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Application of sequential nonparametric confidence bands in finance

Dharmasena, L. Sandamali, de Silva, Basil M. and Zeephongsekul, Panlop 2007, Application of sequential nonparametric confidence bands in finance, in ACE 2007 : Proceedings of 36th Australian Conference of Economists, Conference Design, [Hobart, Tas.], pp. 1-17.

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Title Application of sequential nonparametric confidence bands in finance
Author(s) Dharmasena, L. Sandamali
de Silva, Basil M.
Zeephongsekul, Panlop
Conference name Australian Conference of Economists (36th : 2007 : Hobart, Tas.)
Conference location Hobart, Tas.
Conference dates 24-26 Sept. 2007
Title of proceedings ACE 2007 : Proceedings of 36th Australian Conference of Economists
Editor(s) Blacklow, Paul
Publication date 2007
Conference series Australian Conference of Economists
Start page 1
End page 17
Total pages 17
Publisher Conference Design
Place of publication [Hobart, Tas.]
Summary In a nonparametric setting, the functional form of the relationship between the response variable and the associated predictor variables is assumed to be unknown when data is fitted to the model. Non-parametric regression models can be used for the same types of applications such as estimation, prediction, calibration, and optimization that traditional regression models are used for. The main aim of nonparametric regression is to highlight an important structure in the data without any assumptions about the shape of an underlying regression function. Hence the nonparametric approach allows the data to speak for itself. Applications of sequential procedures to a nonparametric regression model at a given point are considered.

The primary goal of sequential analysis is to achieve a given accuracy by using the smallest possible sample sizes. These sequential procedures allow an experimenter to make decisions based on the smallest number of observations without compromising accuracy. In the nonparametric regression model with a random design based on independent and identically distributed pairs of observations (X ,Y ), where the regression function m(x) is given bym(x) = E(Y X = x), estimation of the Nadaraya-Watson kernel estimator (m (x)) NW and local linear kernel estimator (m (x)) LL for the curve m(x) is considered. In order to obtain asymptotic confidence intervals form(x), two stage sequential procedure is used under which some asymptotic properties of Nadaraya-Watson and local linear estimators have been obtained.

The proposed methodology is first tested with the help of simulated data from linear and nonlinear functions. Encouraged by the preliminary findings from simulation results, the proposed method is applied to estimate the nonparametric regression curve of CAPM.
ISBN 9780959337013
Language eng
Field of Research 140207 Financial Economics
Socio Economic Objective 970114 Expanding Knowledge in Economics
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2007, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30033188

Document type: Conference Paper
Collections: School of Information and Business Analytics
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.