FUNCTIONAL COEFFICIENT AUTOREGRESSIVE CONDITIONAL ROOT MODEL

Jianjun ZHOU , Min CHEN

Journal of Systems Science & Complexity ›› 2012, Vol. 25 ›› Issue (5) : 998-1013.

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Journal of Systems Science & Complexity ›› 2012, Vol. 25 ›› Issue (5) : 998-1013. DOI: 10.1007/s11424-012-0198-y
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FUNCTIONAL COEFFICIENT AUTOREGRESSIVE CONDITIONAL ROOT MODEL

  • Jianjun ZHOU1 , Min CHEN2
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Abstract

This paper proposes an extended model based on ACR model: Functional coefficient autoregressive conditional root model (FCACR). Under some assumptions, the authors show that the process is geometrically ergodic, stationary and all moments of the process exist. The authors use the polynomial spline function to approximate the functional coefficient, and show that the estimate is consistent with the rate of convergence Op(hv+1 + n −1/3). By  imulation study, the authors discover the proposed method can approximate well the real model. Furthermore, the authors apply the model to real exchange rate data analysis.

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Jianjun ZHOU , Min CHEN. FUNCTIONAL COEFFICIENT AUTOREGRESSIVE CONDITIONAL ROOT MODEL. Journal of Systems Science and Complexity, 2012, 25(5): 998-1013 https://doi.org/10.1007/s11424-012-0198-y

Funding

This research was supported by the National Nature Science Foundation of China under Grant Nos. 10961026, 11171293, 71003100, 70221001, 70331001, and 10628104, the Ph.D. Special Scientific Research Foundation of Chinese University under Grant No. 20115301110004, Key Fund of Yunnan Province under Grant No. 2010CC003, the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China under Grant No. 11XNK027.

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