While many senior executives continue to talk about the "voice of the customer," few demonstrate their commitment to this concept by spending time with customers. Many continue to use their intuition or `golden gut' in their attempt to provide superior customer value. Unfortunately, `senior executive intuition' is rarely attuned to the needs of their customers. While the competitive environment continues to intensify, executives have cut back on the time devoted to customers just when it should be increasing. This article discusses the need for senior executives to spend time with customers and provides examples of the benefits that this approach will provide.

This paper studies the error pattern in case of asset pricing models, using the multivariate nonparametric regression technique to extrapolate possible improvement of fit for the nonparametric model over the usual parametric one. The authors have attempted to compare the parametric and the nonparametric regressions in terms of fit. The study concludes that the nonparametric regression is better than its parametric counterpart and the Epanechnikov Kernel gives better estimate than the Gaussian Kernel.

The objective of this article is to find out a nonparametric regression model capable of describing the effect of various market indices (stock market index, sector-specific index, volume of trade, Index of Industrial Production, etc.) on returns of different securities. This article tries to find out the behavior of error terms in case of Capital Asset Pricing Model (CAPM) using the nonparametric regression techniques.

Parametric models are fully determined up to a parameter (vector). The fitted models can easily be interpreted and estimated accurately if the underlying assumptions are correct. If, however, they are violated then parametric estimates may become inconsistent and give a misleading picture of the regression relationship. In reality these assumptions are not followed i.e., errors may not follow a normal distribution and the distribution of errors may not be symmetric at all.On the other hand, nonparametric models of the risk-return trade-off in capital asset pricing situations avoid restrictive assumptions on the functional form of the regression function m (to be discussed in detail below). However, these models may be difficult to be interpreted and yield inaccurate estimates if the number of regression is large. In the nonparametric analysis nothing is assumed about the shape of the distribution prior to analysis. The given data is fitted according to a chosen model and it is tried to find out the distribution from it.

Multivariate Nonparametric Capital Asset Pricing Model, asset pricing models, nonparametric regression technique, Industrial Production, Parametric models, nonparametric analysis, Capital Asset Pricing Model (CAPM), stock market index, sector-specific index.