We introduce nonlinear panel data models for individual risl management and control. Our approach extends traditional models by allowing for nonlinearities in input variables and unobserved individual heterogeneity with possible temporal dependence. This permits us to develop nonlineat models...

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...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high frequency data on stock returns.