Volume Weighted Average Price (VWAP)
Calculate the Volume Weighted Average Price (VWAP) for a given price series.
The Volume Weighted Average Price (VWAP) weighs the typical price of each period by its traded volume over a rolling window, giving a more volume-informed view of the average price than a plain moving average.
The formula is as follows:
\[\text{Typical Price} = (\text{High} + \text{Low} + \text{Close}) / 3\] \[\text{VWAP} = \operatorname{Sum}(\text{Typical Price} \cdot \text{Volume},\; \text{Window}) / \operatorname{Sum}(\text{Volume},\; \text{Window})\]The VWAP that trading desks use as an execution benchmark is calculated from the trades of a single session and resets every day. This method computes a rolling VWAP over several periods from the high, low, close and volume of each period, which works as a volume-weighted moving average, not as the intraday benchmark against which fills are measured.
Also known as: VWAP.
Volume Weighted Average Price (VWAP) in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_volume_weighted_average_price as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(
tickers=["SPY"],
api_key="FINANCIAL_MODELING_PREP_KEY",
start_date="2021-01-01",
end_date="2025-12-31",
benchmark_ticker=None,
)
toolkit.technicals.get_volume_weighted_average_price().tail(5)
Or, after setting up the Finance Toolkit MCP, ask:
What was the volume weighted average price of SPY from 24 to 31 December 2025?
Which returns:
| Date | SPY |
|---|---|
| 2025-12-24 | 675.242 |
| 2025-12-26 | 675.346 |
| 2025-12-29 | 675.664 |
| 2025-12-30 | 675.891 |
| 2025-12-31 | 675.847 |
Parameters
get_volume_weighted_average_price accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
period | str | The time period to consider for historical data. Can be “intraday”, “daily”, “weekly”, “monthly”, “quarterly” or “yearly”. Defaults to “daily”. | "weekly" |
close_column | str | The column name for closing prices in the historical data. Defaults to “Adj Close”, in which case the open, high and low prices are adjusted for dividends in the same way. | "Close" |
window | int | Number of periods to consider for the VWAP. The number of periods (time intervals) over which to calculate the VWAP. Defaults to 14. | 20 |
rounding | int | None | The number of decimals to round the results to. Defaults to None, which uses the rounding of the Toolkit (4 unless set otherwise). | 2 |
growth | bool | Whether to calculate the growth of the VWAP. Defaults to False. | True |
lag | int | list[int] | The lag to use for the growth calculation. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |