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FORECASTING
Année du cours : 1 année(s)
Etablissement : IÉSEG School of Management
Langue : English
Formation(s) dans laquelle/lesquelles le cours apparait :
Période : S2
Algebra, inferential statistics, including (practical) knowledge of distributions, hypothesis testing, confidence intervals and the foundations of regression modeling
At the end of the course, the student should be able to:
– master the forecasting process, its data considerations and business implementation strategies
– apply statistical and econometric methods (modeling, estimation, interpretation, forecasting) to obtain forecasts in practical settings in business and economics
– understand the statistical background of the methods commonly used for forecasting in business and economics, and assess the appropriateness of the methods for specific problems
– build econometric forecasting models using real data into a dedicated econometric software package and interpret the output correctly, including the managerial consequences of the obtained results
– communicate about an econometric forecasting analysis, using appropriate scientific jargon
These competencies and/or skills contribute to the following learning objectives
– 3.A Breakdown complex organizational problems using the appropriate methodology
– 3.B Propose creative solutions within an organization
– 5.A. Predict how business and economic cycles could affect organizational strategy
– 5.B Construct expert knowledge from cutting-edge information
– 7.A Demonstrate an expertise on key concepts, techniques and trends in their professional field
– 7.B Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field
• Forecasting in business and economics
• Basic tools for forecasting
• Exponential smoothing
• Time series decomposition
• ARIMA models
• Forecasting in practice