(solution) Simulate a GARCH (1, 1) process with α = 0.1 and β = 0.8 and of length 500. Plot the time…

(solution) Simulate a GARCH (1, 1) process with α = 0.1 and β = 0.8 and of length 500. Plot the time…

Simulate a GARCH (1, 1) process with α = 0.1 and β = 0.8 and of length 500. Plot the time series and inspect its sample ACF, PACF, and EACF. Are the data consistent with the assumption of white noise? (a) Square the data and identify a GARCH model for the raw data based on the sample ACF, PACF, and EACF of the squared data. (b) Identify a GARCH model for the raw data based on the sample ACF, PACF and EACF of the absolute data. Discuss and reconcile any discrepancy between the tentative model identified with the squared data and that with the absolute data. (c) Perform the McLeod-Li test on your simulated series. What do you conclude? (d) Repeat the exercise but now using only the first 200 simulated data. Discuss your findings.