FA595 Financial Technology (FinTech)



Course Catalog Description

Introduction

This course 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
Web Campus X X X

Instructors

Professor Email Office
Steve Taylor
staylor6@stevens.edu Edwin 130 A

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.
  • Aim to become proficient in the implementation of key ideas behind such topics in the Python programming language.
  • Given exposure to core ideas in financial technology as well as develop hands-on programming skills in the Fintech area.
  • Given outlines for a main project for this course which may lead into future research projects or a masters 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 Class Participation 20%
2 Homework 30%
3 Topic Project 30%
4 Final Project 20%

Lecture Outline

Week Topic Reading Assignments
Initial Class Introduction and Course Overview Required: None
Optional: None
Python Programming Problems
Week 1 Python and Git Python package and Github Tutorial Examples with Fintech Applications Problem Set 1
Week 2 Financial Analytics in Python Required: Python Tutorials pyfolio/Riskfolio-Lib Analytics Programming Project
Week 3 Robo-Advisors Financial Advisement History/Survey Articles Reading
Week 4 Robo-Advisors Wealthfront and Betterment Whitepapers Problem Set 2
Week 5 Robo-Advisors Bayesian Extensions: Black-Litterman Model Robo-Advisor Programming Project
Week 6 P2P Lending P2P Lending Survey and History Reading
Week 7 P2P Lending Logistic Regression and Tree Model Handouts P2P Lending Programming Project
Week 8 Insurtech Peer-to-Peer Insurance Notes Reading
Week 9 Crypto Currencies and Blockchain History of Money/Crypto Currencies Articles Reading
Week 10 Crypto Currencies and Blockchain Original Bitcoin Whitepaper Problem Set 4
Week 11 Crypto Currencies Exchanges and Blockchain Ethereum/Blockchain References Crypto Programming Project
Week 12 DeFi Decentralized Finance/ Central Bank Digital Currency Work on Final Project
Week 13 Regulation Regulatory Initiatives/SEC/CFTC, etc Work on Final Project
Week 14 Final Project Presentations None Give Presentations