This subject aims to introduce techniques for analysing and forecasting time series, and to apply these techniques to a wide variety of time series. It deals with non-seasonal and seasonal time series model identification, estimation, diagnostic examination and forecasting. Topics covered include: time series regression; exponential smoothing; spectral analysis; and Box-Jenkins ARIMA models including stationarity/invertibility criteria, transfer functions, intervention analysis and ARCH/GARCH models.
Assessment: Two assignments worth 20 per cent each; final examination worth 60 per cent.
Spring semester, City campus