Stocks Wey Get Highest Days To Cover Now

Days to cover na how dem measure whether short position don full ground: shares wey dem sell short divide by di stock average daily volume, wey be how many full trading days di shorts go need to buy back dia whole position. Dis page dey rank di stocks wey get di highest days to cover from di latest exchange-reported short-interest settlement, and e dey show di trap wey every days-to-cover leaderboard dey fall inside. Di very top of one raw list na liquidity artifact, no be crowded trade. Di settled column dey tell you which twice-monthly print you dey read, and di page dey refresh as new settlements land.

Di highest days-to-cover stocks wey dey now

Days to cover (wey dem also dey call am short interest ratio) na fraction: shares short dey up, average daily share volume dey down. Dis na di highest readings for di latest settlement wey 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

Di one wey dey lead now, IVPAF, print 146.9 days to cover as at di 2026-06-30 settlement: 105.49 million shares short against just 0.72 million shares of average daily volume. For dat pace, di short position equal well pass one hundred full sessions of di stock entire tape. If you scan di ticker column, pattern go show: di top of raw days-to-cover list full with foreign and thinly traded names, and several of dem dey end with F (na di OTC symbol suffix for foreign ordinary share). Even di last row wey dem show still dey read 21.9 days. Dis no be crowded trades for squeeze sense. Dem na small short positions wey dem measure against almost no volume.

Why the raw top of the list na liquidity artifact

Days to cover na ratio, and ratio go blow up when the bottom number near reach zero. Group the whole settlement file by how much each stock dey trade and the mechanism go show for 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 dey clear for low single digits across every band, from 1.3 days among the ones wey trade pass, reach 2.8 for the moderate band. The maximum column dey tell the real story. For the most liquid band, stocks wey dey trade twenty million shares per day and above, the highest days to cover reach 8.4; for the very-thin band e reach 1000, pass the 16021 names wey dey trade under 200,000 shares per session. The extreme readings dey live entirely among stocks wey almost nobody dey trade, where small short position divide by near-zero volume go produce big number. Days-to-cover screen wey worth reading go open with liquidity floor, not without one.

Di highest days to cover among liquid stocks

Put real liquidity filter, five million shares of average daily volume, and di leaderboard go turn to names wey you fit actually trade and recognise.

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

Wit di floor don rise, MPT dey lead at 16.9 days to cover: 138.11 million shares short against 8.16 million shares of daily volume. Dis na di list wey anybodi wey dey watch squeeze go really mean by "high days to cover": heavily traded stocks wia di short position big pass di stock own tape. Di last row here still dey read 8.4 days, several multiples of di 1.8-day median across all liquid names inside di receipts wey dey below. Di most-shorted leaderboard rank di same settlement file by raw shares short instead, different axis wey dey bring out mega-caps wit big positions wey still clear sharp sharp.

Wetin dey happen, crowd dey grow or e dey comot?

One single settlement na just one frozen picture. The same file dey reach back years, so the next question, how today's liquid leaders take reach where dem dey, get data answer. This panel dey trace 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 dey follow the current leaders backward, so the latest row match the liquid table above: 16.9, 11.5 and 10.9 days. Read each column top to bottom and the texture wey one snapshot dey hide go show. Crowding for this scale dey build and dey unwind across settlements, over weeks and months, no be overnight, and one name fit sit for double-digit days to cover for one whole quarter without anything dey resolve. Half of squeeze-watching na to know whether you dey look at fresh arrival or long-term resident, and how squeeze mechanics take work dey explain wetin must happen before one high reading go matter at all.

How this list na im take dey build, and how to read am for real

Numbers first, then the warnings wey dey follow 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 get mostly names wey no dey trade well. The latest settlement carry 22207 tickers with positive days-to-cover reading, out of which 19005 dey trade under one million shares per day and only 947 clear the five-million-share floor. Raw "highest days to cover" sort dey answer question about the thin many, not the liquid few.
• Median crowding low even among liquid names. The typical liquid stock show 1.8 days to cover, so the leaderboard names above run many multiples of the ordinary reading. High number na genuinely unusual one once you strip out the liquidity artifact.
• The data old by construction. Settlements be exchange-reported twice every month and dem dey publish on lag, so the print wey you dey read don already old for days before e reach screen, and positions don fit don move since then.
• One symbol dey excluded by name inside the SQL. One ticker inside the current file recently change from one company to newly listed one, and vendor feeds fit mix the two entities under the shared symbol, so every query here drop am instead of to risk misattributed row.
• High days to cover na description, not verdict. Crowded short na precondition for squeeze, never prediction of one. Most heavily shorted names never squeeze, and the ratio alone no fit separate the future squeeze from the company wey the market don correctly diagnose.

Highest days to cover FAQ

Which stock get the highest days to cover now?

If you just sort the latest settlement raw, IVPAF dey top the list at 146.9 days, but e be one thinly traded name wey the ratio come from near-zero volume. Among stocks wey really dey liquid (five million shares per day and above), MPT dey lead at 16.9 days. Both tables dey refresh as new settlements publish.

Wetin be high days to cover ratio?

Across liquid names, the median dey around 1.8 days, so anything wey dey mid-single digits don already high and double-digit readings dey rare. Values wey dey dozens or hundreds almost always come from thinly traded stocks wey the average-volume denominator small, no be say the short position unusually big.

Why thinly traded stocks dey show this kind high days to cover?

Days to cover na shares short divided by average daily volume. When one stock hardly dey trade, that denominator dey close to zero, so even small short position go produce huge ratio. The liquidity-band panel wey dey up there dey show the maximum reading dey climb from single digits among heavily traded stocks go reach hundreds among the thinnest ones.

Abeg, high days to cover mean say short squeeze dey come?

No. E be precondition, no be prediction. Crowded exit fit matter if buying pressure show, 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 you read intent into any single number.

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