Going-Concern Radar — Lowest Altman Z-Scores in the S&P 500

What you’re looking at

In 1968, Edward Altman published the first practical bankruptcy-prediction model in The Journal of Finance. He fed five financial ratios into a discriminant analysis and showed that a simple weighted sum could classify companies as bankrupt or non-bankrupt with surprising accuracy — about 95% one year before filing, and 72% two years before. The model has been re-validated dozens of times across decades and markets. It’s not perfect, but it’s the closest thing forensic accounting has to a universally-recognized distress meter.

This list is the S&P 500 companies whose most recent Altman Z-Score sits below 1.81 — the threshold Altman himself identified as the “distress zone” in the original paper, where the bankruptcy-prediction accuracy was highest. Above 2.99 is the “safe zone.” Between 1.81 and 2.99 is the “grey zone.” Below 1.81 is where companies are statistically much more likely to fail within the next two years than the broader market.

The list is sorted from lowest score upward — so the top of the table is the most distressed.

The five ratios, plain English

Altman’s original Z-Score combines five ratios, each weighted by Altman’s original 1968 coefficients (the model has been re-estimated since, but the original is still the most-cited).

X1 — Working Capital / Total Assets. Liquidity. How much of the asset base is short-term and unencumbered by current liabilities. Companies headed for distress have been running this down for years before they fail.

X2 — Retained Earnings / Total Assets. Cumulative profitability. Young companies with limited operating history score low here by construction; mature companies that have been bleeding for years also do. Both populations have elevated failure rates.

X3 — EBIT / Total Assets. Operating profitability. The most important ratio in the model by weight. Companies that can’t generate operating income relative to their asset base aren’t going to survive long.

X4 — Market Value of Equity / Book Value of Liabilities. Market’s verdict on solvency. The market often spots distress before the financials confirm it — equity collapses, the ratio plunges, and the model flags accordingly. Critically, this is the only ratio in the model that’s forward-looking (uses market value), which is why the model can fire warnings before the income statement catches up.

X5 — Sales / Total Assets. Asset turnover. Are the assets generating sales? A bloated balance sheet that isn’t producing revenue is a death-spiral pattern.

Altman’s weights: Z = 1.2·X1 + 1.4·X2 + 3.3·X3 + 0.6·X4 + 1.0·X5. The full ratio is published in every accounting textbook and any number of online calculators. We compute it from the company’s own 10-K and most-recent market data.

How to read this list

A score below 1.81 means the company sits where Altman observed sharply elevated failure rates. That doesn’t mean failure is coming — most distressed-zone companies don’t go bankrupt — but the base rate of failure within two years is substantially higher than for companies in the safe zone.

The interpretation by score band:

• Negative (below 0): Severe distress. The model’s strongest signal. Many companies at this level have already been through a restructuring, have negative book equity, or are subsidiaries of holding companies where the score is misleading. Investigate before drawing conclusions, but treat as a major warning.
• 0 to 1.0: High distress. The classic pre-bankruptcy zone. Companies here typically have several of: declining EBIT, eroded book equity, low working capital, weak sales/assets. The combination is what the model is reacting to.
• 1.0 to 1.81: Distress zone. Still risky, but the failure-rate is lower than the deeper bands. Often companies on the way down (or up) from one of the more severe categories.

What this list won’t tell you:

• Whether the company will actually fail. Altman’s accuracy is measured across a sample. For any individual company, the score is a probability, not a verdict.
• Whether the stock is a short. Some distressed-zone companies are being acquired or restructured. Others have already had their equity wiped out and trade at near-zero. Direction depends on the catalyst, not the score.
• Sector-adjusted distress. Banks and other financial-sector companies have balance sheets that don’t fit Altman’s industrial assumptions. The original Z-Score isn’t built for them. A bank scoring low here is technically valid but interpretively suspect.

Why this list moves slowly — except when it doesn’t

Z-Score updates whenever the company’s annual financials update — roughly once a year per ticker. The X4 component (market value of equity / book liabilities) is the exception: it updates whenever the market price moves materially. A company that was in the safe zone last year can drop into distress when its stock loses 60% of its value, even if the operations haven’t changed.

That market-value sensitivity is the model’s secret weapon and its biggest weakness. It lets Z catch distress that the income statement is too slow to reveal. It also means a Z-Score that just dropped into the distress zone is often telling you more about market sentiment than about the underlying business. Read the company’s own filings before deciding which.

How we use this list internally

Filing.fyi’s discipline for distressed-zone names:

1. Read the most recent 10-K’s risk factors. Distress is almost always disclosed there, often in the auditor’s “going concern” language.
2. Check the value-trap-radar list. Companies that are both distressed and show aggressive accounting are statistically the most likely to surprise on the downside.
3. Look at the trend. A Z-Score that’s been stable in the distress zone for three years tells a different story than a Z-Score that just dropped 4 points.

We generally avoid building positions in distressed-zone names unless the catalyst is specific and short-dated — a confirmed asset sale, a restructuring with binding terms, an acquirer who has signed an LOI. Distressed-zone companies that go up are rarer than the ones that don’t.

Cross-references

• value-trap-radar — high Beneish M-Scores. Names appearing on both lists are the highest-risk cohort.
• highest-piotroski — the strength side. The intersection of distressed Z and weak Piotroski is a name to avoid.

Common questions

A name I own is on this list. Should I sell? Not because of this list alone. Read the company’s most recent 10-K’s risk factors. Check whether the score is improving or deteriorating quarter over quarter. Some distressed-zone names are turnarounds that will work; many aren’t. The score is a screen, not a verdict.

Why are some well-known names here? Companies in cyclical industries spend stretches of every cycle in the distress zone — autos in 2008-2009, energy in 2015-2016, retail every other year. The Z-Score is computed as-of the company’s last full fiscal year; it can lag a recovery. Always cross-check with the most recent 10-Q if you’re using this list operationally.

What about a Z-Score above the threshold but trending down? That’s the more interesting signal, and it’s why each Filing.fyi ticker hub shows the time series, not just the current value. A Z-Score that’s dropped from 5.0 to 2.1 over four years isn’t in the distress zone yet but is heading there. The trend has more predictive power than any one point.

Why is this list mostly small-cap-ish names even though we screen the S&P 500? Survivor bias. The S&P 500 selects on size and stability. Companies that spend long stretches in distress generally get removed from the index. The names that remain on this list are usually either (a) recent additions whose distress is recent, (b) very-large companies whose distress is offset by scale, or (c) companies in industries where distress-zone scores are structurally normal (capital-heavy industrials, certain utilities, recent IPOs). Investigate which case applies to any name you care about.