Highest Days to Cover Stocks Right Now

Days to cover dey measure how crowded short position be: shares wey traders sell short divide by stock average daily volume. Na the number of complete trading days wey short sellers need to buy back their full position.

This page rank stocks wey get the highest days to cover from the latest exchange-reported short-interest settlement. E also show the trap wey every days-to-cover leaderboard fit enter. The very top of raw list fit just be liquidity artifact, no be crowded trade.

The settled column tell you which twice-monthly print you dey read. The page go refresh as new settlements land.

Stocks wey get the highest days to cover right now

Days to cover (dem dey call am short interest ratio too) na fraction: shares wey dem short dey on top, average daily share volume dey for bottom. Na the highest readings for the latest settlement be these, after dem remove stocks wey average volume no reach 500,000 shares.

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, NPPXF, dey show 291.4 days to cover as of the 2026-08-14 settlement: 210.29 million shares short against only 0.72 million shares average daily volume. If the pace continue like this, the short position equal more than one hundred full trading sessions of all the stock’s prints. Check the ticker column, pattern go show: foreign and thinly traded names dey fill the top of raw days-to-cover list, and several end with F, the OTC symbol suffix for foreign ordinary share. Even the last row wey dey show still get 22.5 days. These no be crowded trades in squeeze sense. Na small short positions measured against almost no volume.

Why the raw top of the list na liquidity artifact

Days to cover na ratio, and ratio dey blow up when the denominator dey shrink near zero. Group the whole settlement file by how much each stock really dey trade, and you go see the mechanism 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 1.4 days among the stocks wey people trade pass to 3.2 for the moderate band. The maximum column dey show 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 7.6. For the very-thin band, e reach 1000, across the 16942 names wey trade below 200,000 shares for one session. The extreme readings dey entirely among stocks wey almost nobody dey trade. For these stocks, small short position divided by volume near zero fit produce very big number. Any days-to-cover screen wey worth reading need start with liquidity floor, no be without am.

The days-to-cover wey highest among liquid stocks

If we use real liquidity screen, with five million shares average daily volume, leaderboard go show names wey people know and fit trade.

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

After we raise the floor, MPT dey lead with 15.6 days to cover: 144.5 million shares short against 9.29 million shares daily volume. Na this kind list squeeze-watchers dey mean when dem talk say “high days to cover”: stocks wey dey trade plenty, but the short position big compared with the stock’s own trading activity. Even the last row for here still show 9 days. That one na several times the 2-day median across all liquid names for the receipts below. The leaderboard of stocks with the highest short interest ranks the same settlement file by raw shares short instead. Na another way to look at am, and e brings out mega-caps with very large positions wey still clear quickly.

Crowding dey build or e dey fade?

One settlement na just one frozen frame. The same file reach back several years, so the next question—how today’s liquid leaders take reach here—get answer for the data. This panel dey trace the current liquid top three go 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 go backward, so the latest row match the liquid table wey dey above: 15.6, 15.4 and 13.4 days. Read each column from top reach bottom, and the pattern wey snapshot dey hide go show. Crowding for this scale dey build and unwind across settlements, over weeks and months, no be overnight. A name fit stay for double-digit days to cover throughout one whole quarter without anything resolving. Half of squeeze-watching na to know whether na fresh arrival you dey look at or long-term resident, and the squeeze mechanics explain wetin need happen before high reading fit matter at all.

How dem build this list, and how to read am honestly

Numbers first, then the caveats wey come 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 mostly get names wey no easy trade. The latest settlement carry 22480 tickers wey get positive days-to-cover reading. Out of them, 19804 dey trade below one million shares per day, and only 746 pass the five-million-share floor. If you sort only by “highest days to cover,” you dey answer question about the many thinly traded names, no be the few liquid ones.
• Median crowding low even among liquid names. The normal liquid stock get 2 days to cover, so the leaderboard names above run many multiples of the usual reading. Once you remove the liquidity distortion, high number really unusual.
• The data old by how dem build am. Exchanges report settlements two times every month and publish dem with delay. So the print wey you dey read don already old for days before e reach screen, and positions fit don move since then.
• One symbol dem remove by name inside the SQL. A ticker for the current file recently move from one company go a newly listed company. Vendor feeds fit mix the two entities under the same symbol, so every query here drop am instead of risking a row wey assign the data to wrong company.
• High days to cover na description, no be verdict. Crowded short na condition wey fit come before a squeeze, but e never be prediction say squeeze go happen. Most heavily shorted names never squeeze, and the ratio alone no fit separate the future squeeze from the company wey market don correctly diagnose.

Highest days to cover FAQ

Iza days to cover dey highest for stock right now?

For raw sort of the latest settlement, NPPXF dey top the list with 291.4 days, although na thinly traded name and the ratio come from volume wey nearly zero. Among stocks wey genuinely liquid (five million shares per day and above), MPT lead with 15.6 days. Both tables go refresh as new settlements dey publish.

Wetin high days to cover ratio mean?

Across liquid names, median na about 2 days. So, any reading for mid-single digits don already high, while double-digit readings rare. Values for dozens or hundreds almost always come from thinly traded stocks wey average-volume denominator small well, no be because short positions unusually large.

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

Days to cover dey divide shares short by average daily volume. When stock hardly dey trade, that denominator dey close to zero. So even small short position fit produce very large ratio. The liquidity-band panel above show say maximum reading dey climb from single digits among stocks wey trade heavily to hundreds among the thinnest.

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 stocks with high days to cover never squeeze. Pair the reading with the complete days-to-cover guide and the shares-short leaderboard before you use one number take infer market intent.

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