Interpretable Machine Learning with Python - Second Edition: Build explainable, fair, and robust high-performance models with hands-on, real-world examples

List of Business Snapshots List of Technical Notes 1. Introduction 2. Futures markets and central counterparties 3. Hedging strategies using futures 4. Interest rates 5. Determination of forward and futures prices 6. Interest rate futures 7. Swaps 8. Securitization and the financial crisis of 2007-8 9. XVAs 10. Mechanics of options markets 11. Properties of stock options 12. Trading strategies involving options 13. Binomial trees 14. Wiener processes and Itô's lemma 15. The Black–Scholes–Merton model 16. Employee stock options 17. Options on stock indices and currencies 18. Futures options and Black's model 19. The Greek letters 20. Volatility smiles and Volatility Surfaces 21. Basic numerical procedures 22. Value at risk and expected shortfall 23. Estimating volatilities and correlations 24. Credit risk 25. Credit derivatives 26. Exotic options 27. More on models and numerical procedures 28. Martingales and measures 29. Interest rate derivatives: The standard market models 30. Convexity, timing, and quanto adjustments 31. Equilibrium models of the short rate 32. No-arbitrage models of the short rate 33. Modeling Forward Rates 34. Swaps Revisited 35. Energy and commodity derivatives 36. Real options 37. Derivatives mishaps and what we can learn from them Glossary of terms DerivaGem software Major exchanges trading futures and options Tables for N x "A college textbook for courses in business, economics, financial mathematics and financial engineering. A reference book for practitioners in derivatives markets"-- Provided by publisher