What is the Piotroski F-Score?

The Piotroski F-Score

Those who have been studying the stock market, investing for a while or doing their research, have most likely heard of the Piotroski F-Score. If you have been following along and reading our articles, we mention the Piotroski F-Score a lot. We talk about it in our articles, videos and you will see it in many of our pre-built screens. It is a very popular investment tool and one you want to utilize during your investing journey.

Where did the F-Score come from?

The Piotroski F-Score was created by Joseph Piotroski. He started his academic career at the University of Chicago in 1999, just one year before publishing his famous paper; Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Now serving as a Professor of Accounting at Stanford University, he has been featured in many Accounting journals, and written many papers on his research into the world of Value Investing. His score is used to help investors “rank” their possible investments.

Investors and financial analysts have long sought reliable indicators to assess the financial health and future prospects of companies. Joseph Piotroski’s F-Score is one such tool that gained considerable attention. In this article, we will explain what the score is, the different components that make it up, and see if it lives up to its reputation of predicting companies performance.

What is the Piotroski F-Score

The Piotroski F-Score is a scoring system that evaluates companies based on nine fundamental accounting criteria. Each criterion receives a score of either 0 or 1. The sum of these nine criteria creates the final Piotroski F-Score for the company being evaluated. The higher the score, the better the companies financial stability should be, according to Piotrsoki. The criteria are divided into three main categories:

Profitability, Efficiency, and Operating Metrics:

  • Positive net income (1 point)
  • Positive operating cash flow (1 point)
  • Higher return on assets (ROA) compared to the previous year (1 point)
  • Positive cash flow from operations compared to net income (1 point)

Liquidity and Leverage:

  • Lower long-term debt-to-assets ratio compared to the previous year (1 point)
  • Higher current ratio compared to the previous year (1 point)
  • No dilution of shares (1 point)
  • Operating Efficiency and Quality of Earnings??
  • Asset Turnover ratio must be higher than it was a year ago (1 point)
  • Gross Margin must be higher than it was a year ago (1 point)

The Piotroski F-Score in Equities Lab

The below picture is what the Piotroski F-score formula looks like in Equities lab. Depending on what screening software you use, adding this formula into your screeners can be as easy as typing in “piotroski yearly” or as difficult as manually entering the mess of equations you see below. With Equities lab, you can easily add Piotroski’s F-Score and other complicated formulas into any screen by typing the name we have given it in Equities lab. Using our pre-made formulas and screens can save you a major headache and hours of time!

Companies with a perfect Piotroski F-Score

You may be wondering if it is possible for companies to have a perfect score. The answer is yes! Let’s use Equities lab to find out how many companies have a perfect Piotroski F-Score as of now. We created a screener, shown below, that looks for companies whose score is equal to 9 (a perfect score). There are a total of 62 companies that matched the criteria to have a perfect Piotroski F-Score.

In a bit we will explore how well companies with a perfect or near perfect score performed compared to those with lower scores. We will also compare those against the benchmark S&P 500 since the year 2000 to give us an idea of just how good, or poorly, they performed.

Do companies with a high score outperform the market?

There aren’t a massive number of companies that matched our perfect score screener. Let’s try to widen our results by looking at companies with a high Piotroski F score – those with scores greater than 7.

This time we got 378 matches, a much better number to work with. Next we backtest companies that match our screener criteria since the beginning of 2000.

From the picture above, I would say that at least so far, Piotroski’s score seems to work! Companies with a high Piotroski score (green line) got more than double the total returns of the S&P 500 (red line) over the backtested time period.

Below is another visual (where results are sorted by return), that might help you more easily see that overall we have more companies that gave us a positive return than a negative one.

Do perfect scores do better?

Let’s jump back to companies with a perfect score. Will they perform better than companies with scores of 7 or greater, since 2000?

When we backtested the perfect-score companies, we got almost double the returns than the companies with a score greater than 7! These companies did significantly better than those in our last screen.

It is safe to say that when we are looking at high or perfect Piotroski scores, the Piotroski F-score seems to work, rather well!

Average or below average Scores

Now that we have seen how companies with high and perfect Piotroski scores perform, let’s put Piotroski’s Score further to the test. If we screen for companies with average or low Piotroski scores, we would expect to see those companies do worse than those with high scores, if we want to prove Piotroski’s formula useful and effective.

Let’s screen for companies with a score of 5 or less.

Next we will backtest these companies since 2000:

Just as we expected (and hoped for), worse performance! This means that so far, Piotroski’s F-Score works; companies with a higher F-score perform better than those with a lower score (on average). Companies with a Piotroski score of 5 or less performed far worse than the S&P. The S&P had a total return of 574.3% while our average score companies got a total return of 190.2%. We still got a positive return with these companies, but certainly nothing to write home about.

What about companies with a rising piotroski score?

The results for companies with a growing F-score do not seem to be much different than simply screening for companies with a high score from the outset. In order to make the best performing screen, we need to only look for high Piotroski companies from day one. The score is highly accurate in finding companies that are going to underperform or even go bankrupt, so screening for companies with poor scores on day one will rarely result in a better return.

Expanding our options

A screen that only returns 62 results (companies with a perfect score) doesn’t really give us much room to add more parameters and build the best performing screen we can. Let’s go back to companies with a score greater than 7.

It makes a pretty big difference. We went from 62 results to 378. When we backtest this strategy, we give up a bit of the perfect score performance, but we gain the freedom to add more parameters and find the really great companies that we want for our long term investments.

Now let’s add some more parameters and see if we can get our total returns higher while still having a higher amount of results. First let’s try looking at large cap companies (those with a market cap larger than $10 billion).

Interesting! Companies with a Piotroski score higher than 7 and a large market cap did worse. Let’s try mid cap stocks, those with market caps between 2 and 10 billion, and then small cap stocks, about 300 million to 2 billion.

Both the mid and small cap companies got about the same results as when we didn’t add market cap parameters at all. However our large cap stocks performed quite poorly, so let’s filter those out and just look for small and mid cap since they performed better.

These results are better but let’s try to do even better! Let’s try something new. Our new parameter is shown in the picture below. It takes all the stocks, excludes companies with a market cap smaller than 100 million, measures their one year rate of return, and collates them by industry, taking the worst 25%.

Here are the results we got after adding in these parameters:

These are the kind of results we like to see! We started out at about 1200% total return and ended up with 2,154%!

Is a changing Piotroski F-Score a signal of future performance?

Rather surprisingly, a declining Piotroski F-Score is apparently good for a stock. Although this seems absurd and not the result we would expect, this makes sense when you consider the choices available to a stock with a Piotroski score of 9; it can stay the same, go down a little, or go down a lot. Conversely, a company with a Piotroski score of 0 has nowhere to go but up.

Below is an image of our changing Piotroski findings:

The results we got here are telling us that if your current Piotroski is 3, you are better off it it was higher last year then if it was lower last year. We can conclude that just testing for change in a companies Piotroski F-Score may not be helpful and can get a bit confusing.

Does the Piotroski F-Score work?

Throughout this article we have explored how companies with high, average, rising, and low Piotroski F-Scores perform over a long period of time. We have seen that they all do as we would expect them to. Companies with high scores perform better than those with average or low scores. Piotroski’s F-score overall seems to be a great predictor of a companies overall health and the general direction it is headed. Due to the complexity of the 9 components woven throughout the formula, a company that fits more criteria will perform better. The below image demonstrates what a 20% score looks like all the way up to a 90% score. The lower the score, the lower the line should be and vice versa. (It holds mostly true, through the test of time!)

According to Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers, 2% of the companies considered in his paper with the highest Piotroski score delisted for performance reasons, while 7-10% of the firms with a Piotroski score of 2 or lower also delisted. That is a pretty big difference and a reliable indicator of what stocks could potentially be delisted. Equities Lab does not have performance-based delisting, so we count the number of firms that lost more than 80% of their value within one year after matching and call that “faceplanting.” For firms that are delisted, the last available price was used as the value.

If you are in the position where your stock “face-planted”, remember it isn’t the same as it being delisted, though it is still traumatic to endure. You should check the odds that the stocks will catapult upwards (80% gain in one year) and that they will rocket to new heights (500% gain in one year). If an investor has a portfolio of two stocks, one of which faceplants and one of which catapults, the investor neither gains nor loses money. If an investor has a one-stock portfolio for two years and it face-plants the first year, then it would need to rocket upwards the second year to get the investor back to even. Another reason portfolio diversification should be a priority!

Below is another visual to show how companies with a score of 1 through 9 perform.

You can see that the lower the score the worse the companies performed, while the higher the score, the better the company performed. Further convincing us that Piotroski’s score is in fact effective in predicting a company’s future.

Here we have a picture that shows stocks with earnings, divided into columns based on their Piotroski score over the last 10 years.

Again, Piotroski’s F-Score proves itself effective. On average, the higher the score the better the company performs.

Does Piotroski’s F-score work alongside other factors, though? Let’s take a look!

Does the Piotroski score work with momentum?

Momentum is past stock performance, which is also important in determining future stock prices. More momentum is better, but Piotroski works regardless.

Does the Piotroski score work with value?

Using the simplest interpretation of value (Price to earnings) and choosing four sets of values: under 5, 5 to 20, 20 to 60, and over 60, it seems that Piotroski works everywhere except when the P/E is over 60.

Does the Piotroski score work better in some sectors?

Morningstar breaks its equities down into sectors as follows:

  1. Cyclical
    1. Basic Materials
    2. Consumer Cyclical
    3. Financial Services
    4. Real Estate
  2. Defensive
    1. Consumer Defensive
    2. Health Care
    3. Utilities
  3. Sensitive
    1. Communication Services
    2. Energy
    3. Industrials
    4. Technology

Taking on the top-level divisions first, with this term:

Piotroski seems to work well with all three types of companies. For the defensive companies, firms with a Piotroski of zero seemed to do surprisingly well, but that is the only thing of note other than that the zero Piotroski companies in the sensitive sector managed to lose more than 99% of their value. Ouch!

A summary of how well Piotroski did per sector is below. The concept of swap distance is used to describe how well each sector did. If the values were already in order, then no edits are needed. Otherwise, we count (approximately) how many swaps are required to put the values in order.


  1. Basic Materials – Worked well. The 0 Piotroski outperformed the 1, and the 5 outperformed the 6.
  2. Consumer Cyclical – A complete mess. The 2 and 9 had an insanely good performance, and the rest, other than 0 and 1, were mediocre. At least the 0 and 1 were terrible.
  3. Financial Services – OK. The 9 was bad, with values worse than 0 or 1. The 3 value was slightly worse than the 2 value. Other than that, all was well.
  4. Real Estate – A complete mess. Only the 5, 7, and 8 values made their investors any money, with all the other values having terrible performance.


  1. Consumer Defensive – OK. The lower values were worse, but the 9 was terrible, and the 6 value was worse than 4 or 5. The general trend was intact, though.
  2. Health Care – Worked well. The 9 was less than the 8, and the 0 was better than the 1. The trend, though, was beautiful.
  3. Utilities – A partial mess. The lower values were generally lower, but the 4, 5, and 0 had too good of results, with the 4 and 5 being good, and the 0 being decent. 9 was also bad.


  1. Communication Services – Good. The performance of the whole sector was ghastly, but the lower values were lower and the 9 was beautiful. The 5 was modestly bad.
  2. Energy – OK. The 8 and 9, while OK, weren’t better than the 6 and 7. The 0, 1 and 2 were all as horrible as one could want.
  3. Industrials – Perfect. The low values were terrible, and the high values great.
  4. Technology – Decent. The low values were terrible, with the 0 losing 97% and the 1 losing 100% (!) of the money invested. The values from 4 to 8 were all about the same, and 9 was slightly below that.


If you want to learn more about Piotroski’s F-Score, we have a video here for you to check out – don’t forget to like our videos and also leave any questions you might have in the comment section.

As a warning, we do not suggest jumping in and investing in every stock that you see the screener pop out, no matter how good the historical performance is. Do your due diligence and look into every potential investment you make.The screener is a tool to allow you to cut down your analysis time and give you a smaller pool of companies to look into, which is exactly what the Piotroski Score was designed for.

Don’t take our word for it, though (or anyone else’s)! With Equities Lab, you can test out Piotroski’s score, the Altman Z-Score, the Ascending Triangle, and so much more! Become a well versed and knowledgable investor today by emailing us at sales@equitieslab.com to get started with your free trial!