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FIGURE 1
Mean return on net operating assets (RNOA) for high and low Sscore groups over five years before and after the Sscoring year, Year 0.
The Sscore groups are based on a ranking of firms each year on Sscores, within RNOA groups. The high Sscore group is the top third of firms in that ranking and the low Sscore group is the bottom third of firms in the ranking on Sscores. The RNOA values reported in the figure are the means of 24 yearly median RNOAs computed over the years 1979 to 2002.
FIGURE 2
Panel A: Differences in Mean SizeAdjusted Returns between High and Low E/P Residual Portfolios, for the Year Following the E/P residual estimation Year, 1979 2002
Panel B: Differences in Mean SizeAdjusted Returns between High and Low EMBED Equation.3 Portfolios, for the Year Following the EMBED Equation.3 Estimation Year, 1979 2002
Panel C: Differences in Mean SizeAdjusted Returns between High and Low Sscore Portfolios, for the Year Following the Sscoring Year, 1979  2002
Endnotes
PAGE
PAGE 1
For example, Brooks and Buckmaster (1976) show that extreme current earnings changes are not sustainable. Freeman, Ohlson and Penman (1982) show that, by adding just one line item book value to current earnings, future earnings changes are probabilistically predictable. Ou (1990) and Ou and Penman (1989) involve further financial statement ratios in forecasting earnings changes. Lev and Thiagarajan (1993) and Abarbanell and Bushee (1997) consider fundamental measures popular with analysts. Lipe (1986) and Fairfield Sweeney and Yohn (1996) show that lineitem analysis of the income statement improves forecasts. Sloan (1996) shows that accrual earnings have a different persistence than cash earnings, and Richardson, Sloan Soliman and Tuna (2005) extend that analysis to various components of accruals. Fairfield and Yohn (2001) report that a Du Pont decomposition of operating profitability improves forecasts of changes in profitability in the future, while Fairfield, Whisenant and Yohn (2003) apply financial statement measures of growth to the assessment of persistence. Penman and Zhang (2002) design metrics to identify temporary earnings that result from the creation and release of hidden reserves from applying conservative accounting.
Figure 2 in Penman (1996, p. 247) is helpful in understanding the effect of transitory current earnings and expected future earnings growth on the P/E ratio.
3 Ohlson and JuettnerNauroth (2005) provide an alternative formulation of the (forward) P/E based on expected abnormal earnings growth, that is, cumdividend earnings growth in excess of growth at a rate equal to the required return. Abnormal earnings growth is equal to the change in residual income (under cleansurplus accounting), so the analysis here is consistent with the Ohlson and JuettnerNauroth model.
4 If residual income is expected to be the same as current residual income in all future periods, the premium over book value is calculated by capitalizing current residual income:
Enterprise EMBED Equation.3
= EMBED Equation.3 ,
by the clean surplus relation (6). It follows that
Enterprise EMBED Equation.3 ,
and thus the enterprise P/E ratio is
EMBED Equation.3 .
Free cash flow in the current year, FCF0 is in effect the cash dividend from the enterprise (to be paid to shareholders and debtholders), so this P/E ratio is effectively a cumdividend P/E ratio.
5 Suppose RNOAt = RNOA0 for all t>0. When NOA0 EMBED Equation.3 0 and/or g EMBED Equation.3 1 the P/E ratio will differ from the normal level of (((1)1. The difference depends on how future residual incomes are expected to differ from the current residual income. More specifically,
EMBED Equation.3
Substituting OI0 = RNOA0*NOA1 into the above equation and rearranging terms,
EMBED Equation.3 .
6 Special items include adjustments applicable to prior years, nonrecurring items, gains and losses on assets sales, transfers of reserves provided in prior years, and writedowns of assets, among other items. So, to the extent that firms and COMPUSTAT identify these items, they are excluded from the income whose sustainability we are forecasting.
7Fama and French estimate longrun profitability using nonaccounting information, including stock price information. We wish to confine ourselves to accounting information (and, with a model of the P/E ratio on mind, certainly do not want to include price information!). Fama and French also estimate a model with longrun profitability set to zero, and it is this benchmark that we adopt here. Later we allow for differences in longrun profitability that are due to accounting factors.
8 RNOA0 = (ATO0 PM1) + (PM0 ATO1) + (ATO0 PM0). See Fairfield and Yohn (2001).
9By using (average) current net operating assets in the denominator of the asset turnover, the Fairfield and Yohn (2001) measure of ATO0 incorporates NOA0 whose separate effect we wish to identify (in Step 2) and which we are attempting to normalize (in Step 1). That is, their ATO0 measures the change in sales relative to the change in current NOA whereas our ATO measures the change in sales relative to prior change in NOA, as a control for evaluating NOA0. Further, their ATO0 measure is normalized by prior period s profit margin, so does not have the interpretation of growth in sales relative to (prior) growth in NOA for the purpose at hand here. Fairfield and Yohn include NOA0 in their analysis, but as a control for growth for their examination of turnovers and margins rather than the primary focus that our characterization of sustainable earnings and equation (6) directs for our endeavor.
10 Sales and operating income do not grow proportionally when there are fixedcost components in operating expenses, and thus PM is expected. Nor do sales and net operating assets grow proportionally when assets are not variable with sales, and thus ATO is expected. Ideally one would incorporate this nonproportionality, but financial statements do not disclosure fixed and variable components. However, PM and ATO tend to move together: with fixed components, an increase in sales increases both the PM and the ATO. Accordingly, the mean correlation between PM and ATO in our sample is 0.22. Questions of sustainability arise when the two measures move in the opposite direction. If, for example, PM increases while ATO decreases, the quality of the operating income is called into question: why are expenses declining per dollar of sales when sales are declining? In an extension, we included dummy variables for the interaction and found that conditions of increasing PM with increasing ATO and decreasing PM with increasing ATO both added explanation to the model. See the working paper version of this paper at
HYPERLINK "http://papers.ssrn.com/sol3/papers.cfm?abstract_id=318967" http://papers.ssrn.com/sol3/papers.cfm?abstract_id=318967.
11In an extension, we included dummy variables for cases where asset turnover increases but net operating assets decline and where asset turnover declines but net operating assets increase. Growth in sales with a decline in the net operating assets that maintain the sales might indicate temporary sales growth, but may also indicate excessive expenses booked to the income statement, both explanations implying a positive coefficient. The estimated coefficient was indeed positive. Correspondingly, the estimated coefficient for the case of decreasing sales with increasing net operating assets is negative; this case implies lower future profitability. Results are available in the working paper. Hirshleifer, Hou, Teoh, and Zhang (2004) report that the level of net operating assets predicts future earnings and returns. However, their scaled level variable, NOAt/TAt1 is a growth variable, not the level of NOAt at all, and the same as GNOA here but for the omission of operating liabilities from TAt1.
12 For years prior to 1987 (when firms reported funds from operations rather than cash flow from operations), we calculated accruals as funds from operations adjusted for changes in operating working capital.
13 The Cscore is the estimated reserves, ER, created by applying conservative accounting to R&D investments, advertising, and inventory, relative to net operating assets:
EMBED Equation.3 .
Estimated reserves are the difference between the NOA that would have been booked had conservative accounting not been applied and actual NOA booked, that is, missing NOA that results from conservative accounting. See Penman and Zhang (2002) for details of the estimation. The Qscore is the change is C scores, measuring how balance sheets and earnings are affected by changes in investment growth. Penman and Zhang (2002) develop two Q scores, QA and QB. We use QA in this paper.
14 In an enhancement, we built in a recursive feature, adding RNOA predicted for year 0 ( EMBED Equation.3 ) and the S score for year 0 to the OLS and LOGIT versions of the model, respectively. Both are predicted at the end of year 1. This adds the estimate of whether RNOA in period 1 will be sustained in period 0 as additional information about whether RNOA in period 0 will be sustained in period +1. As actual RNOA0 is already in the OLS regression, the addition of EMBED Equation.3 compares actual with predicted values. The extent of the surprise in this difference may have information for the further sustainability of earnings. Estimated coefficients on EMBED Equation.3 and the S score indicate negative autocorrelation: if the change in profitability is higher (lower) than predicted, it is likely to be lower (higher) subsequently.
15 We prepared an analysis similar to that in Figure 1 for firms in each RNOA0 decile in each year. The S score differentiated RNOA1 for all deciles. For low RNOA0 firms (in the bottom two deciles with mean RNOA0 of 64.9% and 0.85%, respectively), RNOA declined for both high and low S groups prior to year 0, and increased for both groups in year +1; yet the S score forecasted differences in that increase. For high RNOA0 (in the top 3 deciles with mean RNOA0 of 17.4%, 21.9%, and 40.0%, respectively), RNOA increased for both high and low S groups prior to year 0, but increased further in year +1 for high S firms while decreasing for low S firms.
16 Stocks earnings move together because of economywide factors. In years of transitorily low earnings, the marketwide P/E will tend to be high, but stocks with high betas will tend to have even higher P/E ratios because their earnings are most sensitive to economywide events. Conversely, in years of transitorily high earnings, high beta stocks will have even lower P/E ratios than most. Therefore we expect a positive correlation (between beta and P/E) in high P/E years and a negative correlation in low years (Beaver and Morse 1978, p. 70 and appendix).
17 The enterprise P/E ratio is calculated as (market value of common equity0 + net financial obligations0 + free cash flow0)/operating income0. Net financial obligations are financing debt (including preferred stock) minus financial assets, all measured at book value as an approximation of market value. Free cash flow is operating income minus the change in net operating assets, by (3) Free cash flow (FCF) added to the numerator in the calculation is calculated as FCF0(1 r)/2), where r is the required return for operations, set at 10%. This calculation adjusts for free cash flow being generated throughout the period rather than at the end of the period.
18 The mean sizeadjusted return over all portfolios in Table 5 is positive. This is due, partly, to portfolio returns being equally weighted average returns whereas CRSP sizedecile returns are value weighted. Also, our sample covers only NYSE, AMEX, and NASDAQ firms, whereas CRSP cover smaller OTC firms also. (Restricting the sample to these three exchanges increases the mean sizeadjusted annual return from 0.06% to 5.89%.) Our sample may not be representative of the CRSP universe because of requirements for certain accounting items to be available.
19 As firms in a particular calendar year may not have the same fiscal year end, mean returns from which tstatistics were calculated involve some returns that are overlapping in calendar time, and may thus not be independent. However, similar results were found when we included only December 31 fiscal year end firms in the analysis: the mean difference between portfolio 10 and portfolio 1 sizeadjusted returns was 10.70%, with a tstatistic of 3.13. The ranking only on December 31 firms also removes any peeking ahead bias that may arise from ranking all firms as if they had a common fiscal year end. While firms are required to report to the SEC within three months of fiscal year end, some do not. We repeated the analysis taking positions four months after fiscal year end. The mean sizeadjusted return difference dropped to 7.32%, with a tstatistic of 3.54.
20 E/P residuals are (of course) correlated with E/P ratios, so we compared these returns from ranking firms on E/P residuals with those from ranking firms on E/P. The mean difference in sizeadjusted returns between portfolio 10 (high E/P) and portfolio 1 was 4.21%, with a tstatistic of 0.97. The return for 1991 was 37.0% and that for 1998 was 64.2%, due, we suspect, to the effects of momentum investing discussed in the text below. Within the low E/P portfolio, firms with positive E/P residuals earned an average return of 18.47%, compared with 4.87% for firms with negative residuals. Within the high E/P portfolio, the respective numbers were 9.66% and 9.43%.
21 Average crosssectional Pearson correlations between E/P model residuals and estimated CAPM beta, ln(size), ln(booktomarket), and ln(leverage), are 0.022, 0.059, 0.106, and 0.001, respectively. So E/P residuals are not strongly related to any of these socalled risk proxies.
22 Similar results to those in Panel B of Table 5 were obtained when EMBED Equation.3 and S scores were included in the regressions, rather than the E/P model residual. The tstatistic on mean estimated coefficient on EMBED Equation.3 was 3.28 and that on the S score was 6.09.
23 Fairfield, Whisenant and Yohn (2003) show that growth in net operating assets also predict stock returns, but their methodology does not permit a direct comparison with the returns here. Titman, Wei and Xie (2001) also show that investment is negatively related to future stock returns.
24 Thomas and Zhang (2002) indicate that changes in inventory predict stock returns (and earnings), for example, and largely explain returns forecasted by accruals. Richardson, Sloan, Soliman, and Tuna (2005) disaggregate accruals when forecasting returns. Whether these correlations survive with the conditioning variables here is open to question.
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