Portfolio Optimization with Transaction Costs using Python

In this tutorial, we will explore the concept of portfolio optimization with transaction costs using Python. Portfolio optimization is a crucial aspect of financial analysis and it involves the process of constructing a portfolio of assets to maximize returns or minimize risk. Transaction costs are an essential consideration in portfolio optimization as they can significantly impact the performance of a portfolio. We will use the yfinance library to download financial data for real assets and demonstrate how to optimize a portfolio while accounting for transaction costs.

Photo by Kevin Ku on Unsplash

Getting Started

Before we delve into portfolio optimization, let’s ensure that we have all the necessary libraries installed. We will need yfinance for downloading financial data, pandas for data manipulation, numpy for numerical computations and matplotlib for visualizations. If you haven't installed these libraries, you can do so using the following commands:

pip install yfinance pandas numpy matplotlib

Now that we have the required libraries, let’s proceed with downloading financial data using the yfinance library.

Downloading Financial Data

We will download financial data for a selection of real assets using the yfinance…