Listed Volatility and Variance Derivatives

A Python-based Guide



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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 managing partner of The Python Quants Group (cf. http://tpq.io). 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 — Analyze Big Financial Data (O'Reilly, 2014) 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 on Data Science at the htw saar University of Applied Sciences.

Furthermore, Yves organizes Python & Open Source for Quant Finance meetups and conferences 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


http://lvvd.quant-platform.com


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

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

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 http://training.tpq.io or just get in touch below.

Get & Keep in Touch

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