Presentation 2007-03-05
Improving Lyapunov Exponents Using Bootstrap Method and Its Application to Financial Time Series
Yoshihiko IMANO, Yasukuni MORI, Ikuo Matsuba,
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Abstract(in English) When we estimate Lyapunov exponents from time series data, a large quantity of data are usually needed. However, a number of the data is not always available. We therefore have proposed a new method using the Bootstrap method, which can estimate Lyapunov exponents from a small number of data. Our proposed method works well for the data artificially generated from Lorenz model with long correlation. In this paper, we try to adapt the method to daily NIKKEI average and daily TOPIX. The effectiveness of our method is shown for time series data with some autocorrelation and a tendency of appropriate bootstrap length is given by the experiment results.
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Keyword(in English) Time series / Lyapunov / Bootstrap / Daily NIKKEI average / Daily TOPIX
Paper # NLP2006-146
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Committee NLP
Conference Date 2007/2/26(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Improving Lyapunov Exponents Using Bootstrap Method and Its Application to Financial Time Series
Sub Title (in English)
Keyword(1) Time series
Keyword(2) Lyapunov
Keyword(3) Bootstrap
Keyword(4) Daily NIKKEI average
Keyword(5) Daily TOPIX
1st Author's Name Yoshihiko IMANO
1st Author's Affiliation Graduate School of Sciencs and Technology, Chiba University()
2nd Author's Name Yasukuni MORI
2nd Author's Affiliation Faculty of Engineering, Chiba University
3rd Author's Name Ikuo Matsuba
3rd Author's Affiliation Faculty of Engineering, Chiba University
Date 2007-03-05
Paper # NLP2006-146
Volume (vol) vol.106
Number (no) 573
Page pp.pp.-
#Pages 6
Date of Issue