When it comes to dividend-growth investing, we can often learn a lot from other investing styles and approaches—especially from value investing (which shares quite a bit in common with DGI). One area of value investing that has shown promise is the Piotroski F-score model and process for identifying future winners and losers within undervalued companies. This strategy is predicated on an accounting-based fundamental analysis. The question is: Can F-scores improve your dividend-growth investing?
In this article, we will show that F-scores can, in fact, improve your dividend-growth investing by providing you with a framework and process to integrate into your own unique investing plan.
Specifically, we will explore:
Let’s dive right in and explore the potential benefit of F-scores for dividend-growth investing…
A constant theme on Wicked Capital is that long-term investing success requires the right process and the proper mindset.
The reason for this is simple: Investing success requires a logical, consistent, and methodical approach—underpinned by patience and fortitude.
However, this unfortunately runs counter to human nature. Rather than the above, most folks invest emotionally and erratically (unpredictably)—underpinned by impatience, a short attention span, and a propensity to suffer from shiny-object syndrome and herd mentality.
Process and mindset help us to move from the wrong side of the investing aisle (the losing side) to the right side (the winning side).
Specifically, our investing process or method enables us to make logical, consistent, and repeatable investing decisions. Furthermore, we want to keep this process simple—increasing the likelihood that we will stick with it over the long run (a key to success).
We know we want to identify quality dividend-paying companies at a value… but how exactly do you do that?
You need a process!
Valuation is the easy side of the equation. I use a combination of a discounted earnings model (DEM) and other relative valuation methods (e.g., PE metrics and yield ranges). To learn more about how you can easily value companies, I encourage you to read my article How to Easily Value Dividend Stocks Using Discounted Earnings.
However, identifying quality is an entirely different story! This is a much more complex and nuanced task—one that can get quite subjective. This is why it is so critical that you define and develop an effective and efficient process—one you understand, one you can repeat, and one you can stick with long term.
The F-score model/strategy is an example of just such a process—one that helps you identify quality undervalued companies. It provides a selection or filtering framework.
This presents us with two critical questions:
Let’s explore F-scores and answer that question…
In 2000, Joseph Piotroski, a Stanford accounting professor, published a ground-breaking study entitled Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers.
Using stocks from 1976 to 1999, Piotroski examined “whether an accounting-based fundamental analysis strategy, when applied to a broad portfolio of high book-to-market [BM] firms, can shift the distribution of returns earned by an investor.”
In essence, he wanted to know if an accounting-based fundamental analysis would provide a good process for selecting value stocks—one that outperformed the broader market.
His research was, in part, a follow-up to previous work on value as an alpha factor—specifically, the work by Fama and French.
The question he posed was: If value exposure as a whole provides 3.5% of annual alpha (as research indicates), can this premium be increased by differentiating future winners from losers and filtering out the junk?
What he discovered was that a long-short strategy predicated on his F-scores outperformed the S&P by 7.5% annually—double the 3.5% value alpha originally identified by Fama and French (and others).
Additionally, Piotroski’s study found that the F-score benefit was concentrated in small- and mid-cap stocks—providing additional indirect/independent empirical support for the size factor thesis as well.
Before we discuss how this model can potentially help dividend-growth investors, let’s take a closer look at what the F-score model is…
The F-score attempts to identify value stocks that have fundamental strength—differentiating quality from junk and enabling you to filter the bad out.
Obviously, the first step is to identify value stocks. Piotroski, following in the footsteps of Benjamin Graham, suggests using a book-to-market approach and selecting the bottom 20%.
It is important to note that there are lots of ways to identify undervalued stocks and you don’t have to utilize a BM method—it is just the path that Piotroski took for the study. How you select the value stocks is not tied to the F-score model itself.
Once the value stocks are identified, the F-score process evaluates each for nine signals in three fundamental areas: Profitability, Leverage/Liquidity, and Operating Efficiency.
The F-score model is a signal-based analysis; hence, they are binary in nature, meaning each signal is either “good” (1 point) or “bad” (0 points).
The stock’s F-score is the sum of the nine binary signal scores. As such the F-score can range from 0 to 9, where scores of 7-9 represent high (strong) quality and scores of 0-3 represent low (weak) quality. It should be noted that some prefer to highlight scores of 8-9 and 0-2.
Piotroski contends that stocks with F-scores in the high range (7-9) have a high likelihood of being future winners and those in the low range (0-3) are likely to be future losers—despite their apparent value (i.e., they are undervalued for a good reason).
Let’s explore each of the three F-score areas and identify the signals…
The first fundamental area addressed by the F-score is profitability. Profitability and quality are tied at the hip. After all, if a company is going to be a future winner (just temporarily undervalued and out of favor with the market), then it should have a demonstrated capability to:
Based on this underlying premise, Piotroski identified four profitability signals.
The first profitability signal is net income. If the company has a positive net income, it receives one point. If not, it receives zero points.
The second profitability signal is operating cash flow. If the company has positive operating cash flow, it receives one point. If not, it receives zero points.
The third profitability signal is the delta (or change) between net income and operating cash flow. If the company’s operating cash flow is greater than its net income, it receives one point. If not, it receives zero points.
Finally, the fourth profitability signal is return on assets. If the company has a positive return on assets, it receives one point. If not, it receives zero points.
It is worth noting that following Piotroski’s study, many have argued that you should use free cash flow (FCF) for steps two and three rather than operating cash flow. This mitigates any capex impacts and is perfectly acceptable.
The second area addressed by the F-score is the financial health of the company—specifically, its leverage and liquidity.
If a company is going to be a future winner (just temporarily undervalued and out of favor with the market), then it should have improving financial health and demonstrate:
Based on this underlying premise, Piotroski identified three leverage/liquidity signals.
The first signal is the current ratio (measure of liquidity). If the company’s current ratio is greater than the prior year, it receives one point. If not, it receives zero points.
The second signal is the debt-to-equity ratio (measure of leverage). Piotroski defined this as total long-term debt (LTD) divided by average total assets. If the company’s ratio is less than the prior year, it receives one point. If not, it receives zero points.
Finally, the third signal is equity issuance. If the company has not issued equity in the past year, it receives one point. If it has, it receives zero points. It is worth noting that Wesley Gray of Alpha Architect suggests that net equity issuance should be used instead. This provides the opportunity to mitigate small-scale equity issuance for performance-based compensation options with share buybacks. I agree with this idea.
The final area addressed by the F-score is that of operating efficiency.
If a company is going to be a future winner (just temporarily undervalued and out of favor with the market), then it should be demonstrating improved operating efficiency.
Based on this underlying premise, Piotroski identified two efficiency signals.
The first signal is gross margin. Afterall, gross margin lies at the heart of overall operating efficiency. If the company’s gross margin is greater than the prior year, it receives one point. If not, it receives zero points.
The second signal is asset turnover. This metric is critical because efficiency represents the ability to turn assets into revenue. If the company’s asset turnover is greater than the prior year, it receives one point. If not, it receives zero points.
We’ve looked at what the F-score model is, and we’ve seen that Piotroski found it to be highly effective—outperforming the broader market by 7.5% annually.
However, he performed his study in 2000—two decades ago. Does it still work for value investing today?
Evidence from a study by Turtle and Wang in 2017 suggests that the answer is yes.
They studied 125,000 companies from 1973 to 2014 (a large sample size) and found that every high F-score portfolio outperformed low F-score portfolios. Furthermore, they asserted that the study found strong empirical-backed evidence that accounting-based fundamental analysis provides significant conditional performance—even after adjusting for risk.
This is important because one the biggest knocks on the F-score model (and others like it) has been that the outperformance is simply the payoff for taking added risk (e.g., this is the contention of Fama and French).
They also confirmed that the alpha was concentrated in small- and mid-cap stocks. This ties to Piotroski’s original assertion that his study demonstrated (1) the F-score strategy’s “ability to predict future firm performance” and (2) “the market’s inability to recognize these predictable patterns.”
This strategy works—especially with smaller-cap companies—because (a) there is less analyst attention focused on small and out-of-favor value companies and (b) these companies have less liquidity due to less institutional investment and capital movement. In other words, the strategy exploits a market inefficiency.
As the fundamentals of the quality value companies improve, the market is slow to recognize it and react—a perfect combination of inefficiency and time arbitrage!
The Piotroski F-score model may be well-known due to its empirically-backed academic studies; however, there are lots of similar models in common use today.
For example, if you are familiar with Reuters, they provide stock reports with a similar “score.” The Reuters’ model is a bit more complex—using indicators rather than signals and six categories.
Each quantitative indicator is given a score from 1 to 10. The indicators are then weighted within each category—providing a weighted-average category score from 1 to 10.
Next, a simple average of the six category scores is calculated.
Finally, they compare this average score to the normal distribution of a group of stock scores (e.g., entire market, sector, industry, etc.) to arrive at an ultimate score for the company. The goal being the same as Piotroski: To identify those companies that have the highest likelihood of being future outperformers.
One caveat: How each indicator is scored is unknown (proprietary). Thus, this service can provide some general insights; however, it is difficult to fully understand the process—which I always argue you should!
Here is what the Reuters’ model looks like:
A second caveat: The Reuters’ process is predicated on a general investing approach—not specifically growth, value, or dividend. However, based on the categories and weighting, it lends itself more towards growth, as well as being focused on shorter investing time horizons.
However, despite the caveats, it provides an excellent example of how you can take a simple F-score model to a higher level. Furthermore, it demonstrates the wide-range of metrics, combinations, weightings, and variations you can implement in your own process.
Before addressing the dividend-growth takeaways, we need to address a few F-score caveats.
First, both Piotroski and Turtle/Wang highlight that their studies involved broad portfolios. The F-score strategy will not work for a handful of selected stocks. While it does provide an edge (alpha), it necessarily requires the power of large numbers to produce the intended outcome.
Second, the reported results (7.5% annual alpha) were based on a long-short strategy. In other words, the portfolios went long on the stocks with high F-scores (7-9) and short on those with low F-scores (0-2). This is not something that fits dividend-growth investing. Furthermore, we do not know how much of the alpha was attributable to the long and to the short side. However, that doesn’t mean there isn’t potential value in adopting the long-side of this strategy… just understand you’re starting to venture into apples-to-oranges territory.
Third, Piotroski contends that, contrary to growth stocks with valuations predicated on long-term cash flow projections and nonfinancial information, financial analysis of value stocks should focus on recent changes in firm fundamentals. The F-score model only looks at year-over-year (YOY) deltas. This narrow view requires you to be vigilant against a given company manipulating their financials—an increased risk with distressed value companies.
Fourth, the F-score model is a short- to mid-term strategy (typically 1-5 years). As such, it seeks momentum bursts where the market recognizes the value and boosts the price up. Once the stock reaches fair value, this strategy assumes you are closing out your position and booking the profit (and replacing it with a new undervalued, high F-score stock). It is not a long-term investing strategy. This relates to point three above. With dividend-growth investing, you must take a broader look at the fundamentals, business model, and long-term growth prospects because you are intending to hold your positions for a very long time.
Finally, the F-score model—as a pure value strategy—is entirely focused on capital appreciation (see point four). As a dividend-growth investor, you will have to work the dividend component of total return into the picture. After all, the DGI strategy is focused on cash flow/passive income—not capital appreciation.
I believe the F-score model can provide significant benefit to dividend-growth investors—primarily by providing a process framework… a starting point from which you can develop a more dividend-focused model.
Why start from scratch and reinvent the wheel when you have a base model to build upon?
I employ a process that is similar in nature to the F-score, though slightly more complex (which works for me)—much more along the lines of Reuters. Like Piotroski, I start with identifying undervalued opportunities. However, I utilize a discounted earnings approach to valuations, as well as PE and Yield analysis. I then have a scorecard (just like the F-score) that analyzes profitability, leverage, and efficiency. I employ some different metrics, have added a fourth area (dividends), and score on a scale (like Reuters) rather than a binary yes/no… but you get the drift!
Be creative and make it your own. Over the years, you will continue to tweak and improve it as you get real-work feedback. I would add one cautionary note: don’t overemphasize the dividend area. Most folks new to DGI do this.
Yes, I have three dividend-related indicators: consistency, growth, and safety. However, they are no more important than the other fundamental signals. Remember, past dividend performance is NOT indicative of future performance! DO NOT ANCHOR!
What matters is the overall all health of the company. You can have the greatest dividend history in the world… but if the underlying fundamentals are deteriorating and tell a different story, that history is worthless—it can be gone overnight. Develop a well-rounded and balanced process!
One of the knocks on the F-score is that it is to simple. I would argue that simplicity is the beauty of the F-score. Yes, you sacrifice a bit of depth in your analysis, but that can be a good tradeoff for folks who have limited time to devote to investing… and a simple process is always better than no process!
I would argue that creating your own DGI variation of the F-score process will enable you to:
The Piotroski F-score model provides a logical, consistent, and methodical process for identifying high-quality, undervalued stocks—a process with the potential to deliver alpha to value investors.
This pure-value strategy is predicated on the idea that accounting-based fundamental analysis can identify potential future winners based on nine signals in three fundamental areas:
While the out-of-the-box F-score model is not a perfect fit for dividend-growth investing, I would argue that it provides a conceptual framework and a great starting point. Obviously, you will need to adapt and tailor it to fit the DGI strategy and your unique approach.
As such, F-scores can improve your dividend-growth investing—from both a conceptual (process framework) and practical (blueprint) perspective.
The One Really Big Thing
The one really big thing you need to takeaway from our look at the F-score model is that you absolutely positively must have a process—one that includes a method for systematically analyzing the fundamental health of companies.
Having and using an investing process WILL improve your dividend-growth investing!
Again, and not to beat a dead horse, what is absolutely critical is that you develop a logical, consistent, methodical process for your investing—one you understand, can repeat, and can stick with over the long run.
Otherwise, you’re just running with the herd, grasping at shiny objects, and throwing Jello at the wall to see what sticks… none of which make for a good long-term investing plan!
When you understand your process, you will find peace and the confidence to stick with it no matter what the market throws at you or the herd does!
Piotroski, J. D. (2002). Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, The University of Chicago Graduate School of Business.
Turtle, H. J., & Wang, K. (2017). The value in fundamental accounting information. Journal of Financial Research.
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