论文信息 - Derivation of a State-Space Model by Functional Data Analysis

Derivation of a State-Space Model by Functional Data Analysis

SummaryBy approximating a stochastic process by means of spline interpolation of its sample-paths, a time dependent state-space model is introduced. Then we derive the expression of the associated transition matrix that allows to obtain a discrete model useful in applications. In order to essay the behaviour of the proposed models simulations on a narrow-band process are developed. Finally, the paper includes an application with real data obtained from the Stock Market of Madrid.

Ana M. Aguilera | Mariano J. Valderrama | Mónica Ortega-Moreno | Pedro González

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