Skip Navigation
Search

AMS 320, INTRODUCTION TO QUANTITATIVE FINANCE

Catalog Description: The course introduces the main classes of financial securities, the mathematical tools employed to model their prices, and common models for risk and investment management.  Building realistic models relies on having a working knowledge of the empirical properties of financial asset returns which is another focus of the course.  R is used as an environment for modeling.

PrerequisiteAMS 311


Course offered in spring and summer semesters ONLY.

3 credits; A-F grading

IMPORTANT:  The GPNC option is unavailable for this course.


Textbook for Spring 2024:
"Options, Futures and Other Derivatives" by John C. Hull, published by Pearson Publishing, 2021; 11th edition; ISBN: 

eText :   9780136939917

Print Rental:    9780136939979

 

 

Week 1:  Time value of money

Week 2:  Bonds and bond pricing

Week 3:  Determinants of interest rates

Week 4:  Equities and real estate

Week 5:  Exchange rates

Week 6:  Derivative securities I

Week 7:  Derivative securities II

Week 8:  Empirical properties of financial time series

Week 9:  Modern portfolio theory

Week 10:  The CAPM and other asset pricing models

Week 11:  Bond analysis

Week 12:  Option pricing models

Week 13:  Portfolio risk and performance analysis

Week 14:  Summary of methods, special topics, review for final

 


Learning Outcomes for AMS 320, Introduction to Quantitative Finance

* Proficiency in MATLAB programming: including scripting, procedural programming, GUI, debugging, plotting, profiling, and some commonly used toolboxes.

* Proficiency with Python programming, including scripting, object-oriented programming, and commonly used Python libraries.

* Best practices in scientific software engineering, including code modularization, debugging and testing, version control, documentation, performance optimization, etc.