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| Semester | Frühjahrsemester 2022 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende | Enrico Schumann (enrico.schumann@unibas.ch, BeurteilerIn) |
| Inhalt | Computing is an indispensable part of finance: in pricing financial instruments such as derivatives, managing portfolios and running trading strategies, in risk management and data analysis -- computing is everywhere. This course introduces students to computational tools and methods used in finance. Emphasis will be on stochastic methods (aka Monte-Carlo methods) and optimization; we will also discuss the limitations and peculiarities imposed by computing technology and data quality. The course will be hands on, with the better part of lectures dealing with the implementation of techniques and models. All course work will use the R programming language. (Knowledge of R is not required. A brief introduction will be given in the first lecture, and self-study materials will be provided.) |
| Lernziele | Being able to implement financial models using R, and being able to solve quantitative problems in finance. |
| Literatur | There is no designated textbook; useful resources include: General M. Gilli, D. Maringer and E. Schumann (2019). Numerical Methods and Optimization in Finance. 2nd ed. Elsevier/Academic Press Numerical Methods M. T. Heath (2005). Scientific Computing: An Introductory Survey. 2nd. McGraw-Hill Option Pricing D. J. Higham (2004). An Introduction to Financial Option Valuation. Cambridge University Press Simulation L. Devroye (1986). Non-Uniform Random Variate Generation. Springer B. D. Ripley (1987). Stochastic Simulation. Wiley Optimization P. E. Gill, W. Murray and M. H. Wright (1986). Practical Optimization. Elsevier Z. Michalewicz and D. B. Fogel (2004). How to Solve it: Modern Heuristics. Springer Specific recommendations and additional literature to be announced during the course. |
| Bemerkungen | Throughout the course, we will use R to implement methods and concepts. Programming skills help, but are not required. The course will be taught "in class" with a simultaneous livestream. |
| Weblink | Weblink to ADAM |
| Teilnahmebedingungen | *) Solid knowledge of financial theory. *) Solid background in quantitative methods (in particular statistics/econometrics and empirical finance). *) Willingness to work with source code, i.e. willingness to program. |
| 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 |
|---|---|---|---|
| wöchentlich | Donnerstag | 18.15-20.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Bemerkungen | The course will be taught "in class" with a simultaneous livestream. |
| Module |
Modul: Field Electives in Economics and Public Policy (Masterstudium: Economics and Public Policy) Modul: Risiko-Analyse (Masterstudium: Actuarial Science) Modul: Specific Electives in Data Science and Computational Economics (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Monetary Economics and Financial Markets (Masterstudium: Wirtschaftswissenschaften) Vertiefungsmodul: Monetary Economics and Financial Markets (Masterstudium: Wirtschaftswissenschaften (Studienbeginn vor 01.08.2021)) Vertiefungsmodul: Quantitative Methods (Masterstudium: Wirtschaftswissenschaften (Studienbeginn vor 01.08.2021)) |
| Leistungsüberprüfung | Leistungsnachweis |
| Hinweise zur Leistungsüberprüfung | Combination of active participation, assignments and a (small) final project work. |
| An-/Abmeldung zur Leistungsüberprüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| 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 |