Calculate the Chande Momentum Oscillator (CMO) for a given price series.

The Chande Momentum Oscillator is an indicator that measures the momentum of a price series and identifies overbought and oversold conditions.

The formula is as follows:

\[\text{CMO} = ((\text{Sum of Upward Change}) - (\text{Sum of Downward Change})) / ((\text{Sum of Upward Change}) + (\text{Sum of Downward Change}))\]

Also known as: CMO, Chande momentum.

No programming experience? With the Finance Toolkit MCP server, AI assistants such as Claude and ChatGPT can calculate the Chande Momentum Oscillator (CMO) for you. Just ask in plain English.

Calculate the Chande Momentum Oscillator (CMO) in Python

The Chande Momentum Oscillator (CMO) is available in the Technicals module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_chande_momentum_oscillator as shown below.

from financetoolkit import Toolkit

toolkit = Toolkit(tickers=["AAPL", "MSFT"])

toolkit.technicals.get_chande_momentum_oscillator()

Which returns:

Date AAPL MSFT Benchmark
2026-06-18 -21.8609 -62.8906 -10.2182
2026-06-22 -15.625 -81.4368 -14.7997
2026-06-23 -39.1826 -66.1723 -24.6608
2026-06-24 -34.6231 -64.2442 -20.9163
2026-06-25 -54.1904 -69.4937 -23.1112
2026-06-26 -33.0342 -37.3504 -10.1446
2026-06-29 -29.3073 -37.0653 1.8792
2026-06-30 -1.8539 -26.9917 9.8861
2026-07-01 4.1068 -11.1036 23.1787
2026-07-02 16.5859 0.1282 9.1933

Parameters

get_chande_momentum_oscillator accepts the following parameters:

  • period (str, optional): The time period to consider for historical data. Can be “daily”, “weekly”, “quarterly”, or “yearly”. Defaults to “daily”.
  • close_column (str, optional): The column in the historical data that represents the closing prices. Defaults to “Adj Close”.
  • window (int, optional): The number of periods to consider for the CMO calculation. Defaults to 14.
  • rounding (int | None, optional): The number of decimals to round the results to. Defaults to 4.
  • growth (bool, optional): Whether to calculate the growth of the indicator values. Defaults to False.
  • lag (int | list[int], optional): The lag to use for the growth calculation.
  • standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. Defaults to 1.

The Technicals module page introduces the module, and the sidebar lists all of its functions.

Share