Summary
Investor behavior has a pivotal role in price dynamics. The aim of this study was to explore the characteristics and patterns of the investor behavior and network structure behind. The investor behavior propagation model was proposed, which described the intrinsic dynamic mechanism of stock market and had a good fit to the real data. It was found that the Nearest-neighbor coupled network and the disassortative network can depict the investing behavior network precisely. Combining these two aspects, the Nearest-neighbor coupled network with hub nodes was constructed. Performance was superior to other network structures and suggests that the Nearest-neighbor coupled network with hub nodes is more consistent with the real investor networks.