- CFA Exams
- CFA Level I Exam
- Topic 1. Quantitative Methods
- Learning Module 5. Time-Series Analysis
- Subject 2. Autoregressive (AR) Time-Series Models

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**CFA Practice Question**

Which one is true about an autoregressive model?

II. One benefit of using an autoregressive model for forecasting is that it is not necessary to predict the future values of the explanatory variables first.

III. A random walk is a special case of auto-regressive model.

I. It is a model in which you use the statistical properties of the past behavior of a variable (its derivatives with respect to time, in some sense) to predict its behavior in the future.

II. One benefit of using an autoregressive model for forecasting is that it is not necessary to predict the future values of the explanatory variables first.

III. A random walk is a special case of auto-regressive model.

A. I and II

B. II and III

C. I, II and III

**Explanation:**I. An autoregressive model is one in which the independent variable is a lagged value of the dependent variable.

II. If Y

_{t}is expressed as a function of an explanatory variable X, then it is necessary to know or forecast X

_{t+1}in order to forecast Y

_{t+1},but if Y

_{t}is expressed as a function of Y

_{t-1}, we need only know or forecast Y

_{t}in order to forecast Y

_{t+1}.

III. The random walk equation is a special case of an AR(1) model with b

_{0}= 0 and b

_{1}= 1.

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