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Segmentation Study of Foreign Exchange Market

  • Aki-Hiro Sato
Chapter

Abstract

This chapter explains a recursive segmentation procedure under normal distribution assumptions. The Akaike information criterion between independently identically distributed Gaussian samples and two successive segments drawn from different Gaussian distributions is used as a discriminator to segment time series. The Jackknife method is employed in order to evaluate a statistical significance level. This chapter shows univariate and multivariate cases. The proposed method is performed for artificial time series consisting of two segments with different statistics. Furthermore, log-return time series of currency exchange rates for 30 currency pairs for the period from January 4, 2001 to December 30, 2011 are divided into 11 segments with the proposed method. It is confirmed that some segment corresponds to historical events recorded as critical situations.

Keywords

Multivariate Gaussian Distribution Multivariate Time Series Segmentation Procedure Financial Time Series Foreign Exchange Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The author would like to express his sincere gratitude to Prof. Zdzislaw Burda of Jagiellonian University for constructive comments and stimulating discussions.

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Copyright information

© Springer Japan 2014

Authors and Affiliations

  1. 1.Graduate School of InformaticsKyoto UniversityKyotoJapan

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