var
- Model
- Chart
Gets value at risk for specified stock dataframe.
Source Code: [link]
openbb.qa.var(data: pd.DataFrame, use_mean: bool = False, adjusted_var: bool = False, student_t: bool = False, percentile: Union[int, float] = 99.9, portfolio: bool = False)
Parameters
Name | Type | Description | Default | Optional |
---|---|---|---|---|
data | pd.DataFrame | Data dataframe | None | False |
use_mean | bool | If one should use the data mean for calculation | False | True |
adjusted_var | bool | If one should return VaR adjusted for skew and kurtosis | False | True |
student_t | bool | If one should use the student-t distribution | False | True |
percentile | Union[int,float] | VaR percentile | 99.9 | True |
portfolio | bool | If the data is a portfolio | False | True |
Returns
Type | Description |
---|---|
pd.DataFrame | DataFrame with Value at Risk per percentile |
Prints table showing VaR of dataframe.
Source Code: [link]
openbb.qa.var_chart(data: pd.DataFrame, symbol: str = "", use_mean: bool = False, adjusted_var: bool = False, student_t: bool = False, percentile: float = 99.9, data_range: int = 0, portfolio: bool = False)
Parameters
Name | Type | Description | Default | Optional |
---|---|---|---|---|
data | pd.Dataframe | Data dataframe | None | False |
use_mean | bool | if one should use the data mean return | False | True |
symbol | str | name of the data | True | |
adjusted_var | bool | if one should have VaR adjusted for skew and kurtosis (Cornish-Fisher-Expansion) | False | True |
student_t | bool | If one should use the student-t distribution | False | True |
percentile | int | var percentile | 99.9 | True |
data_range | int | Number of rows you want to use VaR over | 0 | True |
portfolio | bool | If the data is a portfolio | False | True |
Returns
This function does not return anything