Q1. An analyst wants to model quarterly sales data using an autoregressive model. She has found that an AR(1) model with a seasonal lag has significant slope coefficients. She also finds that when the second and third lags are added to the model, all slope coefficients are significant too. Based on this, the best model to use would most likely be an: A) AR(1). B) AR(4). C) AR(2).
Q2. The model xt = b0 + b1 xt-1 + b2 xt-2 + b3 xt-3 + b4 xt-4 + εt is: A) an autoregressive conditional heteroskedastic model, ARCH. B) an autoregressive model, AR(4). C) a moving average model, MA(4).
Q3. The model xt = b0 + b1 xt − 1 + b2 xt − 2 + εt is: A) an autoregressive conditional heteroskedastic model, ARCH. B) an autoregressive model, AR(2). C) a moving average model, MA(2).
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发表于 2009-1-10 16:04
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