Listed Volatility and Variance Derivatives
A Python-based Guide
What others say.
“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.
About the author
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).
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.
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.
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