You obtain the following estimates for an AR(2) model of some returns data yt = 0.803yt−1 + 0.682yt−2 + ut
Where ut is a white noise error process. By examining the characteristic equation, check the estimated model for stationarity.

AR(2) model is not stationary

Explanation:

Given model  :  Yt = 0.803yt-1   +  0.682yt-2 +  ut  ---- ( 1 )

ut = noise error process

Aim : Check estimated model for stationarity

step 1 : represent the estimated polynomial of the model ( where: ut ∪ N(o,б^2 ) rewrite equation 1

Yt - 0.803yt-1  - 0.682yt-2  = ut  ------- ( 2 )

hence the polynomial can be represented as :

( 1 - 0.803B - 0.682B^2 )Yt = ut

Characteristic of the obtained polynomial can be represented as ;

1 - 0.803λ - 0.682λ^2 - 1 = 0

attached below is the remaining part of the solution

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