sahandsydney / pyfinance

PyFinance

Portfolio Optimisation

This is a python package which helps you optimise your portfolio of investments. It provides a range of portfolio optimisation methods using random search algorithm

The package provides a set of tools to help users select the best portfolio for their needs. It provides an easy-to-use interface for optimising portfolios using different methods and criteria. The package also allows users to compare different portfolios, view their performance over time, and make adjustments to their portfolios in order to maximise returns.

The package is designed for both novice and experienced investors. It provides detailed documentation and tutorials to help users get started. The package also provides a set of sample portfolios to help users get started quickly.

This package is released under the MIT license

PyFinance/ ├── init.py └── portfolio_optimization.py

To use this package in your own code, you would first need to install it using pip. Then, you could import it and use its functions and classes like this:

Example :

import portfolio_optimization

Create a portfolio with hypothetical returns and covariances

returns = [0.1, 0.15, 0.2] covariances = [[0.01, 0.002, 0.003], [0.002, 0.04, 0.005], [0.003, 0.005, 0.09]] portfolio = portfolio_optimization.Portfolio(returns, covariances)

Calculate the expected return and volatility of the portfolio

expected_return = portfolio.expected_return() expected_volatility = portfolio.expected_volatility()

Optimize the portfolio using the random search algorithm

optimized_portfolio = portfolio.optimize()

Simulate the performance of the optimized portfolio over 10000 trials

performance = portfolio_optimization.simulate_portfolio_performance(optimized_portfolio, num_trials=10000)