Python for Finance Cookbook

How it works...

In Step 2, we defined the parameters (the ticker of the considered stock and timeframes) for later use.

In Step 3, we downloaded the necessary datasets using pandas_datareader, which provides us with a convenient way of downloading the risk-factors-related data without manually downloading the CSV files. For more information on this process, please refer to the There's more section in the Implementing the Fama-French three-factor model in Python recipe. One thing to note here is that we applied the format method to the index, as we had to remove PeriodIndex in order to join multiple datasets later.

In Steps 4 and 5, we downloaded Amazon's stock prices and calculated the monthly returns using the previously explained methodology. ...