Advanced Topics in Computer Science - COMP4060-7570
COMPUTATIONAL FINANCE
A Undergraduate/Graduate Course in Computer Science - Win 2010
Course Abstract
Purpose : The purpose of this course is to expose and attract students
to the field of Computational finance.
This is a graduate course designed
to
grasp fundamentals of finance (particularly, Options)
discover the computational issues therein
abstract some scientific computing (eg. sparse matrix computation) problems
thereof and
introduce how parallel computing becomes useful
This course is intended for students
new to Financial Derivatives (as options are usually called)
to familiarize in the field of finance
to get first hand experience of formulating finance problems into a computational
problems
in developing sequential and parallel algorithms/codes for simple problems
(to begin with)
in improving them (with advanced state-of-the-art computing) for complicated
finance models
in high level understanding of the mathematical theory behind financial derivativese
[This course will not dwell too much into the mathematical rigour the computational finance
generally requires]
in bringing a level of confidence among the students through end-of-the-term
project .
The topics covered in this course will include:
Terminologies, definitions, fundamental theorems on Option pricing
Discussion of famous Black-Scholes Formulation and the difficulties in
solving the resulting Stochastic Partial Differential Equations
The Numerical Methodologies resorted
Elaborate discussion on particular method called Lattice Method
Discussion on Parallel Computing Paradigms
Implementation of Option Pricing problem using Lattice and other Methods.
Introduction to complex financial instruments such as swaps, CDO and modern computational techniques such as ACO and PSO.
The students will be tested through exercise problems on
on Monte Carlo Simulation,
Neural Networks, Fast Fourier Transform and
some cutting edge technologies and algorithms such as
Nature Inspired Algorithms, Grid Finance, and GARCH model for option pricing, to name a few.
Instructor
Dr. Ruppa Thulasiram
E2-576 Engineering and Information Technology Complex
(204) 474-6538
tulsi at cs dot umanitoba dot ca
Lecture Timings:
Tuesdays and Thursdays 1215PM-145PM E2-525 EITC
Important Information and Links
tulsi@cs.umanitoba.ca