kurtosis
Calculate the rolling kurtosis of a target column within a given window size.
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 over a specified rolling window.
Examples
from openbb import obb
# Get Rolling 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.rolling.kurtosis(data=returns, target="close", window=252)
obb.quantitative.rolling.kurtosis(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}])
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 | |
| 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 |
Returns
OBBject
List