n Solution:
A coefficient would be significant if it lies outside (-0.196,+0.196) at the 5% level, so only the first autocorrelation coefficient is significant. Q=5.09 and Q*=5.26 Compared with a tabulated χ2(5)=11.1 at the 5% level, so the 5 coefficients are jointly insignificant.
Learning Outcomes
n In this chapter, you will learn how to n ● Explain the defining characteristics of various types n n n n
of stochastic processes ● Identify the appropriate time series model for a given data series ● Produce forecasts for ARMA and exponential smoothing models ● Evaluate the accuracy of predictions using various metrics ● Estimate time series models and produce forecasts from them in EViews
their past values. Some Notation and Concepts n A Strictly Stationary Process A strictly stationary process is one where P{yt1 ≤ b1,..., ytn ≤ bn } = P{yt1 + m ≤ b1,..., ytn + m ≤ bn} i.e. the probability measure for the sequence {yt} is the same as that for {yt+m} ∀ m. n A Weakly Stationary Process If a series satisfies the next three equations, it is said to be weakly or covariance stationary 1. E(yt) = µ , t = 1,2,...,∞ 2. E ( yt − µ )( yt − µ ) = σ 2 < ∞ 3. E ( y t − µ )( y t − µ ) = γ t − t ∀ t1 , t2 1 2 2 1
