Application aims to offer clients a one-stop online investment solution for their retirement portfolios that’s both inexpensive and high quality. In this application, there are evaluations of the four investment firm that has the most potential investment based on key risk-management metrics: the daily returns, standard deviations, Sharpe ratios, and betas.
This project leverages python 3.7 with the pandas library. Also, using Jupyter notebook in order to organize the code frame.
Before running the application first install the following dependencies.
pip install pandas
pip install jupyterlabTo use this application, simply clone the repository and open jupyter lab from git bash by running the following command:
jupyter lab
After launching the application, navigate risk_return_analysis.ipynb notebook in the repository.
https://github.com/nguyendao21/Portfolio-Risk-Return-Analysis-Application/issues/1#issue-1092091611
daosynguyen21@gmail.com
MIT