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On a class of estimation and test for long memory

Author

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  • Fu, Hui
  • Chen, Wenting
  • He, Xin-Jiang

Abstract

This paper proposes a new analysis method of the estimation and test for long memory time series. We first introduce the definitions of the time scale series, strong variance scale exponent and weak variance scale exponent, and establish the mathematical equations for the variance scale exponents, with which the time series of the white noise, short memory and long memory can be accurately identified. Two statistics for the hypothesis tests of white noise, short memory and long memory time series are constructed, and the Monte Carlo performance for MSE of the weak variance scale exponent estimator and the empirical size and power of SLmemory statistic is subsequently demonstrated, giving practical recommendations of finite-sample. Finally, brief empirical examples are provided based on Sino–US stock index logarithmic return rate data.

Suggested Citation

  • Fu, Hui & Chen, Wenting & He, Xin-Jiang, 2018. "On a class of estimation and test for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 906-920.
    • Handle: RePEc:eee:phsmap:v:509:y:2018:i:c:p:906-920
    DOI: 10.1016/j.physa.2018.06.092
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    More about this item

    Keywords

    Long memory; Weak variance scale exponent; SLmemory statistic; Time scale series;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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