Skip to content

Squeeze Score

0-100 rank of heavily shorted US stocks by odds of a large move

The Tapeboard Short Squeeze Score is a 0-100 rank of heavily shorted US-listed stocks (short interest of at least 15% of float) by the odds of a large price move over the next 5-10 sessions. It is not a directional call: high-scoring names have historically been more likely to jump 20% and more likely to fall 20%.

In short
  • Gate: short interest >= 15% of float (latest published FINRA settlement, split-checked). Listed common stock, price >= $1, liquid, market cap >= $25M.
  • Score = 100 x (0.7 x percentile of 20-day volatility + 0.3 x percentile of 5-day float rotation), percentiles within the gated set. Borrow fee, days to cover and short-volume ratio are context only (weight 0).
  • Out of sample (Oct 2025 - Sep 2026), ranks 1-10 hit +20% within 5 sessions 16.6% of the time and fell 20% 12.0% of the time, vs 4.5% / 2.3% for all stocks.

How is Squeeze Score calculated?

Eligible if SI_pct_float >= 15% (and <= 120%), settlement <= 40 days old,
listed common stock, close >= $1, ADV20 >= 100k shares, median 20d dollar volume >= $500k,
market cap >= $25M, >= 60 daily bars with one in each of the last 5 sessions.

vol20 = population stdev of the last 20 daily log returns
rot5  = (sum of the last 5 sessions' volume) / float

Squeeze Score = 100 * (0.7 * pct(vol20) + 0.3 * pct(rot5))

pct(.) is the average-tie percentile rank within the day's eligible set.

Short interest is used as a gate, not a weight: it defines the population where short covering can amplify a move. Within that population the ranking uses realized volatility and float turnover, the two inputs that best separated large future moves out of sample. Percentiles replace z-scores so a single outlier cannot set the scale, and there is no decay multiplier. Weights were chosen on 2024-03 to 2025-09 data only and tested on later data.

What do traders use Squeeze Score for?

  • Finding heavily shorted names where a violent move (either way) is more likely than usual. The /short-squeeze-stocks leaderboard shows the ranked set daily with historical odds per rank bucket.
  • Sizing risk on a crowded short: the same names that squeeze also crash more often, so the odds cut both ways.
  • Separating setups from same-day movers: stocks already running today appear in a separate In play list with their own (mean-reverting) historical odds.

Worked example

Worked example: $GME
Squeeze score on $GME

Suppose $GME carries short interest of 21.4% of float (above the 15% gate), its 20-day volatility sits at the 90th percentile of the eligible set and its 5-day float rotation at the 60th. Its score is 100 x (0.7 x 0.90 + 0.3 x 0.60) = 81. Where that lands in the day's ranking maps to a historical odds bucket (for example ranks 11-25: about 13% chance of a +20% high and 7% chance of a -20% low within 5 sessions).

Live data: /stock/GME.

What are common pitfalls of Squeeze Score?

  • Short interest publishes twice a month, about 8-9 trading days after settlement, so the gate uses a reading that is typically 2-4 weeks old.
  • The score is not a buy signal. The median 5-day return of the top bucket has been slightly negative; the edge is in the size of moves, not their direction.
  • Reverse splits can corrupt SI %-of-float; settlements flagged for a split, or where the float changed more than 2x since settlement, are excluded rather than guessed.
  • Historical odds are frequencies from one out-of-sample year with wide confidence intervals, not guarantees.

Where this metric appears on Tapeboard

Squeeze score appears on every `/stock/{T}` page (numeric + 0-100 bar), the /scanner/squeeze leaderboard (top 25 daily), the /short-squeeze-stocks landing, and as a screener filter on /scanner.

Tapeboard surfaces this metric as a first-class screening filter. See the comparison pages at all Bloomberg alternatives for how Tapeboard's squeeze score surface compares against Koyfin, Finviz, TradingView, and Unusual Whales.

Related terms

  • Short Interest: FINRA short-interest reports settle bi-monthly with a publication lag of about 10 business days from the report date.
  • Utilization (Lending): Daily-published, sourced from broker-dealer stock-loan books.
  • Days To Cover: Higher DTC means a slower unwind. Above 5 days is a meaningful liquidity constraint on short covering; above 10 is severe.
  • Failures-To-Deliver (FTD): Bi-monthly SEC dataset, lag of about two weeks. Counts unsettled share volume per ticker per day.

Primary sources cited

Methodology last reviewed 2026-05-04 by Marcus Reilly, Editor at Tapeboard. Every claim on this page has a row in the citation registry. Glossary terms reverify on the Jan 15 / Apr 15 / Jul 15 / Oct 15 cron and any time the underlying primary-source publishes a methodology change. See methodology for the full fact-check process and corrections for the public correction log.

Disclaimer. This page is for educational and informational purposes only. Nothing on Tapeboard is investment advice. See the full risk disclaimer.