BUS338 Business Forecasting
Credits (ECTS):10
Course responsible:Daumantas Bloznelis
Campus / Online:Taught campus Ås
Teaching language:Engelsk
Limits of class size:70
Course frequency:Annually
Nominal workload:250 hours.
Teaching and exam period:This course starts in Autumn parallel. This course has teaching/evaluation in Autumn parallel.
About this course
This course is a broad introduction into forecasting. It employs statistical models, decision rules and programming skills to address selected business problems. The course discusses types of forecasting problems and forecastability as well as types of forecasts (point, interval, density) and their optimality under different loss functions. It introduces a number of forecasting methods ranging from simple exponential smoothing to advanced automated algorithms and presents best practices such as forecast averaging. Forecast evaluation and comparison coupled with identification of superior forecasts is also covered.
Our purpose is to acquire practical forecasting skills based on a sound understanding of statistical and decision-theoretic principles and stylized facts of business data. Teaching combines lectures, practical exercise sessions and independent group work on mandatory assignments.
Learning outcome
Knowledge:
Students are familiar with
1. core ideas in forecasting
2. optimization criteria that underlie decision making
3. randomness and its manifestations, interpretations and use in forecasting
Skills:
Students can
1. identify relevant features and aspects of a forecasting problem
2. formulate the problem mathematically
3. anticipate the level of forecastability
4. apply a variety of forecasting techniques
5. evaluate forecast performance
6. compare alternative forecasts and select between them
7. improve forecasts based on historical forecast errors and losses
General Competence:
Students
1. can analyze and discuss real-world forecasting problems
2. can evaluate forecasting solutions and foresee potential failures
3. can use R or other forecasting software
4. appreciate randomness and the human proclivity for mistaking noise for signal
- Lectures, exercises, group work, independent work.
- Office hours by appointment.
STAT100 Statistics or equivalent
Basic knowledge of programing and data management such as BUS350 Introduction to Data Analytics or INF120 Programming and Data Processing or equivalent
- Statistics and econometrics on bachelor level (e.g. ECN201 or STAT200).
3,5 hour written exam counts for 100%.
B1: Calculator handed out, no other aids
School exam Grading: Letter grades Permitted aids: B1 Calculator handed out, no other aids- External examiner will control quality of the syllabus, questions for the final examination, and principles for the assessment of the examination answers.
Two mandatory group assignments. Both must be approved before the student can take the exam.
Compulsory activities are valid until and including the next time the course is offered.
- The subject will be taught the first time in the autumn of 2024.
- 2 lectures a week.
- None.
- The course is intended for students enrolled in master programmes at NMBU. It is also open for exchange students and other students with sufficient prior knowledge.