Financial bubbles: A learning effect modelling approach
Hsieh, Tsung-Han; Li, Youwei; McKillop, Donal G.
Professor Youwei Li Youwei.Li@hull.ac.uk
Donal G. McKillop
This chapter studies financial bubbles by incorporating a learning effect into the coordination game model which was articulated by Ozdenoren and Yuan . Monte Carlo simulation is then utilised to analyse how the addition of a learning effect impacts upon the investment decision of informed investors as well as the formation of the aggregate investment. The simulation exercise demonstrates that both the learning effect and the feedback effect contribute to price multiplicity with price multiplicity observed when informed investors have more precise private information. The analysis emphasises that the learning effect is stronger in situations where informed investors act counter to the price signal and the actions of uninformed investors.
|Publication Date||Mar 1, 2009|
|Journal||Natural Computing in Computational Finance; Studies in Computational Intelligence|
|Publisher||Springer Publishing Company|
|Series Title||Studies in Computational Intelligence|
|Book Title||Natural computing in computational finance|
|APA6 Citation||Hsieh, T., Li, Y., & McKillop, D. G. (2009). Financial bubbles: A learning effect modelling approach. In A. Brabazon, & M. O'Neill (Eds.), Natural computing in computational finance, 117-135. Springer Publishing Company. https://doi.org/10.1007/978-3-540-95974-8_7|
|Keywords||Private information; Risky asset; Aggregate demand; Coordination game; Private signal|
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