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6. Consider the MA (1) process yt = 2.3 0.95et-1 + et a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write your answer as a function of y₁, Y2, Y3, ... YT e₁,e₂, and or ... eT b. Now suppose that et = 0.4 and ET-1 = -1.2. Re-answer part (a).

6. Consider the MA (1) process yt = 2.3 0.95et-1 + et a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write your answer as a function of y₁, Y2, Y3, ... YT e₁,e₂, and or ... eT b. Now suppose that et = 0.4 and ET-1 = -1.2. Re-answer part (a).

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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6. Consider the MA(1) process yt 2.3 — 0.95ер-1+ et a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write аnd your answer as a function of y1, y2, Y3, ... YT e1, e2, or ... eT b. Now suppose that er = 0.4 and er-1 = -1.2. Re-answer part (a). 7. The FRED codes for housing starts in the Midwest are HOUSTMW and HOUSTMWNSA (seasonally adjusted and not seasonally adjusted, respectively). For the South they are HOUSTS and HOUSTSNSA. Graph the autocorrelation functions for these four series. Comment and discuss. 8. Use the real GDP growth data from FRED code A191RL1Q225SBEA. Run an AR(1) regression on these data (with constant). Save the residuals from that regression (predict e, residuals). Graph the time series of the residuals. Graph the autocorrelation function of the residuals. Comment and discuss.
Transcribed Image Text:6. Consider the MA(1) process yt 2.3 — 0.95ер-1+ et a. What is the optimal forecast for time periods T+1, T+2, and T+3. Write аnd your answer as a function of y1, y2, Y3, ... YT e1, e2, or ... eT b. Now suppose that er = 0.4 and er-1 = -1.2. Re-answer part (a). 7. The FRED codes for housing starts in the Midwest are HOUSTMW and HOUSTMWNSA (seasonally adjusted and not seasonally adjusted, respectively). For the South they are HOUSTS and HOUSTSNSA. Graph the autocorrelation functions for these four series. Comment and discuss. 8. Use the real GDP growth data from FRED code A191RL1Q225SBEA. Run an AR(1) regression on these data (with constant). Save the residuals from that regression (predict e, residuals). Graph the time series of the residuals. Graph the autocorrelation function of the residuals. Comment and discuss.
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