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Features extraction and reconstruction of country risk based on empirical EMD

  • Xiaoyang Yao
  • , Xiaolei Sun
  • , Yuying Yang
  • , Dengsheng Wu*
  • , Xun Liang
  • *Corresponding author for this work
  • CAS - Institutes of Science and Development
  • University of Chinese Academy of Sciences
  • School of Information

Research output: Contribution to journalConference articlepeer-review

Abstract

In the application of the Empirical Mode Decomposition (EMD), reconstruction to the intrinsic mode functions (IMFs) which are obtained by EMD is necessary in order to simplify analysis and make reconstruction results of more economic explanatory power. At present, there are two main reconstruction methods; one is based on the changing of data construction, represented by the fine-to-coarse method, the other one takes the correlation of the IMFs into consideration, for example, calculating the correlation between the marginal spectrums of different IMFs. In order to study the internal unity and differences between the two methods, country risk data of the BRICS countries are selected to make the empirical analysis. The results are as follows. Firstly, it is not reasonable that the residue obtained by the EMD is directly regarded as the trend of the original data. Secondly, by fine-to-coarse, all the IMFs can be reconstructed to three time scales, which are denoted as high-frequency mode, low-frequency mode and trend respectively, but explanation of these scales for the real situation is not satisfactory. At last, trend which is extracted based on the correlation of the IMF marginal spectrums can describe the basic behavior of the original data. Contrasted to fine-to-coarse, the results obtained by the second method are more reasonable.

Original languageEnglish
Pages (from-to)265-272
Number of pages8
JournalProcedia Computer Science
Volume31
DOIs
StatePublished - 2014
Externally publishedYes
Event2nd International Conference on Information Technology and Quantitative Management, ITQM 2014 - Moscow, Russian Federation
Duration: 3 Jun 20145 Jun 2014

Keywords

  • Correlation
  • EEMD
  • Fine-to-coarse
  • Hilbert marginal spectrums
  • Hilbert-Huang tranform
  • Reconstruction

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