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CUSUM method in predicting regime shifts and its performance in different stock markets allowing for transaction fees

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  • G. Yi
  • S. Coleman
  • Q. Ren

Abstract

Statistical Process Control (SPC) is a scientific approach to quality improvement in which data are collected and used as evidence of the performance of a process, organisation or set of equipment. One of the SPC techniques, the cumulative sum (CUSUM) method, first developed by E.S. Page (1961), uses a series of cumulative sums of sample data for online process control. This paper reviews CUSUM techniques applied to financial markets in several different ways. The performance of the CUSUM method in predicting regime shifts in stock market indices is then studied in detail. Research in this field so far does not take the transaction fees of buying and selling into consideration. As the study in this paper shows, the performances of the CUSUM when taking account of transaction fees are quite different to those not taking transaction fees into account. The CUSUM plan is defined by parameters h and k. Choosing the parameters of the method should be based on studies that take transaction fees into account. The performances of the CUSUM in different stock markets are also compared in this paper. The results show that the same CUSUM plan has remarkably different performances in different stock markets.

Suggested Citation

  • G. Yi & S. Coleman & Q. Ren, 2006. "CUSUM method in predicting regime shifts and its performance in different stock markets allowing for transaction fees," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(7), pages 647-661.
  • Handle: RePEc:taf:japsta:v:33:y:2006:i:7:p:647-661
    DOI: 10.1080/02664760600708590
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    References listed on IDEAS

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    1. Blondell, David & Hoang, Philip & Powell, John G. & Shi, Jing, 2002. "Detection of Financial Time Series Turning Points: A New CUSUM Approach Applied to IPO Cycles," Review of Quantitative Finance and Accounting, Springer, vol. 18(3), pages 293-315, May.
    2. Kahya, Emel & Theodossiou, Panayiotis, 1999. "Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology," Review of Quantitative Finance and Accounting, Springer, vol. 13(4), pages 323-345, December.
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    Cited by:

    1. A R Brentnall & M J Crowder & D J Hand, 2010. "Likelihood-ratio changepoint features for consumer-behaviour models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 462-472, March.
    2. Wu, Zhang & Yang, Mei & Jiang, Wei & Khoo, Michael B.C., 2008. "Optimization designs of the combined Shewhart-CUSUM control charts," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 496-506, December.

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