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The Improved EWMA Chart for Heteroscedasticity Process

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Listed:
  • Dan Zhou

    (Sichuan Normal University)

  • Liu Liu

    (Sichuan Normal University)

  • Xin Lai

    (Xi’an Jiaotong University)

Abstract

It is doubtful of the validity of the EWMA chart that the observations from heteroscedasticity processes violate the assumption of identical distribution. In this paper, we discuss the effect of heteroscedasticity on the performance of the conventional EWMA chart. Then we analyze the principle of the improved EWMA chart for monitoring heteroscedasticity processes. Then we compare the detection performance of the improved EWMA chart with the conventional EWMA chart by using a criteria based on average run length (ARL). Finally, an instance is given to indicate the effectiveness of the proposed method and analyze the best trading time of the stock.

Suggested Citation

  • Dan Zhou & Liu Liu & Xin Lai, 2018. "The Improved EWMA Chart for Heteroscedasticity Process," Annals of Data Science, Springer, vol. 5(1), pages 21-27, March.
    • Handle: RePEc:spr:aodasc:v:5:y:2018:i:1:d:10.1007_s40745-017-0133-0
    DOI: 10.1007/s40745-017-0133-0
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    References listed on IDEAS

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    1. Alwan, Layth C & Roberts, Harry V, 1988. "Time-Series Modeling for Statistical Process Control," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 87-95, January.
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