CS 522
Computational Tools and Methods for Finance
Spring 1998
Hollister 110
MWF 1:25 -2:15

http://www.cs.cornell.edu/Info/Courses/Spring-98/CS522/

This course will provide a hands-on introduction to computational methods and tools used in finance. We will study three commercial software packages used in finance, their underlying methods, and the financial context. The commercial software packages are the MATLAB Financial Toolbox, the Kamakura software, and the risk management software from Algorithmics.

Student Background: Programming experience (C or FORTRAN), MATLAB. Some study of numerical methods, especially numerical linear algebra.

Meetings: : Each week there will be 2 lectures and 1 lab/help session . The lectures will be on Monday and Wednesday (1:25- 2:15), the lab will be on Friday (1:25 - 2:15).

Course work: Course work will (heavily!) involve computer assignments. Grades will be based solely on homework assignments.

Text: There will be no text. There will be occasional handouts with references on reserve. (List to follow.)

Instructors:

• Prof. T. Coleman, Rhodes Hall 647, coleman@cs.cornell.edu
• Prof. R. Jarrow, 520 Mallott Hall, raj15@cornell.edu

Teaching Assistants: TBA

Note: Alternative class meeting times will be discussed in the first meeting (January 19).

CS 522 SYLLABUS (Spring, 1998)

MATLAB Finance Tools [7 weeks]

• Computing the price of stock options (Black-Scholes, Binomial Model)
• Computing option sensitivity measures and hedging strategies
• Bonds and fixed income securities (basic)
  • evaluation
  • sensitivity visualization
  • computing yield and spot curves
  • computing hedging strategies
• Computational portfolio management
  • The Markowitz model
  • Computing the Efficient Frontier
• Related optimization and inverse problems

The KAMAKURA Software [3.5 weeks]

• Modeling of the term structure
• Valuation methods
• Hedge calculation
• Sensitivity/optimization/stress testing

The ALGORITHMICS Software [3.5 weeks]

• Portfolio selection and immunization
• Scenario optimization (MultiMatlab?)
• Computing Value at Risk
• More on the Efficient Frontier
• Stress testing
• Linear and quadratic programming in finance
• Monte Carlo techniques