Abstract
In recent years, the concept of entropy is widely used to measure the degree of uncertainty or complexity of dynamics system. In our work, we utilize the composite multiscale entropy (CMSE) and the composite multiscale cross-sample entropy (CMSCE) which are two modified algorithms of SampEn and Cross-SampEn by considering multiscale factors, to, respectively, investigate the multiscale complexities and asynchronies (correlations) in the Chinese stock market (SSZ, SZSE and HSI) as well as in our established financial stock price model. The price model is given based on a greatly important statistical physics system, the two-dimensional continuum percolation system. In the model, the fluctuations of stock price changes are assumed to be attributed to the market information interactions among the traders, and the percolation cluster is taken to represent the traders holding the same investment attitude. The empirical CMSE and CMSCE results display and meanwhile make comparisons of abundant complexities and correlations properties about Chinese stock indices and simulation data on both overall and the upwards, downwards trend of their returns.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
