Computational Finance with Matlab
Lecturer: A. Gnoatto
Schedule and Venue
| Lectures Dr. Alessandro Gnoatto |
Dates and Times: July 29th to August 2nd 2013, 9:00 to 13:00 & 14:00 to 16:00 First lecture: Thu 09.10.2014 |
quantLab Room B 121 |
| Exercises Dr. Alessandro Gnoatto |
Dates and Times: July 29th to August 2nd 2013, 16:00 to 18: First lecture: Thu 16.04.2015 |
Course Description
The aim of the lecture is to connect theory and practice in Mathematical Finance. We will look at several examples/models and will produce Matlab/GNU Octave code for each topic allowing us to implement standard and advanced financial models and the associated numerical procedures.
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Schedule of the lecture:
- Introduction to Matlab
- Option pricing using binomial trees
- The Black-Scholes model: closed form solution, Greeks, Monte Carlo simulation, PDE methods, implied volatility via bisection and Newton-Raphson algorithms
- Monte Carlo in a Black-Scholes setting: pricing of Asian, Look-back and Barrier options. Estimating Greeks using Monte Carlo
- Transform methods in Finance: revisiting the Black Scholes model in a FFT framework. The Carr and Madan Formula and the Lewis approach
- Stochastic volatility: the Heston model. Monte Carlo for stochastic volatility models – the Milstein scheme. FFT for the Heston model.
Pre-requisites
A solid knowledge of mathematical finance, measure theoretic probability and linear algebra is assumed.Students without a prior knowledge of Matlab or programming should consult the following tutorial:
- Matlab primer: http://www.math.toronto.edu/mpugh/primer.pdf
- Matlab and GNU Octave are very similar, however, here you can find a list with some differences: http://en.wikibooks.org/wiki/MATLAB_Programming/Differences_between_Octave_and_MATLAB.