VALUE: After Hours (S07 E17): Analysis of The Four Formulas: Piotroski, Magic, Acquirer’s, Conservative

During their recent episode, Taylor, Carlisle, Schwartz and Hanauer discussed Analysis of The Four Formulas: Piotroski, Magic, Acquirer’s, Conservative. Here’s an excerpt from the episode:

What we mean with formula investing is basically simple stock screeners that are aiming on outperformance, even for retail investors. What we did was we tested four very popular investing formulas, the F-score by Piotroski, The Magic Formula, which is probably known to most of the audience from the little book that beats the market and consequently also your formula, The Acquirer’s Multiple, Tobias.

Tobias: Good call, fellas.

Jake: Yeah. [laughs]

Marcel: Definitely. And also, The Conservative Formula from Blitz and Van Vliet. We try to bring all those formulas together on a unified framework really where we tested them on an extensive period of time. So, we used US data from 1963 until end of 2022, and thereby, we were able to compare them also against each other but also test them for time. So, we really– [crosstalk]

Tobias: Let’s talk a little bit about–

Jake: How would zig do during the civil war? Because everyone wants to know.

Tobias: I can’t say that. Can’t say the tickers. Otherwise, I put-

Jake: The Acquirer’s Multiple.

Tobias: -the whole thing through compliance. Let’s talk a little bit about this. So, the F-score is the Piotroski F-score. Just remind us what is in the F-score or roughly how the F-score works.

Matthias The F-score is like an indicator of financial fundamental strength. It’s like the sum of nine binary indicators. It’s about the profitability of a company, the probability growth, the liquidity. Like, if it can surf its debt or also if it’s issue on new shares or not. I think leverage is also included. I think it was, I think, defined in 2000 the paper came out and it was seen as the other side of value. But value measures like book to price. You buy deep value and do not look that much about the fundamental strength. So, it was complementary to the valuation part having also something that is looking at the fundamental strength for a firm.

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How Each Formula Was Adapted for the Study

Tobias: Did you have to adapt that for the data set that you looked at?

Matthias: No. I think we followed closely what is done in the original paper. Maybe some of the details we had to adjust, but we tried to stick as close as possible to the original formulas. But I think we had some adjustments regarding the universe that we had tested the formulas. Of course, we updated the sample length, so we end in 2022. But also, we want to really have comparability across formulas, but maybe masala can add a bit on that.

Marcel: Yeah. So, basically, what we try to achieve is a comparable stock universe for all formulas. I think Piotroski was subsampling first for high book to market ratio stocks so far value stocks and use that subsample, where he applied his nine binary signals on. And to not use subsamples, but the same stock universe for really old formulas. We tried to make a ranking for the formulas course and for the F-score. We basically 50/50 weighted the nine signals and the value factor, so just to make them a little bit more comparable.

Tobias: What’s The Conservative Formula? That’s not one that I’m so familiar with.

Matthias: It’s inspired by a paper of my colleague Pim van Vliet. So, I work for Rubicon. It’s a global asset management firm headquartered in the Netherlands and also founded in the Netherlands. But next to my position, there is a quant researcher. I’m also affiliated researcher at Technical University, as Marcel said.

The Conservative Formula combines low risk measured by low volatility with momentum and what we call net-payout yield. This is a measure that also looks at dividends, but also at share buybacks. So similar to Marc Faber shareholder yield measure.

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Key Findings and Performance Breakdown

Tobias: And The Magic Formula, everybody will know it’s return on invested capital as one factor, and then EBIT earnings yield on enterprise value and then Acquirer’s Multiple as mine, EBIT on EV or operating income on EV. So, what were the findings, gents, just in broad terms? Marcel or Matthias?

Matthias: Yeah. Maybe Marcel can go.

Marcel: I haven’t gotten the question. Sorry.

Tobias: Oh, sorry. What were the findings?

Jake: Which one was the best?

Marcel: Okay. [chuckles]

Tobias: Without putting too fine a point.

Marcel: Yeah. No, our key findings were basically in line with the books and the original findings also for longer time period. So, we were witnessing monotonically increasing returns when we were sorting the stocks into decile portfolios. So, the top decile portfolio was always able to outperform the product market, and also the bottom portfolio and also statistically significant and had high return spreads which were not explained by the CAPM alpha. That was a main finding. We also found that it was not due to some magic, but more due to an efficient exposure to well established factors. So, momentum, value, size. So, most of the returns were explained by well-established asset pricing factors.

On the second part of the research, we were taking a bit more of a do-it-yourself perspective, how we called it. So, really the retail investor perspective where we built long only portfolios of 40 stocks and tested whether they were still able to outperform the market also in the post-2000 period. What we found there was that all formulas were able to outperform the market in raw and risk adjusted terms, but we also noticed some performance decay, especially during the most recent years from the sample.

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