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New models of trader beliefs and their application for explaining financial bubbles

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  • Chen, Zhiping
  • Duan, Qihong

Abstract

One challenging and exigent problem in behavior finance is how to establish verifiable models describing the appearance and burst of price bubbles. Current results are enhanced in this paper through a series of improvement as follows: new models are proposed for describing the return and dividend processes, especially the trader's behavior with the adaptive expectation belief and the bounded rational expectation belief, respectively; with these models, we establish dynamical systems in terms of the price-to-earnings ratio and the forecast-to-earnings ratio; the detailed solution and asymptotic analysis of these equations provide new, elaborate and quantitative explanations for both the formation and disappearance of different price bubbles; inspired by the herd behavior framework, a new random belief evolutionary mechanism is devised to model the belief change between two beliefs; a specific genetic algorithm is designed to efficiently estimate model parameters; simulation and empirical studies are carried out to illustrate the application of new methods. Both theoretical and empirical results sufficiently show the reasonability, practicality, efficiency and robustness of our new models and methods for properly explaining the appearance and burst of different kinds of price bubbles.

Suggested Citation

  • Chen, Zhiping & Duan, Qihong, 2011. "New models of trader beliefs and their application for explaining financial bubbles," Economic Modelling, Elsevier, vol. 28(5), pages 2215-2227, September.
  • Handle: RePEc:eee:ecmode:v:28:y:2011:i:5:p:2215-2227
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    Cited by:

    1. Chen, Shyh-Wei & Hsu, Chi-Sheng & Xie, Zixong, 2016. "Are there periodically collapsing bubbles in the stock markets? New international evidence," Economic Modelling, Elsevier, vol. 52(PB), pages 442-451.
    2. Lu, Jianjun & Tokinaga, Shozo, 2014. "Estimation of state changes in system descriptions for dynamic Bayesian networks by using a genetic procedure and particle filters," Economic Modelling, Elsevier, vol. 39(C), pages 138-145.

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