Corporate governance and financial performance of Chinese Reverse Mergers

Table of contents

1. INTRODUCTION
1.1. MOTIVATION AND RELEVANCE FOR CHOOSING THIS TOPIC
1.2. RESEARCH PLAN

2. LITERATURE REVIEW
2.1. DEFINITION OF TERMS
2.1.1. Corporate governance
2.1.2. Financial performance
2.1.3. Reverse Mergers
2.2. CORPORATE GOVERNANCE ISSUES IN EMERGING MARKETS
2.3. DETAILED DESCRIPTION OF THE REVERSE MERGER MECHANISM
2.4. REVERSE MERGERS AND CHINESE FIRMS ACCESS TO CAPITAL MARKETS
2.5. REVERSE MERGERS AND PERFORMANCE

3. RESEARCH QUESTION AND HYPOTHESES

4. METHODOLOGY FOR DATA SELECTION AND PERFORMANCE EVALUATION
4.1. CORPORATE GOVERNANCE VARIABLES AND CORPORATE GOVERNANCE PROXY
4.2. OWNERSHIP STRUCTURE VARIABLES
4.3. AUDITOR REPUTATION DUMMY
4.4. DATA USED FOR PERFORMANCE EVALUATION
4.4.1. Standard measurement variable: Total Return Index
4.4.2. Alternative measurement variable: sector-adjusted Total Return Index
4.5. CONTROL VARIABLES
4.6. CORRELATION ANALYSIS BETWEEN C.G DUMMIES AND CONTROL VARIABLES:

5. DESCRIPTION OF CRM SAMPLE
5.1. CRM PERFORMANCE MEASUREMENT:
5.2. CRM ANALYSIS BY CORPORATE GOVERNANCE STRUCTURE
5.3. CRM ANALYSIS BY STATUTORY AUDITOR
5.4. DESCRIPTION BY OWNERSHIP STRUCTURE
5.5. DESCRIPTION BY SECTOR DUMMIES

6. METHODOLOGY FOR STATISTICAL TESTS
6.1. T-TESTS
6.2. LINEAR REGRESSION

7. T-TESTS RESULTS DESCRIPTION AND INTERPRETATION
7.1. CORPORATE GOVERNANCE VARIABLE VS SECTOR ADJUSTED T.R.I (H0)
7.2. STATUTORY AUDITOR VS SECTOR ADJUSTED T.R.I (H0’)
7.3. STATUTORY AUDITOR VS 1Y VOLATILITY (H0”)
7.4. STOCK EXCHANGE MARKET CATEGORY, ADJUSTED T.R.I AND STOCK VOLATILITY (H0”’ AND H0””)
7.5. T-TESTS CONCLUSION
7.6. LINEAR REGRESSION RESULTS INTERPRETATION
7.6.1. Linear regression with ownership structure data
7.6.2. Linear regression with corporate governance data

8. CONCLUSION:
8.1. MAIN FINDINGS OF OUR RESEARCH
8.2. LIMITS TO THE RESEARCH
8.3. POTENTIAL DEVELOPMENTS FOR FURTHER RESEARCH
8.4. IMPACT OF THE RESEARCH AND IMPLICATIONS ON INVESTMENT IN STOCK MARKETS

ACKNOWLEDGEMENTS

GLOSSARY:

REFERENCES

APPENDICES

CV AND PUBLICATION

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ABSTRACT

Chinese Reverse Mergers are companies operating in China who listed on the US financial markets through a “backdoor” mechanism called reverse merger. The reverse merger process for going public consists in reverse-merging with a shell company in order to be listed on a stock market without going through the traditional IPO process.

Chinese Reverse Mergers have been under harsh criticism in the US since the unveiling of accounting fraud issues in 2011 that spilled defiance on the CRMs market, followed by a sharp decrease in the stock prices of these companies and destroying significant shareholder value for the US investors¹.

In June 2011, the Securities & Exchange Commission issued a statement warning investors against the lack of transparency of Reverse Mergers on the US markets (with a special focus on Chinese Reverse Mergers).

The debate about CRM’s is far from over but surprisingly, little research has been done on the corporate governance structure of Reverse Merger companies recently, especially CRMs. Among previous research, Jan Jindra, Torben Voetmannb and Ralph Walkingc² show that Chinese reverse merger companies significantly underperform the Chinese companies who went public through regular IPO process. But a study done by Charles M. C. Lee, Kevin K. Li, and Ran Zhang³ defend that the comparison between CRM and Chinese IPO is not accurate, given that the company profiles are too different in terms of size and risk. CRMs tend to be much smaller companies and bear more risk than normal IPOs. Further, their research indicates that CRM performed better in average than US reverse-mergers, showing that CRM are not “toxic companies” compared to other Reverse Mergers. In this situation, corporate governance frameworks might play a central role to understand the difference between good Reverse Mergers companies and poor performers.

Objective

In order to extend the corporate governance analysis to CRMs, this study will focus on the impact of corporate governance structure on the financial performance of CRMs. Through different external factors of governance (existence of a corporate governance committee, limitations on CEO removal, reputation of the statutory auditor, ownership structure), we want to observe whether the existence of corporate governance mechanisms have a positive impact on shareholder value.

Method

Our research method consists in gathering relevant information on corporate governance structure within company boards. We especially observe whether Chinese Reverse Merger companies have a corporate governance committee and a nomination committee in order to create a ‘’corporate governance’’ dummy. The corporate governance data is available on the Thomson Banker database. In the same time, we measure the financial performance of each company using a Total Return Index (T.R.I) that replicates the value of investing in the company’s stock since from the listing date up to December 13th, 2013. The T.R.I index includes stock price variation and dividends that are supposedly reinvested in the company’s stock.

Research conclusions

Finally, the results of our research do not provide strong evidence that the presence of corporate governance structures or reputable statutory auditors have positive influence on the company’s financial performance measured by shareholder returns. In this way, we are not able to adapt the results of the research of Leora F. Kappler and Inessa Love of the World Bank Development Research Group⁴ about the positive influence of corporate governance in companies operating in emerging countries. A possible reason why these results are not applicable in our sample of CRMs is that the measurement for financial performance we use is different, and the corporate governance data collection method is also different, which might create biases in the interpretation of what is a good corporate governance framework.

Our study, however, shows that there is a strong correlation between the stock exchange listing category and the shareholder return. Our observations prove that OTC-traded CRMs significantly underperform Nasdaq and NYSE listed CRMs. This result is robust to control variables in our statistical tests (linear regression model), and constitutes a key finding in our research about financial performance of CRMs. In the same way, we find that OTC-traded CRMs have significantly higher stock volatility than other CRMs.

We also observe that CRMs who are audited by top 6 statutory auditors (BIG 4 audit firms, Grant Thornton, BDO) have a lower stock volatility on a one-year basis. This result, however, is not easy to explain as we are not able to reproduce this result when we take a larger sample of audit firms (top 10 + Mazars).

Key words: IPO, Reverse Mergers, Cross-Border Listings, Corporate governance, Financial Performance.

1. Introduction

1.1. Motivation and relevance for choosing this topic

The topic of Chinese Reverse Mergers has been a hot topic since the unveiling of accounting fraud problems concerning Chinese companies listed in the US in 2011. In regards with my experience in China during my studies at ESCP, Chinese Reverse Mergers were a quite interesting observation case: How a category of companies who were viewed as having great potential suddenly saw their reputation seriously damaged when accounting fraud issues raised for Chinese companies listed in the US? Over 100 CRMs delisted from the US markets due to fraud allegations in 2011 and 2012.

A McKinsey report about the collapse of Chinese cross-borders listings shed the highlight on corporate governance in these events: while US investors were encouraged by the vigorous Chinese growth rates and invested heavily on Chinese companies promising fast growth and high returns, local boards were not ready to meet the heavy requirements of foreign listings. Focus goes on the reverse merger listings that followed the regular IPOs of Chinese large companies, the report quotes: “All major US law firms and banks had a presence in China, as did a group of smaller advisory firms specializing in reverse-merger listings, where an unlisted company acquires a shell that is already listed and registered with the US Securities and Exchange Commission (SEC), bypassing the more rigorous scrutiny of a regular IPO. These tended to be much smaller: as the crisis hit, companies listed by reverse merger had an average market capitalization of only $68 million and represented less than 1 percent of total market capitalization of all New York-listed Chinese companies. As it would turn out, this 1 percent would cause a disproportionate amount of trouble ⁵ ”.

Among reverse merger lies a significant number of companies that delisted from the US stock markets. So far, some of them appear to have mainained good financial performance among the debacle of reverse merger listings. This has led to two studies mentioned which results are in the abstract: Chinese Reverse Mergers (CRMs) tend to underperform normal IPOs in the US markets. On the other hand, CRMs have a relative good performance when compared to similar companies in the US markets.

Hence the question that emerged when I developed my research about CRMS: Is corporate governance a relevant factor to examine when trying to distinguish between successful and bad CRMs? This thesis is an attempt to answer this research question. Although the results of our study do not show that corporate governance has significant influence on the performance of CRMs, we have been able to identify variables that differentiate CRMs in terms of performance (ie listing category). These results could lead to further developments about the complex topic of CRMs and, in a broader topic, corporate governance and cross border listings involving emerging markets companies.

1.2. Research plan

In Section 1, we first go through the definition of terms and the literature review covering corporate governance and Chinese Reverse Mergers, in Section 2 we will present our research question and the main hypotheses that sustain our research.

Then, we outline our methodology for data selection, stock performance calculation and relevant corporate governance mechanisms in Section 3.

In Section 4, we present the figures on corporate governance variables, control variables and financial performance variables of our sample of CRMs.

In Section 5, we outline our methodology for statistical tests to assess the impact of corporate governance and control variables on the financial performance in our sample. Our interpretation of the tests results is in Section 6.

As a conclusion, Section 7 will focus on the implications and limits of the results in regards with the hypothesis we used to structure our research. We also assess the potential developments for future research and potential impact of our research on emerging markets cross-border listings and investment practices.

2. Literature review

2.1. Definition of terms

2.1.1. Corporate governance

Corporate governance can be defined as a framework of rules, controls and incentives to avoid fraud or interest conflicts in a company. Generally, corporate governance rules will aim at reducing or mitigating conflicts due to divergent interest of the company stakeholders⁶. In this regard, corporate governance can be considered as a structure to answer the problems expressed in the Agency Theory. The Agency Theory insists on the differences in goals and information asymmetry between a company’s managements and its shareholders. This information asymmetry explains the importance of corporate governance at the firm level in order guarantee the shareholder’s interests, including the protection of minority shareholders.

The implementation of a corporate governance framework varies according to the legal environment and board structures. For instance, the legal environment for minority shareholders protection or the power repartition between shareholders and the management has a major impact on how corporate governance can address company integrity and compliance.

Recent research about this topic have shown that strong investor protection is generally associated with effective corporate governance and effective allocation of capital⁷

The occurrence of financial scandals in Europe and in the US in the early 2000’s (Parmalat, Enron), has proved the necessity of enforcing corporate governance principles in Western economies. This necessity is even more important in emerging markets. Most emerging economies are indeed strongly exposed to fraud and misconduct due to a lack of legal framework, or a deficient implementation of law regarding governance. In this regard, corporate governance is a key issue especially in China, where numerous corporate scandals have been reported in recent years.

2.1.2. Financial performance

Financial performance can be defined in several ways. It can be related to better operating performance, in which case cost control and profitable investments are able to increase the company’s return on assets, and in fine the value of the company. In this way, a calculated ratio such as the Tobin’s Q (market value of the company/replacement value of assets) would be a reasonable measure for what we define as “Financial performance” that is in fine the main driver for investment. This type of measure to assess firm performance has been widely used in recent research⁸. This approach, however, has not been retained in our study due to the lack of available data.

Instead, we have focused on stock return as a measure for financial performance. In our research, financial performance will be defined as a comprehensive approach for stock performance (including the variation of the share price and the dividends reinvested (see section 3 - 1.4 for the details of how we measure and calculate financial performance).

2.1.3. Reverse Mergers

Reverse Mergers (also called reverse takeovers) are a specific category of listed companies that went public by using a reverse merger process. In a reverse merger, a listed company plays the role of a shell. This company can be a former operating company that is still listed on a stock exchange but has no more operating activities, or it can be a company created on the sole purpose of being used for a reverse merger. During the process, the shell company formerly acquires the private company, and finances this acquisition by issuing shares that are acquired by the management/shareholders of the private company.

This particular situation of reverse acquisition (the legal acquirer is not the economic acquirer) has been interpreted by the IFRS under the principle of substance over form⁹ , meaning that in the case of a reverse takeover, the real acquirer is the economic acquirer (the private company) and not the shell entity. More details on the reverse takeover process and Chinese Reverse Mergers are provided in Section 1 - 1.3 - description of the reverse merger mechanism.

2.2. Corporate governance issues in emerging markets

As we mentioned in the section definition of terms, the role of corporate governance is to deal with the company’s internal rules, controls and incentives created in order to avoid fraud or interest conflicts. In this sub-section, we will focus on corporate governance issues in emerging markets. Actually, corporate governance in emerging markets strongly differs from corporate governance in other countries, due to several reasons related to legal framework and capital allocation.

Countries where legal framework and regulation encourage transparency in corporate governance mechanisms generally have better shareholder return and more investors in the capital markets¹⁰. In this field, the Western corporate governance practices and framework have been considered for long as the most efficient model to protect the shareholder interest against management misconduct, thus encouraging efficiency in capital allocation on the financial markets.

Some research focused on corporate governance in emerging markets outlined that a corporate governance model for firms in emerging markets can be considered as an alternative to the Western model¹¹. Their conclusions also tend to prove that there is no perfection or absolute measure for the effectiveness of corporate governance models.

Additional literature on the topic, however, distinguishes trends of good practices in corporate governance of emerging markets. A research published by the World Bank in 2002¹² insists on the importance of corporate governance practices at the firm level and corporate reputation in emerging markets. The findings of their research indicate that efficient corporate governance is more correlated to firm performance in emerging markets, because companies with strong corporate governance in emerging markets can partially compensate the weakness of the legal environment by establishing corporate governance rules and shareholder protection. In this context, corporate governance in emerging markets can be viewed as a partial substitute for deficient institutional regulation and shareholder legal protection. The results of their research, however, show that in average, corporate governance at the firm level and financial performance are lower in countries with weak legal framework.

Taking into account the results of the literature on corporate governance in emerging markets, we can conclude by saying that corporate governance issues are more important in emerging markets like China, especially for firms operating in China. In the case of Chinese Reverse Mergers, corporate governance is an even more important topic to discuss, since it affects both firm-level issues and crossborder investors relations, many investors being Americans.

2.3. Detailed description of the reverse merger mechanism

A reverse merger (also called reverse takeover) is often considered as a substitute for IPO, although we will see in this section that significant difference in processes make fundamental difference between an IPO company and a company that listed through reverse-takeover.

The reverse merger deal consists in a private company merging with a listed operating company or a shell created for that purpose. The shell company might be a former operating company, or an empty listed shell created on purpose by the promoter. The common characteristic of these shells is that they have no or no longer have operations, and their assets are mainly composed of cash and cash equivalent. From the Private entity point of view, the main purpose of a reverse merger is to successfully be listed on a foreign stock exchange in a simple and affordable way.

In the case of a reverse merger, the acquirer is not the issuing shares entity; the formal acquirer of the private company is actually the shell company. The shell company would finance the acquisition of the private company by issuing shares that are usually sold to the management or shareholders of the private company.

The reverse-merger process can be summarized as follows:

illustration not visible in this excerpt

In the US Market, shell companies are registered under the Securities Exchange Act (1934) and timely reports its files to the Securities Exchange Commission (SEC). In the case of created shells, SEC filings are quite simple and inexpensive operations, while former operating companies, who do not meet the requirements for NYSE or NASDAQ filings usually end up being traded on the Pink OTC board¹³ and constitute potential shells for the purpose of Reverse Mergers.

We can notice an important difference between Reverse Mergers and IPO mechanisms: While IPO typically involves the creation of new shares from the listed entity, Reverse takeovers only imply an exchange of equity interest, the only shares created are actually done by the promoter when the shell company is created or during the acquisition of the private entity. IFRS standards stated the prevalence of economic reality over the form (substance over form principle).

The absence of shares creation during the reverse takeover substantially simplifies the deal in terms of delays and procedures.

The reverse takeover mechanism may seem less risky for the management since the IPO process is not 100% sure to be completed due to regulatory hurdles and due diligence processes, resulting in a great loss of time and fees. This type of risk is almost reduced to zero in a reverse takeover¹⁴ and constitute one of the main arguments for reverse merger promoters.

In addition to that, a reverse takeover is a rapid and inexpensive process compared to an IPO in terms of fees and delays. For many small-midcaps companies, it avoids the heavy cost of pre-IPO due diligence, underwriter participation (usually an investment bank) and the long delays and procedures needed to complete a regular IPO process:

Typical timeline of pre IPO and post IPO requirements¹⁵:

illustration not visible in this excerpt

Table 1: Timeline of pre IPO and post IPO requirements

Compared to an IPO, a reverse takeover listing is only a matter of weeks. It can be successfully completed in a delay as short as 30 days¹⁶.

As a consequence, from the late 1990’s to 2007-2008¹⁷, reverse takeovers have been especially attractive for small-medium size businesses who wanted to access stock markets without having to pay a high price for it. The topic concerning Reverse Mergers and Chinese need for financing on capital markets is further developed in Section 1 - 1.4.

The downside risk in the long term, however, seems much higher for a reverse merger than an IPO. Reverse Mergers tend to be significantly riskier than their IPO counterparts. In the late 2000’s several studies have shown that Reverse Mergers are less reliable for investors in the long run and mostly fail to create value¹⁸. Since 2009, several warnings from the SEC or financial media were publicly stated out, encouraging investors to invest in reverse takeovers only if they dispose from sufficient information¹⁹. As we will see in the literature review section 3, CRM have proved to be a failure after the disclosure of accounting scandals involving Chinese companies listed on the US markets.

As a conclusion, we can see that Reverse Mergers have long been considered as a correct substitute for IPO’s, in addition, the listing process seemed to cheaper, quick and secure compared to IPOs; since then, SEC warnings and accounting scandals in China have revealed hidden risks associated with Chinese Reverse Mergers and investor defiance regarding Reverse Mergers has soared.

2.4. Reverse Mergers and Chinese firms access to capital markets

Reverse Mergers were considered as an opportunity for Chinese companies to be listed on the US capital markets. The reverse takeover move of Chinese firms in the US started in the early 2000’s²⁰ and has actually overtaken the market of Reverse Mergers until 2010. Research show that CRMs made up to 85%²¹ of the total RMs on the US markets between 2001 and 2010. Several hypotheses might explain the appetite of Chinese firms for reverse takeovers.

Before 2001, the Chinese government used to manage IPOs on a quota systems based on sectors and regions splits. Local governments had to negotiate with the regulator (formerly the People’s Bank of China, now it is the China Securities Regulation Commission - CSRC). As a consequence, IPO’s during this period mainly consisted in partial privatization of State-Owned companies. The IPO regulation was reformed in 2001 and named Review and Approval System (RAS)²².

One of the main factors of foreign listings attractiveness for Chinese companies might have been the substantial difference between the Chinese RAS and the US IPO regulation. The IPO requirements in China under the RAS are heavier than in the US. While the basic disclosure documents with the SEC must include materials facts focused on informing the investor of relevant information that might affect his investment decision, the Chinese RAS might take into account several other factors such as the company profitability, business prospect and business scope, as well as the general CSRC review and approval²³.

Another phenomenon that can encourage a Chinese company to get listed abroad is the recurrent phenomenon of shares initial underpricing that was prevalent on the Chinese stock market in the late 1990’s²⁴.

Coupled with regulatory hurdles, restricted stock markets a phenomenon of IPO under-pricing, it is easy to imagine that small or medium private Chinese companies in need for capital viewed reverse takeover listings as an opportunity to raise more capital and access US investors. This Greater need for capital access for small or medium Chinese companies can explain the predominance of small/midcaps in the CRMs market²⁵. But, as the Mc Kinsey report we mentioned in the introduction pointed out, the size and risk profile of these companies was not representative of the average Chinese companies IPOs and finally undermined the reputation of Chinese corporate among US investors.

2.5. Reverse Mergers and Performance

As discussed in the abstract, literature about performance of Chinese Reverse Mergers is relatively scarce, although recent papers tend to develop the current knowledge about RMs in general. A reason might be that RMs (and CRMs) have remained relatively unknown of public attention until accounting scandals enlightened this specific category of listed companies. But some researches are revealing interesting insights about the intrinsic performance and risks associated with Reverse Mergers, and CRMs in particular.

“ Backing into being public: an exploratory analysis of reverse takeovers ” by Kimberly C. Gleason, Leonardo Rosenthal, Roy.A. Wiggins, is a research conducted on 121 reverse takeovers. The results shows that these firms are generally poor performers and that the survival rate of these public companies is very low, as 46% of them do not survive in the next two years following the listing. Their conclusion is that while reverse takeovers constitute an alternative for going public, reverse merger companies are generally riskier and fail to create value.

In the same way, Reverse Mergers: The Chinese Experience, by Jan Jindra, Torben Voetmannb and Ralph A. Walklingc show evidence that large firms based in China are less likely to go public through Reverse Mergers, and use traditional IPO instead. Their research also shows that Chinese Reverse Mergers are more likely to face fraud allegations than Chinese IPOs. Their conclusion indicates that due to significant differences in size and risks, CRMs cannot be considered as a substitute to IPOs.

Several other working papers, however, tend to defend the performance of Chinese Reverse Mergers if they are compared with sample of similar firms. The reason is, some Chinese Reverse Mergers are promising companies that can benefit from access to foreign capital markets to sustain their growth in a dynamic economy such as China. Through reverse takeovers, Chinese small but growing companies would benefit from the strong economic growth, thus representing profitable yet risky opportunities for US investors.

In their research Shell Games: Are Chinese Reverse Merger Firms Inherently Toxic? - Charles M. C. Lee, Kevin K. Li, and Ran Zhang sustain that Chinese Reverse Mergers perform better than US reverse takeover, while remaining risky investments in general. Their research shows evidence that over-defiance from US investors regarding CRMs is not fully justified as several CRMs are actually profitable and growing companies.

In a more specific way, Masako Darrough, Rong Huang, Sha Zhao, in “The Spillover Effect of Fraud Allegations Against Chinese Reverse Mergers”, observe the existence of a spillover effect that affected all CRMs after fraud allegations. Their research underlines the role of short-sellers in the spillover effect of CRMs. Their research also shows that US RMs and other foreign RMs have escaped this phenomenon, suggesting that stock markets defiance has concentrated on the country of origin rather than the listing category of companies involved in Reverse Mergers.

Apart from the case of CRMs, other research conducted by Jordan Siegel and Yanbo Wang²⁶ focuses on foreign Reverse Mergers in the US markets. Their findings suggest that early entrants in the US markets through Reverse Mergers and companies that hired BIG 4 statutory auditors and RMs can be considered as adopters of good corporate governance practice compared to the latest entrants in the market. This research finally outlines the importance of adopting US laws and corporate governance standards, but also shows that in the case of RMs, weak cross- border law enforcements may encourage fraud and shortcomings on corporate governance.

Based on our literature review, we can observe that better corporate governance positively affects firm performance, especially in emerging markets. Research on CRMs shows that, although they are not as profitable as IPOs, CRMs are not all toxic companies, and that a sample of CRM’s might outperform an American benchmark of similar companies. In other terms, listed CRMs contain several profitable Chinese companies that actually succeeded in providing investors with positive value. While some authors explain the performance of CRMs according to the macro-economic environment, the determinants of this success at the firm level (micro-economy), however, are not quite detailed.

So far, we have not found analysis focused on corporate governance structures and financial performance for RMs or CRMs. In this context, our current research constitutes an exploratory analysis of how corporate governance variables might impact performance of Chinese Reverse Mergers.

3. Research Question and hypotheses

As outlined in the abstract and the literature review, academic research has provided extensive literature about the relationship between corporate governance and financial performance of companies. Companies with a good corporate governance framework tend to have a higher performance and increased shareholder return. This statement is especially true in emerging markets, where corporate governance can be a substitute to the weak legal environment. No research however, has been done to prove the positive relationship between good corporate governance and financial performance for Chinese Reverse Mergers listed on the US. Our research question will focus on this topic.

Since good corporate governance a factor for higher financial performance for companies in emerging markets, we intend to replicate this result for Chinese Reverse Mergers. Hence our research question: Is good corporate governance a determinant factor in CRM’s financial performance?

In order to answer that research question, we decide to perform a quantitative analysis on a sample of 68 Chinese companies listed in the US stock exchange through Reverse Mergers.

Our sample of CRMs is based on a Bloomberg listing of CRMs listed on the Nasqad and NYSE Euronext markets as of June 2011²⁷. The number of CRMs in this listing amounts to 85 companies, and is omitting former listed companies that left the stock exchange market following short-selling issues or accounting scandals. After eliminating former companies who delisted or relocated outside of the US market between 2011 and 2013 and companies for which there is no relevant financial information, we obtain our research sample of 68 companies.

After gathering information on the board structure and shareholder structure of these companies, we analyzed the possible impact of the presence corporate governance mechanisms (board structure and shareholders ownership structure) on the financial return. Since data for operating performance or company valuation is not available for many companies in our sample, we finally chose a shareholder return-based index to assess the financial performance of CRMs. This shareholder return index is called Total Return Index and the calculation steps of this index are available in section 3.4 “Data used for performance evaluation”

Our research hypotheses are the following:

1- A Corporate Governance proxy will be defined when the company has a corporate governance structures in its board (Corporate Governance Committee, Nomination Committee).
2- Companies whose information on corporate governance/nomination committee is not available will be considered as having no corporate governance committee. Consequently, for each company, our corporate governance proxy can have two values: 0 or 1.
3- Our observation sample is 68 CRMs. For our research, we consider that the sample of firms we observe follow a normal distribution. This is a strong hypothesis, as 68 is a relatively low number of observations for a statistical analysis. This hypothesis, however, is necessary in order to perform our t- tests.

4. Methodology for data selection and performance evaluation

In order to measure the effect of corporate governance on value creation, we focused on tangible observations that can be observed for a significant sample of CRMs to create a corporate governance proxy.

4.1. Corporate governance variables and corporate governance proxy

As a proxy for corporate governance mechanism, we will observe whether a company has a corporate governance proxy in the board of directors. The corporate governance proxy will have the value “true” (true = 1) if the company complies with two conditions: there is a nomination committee and a corporate governance committee in its board.

A third variable that could be part of the governance proxy if the existence of a compensation committee. We decided, however, that this variable did not provide enough additional information on our sample. Analyzing the corporate governance variables that constitute our dummy variable, we find out that 75% of boards who have a nomination committee also have a compensation committee (see correlation matrix between C.G variables in table 2).

Another variable “Limitations on director removal” was also considered to be part of the corporate governance proxy, but this variable was finally rejected for two reasons:

1 -The lack of specific information it provides about the corporate governance structure makes the date difficult to analyze.
2 -Taking this variable into account would reduce our sample of “corporate governance” firms from 30 to 15, which would decrease the significance of our statistical analysis if the sample is too small.

Correlation matrix between corporate governance variables:

illustration not visible in this excerpt

Table 2: Correlation matrix between corporate governance variables

We can observe that most of corporate governance factors are not strongly correlated to each other (except for the compensation committee and nomination committee). As described in our methodology, we will only consider companies having nomination committee and corporate governance committee as having a corporate governance structure.

4.2. Ownership structure variables

The ownership structure of each company is available on Bloomberg. We have obtained the data²⁸ for the 68 companies constituting our sample:

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Table 3: Description of the ownership structure in our CRMs sample

The detailed ownership structure by company is available in appendix n°6.

4.3. Auditor reputation dummy

The reputation of the legal auditors also enters into account as part of our analysis.

In order to implement the dummy variable corresponding to auditor reputation, we have short-listed the names of the 6 audit companies that appear as top 10 companies in the top 10 of accounting firms in 2012²⁹:

1 PwC
2 Deloitte
3 KPMG
4 Ernst & Young
5 Grant Thornton UK
6 BDO

The dummy variable then takes the value 1 if the auditor belongs to the 10 + 1 list of auditors, or takes the value0.

The number of CRMs that are audited by top 6 auditors is 12. The detailed split between the performance of companies and categories of statutory auditors is given in the Section 4 - Description of CRM sample.

4.4. Data used for performance evaluation

4.4.1. Standard measurement variable: Total Return Index

The measurement for value creation we chose is the Total Return index (in % change) for each company of our CRMs sample, calculated from the date listing of the company to December 18th, 2013 (date of data extraction on datastream). The TRI takes into account the share price variation (in %) from the listing date until 12/18/2013 plus the dividends over the same period. Dividends are supposed to be reinvested the following business day after distribution of the dividend at the spot price.

The calculation details of Total Return Index available on Thomson Reuters Datastream are detailed below³⁰:

Formula on datastream:

TRI = PCHV [X(RI)]

“A return index (RI) is available for individual equities and unit trusts. This shows a theoretical growth in value of a share holding over a specified period, assuming that dividends are re-invested to purchase additional units of an equity or unit trust at the closing price applicable on the ex-dividend date.

For all countries except the USA and Canada detailed dividend payment data is only available on Datastream from 1988 onwards. Up to this time the RI is constructed using the annualised dividend yield. This method adds an increment of 1/260th part of the dividend yield to the price each weekday. There are assumed to be 260 weekdays in a year, market holidays are ignored:

Method 1 (using annualised dividend yield)

RI on the basedate =100, then:

Where:

= return index on day t

= return index on previous day

= price index on day t

= price index on previous day

= dividend yield % on day t

N = number of working days in the year (taken to be 260)

From 1988 onwards (and from 1973 for US and Canadian stocks), the availability of detailed dividend payment data enables a more realistic method to be used in which the discrete quantity of dividend paid is added to the price on the ex-date of the payment. Then:

Method 2 (using ex-dividend date)

Except when t = ex-date of the dividend payment Dt then:

Where:

= price on ex-date

= price on previous day

= dividend payment associated with ex-date t

Gross dividends are used where available and the calculation ignores tax and reinvestment charges. Adjusted closing prices are used throughout to determine price index and hence return index.

Note : where the detailed dividend payment data (after 1988 for countries other than US and Canada) contains a mixture of dividends marked as net and gross, the annualised dividend yield (method 1 above) continues to be used. The net/gross markers can be identified using the datatype DTAX (tax marker) or can be displayed in the Dividend Payment Report in DS Advance. To display the total return using the ‘ex-date’ method in these cases, the alternative total return datatype RZ (return index as paid) may be used. RZ uses the ‘ex-date’ method (method 2 above) irrespective of the tax markers.”

4.4.2. Alternative measurement variable: sector-adjusted Total Return Index

In our descriptive research (see section 3 - Description of CRM sample), we found out that the Total Return index is extremely sensitive to industry variables. As a consequence, the variable “Industry/sector” has a significant impact on the analysis of financial performance. An accurate analysis of sector dummies would render the statistical analysis significantly more complex and introduce analysis biases. CRM companies belong to 18 different SIC codes grouped in 6 sectors dummies in our research). The correct way to take into account the industry effect would be to recreate the 18 sector variables corresponding to the industry in our tests, which is not possible due to software limitations (our analysis add-in for excel only takes into account 16 regression variables).

In order to produce a more accurate analysis, we also considered measuring the financial performance of CRM using a sector-adjusted Total Return Index. The sector-Adjusted TRI follows the calculation below:

Sector Adjusted TRI = PCHV [X(RI) - X(RI)#FEI(RI)]

Where X(RI) represents the T.R.I of the company and X(RI)#FEI(RI) represents the T.R.I of the sector as expressed as “Super Sector)³¹.

The hierarchy for sectors on datastream is defined below³²:

Datastream classifications are based on the FTSE ICB system and there are six datatypes representing each classification level:

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Table 4: Datastream classification for industry codes

4.5. Control variables

To test the robustness of our factors, we will test the Total return index component with the following control variables:

1. Book value of assets
2. Year of listing
3. Category of listing (NYSE, Nasdaq, OTC market)

4.6. Correlation analysis between C.G dummies and control variables:

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Table 5: Correlation matrix between corporate governance variables and control variables

Our correlation analysis shows no interference between C.G variables and control variables. As a consequence, our control variables are valid to test the robustness of our C.G variables.

The detailed methodology for performing tests with C.G variables and control variables is explained in section 6 - Methodology for statistical tests.

5. Description of CRM sample

The information in this section will present an overview of the characteristics of the CRM companies constituting our sample.

The description of our sample will be split in three categories of variables:

1. Performance measurement measures constituted by Total Return Index (TRI) and sector-adjusted TRI. This variable is continuous and measures the performance in % of total return.
2. Corporate governance variables such as the existence of a corporate governance committee, nomination committee, CEO removal policy that constitute the corporate governance dummy, and the quality of the statutory auditor. These are Boolean variables [0;1] giving the value 1 if one of the above structure exists and 0 if it is not.
3. Ownership structure variables (not Boolean) that describe the ownership split and shareholder concentration (dilution) in our CRM sample
4. Control variables such as book value of assets, listing market category or one- year volatility are also gathered in order to control the robustness of our hypothesis.

5.1. CRM performance measurement:

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Table 6: Sector-adjusted T.R.I distribution for our CRMs sample

Sector-Adjusted T.R.Is of our 68 CRMs are represented in the graph above. Firstly, we can observe that the majority of CRMS have negative sector adjusted T.R.I. The CRMs that have positive adjusted T.R.I start at the 70th percentile. The extreme values of the distribution are companies with very high sector adjusted T.R.I located beyond the 90th percentile. We can notice the asymmetry between the lowest T.R.I (floored by the value -2; which is equivalent to -200%) and the highest T.R.I that reaches +600%.

These observations are coherent with economic reasons. When investing in a stock, the loss limit is floored at -100% (values below -100% can exist in T.R.I index if we take into account reinvestment during capital increase). On the other side, profit has no upside limit (cap) and can be infinite, at least in theory.

5.2. CRM analysis by corporate governance structure

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Table 7: CRM analysis by corporate governance structure

The sample of CRMs is almost equally split between CRMS that have a corporate governance proxy (30) and the other CRMs (38). Our observation by mean difference shows that CRMs with a corporate governance proxy have a higher T.R.I than other CRMS. The positive difference is 28,63% for unadjusted T.R.I and 32,59% with sector-adjusted T.R.I.

In order to confirm the existence of a mean difference between the two groups, we will conduct t-tests explained in detail in Section 7.1

5.3. CRM analysis by statutory auditor

Among CRMs, we can notice that the mean difference in terms of T.R.I is important if we split companies who are audited by top 6 companies (BIG4 + Grant Thornton +BDO). The table below summarizes the figures:

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Table 8: CRM analysis by statutory auditor

In our sample of 68 CRMs, we have 12 companies that are audited by top 6 auditors (BIG4 BDO + Grant Thornton). The mean difference of sector-adjusted T.R.I is 66,67% between CRMs that are audited by top 6 auditors and other CRMs.

In order to confirm the existence of a mean difference between CRMs with different categories of statutory auditors, we will conduct t-tests explained in Section 6.2.

5.4. Description by Ownership structure

The chart below shows the average percentage of CRM ownership in our sample:

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Table 9.1: Ownership analysis in our CRM sample (chart) Average different types of shareholders in CRMs

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Table 9.2: Ownership analysis in our CRM sample (table)

As shown in the graph above, we can observe that a very significant part of shareholders are individual investors. Other significant type of shareholders includes unclassified investors and investment advisors. Hedge Fund, Holding entities and Private Equity shareholder also have smaller parts of ownerships.

According to our figures, the different categories of shareholders for a typical CRM is 3,41 in average, which represents a high ownership concentration.

A significant hurdle to the ownership analysis is that the second largest ownership type is of other nature or unclassified according to the Bloomberg source. In these conditions it is hard to conclude on the nature of those investors and their impact on corporate governance practices.

Unlike the precedent variables, no interpretation can be given using means difference, since the ownership structure is too complex to be structured in only two groups.

5.5. Description by sector dummies

Based on the sector defined by the SIC code in the US stock markets, we have created six sector dummies to describe our test sample. We have also calculated the average TRI by sector, as follows:

Starting from 25 SIC classifications, we have merged the comparable sectors in order to reach a number of 6 sector dummies³³.

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Table 10: Sector analysis of our CRM sample - Chart

After comparing the performance of the CRMs grouped by control variables, we can observe significant performance variance between different sectors:

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Table 10.1: Sector analysis of our CRM sample - Table

The results of sector split shows significant variance in T.R.I, with the Technology sector having a unadjusted T.R.I of 104% and adjusted T.R.I of 80%. Among poor performers, we can observe the Food and Energy & Commodities sectors with unadjusted T.R.I of -25% and -23% (respectively -48% and -32% of sector adjusted T.R.I).

Performing statistical analysis with t-tests and linear regression with unadjusted T.R.I would oblige us to create control variables representing each sector. This method would actually create biases and would not be accurate for several reasons:

1 -The 6 sector dummies created in the table above are constituted of weighted average of 18 SIC codes. Using our 6 sector dummies as control variable would create uncertainty and inaccuracy when applied to our sample as none of these variables “really” apply to the industry sector of CRMs.
2 -T-tests can only be applied with one control variable at a time. Using sector dummies would create 6 more t-tests focused on sectors impact on T.R.I
3 -Linear regression also need to have control variables. But the linear regression in our analytics can accept 16 variables at its maximum. It would not be realistic to take into consideration 6 dummies for sector adjustment.

Given the reasons described above, we decide to use the Sector-adjusted T.R.I in order to limit the analysis biases and the number of control variables to test. Using sector adjusted T.R.I provides an accurate measurement of CRMs financial performance compared to their sector and simplifies the analysis by decreasing the number of variables to take into account.

6. Methodology for statistical tests

In Section 4, we described the average differences in our CRM sample, according to whether the companies belong to the C.G dummies (C.G proxy, statutory auditor). We also presented the T.R.I split by sector and explained why we choose to use the sector-adjusted T.R.I instead of the standard T.R.I

In this section, we will focus on the methodology for each series of tests performed. We will insist on the main steps of t-tests and linear regression.

6.1. T-Tests

T-tests (also called student tests) are widely used methods to determine whether a given variable has a significant impact on the average values of observations within our sample, in other words, it can be used to determine if two groups have different means. In our study, we want to know if the C.G proxy really explains the mean difference observed between our C.G group and our non-C.G group, given the estimated variance of T.R.I of our CRM sample.

The t-value used in a t-test is defined as follows:

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Where:

x is the average of the observed sample

μ is a determined value for the average of the sample

S/(sqrt(n)) can be considered as the standard error in our sample (in the case of t- tests, the variance is not known, but it can be distributed under a normal distribution under the Null Hypothesis)

To determine if two groups have a different mean, we test the Null Hypothesis (H0) with a given confidence interval (generally 95% or 99%)³⁴. If the Null Hypothesis H0 is rejected, it means that the two groups observed have a different mean.

Under a certain confidence interval, (x - μ) is considered as “large” (Null Hypothesis rejected) if μ lies outside of the 100*(1- α) confidence interval calculated as:

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Where t(α) is the t-value associated with the confidence interval α

Another method consists in measuring the difference (x - μ) and comparing it to the group standard error measured as:

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If the difference (x - μ) is greater than the group standard error, the Null hypothesis H0 is rejected.

In the case of our corporate governance t-test, we want to test the following Null Hypotheses:

- H0: “CRMs that have C.G structure have the same average T.R.I as CRMs that have no corporate governance structure”
- H0’: “CRMs audited by top audit firms have the same average T.R.I as CRMs who are audited by smaller audit firms”
- H0”: “CRMs audited by top audit firms have the same average stock volatility as CRMs who are audited by smaller audit firms”
- H0”’: CRMs listed in OTC markets have the same average T.R.I as CRMs who are listed on Nasdaq/NYSE”

As we already discussed in section 4, the confidence interval used to determine the results will be 95%. We will consider the CRM sample as a single sample having a unique variance. Hence, we will retain the variance of the T.R.I of our CRM sample as the variance used to perform the t-tests.

As our observations (see section CRM sample) show that the average Return Index (T.R.I) is higher for companies who have a corporate governance structure, we will test the Null hypothesis for a single-sided critical value. If the Null hypothesis is rejected, we can conclude that companies that have a corporate governance structure also have a higher return for their shareholders. We will use the same methodology concerning the other Null hypotheses H0’; H0”; H0”’

6.2. Linear regression

Linear regressions are used to modelize the impact of one or several variables (x1, x2, […] Xn) on a given variable Y. The method consists in creating a line that passes as close as possible to all the data points constituting the variable Y.

The slope of this line (S) is calculated according to the variables (x1, x2, […] Xn) such as

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Mathematically, creating this line translate into the Ordinary Least Squares Method, which determines the line S for which the squares of the distance between S and the data point are minimum.

The accuracy of a linear regression depends on its coefficient of determination R² that measures the proportion of variation (sum of squares) that is explained by the linear regression and the proportion and the variation due to “error” (not explained by the regression). A weak ratio for R² means that the linear relationship in the regression is weak.

With SS referring to “sum of squares”, we have the following equalities:

Total SS: SS due to regression + SS due to error

R² = SS due to regression / Total SS

On the excel data analysis tool pack, the linear regression analysis is limited to 16 variables.

To confront the corporate governance data with other factors that might influence the Return index of CRMs, we have performed two linear regressions following the method described below. The analytics excel add-in can integrate a maximum of 16 variables for a multi-variate linear regression.

1- Our first linear regression will focus on the potential impact of a specific type of ownership on the financial performance of CRMs. We take the 12 ownership variables and the “number of shareholders categories” variable - 13 variables in total - in our X-axis to determine if one of these variables has significant impact on the firm performance (for instance, do Private Equity shareholders impact the financial performance of CRMs measured with T.R.I?)

In order to eliminate the potential sectors biases, we use the sector adjusted T.R.I as measure for financial performance in our Y axis, while the X axis will integrate our regression variables.

2- Our second linear regression focuses on the corporate governance determinants. We re-use the variables (C.G variables and control variables) that we have tested through t-tests and we mix them with the significant ownership variables that we observed in the first linear regression (we only keep the ownership variables that have significant impact on the financial performance). This second linear regression will provide a synthetic view of our C.G variables and control variables in the X-axis.

To eliminate the potential sectors biases in a simple way, we use the sector adjusted T.R.I as measure for financial performance in our Y axis, while the X axis will integrate our regression variables.

7. T-tests results description and interpretation

The first step of our analysis has been to conduct T-tests for each C.G factor and dummy variable to determine whether there is an impact on the sector-adjusted total return index (T.R.I).

In the case of our corporate governance t-test, we have tested the following Null Hypotheses:

- H0: “CRMs that have C.G structure have the same average T.R.I as CRMs that have no corporate governance structure”
- H0’: “CRMs audited by top audit firms have the same average T.R.I as CRMs who are audited by smaller audit firms”
- H0”: “CRMs audited by top audit firms have the same average stock volatility as CRMs who are audited by smaller audit firms”
- H0”’: “CRMs listed in OTC markets have the same average T.R.I as CRMs who are listed on Nasdaq/NYSE”
- H0””: “CRMs listed in OTC markets have the same stock volatility as CRMs who are listed on Nasdaq/NYSE”

T-tests are performed for pairs of variables in the following order:

- Corporate governance variable vs Unadjusted & Sector adjusted T.R.I (H0)
- Statutory auditor vs Sector adjusted T.R.I (H0’)
- Statutory auditor vs 1-year volatility (H0”)
- Stock exchange market vs Unadjusted & Sector adjusted T.R.I (H0”’)

7.1. Corporate governance variable vs Sector adjusted T.R.I (H0)

t-Test: Two-Sample Assuming Equal Variances

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Confidence interval = 95%

Table 11: T-test of C.G variable and sector-adjusted T.R.I

The t-stat for sector-adjusted R.I is 1,39, which is inferior to the critical t-value with a 95% one-sided confidence interval. It means that the Null Hypothesis H0 cannot be rejected. From the above t-test, we cannot conclude that corporate governance structure has a significant impact on the Return Index

7.2. Statutory auditor vs Sector adjusted T.R.I (H0’)

The group companies included in the top 11 audit firms is constituted by companies whose statutory auditors belong to the top 10 ranking plus Mazars (11th) - see Section 3.3 for detailed methodology about auditor rankings. Auditor proxy with the value 1 represents the average T.R.I of CRMS that are audited by top 11 audit firms.

t-Test: Two-Sample Assuming Equal Variances

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Confidence interval = 95%

Table 11.1: T-test of statutory auditor dummy and sector-adjusted T.R.I

The t-stat absolute value is -0,71; which is not significant compared to the critical value of 1,67 for a confidence interval of 95%. As the t-test indicates, we cannot conclude that statutory auditor has any impact on the sector-adjusted return index.

7.3. Statutory auditor vs 1Y Volatility (H0”)

In the former section, we have observed that the category of statutory auditor does not have significant impact on the T.R.I adjusted by sector. In this section, we want to test whether the statutory auditor reputation has an impact on stock volatility instead.

The t-test applied to CRMs audited by top 6 audit firms seems to have an impact on the 1 year volatility of CRM stocks:

t-Test: Two-Sample Assuming Equal Variances

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Confidence interval = 95%

Table 11.2: T-test of top 6 statutory auditor dummy and stock one-year volatility

The t-stat is 1,75 and exceeds the critical value at the 95% confidence interval (onesided); We can then reject the Null Hypothesis and infer that CRMs that are audited by top 6 audit firms have a lower stock volatility than other CRMs.

The relationship between the quality of companies audited by top 6 auditors and others, however, is not clear. It might be difficult to explain why CRMs audited by top 6 audit firms have less volatility than other CRMs. The above result is difficult to explain in the context of our research. Moreover, when we try to replicate the t-test taking into account the top 11 audit firms, we are not able to reproduce this result, and in this case we cannot prove that statutory auditors infer a mean difference in stock volatility.

T-test : Two-Sample Assuming Equal Variances

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Confidence interval = 95%

Table 11.3: T-test of top 6 statutory auditor dummy and stock one-year volatility

In the above t-test, we take into account the top 6 auditors as defined in Section 3.3, plus the following accounting firms: RSM Nelson Wheeler, Baker Tilly, Moore Stephens and Mazars. As explained above, the t-test does not replicate the results we have found in table 11.2.

7.4. Stock exchange market category, adjusted T.R.I and stock volatility (H0”’ and H0””)

Considering the stock exchange market as a dummy variable, we performed a t-test on the basis on two samples: a group of CRM that is listed on OTC stock exchange, and CRM that are listed on a regular exchange (Nasdaq, NYSE, foreign SE). Our observations and tests actually show that the type of stock exchange market has a very significant impact on the sector adjusted return (see table below):

t-Test: Two-Sample Assuming Equal Variances

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Confidence interval = 95%

Table 11.4: T-test of listing category and sector-adjusted T.R.I

In this test, we clearly see that the t-stat is almost twice as high as the critical t-value for a confidence interval of 95%. In this context, we can reject the Null Hypothesis “H0”’: “CRMs listed in OTC markets have the same average T.R.I as CRMs who are listed on Nasdaq/NYSE”.

Our Null Hypothesis being rejected, we can conclude that CRMs that are listed on non-OTC category have a better sector adjusted total return index than CRMs listed on OTC category. This result constitutes a major finding in our research.

When we replicate the t-test for the listing category, but taking one-year volatility as measurement variable, we also find that OTC listed CRMs have a higher stock volatility than other CRMs:

T-test : Two-Sample Assuming Equal Variances

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Confidence interval = 95%

Table 11.5: T-test of listing category and one-year stock volatility

7.5. T-tests conclusion

Among the t-tests we performed, we can come to the conclusion that our corporate governance proxy does not have a very significant impact on the sector-adjusted return index. The same conclusion applies for the influence of statutory auditor reputation and total return; statutory auditor and stock volatility. In all these cases, the t-stat we obtained in our t-test cannot reject the Null Hypotheses H0, HO’, H0” at a 95% confidence interval.

Among the t-tests conducted with our control variables, however, we find that CRMs that are listed OTC actually have lower returns and higher stock volatility than companies that are listed in the Nasdaq/NYSE Stock exchanges. This result is actually the most interesting finding in our research, although we cannot clearly explain the interactions between listing category and corporate governance.

7.6. Linear Regression results interpretation

7.6.1. Linear regression with ownership structure data

Our linear regression (see the entire regression analysis on appendix n°1) shows that categories of ownership structure have no influence on the financial performance of the firm measured by the adjusted T.R.I, but the number of shareholders type has some impact on the adjusted T.R.I. The determination coefficient for multiple variables is 50,75%; while the R² coefficient is 25,75%.

The respective t-values compared with critical values for confidence intervals of 90% and 95% for each variable are presented below:

RAPPORT DÉTAILLÉ

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Table 12: Results for linear regression with ownership structure data

The variables representing the type of shareholders have a t-stat value that does not exceed the inferior or superior limit for a confidence interval (C.I) of 95%, which means that their influence on the Y-axis (sector adjusted T.R.I) is not significant. The variable number of shareholders, however, has a t-stat of 1,92 that exceeds the superior limit of 0,49 for a confidence interval of 95%.

As a conclusion, we can say that the variable “number of shareholders” has an impact on the adjusted T.R.I and should be further compared to control variables to test its robustness.

7.6.2. Linear regression with corporate governance data

The linear regression - including C.G variables and control variables (see the entire regression analysis in appendix n°2) - shows that C.G variables finally have little impact on the determination of adjusted T.R.I. The R² is 22,52%, which means that our C.G variables and C.G variables altogether can explain 22,5% of the adjusted T.R.I.

The t-stat values compared with the limits for a confidence interval of 95% are presented below:

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Table 12.1: Results for linear regression with C.G variables, synthetic ownership variable and control variables

The t-stat values exceed the 95% confidence interval limit for the C.G proxy variable, the Stock exchange market, the past year volatility, year of introduction and the number of shareholder categories. In total, we have 2 valid C.G variables (our C.G proxy and the categories of shareholders) and 3 control variables (Stock exchange market, past year volatility, listing start date).

In terms of coefficients, we can see that the highest coefficient is for the stock exchange market dummy (0,61), followed by the C.G proxy dummy (0,32). The number of shareholders categories variable has a coefficient of 0,095.

These results enable us to conclude that while corporate governance proxies definitely have an impact on the financial performance measured by adjusted T.R.I, the coefficient of determination is quite low, which is coherent with the performed t-tests that do not confirm the mean difference between the group of CRMs with the C.G proxy and the other CRMS at the 95% confidence interval. Meanwhile, one of our control variables - Namely the stock exchange market category - has a more important impact on the financial performance measured by adjusted T.R.I. This conclusion is coherent with the t-tests that show that CRMS listed on NYSE or Nasdaq markets have a significantly higher adjusted T.R.I and lower volatility than CRMs listed on OTC markets.

8. Conclusion:

8.1. Main findings of our research

Our research on potential impact of corporate governance on financial performance of Chinese Reverse Mergers (CRMs) has shown that corporate governance structures do not have significant impact on the financial performance of CRMs. These findings are contradictory in regards to the literature, but can be explained by the difference in methods: Our proxy for corporate governance is quite simple and only takes into account the board structure, while other papers might have been able to experiment a more comprehensive approach of corporate governance mechanisms in emerging markets companies.

When applied to our sample of CRMs, the corporate governance mechanisms that appear in the board structure are not a significant determinant of the financial performance. Another reasons to explain this result in our research is the high variance in the Adjusted T.R.I used to measure the financial performance and the limited sample of observations (68).

But the research has revealed an interesting fact: If CRMs’ financial performance is not strongly impacted by corporate governance structure, it is highly impacted by the stock exchange market categories. Our findings indicate that CRMs that are listed on the OTC markets significantly underperform CRMs that are listed on regular markets - namely NYSE and Nasdaq. The listing category of CRMs also impacts significantly the stock volatility observed on a one-year basis.

8.2. Limits to the research

The investigation potential about CRMs has been limited throughout the research. For instance, alternative measurement factors such as operating performance were not available for our sample. The same applies for other values: P/E Ratio, sales growth, EBIT…

The limitations on data affected both financial performance measurement and corporate governance data. For corporate governance, the limited information on specific shareholder ownership and corporate governance disclosures means that we had to chose proxy values for corporate governance: First, if no information was available for the board structure, then we assumed that there was no corporate governance structure as defined in our proxy. Second, a corporate governance proxy is not an accurate indicator of the corporate governance of a company. For example: Existence of corporate governance and nomination committees in a reverse-merger company does not mean that the company follows specific corporate governance policies. The reverse-merger process itself limits the disclosures of a company usually required for due diligence.

Another major limit in our research is the size of our sample. 68 companies compose our observation sample for our study, which barely fits the normal distribution after the split between C.G variables, Stock market category, statutory auditor... A higher number of observations would have led to more reliable statistical tests and more accurate results.

Last but not least, Chinese companies listed in the US stock exchange markets and identified as Reverse Mergers have been facing short selling issues and defiance from investors since several accounting scandals broke out. As several of these scandals also involved companies audited by Big 4, the Big 4 caution does not work the same way in China as in western capital markets. It is likely that CRMs share prices might be more affected by the (bad) news from accounting scandals than by corporate governance issues (see Appendix n°10 for information). Since the measurement value we chose for financial performance includes share price variation, our financial performance measurement might have been biased by the news effect on shares price.

8.3. Potential developments for further research

If further research had to be done on the topic of financial performance of CRMs, it could be interesting to have a closer look on what differentiates CRM listed on regular Stock exchange versus CRMs listed on the OTC market and verify if they have an impact on the financial performance that we have measured in this research. Another approach can be to explain why some companies are listed on OTC and some are not. Did they choose to be listed on OTC market instead of a regular SE? If not, OTC market listing might be a consequence of bad financial performance.

Further research on the specific topic of CRMs could also analyze the potential impact of fraud allegations on the number of post-2011 Reverse Mergers. After 2011, it is not sure whether new reverse takeovers involving Chinese companies have happened. If Reverse Mergers are not popular anymore, did Chinese companies find new ways for financing on the US stock markets?

Another interesting research could include a broader analysis of corporate governance structures and financial performance for Reverse Mergers of different countries. As mentioned in our literature review, a country-based analysis of Reverse Mergers could lead to some interesting findings on how stock markets value corporate governance improvements according to companies’ different country origins.

8.4. Impact of the research and implications on investment in stock markets

Although Reverse Mergers are only representative of a very little sample of companies from emerging markets listed in the US, the conclusions we can learn from studying them is quite interesting and revelatory of relationship between company size and reputation, corporate governance and financial performance. If our corporate governance proxy does not show strong evidence of financial performance improvement, the listing category is a determinant factor in financial performance as measured by return index and can imply a lot in terms of listing requirements and listing strategy. From our research perspective, we would encourage investors to consider investing in CRMs listed on NYSE or Nasdaq markets, but to avoid invest in CRMs listed on OTC markets, since CRMs listed on OTC significantly underperform CRMs listed on NYSE or Nasdaq.

Further study should be undertaken in order to conclude whether the listing category of Reverse Mergers is a deliberate entry strategy or a consequence of insufficient regulatory filings or reporting quality over time. The objective is to know if CRMs listed on OTC have always been listed on OTC, or if they are formerly NYSE/Nasdaq traded stocks who ended up being traded on OTC due to regulatory fillings problems.

Looking ahead of Reverse Mergers, the recent news shows a come-back of Chinese listings in the US Markets with large tech companies (Alibaba, Sina Weibo, Qunar…) being listed in the first half of 2014. If this come-back is concerning large caps as of now, future developments and listings of mid or small caps are not excluded, although it seems unlikely that reverse merger will be popular again among Chinese companies. Since the heavy reputation damage CRMs have suffered since 2011, Chinese companies are now considering the listing place more carefully, as more and more CEOs claim that Asian investors are more likely to understand the specific business plan and economic environment better than US investors, hence valuing their companies with a higher market value³⁵. But as new emerging companies, especially Chinese technology start-ups, are still getting back on track in the US capital markets³⁶, the question of transparency and corporate governance might be considered as a potential future requirement to reduce corporate fraud, reputation risk and increase the relationship quality between emerging markets companies and US investors.

ACKNOWLEDGEMENTS

Through this acknowledgment, I express my sincere gratitude to all those people who have been associated with this assignment and have helped us with it and made it a worthwhile experience.

Firstly I extend my thanks to Professor Pramuan Bunkanwanicha from ESCP Europe and Yinghong SHAO from Tongji University who accepted to direct and review this thesis. They gave me valuable suggestions regarding the project report.

My thanks also go to Ada Liu, former Research Manager at China Economic Review, who supported me throughout my research on Chinese Reverse Mergers. This research would not have been possible without her advice and support.

GLOSSARY:

C.G: abbreviation for corporate governance

C.I: Confidence interval (used for t-tests and linear regression) CRM: Chinese Reverse Merger

T.R.I: abbreviation for Total Return Index. T.R.I is retained as our standard measure for financial performance. See Section 3.4

Adjusted T.R.I: T.R.I adjusted by super-sector index. This is our alternative measure for financial performance that we use in our research. See Section 3.4

RAS: Abbreviation for review and approval system for IPOs in China

S.E: Abbreviation for Stock Exchange

REFERENCES

Books & Reviews:

- Corporate Finance, Jonathan Berk, Peter DeMarzo (French version translated by, Pearson Education France, 2008)
- An introduction to statistics for managers, Ann Spooner, Colin Lewis - Prentice Hall, 1995
- China Economic Review n°6, June 2011
- IFRS 3 Business combination conclusions

Papers:

-Tobin's q and the Importance of Focus in Firm Performance, Birger Wernerfelt and Cynthia A. Montgomery, The American Economic Review, Vol. 78, No. 1 (Mar., 1988), pp. 246-250
-A Survey of Corporate Governance, Andrei Shleifer and Robert W. Vishny*, the Journal of Finance, vol. LII, n°2, June 1997
-Investor protection and corporate governance, Rafael La Porta, Florencio Lopez-de- Silanes, Andrei Shleifer, Robert Vishny, in Journal of financial economics n°58 (2000), p.3-27.
-Corporate Governance and Institutional Transparency in Emerging Markets, Carla C. J. M. Millar, Tarek I. Eldomiaty, Chong Ju Choi and Brian Hilton, Journal of Business Ethics, Vol. 59, No. 1/2, Voluntary Codes of Conduct for Multinational Corporations (Jun., 2005), pp. 163-174
-Corporate Governance, Investor Protection, and Performance in Emerging Markets, Leora F. Klapper, Inessa Love,The World Bank Development Research Group,Finance, April 2002
-An empirical investigation on underpricing in Chinese IPOs, Dongwei Su, Belton M. Fleisher, 1997
-Backing into being public: an exploratory analysis of reverse takeovers, Kimberly C.Gleasona, Leonard Rosenthalb, Roy A. Wiggins IIIb,* Journal of Corporate Finance 12 (2005) 54- 79
-The truth about Reverse Mergers, William K. Sjostrom jr. *, ENTREPRENEURIAL BUSINESS LAW JOURNAL [Vol. 2:2] SSRN id1028651
- Understanding Reverse Mergers: a first approach, Augusto Arellano-Ostoa, Sandro Brusco, Business Economics Series 11 Universidad Carlos III de Madrid, May 2002
-The Reverse Mergers - Alternatives to initial public offerings, Hurduzeu G., Vlad L.B. and Hurduzeu R., Business Excellence and Management, Volume 2 Issue 2 / June 2012
-Reverse Mergers: The Chinese Experience, Jan Jindra, Torben Voetmannb and Ralph A. Walklingc, Fisher College of Business Working Paper Series, October 2012
-Shell Games: Are Chinese Reverse Merger Firms Inherently Toxic? - Charles M. C. Lee, Kevin K. Li, and Ran Zhang** Draft: September 11th, 2013 http://ssrn.com/abstract=2155425
-The Spillover Effect of Fraud Allegations Against Chinese Reverse Mergers, Masako Darrough, Rong Huang, Sha Zhao, December 2013
-Cross-Border Reverse Mergers: Causes and consequences, Jordan I Siegel, Yanbo Wang, Harvard Business School Strategy Unit Working Paper No. 12-089, September 2013

Press articles and special reports:

-“How they Fell, the collapse of Chinese cross border listings”, Mc Kinsey report, Jan. 2013

-“Full Speed Reverse! The reverse merger, backing into wall street ’ s worst idea”, RCW Mirus Technology Group Research

http://www.bloomberg.com/news/2011-06-22/table-of-chinese-reverse-merger- companies-listed-on-u-s-stock-exchanges.html

http://pcaobus.org/News/Releases/Pages/03152011_ResearchNote.aspx

http://www.reuters.com/article/2011/08/01/us-shell-china- idUSTRE7702S520110801

About SEC and Reverse Mergers:

http://www.bloomberg.com/news/2011-06-22/table-of-chinese-reverse-merger- companies-listed-on-u-s-stock-exchanges.html

http://www.sec.gov/news/press/2011/2011-235.htm

http://www.sec.gov/investor/alerts/reversemergers.pdf

http://www.chinaeconomicreview.com/investor-chien-lee-says-dont-lump-all-prc- listings-together

http://www.chinaeconomicreview.com/China-on-wall-street-Nasdaq-58.com-qunar- IPO-PCAOB-NQ-mobile

Financial data sources :

-Bloomberg
-Thomson Reuters Datastream
-Thomson One Banker

APPENDICES

Appendix n°1: Linear regression n°1

Appendix n°2: Linear regression n°2

Appendix n°3: Table of Chinese Reverse Mergers -Financial performance data

Appendix n°4: Table of Chinese Reverse Mergers - Corporate Governance data

Appendix n°5: Table of Chinese Reverse Mergers - Other data - 1

Appendix n°6: Table of Chinese Reverse Mergers - Other data - 2

Appendix n°7: Table of Chinese Reverse Mergers - Ownership data

Appendix n°8: Original SIC codes classification table

Appendix n°9: Transition table between original SIC codes and our 6 sector dummies

Appendix n°10: Index of tables used in our research

Appendix n°11: Time series- Average T.R.I and sector-adjusted for CRMs since 2009

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Appendix n°1: Linear regression n°1

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Appendix n°2: Linear regression n°2

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Appendix n°3: Table of Chinese Reverse Mergers -Financial performance data

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Appendix n°4: Table of Chinese Reverse Mergers - Corporate Governance data

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Appendix n°5: Table of Chinese Reverse Mergers - Other data - 1

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Appendix n°6: Table of Chinese Reverse Mergers - Other data - 2

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Appendix n°7: Table of Chinese Reverse Mergers - Ownership data

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Appendix n°8: Original SIC codes classification table

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Appendix n°9: Transition table between original SIC codes and our 6 sector dummies

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Appendix n°10: Index of tables used in our research

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Appendix n°11: Time series- Average T.R.I and sector-adjusted for CRMs since 2009

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CV and publication

Education:

- ESCP Europe, Master in Management Grande Ecole - Ranked 2nd Master in Management worldwide by the Financial Times - Accreditations: EQUIS, AACSB Core Subjects: Financial Analysis, Corporate Finance and Risk Management, Empirical Research Methods
- Tongji University, Double-Degree program: Economics and Management
- Core Subjects: Finance, Management Strategy in China, Enterprise Risk Management

Professional experience:

- Jan 2014 - Current

Deloitte Risk Advisory - Financial Risk Management Consulting, Junior Consultant

- Feb-June 2013

KLB Group China - Consulting in automotive and chemicals sectors, China manager assistant

- Feb-Sept 2012

Alcatel-Lucent International - Global leader in telecommunications industry, Intern in the Central treasury Risk & Compliance department

- Sept 2011-Feb 2012

Mazars - Audit and consulting services, Audit intern, Banking and Media sectors

Publications:

- Corporate Governance and financial performance of Chinese Reverse Mergers, May 2014 - ESCP Europe, Tongji University

[...]

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¹ Interview with Michael YANG, Chief representative of NYSE’s Beijing office Special Issue - US listed Chinese firms, China Economic Review n°6, June 2011

² Reverse Mergers, the Chinese Experience, Jan Jindra, Torben Voetmannb and Ralph Walkingc

³ Shell Games, Are Chinese Reverse Mergers Inherently Toxic? Charles M. C. Lee, Kevin K. Li, and Ran Zhang, September 2013 (abstract version)

⁴ Corporate Governance, Investor Protection, and Performance in Emerging Markets , Leora F. Kappler and Inessa Love, The World Bank Development Research Group, April 2002

⁵ “How they Fell, the collapse of Chinese cross border listings ”, Mc Kinsey report, Jan. 2013

⁶ Corporate Finance (French edition), Jonathan Berk, Peter DeMarzo, Pearson education 2008.

⁷ Investor protection and corporate governance, Rafael La Porta, Florencio Lopez-de-Silanes, Andrei Shleifer, Robert Vishny, in Journal of financial economics n°58 (2000), p.3-27.

⁸ Tobin's q and the Importance of Focus in Firm Performance, Birger Wernerfelt and Cynthia A. Montgomery, The American Economic Review, Vol. 78, No. 1 (Mar., 1988), pp. 246-250

⁹ IFRS 3 - Business combination conclusions, 2012

¹⁰ A Survey of Corporate Governance, Andrei Shleifer and Robert W.Vishny, The Journal of Finance, VOL L.II, N2, June 1997

¹¹ Corporate Governance and Institutional Transparency in Emerging Markets, Carla C.J.M Millar, Tare I Eldomiaty, Chong Ju Choi, Brian Hilton, Journal of Business Ethics, Vol.59, N°1/2, Voluntary codes of conduct for multinational corporations, June 2005,p.163-174

¹² Corporate Governance, Investor Protection, and Performance in Emerging Markets , Leora F. Kappler and Inessa Love, The World Bank Development Research Group, April 2002

¹³ The Truth about Reverse Mergers, William K. Sjostrom Jr, Entreprenarial Business Law Journal Vol.2:2, p.744, / SSRN 2018651

¹⁴ http://www.investopedia.com/articles/stocks/09/introduction-reverse-mergers.asp

¹⁵ EY guide to going public http://www.ey.com/Publication/vwLUAssets/Ernst_and_Young_guide_to_going_public/$FILE/Guide_ to_Going_Public.pdf

¹⁶ http://www.investopedia.com/articles/stocks/09/introduction-reverse-mergers.asp

¹⁷ Full Speed Reverse! The reverse merger, backing into wall street ’ s worst idea, RCW Mirus Technology Group Research, p.2

¹⁸ Ibid, p.8

¹⁹ http://www.bloomberg.com/news/2011-06-09/-reverse-merger-stocks-may-be-prone-to-fraud- abuse-sec-says-in-warning.html

²⁰ Reuters special report : China ’ s shortcut to Wall Street, August 1 st 2011, http://www.reuters.com/article/2011/08/01/us-shell-china-idUSTRE7702S520110801

²¹ Shell Games: Are Chinese Reverse Merger Firms Inherently Toxic? Charles M. C. Lee, Kevin K. Li, and Ran Zhan, September 2013, p.1.

²² Regulation of initial public offering of shares in China, Wang Jiangyu, China Law 2009/01 - Original English Article - SSRN id 1382577, p.5

²³ Ibid, p.6

²⁴ See “An empirical investigation on underpricing in Chinese IPOs”, Dongwei Su, Belton M. Fleisher, 1997

²⁵ How they fell: The collapse of Chinese cross-border listings, David Cogman and Gordon Orr, Corporate Finance Practice, Mc Kinsey, December 2013.

²⁶ Cross-Border Reverse Mergers: Causes and consequences, Jordan I Siegel, Yanbo Wang, Harvard Business School Strategy Unit Working Paper No. 12-089, Sept. 2013

²⁷ http://www.bloomberg.com/news/2011-06-22/table-of-chinese-reverse-merger-companies-listed- on-u-s-stock-exchanges.html

²⁸ Ownership structure for one of the companies (Cogo Group, COGO-US)is missing due to a recent buyout. As a proxy value, we consider that the company is 100% owned by individual investors.

²⁹ Top 50 accounting firms rankings, Accountancyage.com 2013 / Top 20 accounting firms in 2013 - Big4accounting firms.org

³⁰ Thomson Reuters datastream content explanation for Total Return Index % change.

³¹ Datastream denomination is retained

³² Thomson Reuters Database data

³³ See the original classification in appendix n°5 and transition Table in appendix n°6 for more details about the structure of the 6 sector dummies

³⁴ An introduction to statistics for managers, Ann Spooner, Colin Lewis - Prentice Hall, 1995

³⁵ “ How they Fell, the collapse of Chinese cross border listings ”, Mc Kinsey report, Jan. 2013

³⁶ “ Amid new Chinese listings, investors must learn from the past ” , China Economic Review article, November 7th 2013 - http://www.chinaeconomicreview.com/China-on-wall-street-Nasdaq-58.com- qunar-IPO-PCAOB-NQ-mobile