Wiley.com

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

ISBN: 978-1-119-03799-6
374 pages
August 2015
US $100.00 Add to Cart

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Business & Finance


July 14, 2015
UK

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

Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. A new book, Derivatives Analytics with Python provides finance professionals with a guide to exploiting Python's capabilities for efficient and performing derivatives analytics. This is the first book that offers a detailed explanation of both the theory and all numerical methods and processes to implement a market-consistent valuation of stock index options, including advanced models, simulation, calibration and hedging.

Topics covered in the book include: Stylised facts of equity and options markets, risk-neutral valuation, Fourier transform methods, Monte Carlo simulation, model calibration, valuation and dynamic hedging. The financial models introduced in the book exhibit features like stochastic volatility, jump components and stochastic short rates.

The book’s approach is practical and important aspects are illustrated by a set of self-contained Python scripts. The companion website features all code and IPython Notebooks for immediate execution and automation.