Value Investing Research: O-Score and Distress Risk

/Value Investing Research: O-Score and Distress Risk

Value Investing Research: O-Score and Distress Risk

By | 2017-08-18T16:53:50+00:00 July 7th, 2015|Value Investing Research, Yahoo Tickers, $vlue, $syld, $iwd|8 Comments

Book-to-Market Equity, Distress Risk, and Stock Returns, by Griffin and Lemmon (2002 Journal of Finance) investigate the relationship between value premiums and distress risk.  There are two schools of thought on the value premium, or the large spread in realized returns between cheap stocks and expensive stocks. On the one hand there is the “risk-based” story for the value premium, which suggests that value stocks are subject to higher risk of distress. On the other hand, the “mispricing story,” as it relates to the value premium, suggests that investors overreact to recent bad news and undervalue cheap stocks, and overreact to recent good news and overvalue expensive stocks. This paper investigates the alternative hypotheses and lets the data speak.

Bottomline: The spread in returns between cheap and expensive firms, given they are classified as “high distress,” is almost double the traditional value premium. And much of the return is driven by expectation changes around earnings announcements (that is, the market is “surprised” by how well the cheap high distress firms do). A win for value investing.

Highest distress risk, as proxied by Ohlson’s (1980) O-score, which is described below:

Griffin and Lemmon 2002

According to O-Score metrics, growth stocks (e.g., low B/M) have similar distress risk when compared with cheap stocks (e.g., high B/M). In the extreme distress category (marked in blue below), cheap stocks are much less distressed than the expensive stocks. This empirical finding is puzzling for the “risk-based” argument for the value premium, since expensive  stocks are actually more distressed, on average, than cheap stocks, in the extreme distress category. Weird.

cheap and distress

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.


But perhaps the most extreme distress firms have odd return patterns that can explain this anomaly through the lens of rational asset pricing?

Not exactly…

In the table below the authors tabulate the annual B&H returns associated with various cuts on distress and value. Value investing always wins, even after controlling for distress. And value investing REALLY wins among the most distressed firms. Oddly enough, expensive firms that are distressed earn 14.44% LESS than cheap firms that are distressed. So given equivalent distress levels, or “risk,” we should see similar returns…

cheap expensive and distress

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

Time to avoid the noise and get back to value investing!

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About the Author:

Wes Gray
After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes,, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.
  • Shyam Sunder

    What bugs me is that there is no explanation for the multipliers. Where did the authors get the magic 6.03, 1.02, etc. multipliers from?

  • Hi Shyam,

    The explanation is in the source paper:

  • Shyam Sunder

    Wouldn’t these numbers change if a dataset outside of 1970-76 is considered?

  • Phil Whittington

    Does this conflict with the Piotroski paper? That showed that high B/M firms (ie, value firms) performed better when you weeded out the “worst” firms (ie, most distressed) (based on the Piotroski score).

    Or is this different because it’s holding distress constant, and simply showing that cheap distressed firms do better than expensive distressed firms?

  • Phil,

    The cheapest 1/3, junkiest 1/5 firms outperform on annual B&H vs. cheap 1/3 least junky 1/5 firms by around 3.65 (20.8-17.15). So in some sense, yes, this conflicts with Piotroski and the general tenor of our own work, which extends Piotroski’s work–hunt in the cheap fish barrel, and try to find the non-rotten cheap fish.

    How can we reconcile or explain the difference?

    Well, we haven’t replicated and reverse engineering this specific paper, so we can really directly address the question, but there are some methodological choices that likely explain the ‘noise.’

    First, they cut the “cheapness” into terciles, which is a very rough cut on value. A lot can happen when you go from top 33% cheap to top 20% to top 10%. Heck, I’d argue you aren’t really value investing unless you are in the bottom 10% of the universe, but that’s just me.

    Second, the O-score isn’t exactly a “quality” metric, such as Piostroski’s F-score, or our various economic moat indicators/metrics we’ve developed. That doesn’t mean O-score is bad, but it just means that a poor O-score may tell you that a firm is a total turd, but a strong O-score may not tell you this is a hiqh-quality gem. In fact, I don’t think O-score tells you much when you are on the hunt for what to buy. The O-score is more focused on what NOT to buy.

    Anyway, these are some quick answers to your question. And as I mentioned in the comment, unless we did a full reverse-engineering of this specific paper, I can’t say definitely why the results don’t jive with a lot of other value investing research. However, one point is clear–buy cheap stuff 🙂

  • Phil Whittington

    Thanks Wes. That makes sense to me and I appreciate you taking the time to answer my question.

  • Doug

    I think what’s even more interesting than the value-growth disparity increasing with higher O-score, is that among the value stocks performance actually seems to improve with higher distress risks. This intra-value disparity seems to exist despite the high-O value stocks having worst quality metrics and lower momentum than the low-O value stocks. It’s true that the high-O value stocks have slightly higher value than the low-O value stocks, but it doesn’t seem enough to explain the return discrepancies. I’d posit two possible explanations:

    1) The high-O stocks do seem to have significantly smaller market capitalization. This is in line with previous research showing that the value effect is strongest among microcaps.

    2) Maybe high-O value stocks are simply the cockroaches of the stock market. Spurned by investors, with financials in shambles, but the fact that they’re still standing indicates some sort of X factor that helped them survive. Management with unusually high psychological grit or commitment to the company. A business model that’s inherently protected from competition. Maybe like the Red Army after Stalingrad, they’re not particularly well-funded, equipped or organized, but they’re just plain battle-hardened.

    I don’t think this would really apply to the high-O growth stocks. They’ve still had on average triple digit three year returns. They may be past the peak, but things probably still look pretty good. Investors, management, employees, even clients are still mostly chasing a rocket ship. That’s the type of “hot money” that’s quick to jump ship at the first sign of distress.

  • Maarish

    What about the GNP price level mentioned?
    Shouldn’t it be Log(Total Assets/GNP price level index)?