For an introduction to using and properly setting up git, see Introduction to git for academics.Students will program and explore all basic techniques in a numerical programming environment and apply these algorithms to real data whenever possible.
#Stochastic methods series#
Topics include a short introduction to the basic notions of financial mathematics, binomial tree models, discrete Brownian paths, stochastic integrals and ODEs, Ito's Lemma, Monte-Carlo methods, finite differences solutions, the Black-Scholes equation, and an introduction to time series analysis, parameter estimation, and calibration. The module is taught as an integrated lecture-lab, where short theoretical units are interspersed with interactive computation and computer experiments. Examples will mostly come from the area of Financial Mathematics, so that this module plays a central role in the education of students interested in Quantitative Finance and Mathematical Economics.
This module is a first hands-on introduction to stochastic modeling. SyllabusĪll the most recent information about class can be found on this website. Thu 11:15 - 12:30, Westhall 4 (+ online via MS Teams)įirst class session: Sep. This class is offered in person by default, but the format can be adapted in case students are not on campus yet or the rules for in-person classes change. Please bring your laptop to every class session. If you plan to take this class, but could not register yet, please come anyway. Class recordings can be found on MS Teams under the "F20_CA-MATH-811_Stochastic Methods Lab" channel.
The first TA question session is on Thursday, Sep. III lecture hall, the Friday sessions in the Res. 13 (to discuss the solution to HW sheet 9, and to introduce the final project / take-home exam). 6 (to discuss the solution to HW sheet 8, and to introduce the last HW sheet 9), and on Fri, Nov. After that, there will be two more sessions: On Fri, Nov. The last regular class session is on Fri, Oct.
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