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 6 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
501
+20.39%
1.5M → 1.8M
—
—
$127.51M
United States
Healthcare
502
+20.38%
10.3M → 12.4M
—
—
$152.05B
United States
Financial Services
503
+20.36%
3.6M → 4.4M
—
—
$2.71B
Brazil
Energy
504
+20.36%
4.5M → 5.4M
—
—
$42.36B
United States
Technology
505
+20.36%
4.4M → 5.3M
—
—
$3.68B
United States
Energy
506
+20.29%
179K → 216K
—
—
$281.90M
United States
Financial Services
507
+20.27%
427K → 513K
—
—
$328.42M
United States
Consumer Defensive
508
+20.26%
3.4M → 4.1M
—
—
$4.39B
United States
Technology
509
+20.14%
13.1M → 15.7M
—
—
$3.54B
United States
Real Estate
510
+20.09%
13.7M → 16.4M
—
—
$2.85B
United States
Real Estate
511
+20.08%
1.1M → 1.3M
—
—
$723.53M
United States
Healthcare
512
+20.08%
29.6M → 35.6M
—
—
$978.60M
United States
Consumer Cyclical
513
+20.05%
14.6M → 17.5M
—
—
$31.16B
Switzerland
Healthcare
514
+20.03%
1.4M → 1.7M
—
—
$40.82B
Switzerland
Healthcare
515
+20.02%
5.4M → 6.4M
—
—
$86.63B
United States
Financial Services
516
+19.98%
4.3M → 5.1M
—
—
$755.62M
United States
Technology
517
+19.93%
654K → 784K
—
—
$352.62M
United States
Financial Services
518
+19.91%
555K → 665K
—
—
$792.79M
United States
Financial Services
519
+19.91%
1.6M → 1.9M
—
—
$4.87B
United States
Industrials
520
+19.82%
36.1M → 43.2M
—
—
$9.51B
Brazil
Basic Materials
521
+19.81%
9.8M → 11.8M
—
—
$4.86B
United States
Healthcare
522
+19.81%
6.4M → 7.7M
—
—
$7.24B
United States
Real Estate
523
+19.77%
1.2M → 1.4M
—
—
$75.90B
United Kingdom
Utilities
524
+19.74%
4.7M → 5.6M
—
—
$2.09B
United States
Technology
525
+19.74%
21.6M → 25.9M
—
—
$786.97M
Canada
Basic Materials
526
+19.74%
1.6M → 2.0M
—
—
$9.37B
Hong Kong
Technology
527
+19.74%
15.2M → 18.2M
—
—
$3.69B
United States
Technology
528
+19.67%
869K → 1.0M
—
—
$9.66B
United States
Financial Services
529
+19.63%
546K → 653K
—
—
$192.60M
Israel
Technology
530
+19.60%
2.9M → 3.4M
—
—
$4.79B
United States
Healthcare
531
+19.56%
4.5M → 5.4M
—
—
$5.18B
United States
Consumer Cyclical
532
+19.56%
906K → 1.1M
—
—
$10.98B
United States
Financial Services
533
+19.56%
1.7M → 2.1M
—
—
$610.15M
Canada
Energy
534
+19.49%
3.1M → 3.7M
—
—
$3.99B
United States
Industrials
535
+19.47%
1.2M → 1.4M
—
—
$283.28M
United States
Technology
536
+19.42%
201K → 241K
—
—
$1.61B
United States
Energy
537
+19.38%
13.6M → 16.3M
—
—
$4.50B
United States
Healthcare
538
+19.31%
94K → 112K
—
—
$399.53M
United States
Financial Services
539
+19.28%
771K → 920K
—
—
$1.08B
United States
Financial Services
540
+19.26%
101K → 121K
—
—
$169.04M
United States
Consumer Cyclical
541
+19.26%
15.3M → 18.2M
—
—
$14.45B
United States
Consumer Cyclical
542
+19.26%
750K → 894K
—
—
$1.16B
United States
Financial Services
543
+19.18%
853K → 1.0M
—
—
$1.48B
United States
Financial Services
544
+19.14%
7.8M → 9.3M
—
—
$398.86M
United States
Healthcare
545
+19.11%
4.8M → 5.8M
—
—
$20.43B
Argentina
Energy
546
+19.10%
6.0M → 7.1M
—
—
$670.25M
United States
Healthcare
547
+19.09%
640K → 762K
—
—
$1.35B
United States
Real Estate
548
+19.07%
8.9M → 10.6M
—
—
$292.52B
United States
Consumer Cyclical
549
+19.05%
8.3M → 9.8M
—
—
$1.82B
United States
Energy
550
+19.03%
1.8M → 2.2M
—
—
$914.19M
United States
Financial Services
551
+18.95%
1.5M → 1.8M
—
—
$356.61M
United States
Consumer Cyclical
552
+18.88%
522K → 621K
—
—
$405.28M
United States
Real Estate
553
+18.87%
1.4M → 1.6M
—
—
$9.70B
United States
Communication Services
554
+18.86%
1.1M → 1.3M
—
—
$260.69M
Canada
Technology
555
+18.86%
314K → 373K
—
—
$220.29M
United States
Basic Materials
556
+18.77%
3.3M → 3.9M
—
—
$2.11B
United States
Financial Services
557
+18.76%
1.2M → 1.4M
—
—
$1.88B
Brazil
Technology
558
+18.69%
5.3M → 6.3M
—
—
$3.36B
United States
Financial Services
559
+18.68%
899K → 1.1M
—
—
$61.70B
United States
Industrials
560
+18.65%
75.7M → 89.8M
—
—
$1.60B
United States
Consumer Cyclical
561
+18.56%
2.3M → 2.8M
—
—
$34.08M
United States
Healthcare
562
+18.55%
641K → 760K
—
—
$668.93M
Israel
Technology
563
+18.51%
2.5M → 2.9M
—
—
$1.99B
United States
Energy
564
+18.50%
976K → 1.2M
—
—
$276.68M
United States
Real Estate
565
+18.48%
11.0M → 13.1M
—
—
$10.36B
United States
Industrials
566
+18.46%
7.4M → 8.8M
—
—
$133.98B
Japan
Financial Services
567
+18.40%
601K → 712K
—
—
$188.11M
United States
Real Estate
568
+18.38%
254K → 301K
—
—
$671.91M
United States
Consumer Defensive
569
+18.27%
1.1M → 1.3M
—
—
$951.74M
United States
Financial Services
570
+18.27%
2.4M → 2.8M
—
—
$1.09B
Canada
Basic Materials
571
+18.23%
885K → 1.0M
—
—
$13.69M
United States
Healthcare
572
+18.19%
238K → 282K
—
—
$52.46M
United States
Consumer Defensive
573
+18.18%
153K → 181K
—
—
$226.68M
United States
Financial Services
574
+18.16%
326K → 385K
—
—
$30.04M
United States
Financial Services
575
+18.11%
6.3M → 7.4M
—
—
$683.86M
United States
Communication Services
576
+18.06%
394K → 466K
—
—
$1.86B
United States
Financial Services
577
+18.04%
381K → 449K
—
—
$73.34M
United States
Financial Services
578
+18.03%
39K → 46K
—
—
$146.65M
China
Consumer Cyclical
579
+18.02%
76K → 89K
—
—
$301.99M
United States
Financial Services
580
+18.02%
211K → 249K
—
—
$1.24B
United States
Consumer Defensive
581
+17.98%
2.2M → 2.6M
—
—
$5.52B
United States
Consumer Cyclical
582
+17.98%
1.5M → 1.8M
—
—
$19.67B
United States
Industrials
583
+17.94%
149K → 176K
—
—
$1.70B
France
Healthcare
584
+17.90%
4.0M → 4.7M
—
—
$238.55M
United States
Healthcare
585
+17.90%
4.1M → 4.8M
—
—
$8.06B
United States
Financial Services
586
+17.88%
608K → 716K
—
—
$31.14B
Hong Kong
Financial Services
587
+17.82%
1.8M → 2.1M
—
—
$4.35B
United States
Financial Services
588
+17.82%
11.6M → 13.7M
—
—
$3.65B
Canada
Utilities
589
+17.73%
5.1M → 6.0M
—
—
$585.64M
United States
Energy
590
+17.71%
373K → 439K
—
—
$17.20M
United States
Healthcare
591
+17.69%
988K → 1.2M
—
—
$1.69B
United States
Financial Services
592
+17.69%
3.4M → 4.0M
—
—
$5.71B
United States
Industrials
593
+17.67%
4.3M → 5.1M
—
—
$3.41B
United States
Technology
594
+17.67%
7.2M → 8.4M
—
—
$1.43B
United States
Consumer Cyclical
595
+17.63%
21.1M → 24.9M
—
—
$11.34B
United States
Real Estate
596
+17.63%
2.8M → 3.3M
—
—
$3.80B
United States
Technology
597
+17.60%
1.1M → 1.3M
—
—
$827.36M
Bermuda
Industrials
598
+17.53%
637K → 749K
—
—
$2.51B
United States
Industrials
599
+17.53%
168K → 198K
—
—
$373.67M
China
Financial Services
600
+17.50%
1.2M → 1.4M
—
—
$1.25B
Argentina
Real Estate
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

IMUX leads this ranking, followed by IBKR and CSAN. 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.