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Financial bubbles: A learning effect modelling approach

Hsieh, Tsung-Han; Li, Youwei; McKillop, Donal G.

Authors

Tsung-Han Hsieh

Donal G. McKillop



Contributors

Anthony Brabazon
Editor

Michael O'Neill
Editor

Abstract

This chapter studies financial bubbles by incorporating a learning effect into the coordination game model which was articulated by Ozdenoren and Yuan [36]. 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
Print ISSN 1860-949X
Electronic ISSN 1860-9503
Publisher Springer Publishing Company
Pages 117-135
Series Title Studies in Computational Intelligence
Series Number 185
Book Title Natural computing in computational finance
ISBN 9783540959731; 9783540959748
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
DOI https://doi.org/10.1007/978-3-540-95974-8_7
Keywords Private information; Risky asset; Aggregate demand; Coordination game; Private signal
Publisher URL https://link.springer.com/chapter/10.1007%2F978-3-540-95974-8_7
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