Evaluating equally-weighted portfolio's performance
We begin with inspecting the most basic asset allocation strategy: the equally-weighted (1/n) portfolio. The idea is to assign equal weights to all the considered assets, thus diversifying the portfolio. As simple as that might sound, DeMiguel, Garlappi, and Uppal (2007) show that it can be difficult to beat the performance of the 1/n portfolio by using more advanced asset allocation strategies.
The goal of the recipe is to show how to create a 1/n portfolio of the FAANG companies (Facebook/Meta, Amazon, Apple, Netflix, and Google/Alphabet), calculate its returns, and then use the quantstats library to quickly obtain all relevant portfolio evaluation metrics in the form of a tear sheet. Historically, a tear sheet is a concise, usually one-page, document, summarizing important information about public companies.
How to do it...
Execute the following steps to create and evaluate the 1/n portfolio.
- 1. Import the libraries:
import...
