The accrual anomaly is deeply connected with the non-cash component of earnings – the accruals. Firstly documented by the Sloan(1996), the accruals anomaly is the negative association between accounting accruals and subsequent stock returns. The theory connected with this particular anomaly is based on the importance of measuring if the company’s earnings (as reported by company management) are based on real cash-flow or questionable accounting practices. According to the research, firms with low levels of accruals are connected with real earnings, and on the other hand, firms with a high level of accruals could be a result of some accounting practice. As a result, stocks with low accruals should earn higher market returns than high accruals stocks.
Moreover, according to the LaFond and his work “Is the Accrual Anomaly a Global Anomaly?“, this anomaly is globally present. Quoting the author: “I investigate the implications of the return of accruals in 17 countries over the 1989 to 2003 period. In general, the results of the country-specific analysis indicate that the accrual anomaly is a global phenomenon.”
Although this anomaly could be exploited by acquiring a long position in low accruals companies and a short position in high accruals companies, more recent research suggests that a simple accruals strategy not only could but should be enhanced, while using the simple accruals anomaly as a building block. Although the strategy could not be traded away as easily and is connected with the lower institutional interest, this is caused by the characteristics of high accruals stocks. These stocks are often connected with small-capitalization, some liquidity issues, and high transaction costs. For example, Mohanram in the: “Analysts’ Cash Flow Forecasts and the Decline of the Accruals Anomaly“, states that: “The accruals anomaly, demonstrated by Sloan (1996), generated significant excess returns consistently for over four decades until 2002, but has apparently weakened in the subsequent period. “On the other hand, Bender and Nielsen in their paper: “Earnings Quality Revisited”, has found that the earnings quality signal stopped working in the mid-2000s but since the end of 2008 has staged a remarkable rebound.
According to the research, an explanation for the accrual anomaly is the earnings fixation hypothesis. The hypothesis says that investors are fixed upon earnings and fail to pay attention separately to the cash-flow and accrual components of earnings. However, this is the main reason for the functionality of the accruals anomaly. Firstly, the cash-flow component of earnings is a superior and better forecaster of future earnings if we would compare it with the accrual component of earnings. Therefore, investors who are not able to distinguish between actual earnings and accruals can become overly optimistic about the prospects of firms with high accruals.
Moreover, they can become even overly pessimistic about the prospect of firms with low accruals. Naturally, if we take into account that the aforementioned is not correct, this results in overvalued high accruals firms that subsequently earn low abnormal returns. And vice versa, low accruals firms become undervalued, which is followed by the high abnormal returns.
Additionally, recent research states that there are two different accrual anomalies with interesting implications for practical usage. Quoting the Detzel, Schabel, and Strauss and their work: “There are Two Very Different Accruals Anomalies“: “We document that several well known asset-pricing implications of accruals differ for investment and non-investment-related components. Exposure to an investment-accruals factor explains the cross-section of returns better than the accruals themselves, and this factor’s returns are negatively predicted by sentiment. The opposite results hold for non-investment accruals. Further tests show cash profitability only subsumes long-term non-investment accruals in the cross-section of returns, and economy-wide investment accruals negatively predict stock-market returns while other accruals do not. These results challenge existing accruals-anomaly theories and help resolve mixed evidence by showing that the anomaly is two separate phenomena: a risk-based investment accruals premium and mispricing of non-investment accruals.”
Confidence in anomaly's validity
Backtest period from source paper
Notes to Confidence in Anomaly's Validity
Period of Rebalancing
Notes to Indicative Performance
per annum, data from table 1
Notes to Period of Rebalancing
Number of Traded Instruments
Notes to Estimated Volatility
estimated from t-statistic in table 1
Notes to Number of Traded Instruments
more or less, it depends on investor’s need for diversification
Notes to Maximum drawdown
Notes to Complexity Evaluation
Simple trading strategy
The investment universe consists of all stocks on NYSE, AMEX, and NASDAQ. Balance sheet based accruals (the non-cash component of earnings) are calculated as:
BS_ACC = ( ∆CA – ∆Cash) – ( ∆CL – ∆STD – ∆ITP) – Dep
∆CA = annual change in current assets
∆Cash = change in cash and cash equivalents
∆CL = change in current liabilities
∆STD = change in debt included in current liabilities
∆ITP = change in income taxes payable
Dep = annual depreciation and amortization expense
Stocks are then sorted into deciles and investor goes long stocks with the lowest accruals and short stocks with the highest accruals. The portfolio is rebalanced yearly during May (after all companies publish their earnings).
Hedge for stocks during bear markets
Not known - Source and related research papers don’t offer insight into the correlation structure of accruals trading strategy to equity market risk; therefore, we do not know if this strategy can be used as a hedge/diversification during the time of market crisis. Strategy using accruals is usually built as a long-short, but it can be split into two parts. The long leg of the strategy is undoubtedly strongly correlated to the equity market; however, the short-only leg can be maybe used as a hedge during bad times. Rigorous backtest is, however, needed to determine return/risk characteristics and correlation.
Strategy's implementation in QuantConnect's framework