kurtosis

Calculate the rolling kurtosis of a target column.

Kurtosis measures the "tailedness" of the probability distribution of a real-valued random variable. High kurtosis indicates a distribution with heavy tails (outliers), suggesting a higher risk of extreme outcomes. Low kurtosis indicates a distribution with lighter tails (less outliers), suggesting less risk of extreme outcomes. This function helps in assessing the risk of outliers in financial returns or other time series data.

Examples

from openbb import obb
# Get Kurtosis.
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.stats.kurtosis(data=returns, target="close")
obb.quantitative.stats.kurtosis(target='close', 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}])

---

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 kurtosis.		False

---

Returns

OBBject
    List