﻿ 非参数协整和误差修正模型及其在金融中的应用

# 非参数协整和误差修正模型及其在金融中的应用Applications of Nonparametric Cointegration and Error Correction Model to Finance

Abstract:
This paper mainly focuses on co-integration theory and nonparametric method with nonlinear co-integration, which includes linear co-integration and linear error correction model, nonlinear co-integration and nonlinear error correction model, the ACE algorithm and local polynomial regression. It is clearly proved right by these analytical methods. The Matlab programming is fully exerted to realize the local polynomial regression, a nonparametric test method. In this paper, co-integration theory is clarified in details including linear theory of co-integration, linear estimation of error correction model, linear co-integration theory and tests, the nonlinear co-integration and error correction model as well as the estimation and inspection towards it. Moreover, the annotation is added for individual specifics, aiming to clarify the structures of co-integration. The existing application of time series nonlinear co-integration is put forward to serve the new method, namely the method of fusing the ridge regression nonparametric local polynomial regression. The simulation shows that this method is proved to be right. The index data assisting the researcher access to the empirical analysis are references from Japan, Singapore and Taiwan. It is on its purpose by combing the non-parametric method of local polynomial regression, co-integration and error correction model to estimate the analysis on the co-integration and error correction model. The precision of the model is assured. The local polynomial regression can be aimed to assist in explaining the significance of the non-parametric method of first derivative stock indexes in Japan, Singapore and Taiwan.

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