In this PhD. Thesis we focus on diffusion models. Diffusions are very attractive and widely applied in many scientific areas, since they provide a useful mathematical tool: the stochastic calculus. Let us think, for instance, to the Finance area. A large class of financial models use both diffusion processes and the stochastic calculus machinery, in order to price financial derivatives or to solve stochastic optimization problems. Thus convinced that diffusions are very important and useful for modeling natural and financial phenomena, we will focus our attention on their statistical analysis. In particular, the main goal of this Thesis will be the definition of a specific robust method, to make parametric inference for the drift and the di...
Data available on continuos-time diffusions are always sampled discretely in time. In most cases, th...
Data available on continuous-time diffusions are always sampled discretely in time. In most cases, t...
The topic of the thesis is statistical inference from diffusion driven models. The the-ory of estima...
In this PhD. Thesis we focus on diffusion models. Diffusions are very attractive and widely applied ...
: A new type of martingale estimating function is proposed for inference about classes of diffusion ...
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
A review is given of parametric estimation methods for discretely sampled mul- tivariate diffusion p...
© Springer-Verlag Berlin Heidelberg 2013. All rights are reserved. Diffusion processes are a pr...
We develop infinitesimally robust statistical procedures for general diffusion processes. We first p...
We develop infinitesimally robust statistical procedures for the general diffusion processes. We fir...
We develop infinitesimally robust statistical procedures for the general diffusion processes. We fir...
We develop infinitesimally robust statistical procedures for general diffusion processes. We first p...
This thesis consists of five papers (Paper A-E) on statistical modeling of diffusion processes. Two ...
The methodological framework developed and reviewed in this article concerns the unbiased Monte Car...
Data available on continuos-time diffusions are always sampled discretely in time. In most cases, th...
Data available on continuous-time diffusions are always sampled discretely in time. In most cases, t...
The topic of the thesis is statistical inference from diffusion driven models. The the-ory of estima...
In this PhD. Thesis we focus on diffusion models. Diffusions are very attractive and widely applied ...
: A new type of martingale estimating function is proposed for inference about classes of diffusion ...
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
A review is given of parametric estimation methods for discretely sampled mul- tivariate diffusion p...
© Springer-Verlag Berlin Heidelberg 2013. All rights are reserved. Diffusion processes are a pr...
We develop infinitesimally robust statistical procedures for general diffusion processes. We first p...
We develop infinitesimally robust statistical procedures for the general diffusion processes. We fir...
We develop infinitesimally robust statistical procedures for the general diffusion processes. We fir...
We develop infinitesimally robust statistical procedures for general diffusion processes. We first p...
This thesis consists of five papers (Paper A-E) on statistical modeling of diffusion processes. Two ...
The methodological framework developed and reviewed in this article concerns the unbiased Monte Car...
Data available on continuos-time diffusions are always sampled discretely in time. In most cases, th...
Data available on continuous-time diffusions are always sampled discretely in time. In most cases, t...
The topic of the thesis is statistical inference from diffusion driven models. The the-ory of estima...