Earticle

초록

영어

We propose a novel approach for estimating the similarity between the trends of two time series, which has been an important problem in the fields of finance, economics and econophysics. We introduce the exit-time correlation (EC) to measure this similarity based on the exit-time method recently used as inverse statistics in financial time series analysis. We use a phase-noise induced Fourier transform method to illustrate the efficiency of our approach compared with the multiscale cross correlation method. The exit-time correlation serves as the inverse statistics for the multiscale cross correlation in analyzing correlation between multivariate time series. The application of our approach to high-frequency foreign exchange rates reveals that the exit-time correlation is related to time organization structure in interactions with a long-range time scale.

목차

Abstract
 I. INTRODUCTION
 II. EXIT-TIME CORRELATION METHOD
  A. Exit-time series
  B. Exit-time Correlation
 III. ESTIMATING SIMILARITY BETWEEN TREND BEHAVIORS OF MULTIVARIATE TIME SERIES
  A. Phase-noise induced Fourier transform
  B. Multiscale cross correlation
  C. The exit-time correlation for foreign exchange rates
 IV. CONCLUSION
 V. ACKNOWLEDGEMENTS

저자

• Woo Cheol Jun [ Hanwha Investment Trust Management, Seoul, 150-717, Korea ]
• Gabjin Oh [ Division of Business Administration, Chosun University Gwangju, 501-759, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국재무학회 학술대회

• 간기

  부정기

• 수록기간

  2006~2024

• 십진분류

  KDC 325 DDC 330