Revenue Management around Seasoned Equity Offerings
|Název práce v češtině:||Manipulace s výnosy před druhotnou emisí vlastního kapitálu|
|Název v anglickém jazyce:||Revenue Management around Seasoned Equity Offerings|
|Klíčová slova anglicky:||Revenues; Earnings management; Discretionary accruals; Seasoned Equity Offerings; Quality of Corporate Governance|
|Akademický rok vypsání:||2016/2017|
|Typ práce:||bakalářská práce|
|Ústav:||Institut ekonomických studií (23-IES)|
|Vedoucí / školitel:||Jiří Novák, M.Sc., Ph.D.|
|Řešitel:||skrytý - zadáno vedoucím/školitelem|
|Datum a čas obhajoby:||13.06.2018 09:00|
|Datum odevzdání elektronické podoby:||02.05.2018|
|Datum proběhlé obhajoby:||13.06.2018|
|Oponenti:||Mgr. Hana Džmuráňová, Ph.D.|
|Seznam odborné literatury|
|1. Stubben, Stephen R. “Discretionary Revenues as a Measure of Earnings Management.” The Accounting Review 85, no. 2 (March 1, 2010): 695–717. doi:10.2308/accr.2010.85.2.695
2. Cohen, Daniel A., and Paul Zarowin. “Accrual-Based and Real Earnings Management Activities around Seasoned Equity Offerings.” Journal of Accounting and Economics 50, no. 1 (May 2010): 2–19. doi:10.1016/j.jacceco.2010.01.002.
3. Shivakumar, Lakshmanan. “Do Firms Mislead Investors by Overstating Earnings before Seasoned Equity Offerings?” Journal of Accounting and Economics 29, no. 3 (June 2000): 339–71. doi:10.1016/S0165-4101(00)00026-4.
4. DuCharme, Larry L, Paul H Malatesta, and Stephan E Sefcik. “Earnings Management, Stock Issues, and Shareholder Lawsuits.” Journal of Financial Economics 71, no. 1 (January 2004): 27–49. doi:10.1016/S0304-405X(03)00182-X.
5. Turner, L., J. R. Dietrich, K. Anderson, and A. Bailey. 2001. Accounting restatements. Working paper, United States Securities and Exchange Commission, The Ohio State University, Georgetown University, and University of Illinois at Urbana–Champaign.
6. Feroz, Ehsan H., Kyungjoo Park, and Victor S. Pastena. “The Financial and Market Effects of the SEC’s Accounting and Auditing Enforcement Releases.” Journal of Accounting Research 29 (1991): 107–42. doi:10.2307/2491006.
7. Sherman, H. David, and S. David Young. “Where Financial Reporting Still Falls Short.” Harvard Business Review 94, no. 7 (2016): 17.
8. Shu, Pei-Gi, and Sue-Jane Chiang. “Firm Size, Timing, and Earnings Management of Seasoned Equity Offerings.” International Review of Economics & Finance 29 (January 2014): 177–94. doi:10.1016/j.iref.2013.05.011.
|Předběžná náplň práce v anglickém jazyce|
|Research question and motivation
Publicly listed companies have, excluding operations, two ways of financing its activities: debt and equity financing. If a firm decides to acquire new capital through offering shares to new investors we say that the firm performs seasoned equity offering (SEO). Naturally, the firm will have strong incentive to have as good results before SEO as possible simply because investor’s willingness to take part in the SEO depends on it. This incentive may sometimes lead to misreporting the results to the extent that it will no longer be in compliance with the reality. In order to prevent this publicly listed companies must have independent auditor opinion attached to its reports or, for instance, there is a possibility of being punished by regulators in case that the manipulation will be detected. But are those means strong enough to offset such incentive?
In my bachelor thesis I am going to study whether firms use revenue manipulation around SEOs. Based on the previous studies (e.g., Shivakumar, 2000; DuCharme et al., 2004; Cohen and Zarowin, 2010) SEOs are associated with earnings management and subsequent declines in operating performance. My intention is to build on the previous results resulting in my expectation that firms that issue SEOs exhibit evidence of revenue manipulation before SEOs, boosting its profits and return on investment in the short run and, on the other hand, subsequent decline in those variables in the long run. In order to test this statement I formulate following hypotheses:
H1: Firms that make Seasoned Equity Offering on average exhibit positive discretionary revenues before the issuance.
H2: There is negative association between discretionary revenues before Seasoned Equity Offering and after Seasoned Equity Offering
H1: According to statistics more than 70% actions taken by SEC in order to prevent accounting manipulation was against manipulation with revenues. This gives us strong evidence that revenue manipulation is the most common type of manipulation with accounting. Confirmation of this hypothesis is crucial for my research question. H2: Firms will need to reverse the manipulation in the years following SEO; those who used manipulation more than usual is expected to face more severe consequences of their actions. Confirmation of this hypothesis is crucial for the second part of my research question.
My motivation to work on this topic is that it has multiple applications in several sectors of finance. For instance, as said before, it has impact on investment decisions because rational investors will include the expected earnings management in pre-investment analysis. Another example can be that the regulators (SEC, Komise pro cenné papíry…) should be more likely to examine the accounting of firms around SEOs if the answer on my research question will be positive. Thus, the results of this study can be applied in real life.
This topic has been already studied multiple times but no one has examined it from the discretionary revenue point of view so far. Stubben showed that his discretionary revenue model (Stubben, 2010) outperforms accrual models both in detecting and failing to detect earnings management, as appropriate. Discretionary revenue model, by nature, fails to detect earnings management when only expense manipulation is used but Stubben also showed that the other models have troubles with detecting expense management as well. Furthermore, revenues are the most common type of financial restatement (Turner, 2001). Thus, revisiting research settings with the revenue model could shed light on whether significant results were driven by misspecification of accrual models. If I get to similar results using Stubben’s model we can claim that the bias of accruals models did not have crucial impact on the past results. From what was said above is clear that my contribution to the existing literature is not only adding new perspective but getting the assurance over the reliability of past results as well. Moreover, as far as I know, I am the first one to tell that revenue, one particular area of accounting, is manipulated somehow. Previous studies were unable to distinguish between what exactly is being manipulated.
In my bachelor thesis I will investigate revenue management in one year preceding SEO, in the year of SEO and one year after SEO. In order to get estimate of the discretionary revenue I am going to apply the conditional revenue model (Stubben, 2010) which models premature revenue recognition and its effect on the relation between revenues and accounts receivable. With respect to previous research premature recognition is expected to be the most commonly used form of revenue management (Feroz, 1991) resulting in believe that we can get quite a good proxy of revenue management by modeling only its premature recognition. The expectation is that the estimate will be positive in the year before SEO with the peak in the year in which SEO takes place and negative in the following years.
Using Stubben’s conditional revenue model the estimate of a firm’s discretionary revenue is the residual (ɛ) from the following equation :
Where AR are accounts receivable, R is revenue, SIZE is the natural log of total assets, AGE is the natural log of the firm’s age in years, AGESQ is its square, GRRP (N) is the positive (negative) industry-median-adjusted growth rate in revenues, GRM is the industry-median-adjusted gross margin and GRMSQ its square.
After solving this equation using multiple linear regression analysis on my data sample I should have an estimate of discretionary revenue which will be used as evidence to either prove or disprove my hypotheses.
• Abstract- In this section of my thesis I will briefly introduce what my research was about and show what I have found out.
• Introduction- In this section I will explain what SEO is, why do we believe that there will be some manipulation or, for instance, what is done to prevent it. After this introduction to the topic I specify my research question and what hypotheses will be tested.
• Literature review- I will introduce some of the previous papers on this topic, explain how previous research helped me to formulate my research question and hypotheses and what is my contribution to the existing literature.
• Methodology- In this part I will introduce my sample and how it was selected. I will also explain my approach to testing and why do I believe that this is the right way of doing it.
• Results and discussion- Here will be introduced the results of my testing and discussed some implications of this outcome.
• Conclusion – In this section I will discuss whether my results prove or disprove my hypotheses and conclude whether and how my research question was answered.
• List of references- In the last section I will provide detailed listing of literature used when working on my research.