Notebooks

These notebooks combine economic ideas with Python implementation.

If you want a shorter version focused on the most important code and all main outputs, use Notebook Summaries.

Notebook Description
Introduction to Jupyter Notebooks Quick introduction to Python notebook workflow, data download with yfinance, basic return calculations, plotting, and a first regression.
Optimization in Python Numerical optimization tools in Python with examples relevant to finance applications.
A Market Index for Cryptocurrencies Builds a crypto market index, estimates coin betas to the index, and compares crypto market behavior with SPY.
Minimum Variance Portfolio Constructs and analyzes minimum-variance portfolios, including covariance estimation and risk-return implications.
Analyzing Mutual Fund Performance Evaluates mutual fund performance with factor-style regressions and performance metrics.
Option Pricing with Neural Networks Trains neural networks to approximate option prices and compares model predictions with observed values.
Volatility Surface Modeling with Neural Networks Uses SPX option data to model implied volatility surfaces with machine learning and visualize fit quality.
Blockchain Foundations Covers bytes, hashing, block structure, PoW intuition, mining pools, and security through a state-process perspective.
Proof of Work Example Implements a minimal Proof of Work blockchain: hashing, mining, block validation, tamper checks, and chain integrity.
Proof of Stake Economics Develops PoS economics: staking returns, slashable-capital security, finality, and PoW-vs-PoS cost structure.
Decentralized Exchanges and AMMs Develops constant-product AMM pricing, quantifies slippage and arbitrage adjustment, and analyzes LP fee income versus impermanent loss.
Stablecoins and Peg Risk Explains stablecoin design, measures depeg behavior in market data, and introduces simple models of arbitrage frictions and run risk.

Supporting Files in notebooks/

The folder also currently contains the following data files used by some notebooks: