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23525-01 - Lecture: Computational Economics 3 CP

Semester spring semester 2019
Course frequency Every spring sem.
Lecturers Dietmar Maringer (dietmar.maringer@unibas.ch, Assessor)
Content Many fields in business and economics make heavy use of quantitative concepts and methods. This is particularly true for financial economics: areas such as risk management, portfolio optimization, pricing, etc., have numerous quantitative models on offer that provide valuable insights and support decision makers. Not surprisingly, "computational finance" has gained substantial importance, and computational methods are now often considered to be key for dealing with the relevant tasks. This is also true for many other areas in economics.

This course addresses such computational methods. By looking at relevant real-world problems (mainly from finance, but also other areas in business and economics), we will look at (numerical) optimization and simulation methods. The latter his its main focus on Monte Carlo simulation methods and covers sampling, path generation, modelling uncertainty and risk, evaluating simulations, etc. Methods covered in the numerical optimization part range from traditional deterministic search and optimization methods (e.g., gradient based methods, simplex-based methods) to innovative methods (e.g., heuristic optimization, evolutionary methods, methods from computational intelligence). To deepen the participants' understanding of these methods, their practical application and their up- and downsides, the course is very much hands-on, allowing for numerous own implementations and computer experiments. No prior programming experience is required; programming skills will be gathered in a "learning by doing" fashion.
Learning objectives Learning Goals:
Successful participants should be familiar with numerical methods, necessary to approach and solve quantitative problems in economics and business. Also, they will acquire programming skills to implement economic / management models and the necessary methods.
Bibliography there is no designated textbook, but to get a flavor of the topics or to deepen their knowledge, (prospective) participants might find the following books helpful:

Miranda, M. J. & Fackler, P. L. Applied Computational Economics and Finance The MIT Press, 2002

Brandimarte, P. Handbook in Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics Wiley, 2014

Brandimarte, P. Numerical Methods in Finance and Economics, Wiley-Interscience, 2006

Gilli, M.; Maringer, D. & Schumann, E. Numerical Methods and Optimization in Finance, Academic Press, 2011

Glasserman, P. Monte Carlo Methods in Financial Engineering, Springer, 2004

Kroese, D. P.; Taimre, T. & Botev, Z. I. Handbook of Monte Carlo Methods Wiley, 2011

Michalewicz, Z. & Fogel, D. B. How to Solve It: Modern Heuristics, Springer, 2005

Brabazon, A.; O'Neill, M. & McGarraghy, S. Natural Computing Algorithms, Springer, 2015

Jones, O.; Maillardet, R. & Robinson, A. Introduction to Scientific Programming and Simulation Using R, CRC Press, 2009

Langtangen, H. P. A Primer on Scientific Programming Using Python Springer, 2014

Additional literature to be announced during the course.
Comments Prior programming skills help, but are not required. Particpants with limited or no Matlab experience are encouraged to attend the "Matlab" part of the "Vorkurs: Arbeiten mit wissenschaftlicher Software" provided at the beginning of the term. For more details, please check the webpages of the Computational Economics and Finance unit.
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Admission requirements Prerequisites:
Completed Bachelor in Business and Economics
Course application Registration: Please enrol in MOnA. EUCOR-Students and students of other Swiss Universities have to enrol at the students administration office (studseksupport1@unibas.ch) within the official enrolment period. Enrolment = Registration for the exam!
Language of instruction English
Use of digital media No specific media used

 

Interval Weekday Time Room

No dates available. Please contact the lecturer.

Modules Module: Interdisciplinary and Transfer of Knowledge (Master's Studies: Actuarial Science)
Module: Non-Life Insurance (Master's Studies: Actuarial Science)
Module: Risk Analysis (Master's Studies: Actuarial Science)
Specialization Module: Areas of Specialization in International and/or Monetary Economics (Master's Studies: International and Monetary Economics)
Specialization Module: Quantitative Methods (Master's Studies: Business and Economics)
Assessment format end-of-semester examination
Assessment details active participation, assignments, and written final exam.
written exam: 05.04.19; 10:15-11:15. WWZ S14: A-Z.
Assessment registration/deregistration Registration: course registration
Repeat examination no repeat examination
Scale 1-6 0,1
Repeated registration as often as necessary
Responsible faculty Faculty of Business and Economics , studiendekanat-wwz@unibas.ch
Offered by Faculty of Business and Economics

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