Pricing and hedging of lookback options in hyper-exponential jump diffusion models
نویسندگان
چکیده
In this article we consider the problem of pricing lookback options in certain exponential Lévy market models. While in the classic Black-Scholes models the price of such options can be calculated in closed form, for more general asset price model one typically has to rely on (rather time-intense) MonteCarlo or P(I)DE methods. However, for Lévy processes with double exponentially distributed jumps the lookback option price can be expressed as one-dimensional Laplace transform (cf. Kou [Kou et al., 2005]). The key ingredient to derive this representation is the explicit availability of the first passage time distribution for this particular Lévy process, which is well-known also for the more general class of hyper-exponential jump diffusions (HEJD). In fact, Jeannin and Pistorius [Jeannin and Pistorius, 2010] were able to derive formulae for the Laplace transformed price of certain barrier options in market models described by HEJD processes. Here, we similarly derive the Laplace transforms of floating and fixed strike lookback option prices and propose a numerical inversion scheme, which allows, like Fourier inversion methods for European vanilla options, the calculation of lookback options with different strikes in one shot. Additionally, we give semi-analytical formulae for several Greeks of the option price and discuss a method of extending the proposed method to generalised hyperexponential (as e.g. NIG or CGMY) models by fitting a suitable HEJD process. Finally, we illustrate the theoretical findings by some numerical experiments.
منابع مشابه
Option Pricing Under a Mixed-Exponential Jump Diffusion Model
This paper aims at extending the analytical tractability of the Black-Scholes model to alternative models with arbitrary jump size distributions. More precisely, we propose a jump diffusion model for asset prices whose jump sizes have a mixed-exponential distribution, which is a weighted average of exponential distributions but with possibly negative weights. The new model extends existing mode...
متن کاملDouble-Exponential Fast Gauss Transform Algorithms for Pricing Discrete Lookback Options
This paper presents fast and accurate algorithms for computing the prices of discretely sampled lookback options. Under the Black-Scholes framework, the pricing of a discrete lookback option can be reduced to a series of convolutions of a function with the Gaussian distribution. Using this fact, an efficient algorithm, which computes these convolutions by a combination of the double-exponential...
متن کاملNumerical pricing of discrete barrier and lookback options via Laplace transforms
URL: www.thejournalofcomputationalfinance.com Most contracts of barrier and lookback options specify discrete monitoring policies. However, unlike their continuous counterparts, discrete barrier and lookback options essentially have no analytical solution. For a broad class of models, including the classical Brownian model and jump-diffusion models, we show that the Laplace transforms of discre...
متن کاملPricing and Hedging of Quantile Options in a Flexible Jump Diffusion Model
This paper proposes a Laplace-transform-based approach to price the fixed-strike quantile options as well as to calculate the associated hedging parameters (delta and gamma) under a hyperexponential jump diffusion model, which can be viewed as a generalization of the well-known Black–Scholes model and Kou’s double exponential jump diffusion model. By establishing a relationship between floating...
متن کاملJump-Diffusion Models for Asset Pricing in Financial Engineering
In this survey we shall focus on the following issues related to jump-diffusion models for asset pricing in financial engineering. (1) The controversy over tailweight of distributions. (2) Identifying a risk-neutral pricing measure by using the rational expectations equilibrium. (3) Using Laplace transforms to pricing options, including European call/put options, path-dependent options, such as...
متن کامل