Derivatives Analytics with Python

Derivatives Analytics with Python Front Cover
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376 pages

Book Description

Derivatives Analytics with Python: Data , , Simulation, Calibration and Hedging (The Wiley Finance Series)

Supercharge options analytics and hedging using the power of Python Derivatives Analytics with Python shows you how to implement market-consistent valuation and hedging approaches using advanced models, efficient numerical techniques, and the powerful capabilities of the Python language. This unique guide offers detailed explanations of all theory, methods, and processes, giving you the background and tools necessary to value stock index options from a sound foundation. You'll find and use self-contained Python scripts and modules and learn how to apply Python to advanced data and derivatives analytics as you benefit from the 5,000+ lines of code that are provided to help you reproduce the results and graphics presented. Coverage includes market , risk-neutral valuation, Monte Carlo simulation, model calibration, valuation, and dynamic hedging, with models that exhibit stochastic volatility, jump components, stochastic short rates, and more. The companion website features all code and IPython Notebooks for immediate execution and automation. Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. This book is the finance professional's guide to exploiting Python's capabilities for efficient and performing derivatives analytics. * Reproduce major stylized facts of equity and options markets yourself * Apply Fourier transform techniques and advanced Monte Carlo pricing * Calibrate advanced option pricing models to market data * Integrate advanced models and numeric methods to dynamically hedge options Recent developments in the Python ecosystem enable analysts to implement analytics tasks as performing as with C or C++, but using only about one-tenth of the code or even less. Derivatives Analytics with Python , Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts.

Table of Contents

Chapter 1. A Quick Tour

Part One The Market
Chapter 2. What is Market-Based Valuation?
Chapter 3. Market Stylized Facts

Part Two Theoretical Valuation
Chapter 4. Risk-Neutral Valuation
Chapter 5. Complete Market Models
Chapter 6. Fourier-Based Option Pricing
Chapter 7. Valuation of American Options by Simulation

Part Three Market-Based Valuation
Chapter 8. A First Example of Market-Based Valuation
Chapter 9. General Model
Chapter 10. Monte Carlo Simulation
Chapter 11. Model Calibration
Chapter 12. Simulation and Valuation in the General Model Framework
Chapter 13. Dynamic Hedging
Chapter 14. Executive Summary

Book Details

  • Title: Derivatives Analytics with Python
  • Author:
  • Length: 376 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2015-08-03
  • ISBN-10: 1119037999
  • ISBN-13: 9781119037996
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