401-4657-00L Numerical Analysis of Stochastic Ordinary Differential Equations
| Semester | Herbstsemester 2019 |
| Dozierende | K. Kirchner |
| Periodizität | jährlich wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
| Kommentar | Alternative course title: "Computational Methods for Quantitative Finance: Monte Carlo and Sampling Methods" |
Lehrveranstaltungen
| Nummer | Titel | Umfang | Dozierende | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 401-4657-00 V | Numerical Analysis of Stochastic ODEs (Comp. Meth. Quant. Fin.: Monte Carlo and Sampling Methods) | 3 Std. |
| K. Kirchner | ||||||
| 401-4657-00 U | Numerical Analysis of Stochastic ODEs (Comp. Meth. Quant. Fin.: Monte Carlo and Sampling Methods) Gruppeneinteilung erfolgt über myStudies. | 1 Std. |
| K. Kirchner |
Katalogdaten
| Kurzbeschreibung | Course on numerical approximations of stochastic ordinary differential equations driven by Wiener processes. These equations have several applications, for example in financial option valuation. This course also contains an introduction to random number generation and Monte Carlo methods for random variables. |
| Lernziel | The aim of this course is to enable the students to carry out simulations and their mathematical convergence analysis for stochastic models originating from applications such as mathematical finance. For this the course teaches a decent knowledge of the different numerical methods, their underlying ideas, convergence properties and implementation issues. |
| Inhalt | Generation of random numbers Monte Carlo methods for the numerical integration of random variables Stochastic processes and Brownian motion Stochastic ordinary differential equations (SODEs) Numerical approximations of SODEs Applications to computational finance: Option valuation |
| Skript | There will be English, typed lecture notes for registered participants in the course. |
| Literatur | P. Glassermann: Monte Carlo Methods in Financial Engineering. Springer-Verlag, New York, 2004. P. E. Kloeden and E. Platen: Numerical Solution of Stochastic Differential Equations. Springer-Verlag, Berlin, 1992. |
| Voraussetzungen / Besonderes | Prerequisites: Mandatory: Probability and measure theory, basic numerical analysis and basics of MATLAB programming. a) mandatory courses: Elementary Probability, Probability Theory I. b) recommended courses: Stochastic Processes. Start of lectures: Wednesday, September 18, 2019. |
Leistungskontrolle
| Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
| ECTS Kreditpunkte | 6 KP |
| Prüfende | K. Kirchner |
| Form | Semesterendprüfung |
| Prüfungssprache | Englisch |
| Repetition | Die Leistungskontrolle wird nur am Semesterende nach der Lerneinheit angeboten. Die Repetition ist nur nach erneuter Belegung möglich. |
| Zusatzinformation zum Prüfungsmodus | Learning tasks: Meaningful solutions to 70% of the weekly homework assignments can count as bonus of up to +0.25 of final grade. End-of-Semester examination will be *closed book*, 2hr in class, and will involve theoretical as well as MATLAB programming problems. Examination will take place on ETH-workstations running MATLAB. Own computer will NOT be allowed for the examination. |
| Digitale Prüfung | Die Prüfung findet auf Geräten statt, die von der ETH Zürich zur Verfügung gestellt werden. |
Lernmaterialien
| Hauptlink | Course webpage |
| Es werden nur die öffentlichen Lernmaterialien aufgeführt. | |
Gruppen
| 401-4657-00 U | Numerical Analysis of Stochastic ODEs (Comp. Meth. Quant. Fin.: Monte Carlo and Sampling Methods) | ||||||
| Gruppen | G-01 |
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| G-02 |
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Einschränkungen
| Keine zusätzlichen Belegungseinschränkungen vorhanden. |
