MSCI 523: Forecasting
(Phase II – Spring Term)
Tutors: Dr Sven F. Crone,
Objectives
You will learn about methods for predicting and forecasting to support managerial decision making about future actions. The module introduces time series and causal forecasting methods so that you will be able to prepare methodologically competent, understandable and concisely presented reports for clients. By the end of the module you should be able to model causal and time series models, assess their accuracy and robustness and apply them in a real world problem domain.
Core texts
Makridakis, S., Wheelwright, S.C. and Hyndman, R. (1998), Forecasting, Wiley (3rd ed.)
Holden, K., Peel, D.A. and Thompson, J.L. (1990) Economic forecasting: an introduction, Cambridge University Press.
The texts provide most relevant aspects of the methods taught. They will be supplemented by readings drawn from journal articles.
Topics
Time series methods: exponential smoothing, ARIMA methods, model selection & evaluation.
Causal methods: simple & multiple regression, dynamic regression, vector autoregression and artificial neural networks
Assessment
Group Coursework = 50%
Individual Coursework = 50%
Contact hours
A weekly two-hour class for the Spring term.
