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  3. GARCH Models in Python

Exercise

Observe volatility clustering

Volatility clustering is frequently observed in financial market data, and it poses a challenge for time series modeling.

In this exercise, you will get familiar with the S&P 500 daily price dataset. You will calculate daily returns as the percentage price changes, plot the results and observe its behavior over time.

Historical S&P 500 daily price data has been preloaded in sp_price for you.

Instructions

100 XP
  • Calculate daily returns as percentage price changes and save it to the DataFrame sp_price in a new column called Return.
  • View the data by printing out the last 10 rows.
  • Plot the Return column and observe signs of volatility clustering.