OpenBB/website/content/platform/reference/quantitative/rolling/quantile.md

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quantile	Calculate the rolling quantile of a target column within a given window size at a specified quantile percentage	quantitative rolling quantile

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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.

Examples

from openbb import obb
# Get Rolling Quantile.
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)
obb.quantitative.rolling.quantile(target='close', window=2, data=[{'date': '2023-01-02', 'close': 0.05}, {'date': '2023-01-03', 'close': 0.08}, {'date': '2023-01-04', 'close': 0.07}, {'date': '2023-01-05', 'close': 0.06}, {'date': '2023-01-06', 'close': 0.06}])

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Parameters

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	PositiveInt	The number of observations used for calculating the rolling measure.		False
quantile_pct	NonNegativeFloat, optional	The quantile percentage to calculate (e.g., 0.5 for median), default is 0.5.		False
index	str, optional	The name of the index column, default is "date".		False

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Returns

OBBject
    results : List[Data]
        An object containing the rolling quantile values with the median.