Laboratory, Notebooks & Workbooks
The three companions — one seeded engine
Every chapter is backed by three companion artifacts driven by a single seeded Python engine. The Laboratory webapp is interactive; the Python notebook runs the same computations in code; the Excel workbook puts one experiment per tab with live formulas beside the engine’s reference values. All three use the book’s seeds (2026CCNN), so their numbers agree by construction.
Downloads by chapter
Chapter 1 · The Mathematical Architecture of Modern Finance
Module 1: Probability and State Space Explorer — Week 1
Chapter 2 · Probability, Uncertainty, and Financial States
Module 2: Probability and Distribution Lab — Week 2
Chapter 3 · Information, Conditional Expectation, and Filtrations
Module 3: Information and Conditional Expectation Simulator — Week 3
Chapter 4 · Valuation, No-Arbitrage, and State Prices
Module 4: State Prices, Completeness, and Bounds — Week 4
Chapter 5 · Martingales, Change of Measure, and Risk-Neutral Valuation
Module 5: Fair Games, Measure Change, and Dynamic Hedging — Week 5
Chapter 6 · Stochastic Processes and Financial Dynamics
Module 6: Paths, Quadratic Variation, and Jumps — Week 6
Chapter 7 · Itô Calculus and Continuous-Time Finance
Module 7: Stochastic Calculus in the Hands — Week 7
Chapter 8 · Derivatives, PDEs, and the Feynman–Kac Bridge
Module 8: The Pricing Machine — Week 8
Chapter 9 · Portfolio Choice and Dynamic Optimization
Module 9: The Allocation Laboratory — Week 9
Chapter 10 · Stochastic Control and the Hamilton–Jacobi–Bellman Equation
Module 10: The Control Room — Week 10
Chapter 11 · Optimal Stopping and Real Options
Module 11: The Timing Desk — Week 11
Chapter 13 · Risk Measures, Ambiguity, and Robustness
Module 13: The Risk Office — Week 13
Chapter 14 · Equilibrium, Liquidity, and the Allocation of Capital
Module 14: The Market Itself — Week 14