含逆风参数和一般信念函数的价格动态模型
A Stock Price Dynamic Model with Reverse Parameter and General Function of Belief
DOI: 10.12677/AAM.2019.81006, PDF,   
作者: 徐燕霞, 师 恪, 潘正红：新疆大学，数学与系统科学学院，新疆 乌鲁木齐
关键词: 一般信念函数；逆风参数；稳定性；分支；A General Function of Beliefs； Reverse Parameter； Stability； Bifurcation
摘要: 本文对图表分析者引入基于价格偏差的一般预期信念函数，将模型一般化。考虑到逆风者在市场中的影响，从而引入逆风参数(逆风参数指逆风者在图表分析者中所占的比例)。根据差分方程理论知识，分析了一般信念函数下系统的平衡解、稳定性、分支等，并讨论了主要参数对系统稳定性的影响。通过分析，验证了逆风者具有稳定市场的作用。
Abstract: In this paper, a general function of expectation beliefs based on stock price deviation is introduced to the chartists. And considering the influence of the reverse investors, we add the reverse param-eter, which represents the proportion of the reverse investors in the chartists. Using difference equation to analyse the equilibrium solutions, stability and bifurcations of the system with general beliefs function, we discuss the influence of main parameters. Through analysis, it is verified that the reverse investors has an important role in the market.
文章引用：徐燕霞, 师恪, 潘正红. 含逆风参数和一般信念函数的价格动态模型[J]. 应用数学进展, 2019, 8(1): 50-63. https://doi.org/10.12677/AAM.2019.81006

参考文献

[1] Zeeman, E. (1974) On the Unstable Behaviour of Stock Exchanges. Journal of Mathematical Economics, 1, 39-49.
[Google Scholar] [CrossRef] 
[2] Brock, W. and Hommes, C. (1998) Heterogeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Models. Journal of Economic Dynamics and Control, 22, 1235-1274.
[Google Scholar] [CrossRef] 
[3] Gaunersdorfer, A. and Hommes, C. (2000) A Nonliner Structural Model for Volatility Clustering. CeNDEF Working Papers, 00-01, 265-288.
[4] Ding, Z., Granger, C. and Engle, R. (1993) A Long Memory Property of Stock Market Returns and a New Model. Journal of Empirical Finance, 1, 83-106.
[Google Scholar] [CrossRef] 
[5] Beja, G. (1980) On the Dynamic Behavior of Prices in Disequilibrium. Journal of Finance, 35, 235-247.
[Google Scholar] [CrossRef] 
[6] 王铎, 彭建平, 郑敏. 做市商调整价格速度与资产价格的波动[J]. 管理评论, 2004, 16(11): 28-34.
[7] Verbic, M. (2012) Memory and Asset Pricing Models with Heter-ogeneous Beliefs. Nonlinearity, Bifurcation and Chaos-Theory and Applications, 12, 214-311.
[8] Hommes, C. and Kiseleva, T. (2012) Is More Memory in Evolutionary Selection (De)stabilizing? Macroeconomic Dynamics, 16, 335-357.
[Google Scholar] [CrossRef] 
[9] 胡建梅. 含逆风参数的两类价格动态模型及实证分析[D]: [硕士学位论文]. 乌鲁木齐: 新疆大学, 2013.
[10] 张艳萍. 基于一类非线性价格预期函数的资产定价模型的研究[D]: [硕士学位论文]. 乌鲁木齐: 新疆大学, 2016.
[11] Chiarella, C. and He, X.-Z. (2002) Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model. Computational Economics, 19, 95-132.
[Google Scholar] [CrossRef] 
[12] Park, B.-J. (2014) Time-Varying, Heterogeneous Risk Aversion and Dynamics of Asset Prices among Boundedly Rational Agents. Journal of Banking & Finance, 43, 150-159.
[Google Scholar] [CrossRef] 
[13] Brock, W. and Hommes, C. (2002) Heterogeneous Beliefs and Routes to Complex Dynamics in Asset Pricing Models with Price Contingent Contracts. In: Hommes, C.H., Ramer, R. and Withagen, C.A., Eds., Equilibrium, Markets and Dynamics, Springer, Berlin, 245-265.
[14] He, X.-Z. and Li, Y. (2015) Testing of a Market Fraction Model and Power-Law Behaviour in the DAX 30. Journal of Empirical Finance, 31, 1-17.
[Google Scholar] [CrossRef] 
[15] He, X.-Z. and Li, Y. (2015) The Adaptiveness in Stock Markets: Testing the Stylized Facts in the Dax 30. Journal of Evolutionary Economics, 27, 1-24.
[16] Polach, J. and Kukacka, J. (2018) Prospect Theory in the Heterogeneous Agent Model. Journal of Economic Interaction & Coordination, 1-28.
[Google Scholar] [CrossRef] 
[17] Schmitt, N. (2018) Heterogeneous Expectations and Asset Price Dynamics.
[18] 周义仓, 曹慧, 肖燕妮. 差分方程及其应用[M]. 北京: 科学出版社, 2014.

为你推荐