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

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variance	Calculate the rolling variance of a target column within a given window size	quantitative rolling variance

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Calculate the rolling variance of a target column within a given window size.

Variance measures the dispersion of a set of data points around their mean. It is a key metric for assessing the volatility and stability of financial returns or other time series data over a specified rolling window.

Examples

from openbb import obb
# Get Rolling Variance.
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.variance(data=returns, target="close", window=252)
obb.quantitative.rolling.variance(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 variance.		False
window	PositiveInt	The number of observations used for calculating the rolling measure.		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 variance values.