FA595 Financial Technology (FinTech)
Course Catalog Description
Introduction
This course covers 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 digital currency and blockchain
technologies, automated wealth management, digital lending, peer-to-peer applications including payments
and insurance, machine learning financial applications.
Pre-requisite: FE520 (Introduction to Python for Financial Applications)
| Campus | Fall | Spring | Summer |
|---|---|---|---|
| On Campus | X | X |
Instructors
| Professor | Office | |
|---|---|---|
|
Victoria Li
|
jli264@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.
- In addition, students should aim to become proficient in the implementation of key ideas behind such topics.
- The main aim of this course is to give students exposure to core ideas in financial technology as well as develop hands-on programming skills in the Fintech area.
- 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
Recommended Readings
- Mastering Ethereum: Building Smart Contracts and DApps (2018) by Andreas M. Antonopoulos and Gavin Wood. ISBN: 1491971940.
- Blockchain Bubble or Revolution: The Future of Bitcoin, Blockchains, and Cryptocurrencies (2019)by Neel Mehta, Aditya Agashe and Parth Detroja. ISBN: 0578528150.
- DeFi and the Futrue of Finance (2021) by Campbell R Harvey, Ashwin Ramachandran and Joey Santoro. ISBN: 1119836018.
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (2017) by William McKinney. ISBN: 1491957662.
Grading
Grading Policies
| Weights | ||
| 1 | Two Exams | 50% (25% each) |
| 2 | Group Project and Presentation | 30% (15% and 15%) |
| 3 | Homework | 15% |
| 4 | Canvas Discussions | 5% |
| 5 | Total | 100% |
Lecture Outline
| Week | Topic |
|---|---|
| Week 1 | Course Introduction FinTech Overview |
| Week 2 | Blockchain Overview and Bitcoin Mechanics Bitcoin Economics and Limitations Discussion 1 Due |
| Week 3 | Scaling Blockchain: Proof-of-Work vs. Proof-of-Stake Proof-of-Stake Mechanics and Proof-of-Stake Blockchains Homework 1 Due |
| Week 4 | President’s Day – No Class |
| Week 5 | Cryptocurrency Exchanges and Price Discovery Crypto Regulation, Tax and Risk Management Web3 and Metaverse Discussion 2 Due |
| Week 6 | Payment Systems Overview Digital Wallets, Payments, and Transactions Homework 2 Due Group Project Member Sheet Due |
| Week 7 | Open Banking, Instant Payment Systems (IPS), Real-Time Payments (RTP), FedNow,
and the Global Banking with the SWIFT Payment Network Discussion 3 Due Exam 1 Review |
| Week 8 | Exam 1 |
| Week 9 | Spring Recess – No Class |
| Week 10 | Introduction to Robo-Advising |
| Week 11 | Construction and Development of a Robo-Advisor Homework 3 Due |
| Week 12 | Introduction to Machine Learning, Generative AI, and LLM |
| Week 13 | Prompt Engineering, LLM Tokenization and Textual Analysis with Python APIs |
| Week 14 | Ethics and Risk Management in AI Exam 2 Review Group Project Due Homework 4 Due Discussion 5 Due |
| Week 15 | Exam 2 |
| Week 16 | Group Project Presentations |