Cliquet option pricing in a jump-diffusion L\'{e}vy model

TL;DR

This paper develops semi-analytic methods for pricing cliquet options within a jump-diffusion Lévy model, incorporating density and Fourier techniques, and analyzes sensitivities like Vega for hedging.

Contribution

It introduces two novel semi-analytic approaches for cliquet option pricing in a jump-diffusion Lévy framework, including density and Fourier transform methods.

Findings

Derived semi-analytic pricing formulas for cliquet options.

Provided representations for Greeks, especially Vega, for hedging.

Compared two approaches: distribution function and Fourier transform.

Abstract

We investigate the pricing of cliquet options in a jump-diffusion model. The considered option is of monthly sum cap style while the underlying stock price model is driven by a drifted L\'{e}vy process entailing a Brownian diffusion component as well as compound Poisson jumps. We also derive representations for the density and distribution function of the emerging L\'{e}vy process. In this setting, we infer semi-analytic expressions for the cliquet option price by two different approaches. The first one involves the probability distribution function of the driving L\'{e}vy process whereas the second draws upon Fourier transform techniques. With view on sensitivity analysis and hedging purposes, we eventually deduce representations for several Greeks while putting emphasis on the Vega.