STA 4853/5856 HW 3 Partial Solutions · Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of...

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Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of 2 Time Series STA 4953/5856 π(z ) from Slide 10 on Feb 6 (2 points) Write π(z )= 1-.9z 1+.5z as an infinite series. Using the geometric series for the denominator, we have π(z ) = (1 - .9z ) X j =0 (-.5) j z j = (1 - .9z )(1 - .5z + .5 2 z 2 - .5 3 z 3 + ··· ) =1 - (.5+ .9)z +(.5(.9) + .5 2 )z 2 - (.5 2 (.9) + .5 3 )+ ··· =1 - (.5+ .9)z + .5(.9+ .5) - .5 2 (.9+ .5) + ··· =1 - 1.4 X j =1 (-.5) j -1 z j #3.14(a) (4 points) Verify if the following models are stationary, invertible, or both. (i) (1 - B)Z t = (1 - 1.5B)a t (ii) (1 - .8B)Z t = (1 - .5B)a t (iv) (1 - .6B)Z t = (1 - 1.2B + .2B 2 )a t For stationary (resp. invertibility) the roots of φ(B) (resp. θ(B)) should lie outside the unit disk. (i) φ(B)=1 - B has a unit root (since φ(1) = 0) and therefore the process is not stationary. The root of θ(B)=1 - 1.5B is 2/3 which is smaller than one in absolute value, and therefore this process is not invertible either. (ii) This part is not graded. (iv) The polynomial φ(B)=1 - .6B has root 1/.6=5/3 which is bigger than one in absolute value, and therefore this process is stationary. The θ(B) polynomial factors as θ(B)= 1 5 (B - 1)(B - 5) and because one of the roots is 1, the process is not invertible. #3.14(b,c) for (i) Consider the ARMA(1,1) process (1 - B)Z t = (1 - 1.5B)a t (a) Express the model in an MA representation if it exists. (b) Express the model in an AR representation if it exists. This process is neither stationary nor invertible, so neither representation exists. Exponential Smoothing (2 points) Show that the process Z t = μ + α X j<t a j + a t is ARIMA(0,1,1).

Transcript of STA 4853/5856 HW 3 Partial Solutions · Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of...

Page 1: STA 4853/5856 HW 3 Partial Solutions · Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of 2 Time Series STA 4953/5856 ˇ(z) from Slide 10 on Feb 6 (2 points) Write ˇ(z)

Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of 2Time Series STA 4953/5856

◦ π(z) from Slide 10 on Feb 6 (2 points) Write π(z) = 1−.9z1+.5z

as an infinite series.

• Using the geometric series for the denominator, we have

π(z) = (1− .9z)∞∑

j=0

(−.5)jzj

= (1− .9z)(1− .5z + .52z2 − .53z3 + · · · )= 1− (.5 + .9)z + (.5(.9) + .52)z2 − (.52(.9) + .53) + · · ·= 1− (.5 + .9)z + .5(.9 + .5)− .52(.9 + .5) + · · ·

= 1− 1.4∞∑

j=1

(−.5)j−1zj

◦ #3.14(a) (4 points) Verify if the following models are stationary, invertible, or both.

(i) (1−B)Zt = (1− 1.5B)at

(ii) (1− .8B)Zt = (1− .5B)at

(iv) (1− .6B)Zt = (1− 1.2B + .2B2)at

• For stationary (resp. invertibility) the roots of φ(B) (resp. θ(B)) should lie outside the unit disk.

(i) φ(B) = 1 − B has a unit root (since φ(1) = 0) and therefore the process is not stationary.The root of θ(B) = 1 − 1.5B is 2/3 which is smaller than one in absolute value, and thereforethis process is not invertible either.

(ii) This part is not graded.

(iv) The polynomial φ(B) = 1− .6B has root 1/.6 = 5/3 which is bigger than one in absolute value,and therefore this process is stationary. The θ(B) polynomial factors as

θ(B) =1

5(B − 1)(B − 5)

and because one of the roots is 1, the process is not invertible.

◦ #3.14(b,c) for (i) Consider the ARMA(1,1) process

(1−B)Zt = (1− 1.5B)at

(a) Express the model in an MA representation if it exists.

(b) Express the model in an AR representation if it exists.

• This process is neither stationary nor invertible, so neither representation exists.

◦ Exponential Smoothing (2 points) Show that the process

Zt = µ+ α∑j<t

aj + at

is ARIMA(0,1,1).

Page 2: STA 4853/5856 HW 3 Partial Solutions · Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 1 of 2 Time Series STA 4953/5856 ˇ(z) from Slide 10 on Feb 6 (2 points) Write ˇ(z)

Spring 2008 STA 4853/5856 HW 3 Partial Solutions Page: 2 of 2Time Series STA 4953/5856

• Computing the difference of Zt gives

∇Zt = Zt − Zt−1

= µ+ α∑j<t

+at −

(µ+ α

∑j<t−1

aj + at

)= αat−1 + at − at−1

= at + (α− 1)at−1

which is a MA(1) process. Therefore Zt is ARIMA(0,1,1).

◦ #4.5 (2 points) Consider the simple white noise process, Zt = at. Discuss the consequences by exam-ining the ACF, PACF, and AR representation of the differenced series, Wt = Zt − Zt−1.

• Only the ACF of Wt is graded. The differenced series Zt = at − at−1 is MA(1) and therefore has anACF given by

ρk =

{−12, k = 1

0, k > 0

(with the usual ρ0 = 1 and ρ−k = ρk).