Dynamic Characteristics Of Transimission In Economic Time Series

The social and economic system is a complex system, the behavior tracks of which can be described through the time series. There contains rich dynamics information, different types of auto regression modes, regression modes and complicate relationships in the economic time series. How to identify the essential feature of the complex system through the dynamical characteristics of the time series is a frontier and difficult problems in the field of the complex scientific management. Thus, this research proposes algorithms to explore and demonstrate the transmission of auto regression modes of univariate time series, the transmission of regression modes between bivariate time series and transmission dynamical features among multivariable time series by the complex network approach. The contribution and research content is presented as follows,(1) According to the Elliott Wave Theory, there are different types of patterns of time sereis, but he current time series analysis approaches hide the diversity of the patterns. In this research, we defined the auto regression mode of the time series based on the econometrics theory and constructed the transmission complex network models of the auto regression of univariate time series. Then, we demonstrate the dynamics features of the transmission of auto regression modes of the Chinese forex burden time series through the analysis of the distribution of the transmission ability, the distribution of the transmission modes, the transmission distance, the group effect of fluctuations and the medium ability. The results show that there are different dynamics features of the transmission of auto regression modes under different length of time fragment. Based on these results, we can understand the mechanism of fluctuation of time series deeply.(2) Granger representation theorem proved that there is progress during which the short-term fluctuations adjust to long term equilibrium, but the details about the progress is not given. Hence, we proposed novel algorithm to construct the transmission complex network models of the regression modes between bivariate time series. Then, we examine the adjustment mechanism from the short-term fluctuation to long-term equilibrium between the crude oil spot and future prices. The details about the adjustment mechanism can be depicts from the following perspective, namely, the statistical distribution of regression parameters, the identifying of the turning point of the adjustment process from the short term fluctuation to long term equilibrium, the distribution of the transmission ability, transmission distance and medium ability. Supporting information for decision-making, the adjustment mechanism from the short-term fluctuation to long-term equilibrium and its dynamics features should be considered to make and adjust the long-term or short-term decision.(3) In the social and economic network, there are hundreds of connections among factors, which form a huge complex network of the connections. It is a critical need for new and fundamental understanding of the structure and dynamics of economic networks. In this paper, we constructed the complex network model for the regression relationships among multivariable economic time series and we examined the dynamics features of Chinese social and economic network. Then, we explore the hidden dynamics features of the social and economic network through the analysis of transmission distance, the distribution of the effect of the factors’, the group effect and the transmission medium. This work enrich the economic sense of the complex network theory, simultaneously, offers reference information for macroscopic readjustment and control.