Accrual Reversals, Earnings and
Stock Returns
Eric Allen
Chad Larson
Richard Sloan
Graham and Dodd (1934)
Main Idea
• Extreme accruals contain a disproportionately high
concentration of extreme accrual estimation errors of
the same sign
• Accrual estimation errors must reverse in a
subsequent period, causing earnings changes that
correspond to the magnitude of the associated
accrual reversal
• Extreme accruals are associated with subsequent
earnings changes of the opposite sign
• Stock prices act as if investors do not fully anticipate
these predictable accrual reversals and earnings
changes
3
Contributions
• Uses our knowledge of accrual accounting to document
and explain economically and statistically significant
properties of accruals and earnings.
•
Corroborates Sloan’s (1996) explanation for the ‘accrual
anomaly’ [see competing explanations from Fairfield,
Whisenant and Yohn (2001), Zach (2007), Kahn (2007),
Ng (2005)].
• Provides an explanation for the robustness of the ‘accrual
anomaly’ for inventory accruals [Thomas and Zhang
(2002)]. We show that inventory accruals are more prone
to extreme reversals.
5
Prior Research on Accrual
Estimation Errors/Reversals
• Dechow and Dichev (2002)
•
•
Derive accrual estimation errors from regressions of accruals on past
present and future cash flows
Show that volatility of estimation errors positively related to absolute
magnitude of accruals and negatively related to earnings persistence
• Chan, Chan, Jegadeesh and Lakonishok (2006)
•
•
Examine relation between magnitude of accruals and magnitude of
subsequent special items
Show that special items are unusually large and negative two and three
years after accruals are unusually large and positive
• Zach (2007)
•
•
Firm-years with extreme accruals in one year are more likely to have
extreme accruals of the same sign in the next year
Weak evidence that abnormal returns are related to accrual reversals for
high accruals, but inconsistent evidence for low accruals
6
Hypothesis Development
• Properties of ‘good’ accruals:
•
•
•
They correctly anticipate future cash flows
Their persistence depends on persistence of underlying economic
growth of the business
They have no direct consequences for the change in future
earnings
• Properties of accrual estimation errors:
•
•
•
They do not anticipate future cash flows
They completely reverse in a subsequent period
They temporarily inflate earnings today and temporarily deflate
earnings tomorrow, causing a future earnings change that is
opposite in sign and twice the magnitude of the error
7
Predictions
P1:
Accruals mean revert more rapidly than cash
flows
P2:
Extreme accruals exhibit a disproportionately
high rate of extreme accrual reversals (and
corresponding earnings changes)
P3:
After controlling for accrual reversals, accruals
are not negatively related to future earnings
changes and future stock returns
P4:
Inventory write-downs are preceded by a
disproportionately high frequency of extreme
positive accruals
8
Samples
• Main accruals sample
─ All observations in intersection of Compustat and
CRSP with variables required to compute accruals
between 1962 and 2006
─ 149,685 firm-years
• Inventory write-down sample
─ Subset of main sample with CIK numbers and fiscal
years ending in 2001-2004
─ 17,690 total firm-years
─ 1,886 firm-years reporting existence and amount of
inventory write-down (hand-collected from Form 10-K
filings using DirectEdgar)
9
Variable Measurement
• Working capital accruals measured using the
balance sheet approach (exclude depreciation)
• Inventory write-downs reported as negative
numbers (note that inventory write-downs
should be charged to cost of goods sold, per
EITF 96-9)
• All financial variables deflated by average total
assets
• Abnormal stock returns measured using buyhold size-adjusted returns, including delisting
adjustments, starting 4 months after FYE
10
Descriptive Statistics: Main Sample
11
Tests of P2:
Proportion of Sample Belonging to Each Cash
Flow Transition Cell
12
Tests of P2:
Proportion of Sample Belonging to Each Accrual
Transition Cell
13
Tests of P2:
Proportion of Sample Belonging to Each
Inventory Accrual Transition Cell
14
Change in Net Income for Accrual
Transition Cells
15
Change in Net Income for Inventory
Accrual Transition Cells
16
Abnormal Stock Returns for Accrual
Transition Cells
17
Abnormal Stock Returns for Inventory
Accrual Transition Cells
18
Tests of P1:
Accruals Mean Revert More Rapidly
Than Cash Flows
19
Tests of P2:
Extreme Accruals Exhibit a Disproportionately
High Rate of Extreme Accrual Reversals
20
Extreme Reversals Help to Explain
Mean Reversion in Accruals
21
Tests of P3:
After controlling for accrual reversals, accruals are no
longer negatively related to future earnings changes
22
Tests of P3:
After controlling for accrual reversals, accruals are no
longer negatively related to future stock returns
23
Descriptive Statistics:
Inventory Write-Down Sample
24
Tests of P4:
Proportion of Inventory Write-Downs Belonging to
Each Inventory Accrual Transition Cell
25
Tests of P4:
Average Magnitude of Inventory Write-Downs
Belonging to Each Inventory Accrual Transition Cell
26
Tests of P4:
Regressions of Inventory Write-Downs on
Previous Changes in Inventory
27
Conclusions
1. Extreme accruals are associated with a
disproportionately high frequency of extreme
reversals
2. These accrual reversals explain the predictable
earnings changes and stock returns following
extreme accruals (Sloan, 1996)
3. Reversals are particularly pronounced for
inventory accruals, explaining the results in
Thomas and Zhang (2002)
28
Implications
• Accountants, auditors regulators and
investors should pay more attention to
extreme accruals
• Accrual estimation errors may arise from:
• active manipulation of accruals
• distortions created by GAAP
• delayed business and accounting responses to changes
in economic conditions
• Better identification of accrual estimation
errors should facilitate improved forecasting
of earnings changes and stock returns
29