Logo do repositório
 
Publicação

A new technique for simulating the likelihood of stochastic differential equations

dc.contributor.authorNicolau, João
dc.date.accessioned2023-04-06T13:09:37Z
dc.date.available2023-04-06T13:09:37Z
dc.date.issued2002
dc.description.abstractThis article presents a new simulation-based technique for estimating the likelihood of stochastic differential equations. This technique is based on a result of Dacunha-Castelle and Florens-Zmirou. These authors proved that the transition densities of a nonlinear diffusion process with a constant diffusion coefficient can be written in a closed form involving a stochastic integral. We show that this stochastic integral can be easily estimated through simulations and we prove a convergence result. This simulator for the transition density is used to obtain the simulated maximum likelihood (SML) estimator. We show through some Monte Carlo experiments that our technique is highly computationally efficient and the SML estimator converges rapidly to the maximum likelihood estimatorpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationNicolau, João .(2002). “A new technique for simulating the likelihood of stochastic differential equations”. Econometrics Journal, Volume 5: pp. 91–103. (Search PDF in 2023)pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/27596
dc.language.isoengpt_PT
dc.publisherRoyal Economic Society | Blackwell Publishers Ltd.pt_PT
dc.subjectSimulated Maximum Likelihood Estimatorpt_PT
dc.subjectSimulation-based Methodpt_PT
dc.subjectEstimationpt_PT
dc.subjectStochastic Differential Equationspt_PT
dc.subjectTransition Density Estimationpt_PT
dc.subjectDiffusion Processespt_PT
dc.titleA new technique for simulating the likelihood of stochastic differential equationspt_PT
dc.typejournal article
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

Ficheiros

Principais
A mostrar 1 - 1 de 1
A carregar...
Miniatura
Nome:
JNICOLAU.2002..pdf
Tamanho:
176.5 KB
Formato:
Adobe Portable Document Format
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição: