and target might be different.

Erel et al. (2012) analyzed the impact of M&A announcements on the merger sample obtained from Security Data Corporation’s (SDC) Mergers and Corporate Transactions database consisting of 56,978 cross-border M&A announcements made from 1990 to 2007 outside of the USA. As previous authors did (Aybar & Ficici, 2009), in this paper was identified that M&A announcements cause negative stock price changes, namely coefficients on the mean stock return are negative and statistically significant. Coefficients of international experience obtained in odds are statistically insignificant, apart from previous studies, similarities in language and religion have positive coefficients, however, are statistically insignificant. As expected, geographical proximity coefficients are positive and statistically significant at 1% level in all sub-groups except for public target and private acquirer. What is more, average currency coefficients are positive and statistically significant at 5% level in subgroup public target and public acquirer and at 1% level in all other subgroups. Finally, such economic factor as income tax rates has positive coefficients and is statistically significant in all sub-groups at 1% confidence level. As a conclusion, the authors summarize that geography and economic similarities matter.

Pereira et al. (2021) explored the impact of M&A announcements on the merger sample collected Zephyr and the Orbis database comprising 8,078 cross-border M&A announcements made by 43 emerging countries from 2006 to 2015. Surprisingly, this is one of few papers which included majorly not only China and India, but in this sample large part of announcement were made by Russia as well. This notion is vital because Russia as emerging capital markets is not up-to-date analyzed by the subject of M&A deals. Overall, as previous authors, it was found that M&A deals impact annual return on assets of a bidder company (Erel et al., 2012; Aybar & Ficici, 2009). As expected, coefficients of experienced and state-owned bidders are positive and statistically significant at 1% level. The same is obtained about the firm size, firm age, tangible assets and annual cash flows. In such model around 70% of dependent variable is explained in terms of chosen independent variables, this means that 30% left are explained by the other factors - still obtained percentage is quite substantial. Finally, the authors mention that in the conducted study the majority of ownership stakes included 100%, however, different stakes may reveal different results.

Chikamoto and Takeda (2016) studied the difference in impact M&A deals create in case of developing and developed countries-acquirors involved. The sample includes 385 US-Japan M&As and 103 China-Japan M&As. Event-windows analysed: (-1;1), (0;+1), (0;-2, (0;-3), (-1;+3). Overall, it was found that M&A deals have positive impact on firm value and the effect is greater in case of the acquiror from the developed country. Further, it was found that such determinant coefficients as price-to-book ratio of the target firm, target’s rate of return on total assets and target classified as manufacturing are, even though positive, statistically insignificant. On the other side, capital participation and management structure are statistically significant on all event widows for both models. However, authors state that for future research determinant measuring management structure should be studied in more detail. Overall, developed capital markets create more value in comparison to the developing ones. Still, developing markets should be analysed in greater detail.

Danbolt and Maciver (2012) investigate into the difference between the impacts of cross‐border and domestic M&A deals on cumulative abnormal returns of firms into and out of the UK. Data were obtained from the Thomson Financial SDC Mergers Database, the final sample included 251 targets and 146 bidders in the period from 1980 to 2008. In general, it was found that overall wealth creation is significantly higher in cross-border than in domestic acquisitions. Within the three-day event period cross-border acquisitions on average have positive significant 1.5 percentage impact on acquirer firm in comparison to domestic deals. Then, the authors add determinants. It was found that deals paid in cash provide bidders with positive cumulative abnormal returns with the statistical evidence of 5%. Relative size of the target is negative but statistically insignificant and relatedness of target and acquiror are positive but statically insignificant. As expected, stake acquired has a significant, positive impact on the cumulative stock return of the bidder company.

Mateev (2017) was aimed at investigating the impact M&A deals have on stock returns of acquiring firms located in the United Kingdom and continental Europe based on the sample of 2823 European acquisitions announced between 2002 and 2010. The event widows used [-5;+5], [-2;+2], [-1;+1], [-1;0)], and [-2;+1]. Overall, it was found that European acquirors earn positive abnormal returns as in domestic, as in cross-border acquisitions at 1% significance level. Surprisingly, cross-border wealth effect of M&A is not significantly contrasting between the UK and continental Europe. Further, the author adds determinants. Payment method, namely stock or cash or mixed, influenced abnormal returns, it was found that bidding companies as in the UK, as in CE have higher returns in case of equity payment in comparison to all other payment methods. The same effect is observed for the unlisted targets, abnormal returns are higher when stocks are used as a payment method. However, in case of listed target, the announcement effect is statistically significant at 1% and negative only for the stock offers. Solely, status of the target, namely listed or unlisted, the difference between the cumulative abnormal returns of listed and unlisted targets is highly significant in all event windows. On a three-day event window bidders acquiring listed targets earn negative abnormal returns, whereas bidders of unlisted realize significant positive return. Third determinant observed was industry relatedness of the target and bidder. In comparison to other authors, who stated that the same industry has negative effect (Aybar & Ficici, 2009), here the author found no empirical support that wealth effects are significantly influenced by the industry relatedness.

Bertrand and Betschinger (2012) state that despite the fact that emerging capital markets has shown a recent growth and that around one third of overall transaction activities volume took place in emerging capital markets, little explored about them in comparison to developed countries. What is more, UNCTAD published that by 2010 Russia took the 7th place in outward direct foreign investment flows, still Russia much less is known about its M&A transactions is comparison to China, for example. Using Bureau Van Dijk Zephir was collected a sample of 609 Russian firms that have acquired target firms at home or abroad during 1999-2008 period. Overall, solely M&A deals appear to be value-destructive or at least no-value-adding. However, additional context matters a lot. In case of cross-border acquisition the acquisition effect is no longer significant. It was found that on average hi-tech firms provide acquirors with positive abnormal returns in case of cross-border acquisitions more than in domestic ones. What is more, firm operating in natural resource industry also provides statistically significant positive abnormal returns. This determinant is important to be considered in the Russian Capital Market because natural resource industry is an influential one in Russia.  However, in comparison to previous authors, state-ownership even though is positive, has not proved to be statistically significant. What is more, size of the firm has positive statistically significant effect only in case of domestic deals. Finally, authors state main limitations, one of them is that the majority of acquirors are unlisted firms, therefore, the results may be not so representative. Anyway, authors state the need for policy reforms in order to gain more in terms of growth, competitiveness and value creation from M&A deals.

Rani et al. (2012) investigate the impact M&A have on bidder’s wealth on particular case of India, emerging capital market country. Sample was obtained from Thompson SDC Platinum data base and finally included 268 M&A domestic announcements during 2003 - 2008 period. Event windows were [-20; -2], [-1; +1)], [-1; 0], [0; +1], [-2; +2], [-5; +5], [-10; +10], [-20; +20], and [-2; +20)]. Overall, it was found that domestic M&A announcements generate positive abnormal return of 1.04% on the day of announcement significant at 1%. The same positive effect is observed in pre-event and short-event widows; however, acquisitions reduce acquiror’s wealth in post-event window. Moreover, cash payment method results in higher statistically significant returns in short pre-event windows. However, acquisitions financed with stocks also result in positive but statistically insignificant returns for the bidders. So, it can be stated that domestic acquisitions financed with cash experience higher returns than those financed with stock. Also, it was observed that bidders targeting unlisted organizations earned higher returns in comparison to those acquiring listed ones. The main limitation of this study is that it observes only short-time effects.

Overall, indeed, in practice M&A deals have different impact on stock return: positive (e.g., Chikamoto et al., 2016; Danbolt & Maciver, 2012; Mateev, 2017; Pereira et al., 2021; Rani et al., 2012) and negative (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Erel et al., 2012; Grigorieva & Petrunina, 2015). The most common determinants are type of payment (e.g., Danbolt & Maciver, 2012; Mateev, 2017), target status (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Mateev, 2017; Rani et al., 2012), relatedness of the industry (e.g., Aybar & Ficici, 2009; Danbolt & Maciver, 2012; Mateev, 2017), presence of the state ownership (e.g., Bertrand & Betschinger, 2012; Chikamoto et al., 2016; Pereira et al., 2021), prior experience (e.g., Aybar & Ficici, 2009; Erel et al., 2012; Pereira et al., 2021; Rani et al., 2012), hi-tech industry (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012), and volume of stake acquired (e.g., Danbolt & Maciver, 2012; Pereira et al., 2021). Apart from this, Erel et al. (2012) focus mostly on cultural proximity including language and religion; and economic including similar tax systems and exchange rates. What is more, Bertrand and Betschinger (2012) add one more determinant particularly for Russia - natural resource industry. All in all, not only plain effect of M&A differs from sample to sample but also impact of determinants varies.

In allowance with literature review conducted, the hypotheses are stated:

Hypothesis 1: M&A deals create significant abnormal returns on stocks of bidder companies in the Russian Capital Market.

Hypothesis 2: Determinants have significant impact on the abnormal returns on stocks of bidder companies in the Russian Capital Market.

2.1. Status of the target has a significant impact on the abnormal returns of bidder companies in the Russian Capital Market analysed within event windows.

2.2. The percentage of stake acquired has a significant impact on the abnormal returns of bidder companies in the Russian Capital Market analysed within event windows.

2.3. Resource-based industry type has a significant impact on the abnormal returns of bidder companies in the Russian Capital Market analysed within event windows.

2.4. Type of payment has a significant impact on the abnormal returns of bidder companies in the Russian Capital Market analysed within event windows.

 2.5. Presence of state ownership has a significant impact on the abnormal returns of bidder companies in the Russian Capital Market analysed within event windows.

Methods and Data

Sampling

This paper investigates into the analysis of M&A deals performed from 2010 to 2019 on Russian capital market.  Data were obtained from Bureau van Dijk Zephyr database. The following criteria were used to form a sample:

1. Publicity of deal participants: listed acquiror, any target, any vendor

2. Percentage of stake: Percentage of final stake (min: 25%)

3. Deal type: Acquisition, Merger, Minority stake

4. Current deal status: Announced, Completed, Rumour

5. Time period: from 01/01/2010 to 31/12/2019

6. Country of acquiror: Russian Federation (RU)

7. Deal value (m USD): min=10 (including estimates)

In more detail, the main criterion was public type of the acquiror because in case acquiror is private then it has a right not to disclose its financial reports. Regarding the percentage of stake, the minority stake is considered to a stake less than 50%. The reason is that starting from 25% the acquiror gains extra right to block the decisions of other shareholders. Deal type chosen was merger, acquisition, and minority stake, and all of them will be analysed together. In the current deal status not only “completed” but also “announced,” and “rumour spread” were included. In the sections above it was described that stock prices reflect information available on the market, so even anticipated events impact stock returns. Time period was limited to 10 years because prior to 2010 there was an economic crisis of 2008, and after 2019 exogenous factors, which are difficult to measure, happened in the face of covid pandemic and further economic crisis. The following term paper is aimed at analysing Russian Capital Market; the country was chosen to be Russia. The minimal deal value was chosen to be 10’000’000 USD to access the impact of M&A deal on large market acquirors (Cui & Leung, 2020). Finally, if firms undertake multiple deals within one year or if events confound, such events were deleted. The reason for exclusion of second and later deals within one year period is that it is impossible to analyse the impact of those deals as stock prices have been already affected by an earlier deal performed in that year. However, if second deal was performed in the second year, so that one year gap exists, then the second deal was not excluded.

Overall, the above criteria shrink sample to 53 deals. Corporate Finance Institute states that sample size, which has 30 and more observations, is considered sufficient to obtain statistically significant results under Central Limit Theory (CFI, 2022). The process of sampling in presented in Appendix 1.

In order to perform event studies analysis stock returns were retrieved from Yahoo! Finance. Adjusted close prices were used one year prior to the deal and within event windows.

According to the hypotheses stated, the following determinants were chosen: presence of state ownership, resource-based industry, status of the target, the percentage of stake, and type of payment. Needed data were obtained from Bureau van Dijk Zephyr database.

Variables

Below the variable list is presented (Table 1).

Table 1.

Variable definitions. Available from: Bureau van Dijk Zephyr

Variable

Definition

- cumulative abnormal return of each stock in event windows

log_value

- natural logarithm of deal value

target_status

- target status. Binary variable: takes value 1, if target is listed and takes value 0, if target is unlisted

stake_25_50

- percentage of stake. Binary variable: takes value 1, if stake %; 50%] and takes value 0, if stake is any other. This variable is used as a base.

stake_50_100

- percentage of stake. Binary variable: takes 1, if stake (50%; 100%) and takes value 0, if stake is any other

stake_100

- percentage of stake. Binary variable: takes value 1, if stake is 100% and takes value 0, if stake is any other

resource

- type of the industry. Binary variable: takes value 1, if either acquiror or target operates in resource-based industry and takes value 0, if industry is any other

cash

- type of payment. Binary variable: takes value 1, if deal was paid in cash and takes value 0, if other payment method was used

gov

- presence of state ownership. Binary variable: takes value 1, if government took part in the deal and takes value 0, if no government was presented

 

The final econometric equation is the following: .

Further, the descriptive statistics is calculated (Table 2).

Table 2.

Descriptive statistics. Available from: Bureau van Dijk Zephyr

    Variable |        Obs        Mean    Std. Dev.       Min        Max

-------------+---------------------------------------------------------

   log_value |         53    4.466412     1.71488   2.302585   9.641741

target_sta~s |         53    .9245283    .2666788          0          1

 stake_25_50 |         53    .0566038    .2332953          0          1

stake_50_100 |         53    .3962264    .4937931          0          1

   stake_100 |         53    .5283019    .5039755          0          1

-------------+---------------------------------------------------------

    resource |         53    .3773585    .4893644          0          1

        cash |         53    .4339623    .5003627          0          1

  government |         53    .6037736    .4937931          0          1

 

Within the sample obtained, the majority of targets obtained are listed, 92%, the rest of 8% are unlisted targets. Regarding the percentage of stake acquired, the majority of volume, 53%, was 100%, 40% are deals with the volume deal from 50% to 100%, and 6% of deals’ volume was from 25% to 50%. Volume from 25% to 50% is used as a base for the percentage of stake acquired variable. Acquisition stake volume was unknown for one deal. Further, above one-third of deals performed were related to the resource-based industry, such as gas, oil, and metal-related field of operations. Further, regarding the type of payment, 43% of deals were paid with cash, the rest of deals were paid with the other types of payment, such variable as other is used as a base. Finally, more than half, namely 60% of deals, included such intermediatory as government. Data required to separate the variables within groups chosen were obtained from Bureau van Dijk Zephyr.

Methodology

The main goal of this paper is to measure the effect such investment strategy as M&A deal has on the value of acquirer firm. Based on the literature review conducted the majority of the authors utilized event studies method (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Chikamoto et al., 2016; Danbolt & Maciver, 2012; Mateev, 2017; Rani et al., 2012; Zhu et al., 2021).

Event studies method measures the impact of a specific event on the value of a firm (MacKinlay, 1997). It is based on the aforementioned efficient market hypothesis given that the effects of a certain event will be reflected in stock prices (Fama, 1970). As stated earlier, in theory M&A deals should create value for acquirers. To assess the impact of M&A deals and determinants it is assumed that the influence of exogenous factors is insignificant. The price movement is caused by the event of interests, and thus leads to abnormal return.

The first date when the market participants are informed about the event, namely announcement of M&A deal or deal itself, is called date of the event. The data of the event is specified as “0” in the timeline of this study. It is worth noticing that prior to the date of the event no other events within one year have happened and there are no confounding events at the same time. In accordance with date of the event, estimation and post-estimation periods are stated. Estimation period is described as time period prior to the event. In the estimation window return of the stock not affected by the event is calculated. The considered estimation window is 260 days (-280; -20). In the post-event window return of the stock affected by the event is calculated.

According to the literature review, authors used different event windows. The most common ones include [-5; +5], [-2; +3], [-3; +1], [-2; +2], [-2; +1], [-1; +3], [-1; +1], [-1;0], [0; +1], and [-10; +10] (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Chikamoto et al., 2016; Danbolt & Maciver, 2012; Mateev, 2017; Rani et al., 2012; Zhu et al., 2021). Rani et al. (2012) have also observed longer event window [-20; +20], but MacKinlay (1997) stated that shorter intervals provide observers with higher power gains. Indeed, Rani et al. (2012) have observed insignificant impact of determinants on this event window.

After particular event windows are determined, rates of return for each stock in each day of the estimation window (-280; -20) and event window (-10; +10) are calculated.

,                                                                         (1)

where: t = [-280; +10];

i – the i-th stock;

– the initial stock price in the day (t-1);

  – the stock price in the day t.

After actual daily rates of return for each stock are calculated (Formula 1), in accordance with the efficient market model approach, expected return on asset of the market portfolio should be calculated using Capital Asset Pricing Model (Sharpe, 1964). Then, using Ordinary Least Squares regression (OLS regression), and  will be estimated using data about stock and index returns within estimation window. states how much on average the stock price changed when the market index was unchanged, and  reflects how much extra the stock price moved for each 1 percentage point change in the market index. These imply that variable of interest is stock return and independent variable is market return.

,                                                            (2)

where: t = [-280; -20];

 – constant term for the i-th stock;

 – the market beta of the i-th stock;

 – the market returns in t;

 – an error term, assume that  for each stock.

Then, after the exact and  for each deal one year prior to the event of interest are calculated (Formula 2), estimated rate of returns, namely the one in case no shock occurs, for each stock for the chosen event windows are calculated (Formula 3).

 =  ,                                                               (3)

where: t = [-10; +10];

– the expected constant term for the i-th stock;

 – the expected market beta of the i-th stock;

 – the market returns in t.

Further, abnormal returns are calculated as the difference between daily returns in event window and the estimated daily returns if no shock occurred in the event window (Formula 4).

,                                                              (4)

where: t = [-10; +10];

 – actual rate of return for the i-th stock;

 – expected rate of return for the i-th stock.

The abnormal return (Formula 4) is described as premium caused by the event of interest, namely M&A deal. As stated earlier, it is assumed that on such narrow event windows other exogeneous factors, whose impact is difficult to measure precisely, are assumed not to affect stock prices, thus abnormal returns reflect the impact of M&A deal. In order to have aggregated abnormal returns for each firm cumulative abnormal return (CAR) concept is used.

,                                                        (5)

where:  – the beginning of the event window;

 – the end of the event window;

 – the abnormal return for the i-th stock.

After CARs are calculated (Formula 5), the statistical significance of these results should be evaluated for each of analysed event window. According to MacKinlay (1997), if the distribution of CARs follows normal distribution with a mean in zero, then those M&A deals do not significantly influence stock prices (Formula 6). Further, only impact of determinants on sample of CARs with a shifted mean will be analysed.

,                                                (6)

For each of the significant CAR, which further will be notated as , will be estimated the impact of M&A deal determinants, which further will be notated as , on cumulative abnormal returns and its significance, using OLS regression (Formula 7).

where: j –the event window;

z – the determinant.

Results

The entire sample was analysed, first, on the subject of impact of M&A deals on the stocks return of bidder companies and, second, on the subject of M&A determinants on the stocks return of bidder companies. Determinants included logarithm of deal value, target status – whether the acquired firm is listed or unlisted, volume of stake acquired – percentage strake of 25 to 50 percent was taken as a base and percentage strake of 50 to 100 percent and 100 percent were analysed, resource – whether a target or an acquiror perform in the natural-resources industry as oil, gas, or metal-related field of operations, cash – whether deal was financed by cash or other type of payment, government – whether government acquired some percentage of stakes in acquiror firm.

Table 3.

CARs of the shareholders of acquiring firms for different event windows

Event window

Abnormal return’ mean

t-statistic (p-value)

95% Conf. Interval

[-5; +5]

.0235841

0.0306 *

[.0022904;.0448778]

[-2; +3]

.022287  

0.0258 *

[.0028008;.0417731]

[-3; +1]

.0047619

0.4941

[-.0091143;.018638]

[-2; +2]

.021937

0.0304 *

[.0021577;.0417163]

[-2; +1]

.0056428

0.3724

[-.0069412;.0182269]

[-1; +3]

.0233608

0.0130*

[.0051322;.0415893]

[-1; +1]

.0067167 

0.2582

[-.0050737;.018507]

[-1; 0]

.0033899

0.4852 

[-.0062864;.0130663]

[0; +1]

.0064045 

0.2446

[-.0045145;.0173236]

[-10; +10]

.0131305

0.1897

[-.0165855;.0428466]

* denotes significance at 5% significance level

 

To begin, cumulative abnormal returns for varying event windows have been analysed on the subject of its distribution mean value shift from the zero. The considered event windows were [-5; +5], [-2; +3], [-3; +1], [-2; +2], [-2; +1], [-1; +3], [-1; +1], [-1;0], [0; +1], and [-10; +10]. Using t-student distribution in STATA, it was found that 4 out of 10 considered event windows are statistically significant at 5% level. According to means of those CARs, it can be stated that M&A deals have on average positive significant impact on CARs. In more detail, it can be said that acquirer shareholders experience CARs of 2.36% during event window of 11 days [-5; +5], of 2,3% during event window of 5 days [-1; +3], and of 2,2% during event windows of 6 and 5 days [-2; +3] and [-2; +2]. All of these results are statistically significant at 10%. However, the results are not significant at the same period of 5 days in event window [-3; +1], at shorter event windows of 4 days [-2; +1], of 3 days [-1; +1], and of 2 days [-1;0] and [0; +1] and during event window of 10 days [-10; +10]. Overall, there is no statistical evidence to reject the first hypothesis for event windows [-5; +5], [-2; +3], [-2; +2], [-1; +3].

Further, to test the second hypothesis on the significance of the impact of determinants in the cumulative abnormal returns of bidder companies OLS regressions were constructed for each of the significant event windows.

Table 4.

Regression results

----------------------------------------------------------------------------

                      (1)             (2)             (3)             (4)  

                  CAR_1_3         CAR_2_2         CAR_2_3         CAR_5_5  

----------------------------------------------------------------------------

log_value          -0.003          -0.002          -0.003          -0.003  

                  (0.005)         (0.005)         (0.005)         (0.006)  

 

target_sta~s        0.007           0.012           0.009          -0.033  

                  (0.033)         (0.037)         (0.036)         (0.040)  

 

1.stake            -0.001           0.012           0.010          -0.025  

                  (0.034)         (0.038)         (0.037)         (0.042)  

 

2.stake             0.067*          0.080**         0.079**         0.048  

                  (0.034)         (0.038)         (0.037)         (0.041)  

 

resource           -0.026          -0.017          -0.015          -0.022  

                  (0.017)         (0.019)         (0.019)         (0.021)  

 

cash               -0.006           0.000           0.000          -0.022  

                  (0.017)         (0.019)         (0.019)         (0.021)  

 

government         -0.040**        -0.046**        -0.049**        -0.045**

                  (0.018)         (0.020)         (0.020)         (0.022)  

 

_cons               0.033           0.008           0.015           0.097  

                  (0.048)         (0.053)         (0.052)         (0.058)  

----------------------------------------------------------------------------

N                  53.000          53.000          53.000          53.000  

r2_a                0.235           0.193           0.210           0.167  

F                   3.279           2.779           2.977           2.493  

aic              -144.353        -132.895        -135.602        -123.402  

bic              -128.591        -117.133        -119.840        -107.640  

----------------------------------------------------------------------------

Standard errors in parentheses

* p<0.10, ** p<0.05, *** p<0.01

 

It was found that 100% volume of stake, namely full acquisition, has positive effect on stock returns of the bidder companies in Russian Capital Market. It was identified that full acquisition creates on average 0.7 additional percent points for the shortest event window of [-1; +3] to CARs in comparison to the effect of minority stake, which is used as a base in this regression model; this result is significant at 10% level. Further, on the event window of [-2; +3] and [-2; +2] firms, practicing full acquisition, obtain on average 0.8 additional percent points to their CARs in comparison to firms, acquiring minority stakes; these results are statistically significant at 5% level. On contrary, the results on longer event window of [-5; +5] are statistically insignificant; no significance has been shown for 50 to 100 percent volume of stake acquired. Overall, there is no statistical evidence to reject the hypothesis that volume of stake acquired impact stock returns of bidder companies for 100% volume of stake acquired for three shorter event windows: [-1; +3], [-2; +2], and [-2; +3].

Further, such determinant as presence of state ownership has also significant impact on share returns of bidder companies. In more detail, the regression has revealed that presence of government on average reduces cumulative stock returns by 0.4 percent points at 5% level on event window [-1; +3] and by 0.5 percent points at 5% level on event windows [-2; +2], [-2; +3], and [-5; +5]. Overall, there is no statistical evidence to reject hypothesis that presence of state ownership has significant impact on stock returns of bidder companies for event windows: [-1; +3], [-2; +2], [-2; +3], and [-5; +5].

What is more, the regression model of the shortest event window [-1; +3] has appeared to be the most statistically significant among others: adjusted R^2 is the highest, this means that 24% of dependent variable is explained by independent, namely 24% of CAR on [-1; +3] event window is explained by the chosen variables. This means that there are other factors, which are not included in the model, but influence CAR. Also, Akaike's Information Criteria (AIC) and Bayesian Information Criteria (BIC) are also the lowest in this model in comparison to the other. Additionally, F-statistic is the highest in this model among the other.

Overall, there is no statistical evidence to reject the first hypothesis that M&A deals have positive effect on stock returns for the bidder companies for event windows [-5; +5], [-2; +3], [-2; +2], and [-1; +3]. In addition, 100% of stake acquired impact positively stock returns of acquiror companies for event windows [-1; +3], [-2; +2], and [-2; +3], and presence of state ownership has negative effect on stock returns of bidder companies for event windows [-1; +3], [-2; +2], [-2; +3], and [-5; +5].

Discussion

The obtained results coincide with the prior research.  Discussed in literature review, firms strive to achieve maximum profit, this can be done by certain investment activities, and one of such activities is M&A deal.

It was identified that on average M&A deals performed in Russia have positive impact on share returns of bidder companies, and these results are significant at 5% confidence level for the following event windows: [-5; +5], [-2; +3], [-2; +2], and [-1; +3]. These outcomes are consistent with the primary goal of investment strategy (Risberg, 2003). In addition, the other authors obtained the same empirical results that M&A deals have positive effect on profitability of the acquiror firm (e.g., Chikamoto et al., 2016; Danbolt & Maciver, 2012; Mateev, 2017; Pereira et al., 2021; Rani et al., 2012). Danbolt and Maciver (2012) and Mateev (2017) investigated developed economies, Pereira et al. (2021) had a large sample of emerging capital markets, Rani et al. (2012) analyzed Indian market solely, and Chikamoto et al. (2016) had a sample, which included as developing, as developed economies, but the author stated in the limitations that the number of countries from each of these two categories were not equal, thus her paper represents majorly developed capital markets. In contrary, the positive impact of M&A on effect on stock returns for the bidder companies in Russia is the opposite to other authors’ findings (e.g., Aybar & Ficici, 2009; Bertrand & Betschinger, 2012; Erel et al., 2012; Grigorieva & Petrunina, 2015). Aybar and Ficici (2009) analysed emerging market multinationals, Bertrand and Betschinger (2012) analysed Russian capital market solely in two periods of 2001-2006 and 2007-2008, Erel et al. (2012) investigated into cross-border M&A in the USA, Grigorieva and Petrunina (2015) observed emerging capital markets. What is more, result of identified significant event windows is constant with the outcomes of Rani et al. (2012), who also observed significant CARs only on the shorter event windows.

In addition to impact of M&A deals, additional impact of M&A determinants was analysed. It was identified that 100% volume of stake, full acquisition, has on average positive effect on stock returns of the bidder companies in Russian Capital Market at 5% level for event windows [-2; +3] and [-2; +2] and at 10% level for event window [-1; +3]. These outcomes are consistent with the findings of Aybar and Ficici (2009). The authors investigated the capital markets of developing economies and identified that level of control obtained by the bidder has positive influence on the return. However, the sample focused Latin America companies, and thus did not include China, India, and Russia. The authors state that inclusion of other developing countries would provide a more comprehensive outcome. Moreover, the obtained results of this paper regarding such determinant as full acquisition reflect outcomes of Pereira (2021), who observed M&A announcements made by 43 emerging countries. However, as one of the limitations the author stated that the majority of stakes acquired were 100%, thus if the distribution of volumes were more balanced, different results might have been obtained.

The next determinant, which appeared to be statistically significant, was presence of state ownership. There is no statistical evidence to reject hypothesis that presence of state ownership has significant impact on stock returns of bidder companies for event windows: [-1; +3], [-2; +2], [-2; +3], and [-5; +5]. These findings contradict with the results obtained by Pereira et al. (2021). The author claims that presence of state ownership has on average positive effect statically significant at 1% level at the sample of 53 emerging countries, which included Russia. The negative effect of state ownership in Russian market can be explained by the MIGA’s Political Risk Survey: the survey states that political regime and government transparency are crucial factors for the investors.

Conclusion

Overall, this paper examines the stock price performance of 53 Russian companies engaged in M&A during 2010–2019.

Using event studies methodology, this study finds evidence that the shareholders of acquirer Russian corporates, engaging in M&A deals, on average experience positive abnormal returns within event windows [-5; +5], [-2; +3], [-2; +2], [-1; +3]. In addition, the firms, acquiring 100% of targets, within event windows [-1; +3], [-2; +3], and [-2; +2] on average experience higher statistically significant returns in comparison to those firms, acquiring minority stake. Further, presence of state ownership decreases returns of the acquiror within event window [-2; +3], [-2; +2], and [-1; +3].

Limitations of the research include, first, availability of public acquirors only. If the research gained data about not only public acquirors but data on deals conducted by the participation of non-public companies, the results might be different. Second, the inclusion of more deals into sample will also increase explanatory power of the model (Murphy et al., 2014). Third, due to the percentage of dependent variable explained in terms of independent, omitted variable bias exists, thus addition of intersections of variables, as it was in the paper of Bertrand and Betschinger (2012), would enhance the model. Finally, different approach, for instance evaluation of accounting reports performed by Grigorieva and Petrunina (2015), may reveal different results.

Overall, this paper updates available scientific knowledge about the Russian market, allows company owners and top managers to develop the further strategy of the company's behaviour after the M&A announcement or the completed transaction, and provides avenue for the further research of M&A transactions in Russia. 

Appendix 1

Sampling strategy

Criterion

Search result

Listed/Unlisted/Delisted companies: listed acquiror, any target, any vendor

376,757

Percentage of stake: Percentage of final stake (min: 25 %)

220,494

Deal type: Acquisition, Merger, Minority stake

183,037

Current deal status: Announced, Completed, Rumour

177,077

Time period: from 01/01/2010 to 31/12/2019

105,903

Country (primary addresses): Russian Federation (RU)

2,393

Deal value (m USD): min=10 (including estimates)

552

Deals by one acquiror performed once within one year

287

No confounding events

53

Final result

53

Sampling strategy. Available from: Bureau van Dijk Zephyr.

 

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