Kernel Based Nonlinear Canonical Analysis.

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce various diagnostics for reversible processes and gaussian processes. The method is first applied to a stimulated series satisfying a diffusion equation allowing us to estimate nonparametrically the drift and volatility functions. The second application involves high frequency data on stock returns.

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Year of publication:	1999
Authors:	Darolles, S. ; Florens, J.-P. ; Gourieroux, C.
Institutions:	Groupe de Recherche en Économie Mathématique et Quantitative (GREMAQ), Toulouse School of Economics (TSE)
Subject:	ECONOMETRICS \| REGRESSION ANALYSIS \| ECONOMIC MODELS

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Series:	Toulouse - GREMAQ.
Type of publication:	Book / Working Paper
Notes:	51 pages
Classification:	C14 - Semiparametric and Nonparametric Methods ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005639400