Listed Volatility and Variance Derivatives: A Python-based Guide

By Yves Hilpisch

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.

• Language: English
• Publisher: Wiley
• Release date: Oct 25, 2016
• ISBN: 9781119167921

Yves Hilpisch

Dr. Yves J. Hilpisch is the founder and CEO of The Python Quants (http://home.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.