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cik
large_stringlengths
10
10
valid_from
date32
valid_to
date32
cumulative_split_factor
float64
0
1.08k
splits_after
int32
0
8
confidence
large_stringclasses
3 values
inserted_at
timestamp[us, tz=UTC]date
2026-09-07 10:37:01
2026-09-07 10:37:01
0000001961
2018-04-02
null
1
0
high
2026-09-07T10:37:01.254000
0000001961
null
2015-02-06
0.3
2
medium
2026-09-07T10:37:01.254000
0000001961
2015-02-06
2018-04-02
0.2
1
medium
2026-09-07T10:37:01.254000
0000002186
2023-11-09
null
1
0
high
2026-09-07T10:37:01.254000
0000002186
null
2023-11-09
0.2
1
medium
2026-09-07T10:37:01.254000
0000002488
2019-02-08
null
1
0
high
2026-09-07T10:37:01.254000
0000002488
2019-02-08
2019-02-08
2
1
low
2026-09-07T10:37:01.254000
0000002488
null
2019-02-08
1
2
low
2026-09-07T10:37:01.254000
0000003116
2016-05-10
null
1
0
high
2026-09-07T10:37:01.254000
0000003116
null
2016-05-10
0.001
1
medium
2026-09-07T10:37:01.254000
0000003545
2023-08-03
null
1
0
high
2026-09-07T10:37:01.254000
0000003545
null
2023-08-03
0.001
1
medium
2026-09-07T10:37:01.254000
0000004281
2016-11-09
null
1
0
high
2026-09-07T10:37:01.254000
0000004281
null
2016-11-09
0.333333
1
medium
2026-09-07T10:37:01.254000
0000004977
2018-05-03
null
1
0
high
2026-09-07T10:37:01.254000
0000004977
null
2018-05-03
2
1
medium
2026-09-07T10:37:01.254000
0000005272
2018-02-16
null
1
0
high
2026-09-07T10:37:01.254000
0000005272
null
2012-08-02
2
2
medium
2026-09-07T10:37:01.254000
0000005272
2012-08-02
2018-02-16
1.333333
1
medium
2026-09-07T10:37:01.254000
0000006176
2023-05-10
null
1
0
high
2026-09-07T10:37:01.254000
0000006176
null
2023-05-10
0.001
1
medium
2026-09-07T10:37:01.254000
0000006201
2020-02-19
null
1
0
high
2026-09-07T10:37:01.254000
0000006201
2015-02-25
2015-02-25
3
2
medium
2026-09-07T10:37:01.254000
0000006201
null
2015-02-25
4
3
medium
2026-09-07T10:37:01.254000
0000006201
2015-02-25
2020-02-19
1.5
1
low
2026-09-07T10:37:01.254000
0000006207
2021-03-11
null
1
0
high
2026-09-07T10:37:01.254000
0000006207
null
2021-03-11
0.001
1
medium
2026-09-07T10:37:01.254000
0000006769
2016-11-03
null
1
0
high
2026-09-07T10:37:01.254000
0000006769
2016-08-04
2016-08-04
8.75
2
low
2026-09-07T10:37:01.254000
0000006769
null
2016-08-04
15.75
3
low
2026-09-07T10:37:01.254000
0000006769
2016-08-04
2016-11-03
2.5
1
low
2026-09-07T10:37:01.254000
0000007039
2014-03-14
null
1
0
high
2026-09-07T10:37:01.254000
0000007039
null
2014-03-14
1.5
1
low
2026-09-07T10:37:01.254000
0000007332
2013-10-31
null
1
0
high
2026-09-07T10:37:01.254000
0000007332
null
2013-10-31
1.5
1
low
2026-09-07T10:37:01.254000
0000008063
2017-08-31
null
1
0
high
2026-09-07T10:37:01.254000
0000008063
null
2017-08-31
1.333333
1
medium
2026-09-07T10:37:01.254000
0000008146
2018-04-10
null
1
0
high
2026-09-07T10:37:01.254000
0000008146
null
2018-04-10
0.001
1
medium
2026-09-07T10:37:01.254000
0000008504
2025-03-31
null
1
0
high
2026-09-07T10:37:01.254000
0000008504
null
2014-11-14
0
4
medium
2026-09-07T10:37:01.254000
0000008504
2014-11-14
2024-08-14
0.000001
3
medium
2026-09-07T10:37:01.254000
0000008504
2024-08-14
2024-11-19
0.00002
2
medium
2026-09-07T10:37:01.254000
0000008504
2024-11-19
2025-03-31
0.02
1
medium
2026-09-07T10:37:01.254000
0000008947
2012-10-01
null
1
0
high
2026-09-07T10:37:01.254000
0000008947
null
2012-10-01
2
1
medium
2026-09-07T10:37:01.254000
0000009092
2019-02-26
null
1
0
high
2026-09-07T10:37:01.254000
0000009092
null
2016-10-26
0.002
2
medium
2026-09-07T10:37:01.254000
0000009092
2016-10-26
2019-02-26
0.001
1
medium
2026-09-07T10:37:01.254000
0000009235
2014-11-14
null
1
0
high
2026-09-07T10:37:01.254000
0000009235
null
2014-11-14
0.001
1
medium
2026-09-07T10:37:01.254000
0000009346
2016-11-09
null
1
0
high
2026-09-07T10:37:01.254000
0000009346
null
2016-11-09
0.001
1
medium
2026-09-07T10:37:01.254000
0000009389
2011-08-09
null
1
0
high
2026-09-07T10:37:01.254000
0000009389
null
2011-08-09
2
1
high
2026-09-07T10:37:01.254000
0000011544
2026-02-27
null
1
0
high
2026-09-07T10:37:01.254000
0000011544
null
2026-02-27
1.5
1
medium
2026-09-07T10:37:01.254000
0000012040
2019-12-20
null
1
0
high
2026-09-07T10:37:01.254000
0000012040
null
2019-12-20
0.001
1
medium
2026-09-07T10:37:01.254000
0000012208
2019-03-30
null
1
0
high
2026-09-07T10:37:01.254000
0000012208
null
2019-03-30
1.25
1
low
2026-09-07T10:37:01.254000
0000012239
2012-11-14
null
1
0
high
2026-09-07T10:37:01.254000
0000012239
null
2012-11-14
0.05
1
medium
2026-09-07T10:37:01.254000
0000014177
2023-08-18
null
1
0
high
2026-09-07T10:37:01.254000
0000014177
null
2023-08-18
0.001
1
medium
2026-09-07T10:37:01.254000
0000014693
2018-06-13
null
1
0
high
2026-09-07T10:37:01.254000
0000014693
null
2012-09-05
9.375
4
medium
2026-09-07T10:37:01.254000
0000014693
2012-09-05
2016-12-07
6.25
3
medium
2026-09-07T10:37:01.254000
0000014693
2016-12-07
2018-03-07
3.125
2
medium
2026-09-07T10:37:01.254000
0000014693
2018-03-07
2018-06-13
2.5
1
low
2026-09-07T10:37:01.254000
0000015847
2019-09-13
null
1
0
high
2026-09-07T10:37:01.254000
0000015847
null
2019-09-13
0.001
1
medium
2026-09-07T10:37:01.254000
0000016099
2012-11-13
null
1
0
high
2026-09-07T10:37:01.254000
0000016099
null
2012-11-13
1.5
1
low
2026-09-07T10:37:01.254000
0000016160
2015-07-20
null
1
0
high
2026-09-07T10:37:01.254000
0000016160
null
2015-07-20
2
1
high
2026-09-07T10:37:01.254000
0000016868
2014-02-03
null
1
0
high
2026-09-07T10:37:01.254000
0000016868
null
2014-02-03
2
1
medium
2026-09-07T10:37:01.254000
0000016875
2021-07-28
null
1
0
high
2026-09-07T10:37:01.254000
0000016875
null
2021-07-28
5
1
medium
2026-09-07T10:37:01.254000
0000017485
2013-08-09
null
1
0
high
2026-09-07T10:37:01.254000
0000017485
null
2013-08-09
0.001
1
medium
2026-09-07T10:37:01.254000
0000018230
2017-02-15
null
1
0
high
2026-09-07T10:37:01.254000
0000018230
null
2017-02-15
1.5
1
low
2026-09-07T10:37:01.254000
0000018349
2014-08-06
null
1
0
high
2026-09-07T10:37:01.254000
0000018349
null
2014-08-06
0.142857
1
medium
2026-09-07T10:37:01.254000
0000018396
2016-03-03
null
1
0
high
2026-09-07T10:37:01.254000
0000018396
null
2016-03-03
5
1
low
2026-09-07T10:37:01.254000
0000018937
2011-10-25
null
1
0
high
2026-09-07T10:37:01.254000
0000018937
null
2011-10-25
0.001
1
medium
2026-09-07T10:37:01.254000
0000019446
2013-09-30
null
1
0
high
2026-09-07T10:37:01.254000
0000019446
null
2013-09-30
1.5
1
medium
2026-09-07T10:37:01.254000
0000019745
2014-11-06
null
1
0
high
2026-09-07T10:37:01.254000
0000019745
null
2013-11-07
0.0015
2
medium
2026-09-07T10:37:01.254000
0000019745
2013-11-07
2014-11-06
1.5
1
medium
2026-09-07T10:37:01.254000
0000020212
2023-07-26
null
1
0
high
2026-09-07T10:37:01.254000
0000020212
null
2019-02-27
6
2
medium
2026-09-07T10:37:01.254000
0000020212
2019-02-27
2023-07-26
2
1
medium
2026-09-07T10:37:01.254000
0000020520
2017-08-03
null
1
0
high
2026-09-07T10:37:01.254000
0000020520
null
2017-08-03
0.066667
1
medium
2026-09-07T10:37:01.254000
End of preview. Expand in Data Studio

US Corporate Actions — dividends and splits

391 639 dividends from 3 327 filers · 5 619 splits from 3 814 filers · 2005 to 2026

Built to close a specific hole. A filing states shares and earnings per share as of the day it was made; every price series is adjusted for splits since. Multiply one by the other and the answer is wrong by the split factor — on Deckers that turned a 6.9% earnings yield into 41.7%, a P/E of 1.8.

The pipeline lives in recipe/ at the same revision as the data. See PIPELINE.md for the method.

Read this before anything else

There are no ex-dates, record dates or pay dates here, and there is no free source for them. SEC's structured data carries only numeric facts; the date-typed XBRL facts exist inside filings but not in the bulk data sets, and the XBRL API returns 404 for them. What this dataset has is what can be had from public filings: how much per share, over which fiscal period, known from when — and split ratios recovered from the trace a split leaves in restated figures.

If you need an ex-date calendar, this is not it, and nothing free is.

The adjustment factor

This is the table most people want. Multiply an as-filed per-share figure by cumulative_split_factor to put it on the same basis as a split-adjusted price series.

import polars as pl

factors = pl.read_parquet("data/adjustment_factors/*.parquet")

# Deckers: a 6-for-1 split detected between 2024-08-01 and 2024-10-31
factors.filter(pl.col("cik") == "0000910521")
# valid_from    valid_to      cumulative_split_factor  splits_after
# null          2024-10-31    6.0                      1
# 2024-10-31    null          1.0                      0

Shares outstanding filed before that window need multiplying by six; earnings per share need dividing by it. Apple carries 28.0 before its 2014 seven-for-one (7 × 4), 4.0 between the two, and 1.0 today.

Splits, and how confident to be

No free feed of US splits exists. What exists, in a dataset that keeps every filing's own version of a period, is the trace: a split forces the company to restate every earlier per-share figure by the ratio. Two filings covering the same quarter, one before and one after, differ by exactly that factor.

That is stronger than the obvious signal. A jump in shares outstanding looks identical for a two-for-one split and an equity raise that doubled the count; only a split reaches back and rewrites the past.

Confidence Rows What it means
high 514 the filer tagged the conversion ratio, or both methods found it
medium 3 728 inferred from four or more restated figures
low 1 377 inferred from two or three

Verified against the ratios filers tagged themselves: the two methods agree for 73% of the companies where both exist, and the inferred method reaches seven times as many companies.

Each split carries a window, not a date: detected_after is the last filing that still used the old figures, detected_before the first that used the new. Deckers' September 2024 split lands in 2024-08-01 → 2024-10-31. That is as precise as filings allow, and a date invented inside that window would be a fiction.

Reverse splits outnumber forward ones almost three to one — 3 933 to 1 686 — which is what the SEC filer universe actually looks like once you leave the index names: shells consolidate to keep a listing far more often than successful companies split.

Dividends

Per-share amounts as filings stated them, for a fiscal period.

declared 276 299 — a decision made in the period
cash_paid 115 340 — cash that moved in the period
common / preferred 369 413 / 22 226
restated later 223 583 rows are a second or later report of the same period
subsequent events 769 declared after the period closed, disclosed in the filing that follows

Declared and paid are kept apart rather than merged: they are different facts, and a company can declare in one quarter and pay in the next. Preferred dividends are included because a preferred coupon ranks ahead of the common holder, and a yield computed without it is wrong for exactly the companies where it matters.

period_start is derived from period_end and quarters; a dividend fact dated to an instant is dropped rather than assigned a day it did not cover.

Configs

Config Rows What one row is
dividends 391 639 one per-share dividend a filing stated for one period
splits 5 619 one split, with the window it must have happened in
adjustment_factors 9 433 one span and the factor that puts an as-filed figure on today's basis
pit 397 258 one point-in-time action event, plus a Delta table for ziplime

entity_id in pit is the issuer CIK, the same key used across the family, so this joins directly to company-fundamentals, insider-trading and security-master.

Known gaps

  • No dividend dates. See above. The period is the finest granularity available.
  • A split window is a window. Typically one quarter wide.
  • Splits before 2009 are not visible. The restatement trace needs XBRL, and XBRL starts in 2009 Q1. A company that split in 2006 shows no split here.
  • Stock dividends under 18% are not detected. A five percent stock dividend and a five percent restatement leave the same trace, so nothing between 0.85 and 1.18 is admitted as a split rather than risk phantom factors.
  • Special and irregular dividends are not separated from regular ones. The filing usually does not distinguish them either.
  • Low-confidence splits are published, not hidden. Filter on confidence if a wrong factor would be worse than a missing one.

Provenance and updates

Derived entirely from ZipLime/company-fundamentals, which is itself SEC XBRL — US Government work, public domain. No source of its own is fetched.

Rebuilt weekly, Monday 08:10 UTC, after the dataset it reads.

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