Quarterly Cash Flows, Accruals and
Future Returns
Joshua Livnat
Professor of Accounting
Department of Accounting
Stern School of Business Administration
New York University
311 Tisch Hall
40 W. 4 th
St.
New York City, NY 10012
(212) 998–0022 jlivnat@stern.nyu.edu
and
Massimo Santicchia
Director
Standard & Poor’s Investment Services
55 Water St.
NYC, NY 10041
(212) 438 3934 massimo_santicchia@sandp.com
First Draft: December 2004
Current Draft: April 10, 2020
The authors gratefully acknowledge the preliminary and original Compustat quarterly data provided by Charter Oak Investment Systems Inc. and the SEC filing dates provided by Compustat. The authors also thank Chiara Szczesny for copy editing. This research project is an outcome of work done by the S&P Equity Research Group.

Quarterly Cash Flows, Accruals and
Future Returns
This study shows that the famous accruals anomaly is also present in quarterly earnings and accruals. Specifically, future quarterly earnings are more highly associated with current net operating cash flows than with accruals, because accruals have lower persistence than net operating cash flows. Consequently, firms with extremely high (low) current quarterly accruals have significant and negative (positive) abnormal returns through the subsequent four quarters. A hedge portfolio that combines short positions in firms with extremely high quarterly accruals and long positions in firms with extremely low quarterly accruals is shown to generate consistently positive and economically significant returns for the 53 quarters in the study. The study is different from prior studies in that it uses the originally reported, or un-restated, quarterly data to calculate accruals and SEC filing dates to identify the precise day on which investors first obtain information about accruals.

Quarterly Cash Flows, Accruals and
Future Returns
In a rigorous study, Sloan (1996) documents that net operating cash flow is more closely associated with future income and stock returns than accruals; which is the difference between income and net operating cash flows. Sloan attributes this phenomenon to the fact that accruals reverse faster than earnings in subsequent periods and are less persistent than net operating cash flows. Investors who focus on total income and not on operating cash flows tend to overestimate the persistence of accruals and underestimate the persistence of net operating cash flows. A trading strategy that holds long positions in companies with extremely low accruals and short positions in companies with high accruals obtains significant abnormal returns over the subsequent three years. Sloan also shows that a substantial portion of the abnormal returns to the accrual strategy occurs around subsequent quarterly earnings announcement dates, consistent with an initial market mispricing of accruals that is corrected when future quarterly earnings become known. Sloan’s findings have been confirmed by many ensuing studies.
To better understand what accruals are and why they are likely to be less persistent than net operating cash flows, the appendix highlights two specific accrual cases of inventory and accounts receivable. In the first case, management is overly optimistic about future sales, building up excessive inventories that are reduced in future periods. Because the current accounting system treats inventory increases as investments in assets which are not expensed on the income statement, earnings are initially higher
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but lower in subsequent periods when inventories are drawn down. The first case does not assume any sinister managerial motives; it is based on the reasonable assumption that some managers may at times be too optimistic about future demand leading to excess inventories. The second case is based on channel stuffing
1
, when a manager inflates current income by booking current sales that are not collected until future periods and that reduce future sales. The accounting system again records the increase in receivables as an investment, and the income statement is based on all sales whether collected during the period or not, leading to higher current income at the expense of lower future income.
Of course, managers can also affect current income through mere accounting choices
(unlike the channel stuffing described in the second case) such as the selection of aggressive accounting methods and estimates. For example, if bad debt expense in the current period is too low it will likely lead to higher bad debt expense in the future and lower future income.
Whether accruals are actively managed to produce a desired level of current income, or are just due to genuine but erroneous managerial expectations about the future, the current accounting system nevertheless includes accruals in current earnings, which may be less persistent into future earnings. Careful financial statement users such as financial analysts, investors and creditors should closely scrutinize the firm’s quarterly accruals for the possibility of future reversals. However, if a sufficiently large proportion of investors are fixated on earnings, ignoring information in net operating cash flows and accruals, prices may not accurately reflect the economic situation of the firm, leading to a potential mispricing and the accruals anomaly.
1 Channel stuffing is a deceptive business practice used by a company to inflate sales by deliberately sending retailers along its distribution channel more products than they are able to sell to customers during the normal course of business.
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The purpose of this study is to investigate whether quarterly accruals exhibit the same pattern as that of annual accruals in prior studies. As the literature review in the next section illustrates, most accruals studies to date focused on annual accruals, which are shown to have lower levels of persistence than net operating cash flows. However, if extreme quarterly accruals contain valuable information about future earnings and stock return reversals, users of financial statements should focus on quarterly cash flows and accruals to obtain an early warning signal that future earnings may reverse. Financial analysts tend to revise earnings forecasts after quarterly earnings are released; therefore, their ability to improve forecasts after a careful consideration of quarterly accruals and cash flows is likely to be extremely important for them. Similarly, investment and credit managers are unlikely to wait around a whole year for the next annual earnings announcement to examine changes in accruals, rebalance their portfolios, or take actions about their outstanding credit positions, if such information is available and is useful on a quarterly basis.
Why then did most previous studies examine annual instead of quarterly accruals?
There are two primary reasons for that. First, accruals typically become known to the market when firms file their 10-Q/10-K forms with the SEC, unless they disclose net operating cash flows in their preliminary earnings announcements, which only about 10% do. Unlike preliminary earnings release dates which are available in the Compustat
Quarterly database, SEC filing dates are not part of computerized databases used by academics, hence quarterly accruals have not been studied by academics in earlier studies due to the massive necessary hand-collection. Instead, these studies focused on annual accruals, beginning the return accumulation period four months after fiscal year-end,
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when firms have already filed their 10-K forms with the SEC. The second reason for not studying quarterly accruals is that quarterly accruals and subsequent reversals may be very natural and likely in companies that are subject to seasonality in their operations. It is unclear whether quarterly accruals may exhibit the same pattern as annual accruals if most firms are affected by within-year seasonality in operations.
Our study shows that quarterly net operating cash flows are more persistent than quarterly accruals, and that future quarterly earnings are more strongly associated with current quarter’s net operating cash flows than with current accruals. Furthermore, there is a negative and statistically significant association between current accruals and subsequent abnormal stock returns through all four subsequent quarters. We also show that a hedge portfolio that holds long positions in companies with the most extreme negative accruals and short positions in companies with the most extreme positive accruals yields positive and significant abnormal returns, whether held for one, two, three or even four quarters. These results indicate that analysts, investors and credit managers need to carefully examine net operating cash flows and accruals when interpreting current quarterly earnings.
The accruals anomaly is based on the implicit premise that accruals tend to be less persistent than net operating cash flows because of intentional or unintentional managerial errors in forecasting future demand, events, or cash flows that cause erroneous levels of current accruals. In particular, managers may use positive accruals to elevate earnings when operating cash flows are low and negative accruals that reduce
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high levels of earnings when operating cash flows are high. Indeed, Sloan (1996) and others document a negative association between net operating cash flows and accruals, as well as higher earnings for companies with higher levels of accruals than those with lower accruals. Xie (2001) and DeFond and Park (2001) provide evidence that the accrual anomaly is driven by the mispricing of abnormal accruals, i.e., those that are subject to managerial discretion. In contrast, Beneish and Vargus (2002) find that the accrual anomaly can mainly be attributed to mispricing of income-increasing accruals, regardless of whether total or discretionary accruals are used. Thomas and Zhang (2002) attribute the accruals anomaly to investors’ failure to correctly understand the role of inventory changes, which is just one although important component of total accruals. Richardson,
Sloan, Soliman and Tuna (2004) provide evidence that the accruals anomaly can be attributed to those accounts that have low earnings quality and potentially high managerial discretion.
Several studies attempt to determine whether the accrual anomaly is unique, supplemented, or subsumed by other known anomalies. Collins and Hribar (2000) show that the accruals anomaly is separate from the post-earnings-announcement drift, and that combining both anomalies yields greater abnormal returns than each of them alone. Barth and Hutton (2003) show that the accruals anomaly can be combined with analysts’ earnings revisions to yield greater abnormal returns. Desai, Rajgopal and Venkatachalam
(2004) provide evidence that the accruals anomaly is another manifestation of the valueglamour (growth) anomaly. Finally, Fairfield, Whisenant and Yohn (2003) suggest that the accrual anomaly is partially driven by mispricing the implications of growth in net operating assets for future profits and returns.
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As for most anomalies, a question remains why the accruals anomaly persists and are not arbitraged away. Collins, Gong and Hribar (2003) provide evidence that firms with a greater proportion of institutional investors, who are supposed to be more sophisticated, are subject to a weaker accruals anomaly. Mashruwala, Rajgopal and
Shevlin (2004) show that the annual accruals strategy does not earn positive abnormal returns in all twelve months after portfolio formation, and that it is indeed weaker for companies with lower arbitrage risk. Lev and Nissim (2004) show that firms with extreme accruals have attributes that institutional investors shun. Finally, Kraft, Leone and Wasley (2004) argue that the accruals anomaly is likely driven by relatively few extreme observations and the failure to properly use delisting returns.
Most accrual studies have followed Sloan’s (1996) use of annual cash flows and accruals, which are associated with annual buy and hold returns. There are just a few studies that examine whether the accruals anomaly is present in quarterly data. Collins and Hribar (2000) provide such evidence, but they accumulate returns from the assumed
SEC filing date through the subsequent two quarters, and not from the actual date on which investors obtain access to the SEC filings. DeFond and Park (2001) examine whether investors seem to interpret quarterly earnings surprises correctly, depending on abnormal working capital accruals for a sample of observations in the years 1992-1995.
They show that abnormal returns for good earnings news firms with income-decreasing accruals during the 80-day period after the preliminary earnings announcement exceed those with income-increasing accruals. However, they essentially assume that the market has the accrual information at the time of the preliminary earnings announcement.
2 Thus,
2 In robustness checks, they mention that their results are weaker for a sub-sample of firms with balance sheet information in the preliminary earnings announcement. They also report that their results do not
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there is very little research into whether quarterly accruals follow the same patterns as those observed for annual accruals. Financial analysts, investors and creditors are likely to be interested in applying the accruals strategy using quarterly data instead of waiting a whole year for the next annual earnings, if quarterly accruals exhibit similar characteristics to annual accruals.
3.1 The Preliminary and Un-restated Compustat Quarterly Data
Data entry into the Compustat databases has been performed in a fairly structured manner over the years. When a firm releases its preliminary earnings announcement,
Compustat takes as many line items as possible from the preliminary announcement and enters them into the quarterly database within 2-3 days. The preliminary data in the database are denoted by an update code of 2, until the firm files its Form 10-Q (10-K) with the SEC or releases it to the public, at which point Compustat updates all available information and uses an update code of 3. Unlike the Compustat Annual database, which is maintained as originally reported by the firm (except for restated items), the Compustat
Quarterly database is further updated when a firm restates its previously reported quarterly results. For example, if a firm engages in mergers, acquisitions, or divestitures at a particular quarter and restates previously reported quarterly data to reflect these events, Compustat inserts the restated data into the database instead of the previously reported numbers. Similarly, when the annual audit is performed and the firm is required change when they use abnormal returns cumulated from the preliminary earnings announcement through the next 20 trading days, which presumably include the SEC filing date. They report that their results hold for the first three fiscal quarters but not for the fourth.
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to restate its previously reported quarterly results by its auditor as part of the disclosure contained in Form 10-K, Compustat updates the quarterly database to reflect these restated data.
Charter Oak Investment Systems, Inc. (Charter Oak) has collected the weekly original CD-Rom that Compustat sent to its PC clients, which always contained updated data as of that week. From these weekly updates, Charter Oak has constructed a database that contains three numbers for each firm for each Compustat line item in each quarter.
The first number is the preliminary earnings announcement that Compustat inserted into the database when it bore the update code of 2. The second number is the “As First
Reported” (AFR) figure when Compustat first changed the update code to 3 for that firmquarter. The third number is the number that exists in the current version of Compustat, which is what most investors use. The Charter Oak database allows us to use the firstreported information in the SEC filing, so that our quarterly earnings, cash flows and accruals correspond to those reported originally by the firms, which are also available to market participants at the time of the SEC filing. Using the restated Compustat Quarterly database may induce a hindsight bias into our back-tests, since we may have used restated earnings, cash flows or accruals that were not known to market participants on the SEC filing dates.
3.2 Sample Selection
The initial population for the study consists of all firm-quarters in the Compustat database between the first quarter of 1988 (the first quarter after the adoption of SFAS
No. 95, which mandated the disclosure of net operating cash flow) and the most recent quarter at the time of the study. The only limitation on the initial selection of firm-
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quarters is that market value at quarter end is in excess of $50 million, yielding an initial population of 368,378 firm-quarters. From this initial population, we delete observations if the originally reported income before extraordinary items and discontinued operations
(Compustat Quarterly item No. 8) is missing; or the originally reported quarterly net operating cash flow (Compustat Quarterly item No. 108) is missing; if market value at the end of the prior quarter is unavailable; or if total assets (Compustat Quarterly item
No. 44) at the end of the prior quarter or the at the end of the current quarter are missing.
This yields a reduced population of 242,292 firm-quarters.
For each firm-quarter in this reduced population, we obtain the SEC filing date of the 10-Q/K forms, which is supplied to us by Compustat for the calendar years 1991-
2004. This reduces the sample to 176,864 observations with SEC filing dates. We then use the GVKEY from Compustat to match the observation to the CRSP database. We compute Buy and Hold excess Returns (BHR) from two days after the SEC filing date through the next four subsequent preliminary earnings announcements. We assume that investors get access to the SEC filings on the day after the filing date, and that after estimating accruals, they take portfolio positions on the following day. We use holding periods through one day after subsequent earnings announcements since prior studies indicate that a substantial portion of the accrual strategy returns are generated around subsequent earnings announcements, presumably when investors understand their earlier mispricing.
To reduce the survival bias, we use holding periods of 90, 180, 270, or 360 days after the SEC filing date if subsequent quarterly earnings announcements are missing. If a security is delisted from an exchange before the end of the holding period, we use the
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delisting return from CRSP if available, and -100% if the stock is forced to delist by the exchange or if the delisting is due to financial difficulties. After delisting, we assume the proceeds are invested in the benchmark size and B/M portfolio. This is the procedure used by Kraft, et al (2004). We first calculate the buy and hold return on the security during the holding period; then subtract the buy and hold return on a similar size and B/M benchmark portfolio for the same holding period. The benchmark returns are from
Professor Kenneth French’s data library, based on classification of the population into six
(two size and three B/M) portfolios.
3
To make sure that our results are not driven by observations with extreme returns, we delete all observations with buy and hold excess returns in any of the four return periods at the top or bottom 0.5% of the distribution. This reduces the sample to 155,985 firm-quarters.
Consistent with the accruals literature, we estimate accruals as earnings minus net operating cash flows, and scale by average assets during the quarter. To be consistent in our scaling, all current and subsequent quarters’ variables (i.e., earnings, net operating cash flows and accruals in quarters t, …,t+4) are scaled by average total assets in quarter t.
4
To eliminate the undue influence of extreme observations, earnings, net operating cash flows and accruals are winsorized to fall in the range [-1,+1]. This procedure keeps all observations, even when some earnings, cash flows, or earnings surprises are extreme.
Table 1 provides summary statistics about our sample. As can be seen from the table, mean (median) quarterly earnings are about -0.07% (1.03%) of average total assets, with over 75% of the firm-quarters having positive earnings. The mean (median) quarterly net operating cash flow is even higher at 1.25% (1.78%) of average total assets,
3 http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.
4 Scaling by net operating assets in subsequent quarters may introduce a bias due to growth in total assets as is shown by Fairfield, et al. (2003).
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but accruals have a negative mean (median) of 1.33% (1.0%) of average assets, mostly due to depreciation and amortization which is included in income but excluded from net operating cash flow. Note that in spite of the negative mean and median accruals, over
25% of the observations have positive, income-increasing accruals. Finally, the mean
(median) buy and hold abnormal return from the SEC filing through the subsequent preliminary earnings announcements are all negative, indicating that the average firm in our sample has been likely to disclose unfavorable news from the SEC filing through the subsequent earnings announcement.
(Insert Table 1 about here)
To focus on firms which are more likely to have extreme accruals that will be less persistent, we further require that all observations in the bottom two deciles of accruals, i.e., the most negative accruals, have both positive income and positive net operating cash flow. Such firms have either decided to manage earnings downwards to reduce already high positive earnings and operating cash flows, or have future expectations that are too pessimistic on the average.
5 We further require that firms in the top two accrual deciles, i.e., the most positive accruals, also have positive current earnings, consistent with either income-increasing earnings management or with too optimistic forecasts on the average.
These restrictions reduce the sample further to 137,012 observations for the remaining analyses.
5 The assignment to accrual deciles is based on all available observations even if they do not have SEC filing dates or abnormal returns. As is well documented by Sloan (1996) and others, firms in the extreme accrual deciles tend to be smaller than other firms.
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Table 2 shows the distribution of excess Buy and Hold Returns (BHR) from two days after the SEC filings through one day after the subsequent earnings announcements for sample observations sorted according to the level of accruals each quarter. The accruals literature provides evidence that firms with income-decreasing, or low, accruals have larger future subsequent abnormal returns than firms with income-increasing, or high, accruals. The evidence in Table 2 is consistent with those prior findings. The bottom accruals decile (decile 0) always has higher subsequent returns than the top accruals decile (decile 9). Note that this difference in BHR is 3.4% for the first quarter, rising to 6.1% through quarter t+2, 8.4% through quarter t+3, and 9.9% through quarter t+4. The latter result is comparable to Sloan’s (1996) hedge portfolio return for the subsequent year. The table also shows that the long portfolio (extreme negative accruals, decile 0) has BHR that exceeds the expected transaction costs of 2%. Thus, the strategy yields positive abnormal returns net of transaction costs, even if only the long position is used.
(Insert Table 2 about here)
The accruals literature attributes the negative association between accruals and returns to the lower persistence of accruals as compared to net operating cash flows.
Table 3 examines the relationship between earnings in the subsequent four quarters and current earnings, net operating cash flows and accruals. As can be seen in the table, there is a positive and statistically significant association between current earnings, and earnings in the subsequent four quarters, where about 78-79 cents of each dollar of current quarter’s earnings is carried over to earnings in the subsequent four quarters (79,
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78, 78, and 83 cents for the subsequent four quarters, respectively)
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. The table also shows that net operating cash flow is more persistent than accruals, with 81 cents of every dollar of cash flow carried over to the subsequent four quarters (81, 81, 81 and 87 cents, respectively), whereas only about 68-74 cents of a dollar of accruals are carried over to earnings in the subsequent four quarters (74, 70, 68, and 73, respectively). Thus, consistent with findings about annual data, quarterly net operating cash flows and accruals exhibit the same pattern of a greater persistence of net operating cash flows than accruals into future earnings.
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(Insert Table 3 about here)
Table 4 provides direct evidence about the persistence of accruals. It shows the associations between accruals in the current quarter t and those in the subsequent four quarters. The table shows a negative and statistically significant association between current accruals and accruals at quarter t+1 (-0.025, p<0.0001), which is then completely reversed by quarter t+2 (0.025, p<0.0001), no association with accruals in quarter t+3
(0.001, p=.831), and a very high and significant positive association with accruals in quarter t+4 (0.419, p<0.0001). Thus, Table 4 shows that quarterly accruals tend to reverse in the immediately subsequent quarter, reverse again (becoming a positive association) in quarter t+2, and exhibit a high level of seasonality at quarter t+4. This evidence may explain why accruals are less persistent than net operating cash flows in predicting future quarterly earnings. The lower level of persistence in quarterly accruals explains why a strategy of long positions in firms with low accruals and short positions in firms with
6 The higher persistence of earnings at the current quarter t into quarter t+4 is evidence of seasonality, which is expected in quarterly data.
7 As noted at the bottom of Table 3, the coefficients on net operating cash flows and accruals are statistically different from each other in all four quarterly regressions.
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high accruals can yield significant positive returns. Earnings in firms with extreme quarterly accruals will tend to be less persistent than earnings of firms with low levels of accruals. When investors learn the surprising actual quarterly earnings in the future, stock prices decline for high accruals firms with lower future earnings and rise for low accruals firms that experience higher earnings in future quarters.
(Insert Table 4 about here)
Table 5 provides regression results that examine the association between future returns and current earnings, net operating cash flows and accruals. It shows that future
BHR’s are positively and significantly associated with current earnings for every holding period through the subsequent four quarters. An even stronger association is observed between future excess returns and current net operating cash flows, likely due to the higher persistence of net operating cash flows. In contrast, there is a significantly lower incremental association between accruals in quarter t and future excess returns, after controlling for the levels of net operating cash flows, likely due to the lower persistence of accruals. These results indicate that future returns are more strongly related to net operating cash flows than to accruals.
(Insert Table 5 about here)
Table 6 examines the differential future returns to the extreme decile portfolios using a methodology that is used extensively in post-earnings-announcement drift studies. Firms are sorted into accrual deciles every quarter and assigned the decile rank
(with the lowest accrual decile obtaining the rank of 0 and the highest the rank of 9). The decile rank is divided by 9, which is then subtracted by 0.5, so that the scaled decile rank now ranges between -0.5 and 0.5. When future BHR’s are regressed on the scaled decile
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rank, the intercept measures the average excess return across all deciles, while the slope coefficient measures the differential return between the highest accrual decile and the lowest accrual decile. As can be seen in Table 6, the intercept is almost never significant, whereas the slope coefficient is always negative and statistically different from zero. This is expected since the highest accrual decile is expected to yield future returns that are lower than the lowest accrual decile. The table also shows that the “hedge” portfolio of the lowest accrual decile minus the highest accrual decile yields an excess return of
2.71% (-0.0271 slope coefficient) for the first subsequent quarter, 5.19% through the second quarter, 6.72% through the third quarter, and 7.82% through the fourth subsequent quarter. These are both economically and statistically significant excess returns, even after transaction costs.
(Insert Table 6 about here)
Table 7 examines the average returns on extreme accruals and hedge portfolios across the 53 quarters, from the first quarter of 1991 through the first quarter of 2004, using a testing methodology similar to Fama and MacBeth (1973). As the table reports, the long portfolio (lowest decile accruals) has a mean return from two days after the SEC filing through one day after the next earnings announcement of 2.62% over the 53 quarters, statistically significant at the 0.0001 level. In 41 of 53 quarters, the portfolio yields positive returns. In 32 of the 53 quarters, the portfolio yields positive returns above the presumed transaction costs of 2%. For the equivalent short portfolio (the highest decile accruals), the mean return is much lower at .98% although statistically significant at the 0.0056 level, with 36 quarters of above zero returns and 19 quarters of above 2% returns. The table shows that the hedge portfolio, which combines the long and
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short positions, has a mean return of 3.59%, is positive in 48 of the 53 quarters, and has above 2% returns in 37 of the 53 quarters. The table also reports the results of longer holding horizons (2-4 quarters after the SEC filings). The table shows that the benefits of the accruals strategy are increasing with longer holding returns with short positions, which provide larger and more significant returns over a period that spans at least two quarters after the SEC filings. Thus, the accruals strategy seems to be yielding abnormal returns that are both statistically and economically significant.
(Insert Table 7 about here)
Figure 1 shows the BHR abnormal returns from two days after the SEC filing through a day after the subsequent earnings announcement by quarter for the lowest
(long) and highest (short) accrual decile, as well as for the hedge portfolio that combines both positions. As can be seen in the figure, most long returns are positive (41 out of 53 quarters), and most short returns are negative (36 out of 53 quarters). Furthermore, the hedge portfolio yields positive BHR in 48 out of 53 quarters, and the magnitude of the most negative BHR is only about 5%. Thus, sorting firms by accruals is successful in predicting the returns through the next quarterly announcements. Figure 2 shows cumulative abnormal returns to the long and short accrual deciles, as well as the hedge portfolio that combines both throughout the 53 quarters used in the study. As can be seen in the figure, the cumulative returns of the long accrual decile are greater than the short accrual decile, but both are clearly dominated by the hedge portfolio. Thus, using the information inherent in accruals can help investors obtain consistent abnormal returns over a lengthy period of time.
(Insert Figures 1 and 2 about here)
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Robustness Checks:
1.
Large Firms – We repeat the analysis in Table 7 for firms with a market value of equity in excess of $1 billion. For these firms, the long portfolio generally yields returns that are not significantly different from zero, but the short portfolio yields returns that are statistically and economically significant. The hedge portfolio yields returns that are larger than those reported in Table 7 for all firms.
2.
Recent Data and Post-EDGAR data – We repeat the analysis in Table 7 with data from quarters after 1999. The hedge portfolio returns are better than those provided in Table 7, but mostly due to the long portfolio position. The short portfolio yields returns that are insignificantly different from zero. We also examined the results of Table 7 for the post-EDGAR period (after 1996). The results are similar to those in Table 7 for both the short and long portfolios, and for the hedge portfolio.
3.
Balance Sheet or Cash Flow Information is not in the Preliminary Earnings
Announcement – We repeat the analysis for firms that did not report information in their preliminary earnings announcements on the main current accruals
(inventories, accounts receivable and accounts payable) or net operating cash flows. The results are very similar to those reported in Table 7.
4.
Fourth fiscal quarter versus other quarters – The main results of Table 7 are similar for the first three fiscal quarters and the fourth quarter, except that returns in the fourth quarter are slightly lower than those in Table 7 although statistically significant, and those for the first three quarters are slightly higher.
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This study shows that, similar to annual accruals, quarterly accruals have lower levels of persistence than quarterly net operating cash flows, a phenomenon that underlies the accruals anomaly for annual data. Specifically, observing quarterly accruals after the
SEC filings are available and sorting firms into deciles to obtain firms with extreme quarterly accruals, can provide investors significant future abnormal returns. The study shows that firms with extremely low accruals in the current quarter have positive abnormal returns over the period from two days after the SEC filing through the day after the subsequent quarterly earnings announcement. Conversely, over the same period, the study shows that firms with extremely high accruals in the current quarter have negative future abnormal returns. Abnormal returns to these groups are also observed for holding periods from two days after the SEC filings through the subsequent four quarterly preliminary earnings announcements. To explain these results, we show that consistent with previous findings about annual accruals, quarterly accruals also tend to have lower levels of persistence than net operating cash flows with respect to future quarterly earnings. For example, firms with extremely high levels of accruals in quarter t tend to have lower levels of future quarterly earnings than firms with the same levels of current earnings but higher current net operating cash flows.
The results of this study have implications for analysts and professional investors.
Analysts should examine carefully the quarterly accruals of firms in the extreme accruals deciles to determine whether these accruals are likely to indicate less persistence of future quarterly earnings. This study will enable financial analysts to identify those extreme
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cases where a forecast revision may be warranted. Professional investors can also use the results of this analysis to identify firms that are more likely to have future changes in stock returns due to expected earnings changes.
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The purpose of this appendix is to explain intuitively why net operating cash flows are more persistent than accruals, which tend to reverse more often because of the nature of accounting systems. The appendix uses two identical firms which are subject to the same exogenous economic forces, but where managerial decisions affect inventory levels in the first case and both inventories and accounts receivable in the second case. The two firms begin operations in quarter 1 with $2000 in cash, with the same cost structure of $1000 fixed production costs per quarter and $2 per unit of variable costs. Each unit is sold for $5, and expected sales in the first quarter are 1,000 units. The firms maintain ending inventory (in units) which is 25% of the subsequent quarter’s unit sales. The firms also incur other expenses, which are assumed to be 20% of sales. All expenses are paid immediately. In the first case, the two firms differ in their expectations; A assumes sales growth of 10% per quarter and B assumes wrongly that sales will grow at 50% per quarter. After the first quarter, B revises its estimates to also have growth of 10% per quarter. The nature of the (FIFO) cost system is such that the cost of beginning inventory plus current production costs are used to determine the cost per unit during the quarter, and that cost per unit is used to calculate the cost of ending inventory. Exhibit A-1 shows earnings, cash flows and balance sheet balances for the two firms.
(Insert Exhibit A-1 about here)
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The exhibit shows that required ending inventory in the first quarter is larger for B than for A (375 and 275 units, respectively), simply because forecasted sales in quarter 2 are higher for B than for A. Because there are more units produced in quarter 1 by firm A than B, the cost per unit of A is higher than that of B ($2.78 compared to $2.73), which means that A will have higher cost of sales than B. Also, B has higher inventory levels
(in units and total cost) at the end of the first quarter than A. The situation is reversed in
Quarter 1, when B works down its excess inventory, resulting in higher unit cost ($2.97 compared to 2.89 of A), higher cost of sales and lower profits. Earnings are affected in quarter 3 as well, simply because of the lingering effects of ending inventory costs from quarter 2.
As the exhibit shows, B has higher earnings in quarter 1 than A, simply due to its decision to hold excess inventories at the end of quarter 1. When B works down the excess inventories in quarter 2, its earnings in quarters 2 and 3 are lower than A, simply because B has higher accruals (inventories on the balance sheet) than A in the first two quarters. The income statement does not penalize B in quarter 1 for building excess inventories, treating them as an asset. Note that the net operating cash flow of B fully reflects the inventory build-up in quarter 1 and liquidation in quarter 2, with lower net operating cash flow in quarter 1 for B than for A and a complete reversal in quarter 2.
Thus, to the extent that there are inventory shocks (excess inventories), the accounting system is likely to cause accruals reversals, whereas the net operating cash flows will portray a more accurate picture of the firm’s likely future earnings.
Assume now that the manager of firm B realizes the excessive inventories buildup, and decides to manage earnings through “channel stuffing”, i.e., promising customers
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that they can take delivery in quarter 2 but not pay until quarter 3. Firm B will now not only have higher inventory accruals, but also higher accounts receivable accruals in quarter 2. For simplicity, we assume that customers who take delivery in quarter 2 reduce their quarter 3 orders by exactly the same amount. Exhibit A-2 shows the effects on the two firms’ financial statements.
(Insert Exhibit A-2 about here)
As the exhibit shows, earnings in quarter 2 are substantially higher for firm B than for A, simply because of booking higher sales, although its cash flows are actually lower since it incurs additional expenses (assumed 20% of sales). When the reversal occurs in quarter 3, i.e., when B’s clients order less goods to work down their own inventories, B’s earnings fall significantly as compared to A.
The above two examples show how the accounting system is likely to “cover” managerial build-up of inventories or receivables, resulting in higher earnings during the period of accruals build-up, which are subsequently reversed when excess inventories or receivables are liquidated. The accounting system can also be used by managers to manage earnings through more favorable accounting methods and estimates, but those are also likely to reverse in the future when new information surfaces (e.g., booking current bad debt expense that is too low). In contrast, the net operating cash flow is likely to provide a better signal of future earnings in these cases. Whether accruals will reverse in the future depends on the extent of managerial build-up of excessive accounting assets and on the extent of managerial actions (economic and accounting) to manage current earnings. Ultimately, whether quarterly accruals are less persistent than net operating
22

cash flows and whether this can be exploited in obtaining abnormal returns is an empirical question.
23

Quarter
Forecasted sales in units
Actual sales
Income Statement
Sales
Cost of Sales
Other expenses
Earnings
Cash Flows
Collections
Production costs
Other expenses
Net operating cash flow
Balances
Ending inventory
Cash
Production data and costs
Inventory -end in units
Actual sales in units
Total needed
Subtract beginning inventory
Production in units
Cost of production
Cost of production per unit
Cost of ending inventory
Cost of sales
1 2 3
A
1000
1000
B
1000
1000
A
1100
1100
B
1500
1100
A
1210
1210
B
1210
1210
$ 5,000.00 $ 5,000.00 $ 5,500.00 $ 5,500.00 $ 6,050.00 $ 6,050.00
$ (2,784.31) $ (2,727.27) $ (3,147.39) $ (3,178.32) $ (3,420.00) $ (3,446.11)
$ (1,000.00) $ (1,000.00) $ (1,100.00) $ (1,100.00) $ (1,210.00) $ (1,210.00)
$ 1,215.69 $ 1,272.73 $ 1,252.61 $ 1,221.68 $ 1,420.00 $ 1,393.89
$ 5,000.00 $ 5,000.00 $ 5,500.00 $ 5,500.00 $ 6,050.00 $ 6,050.00
$ (3,550.0) $ (3,750.0) $ (3,255.0) $ (3,055.0) $ (3,480.5) $ (3,480.5)
$ (1,000)
$ 450.00
$ (1,000)
$ 250.00
$ (1,100)
$ 1,145.00
$ (1,100)
$ 1,345.00
$ (1,210)
$ 1,359.50
$ (1,210)
$ 1,359.50
$ 765.69 $ 1,022.73 $ 873.29 $ 899.40 $ 933.79 $ 933.79
$ 2,450.00 $ 2,250.00 $ 3,595.00 $ 3,595.00 $ 4,954.50 $ 4,954.50
275
1000
1275
0
1275
375
1000
1375
0
1375
302.5
1100
1402.5
-275
1127.5
302.5
1100
1402.5
-375
1027.5
332.75
1210
1542.75
-302.5
1240.25
332.75
1210
1542.75
-302.5
1240.25
$ 3,550.00 $ 3,750.00 $ 3,255.00 $ 3,055.00 $ 3,480.50 $ 3,480.50
$ 2.78 $ 2.73 $ 2.89 $ 2.97 $ 2.81 $ 2.81
$ 765.69 $ 1,022.73 $ 873.29 $ 899.40 $ 933.79 $ 933.79
$ 2,784.31 $ 2,727.27 $ 3,147.39 $ 3,178.32 $ 3,420.00 $ 3,446.11
A
1331
1331
4
B
1331
1331
24

Quarter
Forecasted sales in units
Actual sales
Income Statement
Sales
Cost of Sales
Other expenses
Earnings
Cash Flows
Collections
Production costs
Other expenses
Net operating cash flow
Balances
Ending inventory
Cash
Accounts receivable
Production data and costs
Inventory -end in units
Actual sales in units
Total needed
Subtract beginning inventory
Production in units
Cost of production
Cost of production per unit
Cost of ending inventory
Cost of sales
1 2 3
A
1000
1000
B
1000
1000
A
1100
1100
B
1500
1500
A
1210
1210
B
1210
810
$ 5,000.00 $ 5,000.00 $ 5,500.00 $ 7,500.00 $ 6,050.00 $ 4,050.00
$ (2,784.31) $ (2,727.27) $ (3,147.39) $ (4,060.82) $ (3,420.00) $ (2,435.90)
$ (1,000.00) $ (1,000.00) $ (1,100.00) $ (1,500.00) $ (1,210.00) $ (810.00)
$ 1,215.69 $ 1,272.73 $ 1,252.61 $ 1,939.18 $ 1,420.00 $ 804.10
$ 5,000.00 $ 5,000.00 $ 5,500.00 $ 5,500.00 $ 6,050.00 $ 6,050.00
$ (3,550.00) $ (3,750.00) $ (3,255.00) $ (3,855.00) $ (3,480.50) $ (2,680.50)
$ (1,000.00) $ (1,000.00) $ (1,100.00) $ (1,500.00) $ (1,210.00) $ (810.00)
$ 450.00 $ 250.00 $ 1,145.00 $ 145.00 $ 1,359.50 $ 2,559.50
$ 765.69 $ 1,022.73 $ 873.29 $ 816.91 $ 933.79 $ 1,061.51
$ 2,450.00 $ 2,250.00 $ 3,595.00 $ 2,395.00 $ 4,954.50 $ 4,954.50
$2,000
275
1000
1275
0
375
1000
1375
0
302.5
1100
1402.5
-275
302.5
1500
1802.5
-375
332.75
1210
1542.75
-302.5
332.75
810
1142.75
-302.5
1275 1375 1127.5 1427.5 1240.25 840.25
$ 3,550.00 $ 3,750.00 $ 3,255.00 $ 3,855.00 $ 3,480.50 $ 2,680.50
$ 2.78 $ 2.73 $ 2.89 $ 2.70 $ 2.81 $ 3.19
$ 765.69 $ 1,022.73 $ 873.29 $ 816.91 $ 933.79 $ 1,061.51
$ 2,784.31 $ 2,727.27 $ 3,147.39 $ 4,060.82 $ 3,420.00 $ 2,435.90
A
1331
4
B
1331
25

Barth, Mary and Amy Hutton. 2003. Analyst earnings forecast revisions and the pricing of accruals. Working Paper. Dartmouth College and Stanford University.
Beneish, M. D., and M. E. Vargus. 2002. Insider trading, earnings quality and accrual mispricing. The Accounting Review 77 (October): 755-791.
Collins, D. W., G. Gong and P. Hribar. 2003. Investor sophistication and the mispricing of accruals. Review of Accounting Studies 8: 251-276.
Collins, D. W. and P. Hribar. 2000. “Earnings-Based and Accrual-Based Market
Anomalies: One Effect of Two?”
Journal of Accounting and Economics v 29 (1):
101-123.
DeFond, M. L. and C. W. Park. 2001. The Reversal of Abnormal Accruals and the
Market Valuation of Earnings Surprises, The Accounting Review, 76:3, July: 375-404.
Desai, H., S. Rajgopal and M. Venkatachalam. 2004. Value-Glamour and Accruals
Mispricing: One Anomaly or Two? The Accounting Review, (April).
Fairfield, P., J.S. Whisenant and T.L. Yohn. 2003. Accrued earnings and growth:
Implications for future profitability and market mispricing. The Accounting
Review 78 (1, January): 353-371.
Fama, E. F. and J. MacBeth. 1973. “Risk, Return, and Equilibrium: Empirical Tests.”
Journal of Political Economy 81: 607-636.
Kraft, A., A. Leone and C. Wasley. 2004. “Research Design Issues and Related Inference
Problems Underlying Tests of the Market Pricing of Accounting Information”,
Working paper. University of Rochester.
Lev, Baruch, and Doron Nissim. 2004. The persistence of the accruals anomaly. Working paper, NYU and Columbia U.
Mashruwala, C., S. Rajgopal and T. Shevlin. 2004. Why is the accrual anomaly not arbitraged away? Working paper. University of Washington.
Richardson, S., R. Sloan, M. Soliman and I. Tuna. 2004. Accrual reliability, earnings persistence and stock prices. Working paper. University of Michigan.
Sloan, R. 1996. “Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about Future Earnings?”
The Accounting Review 71, 289-315.
Thomas, J. and H. Zhang. 2002. Inventory changes and future returns. Review of
Accounting Studies , 7: 163-187.
26

Xie, Hong. 2001. The mispricing of abnormal accruals. The Accounting Review 76 (July):
357-373.
27

Variable N
Mean
Standard
Deviation 10% 25% Median 75%
Earnings at t
Net Operating Cash
Flow at t
155985 -0.0007 0.0668 -0.0460 0.0002 0.0103 0.0222
155985 0.0125 0.0645 -0.0478 -0.0048 0.0177 0.0395
Accruals at t
BHR -Filing at t
Through
Preliminary
Earnings at t+1
BHR -Filing at t
Through
Preliminary
Earnings at t+2
BHR -Filing at t
Through
Preliminary
Earnings at t+3
BHR -Filing at t
Through
Preliminary
Earnings at t+4
155985
155985
150067
144683
141803
-0.0133
-0.0020
-0.0066
-0.0106
-0.0085
0.0635 -0.0580
0.2105 -0.2414
0.3213 -0.3760
0.4147 -0.4757
0.5108 -0.5557
-0.0296
-0.1124
-0.1932
-0.2601
-0.3212
-0.0102
-0.0076
-0.0262
-0.0473
-0.0666
0.0069
0.0955
0.1424
0.1704
0.2004
Notes:
1.
The table is based on all sample observations (firm-quarters) where earnings (Compustat Quarterly
Data Item 8) and net operating cash flows (Compustat Quarterly Data Item 108) are available for the current quarter and the market value of equity at quarter-end is at least $50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted.
2.
Earnings (quarterly) are scaled by average total assets during the quarter and winsorized to fall in the range [-1,+1].
3.
Net Operating Cash Flows (quarterly) are scaled by average total assets during the quarter and winsorized to fall in the range [-1,+1].
4.
Accruals are defined as quarterly earnings minus quarterly net operating cash flows, scaled by average total assets over the quarter and winsorized to fall in the range [-1,+1].
5.
BHR is the abnormal buy and hold return on a stock, cumulated from two days after the SEC filing date for quarter t through one day after the preliminary earnings announcement for quarter t+i, i=1,,4. If the preliminary earnings announcement date is missing, it is replaced by 90, 180,
270, and 360 days after SEC filing. The abnormal return is the raw return over the period minus the return on a benchmark portfolio with the same size-B/M portfolio (six portfolios), as provided by Professor French. The BHR uses delisting returns where applicable.
90%
0.0369
0.0660
0.0339
0.2289
0.3566
0.4558
0.5494
28

N for t+1
BHR -
Filing at t
Through
Preliminary
Earnings at t+1
BHR -
Filing at t
Through
Preliminary
Earnings at t+2
BHR -
Filing at t
Through
Preliminary
Earnings at t+3
BHR -
Filing at t
Through
Preliminary
Earnings at t+4 N for t+4
Accrual
Decile
0
1
6854 0.022 0.033 0.044 0.053 6290
10046 0.016 0.031 0.038 0.047 9176
2
15513 0.005 0.006 0.003 0.006 14089
3
4
15614 0.004 0.005 0.007 0.009 14213
16069 0.001 0.000 -0.004 0.002 14612
5
16095 0.000 0.000 -0.003 -0.001 14663
6
7
15950 -0.003 -0.008 -0.010 -0.008 14527
15841 -0.006 -0.015 -0.022 -0.020 14428
8
9
12776 -0.006 -0.014 -0.018 -0.020 11711
12254 -0.012 -0.028 -0.040 -0.046 11200
All 137012 0.001 -0.001 -0.004 -0.001 124909
Low-High
Accruals
0.034 0.061 0.084 0.099
Notes:
1.
The table is based on all sample observations (firm-quarters) where earnings (Compustat Quarterly
Data Item 8) and net operating cash flows (Compustat Quarterly Data Item 108) are available for the current quarter and the market value of equity at quarter-end is at least $50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted. The sample is further restricted to observations with both positive earnings and cash flows in the bottom two accrual deciles and positive earnings in the top two accrual deciles.
2.
BHR is the abnormal buy and hold return on a stock, cumulated from two days after the SEC filing date for quarter t through one day after the preliminary earnings announcement for quarter t+i, i=1,,4. If the preliminary earnings announcement date is missing, it is replaced by 90, 180,
270, and 360 days after SEC filing. The abnormal return is the raw return over the period minus the return on a benchmark portfolio with the same size-B/M portfolio (six portfolios), as provided by Professor French. The BHR uses delisting returns where applicable.
3.
Accruals are defined as quarterly earnings minus quarterly net operating cash flows, scaled by average total assets over the quarter. Firm-observations are sorted each quarter into deciles according to the scaled accruals.
4.
Low-High Accruals reports the returns obtained on a hedge portfolio that holds long (short) positions in firms falling into the lowest (highest) accrual decile.
29

Independent
Variable
Intercept
Significance
Earnings
Significance
Accruals
Significance
Net Operating
Cash Flows
Significance
Dependent Variable
Earnings at t+1
-0.0017
0.0001
0.7911
0.0001
-0.0025
0.0001
0.7390
0.0001
0.8143
0.0001
Earnings at t+2
-0.0022
0.0001
0.7786
0.0001
-0.0032
0.0001
0.7000
0.0001
0.8066
0.0001
Earnings at t+3
-0.0026
0.0001
0.7822
0.0001
-0.0039
0.0001
0.6836
0.0001
0.8126
0.0001
Earnings at t+4
-0.0030
0.0001
0.8324
0.0001
N
R
2
136014
0.3303 0.3382
133428
0.2765 0.2861
128962
0.2473 0.2584
124456
0.2562
Significance 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001
Notes:
1.
The table is based on all sample observations (firm-quarters) where earnings (Compustat Quarterly
Data Item 8) and net operating cash flows (Compustat Quarterly Data Item 108) are available for the current quarter and the market value of equity at quarter-end is at least $50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted. The sample is further restricted to observations with both positive earnings and cash flows in the bottom two accrual deciles and positive earnings in the top two accrual deciles.
2.
Earnings (quarterly) are scaled by average total assets during the quarter and winsorized to fall in the range [-1,+1].
3.
Net Operating Cash Flows (quarterly) are scaled by average total assets during the quarter and winsorized to fall in the range [-1,+1].
4.
Accruals are defined as quarterly earnings minus quarterly net operating cash flows, scaled by average total assets over the quarter and winsorized to fall in the range [-1,+1].
5.
Untabulated tests that the slope coefficient on net operating cash flows is statistically equal to the coefficient on accruals are rejected at the 0.0001 significance level for all four future quarterly earnings.
-0.0044
0.0001
0.7328
0.0001
0.8704
0.0001
0.2961
0.0001
30

Independent
Variable
Dependent Variable
Accruals at t+1
Accruals at t+2
Accrual at t+3
Accruals at t+4
Intercept
Significance
Accrual at Quarter 0
Significance
-0.0116
0.0001
-0.0254
0.0001
-0.0121
0.0001
0.0247
0.0001
-0.0127
0.0001
0.0009
0.8312
-0.0116
0.0001
0.4193
0.0001
N
135499 131947 127451 122908
R-Square
0.0004 0.0003 0.0000 0.0744
Significance
0.0001 0.0001 0.0001 0.0001
Notes:
1.
The table is based on all sample observations (firm-quarters) where earnings (Compustat Quarterly
Data Item 8) and net operating cash flows (Compustat Quarterly Data Item 108) are available for the current quarter and the market value of equity at quarter-end is at least $50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted. The sample is further restricted to observations with both positive earnings and cash flows in the bottom two accrual deciles and positive earnings in the top two accrual deciles.
2.
Accruals are defined as quarterly earnings minus quarterly net operating cash flows, scaled by average total assets over the quarter.
31

Independent
Variable
BHR-Filing at t
Through Preliminary
Earnings at t+1
Dependent Variable
BHR-Filing at t
Through Preliminary
Earnings at t+2
BHR-Filing at t
Through Preliminary
Earnings at t+3
BHR-Filing at t
Through Preliminary
Earnings at t+4
Intercept -0.0016 -0.0035 -0.0068 -0.0105 -0.0114 -0.0161 -0.0091 -0.0144
0.0001 Significance
Earnings
Significance
Net Operating
Cash Flows
Significance
Accruals
Significance
N
R 2
0.0046
0.2068
0.0001
0.0001
0.2522
0.0001
0.0445
0.0098
0.0034
0.0001
0.4528
0.0001
0.0001
0.5379
0.0001
0.1433
0.0001
0.0064
0.0001
0.6349
0.0001
0.0001
0.7363
0.0001
0.2333
0.0001
0.0068
0.0001
0.6466
0.0001
137012
0.0016
131976
0.0032
127365
0.0036
124909
0.0025
Significance 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001
Notes:
1.
The table is based on all sample observations (firm-quarters) where earnings (Compustat Quarterly
Data Item 8) and net operating cash flows (Compustat Quarterly Data Item 108) are available for the current quarter and the market value of equity at quarter-end is at least $50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted. The sample is further restricted to observations with both positive earnings and cash flows in the bottom two accrual deciles and positive earnings in the top two accrual deciles.
2.
BHR is the abnormal buy and hold return on a stock, cumulated from two days after the SEC filing date for quarter t through one day after the preliminary earnings announcement for quarter t+i, i=1,,4. If the preliminary earnings announcement date is missing, it is replaced by 90, 180,
270, and 360 days after SEC filing. The abnormal return is the raw return over the period minus the return on a benchmark portfolio with the same size-B/M portfolio (six portfolios), as provided by Professor French. The BHR uses delisting returns where applicable.
3.
Earnings (quarterly) are scaled by average total assets during the quarter and winsorized to fall in the range [-1,+1].
4.
Net Operating Cash Flows (quarterly) are scaled by average total assets during the quarter and winsorized to fall in the range [-1,+1].
5.
Accruals are defined as quarterly earnings minus quarterly net operating cash flows, scaled by average total assets over the quarter and winsorized to fall in the range [-1,+1].
6.
Untabulated tests that the slope coefficient on net operating cash flows is statistically equal to the coefficient on accruals are rejected at the 0.0001 significance level for all four BHR holding periods.
0.7659
0.0001
0.1823
0.0001
0.0052
0.0001
32

Independent
Variable
Dependent Variable
BHR-Filing BHR-Filing BHR-Filing BHR-Filing at t
Through at t
Through at t
Through at t
Through
Preliminary Preliminary Preliminary Preliminary
Earnings at t+1
Earnings at Earnings at Earnings at t+2 t+3 t+4
Intercept
Significance
Accrual Decile Rank
Significance
0.0017
0.0022
-0.0271
0.0001
0.0002
0.8217
-0.0519
0.0001
-0.0018
0.1100
-0.0672
0.0001
0.0011
0.4536
-0.0782
0.0001
N
137012 131976 127366 124909
R-Square
0.0015 0.0024 0.0024 0.0021
Significance
0.0001 0.0001 0.0001 0.0001
Notes:
1.
The table is based on all sample observations (firm-quarters) where earnings (Compustat Quarterly
Data Item 8) and net operating cash flows (Compustat Quarterly Data Item 108) are available for the current quarter and the market value of equity at quarter-end is at least $50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted. The sample is further restricted to observations with both positive earnings and cash flows in the bottom two accrual deciles and positive earnings in the top two accrual deciles.
2.
BHR is the abnormal buy and hold return on a stock, cumulated from two days after the SEC filing date for quarter t through one day after the preliminary earnings announcement for quarter t+i, i=1,,4. If the preliminary earnings announcement date is missing, it is replaced by 90, 180,
270, and 360 days after SEC filing. The abnormal return is the raw return over the period minus the return on a benchmark portfolio with the same size-B/M portfolio (six portfolios), as provided by Professor French. The BHR uses delisting returns where applicable.
3.
Accruals are defined as quarterly earnings minus quarterly net operating cash flows, scaled by average total assets over the quarter. Firms are sorted into accrual deciles each quarter, are assigned the decile rank divided by 9 minus 0.5. Thus, accrual decile rank ranges between -0.5 to
0.5. The intercept measures the average BHR in the sample, and the slope coefficient the difference in BHR between the highest and lowest accrual deciles.
33

Portfolio
Average
Number of
Securities
Per
Quarter
Mean
Return t Value Significance
Number of
Quarters with
Positive
Returns
Number of
Quarters with
Returns
>2%
BHR-Filing at t
Through
Preliminary
Earnings at t+1
BHR-Filing at t
Through
Long
Short
Hedge
Long
Short
124
222
346
122
218
0.0262
0.0098
0.0359
0.0375
0.0249
7.02
2.89
7.78
6.39
4.34
0.0001
0.0056
0.0001
0.0001
0.0001
41
36
48
46
38
Preliminary
Earnings at t+2
BHR-Filing at t
Hedge
Long
340
120
0.0623
0.0500
9.33
5.98
0.0001
0.0001
46
44
Through
Preliminary
Earnings at t+3
BHR-Filing
Short
Hedge
214
334
0.0339
0.0839
4.08
9.00
0.0002
0.0001
42
44 at t
Through
Preliminary
Earnings at t+4
Long
Short
Hedge
118 0.0616
211 0.0382
329 0.0998
5.52
3.77
9.36
0.0001
0.0004
0.0001
40
37
47
Notes:
1.
The table reports the statistics about portfolios of long positions in the bottom accrual decile
(Long), short positions in the top accrual decile (Short) and the sum of the two (Hedge) across the
53 quarters between the first quarter of 1991 and the first quarter of 2004.
2.
The underlying portfolios are based on all sample observations (firm-quarters) where earnings
(Compustat Quarterly Data Item 8) and net operating cash flows (Compustat Quarterly Data Item
108) are available for the current quarter and the market value of equity at quarter-end is at least
$50 million. In addition, total assets (Compustat Quarterly Data Item 44) are available for the current and prior quarter. Extreme Buy and Hold abnormal Returns (BHR) observations (top and bottom 0.5%) are deleted. The sample is further restricted to observations with both positive earnings and cash flows in the bottom two accrual deciles and positive earnings in the top two accrual deciles.
3.
BHR is the abnormal buy and hold return on a stock, cumulated from two days after the SEC filing date for quarter t through one day after the preliminary earnings announcement for quarter t+i, i=1,,4. If the preliminary earnings announcement date is missing, it is replaced by 90, 180,
270, and 360 days after SEC filing. The abnormal return is the raw return over the period minus the return on a benchmark portfolio with the same size-B/M portfolio (six portfolios), as provided by Professor French. The BHR uses delisting returns where applicable.
4.
t Value and significance are for a test that the time series mean return across all 53 quarters is statistically different from zero, and its associated significance level.
32
19
37
33
28
43
37
31
41
39
31
42
34

Quarterly Return on Long Portfolio
0.12
0.1
0.08
0.06
0.04
0.02
0
19
90
19
91
19
92
19
93
19
93
19
94
19
95
19
96
19
96
19
97
19
98
19
99
19
99
20
00
20
01
20
02
20
02
20
03
-0.04
Quarterly Return on Short Position
0.1
0.08
0.06
0.04
0.02
0
19
90
19
91
19
92
19
93
19
93
19
94
19
95
19
96
19
96
19
97
19
98
19
99
19
99
20
00
20
01
20
02
20
02
20
03
-0.04
-0.06
35

Quarterly Return on Hedge Portfolio
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
19
90
19
91
19
92
19
93
19
93
19
94
19
95
19
96
19
96
19
97
19
98
19
99
19
99
20
00
20
01
20
02
20
02
20
03
-0.04
-0.06
The figure reports quarter by quarter buy and hold abnormal returns on the accruals strategy of holding long positions in the lowest accruals decile, short positions in the top accruals decile and a hedge portfolio that combines both. The BHR are for the period from two days after the SEC filing through one day after the following quarter’s preliminary earnings announcement or 90 days if unavailable.
36

500
400
300
200
Cumulative Reurns
700
600
100
0
19
90
19
91
19
92
19
92
19
93
19
94
19
95
19
95
19
96
19
97
19
98
19
98
19
99
20
00
20
01
20
01
20
02
20
03
Long Short Hedge
The figure reports cumulative buy and hold abnormal returns on the accruals strategy of holding long positions in the lowest accruals decile, short positions in the top accruals decile and a hedge portfolio that combines both. The BHR are for the period from two days after the SEC filing through one day after the following quarter’s preliminary earnings announcement or 90 days if unavailable.
37