Question: 1- a) Explain weak stationarity assuming Yt is a stochastic time series with these properties: Mean: Variance: Covariance: E(Y) = ? Var (Yt) =

1- a) Explain weak stationarity assuming Yt is a stochastic time series with these properties: Mean: Variance: Covariance: E(Y) = ? Var (Yt) = ? Yk= ? where Yk is the covariance (or autocovariance) at lag k. b) Suppose ut is a white noise error term with mean 0 and variance o2. Then the series Yt is said to be a random walk if Yt=Yt-1+ut Now we can write; Y=Y + U Y=Y+U = Yo+U+U Y3 = Y + U3 = Y + U+U+Uz 1 In general, if the process started at some time 0 with a value of Yo, we have Yt=Yo + ut Therefore, E(Yt) = E(Yo + Zut) = Yo . Why?

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