Modeling the impulse response complex network for studying the fluctuation transmission of price indices
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We provide a method for analyzing the transmission of fluctuation among price indices, which combines the complex network method and the impulse response function (IRF). The transmission relationships of price fluctuation among numerous price indices are remarkably complicated, especially under external shocks. In this paper, the empirical data of US, China and Japan are selected as samples, and we analyze the transmission relationships between each two price indices using IRF and construct directed positive and negative impulse response networks of US, China and Japan, respectively. We analyze and compare the price fluctuation transmission characteristics of different countries under external shocks from the aspect of the transmission range, degree, intermediary, clustering and time. The results of the analysis indicate that (1) Positive networks are tighter than negative networks; (2) There is positive correlation between the range and degree of price fluctuation transmission; (3) The intermediation ability of price fluctuation transmission is high; (4) The clustering of networks is different and the transmission probability among clusters are different; (5) The transmission speed of positive networks is faster than that of negative networks. This research could provide some implications for investors in relation to decentralizing investments.
KeywordsEconophysics Complex network Impulse response function Fluctuation transmission Price index
JEL ClassificationC3 D85
This research is supported by the Humanities and Social Sciences planning funds project under the Ministry of Education of the PRC (Grant No. 17YJCZH047), Beijing Natural Science Foundation (Grant No. 9174041), the National Natural Science Foundation of China (Grant No. 41871202) and the fund from Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources (Grant No. CCA2017.11).