Table of Contents
CFA Level 2 – Quantitative Analysis, Session 3 – Reading 13 – LOS l
(Practice Questions, Sample Questions)
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.
1. 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). (Explanation: 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.)
C) Correlation(et, et-5).
2. 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. (Explanation: Forecasting is no different in the case of seasonal component in the time-series model than any other forecasting.)
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.
3. 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. (Explanation: This model is a seasonal AR with first differencing.)
