Keywords

Mergers, Acquisitions, Non-Performing Assets, Banking Sector, Wilcoxon Signed-Rank Test and Financial Performance.

Introduction

The Indian banking industry is making a significant impact on the country's economic growth via helping to mobilize funds and direct investments to sectors that are short on capital. Financial institutions have increasingly relied on mergers and acquisitions (M&As) as a means to increase stability in the industry by gaining a stronger market position and realizing synergies. The efficacy of mergers and acquisitions in accomplishing these aims is a topic of continuing debate among academics, researchers, and government officials. Due to the significant changes that have taken place in this sector over the years, mergers and acquisitions have been crucial in the consolidation, expansion of the market, and improvement of efficiency within the Indian banking industry. Over the last two decades, there has been a great deal of transformation inside the Indian financial industry. In terms of adaptability and innovation, the Indian banking industry is moving at a dizzying rate (Khan, 2011). A new trend that is picking up steam is the increasing number of mergers and acquisitions in India's banking sector. Financial institutions are showing similar trends in their merger activity, and acquisitions in the banking industry point to a kind of horizontal integration. Financial industry mergers and acquisitions, say (Sai & Sultan, 2013), may cut costs, boost operational efficiency, and eliminate competitors from the market, all while making banking less competitive.

To better compete in today's global market, banks are increasingly turning to mergers and acquisitions (M&A) as a strategic financial engineering tool for reorganization and consolidation. Gaining access to new markets, increasing customer bases, ensuring long-term revenue, and optimizing economies of scale are all part of this strategy's aims. In (Gupta, 2015) this study looks at the impact that mergers and acquisitions have on the financial performance of a group of Indian banks and how they relate to one another. Although several methods exist for keeping a close eye on the performance of the financial industry, banks often use mergers as their primary tool. Merging two smaller institutions or weak into strong banks is a viable option to explore when looking to increase income. It's a more reasonable and cost-effective way as compared to typical organic expansion. Achieving size and broad efficiency is the primary goal of mergers and acquisitions in the financial industry. (Singh & Das, 2018) state that purchases reduce risk and boost the output of a broader variety of products. Research from (Arocena, Pérez & Castillo, 2020) indicates that mergers and acquisitions significantly impact a company's economic success and general health because of their versatility as a cost optimization strategy. In addition to the benefits of business development, essential skills, and efficiency improvements for enterprises engaging in strategic acquisitions, there have been significant contributions to the rapid emergence of new investment opportunities (Khan, Sheikh & Raza, 2020).

Mergers should give careful consideration to human capital, according to (Sanda & Benin, 2011). The merger's long-term viability is at risk if these concerns are not adequately addressed, as they might negatively impact employee happiness and well-being. According to (Gutknecht & Keys, 1993), after the merger and acquisition, staff members were more productive. (Cornett & Tehranian, 1992) reported that between 1982 and 1987, researchers were looking at post-acquisition performance and found that staff productivity increased due to mergers and acquisitions. (Siegel & Simons, 2010) discovered that even when ownership changed because of mergers and acquisitions, business performance remained constant because of improved resource allocation and staff alignment due to more successful applications. Allocating resources and workers becomes more efficient with these moves. Organizations from poor countries who take part in CBMA mostly create value, according to (Du & Boateng, 2012), in contrast to their peers in developed market economies, where different experts have found mixed results when it comes to buying companies. Companies in affluent market economies create value in a very different way.

According to research by (Bhaumik & Selarka, 2008), corporate performance in India fell between 1995 and 2002 as a result of mergers and acquisitions. This was especially true for family-owned and group-affiliated enterprises. India also saw this downward trend. Reducing owner-manager agency issues has favorable aspects, while entrenchment between the two has more negative consequences. However, due to the high concentration of family ownership and group connections in Indian enterprises, mergers and acquisitions failed to increase shareholder value. The concentration of ownership in Indian enterprises leads to insider entrenchment, which hinders the purpose of providing the company with the maximum potential value. Accounting and stock market performance indexes, according to (Khanna & Palepu, 2000), show a decline as group diversity increases, but an uptick as diversity beyond a certain point. Accounts and stock market indices were also affected by M&A. According to (Roy, 1999), there were no substantial changes in the rate of return and profit margin between the periods before and after M&A. These results indicate that management's desire to maximize their own gain drove the merger. The acquiring business did not reap undue financial benefits from the combination, according to other studies (Pawaskar, 2001). In a comprehensive analysis, (Beena, 2006) found that the merged companies outperformed both their competitors and themselves before the merger in terms of gross and net profit margins, return on capital employed, return on net worth, R&D intensity, cost intensity, export intensity, and import intensity.

Financial organizations namely “SBI, BOB, CBI, IB, UB, and PNB” are used to carry out this research. Part of the financial statements included in this analysis are based on secondary data that was gathered from RBI websites and NSE. Financial statement analysis involves taking some critical factors into account namely, Dividends (Div), total revenue (TR), gross profit (GP), net profit (NP), interest income (II), interest from borrowings (IB), deposits (Dep), reserves and surplus (R&S), gross nonperforming assets (GNPA), and net nonperforming assets (NNPA) are all parts of this equation. Data about the stock price's closing before and after the merger and acquisition announcement is used in the study. When looking at the numbers, the Wilcoxon and Mann-Whitney tests come into play.

Literature Review

In the banking industry, mergers and acquisitions (M&A) are somewhat frequent as many companies want to combine in order to boost operational efficiency, expand market share, and take use of economies of scale. Mergers and acquisitions are therefore somewhat typical in the banking sector as this is why. Many studies have looked at how mergers and acquisitions (M&A) impact stock prices; many of them have concentrated on how the market responds fast to merger announcements. This literature study attempts to compile papers that investigate the effect of merger and acquisition announcements on the stock prices of Indian Banks (IBs) using statistical methods such the Wilcoxon Signed Rank Test and the Mann-Whitney U test. While the target companies' stock prices rise, (Mandelker, 1974) research shows that the stock values of acquiring companies go up, down, or remain the same based on the value of the merger. Though short-term volatility of stock prices is influenced by market expectations, (Bower, 2001) discovered that effective post-merger integration increases banks' long-term profitability. Masters Degree-bearing researchers (Nazir, 2010) looked at the Pakistani stock market's dividend policy. The study took advantage of 73 KSE-100 banks. Using panel data and fixed effect, random effect, and correlation models, the five-year study (2003–2008) came to this conclusion. Dividend policy is shown to be quite correlated with stock price volatility per data from the Karachi Stock Exchange. Dividend yield, payout ratio, and price volatility seem to have a negative association according evidence. Still, the size of the firm or the volatility of its profits had no effect on the price volatility. Though the impact was minimal, valuations did negatively affect leverage and asset growth.

Under the framework of the capital market, (Mishra, 2010) investigated macroeconomic and financial elements spanning thirty years. Scholars and researchers among other experts in the area have lately concentrated on the topic of the erratic gold price. This research aimed to provide the response, "What is the link between Indian "domestic gold prices and stock market performance?" Employing BSE 100 index data from 1991–2009, the study examined "Granger causality in the Vector Error Correction Model". The information given by every variable allows one to make predictions about the other variables. Using panel data spanning 2000 to 2009, (Nirmala, 2011) examined the factors affecting stock prices in three different Indian sectors—the automobile industry, the healthcare sector, and public sector enterprises. We rebuilt the ordinary least squares method from the ground up for this work. Dividends, price-to---earning ratios, and leverage were found to affect share prices in all three sectors. Within the automotive industry, shareholder profitability was the only element affecting share prices. (Malhotra & Tandon, 2013) contend that many factors influence the NSE 100 stock price. Examining 95 companies using data collected between 2007 and 2012, a linear regression model was used. Positively associated were the book value of the corporation, price-earning ratio, and earnings per share. Still, dividend yield and stock price rises had an adverse relationship.

(Naveed & Ramzan, 2013) investigated the market to see what influences stock prices. For fifteen listed banks, the Karachi Stock Exchange provided data ranging from 2008 to 2011. Whereas the independent factors were dividend yield, size, return on assets (ROA), and asset growth, the share price was the dependent variable. Consider the share price as the dependent variable. A fixed effects regression model tells us that company size favorably correlates with share price; we do not know what other connections the other components expose. (Vijayakumar & Krishnaprabha, 2015) explore the subject of personal risk-reward assessments. Smart investors, according to their studies, reduce losses and maximize gains. Sometimes taking a chance pays off. Investors have to welcome possibilities to increase income. Risk aversion drives poorer investment returns in the banking and automobile sectors. In the medical, fast-moving consumer products, and information technologies sectors, big profits with little risk are feasible. Fundamental analysis examines the many financial, economic, and industrial factors influencing the risk-return connection of assets thus guiding better investment decisions (Sodhi and Waraich, 2016). Stake in stocks and finances abound for Indian banks. Fundamental analysis offers information on the expansion and profitability of banks therefore enabling shareholders to make wise investment decisions. By use of fundamental analysis, investors may evaluate both present and future performance of financial organizations. The study made use of a broad spectrum of actual financial data to evaluate the fundamental strength of various big financial organizations.

H₀₁: Merger and acquisition information does not impact the financial performance of selected banks in India.

(Marvadi & Pandya, 2016) study focuses on the pricing of Indian shares. This study reached a result using a variant of modified ordinary least squares and panel data spanning 2010–2014. The data derived from the thirty financial organizations making up the BSE SENSEX. The factors influencing Indian stock prices are several and include profitability, leverage, price-to-earnings ratio, and dividends per share. Leverage and stock prices have a negative link as banks have to pay interest on borrowed money, which reduces investors' profits. Investors favored a situation devoid of debt. (Patjoshi, 2016) said that India's stock markets were a major determinant of the nation's economic development in 2016. The stock market of India is under the choke of the banking industry. Thirty banking equities traded on the Bombay Stock Exchange and the Sensex underwent a risk-return study. Regarding Indian finance, the Mumbai Stock Exchange was indispensable. Four separate banks—HDFC Bank, ICICI Bank, Axis Bank, and SBI—had their risk-return profiles compared to the Sensex by this study using their respective banking stock indexes. Other than taking public deposits, (Balaji & Kumar, 2016) note that banks are also charged with lending money to people, businesses, and even the government. Simply said, the success of the economy depends much on Indian banks. Every wise investor should aim to lower their loss margin and raise their profit margin. Profit and risk cannot be separated from one other. To find the spectrum of risk and return these Indian banks—public and private—were faced with was investigated. Using quota sampling and secondary data, the study team chose 34 public and commercial banks. All all, the research covers ten years, from 2006–2007 all the way up to 2015–2016. The study made use of data analysis methods like correlation and regression all around. Results revealed that private banks provided performance data more freely than those of state-run equivalents. (Pradhan, 2016) conducted one analysis examining stock prices of Nepalese commercial banks. 2016 marked the publishing year. The dependent variable of a study was the market price per share; the independent factors were the company's size, return on assets, book value per share, and price-earning ratio. Macroeconomics included GDP, inflation, and M2 taken all together. Data obtained from the annual report of the Nepal Rastra Bank as well as from those of other banks and financial organizations. (Ghosh, 2017) investigated the interaction between stock prices of Nepalese commercial banks and both firm-specific and macroeconomic factors using a range of mathematical regression models. Following an analysis of 63 firms' "capital structure on performance," financial managers were recommended to use prudence when choosing capital structures. There have never been any audits of the BSE SENSEX's banks. Finding whether the study supports or refutes earlier studies would be a fascinating project. According to (Sarkar & Sinha, 2017), the stock prices of the target banks surged when merger news leaked but the stock prices of the banks paying for the target banks did not change. Stock returns were measured fifteen days after the announcement. (Li, 2017) looked at the relevance of FinTech digital banking startups. Following investments in such companies, the research looked at the performance of 47 big US retail banks between 2010 and 2016. Its importance was underlined by both the amount of money and the count of completed FinTech transactions. Panel data regression is one approach to determine a relationship between this and stock returns. For conventional retail banks, investments and alliances with FinTech firms produced better stock returns. Though one-third of the banks had positive coefficients, there was no statistically significant variation between the two groups. Data gathered by the banking sector indicates that traditional banking and financial technology are incompatible.

In their analysis on dividend policy and share price volatility at a Mediterranean bank, (Camilleri, 2018) investigated sub-sample and outlier variances. With dividend yield and payment acting as proxies for dividend policy, a multiple-control-variable regression was used in the study to replicate volatility. We might build subsamples from the main data set and use cluster analysis to eliminate outliers arising during the financial crisis of 2007 in order to establish dependability. Whether or not outliers are incorporated into the analysis might affect the volatility and dividend policy. Examining the stock returns of fifteen mergers and acquisitions (M&A) agreements signed by Indian banks between 2000 and 2015, (Chand & Sharma, 2018) found While the stock prices of the purchasing companies exhibited flat to negative responses, the target banks' stock prices climbed in response to merger announcements. According to the study's findings, Indian investors value merger risks and integration expenses above anything else. In an article he wrote in (Reddy, 2018) explored the significance of payment banks in India and how they affected commercial banks. Commercial banks were assessed using the market model utilizing anomaly share returns. Using the event research methodology, one looked at the stock performance during the announcement. Examined in the study between June 2014 and August 2015 were daily results of 39 National Stock Exchange-listed banks: Similar findings came from studies on the association between Indian commercial bank stock prices and payment banks. According to (Kumar & Begum, 2020), businesses, industries, and trade are the basic institutions of any country; they are thus indispensable for contemporary commerce to work well. A nation needs easily accessible financial resources if it is to grow. Those with excess money save it; others apply for loans from banks. Since the COVID-19 epidemic, the importance of bank stocks has shifted dramatically. As the COVID-19 epidemic began to spread, the stock prices of major financial companies started to drop. In middle of March India officially announced the COVID-19 epidemic. The banking sector of the Indian stock market then steadily dropped. Thirty-three analysts investigated how COVID-19 affected equity in the banking industry. Eleven different banks listed on the BSE are the focus of the research. Details taken from the BSE website. This experiment tracked for 150 days the stock prices of different financial firms. We examined the stock price of one bank both before and after we started "COVID-19." Using this paired t-test, researchers sought to ascertain how "COVID-19" influenced stock prices. Following the COVID-19 epidemic, Indian public sector banks showed increase (Rawlin, 2021). Since public sector banks in India are less lucrative and have inferior assets than private sector banks, they have been bad for the economy. Deeper knowledge of the factors influencing the stock prices of publicly listed corporations helped to enable fundraising initiatives. The study examined public sector bank stock prices from 2006 to 2017 using macro and micro factors. Investigating the component-to---component link was done using a panel regression study. The accuracy of the model was ascertained using estimates derived from fiscal years 2018, 2019, and 2020.

According to their studies, "capital structure," another word for long-term financing, affects the market value of BSE SENSEX-listed banks. Noting this, the writers (Agarwal & Saxena, 2021) Between 2010 and 2019, all Indian banks listed on the BSE SENSEX had their capital structure investigated in a regression study to see how it affected share price. ANOVA's significance threshold of 5% let the data indicate that the model was sufficient. Based on the findings of this research, the stock prices of five BSE SENSEX-listed Indian deposit money banks show a clear association with capital structure. Data imply that bank value is influenced by capital structure. The report advised a maximum level of capital increase to protect the market value of the 'Indian Bank' (IB), listed on the BSE and SENSEX. Studies indicate that the Mergers and acquisitions in 2022 might either help or harm bank shareholders depending on their stock and market performance (Kush, 2022). Before and after the event, investigations were carried out including cumulative and aberrant returns (AR). Event-study research made it possible to examine anomalous findings and merger announcements. One hundred and twenty-two years ago this approach investigates five days previous to the merger and five days after it. Twelve merging and acquiring companies in all, running from 2017 and 2020, were chosen at random. Some analysts contend that mergers and acquisitions almost never result in an increase in shareholder value. Both the share price and cumulative abnormal returns (CAR) dropped before and after the transaction was completed. According to (Mamatha & Chundi, 2022), financial trading is an industry plagued with risk and markets react differently to both internal and outside influences. Further complicating the matter were many of these events beyond the control of potential donors. In the realm of securities trading, uncertainty rules. Studying financial transactions might help you to develop your abilities. A lot of factors affected the share price. These generally accepted elements affect the stock price. Different market interest levels might cause inventory costs to increase. Demand exceeding supply causes a rise in the price of bank shares; a decrease in price results from the converse.

H₀₂: Merger and acquisition information does not impact the stock prices of selected banks in India.

Though several studies have looked at how mergers and acquisitions affect Indian banks' performance, significant gaps in the body of current research persist. Most studies concentrate mostly on short-term price swings around the announcement date, paying little attention to long-term performance and the durability of stock price fluctuations after a merger. Furthermore, particularly in the Indian banking industry, the effects of investor mood and risk assessment on stock performance after mergers remain rarely studied. In the end, there is a dearth of comparative analysis between the banking sector and other sectors of Indian economy, therefore offering a more complete knowledge of the effects of mergers in other spheres of economy. Mergers and acquisitions throughout the years have thereby had an impact on the financial indicators and stock values of several "Indian Banks" (IBs). This research looked at their data both before and after the merger and acquisition on numerous financial aspects Figure 1.

Research Methodology

This research makes use of secondary sources. Stock prices from www.nseindia.com and financial statement information from www.moneycontrol.com are examples of secondary sources. Both of these were used in the information-gathering process. In this research, six different financial organizations are utilized: SBI, BOB, CBI, IB, UB, and PNB (Punjab National Bank). The analysis also takes into account the final stock values of these companies. Financial statement analysis primarily focuses on the following metrics: interest income (II), interest from borrowings (IB), total revenue (TR), gross profit (GP), net profit (NP), dividends (Div), borrowings (B), deposits (Dep), reserves and surplus (R&S), and gross nonperforming assets (GNPA) and net nonperforming assets (NNPA). To do this, the study makes use of sixteen quarters' worth of pricing, both before and after the merger or acquisition. This study begins with the date of the merger or acquisition and compares the stock prices of six separate banks fifteen times, both before and after the merger or acquisition. Two analytical approaches were used in the study project: the Wilcoxon Rank Test and the Mann-Whitney U Test. To broaden the scope of the investigation, nonparametric analysis was used. In order to find out how much of an effect information sensitivity has on the stock and financial performance of certain companies, several analyses were conducted. The following goals have been set in order to move the research forward:

• To research the influence that information on mergers and acquisitions has on the financial performance of several banks in India.

• To investigate the influence that information regarding mergers and acquisitions has on the stock prices of a selection of banks in India.

Results and Discussion

Mergers and acquisitions are often seen as a strategy that might reduce competition and enhance a bank's market capitalization. Consequently, they are crucial in assessing the organization's robustness. There is a prevalent concern that mergers and acquisitions (M&A) would significantly impact the financial performance of the firms involved. Numerous situations have been seen in which the assets and liabilities of merging institutions are transferred. This results in challenges and temporarily reduces the financial capacity of the parties concerned. None of the six banks named in Table 1 above are affected by mergers and acquisitions. The six banks are the State Bank of India (SBI), Bank of Baroda (BOB), Central Bank of India (CBI), Indian Bank (IB), Union Bank (UB), and Punjab National Bank (PNB). The estimated numbers are equal in each instance, indicating no change in the banks' financial behavior. All studied events had a significance value of 1, above 0.05. The null hypothesis, asserting that "Merger and acquisition information does not influence the financial performance of selected banks in India," is thus accepted, and it is anticipated that the impact on financial metrics would remain consistent.

Table 1 Stating The effect of M&A on Financial Statement using SPSS-21
‘Bank of Baroda’ (BOB)
	II	IB	TR	GP	NP	Div	B	Dep	R&S		GNPA	NNPA		Decision
‘Mann-Whitney U’	128	128	128	128	128	128	128	128	128		128	128		In all the cases retain the Null Hypothesis
‘Wilcoxon W’	264	264	264	264	264	264	264	264	264		264	264
‘Z’	0	0	0	0	0	0	0	0	0		0	0
‘Asymp. Sig.’ ‘(2-tailed)’	1	1	1	1	1	1	1	1	1		1	1
‘Exact Sig.’ ‘[2*(1-tailed Sig.)]’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’		‘1.00’	‘1.00’
‘Central Bank of India’ (CBI)
	II	IB	TR	GP	NP	Div	B	Dep	R&S		GNPA	NNPA		Decision
‘Mann-Whitney U’	128	128	128	128	128	128	128	128	128		128	128		In all the cases retain the Null Hypothesis
‘Wilcoxon W’	264	264	264	264	264	264	264	264	264		264	264
‘Z’	0	0	0	0	0	0	0	0	0		0	0
‘Asymp. Sig.’ ‘(2-tailed)’	1	1	1	1	1	1	1	1	1		1	1
‘Exact Sig.’ ‘[2*(1-tailed Sig.)]’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’		‘1.00’	‘1.00’
‘Indian Bank’ (IB)
	II	IB	TR	GP	NP	Div	B	Dep	R&S		GNPA	NNPA		Decision
‘Mann-Whitney U’	128	128	128	128	128	128	128	128	128		128	128		In all the cases retain the Null Hypothesis
‘Wilcoxon W’	264	264	264	264	264	264	264	264	264		264	264
‘Z’	0	0	0	0	0	0	0	0	0		0	0
‘Asymp. Sig.’ ‘(2-tailed)’	1	1	1	1	1	1	1	1	1		1	1
‘Exact Sig.’ ‘[2*(1-tailed Sig.)]’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’		‘1.00’	‘1.00’
‘Punjab National Bank’ (PNB)
	II	IB	TR	GP	NP	Div	B	Dep	R&S		GNPA	NNPA		Decision
‘Mann-Whitney U’	128	128	128	128	128	128	128	128	128		128	128		In all the cases retain the Null Hypothesis
‘Wilcoxon W’	264	264	264	264	264	264	264	264	264		264	264
‘Z’	0	0	0	0	0	0	0	0	0		0	0
‘Asymp. Sig.’ ‘(2-tailed)’	1	1	1	1	1	1	1	1	1		1	1
‘Exact Sig.’ ‘[2*(1-tailed Sig.)]’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’		‘1.00’	‘1.00’
‘State Bank of India” (SBI)
	II	IB	TR	GP	NP	Div	B	Dep		R&S	GNPA	NNPA	Decision
‘Mann-Whitney U’	128	128	128	128	128	128	128	128		128	128	128	In all the cases retain the Null Hypothesis
‘Wilcoxon W’	264	264	264	264	264	264	264	264		264	264	264
‘Z’	0	0	0	0	0	0	0	0		0	0	0
‘Asymp. Sig.’ ‘(2-tailed)’	1	1	1	1	1	1	1	1		1	1	1
‘Exact Sig.’ ‘[2*(1-tailed Sig.)]’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’		‘1.00’	‘1.00’	‘1.00’
‘Union Bank’ (UB)
	II	IB	TR	GP	NP	Div	B	Dep	R&S		GNPA	NNPA	Decision
‘Mann-Whitney U’	128	128	128	128	128	128	128	128	128		128	128	In all the cases retain the Null Hypothesis
‘Wilcoxon W’	264	264	264	264	264	264	264	264	264		264	264
‘Z’	0	0	0	0	0	0	0	0	0		0	0
‘Asymp. Sig.’ ‘(2-tailed)’	1	1	1	1	1	1	1	1	1		1	1
‘Exact Sig.’ ‘[2*(1-tailed Sig.)]’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’	‘1.00’		‘1.00’	‘1.00’

Table 2, Table 3 presents a comparative examination of data from six separate banks about stock prices, with statistics calculated for both pre- and post-measurement periods. The data for each bank includes the number of observations (N), mean, standard deviation, lowest and maximum values, as well as pre- and post-measurement rankings and sums of ranks. Beginning with the pre-measurement data, each bank provides the mean and standard deviation of the sample. Punjab National Bank (PNB) has a mean of around 64.37 and a standard deviation of 2.26, with sample values ranging from 59.40 to 68.10. Other banks, like Canara Bank and the State Bank of India (SBI), have increased mean values, with Canara Bank's mean at 211.59 and SBI at 272.13, reflecting differing measurement scales across the institutions.

Table 2 Stating the Effect of M&A on Stock Prices Using Spss-21
‘Banks’	‘N’	‘Mean’	‘Std. Deviation’	‘Minimum’	‘Maximum’	‘Pre N’	‘Pre Mean Rank’	‘Pre Sum of Ranks’
The Punjab National Bank	30	64.36667	2.264582	59.4	68.1	15	19.6	294
Canara Bank	30	211.585	14.46951	189.85	236	15	23	345
The Union Bank of India	30	59.695	3.305778	53.6	64.75	15	21.93	329
Indian Bank	30	104.7833	5.399319	98.2	118.15	15	22.37	335.5
The Bank of Baroda BoB	30	98.56833	2.627129	94.25	104.25	15	22.33	335
The State Bank of India	30	272.1333	3.702267	265.15	278.95	15	17.33	260

Table 3 Stating the Effect of M&A on Stock Prices Using Spss-21
‘Banks’	‘Post N’	‘Post Mean Rank’	‘Post Sum of Ranks’	‘Mann-Whitney U’	‘Wilcoxon W’	‘Z’	‘Asymp. Sig. (2-tailed)’	‘Exact Sig.’	‘Null Hypothesis’
The Punjab National Bank	15	11.4	171	51	171	-2.551	0.011	0.01	Rejected
Canara Bank	15	8	120	0	120	-4.667	0	0	Rejected
The Union Bank of India	15	9.07	136	16	136	-4.003	0	0	Rejected
Indian Bank	15	8.63	129.5	9.5	129.5	-4.273	0	0	Rejected
The Bank of Baroda BoB	15	8.67	130	10	130	-4.252	0	0	Rejected
The State Bank of India	15	13.67	205	85	205	-1.141	0.254	0.267	Accepted

The post-measurement data indicates a significant change in the rankings and sums of ranks, particularly for all institutions save the ‘State Bank of India’ (SBI), which has a relatively higher post-measurement rank. The 'Punjab National Bank' (PNB) demonstrates a notable reduction in mean rank from 19.6 in the pre-measurement phase to 11.4 in the post-measurement phase, accompanied by a fall in the total ranks from 294 to 171. Canara Bank, Union Bank (UB) of India, Indian Bank (IB), and Bank of Baroda (BOB) demonstrate significant declines in their rankings, as evidenced by Mann-Whitney U tests and Wilcoxon tests, which indicate statistically significant changes (p-values below 0.05), thus rejecting the null hypothesis of no difference. However, the 'State Bank of India' (SBI) is an exception, since the change in ranks lacks statistical significance. The Z-value for the State Bank of India (SBI) is -1.141, with a p-value of 0.267, leading to the acceptance of the null hypothesis, which signifies no significant change between pre- and post-measurement data for this institution. The data indicates that most banks saw statistically significant rank changes between the pre- and post-measurement periods, except for the State Bank of India (SBI), which showed no significant variations.

Conclusion

The study results indicate that mergers and acquisitions (M&A) in the banking sector do not uniformly affect the financial performance of certain banks in India. The State Bank of India (SBI) did not demonstrate any statistically significant variations in its financial indicators and rankings before and after the assessment. Conversely, several banks, including Punjab National Bank (PNB), Canara Bank, Union Bank (UB) of India, Indian Bank (IB), and Bank of Baroda (BOB), have seen significant reductions in their rankings and financial performance after the merger and purchase. The findings confirm the null hypothesis for SBI, indicating that mergers and acquisitions did not affect the company's financial performance. The effects of M&A are statistically significant for the remaining banks. Financial institutions undergoing mergers and acquisitions must prioritize the management of short-term disruptions throughout the integration process. This is particularly applicable to the transfer of assets and obligations. Financial institutions must create robust solutions to mitigate the factors that lead to temporary financial instability and a decrease in rankings.

Continuous monitoring of the company's performance post-merger and implementing focused adjustments may facilitate operational stabilization and the restoration of financial strength. The findings underscore the varied impacts of mergers and acquisitions on the financial performance of distinct institutions. They suggest that results are influenced by factors like the bank's size, the efficacy of the integration, and the bank's financial condition prior to the merger. Policymakers and financial regulators must examine these differences when establishing criteria for future mergers and acquisitions in the banking sector. Moreover, investors must exercise caution since the outcomes of mergers and acquisitions might differ significantly amongst institutions. To generalize the findings and examine discrepancies across other types of banks (such as private vs public sector banks), it is advisable for future research to include a larger number of institutions. It is essential to examine the long-term impacts of mergers and acquisitions on financial performance and stability, extending beyond the immediate pre- and post-merger phases. The outcomes after the merger may be affected by qualitative elements such employee morale, client satisfaction, and integration challenges. It is essential to examine these aspects.

References

Agarwal, R., & Saxena, P. (2021). Investigated the relationship between capital structure and stock prices of BSE SENSEX-listed banks. Journal of Finance and Accounting, 17(1), 56-72. 

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Received: 08-June-2026, Manuscript No. AMSJ-26-17295; Editor assigned: 08-June-2026, PreQC No. AMSJ-26-17295(PQ); Reviewed: 22-June-2026, QC No. AMSJ-26-17295; Revised: 26-June-2026, Manuscript No. AMSJ-26-17295(R); Published: 02-July-2026