Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging

Table of contents

1. Preface
2. Chapter 1: A Quick Tour
   1. 1.1 Market-Based Valuation
   2. 1.2 Structure of the Book
   3. 1.3 Why Python?
   4. 1.4 Further Reading
   5. Notes
3. Part One: The Market
   1. Chapter 2: What is Market-Based Valuation?
      1. 2.1 Options and their Value
      2. 2.2 Vanilla vs. Exotic Instruments
      3. 2.3 Risks Affecting Equity Derivatives
      4. 2.4 Hedging
      5. 2.5 Market-Based Valuation as a Process
      6. Notes
   2. Chapter 3: Market Stylized Facts
      1. 3.1 Introduction
      2. 3.2 Volatility, Correlation and Co.
      3. 3.3 Normal Returns as the Benchmark Case
      4. 3.4 Indices and Stocks
      5. 3.5 Option Markets
      6. 3.6 Short Rates
      7. 3.7 Conclusions
      8. 3.8 Python Scripts
      9. Notes
4. Part Two: Theoretical Valuation
   1. Chapter 4: Risk-Neutral Valuation
      1. 4.1 Introduction
      2. 4.2 Discrete-Time Uncertainty
      3. 4.3 Discrete Market Model
      4. 4.4 Central Results in Discrete Time
      5. 4.5 Continuous-Time Case
      6. 4.6 Conclusions
      7. 4.7 Proofs
      8. Notes
   2. Chapter 5: Complete Market Models
      1. 5.1 Introduction
      2. 5.2 Black-Scholes-Merton Model
      3. 5.3 Greeks in the BSM Model
      4. 5.4 Cox-Ross-Rubinstein Model
      5. 5.5 Conclusions
      6. 5.6 Proofs and Python Scripts
      7. Notes
   3. Chapter 6: Fourier-Based Option Pricing
      1. 6.1 Introduction
      2. 6.2 The Pricing Problem
      3. 6.3 Fourier Transforms
      4. 6.4 Fourier-Based Option Pricing
      5. 6.5 Numerical Evaluation
      6. 6.6 Applications
      7. 6.7 Conclusions
      8. 6.8 Python Scripts
   4. Chapter 7: Valuation of American Options by Simulation
      1. 7.1 Introduction
      2. 7.2 Financial Model
      3. 7.3 American Option Valuation
      4. 7.4 Numerical Results
      5. 7.5 Conclusions
      6. 7.6 Python Scripts
      7. Notes
5. Part Three: Market-Based Valuation
   1. Chapter 8: A First Example of Market-Based Valuation
      1. 8.1 Introduction
      2. 8.2 Market Model
      3. 8.3 Valuation
      4. 8.4 Calibration
      5. 8.5 Simulation
      6. 8.6 Conclusions
      7. 8.7 Python Scripts
      8. Notes
   2. Chapter 9: General Model Framework
      1. 9.1 Introduction
      2. 9.2 The Framework
      3. 9.3 Features of the Framework
      4. 9.4 Zero-Coupon Bond Valuation
      5. 9.5 European Option Valuation
      6. 9.6 Conclusions
      7. 9.7 Proofs and Python Scripts
      8. Note
   3. Chapter 10: Monte Carlo Simulation
      1. 10.1 Introduction
      2. 10.2 Valuation of Zero-Coupon Bonds
      3. 10.3 Valuation of European Options
      4. 10.4 Valuation of American Options
      5. 10.5 Conclusions
      6. 10.6 Python Scripts
      7. Notes
   4. Chapter 11: Model Calibration
      1. 11.1 Introduction
      2. 11.2 General Considerations
      3. 11.3 Calibration of Short Rate Component
      4. 11.4 Calibration of Equity Component
      5. 11.5 Conclusions
      6. 11.6 Python Scripts for Cox-Ingersoll-Ross Model
      7. Notes
   5. Chapter 12: Simulation and Valuation in the General Model Framework
      1. 12.1 Introduction
      2. 12.2 Simulation of BCC97 Model
      3. 12.3 Valuation of Equity Options
      4. 12.4 Conclusions
      5. 12.5 Python Scripts
      6. Notes
   6. Chapter 13: Dynamic Hedging
      1. 13.1 Introduction
      2. 13.2 Hedging Study for BSM Model
      3. 13.3 Hedging Study for BCC97 Model
      4. 13.4 Conclusions
      5. 13.5 Python Scripts
      6. Notes
   7. Chapter 14: Executive Summary
6. Appendix A: Python in a Nutshell
   1. A.1 Python Fundamentals
   2. A.2 European Option Pricing
   3. A.3 Selected Financial Topics
   4. A.4 Advanced Python Topics
   5. A.5 Rapid Financial Engineering
   6. Notes
7. Bibliography
8. Index
9. EULA