Fractality and Multifractality in a Stock Market's Nonstationary Financial Time Series

  • Jung, Nam; 
  • Le, Quang Anh; 
  • Mafwele, Biseko J.; 
  • Lee, Hyun Min; 
  • Chae, Seo Yoon; 
  • ... Lee, Jae Woo
Citations

WEB OF SCIENCE

4
Citations

SCOPUS

5

초록

A financial time series, such as a stock market index, foreign exchange rate, or a commodity price, fluctuates heavily and shows scaling behaviors. Scaling and multi-scaling behaviors are measured for a nonstationary time series, such as stock market indices, high-frequency stock prices of individual stocks, or the volatility time series of a stock index. We review the fractality, multi-scaling, and multifractality of the financial time series of a stock market. We introduce a detrended fluctuation analysis of the financial time series to extract fluctuation patterns. Multifractality is measured using various methods, such as generalized Hurst exponents, the generalized partition function method, a detrended fluctuation analysis, the detrended moving average method, and a wavelet transformation.

키워드

Multifractality; Financial market; Stock market; Econophysics; Detrended fluctuation analysis; CROSS-CORRELATION ANALYSIS; DETRENDED FLUCTUATION ANALYSIS; LONG-RANGE CORRELATIONS; VARYING HURST EXPONENT; MOVING AVERAGE; MULTISCALING PROPERTIES; GENERALIZED DIMENSIONS; HIERARCHICAL NETWORK; EMPIRICAL PROPERTIES; WAVELET-TRANSFORM
제목
Fractality and Multifractality in a Stock Market's Nonstationary Financial Time Series
저자
Jung, Nam; Le, Quang Anh; Mafwele, Biseko J.; Lee, Hyun Min; Chae, Seo Yoon; Lee, Jae Woo
DOI
10.3938/jkps.77.186
발행일
2020-08
유형
Review
저널명
Journal of the Korean Physical Society
권
77
호
3
페이지
186 ~ 196