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This is the third part of the series on volatility modelling. For other parts of the series follow the tag volatility.

In this exercise set we will use GARCH models to forecast volatility.

Exercise 1
Load the rugarch and the FinTS packages. Next, load the m.ibmspln dataset from the FinTS package. This dataset contains monthly excess returns of the S&P500 index from Jan-1926 to Dec-1999 (Ruey Tsay (2005) Analysis of Financial Time Series, 2nd ed. ,Wiley, chapter 3).
Also, load the forecast package which we will use for auto-correlation graphs.

Exercise 2
Excess S&P500 returns are defined as a regular zoo variable. Convert this to a time series variable with correct dates.

Exercise 3
Plot the excess S&P500 returns along with its ACF and PACF graphs and comment on the apparent correlation.

Exercise 4
Plot the squared excess S&P500 returns along with its ACF and PACF graphs and comment on the apparent correlation.