Computer-based Portfolio Optimization (R-Module)
Exam number: 6731
Semester: from 2nd semester
Duration of the module: One semester
Form of the module (i.e. obligatory, elective etc.): Elective
Frequency of module offer: Only winter semester 2015/2016
Prerequisites: Simultaneous or previous participation in the track modules “Operations Research”, “Management Science” or “Decision Support under Uncertainty”, good knowledge and deep interest in mathematical modeling and quantitative methods. Maximum 15 participants.
Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.
Person responsible for module: Prof. Dr. Sven Husmann, Prof. Dr. Achim Koberstein
Name of the professor: Prof. Dr. Sven Husmann, Prof. Dr. Achim Koberstein
Language of teaching: English
ECTS-Credits (based on the workload): 6
Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 60 h; self-study: 120 h
Contact hours (per week in semester): 4
Methods and duration of examination:
Successful preparation of a seminar paper of 10-15 pages including a small implementation project, an intermediate presentation in the middle and a final presentation at the end of the 2nd block (20-30 min. each)
Emphasis of the grade for the final grade: Please check regulations of the study programme
Aim of the module (expected learning outcomes and competencies to be acquired):
The participants will learn how to deploy model-based optimization approaches in the field of financial portfolio management.
Contents of the module:
Recently, great progress has been made in taking into account uncertain data explicitly in model-based decision support systems to produce more flexible and robust planning solutions. In this seminar, we want to discuss how these approaches can be applied to the field of financial portfolio optimization. In particular, we will investigate approaches from stochastic programming, robust optimization and dynamic programming. In addition, we want to familiarize ourselves with modelling languages for stochastic optimization and learn how to implement small illustrative applications in portfolio optimization ourselves.
Possible topics for the seminar paper are:
- A stochastic programming approach to portfolio optimization
- A robust optimization approach to portfolio optimization
- A chance-constraint programming approach to portfolio optimization
- A dynamic programming approach to portfolio optimization
The topics can be assigned to groups of up to three participants. The groups can prepare joint presentations and theses, if the responsibility of each member for some part of the presentation / thesis becomes clear.
Teaching and learning methods:
Literature (compulsory reading, recommended literature):
F. J. Fabozzi, P.N. Kolm, D.A. Pachamanova, S. M. Focardi. Robust Portfolio Optimization and Management. John Wiley & Sons 2007.
Additional topic specific material.
Registration in Moodle Viadrina required.