All Overlap Indicators
Calculates and collects various overlap-based indicators based on the provided data.
All Overlap Indicators in Python
collect_overlap_indicators is part of the Technicals module of the open-source Finance Toolkit. Install it with:
pip install financetoolkit -U
Then call collect_overlap_indicators as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(tickers=["AAPL", "MSFT"])
toolkit.technicals.collect_overlap_indicators().xs("AAPL", level=1, axis="columns")
Which returns:
| Date | Simple Moving Average (SMA) | Exponential Moving Average (EMA) |
|---|---|---|
| 2026-06-18 | 300.742 | 298.807 |
| 2026-06-22 | 300.078 | 298.567 |
| 2026-06-23 | 298.585 | 297.998 |
| 2026-06-24 | 297.358 | 297.342 |
| 2026-06-25 | 294.781 | 294.383 |
| 2026-06-26 | 293.098 | 292.969 |
| 2026-06-29 | 291.684 | 291.472 |
| 2026-06-30 | 291.599 | 291.191 |
| 2026-07-01 | 291.799 | 291.616 |
| 2026-07-02 | 292.727 | 293.884 |
Parameters
collect_overlap_indicators 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”.
- window (int, optional): The window size for calculating indicators. Defaults to 14.
- close_column (str, optional): The name of the column containing the close prices. Defaults to “Adj Close”.
- 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.