复杂网络视角下的我国股票之间信息溢出研究

理解股票市场内部股票间的信息溢出规律,对于股票定价、投资组合以及风险防范具有重要的意义。将传统计量经济方法与复杂网络的建模分析方法相结合,从复杂网络的视角出发,实证研究了我国股票市场内股票间的信息溢出关系及其影响因素、个股信息溢出能力分布及其影响因素。研究发现,股票间较长期收益的相互影响要强于较短期收益;股票收益率相关性较强的股票间存在更显著的信息溢出;市场因素显著增强了股票间的信息溢出效应;股票间的信息溢出效应会随着市场行情的上涨(下跌)而增强(减弱);股票的信息溢出能力呈现尖峰、厚右尾的分布;股票成交金额对个股的信息溢出能力具有显著的正向影响。最后,最小生成树能快速而准确有效地揭示股票间信息溢出规律。

Study on Information Flow among Chinese Stocks from the Perspective of Complex Networks

Understanding the information flow between stocks in a stock market plays very important roles in stock pricing, investment portfolio and risk management. This paper integrates traditional econometrical methods with complex network modeling and analyzing methods. We empirically investigate the effects of some influencing factors on the information flow between Chinese stocks, and the individual stock information flow ability distribution and its influencing factors from the perspective of complex networks. We find that the changes of time scale in return affect the information flow among stocks. Stocks with a strong correlation mean more significant information flow than stocks with a weak correlation. The market wide factors significantly strengthen the information flow effects among stocks. The information flow effects are strengthened(weakened)with the up(down)of the market. The individual stock information flow ability obeys a higher peak and fat right tail distribution. The stock transaction amount has a significant positive effect on the stock's information flow ability. Finally, we confirm, via the MST method, that the information flow among stocks could be assessed effectively with the reduced linkage relationships among all links among stocks from the perspective of the overall market.