11. (a) Explain what stylised shapes would be expected for the autocorrelation and partial autocorrelation functions...

 

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11. (a) Explain what stylised shapes would be expected for the autocorrelation and partial autocorrelation functions for the following stochastic processes: white noise an AR(2) an MA(1) an ARMA (2,1). (b) Consider the following ARMA process. y = 0.21 +1.32yt-1 +0.58ut-1 + ut Determine whether the MA part of the process is invertible. (c) Produce one-, two-, three- and four-step-ahead forecasts for the process given in part (b) of the question. (d) Outline two criteria that are available for evaluating the forecasts produced in part (c) of the question, highlighting the differing characteristics of each. (e) What procedure might be used to estimate the parameters of an ARMA model? Explain, briefly, how such a procedure operates, and why OLS is not appropriate. 11. (a) Explain what stylised shapes would be expected for the autocorrelation and partial autocorrelation functions for the following stochastic processes: white noise an AR(2) an MA(1) an ARMA (2,1). (b) Consider the following ARMA process. y = 0.21 +1.32yt-1 +0.58ut-1 + ut Determine whether the MA part of the process is invertible. (c) Produce one-, two-, three- and four-step-ahead forecasts for the process given in part (b) of the question. (d) Outline two criteria that are available for evaluating the forecasts produced in part (c) of the question, highlighting the differing characteristics of each. (e) What procedure might be used to estimate the parameters of an ARMA model? Explain, briefly, how such a procedure operates, and why OLS is not appropriate.

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Stochastic Process Autocorrelation and Partial Autocorrelation Functions a Stylized Shapes of Autocorrelation ACF and Partial Autocorrelation PACF Functions White Noise ACF Flat line at lag 0 perfect ... View the full answer