Stock performance and the mispricing of accruals

The International Journal of Accounting 42 (2007) 153 – 170

Stock performance and the mispricing of accruals ☆ Guohua Jiang Guanghua School of Management, Peking University, Beijing, 100871, PR China

Abstract I investigate the relationship between contemporaneous stock-price performance and the persistence of accrued earnings, and its impact on the accrual anomaly. I find that, in a fiscal year, accrued earnings for stocks that have performed poorly are less persistent in predicting future earnings than accrued earnings for stocks that have performed moderately. I further find that a hedge-strategy based on accruals earns greater abnormal returns following bad-news years. The results are consistent with conservative accounting causing accrued earnings to be even less persistent in bad-news years and investors failing to efficiently price this differential in persistence. © 2007 University of Illinois. All rights reserved. JEL classification: M41; G12; G14 Keywords: Conservative accounting; Accrual anomaly; Efficient market

1. Introduction This study attempts to further our understanding of the “accrual anomaly.” Sloan (1996) separates corporate earnings into two components: accrued earnings and cash earnings, and shows that accrued earnings are less persistent than cash earnings in predicting one-year-

☆ This paper is based on a chapter of my Ph.D. dissertation finished at the Haas School of Business of the University of California, Berkeley. I am grateful to my dissertation committee members Brett Trueman (chair), James Powell and Xiao-Jun Zhang for valuable guidance. Comments and suggestions from Bokhyeon Baik, John Briginshaw, Kevin Chen (the editor), David Tien, two anonymous referees, and seminar participants at Berkeley, Peking University, and the University of Hong Kong were very helpful. I also thank the National Natural Science Foundation of China for financial support in the revision stage of this paper (approval number 70532002). E-mail address: [email protected].

0020-7063/$30.00 © 2007 University of Illinois. All rights reserved. doi:10.1016/j.intacc.2007.04.004

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ahead earnings.1 Furthermore, Sloan (1996) demonstrates that the market appears to overestimate the persistence of accrued earnings, and hence over-/under-prices stocks with large amounts of income-increasing/decreasing accruals. A hedge strategy that takes advantage of the mispricing nets almost a 10% size-adjusted return in the one-year-ahead period. This study focuses on two questions. First, under what circumstances do accrued earnings have lower persistence in predicting future earnings? Second, do different levels of mispricing of accrued earnings occur hand in hand with different levels of persistence of accrued earnings? Invoking accounting conservatism and its impact on (accrued) earnings, I argue that accrued earnings are less persistent when stocks perform poorly in a fiscal year, prompting firms to record accruals following conservative accounting principles. As a result, investors, failing to fully adjust to the differential persistence of accruals under these circumstances, misprice accrued earnings to a greater extent in years with bad stock price performances than in years when stock performance is moderate. Empirical results largely support my predictions. I separate my sample firm-years into three news groups, based on stock performance of the sample firms in each fiscal year: a good-news group when stocks have performed well in a fiscal year; a bad-news group when stocks have performed poorly; and a neutral-news group when stock prices have not moved much. I show that (a) the persistence factor of accrued earnings (the coefficient on accruals in a regression of future earnings on current earnings components) for the bad-news group is 16% lower than that for the neutral-news group; and (b) the persistence factor of accrued earnings for the goodnews group is only 5.3% lower than that for the neutral-news group. Furthermore, the differential persistence leads to a different level of mispricing. In the framework of the Mishkin test, investors overestimate the persistence of accrued earnings by 50.8% for the bad-news group, by 22.5% for the good-news group, and by 18.7% for the neutral-news group. A hedge-portfolio strategy reveals that the mispricing is economically significant. In the Fama-French three-factor model regression, the one-year-ahead abnormal return to an accrual-based hedge strategy is 8.8% for the bad-news group, which is significantly higher than the 4.2% abnormal return for the neutral-news group. The one-year-ahead abnormal return to the good-news group, 5.8%, however, is not significantly higher than that of the neutral-news group. The results in this study are consistent with the notion that persistence is an important aspect of the quality of accounting earnings (Richardson et al., 2005). In particular, when accrued earnings are preceded by abnormally poor stock performance, the persistence of accrued earnings is lower than that of other firms, and consequently, the mispricing of earnings is greater. The results in this study draw our attention, when we analyze financial statements, to the economic events that drive stock-price movement. Accounting numbers (e.g., earnings) are driven by economic events that drive stock prices at the same time. Thus, we should analyze accounting numbers in the same environment that produces them. In this regard, we contribute to the current literature on “accrual anomaly” by pinpointing situations where “accrual anomaly” tends to be more severe and we hope that further research will unravel the perplexing question of why “accrual anomaly” arises and persists. 1 Throughout this paper, I define earnings persistence as the ability of current earnings, or components of current earnings, to predict one-year-ahead earnings. Sloan (1996), and later Richardson, Sloan, Soliman, and Tuna (2005) used this definition. Penman and Zhang (2002) used this concept in a similar fashion.

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This paper is organized as follows. Section 2 reviews the “accrual anomaly” literature and motivates my study. Section 3 presents an empirical analysis of accrued earnings across the three news groups. Section 4 concludes. 2. Motivation In the research on financial-statement analysis, researchers are very interested in how current (or past) earnings (or earnings components) aid in forecasting future earnings or cash flows, both of which are central inputs in accounting-valuation models. Among others, Sloan (1996) shows that accrued earnings are less persistent than cash earnings in predicting future earnings, and presents evidence that investors seem to overestimate the persistence of accrued earnings and subsequently misprice stocks with large amounts of accrued earnings. The Sloan (1996) results seem to have endured over time and been confirmed by others. In follow-up papers, researchers have been able to replicate Sloan's results for different time periods and different definitions of accruals. In addition, these papers have identified some driving components of Sloan's (1996) results and attempted to explain why accrual anomaly arises (Chan, Chan, Jegadeesh, & Lakonishok, 2006; Hribar, 2000; Thomas & Zhang, 2002; Xie, 2001). However, the questions surrounding earnings accruals are still very perplexing. Further research is still warranted into the causes of the differential persistence of cash earnings versus accrued earnings and the reasons for the market's failure to price accrued earnings correctly. The present study tries to add to the existing literature by examining accruals in the context of contemporaneous stock performance and accounting conservatism, and their impact on the generation of accruals. How much contemporaneous return2 news is incorporated in earnings is one factor in determining the persistence of accruals and subsequent mispricing of accruals. As is widely known, stock returns lead accounting earnings (e.g., Beaver, Lambert, & Morse, 1980). Valuerelevant events drive stock-price movement faster than their economic impact flows through the financial-reporting system. Therefore, the extent to which current earnings incorporate the economic impact of these events (hereinafter referred to as return news) has implications for the persistence of current earnings and for the market's forecast of future earnings. At least two (mutually nonexclusive) reasons can affect how much contemporaneous return news current earnings incorporate. First, current GAAP accounting rules are inherently conservative. Accounting conservatism requires bad news to be recognized in current earnings faster and more completely than good news. That is, in the event of bad news, GAAP requires current accounting earnings to fully account for the implications of the event, not only for current cash flow, but also for future cash flows. In effect, this act brings future consequences to the present. However, such a conservative tilt in recognition does not apply for good news. That is, current earnings do not recognize the implications for future cash flows of good news. The impact of good news only flows through earnings as it materializes in operation. By “contemporaneous” I mean that stock returns are measured during the 12 months of the same fiscal year for which accruals are measured. 2

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Because the cash component of current earnings cannot be changed, management needs to use accruals to account for the early recognition of future cash-flow implications of badnews events. This approach thus generates an additional amount of accrued-earnings information in a bad-news year. Second, as Abarbanell and Lehavy (2003) argue, stock-price performance provides management with a strong incentive to manage earnings. These researchers argue that in a bad-news year, it is likely that the traditional earnings targets, such as outstanding analysts' consensus-earnings forecasts, zero profit, or earnings of the last period, will not be met. In this event, some managers tend to take a “big bath” to “clear the deck” for future years. The “big bath” is reflected in current earnings by large amounts of income-decreasing accruals. Thus, taking a “big bath” is consistent with accounting conservatism in the sense that they both incorporate bad news in current earnings faster and more completely than otherwise. Once again, because managerial discretion over cash flow is very limited, to achieve the earnings-management objective, management has to act on accrued earnings. In summary, both accounting conservatism and earnings management in response to stock performance cause additional amounts of accruals to be included in current earnings. The focus of this study is thus on the persistence of accrued earnings when stock performance is bad.3 Furthermore, I examine whether the accrual anomaly is stronger in badnews years. That is, whether an accrual-based hedge strategy generates larger amounts of abnormal returns in bad-news years than otherwise. I separate sample firm-years into three groups: a bad-news group (those firm-years in which stocks have performed poorly); a neutral-news group (those firm-years in which stock prices did not change much); and a good-news group (those firm-years in which stocks have performed well). I then use the neutral-news group as my benchmark to test whether accrued earnings in the bad-news group are less persistent than accrued earnings in the neutral-news group, and whether such differences in persistence lead to different levels of mispricing. Similarly, I also test the differences between the good-news group and the neutral-news group. However, I expect the difference to be small and less economically significant. Following Sloan (1996), I conduct two analyses. The first is a Mishkin test that compares the actual persistence of earnings components with the market-perceived persistence. A significant difference would suggest market mispricing of those earnings components. More relevant to this study, I test whether there is a differential in the persistence of accrued earnings between the bad-news and the neutral-news group-that is, whether the persistence of accrued earnings in one group is larger or smaller than in the other group, and whether the market misprices this differential in persistence. The second test is a hedge-portfolio test that is complementary to the Mishkin test. It determines whether mispricing is economically significant. In a study similar in spirit to my paper, Dopuch, Seethamraju, and Xu (2005) investigate the differential persistence of accruals between profit firms and loss firms. They find that 3 There is potentially another reason to explain the lower persistence of accrued earnings in the bad-news years and in the good-news years. Normally, very bad news or very good news does not recur often and so lacks persistence. As a result, accrued earnings in these years may also lack persistence, aside from what can be explained by accounting conservatism and earnings management. Accrued earnings in good-news years are less persistent than in neutral-news years. However, the magnitude of persistence differential is much smaller for the good-news/neutral-news comparison than for the bad-news/neutral-news comparison. In addition, the differential of persistence was not mispriced by investors.

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accrued earnings are more persistent for profit firms than for loss firms and that only in profit firms accrued earnings are overpriced, while in loss firms accrued earnings are underpriced, albeit insignificantly. Taken together, Dopuch et al. (2005) and this paper emphasize the importance of understanding the environments in which accruals are generated and how investors price accruals differently under different situations. These analyses lead to a sharp improvement in the detection of the mispricing of accruals.4 3. Data analysis 3.1. Variable measurement I begin by defining the variables used in this study. Following Sloan (1996), accruals are derived from successive balance sheets and income statements: ACCRt ¼ ðDCAt  DCASHt Þ  ðDCLt  DSTDt  DTPt Þ  DEPt : CA CASH CL STD TP DEP Δ

ð1Þ

Current assets Cash or cash equivalents Current liability Debt included in current liabilities Income tax payable Depreciation and amortization expenses Indicates change of a variable from year t − 1 to year t.

Total earnings (EARNt) are defined as operating income after depreciation, and, therefore, the cash flow component of earnings (CASHt) is defined as the difference between total earnings and accruals: CASHt ¼ EARNt  ACCRt :

ð2Þ

EARN, CASH, and ACCR are all deflated by average total assets. To test market efficiency with regard to earnings, I compute one-year-ahead twelve-month buy-and-hold size-adjusted returns starting with the fifth month after fiscal-year-end t. The four-month lag is to make sure that the market has already learned the earnings information contained in the firms' annual financial reports. 12

12

i¼1

i¼1

ABRETtþ1 ¼ j ð1 þ RETðiÞÞ  j ð1 þ SIZRETðiÞÞ:

ð3Þ

ABRETt+1 12-month compounded size-adjusted returns in year t + 1, starting from the fifth month after fiscal year end t. RET(i) Firm raw return in month i. Here the first month of the return accumulation period is the fifth month after fiscal year end t. 4

Thanks to the referee's comments, I realize it would be interesting to investigate the impact on accrual anomaly of the interaction between stock performance and earnings performance. I leave this to a later research project.

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SIZRET(i) Return in month i on the size portfolio that the firm belongs to in year t + 1, the size portfolio is supplied by CRSP. Following previous studies (e.g., Basu, 1997; Pope & Walker, 1999), I use a stock's raw annual return during fiscal-year t to measure the return news during the fiscal year: 12

FRETt ¼ j ð1 þ RETðiÞÞ  1: i¼1

ð4Þ

RET(i): firm raw return in month i. Here the first month of the return-accumulation period is the first month of fiscal-year t. The reason that I use raw return as a measure of news, instead of other metrics such as changes in analysts' consensus-earnings forecasts, is as follows. Raw return in a fiscal year is a measure of economic impact on a firm from value-relevant events having occurred to the firm or to the market as a whole during this period. News that are impounded in returns will factor into corporate earnings as the economic impacts materialize in the firm's operations. That is, return leads earnings. In Pope and Walker's (1999) model, accounting conservatism garbles the price-leading-earnings process by requiring fast recognition of bad-return news. Therefore, the property of the time-series of earnings is affected by how return news is incorporated in earnings in different situations. While all the above-cited studies focus on the implications of return news for total earnings, it is logical to believe that the implications have more to do with accrued earnings than with cash earnings because the latter cannot be as easily garbled in response to economic events and accounting rules. Therefore, I choose to use raw return as my measure of news. 3.2. Research design Sloan (1996) developed two complementary tests to examine the persistence of earnings components and market mispricing. The present study utilizes these two tests with some modifications. The first test employs the Mishkin test.5 Mishkin (1983) developed a framework to test the rational-expectation hypotheses in macroeconomics. Sloan (1996) introduced this test into accounting research to test whether the market efficiently prices accrued earnings and cash earnings. The Mishkin test in this study is in the following form:

5

EARNtþ1 ¼ a0 þ a1 IDt þ b0 CASHt þ b1 CASHt ⁎IDt þ c0 ACCRt þ c1 ACCRt ⁎IDt þ e

ð5Þ

ABRETtþ1 ¼ a þ b⁎ðEARNtþ1  a0  a1 IDt  be0 CASHt  be1 CASHt ⁎IDt  ce0 ACCRt  ce1 ACCRt ⁎IDt Þ:

ð6Þ

I thank Scott Richardson, Richard Sloan, and Hong Xie for their assistance in programming the Mishkin test.

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EARNt+1 is operating earnings in year t + 1, ACCRt is total accruals in year t, CASHt is total cash earnings in year t, ABRETt+1 is size-adjusted buy-and-hold returns in the twelve months starting from the fifth month after fiscal-year-end t, IDt is a dummy variable that takes value “one” for bad-news/good-news firms and “zero” for neutral-news firms. A superscript e indicates market expectation. The dummy variable, IDt, indicates which news group a firm belongs to. Each year, I partition firms into three news groups. Firms whose FRETt is in the highest quintile in the annual cross-section are grouped into the good-news group, whereas those in the lowest quintile are grouped into the bad-news group. I classify firms in the three middle quintiles into one group, the neutral-news group. With this partitioning scheme, this study contrasts accrued earnings in the relatively extreme ends of the return-news spectrum with those in the middle. In the analysis below, I discuss the Mishkin test using bad-news/neutral-news groups. However, the same analysis applies to the comparison of good-news/neutral-news groups. Eq. (5) is the forecasting equation that determines the weights (hereafter referred to as the persistence factor) that should be assigned to earnings components in forecasting future earnings. b0 and c0 are the persistence factors for cash earnings and accrued earnings in the benchmark case, the neutral-news group; and (b0 + b1) and (c0 + c1) are the persistence factors for cash earnings and accrued earnings for the bad-news group. Our focus is on c1, which is the differential persistence factor (negative sign expected) for accruals in the bad-news group relative to the neutral-news group. If c1 is significant, it tells us that there is a difference in the persistence of accrued earnings in the bad-news group versus the neutral-news group. Eq. (6) is the pricing equation that estimates the weights that the market assigns to earnings components in forecasting future earnings and uses in valuation. Comparing c0 and (c0 + c1) in Eq. (5) with c0e and (c0e + c1e) in Eq. (6) will tell us whether the market prices accrued earnings efficiently in both the neutral-news group and the bad-news group. In particular, comparing c1 with c1e will tell us whether the market recognizes the differential in the persistence of accruals between the bad-news group and the neutral-news group and prices them efficiently. Eqs. (5) and (6) are estimated jointly, using an iterative generalized non-linear least squared estimation procedure. To test whether the weight on an earnings component is the same between the forecasting equation and the pricing equation-that is, whether the market prices the earnings component efficiently — I calculated the following likelihood-ratio statistic: 2N LnðSSRc =SSRu Þ; where: Ln SSRc SSRu

N is the number of observations in the sample; is natural logarithm operation; is the sum of squared residuals from the constrained regressions of the system; is the sum of squared residuals from the unconstrained regressions of the system.

This likelihood-ratio statistic is asymptotically χ2(q) distributed under the null hypothesis that the market efficiently prices the earnings component with respect to its implications for future earnings, where q is the number of constraints imposed on estimating the system. I

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reject efficient pricing of an earnings component if the likelihood-ratio statistic for it is sufficiently large. The second test in this study is a hedge-portfolio analysis. An accrual-based hedge strategy takes advantage of the mispricing of accruals. It longs undervalued stocks (as predicted by the Mishkin test) and shorts overvalued stocks (as predicted by the Mishkin test) to earn abnormal trading profits when stock prices move back to intrinsic values. If the abnormal trading profits prove to be significant, the hedge-portfolio test supports the Mishkin test's conclusion on the market mispricing of the earnings component of interest. Sloan (1996) conducts the hedge-portfolio analysis by forming portfolios on one variable, accrued earnings. In this study, I first partition sample firms annually into three groups: good news, no news and bad news, based on the return news, FRETt. Then, independently, I partition the whole annual sample again into five portfolios, based on the amount of accrued earnings, ACCRt. Then I track one-year-ahead abnormal returns to the return news-accruals portfolios. That is, I implement the accrual-based hedge strategy within each return-news group. If the persistence of accruals is different across news groups, and if the market fails to fully adjust to this, I expect an accrual-based hedge strategy to earn higher abnormal returns for the news group in which the persistence of accruals is lower, relative to accruals in other news groups. The measure of abnormal returns is the intercept term in a regression based on the Fama-French three-factor model. 6 Fama and French (1993) argued that this model accounts for the majority of the cross-sectional variation in portfolio returns over time. When I use this measure of abnormal returns, I only use firm-years with a December fiscal-year-end. Each year, firms are assigned to one of 15 return news-accrual portfolios. Then I compute the monthly equal-weighted returns for the highest-accrual portfolio, lowest-accrual portfolio, and hedge portfolio for the twelve months in the oneyear-ahead period, starting with the fifth month after fiscal-year-end t. As a result, we have a time-series of monthly portfolio returns and three factors. Then I run the threefactor model, and the intercept term is the monthly abnormal return to the portfolio. Multiplying this by 12, I get an annual portfolio abnormal return (Hribar, 2000; Xie, 2001): Rp;t  Rf ;t ¼ ap þ bp ðRm;t  Rf ;t Þ þ sp SMBt þ hp HMLt þ ep;t : Rf,t Rm,t SMBt HMLt

6

ð7Þ

the one-month Treasury bill rate (from Ibbotson Associates) the value-weighted return on all NYSE, AMEX, and NASDAQ stocks the difference between the month t returns of a value-weighted portfolio of small stocks and one of large stocks the difference between the month t returns of a value-weighted portfolio of high book-to-market stock and one of low book-to-market stocks

Using the Fama-French factors plus a momentum factor produces similar results.

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3.3. Sample selection and descriptive statistics I draw my sample firms from COMPUSTAT industrial, full-coverage and research files, and stock returns and size-portfolio returns from CRSP. Only firms that are traded on the New York Stock Exchange, the American Stock Exchange, and the NASDAQ are included. My sample starts in 1964 and ends in 1997. My final sample with necessary data consists of 56,940 firmyears for 5617 firms. Among these, 11,377 firm-years are classified into the good-news group, 34,188 firm-years into the neutral-news group, and 11,375 firm-years into the bad-news group. Table 1 provides sample statistics of and correlation coefficients among some variables. The results in Table 1 are very consistent with those in prior studies. For example, Panel A Table 1 Descriptive statistics and correlations of selected variables Panel A: Descriptive statistics of selected variables Variables

Mean

STD

5%

10%

25%

Med.

75%

90%

95%

EARN CASH ACCR FRET ABRET

0.110 0.126 − 0.015 0.175 0.028

0.097 0.109 0.080 0.443 0.492

− 0.053 − 0.065 − 0.138 − 0.401 − 0.556

0.002 − 0.005 − 0.105 − 0.302 − 0.444

0.061 0.067 − 0.063 − 0.120 − 0.257

0.111 0.131 − 0.022 0.104 − 0.045

0.165 0.192 0.026 0.376 0.026

0.225 0.255 0.085 0.729 0.054

0.267 0.298 0.129 1.028 0.083

Panel B: Pearson (above diagonal) and Spearman (below diagonal) correlations among selected variables LDEAN LDEARN CASH ACCR FRET ABRET

0.56 0.14 0.29 0.27

CASH

ACCR

FRET

ABRET

0.58

0.13 − 0.52

0.24 0.16 0.09

0.21 0.04 − 0.07 − 0.01

− 0.50 0.19 0.09

0.08 − 0.08

0.01

Notes: variable definition. ACCRt ¼ ðDCAt  DCASHt Þ  ðDCLt  DSTDt  DTPt Þ  DEPt CA = current assets (COMPUSTAT data item 4). CASH = cash (COMPUSTAT data item 1). CL = current liability (COMPUSTAT data item 5). STD = debt included in current liabilities (COMPUSTAT data item 34). TP = income tax payable (COMPUSTAT data item 71). DEP = depreciation and amortization expenses (COMPUSTAT data item 14). CASHt ¼ EARNt  ACCRt EARN = COMPUSTAT data item 178. LDEAR is one-year-ahead earnings. 12

12

i¼1

i¼1

ABRETtþ1 ¼ j ð1 þ RETðiÞÞ  j ð1 þ SIZRETðiÞÞ ABRET: 12-month compounded size-adjusted returns. RET(i): firm raw return in month i, where i = 1 is the fifth month after fiscal-year-end. SIZRET(i): return on the size portfolio corresponding to the firm in month i, the size portfolio is supplied by CRSP. 12

FRETt ¼ j ð1 þ RETðiÞÞ  1 i¼1

FRETt: compounded annual firm returns during fiscal-year t.

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shows that on average, accruals are income-decreasing, with a mean of − 0.015 and a median of − 0.022. Panel B indicates that current cash earnings have a much stronger correlation with one-year-ahead earnings, with a Pearson (Spearman) correlation coefficient of 0.58 (0.56), than current accrued earnings, which have a Pearson (Spearman) correlation coefficient with one-year-ahead earnings of 0.13 (0.14). Next, I test whether or not there is a differential between the persistence of accrued earnings for the bad-/good-news group and that of accrued earnings for the neutral-news group. Then I test whether or not the market efficiently prices this differential in persistence, if it exists. 3.4. Differences in the persistence of accruals among return-news groups I test the differential persistence of accruals between the bad-news group and the neutralnews group by running regressions with Eq. (5). Panel A of Table 2 reports the results. The persistence factor for the neutral-news group is 0.75, but for the bad-news group, the persistence factor is smaller, by − 0.12, at 0.63. The difference is statistically significant with a t-statistic of − 12.99. As expected, accrued earnings for the bad-news group are less persistent in predicting future earnings than accrued earnings for the neutral-news group. Cash earnings are also less persistent for the bad-news group than for the neutral-news group, with a differential of − 0.06. However, the differential for accrued earnings represents a 16.0% drop in persistence, but the differential for cash earnings represents only a 7.2% drop in persistence. Panel B of Table 2 reports parallel results for testing the differential persistence between the good-news group and the neutral-news group. The differential persistence for both accruals and cash earnings, although statistically significant, is much smaller. For accrued earnings, the persistence factor of the good-news group is lower than that of the neutralnews group by − 0.04 (a 5.3% drop in persistence). For cash earnings, the persistence factor of the good-news group is lower than that of the neutral-news group by − 0.03 (a 3.6% drop in persistence). Table 2 Ordinary least squares regressions of future earnings on the accruals and cash components of current earnings Panel A: The bad-news group versus the neutral-news group

Estimate t-statistic

b0

b1

c0

c1

b0 + b1

c0 + c1

R2

0.83 212.46

− 0.06 − 9.18

0.75 138.34

− 0.12 − 12.99

0.77

0.63

0.62

c1

b0 + b1

c0 + c1

R2

0.80

0.71

0.63

Panel B: The good-news group versus the neutral-news group

Estimate t-statistic

b0

b1

c0

0.83 229.13

− 0.03 − 4.35

0.75 149.20

− 0.04 − 3.95

Notes: Variable definitions: see Table 1 notes. IDt is a dummy variable that takes value one for bad-news/goodnews firms and zero for neutral-news firms. EARNtþ1 ¼ a0 þ a1 IDt þ b0 CASHt þ b1 CASHt ⁎IDt þ c0 ACCRt þ c1 ACCRt ⁎IDt þ e

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In the premise of this study, it is difficult to make a clear prediction regarding the difference in the level of persistence for accruals between the good-news group and the neutral-news group, because accounting conservatism and earnings management in response to stock-price movement do not dictate that accrued earnings for the good-news group should be more or less persistent. The result here indicates that accrued earnings are also less persistent in predicting future earnings for the good-news group than for the neutralnews group. However, the differential is much smaller than the differential between the badnews group and the neutral-news group. 3.5. The Mishkin test Sloan (1996) shows that accrued earnings are less persistent than cash earnings, whereas the previous section shows that accrued earnings preceded by bad return news are incrementally less persistent. This section tests whether the market misprices this differential in persistence for accrued earnings. The first test of market efficiency is the Mishkin test. The test results are reported in Table 3. Panel A reports the coefficient estimates of Eqs. (5) and (6). For the neutral-news group, the actual persistence factor for accrued earnings is 0.75; however, the market overestimates this factor by 18.7%, to be 0.89. The likelihood ratio for the efficient-pricing constraint c0 = c0e is 62.43 (Panel B), and it is statistically significant, which rejects the efficient pricing of accrued earnings for the neutral-news group. Between the bad-news group and the neutral-news group, the differential persistence factor is − 0.12, but the market-perceived difference is 0.06. The likelihood-ratio statistic for the efficient pricing of this differential persistence (c1 = c1e) is 31.60, signaling that the market overestimates the differential persistence for accrued earnings between the badnews group and the neutral-news group. Overall, for the bad-news group, the market overestimates the persistence factor for accrued earnings by 50.8% (an actual persistence factor of 0.63 versus a market-perceived persistence factor of 0.95, with a significant likelihood ratio of 219.46 for the efficientpricing constraint, c0 = c0e c1 = c1e). The overestimation of the persistence factor of accrued earnings for the bad-news group (50.8%) is markedly higher than for the neutral-news group (18.7%).7 Thus, the Mishkin test supports the argument that the market does not fully see through the incrementally lower persistence of the accrued earnings for the bad-news group than for the neutral-news group, and that the market misprices the stocks in the bad-news group to a greater extent. Table 3 also reports the results for cash earnings. Sloan (1996) reports that investors underestimate the persistence for cash earnings. However, Table 3 shows no underestimation of the persistence of cash earnings for the neutral-news group (with a likelihood ratio at an insignificant 2.28 for the efficient-pricing constraint b0 = b0e). For the bad-news group, while the actual persistence factor is 0.77, the market overestimates it by 13%, at 0.87 (with a 7 I do not attempt to test statistically the significance level of the difference between the mispricing of accrued earnings for the neutral-news group and the mispricing of accrued earnings for the bad-news group, because such a test statistic is not readily available (Xie, 2001).

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Table 3 Nonlinear generalized least squares estimation (the Mishkin test) of the market pricing of accruals with respect to their implications for one-year-ahead earnings, the bad-news group versus the neutral-news group Panel A: the Mishkin test results Bad-news versus neutral-news

Good-news versus neutral-news

Parameter

Estimate

Estimate

b0 be0

0.83 0.85 2.4%⁎ −0.06 0.02 13.0%⁎ 0.75 0.89 18.7%⁎ −0.12 0.06 50.8%⁎ 2.28

b1 be1 c0 ce0 c1 ce1 β

Asymptotic standard error 0.004 0.013 0.007 0.022 0.005 0.018 0.009 0.031 0.035

0.83 0.85 2.4%⁎ − 0.03 − 0.07 − 2.5%⁎ 0.75 0.89 18.7%⁎ − 0.04 − 0.02 22.5%⁎ 2.47

Asymptotic standard error 0.004 0.011 0.007 0.020 0.005 0.015 0.009 0.028 0.035

Panel B: Test of efficient pricing of earnings components Bad-news versus neutral-news

Good-news versus neutral-news

Efficient pricing constraints

Likelihood ratio statistics

Marginal significance level

Likelihood ratio statistics

Marginal significance level

b0 = be0 b1 = be1 c0 = ce0 c1 = ce1 b1 = be1 c1 = ce1 b0 = be0 b1 = be1 c0 = ce0 c1 = ce1 b0 = be0 b1 = be1 c0 = ce0 c1 = ce1

2.28 13.33 62.43 31.60 33.12 33.50 219.46 228.20

0.14 b0.01 b0.01 b0.01 b0.01 b0.01 b0.01 b0.01

2.69 4.04 72.16 0.44 7.62 4.48 112.03 150.09

0.11 0.05 b0.01 0.52 b0.01 0.04 b0.01 b0.01

Note: Variable definition: see Table 1 notes. IDt is a dummy variable that takes value one for bad-news/good-news firms and zero for neutral-news firms. Numbers with ⁎ are percentages of misestimation and are computed as (market-perceived persistence/actual persistence)/actual persistence. EARNtþ1 ¼ a0 þ a1 IDt þ b0 CASHt þ b1 CASHt ⁎IDt þ c0 ACCRt þ c1 ACCRt ⁎IDt þ e ABRETtþ1 ¼ a þ b⁎ðEARNtþ1  a0  a1 IDt  be0 CASHt  be1 CASHt ⁎IDt  ce0 ACCRt  ce1 ACCRt ⁎IDt Þ

statistically significant likelihood ratio at 33.50 for the efficient pricing constraint b0 = b0e b1 = b1e). The overestimation for the bad-news group is mainly due to the overestimation of the differential-persistence of cash earnings between the bad-news group and the neutralnews group. While the actual differential persistence factor for cash earnings is − 0.06, the market perceives it to be 0.02 (with a statistically significant likelihood ratio of 13.33 for the efficient-pricing constraint b1 = b1e).

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Table 3 also reports the Mishkin results for the good-news group and neutral-news group comparison. First, while the market overestimates the persistence factor of accrued earnings for the neutral-news group by 18.7%, it does so by 22.5% for the good-news group (an actual persistence factor of 0.71 versus a market-perceived persistence factor of 0.87, with a statistically significant likelihood ratio of 112.03 for the efficient pricing constraint c0 = c0e c1 = c1e). The difference in misestimation, 22.5% versus 18.7%, is much smaller than that between the bad-news group and the neutral-news group, 50.8% versus 18.7%. Second, the differential-persistence factor for accrued earnings between the good-news group and the neutral-news group is − 0.04, but the market perceives it to be − 0.02. The likelihood-ratio statistic for the efficient pricing of the differential persistence (c1 = c1e) is only 0.44, which lacks statistical significance. Therefore, the Mishkin test indicates that the market does not misestimate the persistence of accruals to a greater extent for the good-news group than for the neutral-news group. The market does not appear to misestimate the persistence of cash flow for the neutralnews group (an insignificant likelihood-ratio statistic of 2.69 for the efficient-pricing constraint b0 = b0e). With marginal statistical significance (a likelihood ratio of 4.04 for the efficient-pricing constraint b1 = b1e), the market underestimates the differential persistence for cash flow between the good-news group and the neutral-news group. Overall, the market appears to underestimate the persistence of cash earnings in the good-news group by 2.5% (an actual persistence factor of 0.80 versus a market-perceived factor of 0.78, with a significant likelihood ratio of 7.62 for the efficient-pricing constraint b0 = b0e b1 = b1e). This is the only case consistent with Sloan's (1996) finding that market underestimates the persistence of cash earnings.8 3.6. The hedge-portfolio analysis I complement the Mishkin test with a hedge-portfolio test, which tests whether a trading strategy based on accruals would yield higher abnormal returns for the bad-news group than it would for the neutral-news group. For each year, I partition firms independently into five accrual portfolios and three return-news portfolios (bad-news, good-news, and neutralnews). Each of the 15 return news-accruals portfolios that this procedure generates consists of firms falling into an accrual/return news intersection. As a result, I get five accrual subportfolios for each return-news group. To implement a hedge strategy for each return-news group, I long stocks in the lowest-accrual portfolio of that return-news group, and short stocks in the highest-accrual portfolio of that return-news group. The hedge return is the sum of the returns from the long and the short portfolios. I track the returns to the hedge portfolios in the one-year-ahead period to determine whether economically significant abnormal profits can be earned. The measure of abnormal returns is the intercept term from a regression with the FamaFrench three-factor model. The results are reported in Table 4. Panel A reports the coefficient estimates for the long, short, and hedge portfolios for each of the three return-news groups separately. My discussion focuses on the hedge portfolio, whose returns are the sum of 8

I conducted a Mishkin test for the mispricing of accruals and cash flows in the full sample, and find that cash flows were overpriced, contrary to evidence from earlier literature.

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Table 4 Abnormal returns to accrual portfolios and hedge portfolios Panel A: Portfolio returns by return-news groups

Bad-news group

Lowest-accrual portfolio Highest-accrual portfolio Hedge portfolio Lowest-accrual portfolio

Neutral-news group

Highest-accrual portfolio Hedge portfolio Lowest-accrual portfolio

Good-news group

Highest-accrual portfolio Hedge portfolio

Intercept

MKT

SMB

HML

R2

0.488 (2.67) − 0.244 (−1.49) 0.732 (3.86) 0.336 (4.23) − 0.011 (−0.14) 0.347 (3.29) 0.432 (2.75) − 0.146 (−1.29) 0.579 (3.27)

1.019 (22.43) 1.072 (26.32) − 0.054 (−1.14) 0.976 (49.35) 1.021 (52.83) − 0.045 (−1.71) 0.963 (24.66) 1.110 (39.22) − 0.147 (−3.25)

1.353 (21.02) 1.314 (22.75) 0.039 (0.59) 0.828 (29.52) 1.002 (36.57) − 0.174 (− 4.68) 0.892 (16.12) 1.035 (25.77) − 0.142 (− 2.28)

0.530 (7.15) 0.303 (4.55) 0.228 (2.95) 0.327 (10.12) 0.075 (2.36) 0.252 (5.89) − 0.139 (− 2.17) − 0.214 (− 4.64) 0.076 (1.05)

0.774

Intercept

MKT

SMB

HML

R2

0.151 (0.86) − 0.233 (−1.52) 0.385 (1.95) 0.096 (0.58) − 0.136 (−1.03) 0.232 (1.21)

0.043 (0.97) 0.052 (1.36) − 0.009 (−0.18) − 0.013 (−0.31) 0.090 (2.75) − 0.103 (−2.15)

0.526 (8.43) 0.312 (5.78) 0.213 (3.07) 0.065 (1.11) 0.033 (0.71) 0.032 (0.47)

0.204 (2.83) 0.228 (3.67) − 0.025 (− 0.31) − 0.465 (− 6.97) − 0.289 (− 5.41) − 0.176 (− 2.26)

0.171

0.819 0.028 0.923 0.942 0.184 0.783 0.903 0.067

Panel B: Difference in portfolio returns between return-news groups

Bad news/neutral news

Lowest-accrual portfolio Highest-accrual portfolio Hedge portfolio Lowest-accrual portfolio

Good news/neutral news

Highest-accrual portfolio Hedge portfolio

0.105 0.018 0.121 0.128 0.010

Notes: The Fama-French model is based on Fama and French (1993). It is in the following form: Rp;t  Rf ;t ¼ ap þ bp ðRm;t  Rf ;t Þ þ sp SMBt þ hp HMLt þ ep;t Rft = the one-month Treasury bill rate (from Ibbotson Associates). Rmt = the value-weighted return on all NYSE, AMEX, and NASDAQ stocks (from CRSP). SMBt = the difference between the month t returns of a value-weighted portfolio of small stocks and one of large stocks. HMLt = the difference between the month t returns of a value-weighted portfolio of high book-to-market stocks and one of low book-to-market stocks. Rp,t is the equally-weighted returns of all stocks in a portfolio.

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returns to the long and the short portfolios. For the hedge portfolio, the intercept term for the bad-news group is 0.732 (8.8% on an annual basis), 0.579 for the good-news group (6.9% on an annual basis), and 0.347 for the neutral-news group (4.2% on an annual basis), which are all statistically significant. Panel B reports the differential returns to the accrual-based hedge strategy across the three return-news groups. For example, when I compare the bad-news group to the neutralnews group on accrual-based hedge returns, I take the differences between the monthly hedge returns for the bad-news group and the monthly hedge returns for the neutral-news group, then I regress this time-series of monthly differential hedge-returns on the FamaFrench factors. If the intercept term is statistically significantly greater than zero, it indicates that after controlling the Fama-French factors, the accrual-based hedge strategy earns higher abnormal returns for the bad-news group than for the neutral-news group. The intercept term is 0.385 (4.6% on an annual basis) when I compare hedge returns between the bad-news group and the neutral-news group, and the intercept term is significant with a t-statistic of 1.95. This result confirms the Mishkin test finding (Table 3) that investors significantly overestimate the differential persistence of accrued earnings between the bad-news group and the neutral-news groups. Most importantly, such mispricing is economically significant and can be exploited to earn higher abnormal returns for an accrual-based hedge strategy. In the good-news group/neutral-news group comparison, the intercept term is 0.232 (2.8% on an annualized basis), but it is not statistically significant, consistent with the Mishkin test finding (Table 3) that while investors overestimate the persistence of accrued earnings for the good-news group more than for the neutral-news group, the difference is not statistically significant. In summary, the Mishkin test and the hedge-portfolio test suggest that the market fails to recognize the incrementally lower persistence of accrued earnings for the bad-news group and, subsequently, misprices those stocks to a greater extent. For the good-news group, there is evidence of lower persistence of accrued earnings than for the neutral-news group. But the differential is small relative to that between the bad-news group and the neutral-news group, and greater mispricing is not detected. The Sloan accrual anomaly concentrates on bad-news firms. 3.7. Multivariate analysis of returns to accrual-based trading strategy There is one concern about the strength of the conclusions derived from the hedgeportfolio analysis. Low-accrual portfolios tend to contain low-return stocks, and highaccrual portfolios tend to contain high-return stocks. Therefore, the higher hedge returns from the bad-news group may be a result of a larger magnitude of income-decreasing accruals, which tend to accompany bad return-news stocks. Even without a differential in persistence, such a larger magnitude of accruals for the bad-news group would yield higher hedge returns. This argument contradicts my argument that it is the differential in persistence of accrued earnings that leads to the higher hedge returns. To address this concern, I conduct a multivariate analysis in the following form: FRETtþ1 ¼ a0 þ a1 IDt þ b0 ACCR t þ b1 ACCR t ⁎IDt þ g0 SIZEt þ g1 SIZEt ⁎IDt þ d0 B=Pt þ d1 B=Pt ⁎IDt þ f0 BETAt þ f1 BETA t ⁎IDt þ g0 E=Pt þ g1 E=Pt ⁎IDt þ et

ð8Þ

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The dependent variable is a one-year-ahead raw return. This multivariate analysis has two important features. First, the regression includes a variety of control variables used in accounting and finance literature as proxies for factors that predict stock returns (Penman & Zhang, 2002; Sloan, 1996). Among them are firm size, book-to-market ratio, CAPM beta, and earnings-to-price ratio. Second, I include a dummy variable, ID, which interacts with ACCR and other variables in the regression, indicating which return-news group a firm falls into. For the bad-news group and the neutral-news group comparison (other comparisons defined similarly), β 0 measures the relation between accrued earnings and firms' one-year-ahead stock returns for the neutral-news group; and β1 measures the incremental relation (relative to the neutral-news group) between accrued earnings and future stock return. If, after controlling for the magnitude of accruals and these variables that have been proved to predict future returns, β1 is still significantly negative, it supports my argument that the differential persistence of accrued earnings for the bad-news group drives the greater mispricing of accruals. Following Fama and MacBeth (1973), I run Eq. (8) annually. Table 5 reports the means of the time-series of coefficient estimates. The t-statistics are based on the time-series of the standard errors of the estimated coefficients. When comparing the bad-news group to the neutral-news group, β 0, the coefficient on accruals for the neutral-news group, is significantly negative at −0.322. β1, the incremental relation between accrued earnings and future returns Table 5 Cross-sectional tests of the differential explanatory power of accruals with respect to future raw returns Bad-news group/ neutral-news group Definition α0 α1 β0 β1 γ0 γ1 δ0 δ1 ζ0 ζ1 η0 η1

Intercept Incre. Intercept ACCR Incre. ACCR SIZE Incre. SIZE Book-to-Market Incre. Book-to-Market CAPM Beta Incre. CAMP Beta Earnings-to-price Incre. Earnings-to-price

Good-news groups/ neutral-news group

Coefficient

t-statistic

Coefficient

t-statistic

0.259 0.040 −0.322 −0.178 −0.025 −0.013 0.003 −0.006 −0.003 0.006 0.183 0.000

4.78⁎⁎⁎ 1.11 − 4.86⁎⁎⁎ − 2.17⁎⁎ − 3.57⁎⁎⁎ − 2.53⁎⁎ 0.26 − 0.43 − 0.23 − 0.49 2.07⁎⁎ 0.01

0.259 0.029 − 0.322 0.031 − 0.025 0.002 0.003 − 0.000 − 0.003 − 0.039 0.183 0.090

4.78⁎⁎⁎ 0.66 − 4.86⁎⁎⁎ 0.32 − 3.57⁎⁎⁎ 0.24 0.26 − 0.01 − 0.23 − 2.43 2.07⁎⁎⁎ 0.97

Notes: The numbers reported are time-series averages of the estimated parameters from annual cross-sectional regressions. T-statistic is based on the time-series standard errors of the estimated coefficients. The dependent variable is one-year-ahead raw returns. ACCR is defined in Table 1. Size is market value at the end of fiscal-year t. B/P is book value-to-market value at the end of fiscal-year t. E/P is earnings-to-price ratio at the end of fiscal-year t. BETA is estimated from a regression of monthly raw returns on the CRSP value-weighted monthly stock returns up to the last month of fiscal-year t. ⁎⁎ Denotes significance at the 0.05 level using a two-tailed t-test. ⁎⁎⁎ Denotes significance at the 0.01 level using a two-tailed t-test. FRETtþ1 ¼ a0 þ a1 IDt þ b0 ACCRt þ b1 ACCRt ⁎IDt þ g0 SIZEt þ g1 SIZEt ⁎IDt þ d0 B=Pt þ d1 B=Pt ⁎IDt þ f0 BETAt þ f1 BETAt ⁎IDt þ g E=Pt þ g E=Pt ⁎IDt þ et 0

1

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for the bad-news group, is significantly negative at −0.178. This supports my findings that the incrementally lower persistence of accrued earnings for the bad-news group causes greater mispricing, consistent with the findings of the Mishkin and hedge-portfolio tests. On the other hand, β1 in the good-news/neutral-news comparison is insignificant, also consistent with the Mishkin test and the hedge-portfolio test. In summary, multivariate analysis supports the conclusions from the Mishkin and hedgeportfolio tests. 4. Conclusion This paper adds to a growing literature on financial-statement analysis with regard to earnings accruals and their implications for the efficient-market hypothesis. I argue that in response to stock performance, accounting conservatism and earnings management generate earnings accruals that are less persistent for firms that have experienced adverse stock-price movements. The market fails to detect this differential persistence, and subsequently misprices accruals in this situation to a greater extent. The results in this paper largely support this argument. Accrued earnings in years when firms performed poorly tend to be even less persistent than accrued earnings in years when firms' stock prices do not change much. However, investors do not fully understand this differential and subsequently misprice accrued earnings in this group to a greater extent. Overall, this paper indicates that to understand the accrual anomaly, we need to take into account the environment in which accruals are generated. In particular, contemporaneous stock-price movement provides an indicator of the level of persistence of accrued earnings. Nevertheless, this paper only provides one factor that predicts the lower persistence of accruals in the cross-section. The accrual effect is strong even for the neutral-news group, although a lot weaker than documented previously by other studies. Therefore, future work is warranted to enhance our understanding of why the market fails to appreciate this longheld, basic accounting property: accrual accounting.9 References Abarbanell, J., & Lehavy, R. (2003). Biased forecasts or biased earnings? The role of earnings management in explaining apparent optimism and inefficiency in analysts' earnings forecasts. Journal of Accounting and Economics, 36, 105−146. Basu, S. (1997). The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics, 24, 3−37. Beaver, W., Lambert, R., & Morse, D. (1980). The information content of security prices. Journal of Accounting and Economics, 2, 3−28. Chan, K., Chan, L., Jegadeesh, N., & Lakonishok, J. (2006). Earnings quality and stock returns: The evidence from accruals. Journal of Business, 79, 1041−1082. Dopuch, N., Seethamraju, C., & Xu, W. (2005).The accrual anomaly within the context of profit and loss firms. Working Paper, Washington University. Fama, E., & French, K. (1993). Common risk factors in the returns on stocks and bonds. Journal of Finance, 48, 3−56.

9

Dopuch et al. (2005) is another example along this line of research. They find that accruals were mispriced only for profit firms, not for loss firms. In my sample, however, accruals were also overpriced for loss firms.

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