1. Introduction

2. Literature Review

3. Methodology

3.1. Description of Various Performance Measures Used in the Study

The study has used different performance measures such as short-term capital market-based measures, long-term capital market-based measures, accounting-based measures, and market-based measures. The various performance measure used in the study has been described below.

Cumulative Abnormal Return (CAR)

The short-term performance of acquiring companies has been analyzed around the announcement period by taking the different window periods. The study has used two window periods, such as [-2, +2], [-5, +5] of cumulative abnormal return, to investigate the effect of corporate governance characteristics on selected companies. The study has employed event study methods to assess short-term capital market performance. Event analysis allows you to predict how asset prices, such as stock prices, react to economic event announcements that include new information that affects the value of the underlying assets. According to financial theory, all further information is promptly reflected in asset prices in an efficient capital market. Assuming that the market is efficient and that no other events occurred on a given day, the change in the price of an asset is attributable to the reaction of a specific occurrence, which can be called the price effect of that event. The difference between the realized return and the predicted return in the absence of the event is the firm's abnormal return. The use of abnormal returns to assess the impact of an event is critical since it separates the event's influence from the general market movement. The selection of an appropriate model is an essential aspect of the event investigation. According to Brown and Warner (1985), the market model is the standard model for estimating returns after an announcement and produces good results. The study has used the market model to calculate abnormal returns of the acquiring companies.

The event date is when information concerning the mergers and acquisitions became publicly available for the first time.

Event Window: The period considered to capture the complete short-term consequences of the occurrences is known as the event window. We assess abnormal returns over a 41-day window period surrounding the announcement of the merger. To analyze the abnormal returns for the sample companies, we calculate the abnormal returns 20 days before the information announcements and 20 days after the announcement. The 41-day interval was chosen to reduce the impact of abnormal returns on the estimating period while increasing the likelihood of accurately capturing short-term market performance.

Benchmark: The discrepancy between the realized return and the benchmark or normal return is abnormal. The normal return can be calculated using a variety of models. We used the market model to attribute two components of stock returns: systematic risk, which is represented by a linear relationship between stock returns and market returns as assessed by the beta coefficient, and abnormal risk, described by the error term.

Estimation Window: The period the benchmark is calculated varies between investigations. The model's parameters are estimated across a time interval of (-121, -20) in these studies. To evaluate the parameters of our benchmark model, we used the 121-day stock price from 20 days before the announcement day. The daily stock returns are calculated as follows.

$$r_{i,t}=In\left(P_{i,t}\right)-In\left(P_{i,t-1}\right)$$

(1)

$${AR}_{i,t= }{R}_{i,t-}E {(R}_{i,t})$$

(2)

${AR}_{i,t=}$is the abnormal return of the firm, 𝑅_𝑖, is the actual return of the firm, and 𝐸 (𝑅_{𝑖, 𝑡}) is the expected return in the absence of the event. α and β coefficients are calculated using a market index using ordinary least square regression (OLS) over a window period of (-121, -20).

Then, the cumulative abnormal return is calculated as follows:

$${CAR}_{i,T1,T2}={\sum }_{t=T1}^{T2}{AR}_{i,t}$$

(3)

The study calculates cumulative abnormal returns over a given window period. It is used as a short-term market performance indicator to evaluate the effect of corporate governance features on selected companies.

Buy-and-hold-abnormal-return (BHAR)

Buy-and-hold-abnormal-return (BHAR) is the most common method for analyzing long-term market performance. The study uses the BHAR technique to examine Indian bidders' long-term performance in corporate governance and firm-specific qualities. According to Lyon et al. (1999), the BHAR approach is one of the most extensively utilized and is the ideal way because it "particularly measures investor experience." The long-term abnormal return (BHAR) has been calculated by taking the difference between the buy-and-hold return in the acquiring firm with an appropriate expected return. The expected return is calculated with the benchmark, i.e., by using the market index return

$${BHAR}_{i\left(T_1{T}_2\right)}=\prod (1+R_{i,t})-\prod (1+R_{benchmark},t)$$

(4)

The expected return is calculated with the benchmark, i.e., by using market index return. Buy and hold abnormal return is determined for 12 months, 24 months following the mergers and acquisitions announcement for acquiring companies.

Measures of Accounting Performance Measure

Return on Assets (ROA)

ROA is used in the study as an accounting-based measure of a company's performance. Divide earnings before interest and taxes non-recurring transactions by total assets to determine the return on assets. The return on assets represents how well the company's assets have been capitalized to generate shareholder value for the acquiring firms. Several academics, for example, Bansal & Sharma (2013), Mishra & Kapil (2018), and Boussaada & Karmani (2015), have utilized ROA as a reliable performance indicator in their research.

Return on Equity (ROE)

Another way to evaluate a company's performance is to look at its return on equity. The return on equity (ROE) is a critical metric that shows how well a company has managed its owners' resources. This ratio represents the degree to which the goal of maximizing shareholder wealth has been met. A high return on equity (ROE) for the acquiring firm implies that the company's management is effective and works to minimize agency conflict while considering the interests of the shareholders. Several academics, for example, Haldar et al., 2018; Syriopoulos & Tsatsaronis, 2012 have utilized ROE as a reliable performance indicator in their research. This study estimated ROE by dividing net worth.

Market-Based Measures

Tobin's Q Ratio:

The Tobin's Q ratio measures an acquiring firm's growth potential and internal governance quality. Servaes (1991) and Lang (1993) suggested that higher valuation yields higher abnormal returns when a merger is announced (1989). Tobin's Q ratio has been used as a proxy for the quality of management. A ratio greater than one specifies that the financial market favorably perceives firms' investment decisions. It has been argued by scholars that to capture the effect of managerial action on performance, Tobin's Q is a superior measure. Several academics, for example, Golubov et al. (2015), Cheng et al. (2008), Das & Dey (2016) have utilized as a reliable performance indicator in their research. The study has defined Tobin's Q ratio as the ratio between the market value of equity divided by total assets.

Stock Return:

It is a measure of a manager's effectiveness. The stock return of the purchasing corporation has been used to assess managerial performance. Companies with high financial performance are a good signal for investors (Kurniati, 2019). The favorable stock return would boost management's confidence in pursuing mergers and acquisitions. Before the announcement year, we calculated the stock return and averaged it over the previous three years.

Governance Characteristics:

An attempt has been made to determine the impact of governance elements, such as board size, the number of independent directors, and CEO duality, on the performance of acquiring firms, using a variety of accounting-based returns, as well as market-based returns. The detailed description of variables is described below:

Board size –The board size is calculated by the number of directors on the board. It is expected that the small board size has a positive correlation with acquiring firm performance. As the board expands in size, one would anticipate the board's aggregate expertise and talents to grow as well. Larger panels are more likely to boost cognitive diversity, which leads to increased decision-making creativity and the appearance of new options for the firm's development (Shapiro et al., 2015). Larger boards have a broader aggregate body of knowledge and information, including product marketplaces, technology, and legislation (Defrancq et al., 2021). Larger panels may thus be better positioned to provide management with more qualitative strategic advice, potentially leading to better M&A decisions.

Board independence- Board independence characterizes the percentage of independent directors on the board size. Board independence is calculated by the ratio of an independent director to the overall board size. It is expected that board independence has a positive correlation with acquiring firm performance. In the case of M&A, studies on the impact of independent boards on value generation are often mixed (Chi et al., 2011). Outside directors are believed to be more observant of CEO decisions than insiders. As a result, boards with a high percentage of independents are considered more cautious when voting on acquisitions, resulting in improved M&A success (Emanuele Teti et al., 2017). Independent directors on the board of directors, according to previous studies, play a vital role in reviewing managers' decision-making processes (Fama & Jensen, 1983). For a long time, agency theorists have maintained that good corporate governance necessitates more outsiders on the board of directors. The fundamental notion is that independent outsiders are better equipped to defend and promote shareholders' interests.

CEO duality- The CEO duality is a dummy variable that values "1" if the board chairman is the same person as the CEO or managing director or otherwise "0". It is expected that CEO duality has a negative correlation with acquiring firm performance. When it comes to M&A deals, CEOs who are also chairmen of the board of directors are supposed to have more freedom to pursue their interests. In the governance literature, duality, or a situation in which a single person serves as CEO and Board chair, has been linked to poor governance. In a short-run market-based assessment, Masulis, Wang, and Xie (2007) found a negative link between dualism and acquisition performance.

Control variables

The acquiring firm performance is influenced by some of the characteristics of the acquiring firm said to control variable. The control variables used in the study include firm size, risk of the acquiring firm, age and leverage of the firm and volatility of the firm, sales growth, PB ratio, research and development expenses, and cash reserve.

Firm size- Prior studies state that acquiring firm performance can be influenced by the firm's size. According to Moeller et al. (2004), small size leads to better performance as they pay less than large firms. Large-sized firms experienced negative abnormal returns because of the hubris hypothesis stated by Moeller et al. (2005). In line with the previous studies, the present study measured the size as the logarithm of the acquiring firm total assets before the merger announcement.

Leverage- Masulis et al. (2007) stated that a higher level of debt leads to better market performance. Thus, it is expected to have a positive correlation between the acquiring firm and higher leverage. Leverage is calculated by dividing the total liabilities by the total assets of the acquiring firm before the merger announcement year.

The standard deviation of return- Risk is related to future events, as mergers and acquisitions influence the firms to risk in the long run. The study has taken a standard deviation of stock return as a measure of risk. It is calculated as firm volatility in terms of the standard deviation of the stock returns before the acquiring firm's 12 months of the merger announcement.

Age - Because of its increased expertise and capabilities, the firm's period is crucial in decision-making. As a result, the company can make investment decisions and compete effectively with other companies. Older companies gain from the impact of the learning curve on critical strategic choices such as acquisition(Awan et al., 2020).

Beta - Different studies have sought to evaluate the relationship between systematic risk and corporate profitability on the assumption that 'the larger the risk, the higher the return.' The results have been mixed. The beta of the stock, which is a stock market metric, has been included as a company-specific risk indicator.

Sales Growth: The growth potentiality may inspire firms to be optimistic about the future and overpay for the target, resulting in fewer gains for the bidding firm. The average annual compounded growth rate in sales for the three years before the acquisition of each firm is used to determine sales growth.

PB ratio: It's been suggested that companies with a high price-to-book value ratio, dubbed "glamour firms," are more likely to overestimate their acquisition management abilities. It has been suggested that a higher price-to-book value ratio will negatively influence the acquiring firm's return. As proposed by Roll, Hubris's hypotheses will have an impact on them (1986). As a proxy for growth companies, we used the price-to-book value ratio.

Cash Reserve: According to earlier studies, cash flow may lead to agency problems in a firm. Compared to non-cash corporations, it is projected that cash-rich companies will undertake more acquisitions. The cash reserve is calculated by dividing cash and cash equivalent items by total assets in the year before the merger and acquisition announcement.

Research and Development Expenses: Research and development costs increase the bidding firm's charges, whereas acquiring firms are motivated to develop new technology and innovative enterprises to grow. Research and development costs are calculated as a proportion of revenues before the announcement year.

Table 3. Description of variables used in the study.

Table 3. Description of variables used in the study.

Variables	Measurement	Expected Sign
Board Structure Variable
Board size	The number of directors on the board before the merger announcement year	Negative
Board Independence	The ratio of independent directors on the board before the merger announcement	Positive
CEO duality	The dummy variable if the CEO is chairman "1", otherwise "0" before the merger announcement year	Negative
Control Variables
Size	Total assets of the acquiring firm by taking natural log before the one-year announcement, a proxy for acquiring companies' size	Negative
Age	Age of the acquiring firm at the time of the merger announcement	Positive
SD return	The volatility of stock return of the last year before the merger announcement	Negative
Leverage	Debt-equity ratio average past one year before the announcement year	Positive
Beta	The beta of the acquiring company stock at the time of the merger announcement	Negative
Sales Growth	Indicator of average growth in sales before the announcement of the merger averaged over the past three years before the announcement year	Positive
R&D	Research and development as a percentage of sales before the one-year merger announcement	Positive
PB ratio	Dummy for growth If PB ratio is more than one the value is taken as '1' or otherwise '0' before the one-year merger and acquisition announcement	Positive
Cash reserve	Cash and cash equivalent divided by total assets before the merger announcement.	Positive
Dependent Variable
CAR[-5,+5]	An indicator of cumulative abnormal return for the window period [-5,+5]	NA
CAR[-2,+2]	An indicator of cumulative abnormal return for the window period [-2,+2]	NA
BHAR[0,+12]	An indicator of long-term abnormal return for 12 months after the announcement	NA
BHAR[0,+24]	An indicator of long-term abnormal return for 24 months after the announcement.	NA
Tobin's Q ratio	The market value of equity is divided by total assets before the merger announcement.	NA
ROA	An Indicator of profitability measure calculated EBIT divided by the total assets of the acquiring firm.	NA
ROE	EBIT divided by the total net worth of the acquiring company before the announcement year	NA
Stock Return	Stock return is the average of an individual year's stock return over three years before the announcement year	NA

To address the impact of corporate governance characteristics on various measures of financial returns of acquiring companies, eight econometric models have been developed. The corporate governance characteristics, along with various firm-specific factors, are considered in the study and are explained using equation 5-13.

Model 1

$${CAR}_{\left[-5,+5\right]}=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(5)

Model 2

$${CAR}_{\left[-2,+2\right]}=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(6)

Model 3

$${BHAR}_{\left[0,+12\right]}=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(7)

Model 4

$${BHAR}_{\left[0,+24\right]}=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(8)

Model 5

$$\mathrm{R}\mathrm{O}\mathrm{A}=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(9)

Model 6

$$ROE=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(10)

Model 7

$$Tobin,s Q ratio=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(11)

Model 8

$$stockreturn=\alpha +{\beta }_1\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_2\mathrm{B}\mathrm{o}\mathrm{a}\mathrm{r}\mathrm{d} \mathrm{I}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{e}+{\beta }_3\mathrm{C}\mathrm{E}\mathrm{O} \mathrm{D}\mathrm{u}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{t}\mathrm{y}+{\beta }_4\mathrm{S}\mathrm{D} \mathrm{o}\mathrm{f} \mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}\mathrm{s}+{\beta }_5\mathrm{F}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+{\beta }_6\mathrm{f}\mathrm{i}\mathrm{r}\mathrm{m} \mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_7\mathrm{b}\mathrm{e}\mathrm{t}\mathrm{a}++{\beta }_8\mathrm{l}\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}+{\beta }_9\mathrm{p}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{e} \mathrm{t}\mathrm{o} \mathrm{b}\mathrm{o}\mathrm{o}\mathrm{k} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e} \mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}+{\beta }_{10}\mathrm{R}\&\mathrm{D}+{\beta }_{11}\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s} \mathrm{g}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}+{\beta }_{12}\mathrm{C}\mathrm{a}\mathrm{s}\mathrm{h} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{e}+ϵ$$

(12)

4. Results

4. Discussion

5. Conclusions

References

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