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Estimation of Cointegrated Multivariate Continuous-Time Autoregressive Moving Average Processes

Scholz, Markus

Abstract (englisch):
In this thesis we consider cointegrated MCARMA processes. A canonical representation is derived and the probabilistic properties are investigated. A step-wise estimation method of the model parameters from discrete-time observations is derived. Super-consistency for long-run and consistency for short-run parameter estimator are established. The limiting distributions of the estimators are deduced. Lastly, a simulation study to demonstrate the applicability of the estimation method is presented.

Zugehörige Institution(en) am KIT Institut für Stochastik (STOCH)
Publikationstyp Hochschulschrift
Jahr 2016
Sprache Englisch
Identifikator DOI(KIT): 10.5445/IR/1000058237
URN: urn:nbn:de:swb:90-582375
KITopen ID: 1000058237
Verlag Karlsruhe
Umfang 228 S.
Abschlussart Dissertation
Fakultät Fakultät für Mathematik (MATH)
Institut Institut für Stochastik (STOCH)
Prüfungsdaten 22.06.2016
Referent/Betreuer Prof. V. Fasen-Hartmann
Schlagworte Cointegration, MCARMA, Estimation, Linear State Space Models
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