Derivatives Analytics with Python

Data Analysis, Models, Simulation, Calibration and Hedging

Business & Finance, Finance & Investing, Investments & Securities
Cover of the book Derivatives Analytics with Python by Yves Hilpisch, Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Yves Hilpisch ISBN: 9781119038009
Publisher: Wiley Publication: June 15, 2015
Imprint: Wiley Language: English
Author: Yves Hilpisch
ISBN: 9781119038009
Publisher: Wiley
Publication: June 15, 2015
Imprint: Wiley
Language: English

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.

  • 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 — Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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 — Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts.

More books from Wiley

Cover of the book Breaking Into Acting For Dummies by Yves Hilpisch
Cover of the book Green Supply Chains by Yves Hilpisch
Cover of the book Atmospheric Chemistry and Physics by Yves Hilpisch
Cover of the book Spatial Politics by Yves Hilpisch
Cover of the book Managerial Decision Making Leadership by Yves Hilpisch
Cover of the book #EdJourney by Yves Hilpisch
Cover of the book Derrida by Yves Hilpisch
Cover of the book Leadership For Dummies by Yves Hilpisch
Cover of the book Advanced Silicon Materials for Photovoltaic Applications by Yves Hilpisch
Cover of the book Modern Aerodynamic Methods for Direct and Inverse Applications by Yves Hilpisch
Cover of the book Cetacean Paleobiology by Yves Hilpisch
Cover of the book Teaching the Common Core Math Standards with Hands-On Activities, Grades 9-12 by Yves Hilpisch
Cover of the book The Essential Guide to Becoming a Staff Nurse by Yves Hilpisch
Cover of the book Modal Testing by Yves Hilpisch
Cover of the book Inspired! by Yves Hilpisch
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy