The Heston Model for Option Pricing

This quantitative finance training course is on the Heston model, one of the most popular stochastic volatility model for the pricing of options.

The model assumes that the variance of the asset price is stochastic, it is correlated with the asset price and follows a mean-reverting process. With its five parameters, the model allows to reproduce a large number of volatility surfaces. We will discuss how the different parameters impact the return distribution and the shape of the volatility curves.

One strong advantage of the model is that despite its relative complexity, there is a semi-analytic solution for the price of european vanilla options which is useful for the calibration to market prices. We will look at it through a concrete application in Python.

We will discuss the advantages and disadvantages of the model and we will see how the Heston model can be used to price exotic options.

We will finish the training with a tutorial in Python, applying the model to price path-dependent options with Monte-Carlo simulations and path-independent ones by numerical integration with Fast Fourier Transform.

The course is composed of many videos, quizzes, applications in Python.

A certificate of achievements will be delivered once the course has been completed with success.