Statistical Estimation for CAPM with Long-Memory Dependence

Amano, Tomoyuki; Kato, Tsuyoshi; Taniguchi, Masanobu

doi:10.1155/2012/571034

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Actually, the nonlinear cointegration analysis is widely used in financial issues, such as asset pricing (Lieberman & Phillips, 2008;Amano, et al, 2012) [6,13]. Here, the nonlinear cointegration analysis based on SVM will be applied in the investigation of the connection between financial markets.…”

Section: Application To Analysis Of the Connection Between Financial mentioning

confidence: 99%

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A New Framework for Nonlinear Cointegration Analysis and Its Application to Finance

Shen¹,

Liu²,

Liang³

2014

TOAUTOCJ

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With the purpose of analyzing non-stationary time series, this paper innovates the nonlinear cointegration discriminate analysis by introducing support vector machine and innovated feature-weighting model to overcome existing limitations of two methods, that is, the statistical approach and the neural network used by the nonlinear cointegration theory. Then, the application of the innovated method for the investigation of the connection between financial markets is explored. The empirical analysis demonstrates that the support vector machine is effective in analyzing the money demand function and its stability and has advantages in dealing with nonlinear cointegration relations and estimating nonlinear functions over the two methods above.

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Section: Application To Analysis Of the Connection Between Financial mentioning

confidence: 99%

“…Then, the structure of interaction between the money demand function and every influencing factor, reflecting shortterm changes in their direction and extent to which the function varies correspondingly, can be found through the analysis of AAV in (13) and the results are all shown in Table 2.…”

Section: ∑ ∑mentioning

confidence: 99%

A New Framework for Nonlinear Cointegration Analysis and Its Application to Finance

Shen¹,

Liu²,

Liang³

2014

TOAUTOCJ

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“…• Obtain the estimated output value [21]. Here, the nonlinear cointegration analysis based on SVM will be applied in the investigation of the connection between financial markets.…”

Section: B Nonlinear Cointegration Analysis Based On ε -Svrmentioning

confidence: 99%

Nonlinear Cointegration Analysis Based on Support Vector Machines and Its Application to the Connection between Financial Markets

Shen¹,

Liu²,

Liu³

2013

Proceedings of the 2nd International Conference on Advances in Computer Science and Engineering

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Abstract-With the purpose of analyzing non-stationary time series, this paper introduced a novel nonlinear cointegration discriminate analysis by employing support vector machines to overcome existing limitations of two methods, that is, the statistical approach and the neural network used by the nonlinear cointegration theory. The proposed nonlinear cointegration discriminate analysis can effectively address the key step in the nonlinear cointegration test. Then, the application of the innovated method in the investigation of the connection between financial markets was explored. The empirical analysis demonstrates that the support vector machine is significant in investigating the money demand function and its stability and has advantages in dealing with nonlinear cointegration relations among different financial variables and estimating nonlinear function over the two methods above.

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