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Listed Volatility and Variance Derivatives : a Python-based Guide.
Leverage Python for expert-level volatility and variance derivative trading Listed Volatility and Variance Derivatives is a comprehensive treatment of all aspects of these increasingly popular derivatives products.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Somerset :
Wiley,
2016.
|
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Listed Volatility and Variance Derivatives; Contents; Preface; Part One Introduction to Volatility and Variance; Chapter 1 Derivatives, Volatility and Variance; 1.1 Option Pricing and Hedging; 1.2 Notions of Volatility and Variance; 1.3 Listed Volatility and Variance Derivatives; 1.3.1 The US History; 1.3.2 The European History; 1.3.3 Volatility of Volatility Indexes; 1.3.4 Products Covered in this Book; 1.4 Volatility and Variance Trading; 1.4.1 Volatility Trading; 1.4.2 Variance Trading; 1.5 Python as Our Tool of Choice; 1.6 Quick Guide Through the Rest of the Book.
- Chapter 2 Introduction to Python2.1 Python Basics; 2.1.1 Data Types; 2.1.2 Data Structures; 2.1.3 Control Structures; 2.1.4 Special Python Idioms; 2.2 NumPy; 2.3 matplotlib; 2.4 pandas; 2.4.1 pandas DataFrame class; 2.4.2 Input-Output Operations; 2.4.3 Financial Analytics Examples; 2.5 Conclusions; Chapter 3 Model-Free Replication of Variance; 3.1 Introduction; 3.2 Spanning with Options; 3.3 Log Contracts; 3.4 Static Replication of Realized Variance and Variance Swaps; 3.5 Constant Dollar Gamma Derivatives and Portfolios; 3.6 Practical Replication of Realized Variance.
- 3.7 VSTOXX as Volatility Index3.8 Conclusions; Part Two Listed Volatility Derivatives; Chapter 4 Data Analysis and Strategies; 4.1 Introduction; 4.2 Retrieving Base Data; 4.2.1 EURO STOXX 50 Data; 4.2.2 VSTOXX Data; 4.2.3 Combining the Data Sets; 4.2.4 Saving the Data; 4.3 Basic Data Analysis; 4.4 Correlation Analysis; 4.5 Constant Proportion Investment Strategies; 4.6 Conclusions; Chapter 5 VSTOXX Index; 5.1 Introduction; 5.2 Collecting Option Data; 5.3 Calculating the Sub-Indexes; 5.3.1 The Algorithm; 5.4 Calculating the VSTOXX Index; 5.5 Conclusions; 5.6 Python Scripts.
- 5.6.1 indexcollectoptiondata.py5.6.2 indexsubindexcalculation.py; 5.6.3 indexvstoxxcalculation.py; Chapter 6 Valuing Volatility Derivatives; 6.1 Introduction; 6.2 The Valuation Framework; 6.3 The Futures Pricing Formula; 6.4 The Option Pricing Formula; 6.5 Monte Carlo Simulation; 6.6 Automated Monte Carlo Tests; 6.6.1 The Automated Testing; 6.6.2 The Storage Functions; 6.6.3 The Results; 6.7 Model Calibration; 6.7.1 The Option Quotes; 6.7.2 The Calibration Procedure; 6.7.3 The Calibration Results; 6.8 Conclusions; 6.9 Python Scripts; 6.9.1 srdfunctions.py; 6.9.2 srdsimulationanalysis.py.
- 6.9.3 srdsimulationresults.py6.9.4 srdmodelcalibration.py; Chapter 7 Advanced Modeling of the VSTOXX Index; 7.1 Introduction; 7.2 Market Quotes for Call Options; 7.3 The SRJD Model; 7.4 Term Structure Calibration; 7.4.1 Futures Term Structure; 7.4.2 Shifted Volatility Process; 7.5 Option Valuation by Monte Carlo Simulation; 7.5.1 Monte Carlo Valuation; 7.5.2 Technical Implementation; 7.6 Model Calibration; 7.6.1 The Python Code; 7.6.2 Short Maturity; 7.6.3 Two Maturities; 7.6.4 Four Maturities; 7.6.5 All Maturities; 7.7 Conclusions; 7.8 Python Scripts; 7.8.1 srjdfwdcalibration.py.