Seeing is believing!
Before you order, simply sign up for a free user account and in seconds you'll be experiencing the best in CFA exam preparation.
Basic Question 2 of 11
For a time series to be covariance stationary it means:
II. Its variance does not change over time.
III. The covariance of the time series with itself does not change over time.
IV. There is no auto-correlations of the error term.
I. Its mean does not change over time.
II. Its variance does not change over time.
III. The covariance of the time series with itself does not change over time.
IV. There is no auto-correlations of the error term.
User Contributed Comments 0
You need to log in first to add your comment.
Your review questions and global ranking system were so helpful.
Lina
Learning Outcome Statements
describe the structure of an autoregressive (AR) model of order p and calculate one- and two-period-ahead forecasts given the estimated coefficients;
explain how autocorrelations of the residuals can be used to test whether the autoregressive model fits the time series;
explain mean reversion and calculate a mean-reverting level;
contrast in-sample and out-of-sample forecasts and compare the forecasting accuracy of different time-series models based on the root mean squared error criterion;
CFA® 2025 Level II Curriculum, Volume 1, Module 5.