Stocks-Daily-Splits / README.md
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---
pretty_name: Stocks Daily Splits
language:
- en
license: other
task_categories:
- time-series-forecasting
- tabular-regression
tags:
- finance
- quantitative-trading
- backtesting
- algorithmic-trading
- stocks
- equities
- daily
- corporate-actions
size_categories:
- 10K<n<100K
extra_gated_prompt: "This dataset is free to browse and gated for download. Approval is tied to a Papers With Backtest subscription, which also covers the other datasets in this organisation and the strategy catalogue at https://paperswithbacktest.com. Plans and what each one includes: https://paperswithbacktest.com/pricing"
---
# Stocks Daily Splits
Every stock split and reverse split of a US-listed name, with its ratio and the factor applied to earlier prices.
<!-- MEASURED:START - rewritten by dataset_cards/refresh.py -->
Shape measured at the next refresh of `dataset_cards/facts.json`. Refreshed monthly.
<!-- MEASURED:END -->
## Why It Matters
`Stocks-Daily-Price` is back-adjusted, so a split leaves no trace in it: the price series shows nothing on the day. That hides the event the split papers study -- the announcement drift, the post-split change in liquidity and in the shareholder base, and the reverse split as a distress signal. This table is the event. A row with `split_from` 1 and `split_to` 4 is a 4-for-1 split; `split_from` 10 and `split_to` 1 is a 1-for-10 reverse split.
## Load It
```bash
pip install --upgrade pwb-toolbox
```
```python
from pwb_toolbox import datasets as pwb_ds
df = pwb_ds.load_dataset("Stocks-Daily-Splits", symbols=["AAPL"])
print(df.iloc[-1, :])
```
## Columns
| Column Name | Description |
| :--- | :--- |
| **symbol** | Stock ticker. |
| **date** | Execution date: the first session the shares trade on the new basis. |
| **split_from** | Shares held before, per `split_to` shares after. |
| **split_to** | Shares held after, per `split_from` shares before. |
| **adjustment_type** | The vendor's classification of the action (forward, reverse, ...). |
| **historical_adjustment_factor** | Factor to multiply prices before `date` by, to put them on the post-split basis. |
## Access
Browsing the card and the schema is open to anyone. Downloading the files needs an approved request, tied to a subscription: [what each plan includes](https://paperswithbacktest.com/pricing). The same subscription covers every dataset in this organisation and the strategy catalogue.
## Elsewhere
- [The strategy catalogue](https://paperswithbacktest.com/strategies)
- [`pwb-toolbox`](https://github.com/paperswithbacktest/pwb-toolbox), the loader used in the snippet above
- [Every dataset in this organisation](https://huggingface.co/datasets/paperswithbacktest)