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Publikācija: Copula Estimation for GARCH(1

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Nosaukums oriģinālvalodā Copula Estimation for GARCH(1, 1) Processes
Pētniecības nozare 1. Dabaszinātnes
Pētniecības apakšnozare 1.1. Matemātika
Autori Andrejs Matvejevs
Jegors Fjodorovs
Atslēgas vārdi copula, diffusion processes, time series, semi parametric regressions
Anotācija The possibility of identifying nonlinear time series using nonparametric estimates of the conditional mean and conditional variance were studied in many papers. One of the main problems in these papers is development of time series {x(t)} methods of analysis through regression models even without knowing the regression function. The article deals with the estimation of copula-based semi parametric models for GARCH (1, 1) processes with usual kind of information about the distribution law. These models are characterized by conditional heteroscedasticity and have been often used in modeling the variability of statistical data. The basic idea is applied to a local linear regression with squared residuals for finding the unknown function.
Hipersaite: http://www.proceedings.com/22213.html 
Atsauce Matvejevs, A., Fjodorovs, J. Copula Estimation for GARCH(1, 1) Processes. No: Proceeding of the 12th International Conference APLIMAT’ 2013, Slovākija, Bratislava, 5.-7. februāris, 2013. Bratislava: Slovak University of Technology in Bratislava, 2013, 230.-236.lpp. ISBN 978-1-63266-512-6.
Papildinformācija Citējamību skaits:
  • Scopus  0
ID 19001