Volume II: Capital Deployment

Interactive notebooks for strategy, derivatives, and execution. Build hedging models. Price exotic options. Analyze market microstructure. Each notebook implements production-grade methods from the text.

13 Notebooks
42 BUILD Exercises
89 Production Models
Part V

Corporate Strategy

CH. XV

M&A Fundamentals

Deal structure analysis. Synergy valuation with probability weighting. Integration timeline modeling and execution risk quantification.

3 BUILD exercises deal_data.csv
CH. XVI

Capital Structure Decisions

Leverage optimization under uncertainty. Debt capacity estimation with rating constraints. Credit analysis framework for investment-grade thresholds.

3 BUILD exercises leverage_data.csv
CH. XVII

Dividend and Payout Policy

Shareholder return optimization. Buyback vs dividend analysis. Signaling theory implementation and payout sustainability modeling.

2 BUILD exercises dividend_history.csv
Part VI

Derivatives and Hedging

CH. XVIII

Options Fundamentals

Payoff structure visualization. Put-call parity verification. Binomial tree construction for European and American options.

4 BUILD exercises options_chain.csv
CH. XIX

Black-Scholes Framework

PDE derivation and numerical solution. Greeks computation with finite differences. Volatility surface calibration from market data.

4 BUILD exercises vol_surface.csv
CH. XX

Hedging Strategies

Delta hedging simulation with rebalancing costs. Portfolio insurance implementation. Tail risk management with put spreads and variance swaps.

3 BUILD exercises
Part VII

Market Microstructure

CH. XXI

Market Structure and Liquidity

Order type analysis and venue selection. Liquidity measurement with bid-ask spread decomposition. Market impact estimation.

3 BUILD exercises orderbook_data.csv
CH. XXII

Transaction Cost Analysis

Implementation shortfall computation. Slippage attribution by component. Execution algorithm benchmarking against arrival price.

2 BUILD exercises execution_data.csv
CH. XXIII

Algorithmic Trading

VWAP and TWAP algorithm implementation. Optimal execution with Almgren-Chriss framework. Participation rate strategies.

3 BUILD exercises trade_data.csv
Part VIII

Risk and Execution

CH. XXIV

Enterprise Risk Management

VaR and CVaR computation with historical and parametric methods. Stress testing framework. Regulatory capital calculations.

4 BUILD exercises risk_factors.csv
CH. XXV

Alternative Investments

Private equity return modeling with J-curve effects. Hedge fund replication strategies. Real asset valuation with illiquidity adjustments.

3 BUILD exercises pe_returns.csv
CH. XXVI

Behavioral Finance

Cognitive bias detection in trading patterns. Market anomaly analysis. Decision architecture design for institutional governance.

2 BUILD exercises
CH. XXVII

Volume II Capstone

Full system case study integrating strategy, hedging, and execution. End-to-end workflow from deal analysis to position management.

6 BUILD exercises capstone_full.csv

Technical Requirements

Python Environment

  • Python 3.10+
  • numpy, pandas, scipy
  • matplotlib, plotly
  • statsmodels, sklearn

Derivatives Libraries

  • QuantLib-Python
  • py_vollib
  • mibian
  • arch (GARCH models)

Decision Lab Access

  • Professional tier or higher
  • Hosted Jupyter workspace
  • Preloaded datasets
  • GPU compute available