MPCS 52560 Applied Financial Technology (Autumn 2022)

*Please note: This is the syllabus from the 2021/22 academic year and subject to change.*

 

Applied Financial Technology explores how we can leverage technology to implement financial constructs like asset prices, investments, valuation, and payments.  Students can expect to participate in a class that is equal parts finance and technology.  We will cover financial theory and then leverage technological tools available today to execute on these constructs and enhance our understanding of them.

The class is largely group-based, project-based and somewhat self-directed.  The first portion of class is dedicated to students developing investing strategies on publicly traded companies that are of interest to the student.  The second-half of class will cover how to value cash flows and process payments.  Students will work closely with their groups to uncover insights on publicly traded companies using the material covered in course.  Groups will be expected to present their findings regularly. Required individual reading assignments will also be done to provide the basis for the financial topics discussed in the course.

Example topics include:

• What are stock prices and what can/cannot they tell us?
• How do you value a publicly traded company to determine whether they are rich or cheap?
• What does it mean to say that markets are efficient?
• Can everyday traders really beat the market?
• How do we value payments in the future?
• What is a yield curve and what does it tell us?

Example technologies include:

• Python-based algorithmic trading platform QuantConnect
• Javascript-based bond pricing website
• Payments API interactions with Stripe

We will also reference constructs like decentralization and distributed ledger technologies to contextualize and expand upon what we cover in this class, but this class will not focus exclusively on these issues. Students who are interested in such subects can still benefit from learning the financial constructs covered in this class.

Core Programming

Interest in finance and data.

This course requires competency in Unix and Linux. Please plan to attend the MPCS Unix Bootcamp (https://masters.cs.uchicago.edu/page/mpcs-unix-bootcamp) or take the online MPCS Unix Bootcamp Course on Canvas.

This class is scheduled at a time that does not conflict with any other classes this quarter.

Masters Program in Computer Science MS in Computational Analysis in Public Policy (Year 2) MA in Computational Social Science (Year 2) Bx/MS in Computer Science (Option 2: Professionally-oriented - CS Majors) Bx/MS in Computer Science (Option 3: Profesionally-oriented - Non-CS Majors)