Listed Volatility and Variance Derivatives

A Python-based Guide

What others say.

In Academia

“Volatility derivatives are a class of derivative securities where the payoff explicitly depends on some measure of the volatility of an underlying asset. Prominent examples of these derivatives include variance swaps and VIX futures and options” Peter Carr and Roger Lee (2009) — Volatility Derivatives, Annual Review of Financial Economics.

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About the author

Yves Hilpisch is founder and CEO of The Python Quants (cf. https://home.tpq.io) and The AI Machine. The group focuses on Open Source technologies for Financial Data Science, Algorithmic Trading and Computational Finance. It also provides data, financial and derivatives analytics software (cf. Quant Platform and DX Analytics) as well as consulting services and Python for Finance trainings. Yves is also author of the books Python for Finance — Mastering Data-Driven Finance (2nd ed., O’Reilly, 2018) and Derivatives Analytics with Python (Wiley, 2015).

As a graduate in Business Administration with a Dr.rer.pol. in Mathematical Finance, he lectures on Computational Finance at the CQF Program and is Adjunct Professor of Computational Finance at Miami Business School. Yves is also the director of the first University Certificate Programs in Python for Algorithmic Trading and Computational Finance.

Furthermore, Yves organizes Python & Open Source for Quant Finance meetups and events in Frankfurt (cf. Open Source in Quant Finance), London (cf. Python for Quant Finance) and New York (cf.  For Python Quants).

Quant Platform

All Python codes (scripts, modules, etc.) as well as complementary Jupyter Notebooks for immediate execution will be made available on the Quant Platform. No installation necessary, just an easy and quick registration necessary under

Github Repository

All Jupyter Notebooks and all Python code files for easy cloning and local usage are available on Github. Make sure to have a comprehensive scientific Python installation (2.7.x) ready.

DX Analytics

DX Analytics is a purely Python-based derivatives and risk analytics library which implements all models and approaches presented in the book (e.g. stochastic volatility & jump-diffusion models, Fourier-based option pricing, least-squares Monte Carlo simulation, numerical Greeks) on the basis of a unified API.

Our Training

We are offering Python for Finance online training classes — leading to a University Certification — about Financial Data Science, Algorithmic Trading and Computational Finance. In addition, we also offer customized corporate training classes. See https://home.tpq.io/training or just get in touch below.

Get & Keep in Touch

DR YVES J HILPISCH

Write me under lvvd@tpq.io. Stay informed about the latest in Open Source for Quant Finance by signing up below.

The Experts in Data-Driven and AI-First Finance with Python. We focus on Python and Open Source Technologies for Financial Data Science, Artificial Intelligence, Algorithmic Trading and Computational Finance.

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