Question

A) What are the building blocks of a univariate time series model?

B) Give one of the ‘ad hoc’ time series forecasting techniques.  

C) How would you identify the correct specification for an ARIMA model within the BoxJenkins approach?

Answer 1

A. The building blocks of a univariate Time Series model are AR (autoregressive), MA (moving average) and ARMA (autoregressive moving average). We should make the data stationary.

B. ARMA Auto-Regressive Moving Average Technique is an ad-hoc time series forecasting technique.

C. An effective procedure for building

empirical time series models is

the Box-Jenkins approach, which consists of three stages:

(1) Model specification or identification (of ARIMA order),

(2) Estimation

(3) Diagnostics testing.

• Box-Jenkins Approach

1) Make sure data is stationary –check a time plot. If not, differentiate.

2) Using ACF & PACF, guess small values for p & q.

3) Estimate order p, q.

4) Run diagnostic tests on residuals.