http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Yeng-Tseng (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
An Investigation into the Multifractal Characteristics of the TAIEX Stock Exchange Index in Taiwan
Zhi-Yuan Su,Yeng-Tseng Wang 한국물리학회 2009 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.54 No.4
This paper analyzes the minute-by-minute variations of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) over eight years by using the box-counting multifractal spectum f(). The results reveal that the daily return R is directly correlated with the absolute value of for that day while a positive or negative sign of is related to an increasing or decreasing return, respectively The gain probability (G%) and the index increase probability (N%) attain 65 74 % when has a positive value and 8 32 % when has a negative value, but both converge toward 50 % with the number of days considered when computing the value of increases. With regard to prediction of the future index movement the results show that the sign sequences of provide a more reliable predictive performance than those of the index variation parameter . The correlation between the risk measurement parameter and the increasing or decreasing tendency of the TAIEX price index is also examined in this paper and results are opposite to those presented for the SSEC index in China thus suggesting that the phenomenon is market dependent.
-
A Multifractal Detrended Fluctuation Analysis of Taiwan's Stock Exchange
Zhi-Yuan Su,Yeng-Tseng Wang,Hsin-Yi Huang 한국물리학회 2009 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.54 No.4
This paper presents an empirical investigation on the multifractal characteristics of the Taiwan stock exchange by analyzing the minute-by-minute fluctuations in the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) return signal. The generalized Hurst exponent, the Rnyi exponent and the multifractal spectrum of the signal are evaluated using a multifractal detrended fluctuation analysis (MF-DFA), which is also applied in analyzing the multifractal properties of the logarithmic price increment (LPI) signals of 150 highly-capitalized Taiwanese companies. The results reveal the LPI signal of each company preserves multiscaling and multifractal phenomena. The relative contributions of the long-range temporal correlation and the non-Gaussian data fluctuations toward the multifractality of the time series are also examined. The results suggest that the non-Gaussian probability distributions exert a more dominant effect on the multifractality of TAIEX, but that long-range temporal correlations are more important for the LPI signals of share prices.
-
Nonlinear Analysis of the Estrous-cycle Time Series in Mice
Tzuyin Wu,Lieh-Jung Chang,Shu-Yin Wang,Zhi-Yuan Su,Yeng-Tseng Wang 한국물리학회 2009 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.55 No.4
A nonlinear time-series analysis method is used to investigate the dynamic behavior of the estrous cycle in female mice. Taking the daily changes in the cell types observed in the vaginal smears of mice as a single-variable time series, we construct a multi-dimensional state space by using an embedding scheme. The Lyapunov exponent and the correlation dimension of the trajectories in the re-constructed state space are analyzed in order to understand the underlying dynamics of the reproductive cycle of the mice. The time-series analysis results are found to be consistent with the physiological description of the reproductive endocrine system. Moreover, the results suggest that the variations in the estrous cycle of mice have a low-dimensional chaotic motion. A nonlinear time-series analysis method is used to investigate the dynamic behavior of the estrous cycle in female mice. Taking the daily changes in the cell types observed in the vaginal smears of mice as a single-variable time series, we construct a multi-dimensional state space by using an embedding scheme. The Lyapunov exponent and the correlation dimension of the trajectories in the re-constructed state space are analyzed in order to understand the underlying dynamics of the reproductive cycle of the mice. The time-series analysis results are found to be consistent with the physiological description of the reproductive endocrine system. Moreover, the results suggest that the variations in the estrous cycle of mice have a low-dimensional chaotic motion.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
