Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: Graduate Standing or Masters Status in the David Eccles School of Business.
Description
This course unites the power of computing and statistical analysis with the principles of finance. Students will first review the statistical foundations of modern computational finance, including the concepts behind the major theories of portfolio optimization, risk management, and financial modeling. Students will then employ Python programming skills and these essential data analysis concepts and techniques to relevant finance projects and problems. The focus of the course is very much practical. The learning objectives will be achieved by fusing problem-based learning and application of the Python programming language with the principal models of statistics and finance. The goal is to give students the opportunity to enhance their statistical and programming skills, while working on challenging and important problems relevant to a broad range of potential employers in finance.