STOCK TITAN

Short Interest Decreases — Positions Being Covered

US-listed companies whose reported short position fell the most between the two most recent FINRA settlement files. A fall is consistent with covering and equally with a share base that changed underneath the count, so the marked rows matter as much as the ranking.
Settlement Sep 15, 2026
next publication (FINRA schedule) Oct 9, 2026
data 21 days old
Reporting period September 2026
Direction Falling short interest
Page 18 of 18

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.
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
-0.43%
14.3M → 14.2M
14.10%
15.5
$1.78B
United States
Real Estate
1702
-0.40%
6.7M → 6.7M
4.25%
3.9
$20.39B
United States
Consumer Defensive
1703
-0.40%
448K → 447K
0.70%
1.8
$4.34B
Argentina
Financial Services
1704
-0.40%
5.6M → 5.6M
13.43%
5.2
$8.16B
United States
Consumer Cyclical
1705
-0.40%
24.7M → 24.6M
11.05%
29.8
$857.88M
Canada
Basic Materials
1706
-0.39%
63K → 63K
0.51%
1 day or less
$84.95M
United States
Financial Services
1707
-0.39%
2.1M → 2.0M
8.59%
4.9
$4.39B
United States
Financial Services
1708
-0.39%
3.6M → 3.6M
12.19%
4.3
$470.55M
China
Technology
1709
-0.38%
3.7M → 3.7M
3.13%
10.3
$2.75B
Canada
Basic Materials
1710
-0.38%
1.0M → 1.0M
3.21%
3.2
$3.96B
Singapore
Communication Services
1711
-0.37%
7.0M → 7.0M
4.81%
3.9
$9.36B
United States
Financial Services
1712
-0.37%
5.8M → 5.8M
1.45%
2.6
$82.38B
United States
Industrials
1713
-0.36%
18.2M → 18.2M
9.26%
5.2
$18.20B
United States
Consumer Cyclical
1714
-0.36%
526K → 525K
0.23%
11.4
$279.35M
China
Consumer Cyclical
1715
-0.35%
1.4M → 1.4M
4.69%
7.3
$39.48M
United States
Healthcare
1716
-0.34%
4.4M → 4.4M
7.96%
10.3
$153.65M
United States
Healthcare
1717
-0.33%
40.0M → 39.9M
3.50%
7.2
$107.57B
United States
Consumer Cyclical
1718
-0.32%
576K → 574K
14.49%
11.8
$364.69M
United States
Communication Services
1719
-0.31%
186K → 186K
1.45%
15.1
$77.93M
United States
Financial Services
1720
-0.31%
3.2M → 3.2M
30.87%
14.9
$957.38M
United States
Technology
1721
-0.31%
4.8M → 4.8M
11.66%
23.0
$3.73B
United States
Industrials
1722
-0.31%
429K → 428K
3.75%
8.5
$20.89M
Greece
Industrials
1723
-0.30%
3.0M → 3.0M
7.53%
6.7
$1.15B
United States
Financial Services
1724
-0.30%
1.6M → 1.6M
8.33%of outstanding
10.3
$12.14B
United States
Industrials
1725
-0.29%
11.1M → 11.0M
8.60%
6.6
$24.55B
United States
Healthcare
1726
-0.29%
7.8M → 7.8M
15.24%
20.6
$1.53B
United Kingdom
Healthcare
1727
-0.28%
23.3M → 23.2M
4.51%
4.5
$12.38B
United States
Healthcare
1728
-0.28%
1.0M → 1.0M
4.25%
6.4
$3.20B
United States
Utilities
1729
-0.27%
3.3M → 3.3M
7.37%
11.7
$1.81B
United States
Healthcare
1730
-0.27%
1.9M → 1.9M
7.62%
5.6
$1.66B
United States
Real Estate
1731
-0.27%
30.5M → 30.4M
22.71%
7.9
$690.08M
United States
Utilities
1732
-0.27%
2.7M → 2.7M
7.18%
4.8
$1.24B
United States
Industrials
1733
-0.26%
6.4M → 6.4M
12.38%
6.8
$1.44B
United States
Consumer Cyclical
1734
-0.26%
299K → 298K
4.93%
2.3
$1.08B
United States
Industrials
1735
-0.26%
69.8M → 69.6M
7.34%
5.3
$5.88B
United States
Communication Services
1736
-0.26%
7.0M → 7.0M
3.29%
4.4
$93.20B
United States
Consumer Cyclical
1737
-0.26%
8.4M → 8.4M
9.32%
16.4
$5.12B
United States
Financial Services
1738
-0.26%
4.8M → 4.8M
5.28%
8.1
$985.44M
United States
Utilities
1739
-0.25%
7.2M → 7.2M
6.35%
24.3
$79.11M
United States
Consumer Defensive
1740
-0.24%
3.3M → 3.3M
8.62%of outstanding
5.9
$2.97B
United States
Industrials
1741
-0.24%
8.0M → 8.0M
16.30%
14.9
$2.83B
United States
Industrials
1742
-0.24%
153K → 152K
0.82%
2.1
$73.26M
China
Financial Services
1743
-0.24%
179.1M → 178.7M
34.08%
12.6
$2.51B
United States
Healthcare
1744
-0.24%
794K → 792K
1.49%of outstanding
30.6
$1.83B
United States
Financial Services
1745
-0.24%
19.5M → 19.5M
17.30%
15.7
$2.17B
United States
Healthcare
1746
-0.23%
351K → 350K
1.26%
4.8
$2.16B
Canada
Consumer Cyclical
1747
-0.23%
4.4M → 4.4M
16.36%
12.8
$1.94B
United States
Healthcare
1748
-0.23%
3.4M → 3.4M
8.98%
11.4
$343.02M
Isle of Man
Basic Materials
1749
-0.22%
33K → 33K
0.58%
3.8
$23.14M
United States
Technology
1750
-0.22%
6.6M → 6.5M
15.42%
10.3
$116.29M
United States
Technology
1751
-0.21%
1.1M → 1.1M
5.69%
3.3
$46.11M
United States
Technology
1752
-0.20%
84.1M → 84.0M
24.75%of outstanding
7.6
$2.03B
United States
Financial Services
1753
-0.19%
21.3M → 21.2M
9.91%of outstanding
10.0
$103.71M
Israel
Consumer Cyclical
1754
-0.19%
13.7M → 13.6M
1.98%
3.6
$83.10B
United States
Financial Services
1755
-0.19%
1.2M → 1.2M
5.99%
4.8
$652.32M
United States
Industrials
1756
-0.18%
3.0M → 3.0M
12.94%
8.9
$620.97M
United States
Consumer Defensive
1757
-0.18%
125.6M → 125.4M
31.27%
15.9
$10.78B
United States
Healthcare
1758
-0.18%
3.0M → 3.0M
4.15%
2.3
$24.83B
United States
Technology
1759
-0.17%
13.9M → 13.9M
12.96%
9.9
$3.25B
United States
Real Estate
1760
-0.17%
98K → 97K
0.84%
9.0
$105.05M
United States
Real Estate
1761
-0.16%
10.2M → 10.2M
9.27%
4.1
$1.39B
United States
Technology
1762
-0.16%
813K → 812K
4.06%
12.2
$59.94M
United States
Healthcare
1763
-0.16%
20.9M → 20.9M
12.70%
5.2
$7.20B
United States
Healthcare
1764
-0.16%
12.7M → 12.7M
14.50%of outstanding
7.0
$4.22B
United States
Technology
1765
-0.15%
10.3M → 10.3M
15.73%
20.1
$6.23B
United States
Healthcare
1766
-0.14%
1.2M → 1.2M
4.02%
2.2
$16.09B
United States
Industrials
1767
-0.13%
69K → 69K
0.55%
7.6
$60.65M
United States
Industrials
1768
-0.12%
10.1M → 10.1M
4.99%
5.0
$343.67M
United States
Technology
1769
-0.11%
3.2M → 3.1M
10.99%
20.7
$994.87M
United States
Healthcare
1770
-0.10%
19.5M → 19.5M
1.10%
4.5
$463.09B
United States
Healthcare
1771
-0.10%
3.5M → 3.5M
2.92%
11.2
$67.14B
Italy
Consumer Cyclical
1772
-0.09%
7.3M → 7.3M
7.58%
5.7
$4.04B
United States
Energy
1773
-0.09%
2.0M → 2.0M
5.87%
5.5
$421.06M
United States
Consumer Defensive
1774
-0.08%
3.4M → 3.4M
0.50%
8.8
$5.01B
Spain
Healthcare
1775
-0.08%
3.3M → 3.3M
7.38%
5.5
$1.55B
United States
Healthcare
1776
-0.07%
981K → 980K
9.82%
2.5
$951.18M
United States
Technology
1777
-0.07%
8.8M → 8.8M
3.29%
4.6
$263.95B
United States
Industrials
1778
-0.07%
27.8M → 27.8M
13.78%
10.4
$524.82M
United States
Consumer Cyclical
1779
-0.06%
826K → 826K
1.75%
2.0
$92.53B
Uruguay
Consumer Cyclical
1780
-0.05%
4.7M → 4.7M
11.66%
5.7
$14.86B
United States
Consumer Cyclical
1781
-0.04%
3.5M → 3.5M
19.98%
6.7
$507.14M
United States
Technology
1782
-0.03%
237K → 237K
3.13%
9.3
$204.77M
United States
Basic Materials
1783
-0.03%
3.3M → 3.3M
21.43%
14.1
$248.13M
United States
Energy
1784
-0.03%
7.9M → 7.9M
2.91%
8.2
$613.05M
Canada
Basic Materials
1785
-0.03%
64.7M → 64.7M
32.54%
11.3
$1.79B
United States
Technology
1786
-0.03%
4.5M → 4.5M
12.12%
19.7
$811.28M
United States
Consumer Defensive
1787
-0.02%
5.5M → 5.5M
9.50%
6.0
$5.52B
United States
Industrials
1788
-0.02%
1.3M → 1.3M
2.55%
3.5
$3.40B
Bermuda
Financial Services
1789
-0.02%
8.8M → 8.8M
3.09%
7.2
$75.35B
United States
Industrials
1790
-0.02%
5.8M → 5.8M
5.82%
5.0
$164.33M
Canada
Basic Materials
1791
-0.01%
55K → 55K
0.48%
334.4
$159.38M
United States
Financial Services
1792
-0.01%
2.2M → 2.2M
5.33%
10.8
$989.77M
United States
Healthcare
Looking for a specific Symbol?
* 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 decrease this period?
A

NTST leads this ranking, followed by BG and BMA. 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 What does a large drop in short interest actually tell you?
A

Less than it appears. A fall in the reported position is consistent with shorts buying back, which is the reading most people reach for, but it is equally consistent with a share count that changed underneath the figure: a reverse split rebases the position without anyone trading, and a symbol leaving the settlement file entirely can read as a collapse to zero. Even genuine covering says nothing about why, since a short may be closing at a profit, at a loss, or simply rebalancing. Check the raw share counts beside the percentage and whether a corporate action landed between the two settlement dates before treating a decrease as a signal.

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.