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Defining Quality: separating the wheat from the chaff

Defining Quality: separating the wheat from the chaff

18-06-2020 | リサーチ
Quality is a commonly accepted equity factor. But while there is a broad consensus on the fact that stocks of high-quality companies should outperform lower quality ones over time, what quality actually means remains a source of sometimes spirited debate. Our research shows that only those measures that help predict future earnings growth have strong predictive power to forecast future stock returns.
  • Georgi Kyosev
    Georgi
    Kyosev
    Researcher
  • Matthias Hanauer
    Matthias
    Hanauer
    Researcher
  • Joop  Huij
    Joop
    Huij
    Head of Factor Investing Equities and Factor Index Research
  • Simon Lansdorp
    Simon
    Lansdorp
    Portfolio Manager

Speed read

  • A consensus on how to define a high-quality company is missing
  • Finding high-quality stocks is all about looking for future earnings growth
  • Adding Quality to Multi-Factor Equities paid off

Quality is one of the few commonly accepted equity factors, alongside others such as value, momentum or low volatility. But while there is a clear consensus on how to define the latter four factors, academics and practitioners alike are clearly divided on the measures that should be used to define quality.

In fact, a key concern with many ‘quality labelled’ investment products available on the market is that these strategies do not really expose investors to the quality factor premium. Instead, they are in fact often highly correlated with the low volatility factor. In a recently published paper1, Robeco researchers address this issue, in search of the best way to define quality.

This research builds on a thorough analysis of the most popular approaches to defining quality and focuses on the characteristics and performance of eight measures that, in previous studies, have been shown to correlate with future earnings and/or future stock returns and are often associated with aspects of company quality.

These eight measures are: return on equity, margins, return on equity growth, leverage, earnings variability, gross profitability, accruals and investments. The paper assesses which of these measures have predictive power to forecast future company profitability and expected stock returns, as well as the hypothetical performance of these measures in global developed equity markets since 1986.

Robust findings across regions

Our main conclusion is that while there is clearly a quality factor premium, only the quality measures that can predict future earnings growth have also predictive power to forecast stock returns. These findings are robust across geographical regions, including emerging markets, and carry over to corporate bond markets.

In the long run, only gross profitability, accruals and investments can explain differences in the cross-section of stock and bond returns

In all markets, the study finds clear evidence that there is indeed a sizeable and robust quality premium, but that it is of utmost importance to identify those quality measures which have proven to have the power to predict future earnings growth. In the long run, only gross profitability, accruals and investments can explain differences in the cross-section of stock and bond returns. Figure 1 summarizes these results.

Figure 1: Regression-based significance levels of quality measures, controlling for other factors

Source: Georgi Kyosev, Matthias Hanauer, Joop Huij and Simon Lansdorp, 2000,“Does Earnings Growth Drive the Quality Premium?”, The Journal of Banking and Finance. The graph shows t-statistics for Fama-MacBeth regressions of monthly stock returns on individual company characteristics. The regressions include all quality variables simultaneously and correct for the following set of control variables: log (market cap), log (book to price), momentum 12-1 month, beta 3-year, volatility 3-year, distance to default, and dummies for region and sector. All quality variables are multiplied by the expected sign, as shown in Exhibit 1. The sample period is January 1986 - December 2015 for global developed markets.

Figure 1 shows the statistical significance levels (t-statistics) of the earnings predictive quality measures, the earnings non-predictive quality measures, and a set of other factors which are used as control factors. Interestingly, the three earnings predictive quality measures – gross profitability, accruals and investments – have significant predictive power to forecast future stock returns.

In practice, Robeco started incorporating these empirical insights into its quantitative investment strategies several years ago; in particular for equities, but also for credits and for its multi-asset strategies. Since then, our findings have proved their added value for investors.

For instance, the Robeco Global Quality Equities strategy has been outperforming the MSCI All Countries World Index, gross and net of fees, since it was introduced in August 2016. Moreover, this outperformance has been consistent over time, with the strategy beating its benchmark in 10 out of 14 full quarters since inception.

Robeco’s quant researchers and portfolio managers maintain strong ties with the world of academia, making valuable contributions to financial theory and our approach to efficient factor investing. The investment results above illustrate once again the rewards investors can reap from a rigorous, research-driven approach and the impact this can have on their risk-adjusted performance.

1 Kyosev, G., Hanauer, M., Huij, J. and Lansdorp, S., 2020, “Does Earnings Growth Drive the Quality Premium?”, The Journal of Banking and Finance.

重要事項

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