The Jacobi Stochastic Volatility Model

Damien Ackerer (1, 2) , Damir Filipovic (1, 2) , Sergio Pulido (3, 4)

1 EPFL - Ecole Polytechnique Fédérale de Lausanne
2 Swiss Finance Institute [Lausanne]
3 LaMME - Laboratoire de Mathématiques et Modélisation d'Evry
4 ENSIIE - Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise

We introduce a novel stochastic volatility model where the squared volatility of the asset return follows a Jacobi process. It contains the Heston model as a limit case. We show that the the joint distribution of any finite sequence of log returns admits a Gram-Charlier A expansion in closed-form. We use this to derive closed-form series representations for option prices whose payoff is a function of the underlying asset price trajectory at finitely many time points. This includes European call, put, and digital options, forward start options, and forward start options on the underlying return. We derive sharp analytical and numerical bounds on the series truncation errors. We illustrate the performance by numerical examples, which show that our approach offers a viable alternative to Fourier transform techniques.

Keywords: Jacobi process; option pricing; polynomial model; stochastic volatility

Domains: Computational Finance [q-fin.CP]; Pricing of Securities [q-fin.PR]; Probability [math.PR]

Damien Ackerer, Damir Filipovic, Sergio Pulido. The Jacobi Stochastic Volatility Model. 2016. ⟨hal-01338330v1⟩