Python for Finance Cookbook

Implementing the rolling three-factor model on a portfolio of assets

In this recipe, we learn how to estimate the three-factor model in a rolling fashion. What we mean by rolling is that we always consider an estimation window of a constant size (60 months, in this case) and roll it through the entire dataset, one period at a time. A potential reason for doing such an experiment is to test the stability of the results.

In contrast to the previous recipes, this time, we use portfolio returns instead of a single asset. To keep things simple, we assume that our allocation strategy is to have an equal share of the total portfolio's value in each of the following stocks: Amazon, Google, Apple, and Microsoft. For this experiment, we use stock prices ...