/RiskyBusiness

[Open-source contribution] downloads 10K+ : PyPi. A Python library containing various functions to analyze the risk of a business.

Primary LanguageJupyter NotebookMIT LicenseMIT

Analyse the risk of a business using Risky Business

Links :

Functions :

  1. Sharpe Ratio
  2. Returns & Volatility
  3. Risk by Return Ratio
  4. Compounded Percentage
  5. Annual Drawdown
  6. Skewness & Kurtosis
  7. Value Added Risk (VaR - Historic, Gaussian, Cornish-Fisher)
  8. CVaR - Historic
  9. VaR Comparison Plot

Important : Read the DOCUMENTATION.md file before implementing any of the functions.

Installation

Use the package manager pip to install riskybusiness

pip install riskybusiness

Usage

import riskybusiness as rb
rb.FunctionName(dataset = Your_Dataset)

Make sure the dataset is loaded using pandas with the necessary columns.

A sample program using all the functions is displayed in risky.ipynb

  • Open using Jupyter NB or Google Colab
  • This file contains the output samples of all the functions present in the library.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT

Update 0.0.2

Added New Functions :

10.

rb.skewness(dataset)

Description

Computes & returns the skewness of each column.

Parameters

dataset - Name of the dataset you imported.

11.

rb.kurtosis(dataset)

Description

Computes & returns the kurtosis of each column.

Parameters

dataset - Name of the dataset you imported.

12.

rb.var_historic(dataset)

Description

Computes & Returns the historic Value at Risk at a specified level i.e. returns the number such that "level" percent of the returns fall below that number, and the (100-level) percent are above.

Parameters

dataset - Name of the dataset you imported.

13.

rb.cvar_historic(dataset)

Description

Computes & Returns the Conditional VaR of a Series or DataFrame.

Parameters

dataset - Name of the dataset you imported.

14.

rb.var_gaussian(dataset)

Description

Computes & Returns the Parametric Gauusian VaR of a Series or DataFrame

Parameters

dataset - Name of the dataset you imported.

15.

rb.var_fisher(dataset)

Description

The VaR is returned using the Cornish-Fisher modification

Parameters

dataset - Name of the dataset you imported.

16.

rb.plotvar(dataset)

Description

Plots the comparison bar graph between the 3 VaR methods - Historic, Gaussian, Cornish-Fisher.

Parameters

dataset - Name of the dataset you imported.

Find the description of all the functions in the DOCUMENTATION.md file.