COMPUTATIONAL FINANCE - COMP7926/COMP4060  

A Graduate Course in Computer Science - Winter 2023

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 and improve them for complicated finance models to price derivatives and other instruments;
  • bring a high level of confidence among the students through a term project .


    • The topics covered in this course will include:

  • terminologies, definitions, fundamentals of 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 in solving above models; also implementing these models using non-traditional computational intelligence techniques (eg., Ant Colony Optimization, Particle Swarm Optimization) for solving pricing problem;
  • introduction to complex financial instruments such as swaps and managing investments risk through Value at Risk analysis;
  • While these topics will be covered in lectures, additional topics such as using time series data for forecasting, risk analysis and derivative pricing could be covered as exercises and assignment problems.


    • Prerequisites: Strong interest in challenging problems, problem solving skills, sound mathematics/statistics background especially differential and stochastic calculus; Strong programming skills (C, Java, Python, R, 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. 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. For weeekly tentative coverage of the topics refer to the ROASS documnet posted.

    Instructor

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

    Lecture Timings:

    Mondays and Wednesdays 130PM-245PM (Drake Centre 138 until further notice)

    Important Information and Links

  • Lecture Notes Index
    • Page with links to all the lecture slides for the course.
  • Handout Index
    • Page with links to all the class handouts for the course.
  • A2-Papers
    • Page with lnks to the assignments for the course.
  • Symposia
    • Page tabulating the papers for in-class presentation by the students.
  • Special and Invited expert lectures
    • Page tabulating the expertise lectures meant for the students as well as general university community.

    The Computational Financial Derivatives (CFD) Laboratory at the University of Manitoba. Homepage

    tulsi dot .thulasiram at umanitobai dot ca