Overarching point of this presentation: accruals predict significant, excess future returns. We’ll find out more about what exactly that means later.
Firstly, about accruals. Earnings can be broken up into two parts: cash (CFO) and accruals. Eg: you make a sale on cash (goes to cash), vs. you make a sale on credit (goes to accounts receivable, an accrual). Sloan (balance sheet method): Accruals=change in non-cash assets – change in current liabilities (excluding debt, and taxes payable if income is ICO and not NI) – depreciation and amortization expenseWhat about negative accruals: e.g. a very high wages payable?Everyone else: Accrual=Net Income - CFO
Re-arranging Earnings = Accruals + CFO… (picture), which is equal to (picture).This is essentially the indirect method of calculating CFO from NI that you learned in ACCT 101, CFA[Remember the indirect method from ACCT 101, CFA? adjustments that you learned accountants make to NI to get CFO? Subtract change in CA from NI, add change in CL to NI, to get CFO. We’re defining accruals as the opposite of those adjustments.]The basis of the earnings fixation hypothesis is the fact that accruals are mean reverting, that they reverse. Take accounts receivable, which is an accrual. You make a sale on account, accounts receivable goes up, accruals go up. The customer pays you back, accounts receivable go down, accrual go down. Note that in the reversal of the accrual, earnings are not affected.So accruals, which are a part of earnings, are mean reverting. The earnings fixation hypothesis says that investors in aggregate fixate on earnings and fail to recognize that extreme accruals are not only mean reverting, but that they also tend to reverse future earnings.
ExamplesLet’s use an example to explain this: channel stuffingLets say for this company, 70% of sales are made on account, and that this ratio is relatively constant over timeManager, in order to boost current period earnings, stuffs his channel and gets customers to buy way more than they usually domost sales are made on account, accounts receivables go up a lot, accruals are higher than usualNext period, customers not nearly as willing to buy (as they are busy drawing down the excessive inventory they bought last quarter), but they do pay back their debt (so accounts receivables, and thus accruals, fall) next period earnings fallWhere earnings fixation comes inAt t=1, since investors are fixated on the growing earnings and don’t look at the extreme accrual, they might believe earnings will continue to growSo they buy up the stock, price goes upThe earnings announcement at t=2 reveals the truth, investors realize their mispricing and sell the stock, driving down its priceThat’s an example of how an extremely high accrual predicts negative future returnsSecond example: Excessive inventory accumulation. Current assetPerhaps manager is overly optimistic, decides to stock up on inventory way above normal levelsWhen he does: the Dr/Cr only affects assets (e.g. Dr Inventory, Cr Cash), is NOT reflected on the income statementNext year, he realizes he can’t sell all his inventory, forced to sell it at a lower margin, decreasing net income; or even an inventory write-off (an expense), further decreasing net incomePossible third example: AFDA: current liability on balance sheet created in anticipation of customers not being to pay you backSay a company has very pessimistic estimates one year and increases its AFDA a lotAFDA increases through BDE, so NI for the current period goes downNext year, turns out they overestimated the amount of people that wouldn’t pay, will have to reduce AFDA by recognizing a “gain from overestimation”, increases earningsBefore: higher sales, higher earnings, higher accounts receivableAfter: not only do accounts receivable reverse, but sales are hurt too
“Do Stock Prices Fully Reflect Information in Accruals and Cash Flows About Future Earnings”, Sloan, 1996Annual accruals predict excess future returns“Percent Accruals”, Lundholm et al., 2010Another way of measuring accruals, better?“Quarterly Cash Flows, Accruals, and Future Returns”, Livnat et al., draft 2011Quarterly accruals also predict excess future returns
Size adjustment is:Ken French has constructed 6 portfolios formed on 2 size classifications (small vs. big) and 3 value classifications (value, neutral, growth). “Size adjustment” in this presentation refers to “size and value adjustment”, which is the process of taking a stock, finding which one of the size/value portfolios it belongs to, taking the stock’s buy and hold return and subtracting the size/value portfolio’s buy and hold return over the same period.
Sloan: long: 4.9%, short: 5.5% (1962-1991)Lundholm: long (best decile): 5.53%, short (worst decile): 6.15% (1989-2008)Reason why percent accruals works better: take companies with very negative earnings and negative CFOTheir normal accrual will still be negative, and when scaled by assets are still negativeThus we have poor quality companies in the bottom decileWhereas in percent accruals, the most negative signals will be ones with close to 0 net income, meaning positive CFOThus we have higher quality companies in the bottom decileLivnat: long: 2.2%, short: -1.2% (1991 - 2004)
Using our CRSP and COMPUSTAT data, we ran some SQL and R scripts to replicate some of the research in Livnat’s quarterly accrual paper. That is a table of average buy and hold returns for 3, 6, and 9 months after we get the quarterly accruals signal. We can see that the lowest decile of accruals consistently has higher returns than the highest decile of accruals. Additionally, the decile returns are ordinal, meaning that decile 1 returns are higher than decile 2 returns, which are higher than decile 3 returns, so on and so forth. You can see this in the graph, how the colors progress relatively smoothly from cyan, the highest decile accrual return, to blue, the lowest decile accrual return, and the decile return lines don’t really overlap.
Let’s compare our attempt at replicating Livnat’s results with Livnat’s actual results. We can see some differences here: mainly that the magnitude of our returns are larger (14% over 9 months for us, returns never get that high in Livnat’s table), and that we only have returns up to 9 months whereas he has returns up to 12 months.
Let’s compare our attempt at replicating Livnat’s results with Livnat’s actual results. We can see some differences here: mainly that the magnitude of our returns are larger, and that we only have returns up to 9 months whereas he has returns up to 12 months. Differences: Livnat uses the SEC filings date (audited financials, whereas preliminary earnings announcements aren’t), whereas we used a 3 month delayLivnat’s returns are size adjusted, ours aren’tHe uses non restated Compustat financials, provided by Charter Oak. We only have restated.? Livnat includes delistings and bankruptcies. We have blanks, which could be bankruptcies, or they could be mergers[We’re calculating accruals from balance sheet, he uses CFS (difference?)]
Make sure holding period, signal and returns calculations (size adjustment) are correct when replicating researchCan make a huge difference as we’ve seenData processing using SQL vs. RTry to do most of the data processing in SQLHad an R script that looked at all 240,000 accrual signals, and calculated the 3, 6, 9 month returns after each of them, given a giant table of monthly returns for all stocks in the universeTook a while (had to run it overnight for a few days)It can get really annoying, especially when they restart your computer and your script doesn’t write the results it has so far to a text fileBe careful of delistings, bankruptciesHow were they reflected in monthly returns table?Eg if company went bankrupt in middle of month, would the end of month return be blank? It should be -100%Look at percent quarterly accrualsLundholm already looked at annual percent accruals and found that they predict higher excess returns than traditional accruals doSince quarterly data is more timely, would be interesting to test quarterly percent accruals, and to compare that with the quarterly traditional accruals in Livnat’s paperIs the accrual anomaly dying?Hedged returns have been erratic, even during the 2003-2007 boom Also, how about recent performance of accruals up until today (3.5 years since Lundholm)
Transcript of "Troy Shu Accrual Presentation"
The Accrual Anomaly<br />What it is, empirical evidence, and future research<br />Troy Shu<br />
Accruals are a measure of earnings quality.<br />Earnings = CFO + Accruals<br />Example of an accrual: account receivables<br />We are looking for companies with low accruals, high quality earnings<br />Accrual anomaly: high accruals tend to predict lower excess returns, low accruals tend to predict higher excess returns<br />
“Earnings fixation” is the primary hypothesis for why there is an accrual anomaly.<br />Accruals = Earnings – CFO =<br />∆Non-cash Current Assets - ∆Non-Debt Current Liabilities + other adjustments for non-cash and non-operating transactions<br />Basis: accruals are mean reverting<br />Example: accounts receivable<br />Investors fixate on earnings and, in aggregate, fail to consider that extreme accruals tend to “reverse” future earnings<br />Example: excessive inventory<br />
We read three different research papers on the accrual anomaly.<br />Sloan: annual accruals (1996)<br />Lundholm et al.: annual percent accruals (2010)<br />Livnat et al.: quarterly accruals (2011)<br />Accrual Signal = (Earnings – CFO ) / Average Assets<br />Percent Accrual Signal = (Earnings – CFO ) / |Earnings|<br />
Here’s how they measured the accrual anomaly’s excess returns:<br />Every period, get previous year’s accruals, sort into deciles<br />Measure the (size adjusted) return of buying after the signal announcement and holding for a year<br />Repeat for next year<br />At very end, calculate buy and hold return averages for each of the deciles<br />
Accruals predict future excess returns pretty well.<br />Sloan (1962-1991): 10.4% (hedged) size adjusted returns in the first year<br />Lundholm (1989-2007): 11.7% (hedged) size adjusted returns in first year<br />Finds that Sloan’s traditional accrual only produces 6.5% (hedged) size adjusted returns for the same period<br />Livnat (1991 - 2004): 3.4% (hedged) size adjusted returns in first quarter, 9.9% over first year<br />“Do Stock Prices Fully Reflect Information in Accruals and Cash Flows about Future Earnings?”, Sloan, 1996<br />
Despite data and time constraints, the results of our replication of Livnat’s quarterly accrual research appear to be reasonable.<br />Pretty graph made with ggplot2 R library<br />
Despite data and time constraints, the results of our replication of Livnat’s quarterly accrual research appear to be reasonable.<br />“Quarterly Cash Flows and Accruals”, Livnat et al, 2011<br />
Despite data and time constraints, the results of our replication of Livnat’s quarterly accrual research appear to be reasonable.<br />Livnat uses the SEC filings date, whereas we used a 3 month delay<br />Livnat’s returns are size adjusted, ours aren’t<br />He uses non restated Compustat financials, provided by Charter Oak. We only have restated.<br />
Here is a summary for future accruals research<br />Make sure holding period, signal and returns calculations are correct<br />Data processing using SQL vs. R<br />Be careful of delistings, bankruptcies<br />Look at percent quarterly accruals<br />Is the accrual anomaly dying?<br />“Percent Accruals”, Lundholm et al., 2010<br />
Appendix AReplicating Livnat’s quarterly accrual study<br />What we want to reproduce: Table 2 “Accruals and Subsequent Returns” in Livnat’s paper<br />Data period<br />1991-2004<br />See page 9 of Livnat for sample reduction conditions: market cap, missing financials, etc.<br />Accrual signal<br />Accrual = <br />[ Earnings (CS Quarterly Item 8) – CFO (CS Qtr Item 108) ] / Average assets (CS Qtr Item 44) between current and last quarter <br />Livnat uses non-restated financials from Charter Oak’s database to eliminate hindsight bias<br />Holding period<br />Start: two days after SEC filing date for quarter t<br />Two days assumes that investors receive the filing the next day and after processing it, enter the position the 2nd day<br />Through: one day after preliminary earnings announcement for quarter t+iwhere i=1,2,3,4<br />If preliminary announcement date is missing, replaced by 90, 180, 270, and 360 (calendar) days after SEC filing<br />Livnat says SEC filing dates of the 10Q/K forms are provided by Compusta. CS Filing Dates Database? http://www.compustat.com/products.aspx?id=2147492874<br />[Preliminary] earnings announcement dates are apparently Compustat Data Item RDQE… can also get from IBES<br />Return adjustment<br />Excess return = raw return – return on corresponding French size-B/M portfolio for same period<br />See top of page 10 in Livnat for more details on size-value return adjustment<br />Delistings: if security is delisted before the end of a holding period, Livnat uses the CRSP delisting return if available, <br /> -100% if company is forced to delist by exchange or bankruptcy<br />Note: Livnat deletes top and bottom 0.5% extreme buy and hold returns… don’t do this?<br />Decile ranking<br />At the end of every calendar quarter (April 1, July 1, October 1, Jan 1), accruals released in the previous 3 months are ranked into deciles<br />After all accrual signals have been sorted into deciles, one can calculate aggregate return statistics (e.g. average return) for each of the deciles<br />