This repository complements my master's thesis on introduction to Lévy processes with applications in finance.
It serves as a guide to see how to implement almost from scratch, model selection and valuation of European options using Lévy exponential models. Lewis Fourier transform method and Monte Carlo are used.
The code is free of usage, but the author does not take responsibility for its use in practice since there may be some minor bugs.
For a more advance topics and a complete work in the same lines see https://github.com/cantaro86/Financial-Models-Numerical-Methods.
- utils.py : Lewis Fourier transform method and functions for the payoffs
- mertonPricer: Class for model fitting and option valuation using Merton’s model
- alPhaStablePricer.py : Class for model fitting and option valuation using alpha stable model
- ghPricer.py : Class for model fitting and option valuation using generalized hyperbolic model (It contains some bugs. Although the fit part seems to be fine, in option valuation unexpected results are seen!)
- TFM_INAKI.ipynb : Notebook with the graphs and some results shown in the work
- Tests.ipynb : Notebook with tests for Merton and alpha stable
- Goodness of fit.ipynb : Notebook with alpha stable Kolmogorov–Smirnov test and q-q plot
[1] R Cont and P Tankov.Financial Modelling with Jump Processes. Chapman & Hall/CRC,2003.
[2] Alan L. Lewis. A Simple Option Formula for General Jump-Diffusion and otherExponential Levy Processes. Related articles explevy, Finance Press, August 2001.
- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request 👍
Author: Iñaki Gorostiaga ([email protected])
The MIT License (MIT)
Copyright (c) 2021 Iñaki Gorostiaga
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