Josef Teichmann: Catalogue data in Autumn Semester 2018

Name	Prof. Dr. Josef Teichmann
Field	Financial Mathematics
Address	Professur für Finanzmathematik ETH Zürich, HG G 54.2 Rämistrasse 101 8092 Zürich SWITZERLAND
Telephone	+41 79 584 55 40
E-mail	josef.teichmann@math.ethz.ch
URL	http://www.math.ethz.ch/~jteichma
Department	Mathematics
Relationship	Full Professor

Number	Title	ECTS	Hours	Lecturers
401-3910-68L	Topics in Mathematical Finance and Machine Learning Number of participants limited to 20.	4 credits	2S	J. Teichmann
Abstract
Learning objective
401-4611-68L	Regularity Structures	6 credits	3V	J. Teichmann
Abstract	We develop the main tools of Martin Hairer's theory of regularity structures to solve singular stochastic partial differential equations in a pathwise way or addtionally by re-normalization techniques.
Learning objective
401-5820-00L	Seminar in Computational Finance for CSE	4 credits	2S	J. Teichmann
Abstract
Learning objective
Content	We aim to comprehend recent and exciting research on the nature of stochastic volatility: an extensive econometric research [4] lead to new in- sights on stochastic volatility, in particular that very rough fractional pro- cesses of Hurst index about 0.1 actually provide very attractive models. Also from the point of view of pricing [1] and microfoundations [2] these models are very convincing. More precisely each student is expected to work on one specified task consisting of a theoretical part and an implementation with financial data, whose results should be presented in a 45 minutes presentation.
Literature	[1] C. Bayer, P. Friz, and J. Gatheral. Pricing under rough volatility. Quantitative Finance , 16(6):887-904, 2016. [2] F. M. Euch, Omar El and M. Rosenbaum. The microstructural founda- tions of leverage effect and rough volatility. arXiv:1609.05177 , 2016. [3] O. E. Euch and M. Rosenbaum. The characteristic function of rough Heston models. arXiv:1609.02108 , 2016. [4] J. Gatheral, T. Jaisson, and M. Rosenbaum. Volatility is rough. arXiv:1410.3394 , 2014.
Prerequisites / Notice	Requirements: sound understanding of stochastic concepts and of con- cepts of mathematical Finance, ability to implement econometric or simula- tion routines in MATLAB.
401-5910-00L	Talks in Financial and Insurance Mathematics	0 credits	1K	P. Cheridito, M. Schweizer, M. Soner, J. Teichmann, M. V. Wüthrich
Abstract	Research colloquium
Learning objective
Content	Regular research talks on various topics in mathematical finance and actuarial mathematics
406-2604-AAL	Probability and Statistics Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.	7 credits	15R	J. Teichmann
Abstract	Introduction to probability and statistics with many examples, based on chapters from the books "Probability and Random Processes" by G. Grimmett and D. Stirzaker and "Mathematical Statistics and Data Analysis" by J. Rice.
Learning objective	The goal of this course is to provide an introduction to the basic ideas and concepts from probability theory and mathematical statistics. In addition to a mathematically rigorous treatment, also an intuitive understanding and familiarity with the ideas behind the definitions are emphasized. Measure theory is not used systematically, but it should become clear why and where measure theory is needed.
Content	Probability: Chapters 1-5 (Probabilities and events, Discrete and continuous random variables, Generating functions) and Sections 7.1-7.5 (Convergence of random variables) from the book "Probability and Random Processes". Most of this material is also covered in Chap. 1-5 of "Mathematical Statistics and Data Analysis", on a slightly easier level. Statistics: Sections 8.1 - 8.5 (Estimation of parameters), 9.1 - 9.4 (Testing Hypotheses), 11.1 - 11.3 (Comparing two samples) from "Mathematical Statistics and Data Analysis".
Literature	Geoffrey Grimmett and David Stirzaker, Probability and Random Processes. 3rd Edition. Oxford University Press, 2001. John A. Rice, Mathematical Statistics and Data Analysis, 3rd edition. Duxbury Press, 2006.