复杂信息环境下投资者学习行为对其收益影响分析

发布时间：2018-03-13 19:09

本文选题：复杂网络　切入点：信息扩散　出处：《天津大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着信息技术的发展，证券市场中投资者个体间关于信息的互动方式与互动网络日趋复杂，这些信息可能来自于投资者根据自身经验对市场环境的分析、对其他投资者投资行为的观察，或者与他人进行的沟通交流。这些投资者间进行的关于投资经验的分享与交流，使得能力差的投资者倾向于借鉴和学习能力强的投资者的投资策略，能力强的投资者会基于历史数据和相关理论知识分析，进行个人学习提高投资能力。因此投资者的学习行为将证券市场乃至宏观经济产生深远影响，研究学习行为对证券市场的影响就具有非常有益的现实意义。本文基于行为金融学理论，充分考虑投资者学习类型的异质性，结合证券市场中的不对称信息现象与投资者对信息来源的信任累积现象，以投资者主体为节点，信息传播途径为边，构建择优连接的复杂信息扩散网络来模拟投资者学习过程。通过分析复杂信息扩散网络的网络结构，研究不同学习方式和学习时间对投资者收益的影响，从而提出证券市场中投资者应采取的学习类型及其对投资者收益的影响。对复杂信息扩散网络进行网络分析，该网络具有明显的无标度性和较弱的小世界性，属于社会网络。网络中节点数与信任阈值的改变会影响到网络结构的变化，从而影响到投资者收益。在此基础上得出结论：采取混合学习方式的投资者的学习效果最佳，采取社会学习方式的投资者学习效果最差；学习次数的增加有助于收益从掌握大量资源的hub投资者向普通投资者转移。随着信任阈值的增大或者随着网络规模的增大，投资者收益分布图均呈现出先聚集后分散的现象。因此，对他人保持合理的信任和适度增大自己的信息网络规模，，能够提高投资者收益；在保持网络结构不变的情况下，通过混合学习方式进行较长时间学习，即长时间内既关注公开信息、观察与学习其他投资者的投资策略，又坚持自省的投资者将会获得更高的投资收益。
[Abstract]:With the development of information technology, investors in the stock market between individuals on information interaction and interactive network is becoming more and more complex, this information may come from investors according to their own experience on the analysis of the market environment, the observation of other investors, or to communicate with him. These investors of investment experience share and exchange, the poor investors tend to learn from the strong ability of investors, the ability of the investors will analyze the historical data and related theoretical knowledge based on individual learning ability. So learning to improve the investment behavior of investors will have a profound impact of stock market and macroeconomic impact, research on learning behavior of securities the market will have practical significance very useful.
In this paper, based on the behavioral finance theory, considering the heterogeneity of investors learning types, combined with the information asymmetry phenomenon in the stock market and investors accumulated phenomenon on sources of information to trust investors for the node, transmission of information as edges, constructing complex information diffusion network to simulate the preferential attachment of investors through the analysis of the network structure learning process. The complex information diffusion network, study the influence of different learning methods and learning time for investors, so as to put forward the investors in the stock market should adopt the type of learning and its impact on investment returns.
The network analysis of the complex information diffusion network, the network has small world scale-free and less obvious, belongs to the social network. The number of nodes in the network and trust threshold could be influenced by the change of network structure, which affects the return of investors. On the basis of the conclusion: adopt the hybrid learning approach to investors the best effect of learning, social learning take the way investors learn the difference; learning times increase contributes to benefit from mastering a lot of resources hub investors to ordinary investors transfer. With increased the confidence threshold or increase with the network size, distribution of income investors were first aggregated dispersion phenomenon.
Therefore, to maintain a reasonable trust and properly increase the scale of their network information to others, can improve the return of investors; in keeping the network structure unchanged, a long time study in the mixed way of learning, which is a long time not only pays attention to public information, observation and study other investors, investors will also insist on introspection get a higher return on investment.

【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：O157.5;F832.51

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