Comparing Custom Portfolios to the Efficient Frontier: A Python Workflow

Introduction

When it comes to investing, one of the most important decisions you’ll make is how to allocate your assets across different securities. There are many approaches to portfolio construction, each with its own advantages and drawbacks. One common method is to create a custom portfolio, where you hand-pick a selection of securities based on your investment goals and risk tolerance. However, how do you know if your custom portfolio is performing as well as it could be? In this article, we’ll explore how to compare a custom portfolio to the efficient frontier using Python, and see how this analysis can help you optimize your investment strategy.

Understanding the Efficient Frontier

To start, we need to understand what the efficient frontier is and why it’s important. The efficient frontier is a graph that shows the optimal portfolios that maximize expected returns for a given level of risk. This means that any portfolio that falls on the efficient frontier represents the best possible risk-return tradeoff for that level of risk. By comparing a custom portfolio to the efficient frontier, we can see how well it’s performing relative to the optimal portfolios.

Building a Custom Portfolio

Before we can compare our custom portfolio to the efficient frontier, we need to build it. We can do this using Python and a financial data library like pandas and pypfopt. Here’s an example code snippet:

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