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97 lines
3.0 KiB
Markdown
Vendored
97 lines
3.0 KiB
Markdown
Vendored
---
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title: var
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description: This Docusaurus page contains Python source code for 'var/model' and
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'var chart' functions. Each section provides detailed explanations of parameters
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and returns, and links to the respective source code. The functions are a part of
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quantitative analysis of a specified stock dataframe.
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keywords:
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- Docusaurus page
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- tab items
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- Python code
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- quantitative analysis
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- dataframe
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- var/model
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- var chart
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- parameters
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- returns
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---
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import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
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<HeadTitle title="qa.var - Reference | OpenBB SDK Docs" />
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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<Tabs>
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<TabItem value="model" label="Model" default>
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Gets value at risk for specified stock dataframe.
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Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/common/quantitative_analysis/qa_model.py#L224)]
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```python
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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)
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```
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---
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## Parameters
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| Name | Type | Description | Default | Optional |
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| ---- | ---- | ----------- | ------- | -------- |
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| data | pd.DataFrame | Data dataframe | None | False |
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| use_mean | bool | If one should use the data mean for calculation | False | True |
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| adjusted_var | bool | If one should return VaR adjusted for skew and kurtosis | False | True |
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| student_t | bool | If one should use the student-t distribution | False | True |
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| percentile | Union[int,float] | VaR percentile | 99.9 | True |
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| portfolio | bool | If the data is a portfolio | False | True |
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---
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## Returns
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| Type | Description |
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| ---- | ----------- |
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| pd.DataFrame | DataFrame with Value at Risk per percentile |
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---
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</TabItem>
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<TabItem value="view" label="Chart">
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Prints table showing VaR of dataframe.
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Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/common/quantitative_analysis/qa_view.py#L1048)]
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```python
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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)
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```
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---
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## Parameters
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| Name | Type | Description | Default | Optional |
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| ---- | ---- | ----------- | ------- | -------- |
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| data | pd.Dataframe | Data dataframe | None | False |
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| use_mean | bool | if one should use the data mean return | False | True |
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| symbol | str | name of the data | | True |
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| adjusted_var | bool | if one should have VaR adjusted for skew and kurtosis (Cornish-Fisher-Expansion) | False | True |
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| student_t | bool | If one should use the student-t distribution | False | True |
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| percentile | int | var percentile | 99.9 | True |
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| data_range | int | Number of rows you want to use VaR over | 0 | True |
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| portfolio | bool | If the data is a portfolio | False | True |
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---
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## Returns
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This function does not return anything
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---
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</TabItem>
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</Tabs>
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