Forecasting Techniques

Code 3.7.3260.8
Semester 8th
Flow O - Management and Decision Support Systems
Category Obligatory (main flow)
Credits 6
Class Hours - Lab Hours 4 - 0
Lecturers Vassilis Assimakopoulos, Vangelis Marinakis
Links Helios, Course's Website
Web Platform Class 1: Microsoft Teams


The course describes the latest forecasting techniques, both statistical and non-statistical ones, in order the students to be able to understand and implement a forecasting procedure. The main objects of the course are the statistical analysis and extrapolation of time series: Basic statistical concepts, Time series analysis, Time series characteristics, Decomposition, Forecasting methods, Forecasting performance evaluation and monitoring, Special events and treatment methods, Smoothing methods (moving averages), Exponential smoothing methods (Single, Holt, Winters, Damped), Regression models (simple and multiple regression), ARIMA models, Theta (θ) method, Long term predictions, Judgmental forecasting, Forecasting competitions, Hierarchical forecasting (bottom-up/top-down). The course focuses also on the use of IT systems to familiarize students with the exploitation of forecasting techniques in practice, the comparative evaluation of alternative techniques and their implementation in businesses. The ultimate goal is students to acquire both theoretical and practical knowledge in business forecasting techniques. In this respect, the course includes both theoretical lessons and practical training through electronic online games and interactive quizzes.