Profitable firms have more significant market returns, then unprofitable firms. This is something that matches common sense logic of everyday life. But the Effective Market Theory was telling us for a long time that there shouldn‘t be any return difference between profitable and unprofitable firms as the factor of profit should be already fully priced into the price of the stock.

However, recent academic studies confirm what every Wall-Streeter (and also Main-Streeter) already knew. They show there is a robust and strong return premium in holding profitable stocks and so it makes sense to go long firms with strong ROA (Return on Assets) and short firms with weak ROA. Source paper for this effect also shows that the ROA effect could explain a lot of other anomalies (mainly earnings and profitability related – like popular price-to-earnings ratio, etc.). The strategy is built as a long-short portfolio and for example, is using thousands of stocks in an investment portfolio. Still, it is indeed possible to exploit this effect also in a smaller portfolio.

Fundamental reason

Research explains that firms with productive assets should yield higher average returns than firms with unproductive assets. Productive firms for which investors demand high average returns should be priced similarly to less productive firms for which investors demand lower returns. Variation in productivity, therefore, helps identify variation in investors’ required rates of return. Therefore profitable firms generate higher average returns than unprofitable firms (as productivity helps identify this variation – with higher profitability indicating higher required rates). This fact motivates the return-on-asset factor.

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Markets Traded
equities

Financial instruments
stocks

Confidence in anomaly's validity
Strong

Backtest period from source paper
1972-2006

Notes to Confidence in Anomaly's Validity

Indicative Performance
12.15%

Period of Rebalancing
Monthly

Notes to Indicative Performance

per annum, annualized (geometrically) monthly return of 0.96%, data from table 1


Notes to Period of Rebalancing

Estimated Volatility
13.36%

Number of Traded Instruments
1000

Notes to Estimated Volatility

estimated from t-statistic 5.10, data from table 1


Notes to Number of Traded Instruments

more or less, it depends on investor’s need for diversification


Maximum Drawdown
0%

Complexity Evaluation
Complex strategy

Notes to Maximum drawdown

not stated


Notes to Complexity Evaluation

Sharpe Ratio
0.61

Simple trading strategy

The investment universe contains all stocks on NYSE and AMEX and Nasdaq with Sales greater than 10 million USD. Stocks are then sorted into two halves based on market capitalization. Each half is then divided into deciles based on Return on assets (ROA) calculated as quarterly earnings (Compustat quarterly item IBQ – income before extraordinary items) divided by one-quarter-lagged assets (item ATQ – total assets). The investor then goes long the top three deciles from each market capitalization group and goes short bottom three deciles. The strategy is rebalanced monthly, and stocks are equally weighted.

Hedge for stocks during bear markets

Not known - Source and related research papers don’t offer insight into correlation structure of proposed 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. The strategy is built as a long-short, but it can be split into two parts. The long leg of the strategy is surely strongly correlated to the equity market; however, the short-only leg might be used as a hedge during bad times. Rigorous backtest is, however, needed to determine return/risk characteristics and correlation.

Source paper
Strategy's implementation in QuantConnect's framework (chart+statistics+code)
Other papers

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