兰州大学机构库 >数学与统计学院
基于双时滞传染模型的行为金融研究—以中国证券市场为例
Alternative TitleTHE BEHAVIORAL FINANCE STUDIES BASED ON EPIDEMIC MODEL WITH TWO DELAYS---CONSIDER CHINA’S SECURITIES, FOR EXAMPLE
周骐
Thesis Advisor严定琪
2016-05-14
Degree Grantor兰州大学
Place of Conferral兰州
Degree Name硕士
Keyword双时滞 资金传染 羊群效应 贝叶斯神经网络
Abstract本文利用传染病模型为理论工具,研究了中国证券市场的资金传染模型,将双时滞的传染病模型与行为金融有机的结合,分析了中国证券市场(深市和沪市)资金传染流动的宏观规律和法则。首先运用Liapunov 函数证明了本文所构建的传染模型的局部和全局渐近稳定性;其次利用CSAD检验中国证券市场的羊群效应;然后从无风险利率入手,分析中国证券市场资金传染模型的各个参数;最后利用贝叶斯人工神经网络算法反演求出传染模型的参数值。其结论是,中国证券市场对应传染病模型中存在地方病平衡点的一类情况,且存在局部和全局平衡点。基于中国证券市场存在明显的羊群效应,为我们进一步研究资金传染行为提供了佐证,研究发现,当资金有效传染率(λ)等于0.08为一个特殊的经济节点,其值正好对应中国证券市场资金饱和度(i=15%);研究还发现,在市场正常波动的情形下,资金移除率的取值范围是(0.005,0.03);此外,对时滞项的分析表明,第一时滞项对传染模型平衡点的稳定性贡献较大,故可政策性的调控第一时滞项大小,改变系统稳定点的属性,促进经济增长。参数反演算法的结果与上述仿真结果基本一致,说明贝叶斯神经网络在参数反演算法的应用上具有一定的可行性。
Other AbstractBased on the Epidemic Model, this paper researches the financial epidemic model of China Securities Market, and discusses the operation law of China Securities Market(Shenzhen and Shanghai) and macro law of funds contagion flow by combining the epidemic model with double delays with Behavioral Finance. Firstly, we apply Liapunov Function to prove the locally asymptotical stability and globally asymptotically stability of the epidemic model constructed; secondly, we use CSAD (cross-sectional absolute deviation of returns) to test the existence of herd behavior in China Securities Market; then, starting with risk-free interest rate, we analyze each parameter of financial epidemic model; finally, using Bayesian neural network for inversion of differential transmission model’s parameter values. We conclude that a case like endemic equilibrium (θ>1) exists in the corresponding epidemic model of China Securities Market, and local equilibrium and global equilibrium are included. The herd behavior provides us evidence for further studying the funds contagion behavior. We find that when the effective infectious rate of funds (λ) equals 0.08 (a special economic node), its value corresponds to the capital saturation level (i = 15%); we also find that in the case of normal market fluctuations, the removal rate of funds range from 0.005 to 0.03. Besides, the study on delay items shows that the first delay item contributes great to the stability of equilibrium point, so we can control the size of delay items with the change of policy to achieve the purpose of macro-economic regulation. The result of the parameter inversion algorithm is basically identical with the simulation result, it shows clearly that the application of Bayesian neural network in parameter inversion algorithm has certain feasibility.
URL查看原文
Language中文
Document Type学位论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/225115
Collection数学与统计学院
Recommended Citation
GB/T 7714
周骐. 基于双时滞传染模型的行为金融研究—以中国证券市场为例[D]. 兰州. 兰州大学,2016.
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