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| 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 | Wochentag | Zeit | Raum |
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Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| 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. online exam: April 28, 14:00-15:00 (details will be communicated via email). |
| An-/Abmeldung zur Leistungsüberprüfung | Anmeldung: Belegen |
| 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 |