Highest Days to Cover Stocks Right Now

Days to cover measures how crowded a short position is: shares sold short divided by the stock's average daily volume, which is how many full trading days the shorts would need to buy their entire position back. This page ranks the stocks with the highest days to cover from the latest exchange-reported short-interest settlement, and shows the trap every days-to-cover leaderboard walks into. The very top of a raw list is a liquidity artifact, not a crowded trade. The settled column tells you which twice-monthly print you are reading, and the page refreshes as new settlements land.

The highest days to cover stocks right now

Days to cover (also called the short interest ratio) is a fraction: shares short on top, average daily share volume on the bottom. Here are the highest readings in the latest settlement that clear a minimal 500,000-share average-volume floor.

SELECT ticker,
       round(days_to_cover, 1) AS days_to_cover,
       round(short_interest / 1e6, 2) AS shares_short_m,
       round(avg_daily_volume / 1e6, 2) AS avg_daily_volume_m,
       toString(settlement_date) AS settled
FROM global_markets.stocks_short_interest
WHERE settlement_date = (SELECT max(settlement_date) FROM global_markets.stocks_short_interest)
  AND avg_daily_volume > 500000
  AND days_to_cover > 0
  AND ticker NOT IN ('SPCX')
ORDER BY days_to_cover DESC, ticker
LIMIT 12

The current leader, IVPAF, prints 146.9 days to cover as of the 2026-06-30 settlement: 105.49 million shares short against just 0.72 million shares of average daily volume. At that pace the short position equals well over a hundred full sessions of the stock's entire tape. Scan the ticker column and a pattern appears: the top of a raw days-to-cover list fills with foreign and thinly traded names, several ending in F (the OTC symbol suffix for a foreign ordinary share). Even the last row shown still reads 21.9 days. These are not crowded trades in the squeeze sense. They are small short positions measured against almost no volume.

Why the raw top of the list is a liquidity artifact

Days to cover is a ratio, and a ratio blows up when its denominator shrinks toward zero. Group the entire settlement file by how much each stock actually trades and the mechanism is visible in one panel.

SELECT multiIf(avg_daily_volume >= 2e7, '1 Very liquid (20M+ ADV)',
               avg_daily_volume >= 5e6, '2 Liquid (5-20M ADV)',
               avg_daily_volume >= 1e6, '3 Moderate (1-5M ADV)',
               avg_daily_volume >= 2e5, '4 Thin (200k-1M ADV)',
                                        '5 Very thin (<200k ADV)') AS liquidity_band,
       count() AS names,
       round(quantileDeterministic(0.5)(days_to_cover, cityHash64(ticker)), 1) AS median_dtc,
       round(max(days_to_cover), 1) AS max_dtc
FROM global_markets.stocks_short_interest
WHERE settlement_date = (SELECT max(settlement_date) FROM global_markets.stocks_short_interest)
  AND days_to_cover > 0
  AND ticker NOT IN ('SPCX')
GROUP BY liquidity_band
ORDER BY liquidity_band

The median name clears in low single digits across every band, from 1.3 days among the most heavily traded stocks to 2.8 in the moderate band. The maximum column tells the real story. In the most liquid band, stocks trading twenty million shares a day and up, the highest days to cover reaches 8.4; in the very-thin band it reaches 1000, over the 16021 names that trade under 200,000 shares a session. The extreme readings live entirely among stocks almost nobody trades, where a modest short position divided by near-zero volume produces an enormous number. A days-to-cover screen worth reading opens with a liquidity floor, not without one.

The highest days to cover among liquid stocks

Apply a real liquidity screen, five million shares of average daily volume, and the leaderboard becomes tradeable, recognizable names.

SELECT ticker,
       round(days_to_cover, 1) AS days_to_cover,
       round(short_interest / 1e6, 2) AS shares_short_m,
       round(avg_daily_volume / 1e6, 2) AS avg_daily_volume_m
FROM global_markets.stocks_short_interest
WHERE settlement_date = (SELECT max(settlement_date) FROM global_markets.stocks_short_interest)
  AND avg_daily_volume >= 5000000
  AND days_to_cover > 0
  AND ticker NOT IN ('SPCX')
ORDER BY days_to_cover DESC, ticker
LIMIT 12

With the floor raised, MPT leads at 16.9 days to cover: 138.11 million shares short against 8.16 million shares of daily volume. This is the list a squeeze-watcher actually means by "high days to cover": heavily traded stocks where the short position is large relative to the stock's own tape. The last row here still reads 8.4 days, several multiples of the 1.8-day median across all liquid names in the receipts below. The most-shorted leaderboard ranks the same settlement file by raw shares short instead, a different axis that surfaces mega-caps with huge positions that still clear quickly.

Is the crowding building or fading?

A single settlement is one frozen frame. The same file reaches back years, so the next question, how did today's liquid leaders get here, has a data answer. This panel traces the current liquid top three backward across the last eight settlements, about four months.

WITH dates AS (
    SELECT DISTINCT settlement_date AS d
    FROM global_markets.stocks_short_interest
    ORDER BY d DESC
    LIMIT 8
),
top3 AS (
    SELECT ticker, row_number() OVER (ORDER BY days_to_cover DESC, ticker) AS rank
    FROM global_markets.stocks_short_interest
    WHERE settlement_date = (SELECT max(d) FROM dates)
      AND avg_daily_volume >= 5000000
      AND days_to_cover > 0
      AND ticker NOT IN ('SPCX')
    ORDER BY days_to_cover DESC, ticker
    LIMIT 3
)
SELECT toString(settlement_date) AS settlement_date,
       maxIf(round(days_to_cover, 1), ticker = (SELECT ticker FROM top3 WHERE rank = 1)) AS leader_dtc,
       maxIf(round(days_to_cover, 1), ticker = (SELECT ticker FROM top3 WHERE rank = 2)) AS second_dtc,
       maxIf(round(days_to_cover, 1), ticker = (SELECT ticker FROM top3 WHERE rank = 3)) AS third_dtc
FROM global_markets.stocks_short_interest
WHERE ticker IN (SELECT ticker FROM top3)
  AND settlement_date IN (SELECT d FROM dates)
GROUP BY settlement_date
ORDER BY settlement_date

The columns follow the current leaders backward, so the latest row matches the liquid table above: 16.9, 11.5 and 10.9 days. Read each column top to bottom and the texture a snapshot hides comes through. Crowding at this scale builds and unwinds across settlements, over weeks and months, not overnight, and a name can sit in double-digit days to cover for an entire quarter without anything resolving. Half of squeeze-watching is knowing whether you are looking at a fresh arrival or a long-term resident, and the squeeze mechanics explain what has to happen for a high reading to matter at all.

How this list is built, and how to read it honestly

Numbers first, then the caveats that ride along with every row above.

SELECT count() AS tickers_reported,
       countIf(avg_daily_volume >= 5e6 AND days_to_cover > 0) AS liquid_names,
       countIf(avg_daily_volume < 1e6 AND days_to_cover > 0) AS thin_names,
       round(quantileDeterministicIf(0.5)(days_to_cover, cityHash64(ticker), avg_daily_volume >= 5e6), 1) AS liquid_median_dtc,
       toString(max(settlement_date)) AS settled
FROM global_markets.stocks_short_interest
WHERE settlement_date = (SELECT max(settlement_date) FROM global_markets.stocks_short_interest)
  AND days_to_cover > 0

• The file is mostly untradeable names. The latest settlement carries 22207 tickers with a positive days-to-cover reading, of which 19005 trade under a million shares a day and only 947 clear the five-million-share floor. A raw "highest days to cover" sort answers a question about the thin many, not the liquid few.
• Median crowding is low even among liquid names. The typical liquid stock shows 1.8 days to cover, so the leaderboard names above run many multiples of the ordinary reading. A high number is genuinely unusual once the liquidity artifact is stripped out.
• The data is dated by construction. Settlements are exchange-reported twice a month and publish on a lag, so the print you are reading is already days old before it reaches a screen, and positions may have moved since.
• One symbol is excluded by name in the SQL. A ticker in the current file was recently reassigned from one company to a newly listed one, and vendor feeds can mix the two entities under the shared symbol, so every query here drops it rather than risk a misattributed row.
• High days to cover is a description, not a verdict. A crowded short is a precondition for a squeeze, never a prediction of one. Most heavily shorted names never squeeze, and the ratio alone cannot separate the future squeeze from the company the market has correctly diagnosed.

Highest days to cover FAQ

What stock has the highest days to cover right now?

On a raw sort of the latest settlement, IVPAF tops the list at 146.9 days, though it is a thinly traded name whose ratio comes from near-zero volume. Among genuinely liquid stocks (five million shares a day and up), MPT leads at 16.9 days. Both tables refresh as new settlements publish.

What is a high days to cover ratio?

Across liquid names the median is about 1.8 days, so anything in the mid-single digits is already elevated and double-digit readings are rare. Values in the dozens or hundreds almost always come from thinly traded stocks where the average-volume denominator is tiny, not from unusually large short positions.

Why do thinly traded stocks show such high days to cover?

Days to cover divides shares short by average daily volume. When a stock barely trades, that denominator is close to zero, so even a small short position produces a huge ratio. The liquidity-band panel above shows the maximum reading climbing from single digits among heavily traded stocks to the hundreds among the thinnest.

Does high days to cover mean a short squeeze is coming?

No. It is a precondition, not a prediction. A crowded exit can matter if buying pressure arrives, but most high-days-to-cover stocks never squeeze. Pair the reading with the full days-to-cover guide and the shares-short leaderboard before reading intent into any single number.

Every table here is a stored, versioned query over the exchange-reported short-interest file. Expand the SQL under any panel, or screen the full universe your own way on the Strasmore terminal.