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Abstract:
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Generalized Estimating Equation has been widely used in longitudinal study and panel data. In order to capture the flexible structure of working correlation matrix, Lin and Carroll used non-parametric GEE and semi-parametric GEE to construct kernel smoother GEE. Wang, Lin and Carroll achieved the semi-parametric efficiency in GEE using 2 steps iteration method. This paper follows semi-parametric GEE method with various working correlation matrix and kernel functions to study the structure of financial data, in order to improve the efficiency and predictive accuracy. The paper will use different working correlation matrix to approach the correlation in financial instruments while using different kernel functions to increase efficiency.
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