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Review of Quantitative Finance and Accounting

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01.08.2016 | Original Research

Sneaking in the back door? An evaluation of reverse mergers and IPOs

verfasst von: Troy Pollard

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 2/2016

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Abstract

I examine whether the financial reporting quality of firms that access capital markets through reverse mergers differs from that of firms that rely on the traditional and more onerous IPO process. Using a broad sample of reverse merger firms and a propensity-score matched sample of IPOs, I find that reverse merger firms exhibit lower earnings quality as measured by several earnings attributes established in prior literature: accrual quality, earnings persistence, earnings predictability, cash persistence, cash predictability, earnings smoothness, timeliness, and value relevance. I document similar results for firms with low levels of institutional ownership. Differences in earnings quality, however, are attenuated for reverse merger firms with higher levels of institutional ownership. Given recent U.S. Securities and Exchange Commission enforcement actions against Chinese reverse merger firms, I also use a difference-in-differences technique and find that the lower financial reporting of reverse merger firms is actually driven by the non-Chinese reverse merger firms.

Vorheriger Artikel Market share and risk taking: the role of collateral asset managers in the collapse of the arbitrage CDO market

Nächster Artikel Political connections, financial constraints, and corporate investment

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I provide further institutional details on reverse merger transactions in Sect. 2.

Results are robust to the removal of firms identified as fraudulent and/or issued restated financial statements.

I use the terms “earnings quality” and “financial reporting quality” interchangeably.

I refer to Chinese reverse mergers as operating companies, located in China, that merge with shell companies that are listed on U.S. stock exchanges. 32 % of the sample reverse mergers are from China, 63 % are from the U.S. and the remaining 5 % are from other foreign countries.

The JOBS Act changed securities law to allow general solicitation for Regulation D offerings, which means that companies and their brokers may advertise to the general public. Critics are concerned this will allow brokers to solicit unsuspecting investors, e.g., the elderly. The JOBS Act also reduced financial reporting requirements for firms with <$1 billion in gross annual revenue in their most recently annual periods.

In its 10-K filing on March 31, 2008, Northern Oil and Gas Inc. described its decision to perform a reverse merger as follows: “This process avoids the high cost of the registration of securities for public sale, including attendant legal and accounting expenses, and the usually lengthy process involved in the registration of securities”.

Securities Act Rule 405 and Exchange Act Rule 12b-2 define a shell company as “a registrant, other than an asset-backed issuer … that has: (1) No or nominal operations; and (2) Either: (i) No or nominal assets; (ii) Assets consisting solely of cash and cash equivalents; or (iii) Assets consisting of any amount of cash and cash equivalents and nominal other assets”.

Reverse mergers occur on foreign exchanges as well, but I limit my analysis to U.S. exchanges due to data restrictions.

Reverse mergers can also occur between two operating public companies, which would meet the description of a reverse takeover. I have not included reverse takeovers in my sample, see Sect. 4.1 for further discussion.

Regulation D Rule 506 states: “[S]hares offered under Rule 506 are limited to no more than 35 purchasers. A corporation, partnership, or other entity shall be counted as one purchaser. Accredited investors are excluded from the calculation. Each purchaser who is not an accredited investor must have knowledge and experience in financial and business matters that he is capable of evaluating the merits and risks of the prospective investment”.

Instead of registering the shares, the company may leave the shares unregistered in which case the shares would be subject to the holding period of Rule 144 before resale.

Chu et al. (2014) examine reverse takeover firms, a similar yet different setting. Reverse takeovers (collected from Securities Data Corporation) are business combinations in which the acquiring company offers more than 50 % of its equity as consideration to the target company. While similar, these transactions can occur between two operating and reporting companies and thus likely did not use the reverse merger as a mechanism to go public. Additional details about reverse takeovers are provided in Sect. 4.1.

Other studies examine corporate governance (Siegel and Wang 2013) and the spillover effect of fraud allegations against Chinese reverse mergers on other Chinese firms (Darrough et al. 2013).

Some of the rule and rule amendments include (1) revising the definition of a “shell company,” (2) adding a check box to company annual and quarterly filings to identify shell companies filing those forms, (3) requiring shell companies to report on Form 8-K the transactions causing them to cease being shell companies, and (4) requiring the Form 8-K to be filed within four business days of the transaction instead of the previous 71-day filing window.

An S-1 includes detailed explanations of the services or products the firm provides, the risk factors associated with its industry and operations, the intended use of the money raised, as well as information about the firm’s officers and directors. IPO firms must respond to the SEC’s comments and file amended S-1 registration statements (Nahoum 2007).

Institutional investors are organizations (banks, insurance companies, pension funds, hedge funds, and mutual funds) that pool large sums of money and invest in securities. They meet the requirements to be accredited investors under Regulation D.

If either the reverse merger or IPO firms are closely held, then it is possible that a majority of the shareholders would have access to material non-public information. In this case earnings quality measures based on public information are not as relevant to them. However, my evaluation of the first year of public trading reveals that neither group of firms appears closely held. Reverse mergers had a mean (median) of 518 (226) shareholders, while IPOs had a mean (median) of 3,527 (165) shareholders.

DealFlow Media has staff dedicated to search for all shell reverse mergers as they occur. They search SEC filings, Lexus–Nexus, and other media outlets. DealFlow Media provides a paid subscription service with live data. Given the make-up of their customer base (investment banks, market analysts, venture capital firms, etc.) and their demand for current and accurate data, I rely on their search procedures to ensure completeness of the data.

My true population contains 440 reverse merger firms and 1,739 IPO firms. When bootstrapping, I randomly assign firms to the two respective groups in the same proportion as the original sample. For example, 20 % of the original sample is reverse merger firms. As such, my pseudo populations are randomly assigned, with 80 % of the firms assigned to IPOs and 20 % to reverse mergers.

In addition to the bootstrapping technique, I also use an F test to test the equality of the variances for Accrual Quality, Earnings Predictability, and Cash Predictability. I find similar statistical differences as indicated by the bootstrapping technique.

Matching was performed by using a one-to-one nearest-neighbor match without replacement. Results are robust to other matching specifications.

I find that 55 reverse mergers and 419 IPOs that did not have all variables available for the year prior to going public for the model and thus are excluded.

I scale all continuous variables by total assets and include a separate intercept term (Kothari et al. 2005).

Matching was performed on unwinsorized data and all analysis following used winsorized data. To verify the robustness of the matching procedure, I used an alternative procedure to identify matched firms. First, I eliminated observations in the top and bottom 1 % of the continuous matching variables. With the trimmed dataset 22 fewer matched pairs were identified (reduced to 305 from 327). However, results of the estimation model and subsequent matched-sample tests are quantitatively and qualitatively similar to the tabulated results.

Results of the matching procedure indicate that 58 reverse mergers are outside the common support. As such, these observations are thus excluded from Table 3 Panel C and further regression analysis to ensure the integrity of the matched pairs.

Another advantage of parametric procedures after matching is that results are doubly robust in that, if either the matching or the parametric model is correct (but not necessarily both), causal estimates will still be consistent (Robins and Rotnitzky 2001). The common procedure of matching followed by an unadjusted difference in means test does not possess this double robustness (Ho et al. 2007).

To further test whether results are driven by a size effect, I performed a double sorting at the median of size and institutional ownership. Within each of the four cells, I tested for differences in earnings attributes between reverse mergers and IPOs. For each of the four cells at least four earnings attributes are statistically significant in the predicted direction at p values <0.05. I also performed a double sorting into quartiles based on both size and institutional ownership. While this significantly reduces the power of the tests as the number of firms are divided into 16 cells, for the top quartile based on size, two earnings attributes exhibit statistical differences at conventional levels and a third attribute is significant based on a one-tailed test. Overall, results of double sorting are consistent with Table 5.

Bergstresser and Philippon (2006) note that earnings manipulation involves positive and negative accruals. Further, the Center for Audit Quality reported that from 2003 to 2012 there were a total of 3,192 restatements that involved a change in net income, of which 24 % involved an increase to net income (Scholz 2014). Given that firms have managed earnings in both directions, I use the absolute value of discretionary accruals as the dependent variable. In robustness tests I estimated the model using just positive accrual firms and then just negative accrual firms. Results are quantitatively and qualitatively similar.

Of the 440 firms in my reverse merger population, 144 are Chinese firms and 20 are located in other countries outside the U.S.

Ang et al. (2014) report that U.S.-listed Chinese companies involved in financial scandals were more likely to gain their U.S. listing via reverse mergers. Clearly, if the accounting reports have been fabricated or there have been significant audit failures then the earnings properties are meaningless. Thus as a robustness test, I removed all firms that restated their financial statements for any reason. After removing these misreporting firms, the results remain unchanged.

I also tested Chinese reverse mergers compared to all other reverse merger firms and found Chinese reverse mergers to exhibit stronger financial reporting quality.

An alternative approach is to base comparisons on alternative metrics constructed using a time series of firm-specific data. Data limitations preclude this approach because of short lifespan of reverse merger and IPO firms in the sample. It is also unclear whether this approach would result in more accurate inferences because firm-specific estimates would be based on a small number of observations, limiting power and introducing estimation error (Barth et al. 2008).

Given that accruals and cash flows have been found to be highly negatively correlated, parameter estimates could be unstable. Parameter estimates are unbiased, but small changes in the sample composition could cause changes in parameter estimates. Model 3 attempts to test the persistence of cash and results are robust to the inclusion or exclusion of lagged accruals in the model.

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Titel: Sneaking in the back door? An evaluation of reverse mergers and IPOs
verfasst von: Troy Pollard
Publikationsdatum: 01.08.2016
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 2/2016
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-015-0502-8

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