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 18 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
1701
+5.92%
7.0M → 7.4M
—
—
$366.66M
United States
Consumer Cyclical
1702
+5.92%
7.5M → 7.9M
—
—
$17.87B
United States
Consumer Cyclical
1703
+5.90%
37.6M → 39.8M
—
—
$5.13B
United States
Financial Services
1704
+5.90%
776K → 821K
—
—
$287.39M
United States
Industrials
1705
+5.90%
2.9M → 3.1M
—
—
$3.52B
Israel
Industrials
1706
+5.89%
15.2M → 16.1M
—
—
$758.07M
United States
Healthcare
1707
+5.89%
2.3M → 2.4M
—
—
$6.91B
United States
Industrials
1708
+5.87%
3.8M → 4.0M
—
—
$610.32M
United States
Real Estate
1709
+5.86%
17.5M → 18.5M
—
—
$10.61B
United States
Utilities
1710
+5.86%
4.7M → 5.0M
—
—
$1.65B
United States
Financial Services
1711
+5.86%
58.9M → 62.4M
—
—
$5.56B
United States
Technology
1712
+5.84%
1.7M → 1.8M
—
—
$653.58M
United States
Industrials
1713
+5.83%
4.7M → 5.0M
—
—
$489.72M
United States
Healthcare
1714
+5.83%
1.0M → 1.1M
—
—
$3.53B
United States
Financial Services
1715
+5.83%
1.3M → 1.4M
—
—
$272.87M
United States
Real Estate
1716
+5.82%
4.7M → 5.0M
—
—
$9.38B
South Korea
Communication Services
1717
+5.82%
97K → 102K
—
—
$174.26M
United States
Energy
1718
+5.81%
2.8M → 3.0M
—
—
$2.62B
United States
Technology
1719
+5.81%
9.7M → 10.3M
—
—
$5.06B
United States
Technology
1720
+5.80%
6.3M → 6.7M
—
—
$5.99B
United States
Consumer Defensive
1721
+5.80%
296K → 313K
—
—
$389.96M
United States
Financial Services
1722
+5.80%
10.8M → 11.4M
—
—
$17.34B
United States
Financial Services
1723
+5.78%
4.7M → 4.9M
—
—
$825.89M
United States
Real Estate
1724
+5.76%
31.2M → 33.0M
—
—
$4.98B
United States
Healthcare
1725
+5.76%
1.4M → 1.5M
—
—
$4.12B
United States
Healthcare
1726
+5.76%
5.5M → 5.8M
—
—
$20.27M
United States
Healthcare
1727
+5.76%
5.7M → 6.0M
—
—
$3.38B
United States
Industrials
1728
+5.76%
4.5M → 4.7M
—
—
$1.95B
United States
Healthcare
1729
+5.75%
16.9M → 17.8M
—
—
$9.50B
United States
Technology
1730
+5.75%
17.4M → 18.4M
—
—
$98.15M
Canada
Healthcare
1731
+5.75%
1.7M → 1.8M
—
—
$160.79M
China
Consumer Cyclical
1732
+5.74%
326K → 345K
2.26%
3.1
$13.89M
United States
Technology
1733
+5.74%
7.5M → 7.9M
—
—
$488.50M
United States
Healthcare
1734
+5.74%
425K → 449K
—
—
$205.37M
United States
Consumer Cyclical
1735
+5.74%
5.7M → 6.0M
—
—
$8.47B
United States
Financial Services
1736
+5.73%
140.8M → 148.9M
—
—
$17.33B
Netherlands
Consumer Cyclical
1737
+5.73%
3.1M → 3.2M
—
—
$62.44M
United States
Technology
1738
+5.72%
659K → 697K
—
—
$245.52M
United States
Industrials
1739
+5.72%
17.1M → 18.1M
—
—
$177.45B
United States
Communication Services
1740
+5.71%
119K → 126K
—
—
$647.19M
United States
Financial Services
1741
+5.70%
6.4M → 6.7M
—
—
$632.23M
United States
Real Estate
1742
+5.70%
12.4M → 13.1M
—
—
$13.65B
United States
Financial Services
1743
+5.69%
3.1M → 3.3M
—
—
$3.73B
United States
Consumer Cyclical
1744
+5.67%
153K → 162K
—
—
$562.89M
United States
Financial Services
1745
+5.66%
4.9M → 5.2M
—
—
$503.60M
United States
Real Estate
1746
+5.65%
2.6M → 2.7M
—
—
$10.54B
United States
Healthcare
1747
+5.64%
38.6M → 40.8M
—
—
$20.48B
United States
Healthcare
1748
+5.63%
404K → 427K
—
—
$41.65M
United States
Technology
1749
+5.63%
13.1M → 13.8M
—
—
$3.14B
United States
Healthcare
1750
+5.62%
3.0M → 3.2M
—
—
$5.02B
United States
Financial Services
1751
+5.62%
1.7M → 1.8M
—
—
$1.84B
United States
Industrials
1752
+5.62%
10.4M → 11.0M
—
—
$50.96B
United States
Utilities
1753
+5.62%
6.3M → 6.6M
—
—
$6.14B
United States
Technology
1754
+5.62%
14.9M → 15.8M
—
—
$1.77B
United States
Healthcare
1755
+5.61%
44.2M → 46.7M
—
—
$24.27B
United States
Utilities
1756
+5.61%
6.1M → 6.5M
—
—
$94.31B
United States
Healthcare
1757
+5.60%
792K → 836K
—
—
$9.40B
United States
Consumer Cyclical
1758
+5.60%
2.4M → 2.6M
—
—
$4.08B
United States
Technology
1759
+5.59%
15.8M → 16.7M
—
—
$1.94B
United States
Industrials
1760
+5.56%
1.1M → 1.2M
—
—
$89.99M
United States
Healthcare
1761
+5.56%
46.1M → 48.7M
—
—
$2.33B
United States
Consumer Defensive
1762
+5.56%
6.1M → 6.4M
—
—
$5.51B
United States
Utilities
1763
+5.55%
30.6M → 32.3M
—
—
$266.20M
United States
Technology
1764
+5.55%
5.3M → 5.6M
—
—
$876.39M
United States
Financial Services
1765
+5.54%
13.7M → 14.4M
—
—
$1.56B
United States
Healthcare
1766
+5.54%
7.2M → 7.6M
—
—
$1.51B
United States
Industrials
1767
+5.54%
10.6M → 11.2M
—
—
$3.00B
United States
Healthcare
1768
+5.54%
7.7M → 8.1M
—
—
$9.18B
United States
Healthcare
1769
+5.53%
40K → 43K
—
—
$77.27M
—
—
1770
+5.52%
671K → 708K
—
—
$37.73M
United States
Healthcare
1771
+5.52%
11.7M → 12.3M
—
—
$6.80B
United States
Industrials
1772
+5.52%
448K → 473K
—
—
$423.06M
United States
Energy
1773
+5.51%
2.4M → 2.5M
—
—
$381.58M
United States
Healthcare
1774
+5.50%
2.0M → 2.1M
—
—
$1.73B
United States
Financial Services
1775
+5.50%
15.1M → 16.0M
—
—
$25.10B
United States
Industrials
1776
+5.50%
17.8M → 18.8M
—
—
$23.73B
United States
Financial Services
1777
+5.49%
9.4M → 9.9M
—
—
$13.32B
United States
Technology
1778
+5.48%
441K → 465K
—
—
$289.10M
United States
Consumer Cyclical
1779
+5.46%
689K → 726K
—
—
$990.99M
United States
Basic Materials
1780
+5.45%
26K → 27K
—
—
$1.44B
United States
Healthcare
1781
+5.45%
2.8M → 2.9M
—
—
$18.53B
Brazil
Communication Services
1782
+5.45%
900K → 949K
—
—
$1.40B
United States
Financial Services
1783
+5.44%
3.3M → 3.5M
—
—
$250.56M
Switzerland
Healthcare
1784
+5.44%
2.4M → 2.6M
—
—
$1.17B
United States
Technology
1785
+5.44%
4.5M → 4.8M
—
—
$225.37M
United States
Consumer Defensive
1786
+5.44%
2.5M → 2.7M
—
—
$79.87M
—
—
1787
+5.43%
2.1M → 2.2M
—
—
$11.71B
Israel
Technology
1788
+5.43%
26.6M → 28.0M
—
—
$1.36T
South Korea
Technology
1789
+5.42%
2.6M → 2.7M
—
—
$323.18M
United States
Industrials
1790
+5.41%
508K → 536K
—
—
$207.49M
United States
Industrials
1791
+5.40%
3.4M → 3.5M
—
—
$1.81B
United States
Healthcare
1792
+5.39%
3.2M → 3.4M
—
—
$8.63B
United States
Industrials
1793
+5.39%
1.1M → 1.2M
—
—
$5.77B
Italy
Healthcare
1794
+5.39%
16.2M → 17.1M
—
—
$248.18M
United States
Technology
1795
+5.38%
4.4M → 4.7M
—
—
$2.15B
United States
Industrials
1796
+5.38%
3.9M → 4.1M
—
—
$6.75B
Israel
Consumer Cyclical
1797
+5.37%
5.8M → 6.1M
—
—
$18.19B
United States
Technology
1798
+5.34%
11.7M → 12.3M
—
—
$96.47M
United States
Healthcare
1799
+5.34%
18.2M → 19.1M
—
—
$5.45B
United States
Real Estate
1800
+5.33%
410K → 431K
—
—
$648.13M
United States
Financial Services
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

FOSL leads this ranking, followed by GPC and FLG. 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.