by Tajinder Dhillon.
The COVID-19 pandemic has caused unprecedented market turmoil, with volatility reaching levels not last seen since 2008. As a result, we have observed a “flight to safety” where risk assets such as equities and commodities have sold off, while safe-haven assets, including bonds and have soared.
For equity investors looking to maintain or increase equity exposure, incorporating a quality factor to the stock selection process can be effective during a market downturn. The StarMine Earnings Quality Model can be viewed as a proxy for quality, which analyzes the persistence and sustainability of future earnings by looking at accruals, cash flow, operating efficiency, and in the U.S., exclusions (GAAP vs. Non-GAAP). Companies with higher quality tend to have greater cash-flow generation and operational efficiency. This provides greater assurance of a company’s future earnings which is of paramount importance during times of extreme turmoil.
The aggregates app in Eikon by Refinitiv allows users to view aggregate data by business classification, geography, portfolio, or index in a fully customizable display, enabling trend observation and relative asset allocation decisions.
Using the aggregates app, we look at the aggregate industry price movement over the last 30 days in the S&P 500, STOXX 600, FTSE 350, and FTSE All-World Asia Pacific as shown in Exhibit 1. Most indices observed similar price movement, so we focus on the S&P 500.
Exhibit 1: Aggregate Earnings Quality by Economic Sector (TRBC) for S&P 500, STOXX 600, FTSE All-Share Asia Pacific, and FTSE 350
We observe that industries with the highest StarMine Earnings Quality (EQ) scores have fared better off relative to industries with lowest scores. The exception is for consumer-related industries, which have high aggregate EQ scores but were severely impacted during the sell-off (hotels, casinos, and cruises).
Food, household, medical, and telecommunication industries have seen less dramatic price declines. While these industries are of vital importance during the pandemic, they also demonstrate high aggregate EQ scores suggesting they are more defensive plays.
Companies are ranked from 1-100 (lowest-highest) among regional peers on a percentile basis. The aggregates app allows users to dive into each industry, where we see Proctor & Gamble (PG.N) (99), Colgate-Palmolive (CL.N) (83), Clorox (CLX.N) (96), Johnson & Johnson (JNJ.N) (97), Merck & Co (MRK.N) (99), Walmart (WMT.N) (73), Verizon (VZ.N) (87), and Coca-Cola (KO.N) (85) among those who exhibit high Earnings Quality.
Furthermore, companies with higher quality tend to be safer from a credit risk perspective (i.e. less risk of defaulting on bond obligations or bankruptcy). When looking at all active equities on a global basis (25,000+), we observe a strong correlation between StarMine EQ and credit risk at an aggregate industry level (StarMine Combined Credit Risk) as shown in Exhibit 2.
Exhibit 2: Aggregate Earnings Quality by Economic Sector (TRBC) for all active equities
One of the inputs into the Combined Credit Risk model includes the Smart Ratios Credit Risk model, which analyzes credit risk by looking at such items as leverage, profitability, liquidity, and coverage ratios.
The energy industry has seen the largest price declines in the S&P 500 given a collapse in oil prices. A lower oil price environment combined with excess high-yield debt creates a challenging outlook for oil companies. To add further worries, companies in this industry exhibit lower Earnings Quality (aggregate EQ score of 51), which raises concerns over whether future dividend payments will be met or, at risk of being cut.
Using our cloud based back-testing tool QA Point, we can see how quality has performed over the last decade in different regions for both long-only and long-short investors. We created a single-factor model which uses the Earnings Quality model as the sole factor. Using a monthly rebalancing frequency, we display the results in ten fractiles.
Exhibit 3 showcases the consistent outperformance of the Earnings Quality model over the last decade in all major regions. The strongest performance can be seen in Europe and Asia Pacific, with annualized top/bottom decile returns of 13.90% and 17.27% respectively. Both regions have an information ratio of 0.08 and a high risk-adjusted Sharpe Ratio of 1.76 and 2.33 respectively.
Strong performance is also observed in the U.S, which is home to the most efficient index — the S&P 500. The top decile (F1: Fractile 1) significantly outperforms the overall benchmark. Similar outperformance is also observed in the U.K, with annualized top/bottom decile returns of 8.69%.
Across all regions, we observe smaller draw-down risk when comparing the top decile vs. bottom-decile, highlighting the benefit of incorporating quality into the investment decision process.
Exhibit 3: Earnings Quality Performance from Dec. 31, 2009 to Feb. 29, 2020, rebalanced monthly
TR Asia Pacific
To see how quality has performed in the most recent bear market, we performed an EQ backtest from the beginning of February to as of writing with a daily rebalancing. Our goal was to examine the performance of EQ during the current market sell-off, looking at the U.S., where market declines have been especially acute. Although this is over a very short horizon, we see the top quintile outperforming the equal-weighted universe and the bottom quintile underperforming. We also observed strong top-bottom decile spreads on a cumulative basis with a high Sharpe Ratio, implying that quality provides investor protection from the disproportionate downside of low-earnings quality stocks.
For a more detailed look at our original StarMine Research Note on this topic, please click here (Research note: Evidence for Tilting Portfolios Toward Quality During Market Downturns, 2018).