Pricing of European options in incomplete jump diffusion markets

TL;DR

This paper develops a stochastic control approach to explicitly compute minimal variance option prices in incomplete markets with jump diffusions, extending previous theoretical work with practical formulas and examples.

Contribution

It introduces a method using stochastic control and Stackelberg games to explicitly determine minimal variance prices in jump diffusion markets, including deterministic and general cases.

Findings

Explicit formulas for minimal variance prices in deterministic coefficient cases.

Representation of prices as expectations under specific equivalent martingale measures.

Application of stochastic maximum principle to relate prices to Hamiltonian and adjoint processes.

Abstract

We study option prices in financial markets where the risky asset prices are modelled by jump diffusions. It was proposed by Schweizer (1996) in a general semimartingale setting, following earlier works by F\"ollmer and Sondermann (1986) and Bouleau and Lamberton (1989), that the right price of such an option is the initial wealth needed to make it possible to generate by a self-financing portfolio a terminal wealth which is as close as possible to the payoff F in the sense of variance. Schweizer calls this price the approximation price and he investigates interesting general properties of this price and its corresponding optimal portfolio. -However, neither of these authors compute explicitly this price in concrete cases. This is the motivation for the current paper: We apply stochastic control methods to compute this price in the setting of markets with assets described by jump diffusions. Our method involves Stackelberg games and a suitably modified stochastic maximum principle. We show that such an optimal initial wealth, denoted by z^, with corresponding optimal portfolio {\pi}^ exist and are unique. - If the coefficients of the risky asset prices are deterministic, we show that z^=E_{Q*}[F], for a specific equivalent martingale measure (EMM) Q*. This shows in particular that the minimal variance price is free from arbitrage. -Then for the general case we apply a suitable maximum principle of optimal stochastic control to relate the minimal variance price z^=p_{mv}(F) to the Hamiltonian and its adjoint processes, and we show that, under some conditions, z^=E_{Q_0}[F] for any Q_0 in a family M_0 of EMMs, described by the set of solutions of a system of linear equations. -Finally, we illustrate our results by looking at specific examples.