Root Mean Squared Error (RMSE)
Calculate the Root Mean Squared Error (RMSE) between every unordered pair of tickers’ series in the Toolkit instance.
Also known as: RMSD (Root Mean Squared Deviation).
See forecast_evaluation_model.get_rmse for the formula. This controller method compares two ASSETS’ series directly, treating one as a naive “forecast” proxy for the other – a simple, tracking-error style measure of how closely two series move together in absolute deviation terms (e.g. a portfolio versus a benchmark, or one asset as a naive stand-in forecast for a similar one). For evaluating an actual FORECASTING MODEL (ARIMA/VAR) rather than one asset as a naive proxy for another, use get_out_of_sample_validation instead.
Root Mean Squared Error (RMSE) in Python
get_rmse is part of the Econometrics module of the open-source Finance Toolkit. Install it with:
pip install financetoolkit -U
Then call get_rmse as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(["AAPL", "MSFT"], api_key="FINANCIAL_MODELING_PREP_KEY")
toolkit.econometrics.get_rmse(period="quarterly")
Which returns:
| Ticker A | Ticker B | RMSE |
|---|---|---|
| AAPL | MSFT | 0.1084 |
Parameters
get_rmse accepts the following parameters:
- period (str, optional): The data frequency (daily, weekly, monthly, quarterly, or yearly). Defaults to “daily”.
- column (str, optional): The historical data column to compare. Defaults to “Return”.
- include_benchmark (bool, optional): Whether to include “Benchmark” among the tickers paired up. Defaults to False.
- rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.