Question

Suppose ?? is generated by an ARMA(2,2) process, such that ?? = ??−1 − 0.25??−2 +...

Suppose ?? is generated by an ARMA(2,2) process, such that ?? = ??−1 − 0.25??−2 + ?? − ??−1 + 0.25??−2; ??~??(0, ? 2 )

(a) Suppose we write the ARMA(2,2) process ϕ(L)?? = ?(?)?? how to define ϕ(L) and ?(?)?

(b) Is this ARMA(2,2) process invertible and stationary

Homework Answers

Answer #1

Part (a)

this form of representing ARMA process is called lag operator notation

Part (b)

for ARMA (2,2) process to be stationary roots of the AR characteristic polynomial should exceed 1 in absolute value

for ARMA (2,2) process to be invertible roots of the MA characteristic polynomial should exceed 1 in absolute value

Since roots of AR characteristic polynomial and MA characteristic polynomial is greater than 1

Therefore, above ARMA (2,2) process is both stationary and invertible

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
True or false? You do not have to provide explanations. (a) Any moving average (MA) process...
True or false? You do not have to provide explanations. (a) Any moving average (MA) process is covariance stationary. (b) Any autoregressive (AR) process is invertible. (c) The autocorrelation function of an MA process decays gradually while the partial autocorrelation function exhibits a sharp cut-off. (d) Suppose yt is a general linear process. The optimal 2-step-ahead prediction error follows MA(2) process. (e) Any autoregressive moving average (ARMA) process is invertible because any moving average (MA) process is invertible. (f) The...
We know that when ?~?(?,?), ?−? ? ~?(0,1). (a) Suppose that ?~?(2,2). We would like to...
We know that when ?~?(?,?), ?−? ? ~?(0,1). (a) Suppose that ?~?(2,2). We would like to calculate ?(−2 < ? < 4). We know that ?(−2 < ? < 4) = ?(? < ? < ?) for a standard random variable ?, i.e., ?~?(0,1). What are the values of ? and ?? (b) Suppose that ?~?(2,1). We would like to calculate ?(−2 < ?). We know that ?(−2 < ?) = ?(? < ?) for a standard random variable ?,...
Suppose {et : t = −1, 0, 1, . . .} is a sequence of iid...
Suppose {et : t = −1, 0, 1, . . .} is a sequence of iid random variables with mean zero and variance 1. Define a stochastic process by xt = et − 0.5et−1 + 0.5et−2, t = 1, 2, . . . a. Is xt stationary? Show your work. 2. Is xt weakly dependent? Again, show your work.
1. General features of economic time series: trends, cycles, seasonality. 2. Simple linear regression model and...
1. General features of economic time series: trends, cycles, seasonality. 2. Simple linear regression model and multiple regression model: dependent variable, regressor, error term; fitted value, residuals; interpretation. 3. Population VS sample: a sample is a subset of a population. 4. Estimator VS estimate. 5. For what kind of models can we use OLS? 6. R-squared VS Adjusted R-squared. 7. Model selection criteria: R-squared/Adjusted R-squared; residual variance; AIC, BIC. 8. Hypothesis testing: p-value, confidence interval (CI), (null hypothesis , significance...
Let f have a power series representation, S. Suppose that f(0)=1, f’(0)=3, f’’(0)=2 and f’’’(0)=5. a....
Let f have a power series representation, S. Suppose that f(0)=1, f’(0)=3, f’’(0)=2 and f’’’(0)=5. a. If the above is the only information we have, to what degree of accuracy can we estimate f(1)? b. If, in addition to the above information, we know that S converges on the interval [-2,2] and that |f’’’’(x)|< 11 on that interval, then to what degree of accuracy can we estimate f(1)?
Given a random variable X has the following pmf: X -1 0 1 P[X] 0.25 0.5...
Given a random variable X has the following pmf: X -1 0 1 P[X] 0.25 0.5 0.25 Define Y = X2 & W= Y+2. Which one of the following statements is not true? A) V[Y] = 0.25. B) E[XY] = 0. C) E[X3] = 0. D) E[X+2] = 2. E) E[Y+2] = 2.5. F) E[W+2] = 4.5. G) V[X+2] = 0.5. H) V[W+2] = 0.25. I) P[W=1] = 0.5 J) X and W are not independent.
Define g(x) = f(x) + tan-1 (2x) on [−1, √3/2 ]. Suppose that both f'' and...
Define g(x) = f(x) + tan-1 (2x) on [−1, √3/2 ]. Suppose that both f'' and g'' are continuous for all x-values on [−1, √3/2 ]. Suppose that the only local extrema that f has on the interval [−1, √3/2 ] is a local minimum at x = 1/2 . (a) Determine the open intervals of increasing and decreasing for g on the interval [1/2 , √3/2] . (b) Suppose f(1/2) = 0 and f(√3/2) = 2. Find the absolute...
Suppose that X(n) is a discrete-time process with mean m(n)=3 and autocovariance function R(n1, n2) =...
Suppose that X(n) is a discrete-time process with mean m(n)=3 and autocovariance function R(n1, n2) = 4e−0.2|n2−n1|. Here n = 0, ±1, ±2, .... Determine the mean, the variance and the covariance of the random variables X(5) and X(8). Is the process stationary? Does the process have mean-ergodicity?
Suppose we want to minimize the cost function C = (x−2)^2 + (y −3)^2 subject to...
Suppose we want to minimize the cost function C = (x−2)^2 + (y −3)^2 subject to the constraints 2x + 3y ≥ 10 and −3x − 2y ≥ −10. Also, x and y must be greater than or equal to 0. 1. Write the Lagrangian function L. 2. Write the Kuhn-Tucker conditions for this problem. Remember, there should be a set of conditions for each variable. 3. Use trial and error to solve this problem. Even if you cannot complete...
Let X = [0, 1) and Y = (0, 2). a. Define a 1-1 function from...
Let X = [0, 1) and Y = (0, 2). a. Define a 1-1 function from X to Y that is NOT onto Y . Prove that it is not onto Y . b. Define a 1-1 function from Y to X that is NOT onto X. Prove that it is not onto X. c. How can we use this to prove that [0, 1) ∼ (0, 2)?