Return on Equity (ROE) and other similar metrics such as Return on Assets (ROA), Return on Invested Capital (ROIC), and Return on Total Capital (ROTC) are widely regarded as indicators of operational quality. While the denominator of these ratios varies to a degree, these metrics all generally measure how well a company uses its resources to generate profits. For example, ROE specifically measures how effective a company is at investing shareholder capital such that a company with a higher ROE has a better ability to reinvest in itself. Accordingly, as indicators of operational quality, these ratios are commonly presumed to hold predictive power in stock selection.
As behavioral investors, we understand that conventional wisdom is many times the result of behavioral biases, and thus we believe that any assumptions should be objectively tested. In order to do this, the table and chart below summarize the results of a test we performed that measures historical returns generated by the four metrics mentioned above, in addition to a factor that represents an equally weighted blend of these individual ratios.
The table on the left displays the average twelve-month returns by decile over the test period with the first decile representing the companies with the best (highest) ratios and the tenth decile representing the companies with the worst (lowest) ratios. The color-coding helps highlight the top-performing (green) and bottom-performing (red) deciles. It is important to note that these deciles are sector neutral, meaning that each decile is comprised of the same sector weights as the overall universe.
The chart on the right breaks out how the blended factor performed throughout the test period, with the data specifically representing the rolling twelve-month return spread of the top three (best) deciles of the factor versus the factor average. The results reflect a test period of 2000-2019 that was run with a quarterly frequency and with the Russell 3000 used as the universe. Additionally, the results below only reflect companies that offered positive ratio values.
The test results contradict the conventional wisdom as the data shows that these various metrics alone have not been effective predictors of stock returns during the most recent approximately twenty-year period. This can be seen when considering that no matter how the data is cut between the best and worst deciles (e.g. the best three deciles versus the worst three, etc.), companies that have high ROEs, ROAs, ROICs, and ROTCs, or a combination of all four, do not perform better than other companies.
Furthermore, the time-series data shows that these results are not concentrated to a specific period. The best three deciles of the blended factor have only outperformed the average decile in 53% of periods, a probability not much better than a coin toss.
This evidenced ineffectiveness of ROE and similar ratios begs the question of why these metrics are commonly considered to hold predictive power in stock selection in the first place. We believe this phenomenon is driven by the flawed assumption that there is a fixed relationship between a company’s operational quality and the attractiveness of a company as an investment. This tendency to incorrectly conflate operating quality with investment quality is the result of a range of behavioral biases, perhaps most notably the representative heuristic, which is the tendency to believe that something belongs to a group based on a superficial resemblance.
This heuristic comes into play in this case as investors tend to see a resemblance between strong operational quality and strong investment opportunity and thus believe that companies with strong operations will outperform. However, research objectively shows that this is not necessarily the case.
We are not proposing that it is wrong to seek out companies with strong ROEs and ROAs, although we do believe it is important to understand which metrics are predictive of investment returns and which are not. Accordingly, while data does not support the notion that ROE and similar ratios hold predictive value in stock selection, we have included the test results of several LTM (Last Twelve Month) valuation metrics below for comparison purposes. Similar to the previous data, the results are sector neutralized and reflect a test period of 2000-2019 that was run with a quarterly frequency and with the Russell 3000 used as the universe.
Additionally, because the valuation metrics are expressed on a “yield” basis rather than a “multiple” basis, the first decile represents the cheapest companies and the tenth decile represents the most expensive companies.
As can be seen in the results, these sample measures of valuation all possess the ability to generate notable outperformance with a relative consistency throughout time. There is a stark contrast between the efficacy of valuation versus ROE and other similar metrics as the data exhibits that company valuation, not various proxies of operational quality, is the primary arbiter of investment returns. This foundational but routinely dismissed investing truth is driven by the reality that any company can be a successful investment if purchased at an attractive price.
We believe this information is useful, given that these results objectively show that investors should not find comfort in a particular company solely due to the strength of these operational metrics. Furthermore, strong operational quality and attractive valuations are certainly not mutually exclusive; and there are opportunities to find companies that offer both aspects.
However, the key to effectively identifying attractive investments is to hold company valuation as a primary priority in the stock selection process. While doing this is inherently contrarian and involves fighting naturally ingrained biases and heuristics, placing valuation as the order of first importance rather than measures of operational quality is objectively rewarded by the market over time.
Any forecasts, figures, opinions or investment techniques and strategies explained are Hillcrest Asset Management, LLC’s as of the date of publication. They are considered to be accurate at the time of writing, but no warranty of accuracy is given and no liability in respect to error or omission is accepted. They are subject to change without reference or notification. The views contained herein are not to be taken as advice or a recommendation to buy or sell any investment and the material should not be relied upon as containing sufficient information to support an investment decision.
Data is provided by various sources and prepared by Hillcrest Asset Management, LLC and has not been verified or audited by an independent accountant. Test result are not indicative of future results and should not be relied upon. While the information provided above is not based on the performance of any individual security or group of securities, the methodology used to provide the information can be obtained by contacting Hillcrest Asset Management, LLC.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
