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5) (20 marks) Consider the stationary GARCH(1.1) model X στ = Εισι Ει N(0.1) 0.1+0.38?…., +0.150,7-\. a) (5 marks) Express X as an ARMA model. b) (6 marks) Find E(X) and E(0). c) (5 marks) Find Cov(X, σ). d) (4 marks) Given a data set {X1, X2, X3, X4} = {1.1.3.1,-2.2.1.4}. find the log-likelihood for the GARCH model.

5) (20 marks) Consider the stationary GARCH(1.1) model X στ = Εισι Ει N(0.1) 0.1+0.38?…., +0.150,7-\. a) (5 marks) Express X as an ARMA model. b) (6 marks) Find E(X) and E(0). c) (5 marks) Find Cov(X, σ). d) (4 marks) Given a data set {X1, X2, X3, X4} = {1.1.3.1,-2.2.1.4}. find the log-likelihood for the GARCH model.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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5) (20 marks) Consider the stationary GARCH(1.1) model X στ = Εισι Ει N(0.1) 0.1+0.38?…., +0.150,7-\. a) (5 marks) Express X as an ARMA model. b) (6 marks) Find E(X) and E(0). c) (5 marks) Find Cov(X, σ). d) (4 marks) Given a data set {X1, X2, X3, X4} = {1.1.3.1,-2.2.1.4}. find the log-likelihood for the GARCH model.
Transcribed Image Text:5) (20 marks) Consider the stationary GARCH(1.1) model X στ = Εισι Ει N(0.1) 0.1+0.38?…., +0.150,7-\. a) (5 marks) Express X as an ARMA model. b) (6 marks) Find E(X) and E(0). c) (5 marks) Find Cov(X, σ). d) (4 marks) Given a data set {X1, X2, X3, X4} = {1.1.3.1,-2.2.1.4}. find the log-likelihood for the GARCH model.
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