Skip to content

A python implementation of the fast-reversion Heston model of Mechkov [2015, https://goo.gl/2awbrV], for FX purposes.

License

Notifications You must be signed in to change notification settings

ryanmccrickerd/frh-fx

Repository files navigation

Fast-reversion Heston FX

This repo contains code for the fast-reversion Heston (FRH) model of Mechkov, 2015, which is a reparameterisation of the normal-inverse Gaussian (NIG) process, studied greatly by Barndorff-Nielsen, among others. In particular, one can produce implied volatility surfaces analytically (fourier transform), and verify them by simulation.

The key contribution here is an implementation of a simple dependence structure between multiple FRH models, as well as the measure change analytics required to consistently evaluate inverse and cross process. We provide a very simple simulation procedure, amenable to quasi-random sampling, and expose some very interesting volatility surface symmetries exhibited by this model.

Cross symmetry:

Sample paths:

Delta symmetry:

Market comparison:

Example jupyter notebooks are included which demonstrate usage. Tested with Python 3.5.2 and macOS Sierra 10.12.5.