hfsl_course

FE516 MATLAB for Finance
W 09:00-10:00AM
Babbio Center: Hanlon Financial Systems Lab
2-3pm Monday
• Fall On Campus
• Spring On Campus
Students will get hands-on experience with Matlab, and they will gain fundamental knowledge in developing applications involving financial data. The course is designed so that upon completion the students will be able to use Matlab for their assignments and research involving programming, particularly in future finance courses (e.g., FE 621, FE 630, FE 635, FE 535). Knowing Matlab is a very useful skill for a quantitative analyst working in the financial industry.

The purpose of the this course is to introduce the basics of Matlab programming and some relevant toolboxes for finance. This short course is intended for students with little or no experience with the software covering Matlab’s basic operations and features. In addition, the course works through several applications, to give the students the necessary knowledge on developing their own projects. Topics covered include functions, arrays, Matlab plotting, simulation of stochastic processes in finance, numerical and symbolic solvers. Assignments are designed to build an appreciation for randomness, simulation, and the role of approximation. Also, in-class workshops are designed for students to gain better insights and develop their skills.

Several useful and powerful Matlab toolboxes are studied with relevant examples: Curve fitting Toolbox, Optimization Toolbox, Statistics Toolbox, Database Toolbox, numerical solvers (solving equations, integration, differentiation, ODEs, etc.), Symbolic Math Toolbox, Simulink. The final part of the class involves financial applications (Monte Carlo Simulation, Brownian Motion Simulation and Calibration, Black–Scholes option pricing, etc.) Other topics could be added at students’ request.

After taking this course, the students will be able to:

(i) Import/export data

(ii) Create and manipulate variables

(iii) Working data in and out of databases

(iv) Analyze and visualize data

(v) Implement algorithms, simulate stochastic processes

(vi) Use symbolic and numerical solvers

Attaway, Stormy. Matlab: a practical introduction to programming and problem solving (2011)

Matlab Primer, Matlab help

HW 40%, Class work 20%, Final Project 40%.