FA595 Financial Technology (FinTech)
Course Catalog Description
Introduction
FA 595 will survey emerging topics in the area of financial technology and also allow students to develop practical programming, statistics, and mathematical skills that are valued in the Fintech industry. We will explore topics from both theoretical and practical perspectives in the areas of automated wealth management, digital lending, peer-to-peer applications including payments and insurance, machine learning financial applications, and digital currency and blockchain trends. During this course, students will have the opportunity to gain an understanding of each of these topics as well as develop their own software in the Python programming language related to these areas. For example, when discussing robo-advising, we will examine how a robo-advisor can select ETFs based on tracking error and expense ratio considerations, construct a portfolio based upon client preferences and asset allocation techniques, and rebalance the portfolio on a regular basis.
Campus | Fall | Spring | Summer |
---|---|---|---|
On Campus | X | X |
Instructors
Professor | Office | |
---|---|---|
Steve Taylor
|
staylor6@stevens.edu |
More Information
Course Outcomes
After successful completion of this course, students will:
- Be conversant in both the main theoretical ideas and high level concepts of the financial technology topics to be discussed.
- Conversant in both the main theoretical ideas and high-level concepts of the financial technology topics to be discussed.
- Students should aim to become proficient in the implementation of key ideas behind such topics.
- Give students exposure to core ideas in financial technology as well as develop hands-on programming skills in the Fintech area.
- Students will also be given outlines for a main project for this course which may lead into future research projects or a master’s thesis topic.
- Finally, this course is a precursor for further Fintech topic-specific graduate courses.
Course Resources
Textbook
- McKinney, Wes. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Additional References
- Whitepapers, Survey Articles, and Video materials will be given to students throughout the class
Grading
Grading Policies
Weights | ||
1 | Participation | 20% |
2 | Homework | 30% |
3 | Topic Projects | 30% |
4 | Final Project | 20% |
5 | Total | 100% |
Lecture Outline
Week | Topic |
---|---|
Initial Class | Introduction and Course Overview
Required Reading:None Assignment:Python Programming Problems |
Week 1 | Python and Git
Reading:Python package and Github Tutorial Examples with Fintech Applications Assignment:Problem Set 1 |
Week 2 | Financial Analytics in Python Required Reading: Python Tutorials pyfolio/Riskfolio-Lib Assigmnent:Analytics Programming Project |
Week 3 | Robo-Advisors Reading:Financial Advisement History/Survey Articles Assignment:Reading |
Week 4 | Robo-Advisors Reading:Wealthfront and Betterment Whitepapers Assignment:Problem Set 2 |
Week 5 | Loan Programs Reading:PPP and Business Loan Program Documents Assignment:Reading |
Week 6 | P2P Lending Reading:P2P Lending Survey and History Assignment:Reading |
Week 7 | Insurtech Reading:Current trends and captive insurance documents Assignment: Insurtech Project |
Week 8 | Insurtech Reading:Peer-to-Peer Insurance Notes Assignment: Reading |
Week 9 | Crypto Currencies and Blockchain Reading:History of Money/Crypto Currencies Articles Assignment:Reading |
Week 10 | Crypto Currencies and Blockchain Reading:Original Bitcoin Whitepaper Assignment:Problem Set 4 |
Week 11 | Crypto Currencies Exchanges and Blockchain Reading:Ethereum/Blockchain References Assignment:Crypto Programming Project |
Week 12 | DeFi Reading:Decentralized Finance/ Central Bank Digital Currency Assignment: Work on Final Project |
Week 13 | Regulation Reading: Regulatory Initiatives/SEC/CFTC, etc Assignment: Work on Final Project |
Week 14 | Final Project Reading:None Assignment: Presentations |