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Stocks Weekly LiquidityMarketOpportunity

Weekly measurements of displayed liquidity and market opportunity for US equities.

507,891 rows over 13,116 symbols, 19 columns, covering 2023-11-27 to 2026-07-03. Refreshed monthly.

Why It Matters

This dataset integrates liquidity constraints into trading system design by:

  • Execution planning: Liquidity and opportunity metrics inform venue routing, order slicing, and slippage assumptions.
  • Capacity checks: Weekly aggregates help size positions for intraday and swing strategies without exceeding market depth.
  • Signal conditioning: Adjust model outputs by liquidity availability to avoid trading illiquid names.

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-LiquidityMarketOpportunity", symbols=["AAPL"])
print(df.iloc[0, :])

Example Output:

symbol                                   AAPL
datetime                  2023-11-27 00:00:00
missed_liquidity                      7329076
exhausted_liquidity                   1681740
routed_liquidity                       182015
volume_opportunity                    9192832
average_daily_vol                   4650741.0
rolling_daily_vol                   4650741.0
buy_pressure_log                     0.043455
buy_pressure_pct                     0.407939
missed_liquid_pct                     0.79726
exhausted_liquid_pct                  0.18294
vol_uncaptured                            0.5
retail_pressure                      0.871567
institutional_pressure               0.713661
algorithmic_pressure                 0.705546
retail_institute_ratio               1.221261
algo_institute_ratio                 0.988629
retail_algo_ratio                    1.235307

Columns

Column Name Description
symbol Stock ticker.
datetime Week-ending date (YYYY-MM-DD).
missed_liquidity Volume of liquidity not captured.
exhausted_liquidity Volume of liquidity exhausted.
routed_liquidity Volume routed elsewhere.
volume_opportunity Total volume opportunity measured.
average_daily_vol Average daily volume baseline.
rolling_daily_vol Rolling daily volume measure.
buy_pressure_log Log-transformed buy pressure metric.
buy_pressure_pct Percentage-based buy pressure metric.
missed_liquid_pct Percentage of liquidity missed.
exhausted_liquid_pct Percentage of liquidity exhausted.
vol_uncaptured Share of volume left uncaptured.
retail_pressure Retail participation pressure metric.
institutional_pressure Institutional participation pressure metric.
algorithmic_pressure Algorithmic participation pressure metric.
retail_institute_ratio Ratio of retail to institutional pressure.
algo_institute_ratio Ratio of algorithmic to institutional pressure.
retail_algo_ratio Ratio of retail to algorithmic pressure.

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

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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