Option pricing model based on a Markov-modulated diffusion with jumps

The paper proposes a class of financial market models which are based on inhomogeneous telegraph processes and jump diffusions with alternating volatilities. It is assumed that the jumps occur when the tendencies and volatilities are switching. Such a model captures well the stock price dynamics under periodic financial cycles. The distribution of this process is described in detail.We also provide a closed form of the structure of risk-neutral measures. This incomplete model can be completed by adding another asset based on the same sources of randomness. For completed market model we obtain explicit formulae for call prices. © 2010, Brazilian Statistical Association. All rights reserved

Random motions in inhomogeneous media

Space inhomogeneous random motions of particles on the line and in the plane are considered in the paper. The changes of the movement direction are driven by a Poisson process. The particles are assumed to move according to a finite velocity field that depends on a spatial argument. The explicit distribution of particles is obtained in the paper for the case of dimension 1 in terms of characteristics of the governing equations. In the case of dimension 2, the distribution is obtained if a rectifying diffeomorphism exists. © 2008 American Mathematical Society

Piecewise deterministic processes following two alternating patterns

We propose a wide generalization of known results related to the telegraph process. Functionals of the simple telegraph process on a straight line and their generalizations on an arbitrary state space are studied. © Applied Probability Trust 2019

Piecewise linear process with renewal starting points

This paper concerns a Markovian piecewise linear process, based on a continuous-time Markov chain with a finite state space. The process describes the movement of a particle that takes a new linear trend starting from a new random point (with state-dependent distribution) after each trend switch. The distribution of particle's position is derived in a closed form. In some special cases the distributions of the level passage times are provided explicitly. © 2017 Elsevier B.V

Option pricing model based on a Markov-modulated diffusion with jumps

The paper proposes a class of financial market models which are based on inhomogeneous telegraph processes and jump diffusions with alternating volatilities. It is assumed that the jumps occur when the tendencies and volatilities are switching. Such a model captures well the stock price dynamics under periodic financial cycles. The distribution of this process is described in detail.We also provide a closed form of the structure of risk-neutral measures. This incomplete model can be completed by adding another asset based on the same sources of randomness. For completed market model we obtain explicit formulae for call prices. © 2010, Brazilian Statistical Association. All rights reserved

Option Pricing Under Jump-Diffusion Processes with Regime Switching

We study an incomplete market model, based on jump-diffusion processes with parameters that are switched at random times. The set of equivalent martingale measures is determined. An analogue of the fundamental equation for the option price is derived. In the case of the two-state hidden Markov process we obtain explicit formulae for the option prices. Furthermore, we numerically compare the results corresponding to different equivalent martingale measures. © 2015, Springer Science+Business Media New York

Option Pricing Under Jump-Diffusion Processes with Regime Switching

We study an incomplete market model, based on jump-diffusion processes with parameters that are switched at random times. The set of equivalent martingale measures is determined. An analogue of the fundamental equation for the option price is derived. In the case of the two-state hidden Markov process we obtain explicit formulae for the option prices. Furthermore, we numerically compare the results corresponding to different equivalent martingale measures. © 2015, Springer Science+Business Media New York

Random motions in inhomogeneous media

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Piecewise linear process with renewal starting points

This paper concerns a Markovian piecewise linear process, based on a continuous-time Markov chain with a finite state space. The process describes the movement of a particle that takes a new linear trend starting from a new random point (with state-dependent distribution) after each trend switch. The distribution of particle's position is derived in a closed form. In some special cases the distributions of the level passage times are provided explicitly. © 2017 Elsevier B.V