digital-finance-course
Digital Finance Course - Blockchain, DeFi, and Crypto-Assets (MSc/BSc)
Information
| Property | Value |
|---|---|
| Language | Jupyter Notebook |
| Stars | 0 |
| Forks | 0 |
| Watchers | 0 |
| Open Issues | 0 |
| License | No License |
| Created | 2026-01-28 |
| Last Updated | 2026-03-25 |
| Last Push | 2026-02-06 |
| Contributors | 1 |
| Default Branch | main |
| Visibility | private |
Notebooks
This repository contains 22 notebook(s):
| Notebook | Language | Type |
|---|---|---|
| L01_notebook | PYTHON | jupyter |
| L05_notebook | PYTHON | jupyter |
| L06_notebook | PYTHON | jupyter |
| L07_notebook | PYTHON | jupyter |
| L08_notebook | PYTHON | jupyter |
| L09_notebook | PYTHON | jupyter |
| L10_notebook | PYTHON | jupyter |
| L11_notebook | PYTHON | jupyter |
| L12_notebook | PYTHON | jupyter |
| L13_notebook | PYTHON | jupyter |
| L14_notebook | PYTHON | jupyter |
| L15_notebook | PYTHON | jupyter |
| L16_notebook | PYTHON | jupyter |
| L17_notebook | PYTHON | jupyter |
| L18_notebook | PYTHON | jupyter |
| L19_notebook | PYTHON | jupyter |
| L20_notebook | PYTHON | jupyter |
| L21_notebook | PYTHON | jupyter |
| L22_notebook | PYTHON | jupyter |
| L23_notebook | PYTHON | jupyter |
| L24_notebook | PYTHON | jupyter |
| notebook_template | PYTHON | jupyter |
Reproducibility
No specific reproducibility files found.
Status
- Issues: Enabled
- Wiki: Enabled
- Pages: Enabled
README
Digital Finance: A Systems Thinking Approach
A PhD-level course examining blockchain, DeFi, and cryptocurrency through the lens of systems thinking.
Course Philosophy
Finance needs systems thinking.
Traditional finance education treats financial systems as given. This course treats them as designed artifacts that can be understood, analyzed, and improved through engineering principles.
Four Analytical Lenses
Every topic is examined through four complementary perspectives:
| Lens | Core Question | Application |
|---|---|---|
| Evolution | What determines protocol survival and value? | Selection pressures, network effects, competitive dynamics |
| Incentives | How do mechanisms shape behavior? | Game theory, tokenomics, emergent outcomes |
| Laboratory | What does DeFi teach about finance? | DeFi as experiment revealing market truths |
| Trust | Where does trust actually live? | Hidden assumptions in "trustless" systems |
Course Structure
Format: 24 lectures x 45 minutes Level: PhD Language: English
Modules
| Module | Topic | Lectures |
|---|---|---|
| M1 | Foundations | L01-L04: Introduction, Cryptography, Blockchain, Bitcoin |
| M2 | Smart Contracts | L05-L08: Ethereum, Solidity, Tokens, NFTs |
| M3 | DeFi Core | L09-L12: AMMs, Lending, Derivatives, Stablecoins |
| M4 | Advanced DeFi | L13-L16: MEV, Layer 2, DAOs, RWA |
| M5 | Analysis & Failures | L17-L20: Analytics, Security, Protocol Failures, Exchange Failures |
| M6 | Frontiers | L21-L24: Regulation, Privacy, Lightning/CBDCs, Future Research |
Repository Structure
Digital-Finance-Course/
|-- README.md # This file
|-- SYLLABUS.md # Full syllabus with schedule
|-- READING_LIST.md # All 24 papers + supplementary
|
|-- M1_Foundations/
| |-- L01_Introduction/
| | |-- L01_slides.tex # Beamer slides
| | |-- L01_notes.md # Instructor notes
| | |-- L01_readings.md # Paper summaries
| | |-- L01_problems.md # Problem set
| | |-- L01_solutions.md # Solutions
| | |-- L01_notebook.ipynb # Jupyter notebook
| | |-- 01_chart_folder/ # Chart with chart.py and chart.pdf
| | `-- temp/ # LaTeX auxiliary files
| |-- L02_Cryptography/
| |-- L03_Blockchain/
| `-- L04_Bitcoin/
|
|-- M2_Smart_Contracts/
|-- M3_DeFi_Core/
|-- M4_Advanced_DeFi/
|-- M5_Analysis_Failures/
|-- M6_Frontiers/
|
|-- capstone/
| |-- instructions.md # Capstone requirements
| |-- rubric.md # Grading rubric
| `-- examples/ # Example submissions
|
|-- resources/
| |-- glossary.md # Key terms defined
| |-- math_notation.md # Notation conventions
| `-- data_sources.md # Where to get data
|
`-- templates/
|-- chart_template.py # Standard chart boilerplate
|-- slide_template.tex # Beamer template
`-- notebook_template.ipynb # Jupyter template
Learning Outcomes
After completing this course, students will be able to:
- Research: Conduct original research publishable in top finance/CS journals
- Design: Design, audit, and evaluate DeFi protocols and systems
- Advise: Advise banks, regulators, and startups on digital finance strategy
- Analyze: Apply systems thinking to analyze any financial infrastructure
Prerequisites
None assumed. The course builds from scratch: - Module 1 covers cryptographic foundations - Each concept is introduced before use - Background sections accommodate mixed-background PhD students
Materials Per Lecture
Each lecture includes: - Slides: Beamer presentation (PDF) - Notes: Instructor notes with additional context - Readings: Primary paper + supplementary readings - Problems: Problem set with conceptual, calculation, and coding exercises - Solutions: Complete solutions - Notebook: Jupyter notebook with implementations - Charts: Publication-quality visualizations
Assessment
- Problem Sets: 40% (8 problem sets, best 6 count)
- Participation: 10%
- Capstone Project: 50% (Presentation + Paper)
Capstone Project
Format: 15-minute presentation + 15-20 page paper
Requirements: 1. Original research question in digital finance 2. Apply at least 2 of the 4 analytical lenses 3. Empirical analysis or protocol design 4. Literature grounding (minimum 15 sources) 5. Presentation to class for peer feedback
Key Resources
- Primary Readings: See READING_LIST.md
- Data Sources: See resources/data_sources.md
- Glossary: See resources/glossary.md
License
This course material is provided for educational purposes.
Digital Finance: A Systems Thinking Approach PhD-Level Course in Blockchain, DeFi, and Cryptocurrency