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Stocks Weekly LiquidityPriceImprovement
Weekly metrics on price improvement and execution quality for US equities.
772,556 rows over 13,506 symbols, 6 columns, covering 2022-11-25 to 2026-07-10. Refreshed monthly.
Why It Matters
This dataset adds execution quality insights to trading models by:
- Cost control: Price-improvement statistics quantify execution quality relative to quotes.
- Venue selection: Use improvement rates to refine routing strategies and broker evaluation.
- Model realism: Incorporate achievable price improvement into backtests for more accurate P&L expectations.
Load It
Installation/Upgrade:
pip install --upgrade pwb-toolbox
Load the Dataset:
from pwb_toolbox import datasets as pwb_ds
df = pwb_ds.load_dataset("Stocks-Weekly-LiquidityPriceImprovement", symbols=["AAPL"])
print(df.iloc[0, :])
Example Output:
symbol AAPL
datetime 2022-11-25 00:00:00
total_price_improvement 9294.824
shares 9701773
price_improvement_per_share 0.00075
average_price_improvement 0.000958
Columns
| Column Name | Description |
|---|---|
| symbol | Stock ticker. |
| datetime | Week-ending date (YYYY-MM-DD). |
| total_price_improvement | Total notional price improvement captured. |
| shares | Number of shares associated with the measurement. |
| price_improvement_per_share | Price improvement per share. |
| average_price_improvement | Average price improvement per trade. |
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. The same subscription covers the other datasets in this organisation.
Elsewhere
- Dataset page and coverage charts
- The strategy catalogue, 3,806 papers and 4,837 replicated strategies
pwb-toolbox, the loader used in the snippet aboveawesome-systematic-trading, the replicated strategies with their measured Sharpe- Every dataset in this organisation
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.
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