quantile
Calculate the rolling quantile of a target column within a given window size at a specified quantile percentage.
Quantiles are points dividing the range of a probability distribution into intervals with equal probabilities, or dividing the sample in the same way. This function is useful for understanding the distribution of data within a specified window, allowing for analysis of trends, identification of outliers, and assessment of risk.
Example
from openbb import obb
stock_data = obb.equity.price.historical(symbol="TSLA", start_date="2023-01-01", provider="fmp").to_df()
returns = stock_data["close"].pct_change().dropna()
obb.quantitative.rolling.quantile(data=returns, target="close", window=252, quantile_pct=0.25)
obb.quantitative.rolling.quantile(data=returns, target="close", window=252, quantile_pct=0.75)
Parameters
- standard
| Name | Type | Description | Default | Optional |
|---|---|---|---|---|
| data | List[Data] | The time series data as a list of data points. | False | |
| target | str | The name of the column for which to calculate the quantile. | False | |
| window | int | The number of observations used for calculating the rolling measure. | 21 | False |
| quantile_pct | float | The quantile percentage to calculate (e.g., 0.5 for median), default is 0.5. | 0.5 | False |
| index | str | The name of the index column, default is "date". | date | False |
Returns
OBBject
results : List[Data]
An object containing the rolling quantile values with the median.