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Polymarket’s Reported Earnings Edge: Read the Baseline First
Unpack the reported 78.5% versus 43.7% earnings result, the 75.9% beat-rate baseline, and what the comparison does—and does not—prove.
A September 2026 summary reports that Polymarket outperformed an analyst-consensus benchmark in a six-month earnings study: 78.5% correct beat-or-miss calls versus 43.7%. That is a substantial difference—but it is not evidence that Polymarket forecasts earnings-per-share amounts twice as accurately as analysts, or that following its favorites would have made money.
The comparison also has an important baseline: companies beat the earnings threshold 75.9% of the time. If that rate covers the same observations and outcome definition, always predicting a beat would have finished just 2.6 percentage points behind Polymarket. The headline advantage over analysts and the advantage over a simple default answer are very different numbers. Larry Swedroe’s September 2026 summary in Financial Advisor reports all three figures.
What the reported study compared
Swedroe attributes the findings to Beating the Earnings Game, an April 2026 study by Daniel Rabetti, Jiaqi Shao and Che Zhang. His account describes 469 contract settlements covering 383 U.S. companies, from September 2025 through February 2026. The market input was Polymarket’s closing probability on the day before the earnings announcement; the analyst input came from the Institutional Brokers’ Estimate System, or I/B/E/S. Both were compared with the eventual earnings outcome. Source
The forecasting target was binary: would a company beat a stated EPS threshold for a particular quarter? That is narrower than predicting the reported EPS amount, revenue, guidance or the subsequent stock return.
The figures below are secondary-reported study results, not an independently reproduced backtest.
| Reported figure | What it measures | What it does not measure |
|---|---|---|
| Polymarket: 78.5% | Share of beat-or-miss calls classified correctly | Whether every quoted probability was calibrated |
| Analyst benchmark: 43.7% | Share of benchmark beat-or-miss calls classified correctly | Accuracy of analysts’ EPS estimates in dollars |
| Actual beat rate: 75.9% | Share of observed outcomes that were beats | A forecast or investment return |
| Analyst-implied beat probability: 43.9% | Aggregate implied probability described in the summary | The 43.7% classification hit rate |
That last distinction explains the two September headlines. The September 21 article from 24/7 Wall St. emphasized classification accuracy. Its September 23 follow-up emphasized the observed beat rate versus the analyst-implied rate. 43.7% and 43.9% are not interchangeable.
There is also a methodological gap in the published summary: an EPS consensus is a dollar estimate, not inherently a probability. The summary does not specify the full conversion from analyst estimates into beat probabilities or the classification rule. Those details matter before treating the headline as a fully auditable comparison.
Why the 75.9% baseline matters
In a sample dominated by beats, high classification accuracy can come from favoring the common outcome. Under the same-observation assumption, Polymarket’s reported accuracy is 2.6 points above an always-beat rule, alongside its 34.8-point advantage over the analyst benchmark. These differences are calculated from rounded reported rates; they do not, by themselves, establish a statistically reliable edge.
This does not erase the result. It changes the question: how much information did market prices add beyond knowing that beats were common?
For probability forecasts, classification accuracy discards useful detail. A 51% forecast and a 95% forecast both become “beat” calls under a greater-than-50% rule, despite expressing very different confidence. A Brier score instead averages squared probability errors; calibration checks whether events assigned, for example, roughly 80% probability occur roughly 80% of the time. See Brier score versus calibration.
Likewise, comparing a 43.9% aggregate forecast with a 75.9% outcome rate can reveal an aggregate mismatch, but cannot establish calibration across probability ranges. A stronger evaluation would compare market and analyst probabilities with a historically estimated beat-rate baseline, fixed before the test period—not a probability chosen after seeing the outcomes.
Promising evidence, limited reach
Swedroe reports that direct comparison regressions continued to favor prediction-market probabilities after accounting for company characteristics such as size, analyst coverage and trading volume. That suggests the reported evidence goes beyond the headline hit rate. But it remains a short sample restricted to companies with active prediction markets, likely favoring larger, more liquid names. It does not establish performance for the entire listed-company universe or across many earnings cycles. Source
The proposed explanations include more frequent price updates and analyst incentive distortions, but the summary notes that mechanisms are inferred from observed patterns rather than directly measured. Expectations management is not a new hypothesis: a 2001 study of annual analyst forecasts from 1983–1998 documented estimates being walked down to beatable levels, particularly after 1992. That historical evidence supports the plausibility of the mechanism, not proof that it caused this Polymarket result.
Accuracy is not a trading return
A hypothetical strategy that buys every YES share at $0.90 and wins 75.9% of the time loses an average $0.141 per share before costs: average settlement value of $0.759 minus the $0.90 purchase price. Being right often is insufficient if the purchase price demands an even higher win rate. This is an illustration, not a reported strategy result.
Nor is a displayed probability necessarily executable. Polymarket’s price documentation says the display normally uses the bid–ask midpoint, switching to the last trade when the spread exceeds $0.10. A return test needs actual fills, available size and applicable costs, not just displayed odds.
For evaluating the earnings comparison, require the same EPS definition and threshold, synchronized pre-announcement inputs, explicit probability-conversion rules, and paired probability scores against a pre-specified baseline. The reported evidence favors Polymarket’s binary forecasts in this sample; the 78.5% headline alone does not establish broad analyst inferiority, calibrated odds or profitable bets.