Calculate the Rate of Change (ROC) for a given price series.

The Rate of Change is a pure momentum oscillator that measures the percentage change in price between the current period and the price a fixed number of periods ago. It oscillates around zero: positive values indicate price is higher than window periods ago (upward momentum), while negative values indicate price is lower (downward momentum).

The formula is as follows:

\[\text{ROC} = (\operatorname{Close}(t) / \operatorname{Close}(t - \text{window}) - 1) \cdot 100\]

Also known as: ROC, Price Rate of Change, momentum.

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Calculate the Rate of Change (ROC) in Python

The Rate of Change (ROC) is available in the Technicals module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_rate_of_change as shown below.

from financetoolkit import Toolkit

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

toolkit.technicals.get_rate_of_change()

Parameters

get_rate_of_change 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 name for closing prices in the historical data. Defaults to “Adj Close”.
  • window (int, optional): Number of periods to look back for the rate of change calculation. Defaults to 12.
  • 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 Rate of Change. 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.
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The Technicals module page introduces the module, and the sidebar lists all of its functions.

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