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| STAT0803-1 | Forecasting : models and methods
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| Duration : | 24h Th |
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| Credits/ECTS : |
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| Holder(s) : | |
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| Language : | French language |
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| Course contents : | The financial world shows a deeper and deeper interest for quantitative forecasting methods. For the broker, having good approximations of future values of his equity portfolio is essential. A financial analyst should always anticipate as well as possible the behaviour of firms in which his clients are likely to invest. In this framework, this course develops different existing methods to treat those problems. Its content heavily depends on students' interests and their professional expectations. Among others, topics in the sequel can be involved.
- Forecasting of seasonal data
- Risk management
- Causality
- Autoregressive moving average models (ARMA models)
- Generalized autoregressive conditional heteroscedasticity models (GARCH models)
- Kalman filter
- ... |
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| Course objective : | P2. Application of basic statistical methods to stochastic processes
C3. Analysis, identification of common denominators in the different methods
C4. Critical analysis of existing methods with respect to practical situations |
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| Prerequisites : | A basic course of probability and statistics, for example,
STAT0067 Probabilités et inférence statistique and
one course of quantitative methods in management:
STAT0800-1 Applied statistics: models and methods,
MQGE0005-2 Quantitative Methods in Management (Partim Statistics)
or any other course of equivalent level. |
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| Organization : | Used methodology
A3. Analysis of a practical problem by each student (partially followed up by the teacher).
A4. Critical synthesis of the research, readings and/or practical applications achieved by the student. In principle, each student presents his readings and obtained results at the end of the semester. During his talk, he is invited to
1) clearly present a problem of interest in its financial context and the existing methods to solve it,
2) discuss those methods and justify the choice of one or several of them in specific cases.
Moreover, he is expected to attend to presentations of the other students and discuss the way they treat their own problem.
Overview of the course agenda
The course is taught during six weeks. The first three weeks, the teacher presents the different problems of interest with the necessary corresponding theoretical basic knowledge. Then, students choose a problem and begin a personal bibliographic research. During the next three weeks, the students and the teacher meet to evaluate the progress of the work and define the remaining steps to achieve. Finally, the students write a report and prepare an oral presentation of their problem for the evaluations period that follows the course.
Decomposition of the student workload
A1 Ex-cathedra lectures 12h
A3 Personal analysis of the problem 55h
A3 Meetings with the teacher 4h
A4 Report 20h
A4 Presentation 5h |
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| Written notes : | Introduction syllabus
Advised readings:
1. Brockwell, P. J., & Davis, R. A. (1996). Introduction to Time Series and
Forecasting. New York : Springer.
2. Franses, P. H. (1998). Time series models for business and economic forecasting. Cambridge University Press.
3. Mills, T. C. (1999). The Econometric Modelling of Financial Time Series (Second ed.). Cambridge University Press.
4. Advised readings (according to each student) |
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| Assessment : | Evaluation tools, evaluation criterions and weighting
E4. Final report (40% of the final note)
The evaluation is based on the clarity, the ability to synthesize and the critical analysis of the students.
E4. Oral presentation (40% of the final note)
1. Quality of the presentation: scientific methodology (10%), slides content (10%) and quality of the explanations (10%).
2. Defence of the work: answers to the questions of the teacher and the other students (10%).
E4. Attending and discussing the works of the other students (20%)
Evaluations agenda
The final report has to be sent to the teacher before the evaluations period that follows the course. The oral presentation is held during this evaluations period. |
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| Contacts : | Cédric HEUCHENNE, HEC-ULg Management School of the University of Liège, B31, local 2.53, email: C.Heuchenne@ulg.ac.be |
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