Pricing of options on stocks driven by multi-dimensional operator stable Levy processes
Przemyslaw Repetowicz, Peter Richmond

TL;DR
This paper develops a novel model for stock prices driven by multi-dimensional operator stable Levy processes, deriving exact Fourier transform relations and analyzing option pricing within this framework.
Contribution
It introduces a generalized operator stable Levy process model with compound Poisson fluctuations for stock prices, extending previous models and deriving new Fourier transform relations for pricing.
Findings
Derived exact Fourier transform relations for jump intensities.
Established conditions for zero-mean portfolio deviations.
Proposed a functional equation for option prices ensuring no arbitrage.
Abstract
We model the price of a stock via a Lang\'{e}vin equation with multi-dimensional fluctuations coupled in the price and in time. We generalize previous models in that we assume that the fluctuations conditioned on the time step are compound Poisson processes with operator stable jump intensities. We derive exact relations for Fourier transforms of the jump intensity in case of different scaling indices of the process. We express the Fourier transform of the joint probability density of the process to attain given values at several different times and to attain a given maximal value in a given time period through Fourier transforms of the jump intensity. Then we consider a portfolio composed of stocks and of options on stocks and we derive the Fourier transform of a random variable (deviation of the portfolio) that is defined as a small…
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Taxonomy
TopicsStochastic processes and financial applications · Complex Systems and Time Series Analysis · Financial Risk and Volatility Modeling
