Multiple factors are explaining abnormal equity returns, which could be used to build a profitable equity long-short strategy. The most common are momentum, value, short-term reversal, size factors, etc..
We present an academic research paper that shows additional useful factor – earnings quality. Stocks with high quality (defined via multiple ratios) outperform stocks with low quality. Earnings quality factor portfolio has low to negative correlation to other factor portfolios. Therefore, it could be used as a valuable diversifier in a multifactor long-short equity strategy.
The effect is explained mainly by investors’ behavioural defects. The majority of investors usually overly fixate on actual earnings, and they do not investigate the quality of earnings scrutinizingly. The in-depth analysis, therefore, allows exploiting this inefficiency.
Backtest period from source paper
Confidence in anomaly's validity
Notes to Confidence in Anomaly's Validity
Notes to Indicative Performance
per annum, annualized (geometrically) monthly return of 0.6399%, data from table VIII for “Mix” portfolio in US
Period of Rebalancing
Notes to Period of Rebalancing
Notes to Estimated Volatility
estimated from t-statistic 9.09, data from table VIII for “Mix” portfolio in US
Number of Traded Instruments
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 non-financial stocks from NYSE, Amex and Nasdaq.
Big stocks are defined as the largest stocks that make up 90% of the total market cap within the region, while small stocks make up the remaining 10% of the market cap. Investor defines breakpoints by the 30th and 70th percentiles of the multiple “Earnings Quality” ratios between large caps and small caps.
The first “Earnings Quality” ratio is defined by cash flow relative to reported earnings. The high-quality earnings firms are characterized by high cash flows (relative to reported earnings) while the low-quality firms are characterized by high reported earnings (relative to cash flow).
The second factor is based on return on equity (ROE) to exploit the well-documented “profitability anomaly” by going long high-ROE firms (top 30%) and short low-ROE firms (bottom 30%).
The third ratio – CF/A (cash flow to assets) factor goes long firms with high cash flow to total assets.
The fourth ratio – D/A (debt to assets) factor goes long firms with low leverage and short firms with high leverage.
The investor builds a scored composite quality metric by computing the percentile score of each stock on each of the four quality metrics (where “good” quality has a high score, so ideally a stock has low accruals, low leverage, high ROE, and high cash flow) and then add up the percentiles to get a score for each stock from 0 to 400. He then forms the composite factor by going long the top 30% of small-cap stocks and also large-cap stocks and short the bottom 30% of the small-cap stocks and also large-cap stocks and cap-weighting individual stocks within the portfolios.
The final factor portfolio is formed at the end of each June and is rebalanced yearly.
Hedge for stocks during bear markets
Yes - Based on the source and related research papers (see, for example, tables 4.2 and 3.5 from paper Jensen-Gaard: Equity Investment Styles – Recent evidence on the existence and cyclicality of investment styles), the strategy has a positive return during recession months therefore probably can be used as a hedge/diversification to equity market risk factor during bear markets.
Out-of-sample strategy's implementation/validation in QuantConnect's framework