A new method of estimating a component model for the analysis of financial durations is proposed. The components are long-run dynamics and seasonality. The latter is left unspecified and the former is assumed to fall within the class ofa certain family of parametric functions. The proposed...

In this paper, we investigate the methodological issue of determining the number of state variables required for options pricing. After showing the inadequacy of the principal component analysis approach, which is commonly used in the literature, we adopt a nonparametric regression technique...

The use of nonparametric methods, which posit fewer assumptions and greater model flexibility than parametric methods, could provide useful insights when studying brand choice. It was found, however, that the data requirement for a fully nonparametric brand choice model is so great that...

The use of nonparametric methods, which posit fewer assumptions and greater model flexibility than parametric methods, could provide useful insights when studying brand choice. It was found, however, that the data requirement for a fully nonparametric brand choice model is so great that...

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...

A nonparametric version of the Final Prediction Error (FPE) is proposed for lag selection in nonlinear autoregressive time series. We derive its consistency for both local constant and local linear estimators using a derived optimal bandwidth. Further asymptotic analysis suggests a greater...