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

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Author Yves Hilpisch
Edition 1
Edition Year 2015
Format PDF
ISBN 9781119037996
Language English
Number Of Pages 374
Publisher Wiley

Description

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 financial models, efficient numerical techniques, and the powerful capabilities of the Python programming 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 data analysis, 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.

Additional information

Author

Yves Hilpisch

Edition

1

Edition Year

2015

Format

PDF

ISBN

9781119037996

Language

English

Number Of Pages

374

Publisher

Wiley

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