STOCK TITAN

Short Interest Increases — Rising Bearish Positions

US-listed companies whose reported short position grew the most between the two most recent FINRA settlement files. A larger position records positioning rather than an outcome; the share counts beside each percentage are what make it readable.
Settlement Sep 15, 2026
next publication (FINRA schedule) Oct 9, 2026
data 13 days old
Reporting period September 2026
Direction Rising short interest
Page 19 of 29

Swipe the table sideways for more columns.

What these columns measure
Short Interest Change
How far the reported short position moved between the two most recent FINRA settlement files. The share counts under each percentage are the two positions it was computed from. A position that grew from almost nothing has no meaningful percentage, so those rows report a floor of over 999.99% instead, and only when the current position is at least 275,000 shares.
Split in period
A share split that took effect between the two settlement dates puts the two counts on different share bases, so the percentage measures the rebase rather than any trading. Those rows are struck through and marked, never adjusted, because a heuristic correction here is a number nobody can verify.
SI % of Float*
Shares sold short measured against the shares actually available to trade. Where no reliable float exists the position is measured against shares outstanding instead and the row says "of outstanding", because the same position reads lower on the wider denominator.
Days to Cover
Shares sold short divided by average daily volume: how many days of ordinary trading buying the position back would take. FINRA floors the value at 1.00 whenever average daily volume already exceeds the position, so those rows read "1 day or less" rather than stating a precision the source withheld.
Why a cell shows a dash
A percentage is withheld rather than guessed whenever its denominator cannot be trusted: the security class publishes no float, the share-count sources disagree, a split leaves the basis uncertain, the settlement file reports no position, or the computed percentage failed the reliability check. The raw share counts stay visible in every one of those cases.
Rank
Symbol
Company Name
Short Interest Change
SI % of Float*
Days to Cover
Market Cap
Country
Sector
1801
+5.33%
1.7M → 1.8M
—
—
$10.24B
United States
Financial Services
1802
+5.33%
5.7M → 6.0M
—
—
$1.45B
United States
Healthcare
1803
+5.32%
11.4M → 12.0M
—
—
$855.31M
United States
Financial Services
1804
+5.31%
673K → 708K
—
—
$4.56B
United States
Industrials
1805
+5.31%
12.8M → 13.5M
—
—
$8.07B
United States
Energy
1806
+5.31%
486K → 512K
—
—
$379.90M
United States
Industrials
1807
+5.30%
14.5M → 15.2M
—
—
$1.81B
United Kingdom
Healthcare
1808
+5.30%
590K → 622K
—
—
$1.11B
United States
Financial Services
1809
+5.30%
46.8M → 49.3M
—
—
$1.93B
United States
Financial Services
1810
+5.29%
5.4M → 5.7M
—
—
$59.58B
United States
Energy
1811
+5.27%
13.4M → 14.1M
—
—
$30.54B
United States
Healthcare
1812
+5.27%
5.1M → 5.4M
—
—
$2.95B
Bermuda
Financial Services
1813
+5.26%
604K → 635K
—
—
$435.84M
United States
Consumer Cyclical
1814
+5.26%
8.0M → 8.5M
—
—
$5.84B
United States
Financial Services
1815
+5.25%
15.4M → 16.2M
—
—
$8.84B
United States
Real Estate
1816
+5.25%
88K → 93K
—
—
$279.39M
United States
Financial Services
1817
+5.24%
156.9M → 165.1M
—
—
$2.69B
United States
Technology
1818
+5.23%
11.0M → 11.6M
—
—
$57.01B
United States
Financial Services
1819
+5.23%
877K → 922K
—
—
$38.54M
United States
Healthcare
1820
+5.23%
5.5M → 5.7M
—
—
$27.31B
United States
Consumer Cyclical
1821
+5.21%
2.9M → 3.0M
—
—
$3.71B
United States
Industrials
1822
+5.21%
4.3M → 4.5M
—
—
$3.51B
United States
Consumer Cyclical
1823
+5.21%
519K → 546K
—
—
$16.02B
United States
Industrials
1824
+5.20%
24.3M → 25.6M
—
—
$64.43B
United States
Utilities
1825
+5.20%
103K → 108K
—
—
$796.86M
United States
Financial Services
1826
+5.20%
1.7M → 1.8M
—
—
$3.97B
United States
Industrials
1827
+5.19%
1.6M → 1.7M
—
—
$48.36M
United States
Healthcare
1828
+5.19%
16.1M → 16.9M
—
—
$124.63M
United Kingdom
Industrials
1829
+5.18%
11.7M → 12.3M
—
—
$3.38B
United States
Real Estate
1830
+5.18%
3.7M → 3.9M
—
—
$32.15B
United States
Financial Services
1831
+5.18%
40K → 42K
—
—
$961.21M
United States
Financial Services
1832
+5.17%
10.0M → 10.5M
—
—
$9.11B
United States
Financial Services
1833
+5.16%
8.7M → 9.2M
—
—
$4.35B
United States
Industrials
1834
+5.15%
8.3M → 8.7M
—
—
$16.43B
United States
Technology
1835
+5.15%
6.3M → 6.6M
—
—
$3.39B
United States
Consumer Cyclical
1836
+5.14%
11.9M → 12.6M
—
—
$1.89B
United States
Healthcare
1837
+5.14%
170K → 179K
—
—
$265.67M
United States
Financial Services
1838
+5.14%
9.3M → 9.8M
—
—
$129.67M
United States
Healthcare
1839
+5.13%
58K → 61K
—
—
$207.99M
United States
Financial Services
1840
+5.13%
5.3M → 5.5M
—
—
$4.37B
United States
Financial Services
1841
+5.13%
43.9M → 46.1M
—
—
$57.92B
Brazil
Basic Materials
1842
+5.11%
9.5M → 9.9M
—
—
$12.43B
United States
Industrials
1843
+5.10%
3.0M → 3.1M
—
—
$1.62B
United States
Healthcare
1844
+5.10%
3.8M → 4.0M
—
—
$922.28M
United States
Communication Services
1845
+5.10%
5.6M → 5.9M
—
—
$833.18M
United States
Healthcare
1846
+5.10%
216K → 227K
—
—
$48.40M
United States
Healthcare
1847
+5.09%
60.4M → 63.5M
—
—
$2.89B
United States
Real Estate
1848
+5.08%
145K → 152K
—
—
$347.35M
United States
Financial Services
1849
+5.07%
4.9M → 5.2M
—
—
$25.27B
United States
Utilities
1850
+5.07%
259K → 273K
—
—
$389.18M
United States
Financial Services
1851
+5.06%
9.8M → 10.3M
—
—
$2.52B
United States
Consumer Cyclical
1852
+5.05%
3.6M → 3.7M
—
—
$247.88M
United States
Healthcare
1853
+5.05%
229K → 240K
—
—
$448.91M
United States
Financial Services
1854
+5.03%
7.7M → 8.1M
—
—
$145.17B
United States
Healthcare
1855
+5.00%
5.6M → 5.9M
—
—
$43.09B
United States
Industrials
1856
+5.00%
468K → 491K
—
—
$101.53M
Canada
Basic Materials
1857
+5.00%
16.7M → 17.5M
—
—
$3.61B
United States
Healthcare
1858
+5.00%
8.0M → 8.4M
—
—
$1.13B
United States
Technology
1859
+5.00%
4.5M → 4.7M
—
—
$12.93B
United States
Consumer Defensive
1860
+4.99%
22.4M → 23.5M
—
—
$9.37B
Canada
Basic Materials
1861
+4.99%
2.2M → 2.4M
—
—
$332.13M
Luxembourg
Basic Materials
1862
+4.99%
2.4M → 2.5M
—
—
$7.76B
Canada
Industrials
1863
+4.98%
8.8M → 9.3M
—
—
$11.88B
United States
Real Estate
1864
+4.97%
1.1M → 1.2M
—
—
$241.38M
United States
Healthcare
1865
+4.96%
8.8M → 9.2M
—
—
$129.18M
United States
Basic Materials
1866
+4.96%
8.2M → 8.6M
—
—
$2.13B
Canada
Healthcare
1867
+4.96%
3.7M → 3.8M
—
—
$2.83B
United States
Financial Services
1868
+4.95%
4.7M → 4.9M
—
—
$838.68M
United States
Energy
1869
+4.95%
1.3M → 1.4M
—
—
$16.96M
Israel
Industrials
1870
+4.94%
1.0M → 1.1M
—
—
$9.56B
United States
Industrials
1871
+4.94%
26.0M → 27.3M
—
—
$55.87B
United States
Energy
1872
+4.92%
2.0M → 2.1M
—
—
$1.12B
United States
Real Estate
1873
+4.92%
212K → 222K
—
—
$171.50M
United States
Financial Services
1874
+4.92%
14.8M → 15.5M
—
—
$73.62B
United States
Energy
1875
+4.92%
32.0M → 33.6M
—
—
$41.56B
United States
Utilities
1876
+4.92%
5.8M → 6.1M
—
—
$3.54B
Israel
Technology
1877
+4.92%
911K → 956K
—
—
$482.60M
United States
Healthcare
1878
+4.91%
9.4M → 9.9M
—
—
$5.20B
United States
Consumer Cyclical
1879
+4.91%
24.2M → 25.4M
—
—
$14.40B
United States
Real Estate
1880
+4.91%
3.8M → 4.0M
—
—
$5.77B
United States
Industrials
1881
+4.90%
4.3M → 4.5M
—
—
$7.73B
United States
Industrials
1882
+4.89%
34.1M → 35.7M
—
—
$2.50B
United States
Healthcare
1883
+4.89%
7.9M → 8.3M
—
—
$713.30M
Canada
Energy
1884
+4.88%
10.8M → 11.3M
—
—
$3.91B
United States
Real Estate
1885
+4.86%
547K → 573K
—
—
$67.40M
United States
Technology
1886
+4.84%
38.3M → 40.2M
—
—
$240.91M
United States
Energy
1887
+4.84%
50.1M → 52.5M
—
—
$32.74B
United States
Consumer Defensive
1888
+4.84%
2.9M → 3.0M
—
—
$288.61M
United States
Communication Services
1889
+4.82%
3.7M → 3.9M
—
—
$179.15M
United States
Healthcare
1890
+4.82%
196K → 206K
—
—
$287.77M
United States
Industrials
1891
+4.81%
1.8M → 1.9M
—
—
$4.42B
United States
Energy
1892
+4.80%
1.4M → 1.5M
—
—
$6.88B
United States
Industrials
1893
+4.80%
14.8M → 15.6M
—
—
$276.26M
United States
Healthcare
1894
+4.80%
265.0M → 277.8M
—
—
$6.01B
Switzerland
Energy
1895
+4.80%
908K → 952K
—
—
$136.74M
United States
Industrials
1896
+4.78%
3.0M → 3.1M
—
—
$228.46M
United States
Industrials
1897
+4.78%
4.3M → 4.6M
—
—
$181.81M
United States
Financial Services
1898
+4.78%
5.9M → 6.2M
—
—
$258.06M
United States
Consumer Cyclical
1899
+4.77%
623K → 652K
—
—
$1.69B
United States
Financial Services
1900
+4.77%
4.8M → 5.1M
—
—
$5.23B
United States
Industrials
Looking for a specific Symbol?
A position that grew from almost nothing has no meaningful percentage, so rows marked this way report >999.99% as a floor rather than a measurement, and only when the current position is at least 275,000 shares. Read the share counts beside them instead. Rows whose position stayed under that size show no percentage at all.
* Measured against the tradable float where one is published, and against shares outstanding where none is. Rows on the wider denominator say "of outstanding", because the same position reads lower against it.
Short interest data is provided by FINRA and updated bi-monthly. Data as of September 2026. A settlement records positions open on that date rather than trading in between. This ranking is informational and is not investment advice.

Frequently Asked Questions

Q Which stocks had the biggest short interest increase this period?
A

BPOP leads this ranking, followed by KLRA and NAVI. The ranking measures the change in reported short positions between two consecutive FINRA settlement files, so it reflects positions that were open on those two dates rather than trading that happened in between. The figures on this page come from the settlement dated Sep 15, 2026.

Q How often is short interest data updated?
A

FINRA collects short positions twice a month, on the settlement dates around mid-month and month-end, and publishes each file about seven business days later, on dates it announces a year ahead. That gap is why this page states its settlement date and the age of the figures: a position can have changed substantially before the next file confirms it.

Q What do short interest as a percentage of float and days to cover actually mean?
A

Short interest as a percentage of float is the shorted position measured against the shares actually available to trade, so it answers how crowded the short side is. Days to cover divides that position by average daily volume, answering how long ordinary trading would take to buy it back. Where no reliable float exists, the percentage is measured against shares outstanding instead and the row says so, because the same position reads lower on the wider denominator.

Q Why do some rows show no percentage change?
A

A position that grew from almost nothing has no meaningful percentage: dividing by a near-zero previous position produces a number that says more about the denominator than about the position. Rows in that state report a floor of over 999.99% instead, and only when the current position is at least 275,000 shares. Below that size the page shows no percentage at all and leaves the raw share counts, which are the reliable figures.

Q How do traders screen for short squeeze candidates?
A

A squeeze needs three things together, and no single column identifies one. First, a crowded position: a high percentage of float, not merely a large share count. Second, difficulty exiting: a high days-to-cover figure, meaning ordinary volume cannot absorb the buying that covering requires. Third, a catalyst that forces the timing, such as an earnings surprise, a regulatory decision or a financing announcement. Screening on any one of the three in isolation produces mostly false positives. Rows marked as split-affected belong in none of it: a split between the two settlement dates rebases the share count, so their change reflects arithmetic rather than anyone trading, and they are marked precisely so they can be set aside.

Q Does high short interest mean a stock will fall?
A

No. Short interest records positioning, not outcomes. Institutions short for hedging as well as for directional bets, so a large position may be one leg of a trade rather than a view on the company. Heavily shorted stocks have both fallen and risen sharply; the data tells you who is positioned how, and nothing about who is right.