The app works by pulling the stock close data from the yahoo finance api. We then calculate the log returns and the volatility of the data to see what the overall trend for the stocks look like. We then generate random portfolio weights and use scipy to maximize a function that calculates the best portfolio weights for a portfolio with a maximum return to volatility ration (this is known as the Sharpe ratio). This is effectively a Monte Carlo simulation to find the optimal stock portfolio.
- Why Log Returns
- Sharpe Ratio
- Efficient Frontier
- Markowitz Modern Portfolio Theory
- Monte Carlo Simulation
- Volatility
MIT License
Copyright (c) 2021 Greg James
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
This project and it's generated portfolios are NOT investment advice. This is purely educational.
