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23525-01 - Vorlesung: Computational Economics 3 KP

Semester Frühjahrsemester 2020
Angebotsmuster Jedes Frühjahrsem.
Dozierende Dietmar Maringer (dietmar.maringer@unibas.ch, BeurteilerIn)
Inhalt 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.
Lernziele 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.
Literatur 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, 2nd edition 2019. (or 1st ed., 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.
Bemerkungen 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.
Weblink Weblink


Teilnahmebedingungen Prerequisites:
Completed Bachelor in Business and Economics
Anmeldung zur Lehrveranstaltung 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!
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz


Intervall wöchentlich
Datum 21.02.2020 – 03.04.2020
Zeit Freitag, 10.15-14.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Datum Zeit Raum
Freitag 21.02.2020 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 28.02.2020 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 06.03.2020 10.15-14.00 Uhr Fasnachtsferien
Freitag 13.03.2020 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 20.03.2020 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 27.03.2020 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 03.04.2020 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Module Modul: Interdisziplinäres und Wissenstransfer (Masterstudium: Actuarial Science)
Modul: Risiko-Analyse (Masterstudium: Actuarial Science)
Modul: Schadenversicherung (Masterstudium: Actuarial Science)
Spezialisierungsmodul: Areas of Specialization in International and/or Monetary Economics (Masterstudium: International and Monetary Economics)
Vertiefungsmodul: Quantitative Methods (Masterstudium: Wirtschaftswissenschaften)
Leistungsüberprüfung Semesterendprüfung
Hinweise zur Leistungsüberprüfung active participation, assignments, and written final exam.
written exam: tba
An-/Abmeldung zur Leistungsüberprüfung Belegen via MOnA innerhalb der Belegfrist
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,1
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch
Anbietende Organisationseinheit Wirtschaftswissenschaftliche Fakultät / WWZ