Digital AI Finance

Digital Finance: Theory, Models,
and Industry Practice

10-Day PhD, MSc & BSc Seminar Series

Seminar Overview

Format 10 days, 2 hours per session (20 hours total)
Target Audience PhD students and advanced researchers in finance, economics, computer science
Prerequisites Graduate-level probability, stochastic processes, optimization; familiarity with Python
Assessment Research proposal (60%), problem sets (40%)

Learning Objectives

  1. Master the mathematical foundations underlying digital finance—stochastic calculus, game theory, mechanism design, and optimal control
  2. Critically evaluate state-of-the-art research in DeFi, crypto asset pricing, blockchain economics, and machine learning for finance
  3. Connect theoretical models to real-world industry implementations including Uniswap, Aave, Deribit, Flashbots, and FinRL
  4. Formulate original research questions at the frontier of digital finance and defend a viable research methodology
PhD

PhD Seminar: Theory, Models, and Industry Practice

Day 1

Pricing Digital Assets

Theory
Jump-diffusion models (Merton, Kou), stochastic volatility (Heston, Bates), equilibrium pricing under incomplete markets
Entry Point
“Why Black–Scholes Fails for Bitcoin”
Industry
Deribit options market, model calibration to BTC/ETH implied volatility surfaces
Day 2

DeFi Mathematics

Theory
CFMM geometry and convex optimization, impermanent loss analytics, optimal lending rate models
Entry Point
“Uniswap: Swap, Provide Liquidity, Lose Money”
Industry
Uniswap V3 concentrated liquidity empirics, Aave lending protocol mechanics
Day 3

Blockchain Economics

Theory
Transaction fee mechanism design, MEV game theory, tokenomics and dynamic adoption models
Entry Point
“The Invisible Tax: What Is MEV?”
Industry
Flashbots proposer–builder separation, EIP-1559 fee market empirics
Day 4

ML & Market Microstructure

Theory
Kyle model of informed trading, VPIN, reinforcement learning for order execution, transformers for limit order books
Entry Point
“Can a Machine Learn to Trade Bitcoin?”
Industry
Microstructure signal construction, SHAP-based model explanations for regulatory compliance
Day 5

Risk, Regulation & the Future

Theory
Network contagion models, extreme value theory, copula dependence structures, CBDCs, stablecoin stability mechanisms
Entry Point
“The $2.57 Billion Wash Trading Problem”
Industry
Real-world asset tokenization, RegTech solutions, compliance automation
Day 6

DeFi Derivatives

Theory
Perpetual futures pricing, power perpetuals (Squeeth), option vaults, structured products
Entry Point
“The $80B/Day Market”
Industry
Deribit perps, on-chain options, vAMM mechanics
Day 7

AI Agents & Autonomous Finance

Theory
POMDP formalization, multi-agent game theory, LLM oracles, account abstraction security
Entry Point
“When GPT-4 Resolves a $100M Bet”
Industry
Autonomous DeFi agents, oracle design
Day 8

Zero-Knowledge Proofs for Finance

Theory
Interactive proof systems, polynomial commitments (KZG, FRI), ZK-rollup validity proofs
Entry Point
“Proving Facts Without Revealing Secrets”
Industry
Aztec private DeFi, ZK-KYC
Day 9

Prediction Markets

Theory
LMSR derivation from scoring rules, information aggregation theory, Milgrom–Stokey theorem
Entry Point
“When Markets Know More Than Experts”
Industry
Polymarket microstructure, cross-platform arbitrage
Day 10

Real-World Asset Tokenization

Theory
RWA pricing (DCF + risk premia), liquidity models, auction design for token issuance
Entry Point
“Can You Price Liquidity in a Market That Barely Trades?”
Industry
BlackRock BUIDL, EU DLT Pilot Regime
PhD

PhD Course Materials

Lecture Slides

Day 1: Crypto Derivatives Day 2: DeFi Mathematics Day 3: Blockchain Economics Day 4: ML & Microstructure Day 5: Risk & Regulation Day 6: DeFi Derivatives Day 7: AI Agents Day 8: ZK Proofs & Privacy Day 9: Prediction Markets Day 10: RWA Tokenization

Problem Sets & Templates

Problem Set 1: Crypto Derivatives Problem Set 2: DeFi Mathematics Research Proposal Template
MSc

MSc Seminar: Models, Markets, and Implementation

Master’s Level (1st/2nd Year MSc)

Format 10 days, 2 hours per session (20 hours total)
Target Audience 1st and 2nd year MSc students in finance, data science, or quantitative economics
Prerequisites Intermediate statistics and econometrics; working knowledge of Python; introductory finance
Assessment Individual case study (60%), daily exercises (40%)
Day 1

Pricing Digital Assets — Models That Actually Work

Concepts
GARCH with MLE, Merton jump-diffusion (simulation), implied volatility surface
Hook
“What the Models Missed: March 2020 Crash”
Exercise
GARCH modeling in Python
Day 2

DeFi Protocol Design

Concepts
V3 concentrated liquidity derivation, IL formula proof, lending rate economics
Hook
“$1.8B in 24 Hours: Uniswap V3 Launch”
Exercise
V3 LP simulator
Day 3

Blockchain Game Theory

Concepts
Consensus games (payoff matrices), EIP-1559 mechanism design, MEV formalization
Hook
“The $25M FBI Sting: Operation Token Mirrors”
Exercise
MEV detection + EIP-1559 simulation
Day 4

ML for Crypto Markets

Concepts
Feature engineering, random forests/XGBoost, SHAP explainability, walk-forward testing
Hook
“The Backtest That Fooled Wall Street”
Exercise
Full ML prediction pipeline
Day 5

Risk, Regulation & the Future

Concepts
Student-t VaR/ES, CVaR optimization, DeFi contagion networks, MiCA regulation
Hook
“The Day DeFi Nearly Died: MakerDAO 2020”
Exercise
Portfolio risk analysis + stress testing
Day 6

DeFi Derivatives & Structured Products

Concepts
Perpetual futures funding rates, power perpetuals, option vaults (DOVs), structured product payoffs
Hook
“The $80B/Day Market Nobody Talks About”
Exercise
Perpetual funding rate simulator + vault payoff analysis
Day 7

AI Agents & LLMs in Finance

Concepts
Autonomous agents in DeFi, LLM-based oracle resolution, POMDP for trading, agent safety
Hook
“When GPT-4 Settles a $100M Prediction Market”
Exercise
Build a simple LLM-based trading agent
Day 8

Privacy & Zero-Knowledge Proofs

Concepts
ZK proof intuition, SNARKs vs STARKs, ZK-rollups for scaling, private DeFi
Hook
“How to Prove You’re Rich Without Showing Your Balance”
Exercise
ZK circuit walkthrough + rollup cost comparison
Day 9

Prediction Markets & Information Aggregation

Concepts
LMSR market maker, information aggregation, calibration, Polymarket mechanics
Hook
“When Markets Called the Election Better Than Polls”
Exercise
LMSR pricing simulation + arbitrage strategy
Day 10

Real-World Asset Tokenization

Concepts
RWA valuation frameworks, token issuance mechanics, liquidity bootstrapping, regulatory sandboxes
Hook
“BlackRock Puts $500M on a Blockchain”
Exercise
RWA token pricing model + liquidity analysis
MSc

MSc Course Materials

Lecture Slides

Day 1: Crypto Pricing & Volatility Day 2: DeFi Protocol Design Day 3: Blockchain Game Theory Day 4: ML for Crypto Day 5: Risk & Regulation Day 6: DeFi Derivatives Day 7: AI Agents Day 8: ZK & Privacy Day 9: Prediction Markets Day 10: RWA Tokenization

Case Study

Individual Case Study Brief & Rubric
BSc

BSc Seminar: From Bitcoin to DeFi

Undergraduate Level (3rd/4th Year)

Format 10 days, 2 hours per session (20 hours total)
Target Audience 3rd and 4th year undergraduate students in finance, economics, or related fields
Prerequisites Introductory statistics and probability; basic Python familiarity helpful but not required
Assessment Group project (50%), daily hands-on exercises (30%), participation (20%)
Day 1

What Makes Crypto Different?

Concepts
Random walks, fat tails, GARCH volatility, Black–Scholes intro
Hook
“The Pizza That Cost $800 Million”
Hands-On
Crypto returns analysis in Python
Day 2

DeFi Explained

Concepts
Constant product AMM (x·y=k), impermanent loss, Aave lending
Hook
“The $3 Billion Vending Machine”
Hands-On
Build your own AMM in Python
Day 3

Blockchain Economics

Concepts
PoW/PoS consensus, EIP-1559 fees, MEV, CBDCs & stablecoins
Hook
“The $50 Invisible Tax on Every Trade”
Hands-On
EIP-1559 fee market simulation
Day 4

AI Meets Finance

Concepts
ML basics, microstructure features, decision trees, random forests
Hook
“The Bot That Made $1M in a Day”
Hands-On
Predict BTC returns with ML (scaffolded)
Day 5

Risk, Regulation & Future

Concepts
VaR, Expected Shortfall, portfolio theory, MiCA, tokenization
Hook
“The $40 Billion Terra/Luna Crash”
Hands-On
Build a crypto portfolio
Day 6

What Are Perpetual Futures?

Concepts
Perpetual futures vs. traditional futures, funding rates, leverage, liquidation mechanics
Hook
“The Contract That Never Expires”
Hands-On
Funding rate tracker + PnL simulator
Day 7

The Robot That Trades While You Sleep

Concepts
AI agents, chatbots in finance, LLMs for market analysis, autonomous trading basics
Hook
“Meet the AI That Manages Its Own Wallet”
Hands-On
Build a simple rule-based trading bot
Day 8

Proving Facts Without Revealing Secrets

Concepts
Zero-knowledge proofs (intuition), privacy on blockchains, ZK-rollups for cheaper transactions
Hook
“How to Prove You’re 18 Without Showing Your ID”
Hands-On
Interactive ZK proof demo + rollup cost comparison
Day 9

When Crowds Beat Experts

Concepts
Prediction markets, wisdom of crowds, betting odds as probabilities, Polymarket
Hook
“The Website That Predicted the Election”
Hands-On
Create a classroom prediction market
Day 10

When Your House Becomes a Token

Concepts
Real-world asset tokenization, fractional ownership, digital bonds, regulatory basics
Hook
“Own a Piece of a Skyscraper for $50”
Hands-On
Design a tokenized asset + pitch presentation
BSc

BSc Course Materials

Lecture Slides

Day 1: Crypto Pricing & Volatility Day 2: DeFi Mechanics Day 3: Blockchain Economics Day 4: AI & Crypto Markets Day 5: Risk & Regulation Day 6: DeFi Derivatives Day 7: AI Agents Day 8: ZK & Privacy Day 9: Prediction Markets Day 10: RWA Tokenization

Group Project

Group Project Brief & Rubric

Key Reading List

  1. Lehar, A. & Parlour, C.A. (2025). Decentralized Exchange: The Uniswap Automated Market Maker. Journal of Finance, 80(1).
  2. Angeris, G., Agrawal, A., Evans, A., Chitra, T. & Boyd, S. (2024). The Geometry of Constant Function Market Makers. ACM Conference on Economics and Computation (EC).
  3. Li, J., Osterrieder, J. & Windcliff, H. (2026). Equilibrium Pricing of Bitcoin Options. Journal of Futures Markets.
  4. Bahrani, M., Garimidi, P. & Roughgarden, T. (2024). Transaction Fee Mechanism Design. Advances in Financial Technologies (AFT).
  5. Cong, L.W., Li, Y. & Wang, N. (2021). Tokenomics: Dynamic Adoption and Valuation. Review of Financial Studies, 34(3).
  6. Echenim, M., Gobet, E. & Maurice, A.-C. (2025). Uniswap v3: Impermanent Loss Modeling. SIAM Journal on Financial Mathematics.
  7. Easley, D., O’Hara, M. et al. (2024). Microstructure and Market Dynamics in Crypto Markets. SSRN Working Paper.
  8. Kou, S.G. (2002). A Jump-Diffusion Model for Option Pricing. Management Science, 48(8).
  9. Heimbach, L. & Huang, W. (2024). DeFi Leverage. BIS Working Paper No. 1171.
  10. Gudgeon, L., Perez, D., Harz, D., Livshits, B. & Gervais, A. (2023). Systemic Fragility in Decentralized Markets. BIS Working Paper No. 1062.

Recommended Textbooks

  • Harvey, C.R., Ramachandran, A. & Santoro, J., DeFi and the Future of Finance (Wiley, 2021)
  • Di Maggio, M., Blockchain, Crypto and DeFi (Wiley, 2024)
  • Föllmer, H. & Schied, A., Stochastic Finance: An Introduction in Discrete Time (de Gruyter)
  • López de Prado, M., Advances in Financial Machine Learning (Wiley, 2018)
  • O’Hara, M., Market Microstructure Theory (Wiley, 1995)