COMPUTATIONAL FINANCE - COMP7926  

A Graduate Course in Computer Science - Win 2018

Course Description

Purpose : The purpose of this course is to expose students challenging new opportunities for application of Computer Science to the field of Computational Finance.
This graduate course is designed to
  • grasp fundamentals of finance (particularly, Derivative markets)
  • discover the computational issues therein
  • abstract some scientific computing problems thereof

  • This course is intended to

  • familiarize a part of world of finance, especially derivative markets;
  • understanding high level and deeper mathematics behind financial derivatives;
  • getting first hand experience of formulating finance problems into computational problem(s);
  • developing algorithms/codes (sequential and possibly parallel) for simple problems (to begin with) and
  • improving them for complicated finance models to price derivatives;
  • bring a good understanding of the mathematical theory behind financial derivatives
  • bring a high level of confidence among the students through a term project .

  • The topics covered in this course will include:

  • terminologies, definitions, fundamental theorems on derivative pricing
  • discussion of famous Black-Scholes Formulation and the difficulties in solving the resulting Stochastic Partial Differential Equation;
  • formulating a solution model in discrete time; Introduction to Generalized Auto Regression Conditional Heteroskadasticity (GARCH) model;
  • traditional computational/numerical approaches such as finite-differencing, fast Fourier transform in solving above models; also implementing these models using non-traditional computational intelligence techniques for solving pricing problem;
  • numerical methodologies resorted;
  • introduction to complex financial instruments such as swaps and managing investments through portfolio management and Value at Risk;
  • some cutting edge technologies using nature inspired algorithms such as ACO and PSO;

  • Prerequisites: Strong interest in challenging problems, problem solving skills, sound mathematics/statistics background especially differential and stochastic calculus; Strong programming skills (C, Java, Python etc.), keeping abreast of current events in financial market for every day in-class discussion.:


    Main required readings from: Options, Futures and other Derivatives, John C. Hull, Prentice Hall, 8th (or later) edition. Relevant materials from other sources (books, conference/journal papers, reports and online documents) are highly encouraged. Tentative weekly coverage. We will start every class with a 5-10 minute discussion of current events presented by one student. Each student will have his/her opportunity to present his/her observation during the term.

    Instructor

    Dr. Ruppa Thulasiram
    E2-576 Engineering and Information Technology Complex
    (204) 474-6538
    tulsi at cs dot umanitoba dot ca
     

    Lecture Timings:

    Mondays and Wednesdays 1130AM-1245PM E2-360 EITC

    Important Information and Links


    tulsi@cs.umanitoba.ca