Liquidity

Measure how liquid every fund is to trade over the last year of the period: its average daily volume and dollar volume, that dollar volume relative to the fund’s assets under management, and the price impact of trading 100 million dollars in a day (the Amihud, 2002, illiquidity: the average absolute daily return per dollar traded, scaled to 100 million). An ETF can also be traded through its holdings, so a thinly traded fund of liquid holdings is easier to trade than its own volume suggests; a fund whose holdings are themselves illiquid (small companies, high yield bonds) is not.

For more information, see the following paper:

• Amihud, Y. (2002). “Illiquidity and Stock

Returns: Cross-Section and Time-Series Effects.” Journal of Financial Markets, 5(1), 31-56.

Also known as: ETF liquidity, dollar volume, Amihud illiquidity, price impact.

Liquidity in Python or via the MCP

Install the Finance Toolkit with:

pip install financetoolkit -U

Then call get_liquidity as shown below.

from financetoolkit import Toolkit

toolkit = Toolkit(
    ["VOO", "QQQ", "ARKK"],
    api_key="FINANCIAL_MODELING_PREP_KEY",
    start_date="2025-01-01",
    end_date="2025-12-31",
)

toolkit.etf.get_liquidity(rounding=6)

Or, after setting up the Finance Toolkit MCP, ask:

Which returns:

Parameters

get_liquidity accepts the following parameters.

Related Fund Analysis