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Minimum entropy density method for the time series analysis
Authors:Jeong Won Lee  Joongwoo Brian Park  Hang-Hyun Jo  Jae-Suk Yang  Hie-Tae Moon
Institution:1. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA;2. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;3. School of Physics, Korea Institute for Advanced Study, Seoul 130-722, Republic of Korea;4. Department of Physics, Korea University, Seoul 136-713, Republic of Korea;5. Department of Physics, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Republic of Korea;1. Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, P.R. China;2. Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;1. School of Control Science and Engineering, Shandong University, Jinan, Shandong 250010, China;2. Department of Radiology, Taishan Medical University, Taian, Shandong 271000, China;3. Medical Imaging Department, Taian Tumor Prevention and Treatment Hospital, Taian, Shandong 271000, China;1. BK21plus Physics Division and Department of Physics, Pohang University of Science and Technology, Pohang 37673, Republic of Korea;2. Department of Computer Science, Aalto University School of Science, P.O. Box 15400, Finland;3. University of Liverpool Management School, Liverpool L69 7ZH, United Kingdom;1. Dipartimento di Matematica e Informatica, Università di Udine, Via delle Scienze 206, 33100 Udine, Italy;2. Departament de Matemàtiques, Universitat Jaume I, Campus Riu Sec s/n, 8029 AP Castelló, Spain
Abstract:The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.
Keywords:
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