Conditional Heteroscedasticity
Pick a stock from yahoo finance or equivalent and do the following:
1. Import five years of daily data into SAS.
2. Generate returns
3. Estimate an appropriate model and save the residuals
4. Generate the squared residuals
5. Examine the ACF, PACF, and IACF of the squared residuals to see if a GARCH or ARCH model is needed
6. If it is needed, estimate a GARCH or ARCH model for the returns using Proc autoreg
7. Save the conditional variance
8. Plot the conditional variance
Turn in the following in a short report:
1. A plot of the returns
2. A plot of the ACF and PACF of the squared residuals from the initial AR model.
3. A statement about the need or lack of need for an ARCH, GARCH model
4. If ARCH or GARCH is needed, a plot of the conditional variance.