首頁 > 網路資源 > 大同大學數位論文系統

Title page for etd-0806104-145644


URN etd-0806104-145644 Statistics This thesis had been viewed 2707 times. Download 9 times.
Author Yi-lin Huang
Author's Email Address g9106026@ms2.ttu.edu.tw
Department Computer Science and Enginerring
Year 2003 Semester 2
Degree Master Type of Document Master's Thesis
Language English Page Count 44
Title Detecting Long-range Power-law Correlations in Financial Time Series: A Case on Listed Companies of Taiwan Stock Market
Keyword
  • Time Series Analysis
  • Long Memory
  • Detrended Fluctuation Analysis
  • Detrended Fluctuation Analysis
  • Long Memory
  • Time Series Analysis
  • Abstract In time series analysis, there have been many statistic models widely used; some models could estimate long memory. A new idea for analyzing time series is Detrended Fluctuation Analysis (DFA), which was originally developed for finding long-rage power-law correlations in DNA sequences. We apply DFA to Taiwan stock market for three categories of data: TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index), the group indices aggregated from individual stock indices, and individual stock indices. The results show that long memory exists in most listed companies of Taiwan stock market for the cases when scaling exponent not equals to 0.5. However, the correlations detected from aggregated data series do not imply the correlation of original data series. Our findings are that the correlations detected from main index do not imply the same correlation of group indices and individual stock indices, but there are greater than half of group indices and individual stock indices following the same correlation with the main index.
    Advisor Committee
  • Huei-huang Chen - advisor
  • Jin-Long Wang - co-chair
  • none - co-chair
  • Files indicate in-campus access only
    Date of Defense 2004-07-21 Date of Submission 2004-08-06


    Browse | Search All Available ETDs