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Reading 13: Time-Series Analysis-LOS l 习题精选

Session 3: Quantitative Methods for Valuation
Reading 13: Time-Series Analysis

LOS l: Discuss how to test and correct for seasonality in a time-series model, and calculate and interpret a forecasted value using an AR model with a seasonal lag.

 

 

Barry Phillips, CFA, is analyzing quarterly data. He has estimated an AR(1) relationship (xt = b0 + b1 × xt-1 + et) and wants to test for seasonality. To do this he would want to see if which of the following statistics is significantly different from zero?

A)
Correlation(et, et-1).
B)
Correlation(et, et-4).
C)
Correlation(et, et-5).


 

Although seasonality can make the other correlations significant, the focus should be on correlation(et, et-4) because the 4th lag is the value that corresponds to the same season as the predicted variable in the analysis of quarterly data.

Which of the following statements regarding seasonality is least accurate?

A)
Not correcting for seasonality when, in fact, seasonality exists in the time series results in a violation of an assumption of linear regression.
B)
The presence of seasonality makes it impossible to forecast using a time-series model.
C)
A time series that is first differenced can be adjusted for seasonality by incorporating the first-differenced value for the previous year's corresponding period.


Forecasting is no different in the case of seasonal component in the time-series model than any other forecasting.

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Which of the following is a seasonally adjusted model?

A)
Salest = b0 + b1 Sales t-1 + b2 Sales t-2 + εt.
B)
Salest = b1 Sales t-1+ εt.
C)
(Salest - Sales t-1)= b0 + b1 (Sales t-1 - Sales t-2) + b2 (Sales t-4 - Sales t-5) + εt.


This model is a seasonal AR with first differencing.

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