---
pretty_name: Universe Daily Price
language:
- en
license: other
task_categories:
- time-series-forecasting
- tabular-regression
tags:
- finance
- quantitative-trading
- backtesting
- algorithmic-trading
- market-data
- daily
- ohlcv
- time-series
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"
dataset_info:
  features:
  - name: symbol
    dtype: string
  - name: repo_id
    dtype: string
  - name: liquidity
    dtype: float64
  - name: max_pct_change
    dtype: float64
  splits:
  - name: train
    num_examples: 21693
---

# Universe Daily Price

The index of every symbol carried by the public daily price datasets, with the repository that holds it.

**21,693 rows** over 20,895 symbols, 4 columns. Updated by Papers With Backtest.

## Why It Matters

This is the lookup table the other price datasets need:

- **Routing:** A symbol on its own does not say which file holds it. `repo_id` answers that in one join, so a strategy that mixes equities, futures and rates loads from the right place without hardcoding a map.
- **Liquidity screens:** `liquidity` is the latest close multiplied by the latest volume, which is enough to drop the untradable tail before downloading anything.
- **Sanity screens:** `max_pct_change` is the largest absolute daily move a symbol has ever printed. A series with a 900% day is usually a data error rather than an opportunity, and this column finds those without loading the price history.

## Load It

**Installation/Upgrade:**

```bash
pip install --upgrade pwb-toolbox
```

**Load the Dataset:**

```python
from pwb_toolbox import datasets as pwb_ds

df = pwb_ds.load_dataset("Universe-Daily-Price")
liquid = df[(df["liquidity"] > 1e7) & (df["max_pct_change"] < 0.5)]
print(liquid.groupby("repo_id").size())
```

**Example Output:**

```
symbol                                            AAPL
repo_id          paperswithbacktest/Stocks-Daily-Price
liquidity                                 2.184261e+10
max_pct_change                                0.518692
```

## Columns

| Column Name | Description |
| :--- | :--- |
| **symbol** | The instrument symbol, as it appears in the price file. |
| **repo_id** | The Hugging Face dataset that carries the daily prices for this symbol. |
| **liquidity** | Latest close multiplied by latest volume, in quote currency. |
| **max_pct_change** | Largest absolute daily percent change in closing price over the symbol's history. |

## What This Data Does Not Cover

**The crypto rows over-count by two orders of magnitude.** The index lists 6,730 symbols against `Cryptocurrencies-Daily-Price`, and 88 of them are actually in that file. The other six files line up: 209 of 210 bonds, 166 of 171 currencies, 113 of 117 indices and all 63 commodities resolve to a series that exists. Check membership against the price file before treating a row here as tradable.

**No dates.** This is a snapshot of the current universe, not a history of it. `liquidity` and `max_pct_change` describe the symbol as of the last refresh, so neither can be used point-in-time.

## 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 the other datasets in this organisation.

## Elsewhere

- [Dataset page and coverage charts](https://paperswithbacktest.com/datasets/universe-daily-price)
- [The strategy catalogue](https://paperswithbacktest.com/strategies), 3,806 papers and 4,837 replicated strategies
- [`pwb-toolbox`](https://github.com/paperswithbacktest/pwb-toolbox), the loader used in the snippet above
- [`awesome-systematic-trading`](https://github.com/paperswithbacktest/awesome-systematic-trading), the replicated strategies with their measured Sharpe
- [Every dataset in this organisation](https://huggingface.co/datasets/paperswithbacktest)

Papers With Backtest publishes 32 datasets on the Hub and codes the papers that use them. Every strategy in the catalogue is run over its own full history before it is published, which is where the numbers above come from.