AbstractWe investigate which type of diffusion equation is most appropriate to describe the time evolution of foreign exchange rates. We modify the geometric diffusion model assuming a non-exponential time evolution and the stochastic term is the sum of a Wiener noise and a jump process. We find the resulting diffusion equation to obey the Kramers–Moyal equation. Analytical solutions are obtained using the characteristic function formalism and compared with empirical data. The analysis focus on the first four central moments considering the returns of foreign exchange rate. It is shown that the proposed model offers a good improvement over the classical geometric diffusion model
This thesis aims to study a new Levy-driven diffusion process, where the random innovations that und...
Arguably the most important problem in quantitative finance is to understand the nature of stochasti...
This thesis investigates the stochastic properties of high frequency foreign exchange data. We study...
AbstractWe investigate which type of diffusion equation is most appropriate to describe the time evo...
AbstractThe rates of exchange between r continuously traded currencies are modelled by a diffusion p...
Diffusion processes are widely used for mathematical modeling in finance e.g. in modeling foreign ex...
This text presents a study of various models based on jump processes in the context of foreign exch...
In this study, a multi-country nonlinear model with jump diffusion process is constructed to simulta...
The main objective of this thesis has been to develop an analysis of the dynamics of exchange rates ...
This paper investigates asymmetric effects of monetary policy over the business cycle. A two-state M...
We investigate the consistency under inversion of jump diffusion processes in the foreign exchange m...
The performance of the well-known stochastic processes used for the empirical distribution of the ex...
We propose a general continuous time bivariate jump-diffusion representation for the exchange rates ...
For over a hundred years, diffusion differential equations have been used to model the changes in as...
Modified Cox-Ingersoll-Ross model is employed, combining with Hamilton (1989) type Markov regime swi...
This thesis aims to study a new Levy-driven diffusion process, where the random innovations that und...
Arguably the most important problem in quantitative finance is to understand the nature of stochasti...
This thesis investigates the stochastic properties of high frequency foreign exchange data. We study...
AbstractWe investigate which type of diffusion equation is most appropriate to describe the time evo...
AbstractThe rates of exchange between r continuously traded currencies are modelled by a diffusion p...
Diffusion processes are widely used for mathematical modeling in finance e.g. in modeling foreign ex...
This text presents a study of various models based on jump processes in the context of foreign exch...
In this study, a multi-country nonlinear model with jump diffusion process is constructed to simulta...
The main objective of this thesis has been to develop an analysis of the dynamics of exchange rates ...
This paper investigates asymmetric effects of monetary policy over the business cycle. A two-state M...
We investigate the consistency under inversion of jump diffusion processes in the foreign exchange m...
The performance of the well-known stochastic processes used for the empirical distribution of the ex...
We propose a general continuous time bivariate jump-diffusion representation for the exchange rates ...
For over a hundred years, diffusion differential equations have been used to model the changes in as...
Modified Cox-Ingersoll-Ross model is employed, combining with Hamilton (1989) type Markov regime swi...
This thesis aims to study a new Levy-driven diffusion process, where the random innovations that und...
Arguably the most important problem in quantitative finance is to understand the nature of stochasti...
This thesis investigates the stochastic properties of high frequency foreign exchange data. We study...