Earnings management, cash flow volatility and corporate value
Name: Yongzhe Wei Student number: 11650427 Thesis supervisor: Qi Yang Date: Jun. 24, 2018
Word count: 12,339
MSc Accountancy & Control, specialization [Control]
Statement of Originality
This document is written by student Yongzhe Wei who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract
This paper uses American listed corporates’ financial data on the COMPUSTAT to test and verify the relationship between the cash flow volatility and corporate value. What’s more, earnings management is also an important research point in the financial file. After considering the existence of earnings management, I take earnings management into account and to test how earnings management affects the relationship between cash flow volatility and corporate value. According to my regression analysis, I proved that investors can identify and understand the intrinsic meanings of each component of the financial reports. What’s more, investors and analysts will give higher estimation of corporate value to those companies with smooth and stable cash flow when earnings management is not detected. However, as long as investors and analysts are aware of the existence of earnings management, the estimation of corporate value will be totally different. Investors will more prefer a company with more volatile cash flow when they know that companies are managing earnings. I will do further research t support my hypothesis.
Contents
1. Introduction ... 5
2. Literature review ... 8
2.1 Risk management theory ... 8
2.2 Agency theory ... 8
2.3 Prior literatures about firm value ... 9
2.4 Prior literatures about cash flow volatility ... 13
2.5 Prior literatures about earnings management ... 16
3 Methodology and measures for variables ... 19
3.1 Source of data ... 19
3.2 Measures for firm value ... 19
3.3 Measures for cash flow volatility ... 20
3.4 Measures for earnings management ... 21
3.5 Measures for other control variables ... 22
3.6 Methodology and regression models ... 23
3 Tests results ... 25
3.5 Descriptive statistics of variables ... 25
3.6 The correlation coefficients among variables ... 26
3.7 Multiple regression analysis of firm value and cash flow volatility ... 28
3.8 Robustness test ... 30
4 Conclusions ... 32
4.5 Cash flow volatility has negative effect on firm value ... 32
4.6 Earnings management changes the effect of cash flow volatility on firm value ... 32
1. Introduction
The most obvious way for outside investors, equity holders and debt holders to know the operation information of a company and to make some predictions of a company’s future development is based on the financial report. Among the financial report, cash flow statement is quite an important part to demonstrate how well a company generates cash to pay its debt obligations and fund its operating expenses. When company is going to conduct a project requiring big investments today, the cash flow statement in the following years will be affected. The cash flow will volatile. How will this volatility influence firm value with regard to outside investors’ opinion?
The relationship of cash flow and firm value is very important because it can influence the strategy decision and risk management of top managements, as well as whether a company should employ a smooth financial statement. Investors who look deeply into cash flow statements can use such information like cash flow volatility to determine their investment decision regarding cash flow statement in an attempt to make sure they can have a good return on their investments. The purpose of this thesis is to examine the relationship between the volatility of cash flow of a company and its corporate value. In that, this thesis aims to answer the following research question:
RQ1: How does the volatility of cash flow affect a firm’s value?
Empirical findings about how cash flow volatility impacts on a firm’s value are inconsistent from the previous research. Minton and Schrand (1999) point out that cash flow volatility is associated with higher costs of accessing external capital as well as higher possibility of need for outside investments. In the study of Minton and Schrand (1999), one important highlight is that a company with a stable cash flow should be highly evaluated and valued, because equity holders value the stable dividend payment. In short, the lower the cash flow volatility is the higher a firm’s value is. Minton and Schrand (1999) thought cash flow volatility will hurt investment. However, Black and Scholes (1973) said something opposite in an alternative point. They said that shareholders’ equity could be seen as a call option for the corporate assets. And according to their theory, a higher cash flow volatility as risks should increase the value of a call option, which means that high cash flow vitality lead to high firm value. The proposition of Black and Scholes (1973) and the study of Minton and Schrand (1999) are totally opposite. These two completely contrast propositions could both make sense from their own point because cash flow volatility means that company is taking risks and risk relates to higher return
in the future. But, high volatility could also mean possible loss if the risks taken is not under control. The above two opposite analysis goes from empirical studies of former literatures and theories and they do not have regression analysis to directly show the relationship. This study is going to directly detect the connection between cash flow volatility and a firm’s value through regression analysis of large public company samples. This study is intended to figure out whether cash flow volatility directly influences a firm’s value. If it is true, to what extent cash flow volatility is influencing a firm’s value.
Based on the prior research, intuitionally I think that a higher cash flow volatility leads to a lower valuation of firm value. Then it comes with the possibility that management will choose a smooth financial statement and management to show a better company performance. Graham, Harvey, and Rajgopal (2005) finds that a large sample of CFOs exhibit a nearly exclusive focus on earnings as opposed to cash flow targets. Actually, they report that firms may even forego some positive Net Present Value (NPV) projects in an effort to produce a smooth earnings stream, implying that corporate managers do perceive a positive market preference over lower earnings volatility while earnings volatility is directly related to cash flow volatility. Latif, Saira Yang Yi (2011) provides opposite results from sample examinations that ex ante earnings management eventually results in a less negative market reaction to adverse events like terminations. By that conclusion, it really supports what Graham, Harvey, and Rajgopal say, which a company should emphasize on the earnings management. This kind of findings clearly shows that it is very important for a firm to apply a good and convincing earnings management. However, Wu Shih-Wei et. al. (2012) say that the manipulation of earnings management shows a negative relationship between earnings management and investor stock returns, which represents investors won’t take the earnings management as a good signal. In order to clearly show how earnings management would influence the relationship between the cash flow volatility and firm value, hereby I propose my second research question:
RQ2: When investors and analysts detect earnings management, how does the volatility of cash flow affect a firm’s value evaluated by investors and analysts?
Would the emergence of earnings management in the financial report change investors’ idea about the relationship between cash flow volatility and firm value? When investors discover the earnings management in financial reports, how will investors, outside equity holders and debt holders consider cash flow volatility. Are they still going to stick to the previous investment decision? Or the earnings management would make the relationship of cash flow volatility and firm value to be better off. This is important to investors who care about and
consider earnings management as an action that should be punished and want to find a solution to accurately analyze the firm value and its potential return for his investment under the circumstances of earnings management.
The paper proceeds as follows. Section 2 explains an outline of various predictions and hypothesis of cash flow volatility, firm value and earnings management referred to in the financial statement. Section 3 shows measures for cash flow volatility, firm value and earnings management and discusses the methodology for analysis of the relationship between cash flow volatility and firm value and this relationship under earnings management. Section 4 uses data from selected European public company samples to test hypothesis and then drills down this relationship of cash flow volatility and firm value by analyzing what happens when we take the existence of earnings management into consideration as well as results of all tests. Section 5 provides conclusions of this study.
2. Literature review
2.1 Risk management theory
This paper aims at researching the association between firm value and cash flow volatility. Talking about volatility, the first idea that I come up with the cash flow volatility is risk. It is very often to see or hear from the news that the cash flow becomes volatile for a company when it faces some unexpected problems or difficulties. In this situation, it is very important to have a mature and well-functioned risk management strategy and system.
Based on the article of Nocco and Stulz (2006), enterprise risk management can create value through its effect on a company at both macro and micro level. Macro level refers to the top management and micro level usually refers to business units. For top management, enterprise risk management can help create value by assisting top management to manage to make a tradeoff between risk and return. At the business unit level, all lower level managers and employees will stick to the company strategy if there is a well-designed risk management system.
The first step of risk management is to identify and characterize potential threats to a company. And then assess the result of these potential threats to specific assets that will be influenced by certain critical threats. After that, it comes to the most important part. This part is about how to figure out a way to reduce and mitigate the possible consequences of certain threats. In this paper, due to various kinds of reasons including global financial crisis or impact of new technology, a company have appeared a situation called cash flow volatility. To deal with this situation, some companies may take actions like hedging to smooth the cash flow, as a way to reduce this risk in advance. Some companies may feel that they will not be affected by certain cash flow volatility.
2.2 Agency theory
Agency theory extends the analysis of the firm management to separating ownership and control, and managerial motivation. It gives me another aspect to value the firm value from the actions of top management behavior like earnings management. In the research field of corporate risk management, agency issues have been clearly stated to affect management attitudes toward risk appetite and risk averse actions (Smith and Stulz (1985)). Theory also explains a probable mismatch of interest between shareholders, top managements and debt
holders due to inforamtion asymmetries in firm profit distribution, which can lead to the firm taking too much risk or not engaging in positive net present value projects (Mayers and Smith (1987)). Consequently, agency theory indicates that defined hedging and earnings management policies can have important influence on firm value (Fite and Pfleiderer (1995)).
Managerial earnings management in implementation of corporate risk management have been empirically investigated in a few studies with a negative effect on firm value (Faff and Nguyen (2002), MacCrimmon, Wehrung (1990) and Geczy et al. (1997)). Notably, positive evidence was found however by Tufano (1996) in his analysis of the gold mining industry in the US. Agency theory provides strong support for earnings management as a response to mismatch between management profit and shareholder interests. That could be some reasons that outside shareholders underestimate the value of a company when they find a tiny proof or possibility of earnings management.
2.3 Prior literatures about firm value
In the early 1960s, equity market started to emerge. Meanwhile, scholars proposed the idea of enterprise value, which is the origin of the following studies. The ownership of a company and company itself became a kind of special goods because company equities can be traded freely in the stock market. Once the ownership can be traded freely on the equity market and it can be evaluated and assessed by investors, equity evolves from simple proof of ownership to a kind of special merchandise. In Fang, Noe and Tice (2009), they define the firm value as a combination of company operation condition and profitability, which can reflect the outside investors’ view on this company. A precise and correct definition of firm value is the foundation of the following research. Out of different perspectives, I can have different definition of firm value. For example, firm value is defined as the present value of the future profitability of a firm or firm value is defined as the total value of the life-time asset value of a firm by the accounting principle like IFRS.
However, with the equity market growing and the study of concerned fields developing, the firm value will have more definitions from different perspectives. As for now, the firm value can be viewed as the intrinsic value of its asset including life-time profitability. Firm value can also be seen extrinsic value decided by the outside investors’ assessment based on the equity trading market. This shows that different perspectives can lead to different definitions of firm value.
What’s more, equity market has a great influence on the company. And how to create value for equity holders becomes an important part of the company strategy. In that, top management pays more and more attention to managing firm value as well as to facts and factors that can influence firm value. The ability to identify factors influencing firm value is closely connected to improving operational efficiency and outcome. Out of this reason, a lot of scholars devoted themselves to related fields of recognizing factors influencing firm value.
For listed companies, they put a lot of emphasis on the indicators related to firm value that can directly reflect the operational situations, like company net profit, earnings per share, etc. Harvey and Shirley (1981) used to make a research concerning British flight industry and they find that the increased asset turnover rate can effectively increase the enterprise value. Bernard (1993) shows that 55% of firm value is affected by its book value and return on asset is another effective explanatory variable for firm value when researching American public company. Combining book value and return on asset together can explain 64% of the firm value. Penman (1992) and Ohlson (1995) conclude that the present value of company’s future earnings should be at least equal to its cost to acquiring assets, so the asset book value can present the lowest possible earnings in the future. Thus, company book value is the bottom line for assessing its firm value. Raymond and John (1998) also use sample companies from Britain, Norway and Germany to research the relationship between book value and company firm value as well as return on asset and company firm value. As a result, Raymond and John (1998) find that book value and return on asset are significantly and positively related to the stock price of listed companies, but this relationship will be affected by accounting principle policies in different areas. Hollis and Per (2002) get similar conclusions through their researches. They find that when companies employ different accounting principle, for outside shareholders the reliability of its financial indicators for firm value will be different.
Other than financial indicators that can affect firm value, there are also many non-financial factors that can also influence firm value. Jenson and Meckling (1976) propose that the higher the administrative expense is, the fewer agency problems will be and these agency problems are usually connected to the decrease of firm value. So that top management will can maximize the profit of shareholders and improve firm value. Meanwhile, Jenson and Meckling (1976) classify the shareholders into two parts, inside shareholders and outside ones. Top management as inside shareholders can effectively decrease the agency problems and firm value will increase along with the increase of the number of inside shareholders. Mehran (1995) using American manufacturing industry as sample also concludes that company management holding
certain number of shares can effectively increase the firm value through better operation performance. Shleifer Vishny (1993) shows that firm value can be explained by the equity structure of the enterprise and firm value will be increased by the influence of major shareholders. Similar researches are conducted including McConnel and Servaes (1990), Jain and Kini (1994), Yermark (1996) and Wenyi Chu (2009). McConnel and Servaes (1990) use non-financial companies to do their researches and they find that equity structure does have great influence on firm value. McConnel and Servaes (1990) conclude that firm value is maximized when 40% of total company shares are held by manager and employees. Jain and Kini (1994)’s research of American listed companies shows that inside shareholders can bring long-time market income and this market income can increase firm value. Yermark (1996) makes a research about how the scale of board of directors can influence firm value. In the end, Yermark (1996) concludes that scale of board of directors is negatively associated with firm value. More members in the board of directors can decrease firm value and especially the deductive effect are at peak in the very early stage of increasing directors. Wenyi Chu (2009) bases his research on the company data from Hongkong. Wenyi Chu (2009) concludes that family business is significantly associated with firm value. When the enterprise is owned by a family, the higher percentage of shares are owned by this family, the higher value of this company will be. Besides, diversified operation strategy will decrease the firm value and more emphasis on research and development will give rise to increasing firm value.
Based on the definition of firm value, scholars develop various methods to assess firm value. For example, one way is called discounted cash flow method. Discounted cash flow is based on accounting method to assess firm value. Irving Fisher (1930) conduct a research and developed this method. Discounted cash flow method uses certain discounting rate to calculate the present value of expected future revenue and this method uses this present value as an indicator to assess firm value. On the basis of discounted cash flow method research, Franco and Miller (1958) propose famous MM theory intended to improve discounted cash flow method because discounted cash flow method do not take the corporate capital structure and government tax into account. As a result, Franco and Miller (1958) propose the idea that companies can increase firm value by managing their debts to reduce government income tax. There are several ways of applying discounted cash flow method. One is to discount dividends, and another is to discount expected net future cash flow. However, there are two basic requirements for discounting dividends. First, the corporate must have certain pattern of giving dividends and the business duration time needs to be known. Second, it is essential to assume
a reasonable discounting rate. However, it is not practical to discount cash flow because a lot of corporates usually don’t give dividends and the business duration time is also hard to predict. So, I cannot use discounted cash flow method for assessing my firm value.
Relative pricing method is also a good way to assess firm value, but it also has some shortcomings. In order to assess firm value of a company by relative pricing method, first I need to find another company in the same industry with similar conditions. And then considering some indicators like P/E ratio, P/B ratio, etc. to assess the firm value. Fer example, I can use P/E ratio of the similar company in the same industry to calculate the total market value of object company by multiplying outside shares by a relative company P/E ratio. However, using relative pricing method cannot assess a company currently in loss.
Tobin’s Q ratio can be used to assess firm value through forming a proportion ratio. The calculation is the corporate market value divided by the cost of replacement. James Tobin (1969) propose this method to assess firm value and this method is also named after him. Tobin’s Q ratio is universally applied in finance area because this method does not need to take consider depreciation into consideration and use market investment information to decide the firm value. While it is quite hard to get precise replacement cost, practically replacement cost is approximately estimated by book value. There are two most accepted ways to calculate Tobin’s Q ratio. One is market value / (total asset - intangible asset). Another is (corporate market value + debt book value) / total asset. Tobin’s Q ratio reflect the future growth of the company. The higher Tobin’s Q ratio is, the better company it will be in the future. If Tobin's Q ratio is greater than one, then the market value is greater than the book value of the company's asset. This suggests that the market value reflects some unmeasured or unrecorded assets of the company. High Tobin's Q ratio encourages companies to invest more in capital because they are worth more than the price they paid for them. On the other hand, if Tobin's Q ratio is less than one, the market value is less than the recorded book value of the assets. This suggests that the market may be undervaluing the company.
Among the above three methods for assessing firm value, discounted cash flow method and relative pricing method has some shortcomings. Discounted cash flow method is hard for me to decide a discounting rate fit for all company and the prediction of future revenue will also have deviations. Firm value is also known as enterprise value. Firm value is the amount of a company's total value, often used as a more comprehensive alternative to equity market capitalization. Enterprise value can be thought of as the theoretical takeover price if a company were to be bought. This study is going to use Tobin’s Q ratio as a proxy for firm value. This
methodology is common in the prior literatures. For instance, the methodology has been applied in corporate diversifications (Lang and Stulz (1994), and Servaes (1996)), cross-listing (Doidge, Karolyi, and Stulz (2003)), equity holders (La Porta, Lopez de Silanes, Shleifer Vishny (2002) and Lins (2003)), and risk managements (Shin and Stulz (2000), and Allayannis and Weston (2001)), takeovers (Servaes (1991)). So, I will use Tobin’s Q ratio to evaluate firm value for the reason that it can better compare companies from different industries on a reliable level.
2.4 Prior literatures about cash flow volatility
According to the corporate risk management theory, investors are better off when a firm maintains a smooth cash flow. In the traditional corporate finance research area, scholars (Froot, Scharfstein and Stein (1993), Vuolteenaho (2002) and Zhang (2006)) universally consider that investors will prefer those companies with stable cash flow. In other words, the higher the cash flow volatility is, the lower a firm’s value is.
To be specific, Froot, Scharfstein and Stein (1993) figure out that a stable cash flow could ensure the cash needed for the security of investments and continuing operation of the companies and then it can decrease the dependence on the expensive external finance. Thus, there are fewer constraints and limits implemented on such a company to deploy its investment projects for taking more risks and then the company can have higher payback. In other words, the low reliance on the public capital could increase the potential value of a company.
Vuolteenaho (2002) shows that stock returns are driven by shocks to cash flow or shocks to discounting rate. Shocks to cash flow refers to news or information about future cash flow. Usually, such shocks are followed by cash flow volatilities including cash flow shortfall or boost. Same consequence also applies to the shocks to discounting rate. According to the dividend discounting model, once the future return or discounting rate changes it will definitely affect present firm value.
In Zhang (2006), he concludes that greater information uncertainty about the impact of news (e.g. cash flow volatility) on stock value results in higher expected stock returns following good news. When there is less information asymmetry or uncertainty about bad news (e.g. cash flow volatility), the expected stock return will be lower. Considering above conclusion, the employment of earnings management will lead to the information uncertainty of cash flow
volatility. So, it is very possible that earnings management will have incremental effect on the cash flow volatility. Earnings management may promote investors to make even higher or lower estimation on firm value than their original one.
What’s more, due to the reliable and universally accepted study of Froot, Scharfstein and Stein (1993), higher future payback should be recognized and presented as high firm value of today. The volatility of cash flow can be considered as a symbol or a signal of taking more risk. So, an increased volatility of cash flow implies the increase of a firm’s value, because to some extent, cash flow can determine a firm’s value and a firm’s value is what the investors care about. By finding out the abnormal or unusual volatility in the cash flow statement, I think that it is helpful for investors to make a better investment decision. Investors are more likely to invest in a company with higher value and potential to grow, so when investors are making their investing decisions, paying attention to abnormal volatility in the cash flow statement could be a good to discover a golden chance. The information contained in the cash flow statement could tell an investor how this company is operating now and how the future value of this company is possibly going to be. Although it is a mainstream to evaluate a company’s financial performance by paying attention to its return on capital employed (ROCE) or return on investment (ROI), more and more investors also don’t forget to concentrate on the company cash flow statement to make sure their payback of investment. This study will emphasize on how the volatility of cash flow affects a firm’s value.
According to IAS 7 - statement of cash flows, the statement of cash flows analyses changes in cash and cash equivalents during a period. Cash and cash equivalents consist of cash on hand and demand deposits, together with short-term, highly liquid investments that are readily convertible to a known amount of cash, and that are subject to an insignificant risk of changes in value. Cash flow volatility is defined as the variation in a firm's quarterly operating cash flow. The resulting metric is a measure of cash flow variation that has been employed by Albrecht and Richardson (1990) and Michelson et al. (1995).
Researches about cash flow volatility are enormous. Some scholars take cash flow volatility as a risk, like the study of Black and Scholes (1973). According to the option pricing theory of Black and Scholes (1973), the equity could be seen as a call option. When the cash flow volatility represents the uncertainty of a company’s future return on equity, this uncertainty will increase the value of this call option. Since uncertainty is associated with a higher expected return, the higher volatility of cash flow could increase valuation of the corporate value. From this prospective, equity value as a call option can undoubtedly increase present value due to
discounting a higher return in the future. In short, the higher cash flow volatility is the higher a firm’s value will be. Considerable researches (Yin Yugang and Tian Rongfu (2017), Kriele Marcus and Wolf Jochen (2014) and Bohnert, Gatzert, Hoyt and Lechner (2017)) have been conducted with attention to enterprise risk management interacted with firm value. To better comprehend the influence and effect of corporate risk on firm value, I explore existing relevant studies to figure out how risks would affect firm value by concentrating on the only one representative of risks, namely cash flow volatility, and deeply drill down how cash flow volatility as a risk affects firm value.
Firm value is associated with many internal and external aspects of a firm. Internal aspects can be profitability, risk management, company strategy and operation. External aspects can be policies, market, etc. Among these aspects, profitability of a company is a relatively more important one. However, Jayaraman (2008) points out that the profitability will be affected by the accounting principle and financial information manipulated, so it is not a very convincing and accurate indicator in the corporate evaluation. To solve the inaccuracy of profitability, Teoh, Welch and Wong (1998) divides net profit into free cash flow and accrual profit, which can calculate the volatility rate of each. Then, the evaluation of a company can be determined by the future cash inflow, because cash flow is easier to be traced, which is hard to be manipulated by the managements. Cash flow more truthfully and accurately represent company financial performance from the investors’ own profit, because cash flow generated can assure the capital expenditure and dividends. These two are the cash paid to debt holders and equity holders. That is why cash flow statement means so much to investors. As long as a company expands and invests to a new project or asset, there is always some cash flow shortfall. So, it is very common to see cash flow volatility in the cash flow statement. Jayaraman (2008) and Rountree, Weston and Allayannis (2008) suggest that higher volatility of cash flow implying higher risk of operation and then investors will ask for higher return of investment. This is a proof for the risk-return tradeoff which is the principle that potential return rises with an increase in risk. Low levels of uncertainty or risk are associated with low potential returns, whereas high levels of uncertainty or risk are associated with high potential returns.
Prior empirical studies in risk management have answered a variety of important questions about risks related to firm value. For example, Kriele and Wolf (2014), Bohnert, Gatzert, Hoyt and Lechner (2017), Thöns (2018), Pérez‐González and Yun (2013), Dos Santos, Lima, Gatsios and De Almeida (2017), Li, Wang, Yu and An (2015) and Hogarth, Hutchinson and Scaife (2016), among these articles, have examined firm characteristics, all kinds of information
monitoring, hedging with weather derivatives, factors like corporate reputation, etc. to show the value effect of risk management. These studies are across industries or within industries and are limited to one country or across several countries. These studies are using all kinds of related financial derivatives to examine how hedging practices work for financial profits. In other words, how uncertainty can be related to future value created, which proves how risks can add future value of a company. In that, they consider that risks which can be under well management are potential signal for investors to see the future value that might be created. In some simple words, risks should actually add value to a corporate if everything goes well. So, first hypothesis is as follows:
Hypothesis 1: A company with a volatile cash flow is less valuable than a company with a stable and smooth cash flow.
There is a lot of other ways to analyze the risks like cash flow volatility interacted with the firm value. For example, CAPM tells that systematic risk should be negatively related to value, since higher discount rates yield a lower value. What’s more, recent empirical work suggests that not only systematic risks will affect value, but also idiosyncratic risks need to be taken into account. For example, Shin and Stulz (2000) examine the relationship between systematic, unsystematic, total risk, and firm value in a large sample of firms. This study complements these above studies about risks interacted with the corporate value by focusing on one specific form of risks, cash flow volatility.
2.5 Prior literatures about earnings management
Since cash flow volatility is considered as a risk for company, top management must find out a way to mitigate and manage this risk. According to De Jong Abe (2014), survey evidence shows that CFOs believe that earnings management can enhance the valuation of their firms. Taking the relevance of earnings management and cash flow into consideration, I can conclude from the prior literature that earnings management exists in companies’ financial reports to provide tax shields or to show a better performance. However, things are not always leading to a good result. Earnings management will give misleading information to the market, which is harmful to the interest of investors as well as the evaluation of firm value. (Teoh et al. (2008)) earnings management is also one way to mitigate the influence of cash flow volatility. Some shareholders and analysts (Wu Shih-Wei, Lin Fengyi and Fang Wenchang (2012)) respond negatively to earnings management. They consider the existence of earnings management as a negative signal for operation condition of a company. Investors may ask what if the risk
management fails? Risks can be out of control. It is not very rare to see the bankruptcy of a company with high risks and claimed high return rates. Especially before the bankruptcy is exposed to the public by some parties like auditors or public media, companies facing the possibility to bankrupt will do something crazy to pretend that they are still in good operation. In such a situation, earnings management of course is a negative signal to investors. Because this is much more beyond earnings management. It is scandal, fraud, cooking the book, etc. Regardless of the potential frauds, the second step I take is to find out how the earnings management will influence the relationship between cash volatility and firm value.
Many related literatures (Teoh, S. H., I. Welch and T. J. Wong (1998)) show that investors always overestimate corporate value in the capital market due to not finding out the earnings management behaviors in time, so that investors are misled by such earnings management. Meanwhile, stock price could not fully express the impound information in accruals about future earnings (Sloan, R. (1996)). The research of Sloan et al. is mainly related to the influence of accrual profit and cash flow information to the stock price change. Above articles pay attention neither to the volatility of each part of cash flow in the financial report nor to the influence of accrual cash flow information to corporate value in long term. Thus, I am going to separately examine the volatility of cash flow to find out what the internal relationship is between cash flow volatility and firm value under earnings management, so that we can see how investors could identify and interpret the intrinsic meaning of the information from financial statement, specifically cash flow statement. As mentioned before, investors tend to overestimate a firm’s value due to earnings management. When earnings management is aiming to smooth the cash flow to show a company under good operation, it is usually trying to conceal some very big operating failures or operating losses. By interpreting such information in financial report, investors should make a lower estimation of firm value to those companies with earnings management. Based on the discussion above, I assume:
Hypothesis 2: When detecting the earnings management, a company with a stable and smooth cash flow is less valuable than a company with a volatile cash flow.
Earnings management is also related to the quality of financial reports and this study also contributes to the research of the information quality by analyzing the indicator cash flow volatility to accurately understand a financial report containing earnings management. It is widely accepted that earnings management is intended to present a consistent profit, because conservative investors hate fluctuations and risks. When a company has a relatively good cash flow, its future cash inflow will be well guaranteed to pay dividends to equity holders and
interests to debt holders. Once a firm’s cash flow becomes much more volatile than usual cash flow, the investors will naturally ask for higher return of investment due to the potential risk indicated by the volatility, which alternatively increases the equity cost. Meanwhile, Jayaraman, S. (2008) points out that the volatility will be affected by the accounting principle and financial information manipulation, which means that cash flow volatility could also be a very easily affected financial factors by the management through the change of accounting principle and accounting methods. A lot of other related literatures like Yin and Tian (2017), Krishnan, Wen and Zhao (2011), etc. also give proof for some concerns about the financial report quality in public companies as empirical evidence. Yin and Tian (2017) find that investor’s sentiment about future stock price crash risk is strengthened by the poor financial reporting quality. In that, the second contribution of my paper is to give a convincible indicator for valuation of corporate value under earnings management by using the volatility of cash flow and it can help the investors better understand corporate financial report to support their decision making. I will use regressions analysis of public companies to show whether and how earnings management would influence cash flow volatility.
3 Methodology and measures for variables
3.1 Source of data
The research objects are the public companies of North America, because it is the largest equity market in the world and the equity of over five thousand companies are now being traded every day in NASDAQ. Compared with the equity market of other places in the world, I think, the equity market of America is more complicated and mature. Besides, American investors are closer to the idealized type of investors which means that they have a good prediction of the possible incidents and future results. Regarding the long history of North American equity market, the stock prices are better reflecting the true value of these companies. Besides, there are more public companies traded in the North America equity market than others. Recently, the Federal Reserve System announced that they are going to increase the benchmark interest rate. Historically, the increase of benchmark interest rate will greatly affect the stock market investment all over the world, especially those investors in America. When the benchmark interest rate raises, it is more expensive for investors and companies to borrow money from bank. Therefore, they need to make sure their investment returns. Under this situation, the cash flow becomes even more important for the assurance of payback. So, it could be really interesting to analyze the last several years’ market data and analyze the correlation of a firm’s value and its cash flow.
My sample incudes all firms with non-missing observations with revenue, sales, asset, working capital, market value, equity book value and selling and administrative expenses for which I found matching on the COMPUSTAT data base between 2011 and 2017. For the purpose of calculating the cash flow volatility, I need non-missing data for 4 quarters a year and for 7 years. And this is a very strong data requirement. So, at last I have a sample consisted of 1259 companies with non-missing data from 2011 to 2017.
3.2 Measures for firm value
For the regression model of this study, there are two main explanatory variables, a firm’s value and its cash flow volatility. As I said in the above literature review, stock price is not a very precise indicator for firm value, because it can be affected by many noises. So instead I use Tobin's Q Ratio to present a firm’s value. Tobin’s Q ratio is a universally accepted indicator for many researchers to evaluate a company value on the long-term basis (Chung Pruitt (1994), Rountree (2008)). Tobin’s Q ratio is the ratio between a physical asset's market value and its
replacement value. Approximately, the equation for Tobin’s Q ratio is a firm’s equity market value plus debt book value divided by a firm’s equity book value (Garg. (2007)).
The firm’s equity market value is the fair value on the stock market which is constructed by the stock price multiplying the number of shares outstanding. The firm’s equity book value is equity value from balance sheet.
The equation is:
Tobin’s Q ratio = (MV + DBV)/TA MV = corporate market value DBV = book value of debt TA = book value of total asset
3.3 Measures for cash flow volatility
According to Minton and Schrand (1999), I use operating cash flow to present the cash flow from certain period of operation instead of simple cash flow from the operating activities. Operating cash flow is calculated quarterly for all non-financial firms on COMPUSTAT as sales less cost of goods sold, less selling, general and administrative expenses and less the changes in working capital of that period. Working capital is current assets other than cash and short-term investments less current liabilities and it is computed as the sum of the non-missing amounts for accounts receivable, inventory and other current assets less the sum of the non-missing amounts for accounts payable, income taxes payable and other current liabilities. Quarterly selling, general and administrative expenses exclude one-quarter of annual research and development costs and advertising expenses when those data are available. Thus, operating cash flow represents the cash flow for the operation results of a period and this can be used to calculate the cash flow volatility.
The simple equation is:
Operating cash flow = REV - CGS - SGAE – ΔWC REV = revenue of that period.
CGS = cost of goods sold in that period
ΔWC = changes of net working capital which is the current net working capital less the net working capital of previous period
Cash flow volatility is defined as the variation in a firm's quarterly operating cash flow per share over the six-year period preceding each of the seven sample years from 2011 through 2017 according to prior researches. This is a reasonable and reliable measures accepted by empirical studies (Chihmin Hung and Daiki Wakayama (2005)). Thus, for the sample year 2017, the volatility of cash flow is calculated using data of 28 quarters from the first quarter of fiscal year 2011 to the fourth quarter of fiscal year 2017. A firm is included in the sample if it has at least 15 continuing observations during the 24 quarters. The volatility of cash flow is the standard deviation of operating cash flow per share for 28 quarters from 2011 to 2017. The resulting metric is a unitless measure of variation that has been employed by Albrecht and Richardson (1990) and Michelson et al. (1995).
The equation for cash flow volatility is:
Volatility of cash flow = STDEV (CF1, CF2, …., CF28)
STDEV (CF1, CF2, …., CF28) = the standard deviation of 28-quarter operating cash flow per
share from 2011 to 2017.
3.4 Measures for earnings management
As for the second regression model including earnings management, I will use the modified Jones model to estimate the level of earnings management. (Patricia M. Dechow et al. (2018)) This modified version of the Jones Model is based on the empirical analysis and the modification is designed in order to eliminate the conjectured attempt of the Jones Model to measure discretionary accruals with error when discretion is exercised over revenues. In the modified model, nondiscretionary accruals are estimated during the event period (i.e., during periods in which earnings management is assumed to exist) as:
NDAt = a1 * (1/ At-1) + a2 * (ΔREVt - ΔRECt) + a3 * PPEt
At-1 = the total assets at year t-1.
ΔREVt = the revenue in year t minus the revenue in year t-1 scaled by total assets in
year t-1.
ΔRECt = the net receivables in year t minus net receivables in year t-1 scaled by total
PPEt = the gross properties and equipment in year t scaled by total assets in year t-1.
a1, a2 and a3 are firm-specific parameters which are OLS estimates calculated by
using the OLS regression model.
Where the NDAt refers to the nondiscretionary accruals of year t, which is relatively the higher the better.
The earnings management is defined as the discretionary accruals (DA) by Michelson et al. (1995).
By total accruals less nondiscretionary accruals, we can get the number of discretionary accruals, which indicates the level of earnings management. Total accruals are the difference of net income and net operating cash flow. The equation is as the following:
TAt = NIt -CFOt
What’s more, TAt = a1 * (1/ At-1) + a2 * (ΔREVt - ΔRECt) + a3 * PPEt + e
Because TAt = NDAt + DAt, then according to the regression, we can see that the residual value
of the regression of TA will be the discretionary accruals of year t, which will be used in the following analysis of the association of firm value, cash flow volatility and earnings management.
3.5 Measures for other control variables
I use the characteristic variables of the company as control variables. These characteristic variables include leverage ratio, return on assets and company size. Company size is evaluated by the total assets of the company (Froot (1993)). The possibility of bad debt and earnings management will increase with the growing company size because when company size becomes bigger, the financial report and financial data will become more complex. Thus, firm of bigger size are more likely to manage its earnings and are harder to implement effective administration. So, I expect that the firm value is negatively related to company size.
I use debt / asset to evaluate the leverage ratio which are universally applied in prior studies (Rajan Zingales (1995)). Companies with relatively higher leverage ratio will face the pressure to pay back debts and interest. Thus, companies with relatively higher leverage ratio must have enough cash to deal with any unexpected risk and intend to accept projects with higher risks. Large capital shortfall followed by failure of high risk project could lead to bankrupt. This possibility of capital shortfall is increased with leverage ratio. Thus, investors underestimate
companies with high leverage ratio. So, I presume that leverage ratio is negatively related to firm value.
Considering different companies with different profitability, I use return on asset to evaluate company profitability. Investors are more likely to invest in companies with higher return on assets because they can get higher pay back on such investment than the same amount of capital invested in a company with relatively lower return on asset. A company with better profitability definitely should be overestimated. Thus, I assume that return on asset is positively related to firm value.
3.6 Methodology and regression models
There are two main regression models of my paper which are connected to my hypothesis. First, it is the model to test the association of the firm value and cash flow volatility. To verify how an investor views the cash flow volatility, the first model is quite simple. The first regression model includes all three control variables that are the characteristic features of the sample companies.
Regression model 1 is:
Tobin’s Q ratio = a1 * STDEV + e
STDEV = standard deviation of cash flow per share Regression model 2 is:
Tobin’s Q ratio = b1 * STDEV + b2 * LEV + b3 * ROA + b4 * SIZE + e
STDEV = standard deviation of cash flow per share LEV = leverage ratio of the company
ROA = return on assets SIZE = company total assets
In the second regression model, I drill down the association of firm value and cash flow volatility to discuss the effect of cash flow volatility on firm value.
The regression model 3 is:
Tobin’s Q ratio = c1 * NDA + c2 * LEV + c3 * ROA + b4 * SIZE + e
LEV = leverage ratio of the company ROA = return on assets
SIZE = company total assets
The third regression model aims at showing the relationship between non-discretionary accruals and Tobin’s Q ratio, so I can do a further test to verify how earnings management will affect the association of firm value and cash flow volatility.
The regression model 4 is:
Tobin’s Q ratio = d1 * STDEV + d2 * NDA + d3 * LEV + d4 * ROA + d5 * SIZE + e
STDEV = standard deviation of cash flow per share NDA = non-discretionary accruals
LEV = leverage ratio of the company ROA = return on assets
SIZE = company total assets
In order to find out how earnings management will affect the association of firm value and cash flow volatility, I use the forth model to do the regression test. Tobin’s Q ratio and STDEV presents firm value and cash flow volatility. I use non-discretionary accruals (NDA) to present earnings management (Wu, Lin and Fang. (2012)).
After the above two model test, I will further classify my sample data by their total asset and classify them into 5 groups of different sizes. This will more precisely show the relationship of cash flow volatility, earnings management and firm value according to the methodology taken by most scholars (Jayaraman. (2008), Lang and Stulz (1994), and Servaes (1996)).
At last, I will classify my data into different groups by the Standard Industrial Classification code. Established in the United States in 1937, Standard Industrial Classification code is used by government agencies to classify industry areas. The SIC system is also used by agencies in other countries, e.g., by the United Kingdom's Companies House. I use this code to classify my sample companies to have a further and more detailed analysis results of my hypothesis test.
3 Tests results
3.5 Descriptive statistics of variables
Table 1 - Descriptive statistics
Variable Name Obs Mean SD Min Median Max 25% 75%
Firm value (Tobin’s Q ratio) 8288 3.482 27.357 0.223 1.344 713.895 0.954 2.209
Cash flow volatility (standard
deviation of cash flow) 1184 1.357 2.233 0 0.738 27.421 0.31 1.572
Earnings management
(non-discretionary accruals) 1184 -0.1 1.47 -35.448 -0.073 29.55 -0.28 0.076
Leverage ratio (debt / asset) 8288 0.281 1.927 0 0.155 62.274 0.002 0.313
Return on assets (net income /
total asset) 8288 -0.689 18.42 -631.773 0.031 1.075 -0.038 0.067
Company size (total asset) 8288 6748.105 22704.20 0.013 947.132 331052 171.881 4266.022
Table 1 is the summary of statistics of my data sample. It presents the characteristics of my dependent variable, independent variables and control variables. The above table includes average, minimum, maximum, 25% quantile, 50% quantile and 75% quantile. For these mentioned variables, it is not possible to draw a conclusion just through the number of average and quantile, but I can have a rough knowledge of all variables in the following test.
I use market fair value plus book value of total debt to book value of asset as an approximation of Tobin’s Q ratio, proxying for the firm value of my sample companies. My sample companies have an average Tobin’s Q ratio of 3.482 and a median Tobin’s Q ratio of 1.344. However, the maximum number is 713.895. Thus, there could be several companies that is in the starting phases of their life-cycle like information technology company. The average number of standard deviation of cash flow is 1.357 and the median number of standard deviation of cash flow is 0.738.
According to Michelson et al. (1995), the non-discretionary accruals is calculated by using STATA to regress the modified version of the Jones Model. The average number of non-discretionary accruals in my data sample is -0.1 and the median of non-non-discretionary accruals non-discretionary accruals is -0.073. This means that in general nearly half of the companies in my data sample are trying to reduce their reported revenue by managing their earnings. Reducing reported revenue can decreasing tax payment and it can be seen as an increase of asset and a decrease of cash outflow.
The average company size of my sample companies is 6748.105 million dollars. The median number of company size is 947.132. This means that there exists a large difference in the control variable of company size.
3.6 The correlation coefficients among variables
In order to verify the correlation of Tobin’s Q ratio (dependent variable), standard deviation of cash flow (independent variable), non-discretionary accruals (independent variable) and other 3 control variables, I use STATA to do a correlation test to all the variables included in the regression model.
Table 2 - Correlation coefficient
Variable name Firm value (ln (Tobin’s Q ratio)) Cash flow volatility (ln (standard deviation of cash flow)) Earnings management (non-discretionary accruals) Return on assets Company size (ln (total asset)) Leverage ratio (debt / asset)
Firm value (ln (Tobin’s Q
ratio)) 1 -0.108*** 0.124*** -0.094*** 0.194*** -0.178***
Cash flow volatility (ln (standard deviation of cash flow))
-0.224*** 1 0.035 0.127*** 0.258*** 0.483***
Earnings management
(non-discretionary accruals) -0.012 0.110*** 1 -0.048* 0.104*** 0.014
Return on assets (net income /
total asset) 0.175*** -0.073** 0.206*** 1 -0.060** 0.447***
Company size (ln (total asset)) -0.269** 0.201*** 0.670*** -0.012 1 0.370***
Leverage ratio (debt / asset) -0.315*** 0.517*** 0.038 -0.019 0.148*** 1
Notes: Lower-triangular cells report Pearson's correlation coefficients, upper-triangular cells are Spearman’s rank correlation and *, **, *** denotes a statistical coefficient at the 1%, 5% and 10% alpha level, respectively.
Table 2 preliminarily presents the correlation of the various coefficients. From the above table, I can see two of the dependent variables, non-discretionary accruals and ln (standard deviation of cash flow per share), are verified to be significantly related to ln (Tobin’s Q ratio). Besides, three control variables including company size, return on assets and leverage ratio show a
significant correlation with firm value. Only the return on assets is positively related to frim value and the other two control variables are negatively related to firm value. Although it is very difficult to draw a conclusion from table 2, I find several interesting points.
First, ln (Tobin’s Q ratio) is significantly correlated with the standard deviation of operating cash flow as known as the cash flow volatility at 1% level. The correlation coefficient of standard deviation of operating cash flow for ln (Tobin’s Q ratio) at lowertriangular cells is -0.224. This coefficient means that companies with higher cash flow volatility have higher firm value. Thus, it is consistent with my first hypothesis about firm value and cash flow volatility. So, I can do further regression test about cash flow volatility and firm value. however, earnings management is not proved to be significantly related to firm value and they are negatively related. This is not consistent with empirical study theory (Wu Shih-Wei, Lin Fengyi and Fang Wenchang (2012)). The reason why earnings management is not consistent with the firm value could result from the fact that most investors are not able to detect the earnings management in the highly complicated financial report due to lack of essential knowledge and skills. Since the earnings management is insignificantly correlated with firm value, I should do a further regression test to get a detailed conclusion taking control variables into consideration.
Secondly, control variables including company size, return on assets and leverage ratio are all significantly correlated with firm value. These results are consistent with my assumption based on prior literatures (Rajan Zingales (1995) and Froot (1993)). The reason why coefficient of company size is only significant at 5% level could be caused by some abnormal data with very large scale of total assets. However, the coefficient of company size is -0.269, which shows that company size is negatively connected with firm value. Meanwhile, the coefficient of leverage ratio is -0.315. This coefficient means that leverage ratio is negatively connected with firm value and this is against my prediction. This can be caused by recently America has quite low interest rate and investors do not pay much attention to leverage ratio resulting in the insignificant correlation. What’s more I can see that return on asset is significantly and positively related to ln (Tobin’s Q ratio).
3.7 Multiple regression analysis of firm value and cash flow volatility
Table 3 - full sample multiple regression results
Variable name
(1) (2) (3) (4)
Ln (Tobin’s Q ratio) Ln (Tobin’s Q ratio) Ln (Tobin’s Q ratio) Ln (Tobin’s Q ratio)
Cash flow volatility (ln (standard deviation of cash flow per share))
-0.125*** -0.017** / 0.021*** (-7.89) (-0.99) (-1.20) Earnings management (non-discretionary accruals) / / 0.120*** 0.121*** (-6.31) (-6.35)
Leverage ratio (debt /
asset) /
0.146*** 0.104*** 0.102***
(-6.22) (-4.33) (-4.22)
Return on assets (net
income / total assets) /
-0.009** -0.016*** -0.016***
(-8.23) (-10.58) (-10.44)
Company size (ln (total
asset)) / -0.085*** -0.086*** -0.080*** (-8.53) (-10.07) (-8.09) _cons 0.380*** 0.950*** 0.980*** 0.932*** (-16.76) (-12.88) (-16.18) (-12.84) N 1184 1184 1184 1184 R-Square 0.05 0.423 0.205 0.206 Adj.R-Square 0.05 0.42 0.2 0.2
Notes: *, **, *** denotes a statistical coefficient at the 1%, 5% and 10% alpha level, respectively and the number in the brackets are p-values.
The above table shows the result of multiple OLS regression of my dependent variable (Tobin’s Q ratio), two independent variables (standard deviation of cash flow per share and non-discretionary accruals) and three other control variables.
In table 3 model 1, I use Tobin’s Q ratio as a dependent variable and cash flow volatility as dependent variable. This is a test without control variables. The results show that cash flow volatility is negatively and significantly related to firm value at 1% level. The coefficient of
the ln (standard deviation of cash flow per share) for Tobin’s Q ratio is -0.125. This is consistent with my hypothesis 1. In the hypothesis 1, I assume that a company with a volatile cash flow is less valuable than a company with stable and smooth cash flow. Prior literatures (Jayaraman (2008) and Rountree, Weston and Allayannis (2008)) shows that high risk usually must come together with high return for investors. For listed company, it is very critical to have a good cash flow. Once cash flow has a big shortfall and companies fail to finance enough cash for that shortfall, bankruptcy will come after that. So, investors are very emphasized on the cash flow volatility. As long as a company has a high cash flow volatility, investors pay attention to the company’s investment project and require higher return for increased risk. What’s more, investors will make a relatively lower estimation for firm value.
In regression model 2, I introduce leverage ratio, return on assets and company size as control variables. From the results of table 3, I can conclude that company size which is presented by ln (total asset) is significantly and negatively related to Tobin’s Q ratio at 1% level. This negative relationship means company with high level of company size could have a relatively lower firm value evaluated by investors and analysts. One possible reason for this result is when a company grows, its company structure becomes complicated and so does its financial report. In that, it is harder for investors to get precise and clear information to correctly estimate the firm value. Another reason is that a big mature company is usually growing much more slowly than a small developing company. Thus, investors can have less investment pay back if they invest in a big mature company than the investment pay back if they invest same amount in a small developing company. Due to the above reasons, company size is negatively related to firm value. Return on assets is negatively and significantly associated with firm value at 1% level. The coefficient of return on assets is -0.009. This is inconsistent with my expectation that higher return on assets leads to a higher estimation of firm value. A good explanation for negative relationship between return on assets and firm value lies in the low leverage ratio implying that companies fail to fully exploit its asset. Investors are expecting higher return on asset and find that the companies’ return on asset is lower than expectation or even lower than the risk-free rate like bank interest rate. Of course, investors are underestimates firm value for the low return on assets. The leverage ratio and firm value are positively and significantly associated at 1% level and this is inconsistent with my expectation before. A reasonable explanation is a high leverage ratio shows that a company has perfectly utilized its capital. Usually companies with high leverage has high return for debt holders, which is very attractive for investors.
In regression model 3, I introduce a new dependent variable, earnings management. Regression result shows that earnings management is significantly and positively related to firm value at 1% level. This regression result of model 3 is inconsistent with the conclusion of prior literatures (Wu Shih-Wei, Lin Fengyi and Fang Wenchang (2012)). As shown in the prior literatures, earnings management is a negative signal for firm value because it implies that the management is trying to conceal bad operating failures or losses. A reasonable explanation for earnings management to have an incremental effect on firm value is most of my sample company are still in the developing stage. Since the average Tobin’s Q ratio and median number of Tobin’s Q ratio in table 1 are above 1, it indicates that most companies in my data sample are developing very fast and have a very bright future. Thus, the aim of earnings management conducted by the management is to reduce net income to save tax. Tax-saving is another kind of asset increasing. So, investors make a higher estimation of firm value due to earnings management. The rest three control variables are almost the same as those in the model 1. However, the introduction of cash flow volatility increases the adjusted R-Square from 0.18 to 0.42 which make it more reliable than before.
In regression model 4, I introduce earnings management and cash flow volatility at the same time. Results in table 3 show almost the same significant relationship as the former models. The coefficient of cash flow volatility is 0.021. Cash flow volatility is significantly and positively related to firm value at 1% level. This coefficient means that increase of cash flow volatility will result in the increase of firm value evaluated by investors. This result is consistent with my hypothesis 2. When detecting earnings management, investors make higher firm value estimation for companies with high cash flow volatility than firm value estimation for companies with stable cash flow. The coefficient of earnings management is 0.121. Earnings management is positively and significantly related to firm value at 1% level. Considering the positive and significant correlation of cash flow volatility and earnings management in table 2, I can conclude that earnings management has incremental effect on firm value and cash flow volatility.
3.8 Robustness test
The main method for robustness test is alternative specifications and estimation techniques. I will make following alternatives to the original measures:
2. I will use variance of operating cash flow per share instead of standard deviation of operating cashflow per share as the cash flow volatility.
3. I will use debt to equity ratio instead of debt to asset ratio as the leverage ratio. The following table shows the results of robustness test:
Table 4 robustness test
Variable name (1) (2) (3) (4) Ln (price / book value) Ln (price / book value) Ln (price / book value) Ln (price / book value) Cash flow volatility (ln
(variation of cash flow per share)) -0.005** -0.009** / 0.013** (-0.52) (-0.76) (-0.78) Earnings management (non-discretionary accruals) / / 0.04*** 0.04*** (-1.61) (-1.61) Leverage ratio (debt /
equity) /
0.002*** 0.002*** 0.002*** (-4.53) (-4.55) (-4.52)
Return on assets (net
income / total assets) /
0.003** 0.001 0.001
(-1.97) (-0.31) (-0.39) Company size (ln (total
asset)) / 0 -0.004 0.002 (-0.00) (-0.31) (-0.12) _cons 1.022*** 1.018*** 1.052*** 1.009*** (-35.46) (-10.2) (-12.71) (-10.11) N 1184 1184 1184 1184 R-Square 0.302 0.305 0.202 0.203 Adj.R-Square 0.3 0.31 0.2 0.2
Notes: *, **, *** denotes a statistical coefficient at the 1%, 5% and 10% alpha level, respectively and the number in the brackets are p-values.
According to the results of above robustness test, we can see that the dependent variable, firm value, and two main independent variables (cash flow volatility and earnings management) are in the same relationship as before alternative of variable measures. Cash flow volatility is significantly and negatively related to firm value at 5% level, which is consistent with hypothesis 1. When taking earnings management into consideration, cash flow volatility is positively and significantly related to firm value at 1% level. And this result supports my hypothesis 2. When detecting earnings management, investors make higher firm value estimation for companies with high cash flow volatility than firm value estimation for companies with stable cash flow. Given the strength of my results, I find support in the robustness test for my conclusions presented in 4.3.
4 Conclusions
4.5 Cash flow volatility has negative effect on firm value
This paper tests the hypothesis that cash flow volatility has negative effect on firm value. After using leverage ratio, company size and return on assets as control variables, I verify the negative relationship of cash flow volatility and firm vale. In other words, the increase of ash flow volatility causes investors to decrease their value estimation of a firm. When cash flow volatility become higher, company needs more cash and cash equivalent for operating activities. High cash flow volatility will decrease the capital utilization and will result in a worse performance than smooth cash flow volatility does. On the other hand, cash flow volatility can also reflect corporate financial problems. Usually a cash flow volatility is associated with cash flow shortfall. These are risks for investors. As a result, investors lower their estimation of a firm’s value and require higher return for their investment. Vise versa, a low cash flow volatility can reduce the need and cost of external capital and avoid external administration and constraint on investment decision of a company. This is helpful to increase firm value and effective decision making.
4.6 Earnings management changes the effect of cash flow volatility on firm value
This paper tests the hypothesis that when detecting earnings management, investors make higher firm value estimation for companies with high cash flow volatility than firm value estimation for companies with stable cash flow. According to regression test, I get a conclusion different from empirical studies. At the existence of earnings management, cash flow volatility has a positive effect on firm value and earnings management also has a positive effect on firm value. I think one reason is resulted from a positive intention of public enthusiasm for investment. Cash flow volatility can bring opportunities for high return. And people are usually drawn to such dangerous investing opportunities. Another explanation is since the technology is developing very fast, there are more and more new developing companies emerging in recent years. These developing technology companies have very good growth prospects and investors do not hesitate to invest in such companies for high return. Holding such thoughts in mind, investors have an open risk appetite.
