Listed Volatility and Variance Derivatives: A Python-based Guide (Wiley Finance) 1st Edition

by Yves Hilpisch (Author)

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ISBN-13: 978-1119167914

ISBN-10: 1119167914

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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, and has the distinction of being both the first to cover European volatility and variance products provided by Eurex and the first to offer Python code for implementing comprehensive quantitative analyses of these financial products. For those who want to get started right away, the book is accompanied by a dedicated Web page and a Github repository that includes all the code from the book for easy replication and use, as well as a hosted version of all the code for immediate execution.

Python is fast making inroads into financial modelling and derivatives analytics, and recent developments allow Python to be as fast as pure C++ or C while consisting generally of only 10% of the code lines associated with the compiled languages. This complete guide offers rare insight into the use of Python to undertake complex quantitative analyses of listed volatility and variance derivatives.

Learn how to use Python for data and financial analysis, and reproduce stylised facts on volatility and variance markets
Gain an understanding of the fundamental techniques of modelling volatility and variance and the model-free replication of variance
Familiarise yourself with micro structure elements of the markets for listed volatility and variance derivatives
Reproduce all results and graphics with IPython/Jupyter Notebooks and Python codes that accompany the book

Listed Volatility and Variance Derivatives is the complete guide to Python-based quantitative analysis of these Eurex derivatives products.

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Editorial Reviews

From the Inside Flap

Python in general requires much less code than other languages, like C++ or C#, to accomplish the same goal. Because of this and also due to its powerful ecosystem of libraries, it has become one of the most widely used programming languages and technology platforms in the financial industry. Listed Volatility and Variance Derivatives is your Python-based A-to-Z guide to the most important listed volatility and variance derivatives provided by Eurex.

This complete guide is the first of its kind to offer practical, expert insight into how industry leaders use Python to undertake complex quantitative analysis in the field. From understanding the fundamental techniques of modeling to reproducing your own results and graphics with Jupyter Notebooks, this single resource gives you everything you need to use this powerful language to support portfolio, trading and risk management functions.

Enhance and streamline your quantitative analysis with Listed Volatility and Variance Derivatives.

From the Back Cover

Robust Analytics for Trading Listed Volatility and Variance Derivatives

Whether you're new to programming or want to step up from C++, C# or Matlab, Listed Volatility and Variance Derivatives jumpstarts you on a faster, more powerful way to execute quantitative analysis to trade listed volatility and variance products. No other resource offers indepth coverage on European products provided by Eurex along with step-by-step explanations of the Python codes you need to gain an edge in this competitive space.

Complete with an accompanying website allowing you to download all the code inside, you can easily and immediately execute the covered techniques for:

Using Python to analyze data and financials and reproduce stylized facts on volatility and variance markets.
Modeling volatility and variance and replicating variance in a model-free fashion.
Navigating the micro-structure elements of the markets for listed volatility and variance derivatives.

The Python ecosystem thrives in the most demanding financial environments, and Listed Volatility and Variance Derivatives is the only guidebook for using it to master this analytics space.

Start reading Listed Volatility and Variance Derivatives on your Kindle in under a minute.

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Product details

Publisher ‏ : ‎ Wiley; 1st edition (December 27, 2016)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 368 pages
ISBN-10 ‏ : ‎ 1119167914
ISBN-13 ‏ : ‎ 978-1119167914
Item Weight ‏ : ‎ 1.75 pounds
Dimensions ‏ : ‎ 6.9 x 1.1 x 9.7 inches

Best Sellers Rank: #1,624,358 in Books (See Top 100 in Books)
- #192 in Derivatives Investments
- #1,487 in Business Finance
- #1,840 in Python Programming

Customer Reviews:
3 ratings

About the author

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Yves J. Hilpisch

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Dr. Yves J. Hilpisch is founder and CEO of The Python Quants (http://tpq.io), a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading, and computational finance. He is also the founder and CEO of The AI Machine (http://aimachine.io), a company focused on AI-powered algorithmic trading based on a proprietary strategy execution platform.

Yves has a Diploma in Business Administration, a Ph.D. in Mathematical Finance and is Adjunct Professor for Computational Finance.

Yves is the author of five books (https://home.tpq.io/books):

* Artificial Intelligence in Finance (O’Reilly, forthcoming)

* Python for Algorithmic Trading (O’Reilly, forthcoming)

* Python for Finance (2018, 2nd ed., O’Reilly)

* Listed Volatility and Variance Derivatives (2017, Wiley Finance)

* Derivatives Analytics with Python (2015, Wiley Finance)

Yves is the director of the first online training program leading to University Certificates in Python for Algorithmic Trading (https://home.tpq.io/certificates/pyalgo) and Computational Finance (https://home.tpq.io/certificates/compfin). He also lectures on computational finance, machine learning, and algorithmic trading at the CQF Program (http://cqf.com).

Yves is the originator of the financial analytics library DX Analytics (http://dx-analytics.com) and organizes Meetup group events, conferences, and bootcamps about Python, artificial intelligence and algorithmic trading in London (http://pqf.tpq.io), New York (http://aifat.tpq.io), Frankfurt, Berlin, and Paris. He has given keynote speeches at technology conferences in the United States, Europe, and Asia.

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Cary

For true Pythonistas wanting to jump inside quant finance

Reviewed in the United States on December 22, 2016

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I've had many discussions with Yves and followed his trajectory over the past few years. He is basically a full time professor with a side job as a leading expert in Python for quantitative finance who travels around the world consulting WS and educationally paving the way for any kid who dreams of not just being a Quant, but a new, cutting-edge type of one. For myself having spent most of my career in volatility, he is an invaluable resource. Be warned though this is the third book in his Python quant collection and for most people they'll be better off starting with his first two works.

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