复杂网络上的信息甄别、扩散与资产定价
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摘要
互联网和社会化媒体的发展从三个方面显著地改变了金融市场中个体的信息交互模式：1.产生了大量且影响广泛的“个体信息源”，个体决策行为面对着了从未有过的大量的信息渠道；2.市场信息表现出异质性和即时交互性，在信息传播速度得到提升的同时，也带来了虚假信息和市场信息操纵等问题，个体决策必须更多的考虑对信息真实性的甄别；3.个体拥有了大范围信息搜索能力，在决策过程中可以随时改变获取信息来源，从而使金融市场信息交互网络结构呈现出动态演化的复杂特性。这些改变对个体利用信息做出投资决策的过程产生了重要影响，也更进一步地影响了资产价格的形成。
面对由科技进步带来的信息扩散渠道和个体对信息处理方式的转变，现有的研究均只从某一个侧面反映了市场信息扩散过程的改变。本文利用计算实验建模的优势，自底向上地对个体信息甄别行为建模，并在个体信息交互层面加入复杂网络作为信息的扩散渠道。分别建立了具有固定信息扩散网络结构的人工股票市场和具有动态演化信息扩散网络结构的人工股票市场，研究异质信息源、动态信息扩散网络结构等多种要素对个体信息甄别能力和资产价格的影响。
本文通过引入异质信息源和复杂网络结构，得到了与传统信息甄别模型不一致的结论。本文发现信息扩散网络结构和异质信息源可以影响非知情者的信息甄别能力和资产价格，在某些异质信息源和特定网络扩散结构条件下，非知情者的信息甄别能力将得到很大的提高。此外，本文进一步研究发现，异质信息源对非知情者甄别信息能力的提升具有“阀值效应”，只有保证市场中信息有足够的异质性，非知情者才能以较高概率准确甄别信息。本文还检测了信息精度、传播时间、信息搜索范围和信息源鉴别成本等因素对个体信息甄别能力及资产价格的影响，这些发现都为防范金融市场虚假信息扩散及市场信息操纵提供了必要的理论基础和政策建议。
The development of the Internet and social media significantly changed theinteraction of information among individuals in the financial markets from threeaspects:1. Emerging a large number of "individual information sources" who haswide influence. Individual faces more information channels than ever before whenmaking decision;2. Market information becomes heterogeneous, instant andinteractive. The information transmission speed in stock market is greatly improved,which also brought the problems such as false information diffusion and informationmanipulation. Individuals must pay more attention on information identification whenmaking decision;3. Individuals have a wide range of information search ability,which help them to change information sources freely in the decision making process.Information diffusion network structure in financial market presents a complexdynamic evolution. These changes has produced important influences on the useageof information to make a decision process in financial markets, and further affect theformation of asset prices.
From the point of view in this kind of change, it needs to answer two related questionsbelow at least to accurately describe the information diffusion process in financialmarket: How the agents send, transmit, distort the information and identify it in theprocess of information diffusion? What kind of information network structuresfollowed by stock investors changing information? So far, current studies only focuson one of the two questions. In this paper, using the advantage of agent-basedmodelling, we studied information network and heterogeneous information sourcesinfluence on uninformed agents in the artificial stock market. We established twoartificial stock markets. One of which is information diffusion in fixed networkstructure and the other is information diffusion in a dynamic evolution networkstructure. All of agents update their strategies through reinforcement learning andpredict next period price with genetic algorithm. In order to make this informationtransmission networks closer to the real market, agents interact with each otherthrough the Small-world Network in basic model. We tested the changing ofuninformed agents identification ability and asset price by controlling networkstructure conditions and heterogeneous information source conditions.
Because of the introduction of heterogeneous information sources and complexnetwork structure, we obtained conclusions very different from the traditionalcheap-talk game model. We discover that the informationd diffusion networkstructure between individuals and heterogeneous sources can improve the uninformedagents identification ability. Uninformed agents can improve their identificationability with heterogeneous information sources. However, the threshold effects existin heterogeneous information sources, which means uninformed agents will notdistinguish dishonest informed agent with few heterogeneous information sources.Their identification ability will have a great improvement only if there exists enoughheterogeneous information sources in stock market. This article also examined the accuracy of information sources, the diffusion time, the information search ability andcosts to identify information sources. Finally, our studiy provides the necessarytheoretical basis and policy suggestions for false information diffusion preventing andinformation manipulation preventing.
面对由科技进步带来的信息扩散渠道和个体对信息处理方式的转变，现有的研究均只从某一个侧面反映了市场信息扩散过程的改变。本文利用计算实验建模的优势，自底向上地对个体信息甄别行为建模，并在个体信息交互层面加入复杂网络作为信息的扩散渠道。分别建立了具有固定信息扩散网络结构的人工股票市场和具有动态演化信息扩散网络结构的人工股票市场，研究异质信息源、动态信息扩散网络结构等多种要素对个体信息甄别能力和资产价格的影响。
本文通过引入异质信息源和复杂网络结构，得到了与传统信息甄别模型不一致的结论。本文发现信息扩散网络结构和异质信息源可以影响非知情者的信息甄别能力和资产价格，在某些异质信息源和特定网络扩散结构条件下，非知情者的信息甄别能力将得到很大的提高。此外，本文进一步研究发现，异质信息源对非知情者甄别信息能力的提升具有“阀值效应”，只有保证市场中信息有足够的异质性，非知情者才能以较高概率准确甄别信息。本文还检测了信息精度、传播时间、信息搜索范围和信息源鉴别成本等因素对个体信息甄别能力及资产价格的影响，这些发现都为防范金融市场虚假信息扩散及市场信息操纵提供了必要的理论基础和政策建议。
The development of the Internet and social media significantly changed theinteraction of information among individuals in the financial markets from threeaspects:1. Emerging a large number of "individual information sources" who haswide influence. Individual faces more information channels than ever before whenmaking decision;2. Market information becomes heterogeneous, instant andinteractive. The information transmission speed in stock market is greatly improved,which also brought the problems such as false information diffusion and informationmanipulation. Individuals must pay more attention on information identification whenmaking decision;3. Individuals have a wide range of information search ability,which help them to change information sources freely in the decision making process.Information diffusion network structure in financial market presents a complexdynamic evolution. These changes has produced important influences on the useageof information to make a decision process in financial markets, and further affect theformation of asset prices.
From the point of view in this kind of change, it needs to answer two related questionsbelow at least to accurately describe the information diffusion process in financialmarket: How the agents send, transmit, distort the information and identify it in theprocess of information diffusion? What kind of information network structuresfollowed by stock investors changing information? So far, current studies only focuson one of the two questions. In this paper, using the advantage of agent-basedmodelling, we studied information network and heterogeneous information sourcesinfluence on uninformed agents in the artificial stock market. We established twoartificial stock markets. One of which is information diffusion in fixed networkstructure and the other is information diffusion in a dynamic evolution networkstructure. All of agents update their strategies through reinforcement learning andpredict next period price with genetic algorithm. In order to make this informationtransmission networks closer to the real market, agents interact with each otherthrough the Small-world Network in basic model. We tested the changing ofuninformed agents identification ability and asset price by controlling networkstructure conditions and heterogeneous information source conditions.
Because of the introduction of heterogeneous information sources and complexnetwork structure, we obtained conclusions very different from the traditionalcheap-talk game model. We discover that the informationd diffusion networkstructure between individuals and heterogeneous sources can improve the uninformedagents identification ability. Uninformed agents can improve their identificationability with heterogeneous information sources. However, the threshold effects existin heterogeneous information sources, which means uninformed agents will notdistinguish dishonest informed agent with few heterogeneous information sources.Their identification ability will have a great improvement only if there exists enoughheterogeneous information sources in stock market. This article also examined the accuracy of information sources, the diffusion time, the information search ability andcosts to identify information sources. Finally, our studiy provides the necessarytheoretical basis and policy suggestions for false information diffusion preventing andinformation manipulation preventing.
引文
2参见Wikipedia：http://en.wikipedia.org/wiki/Social_media
3数字来源：http://tech.sina.com.cn/i/2012-05-15/12307109653.shtml
4数字来源：http://data.weibo.com/top/hot/all
5来源：http://en.wikipedia.org/wiki/The_Wall_Street_Journal
6证监会刘新华副主席2011年10月24日讲话。http://finance.sina.com.cn/hy/20111024/104810675475.shtml
7详见：http://en.wikipedia.org/wiki/Agent-based_model
11见Arthur、Holland和LeBaron等（1997）。
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3数字来源：http://tech.sina.com.cn/i/2012-05-15/12307109653.shtml
4数字来源：http://data.weibo.com/top/hot/all
5来源：http://en.wikipedia.org/wiki/The_Wall_Street_Journal
6证监会刘新华副主席2011年10月24日讲话。http://finance.sina.com.cn/hy/20111024/104810675475.shtml
7详见：http://en.wikipedia.org/wiki/Agent-based_model
11见Arthur、Holland和LeBaron等（1997）。
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