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Financial Bubbles: A Learning Effect Modelling Approach

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Natural Computing in Computational Finance

Part of the book series: Studies in Computational Intelligence ((SCI,volume 185))

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Summary

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.

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Authors and Affiliations

  1. School of Management, Queen’s University Belfast, 25 University Square, Belfast, BT7 1NN, United Kingdom

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

  2. Tajen University, Taiwan

    Tsung-Han Hsieh

Authors
  1. Tsung-Han Hsieh
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  2. Youwei Li
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  3. Donal G. McKillop
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Editors and Affiliations

  1. University College Dublin, Belfield, Dublin, Ireland

    Anthony Brabazon  & Michael O’Neill  & 

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Hsieh, TH., Li, Y., McKillop, D.G. (2009). Financial Bubbles: A Learning Effect Modelling Approach. In: Brabazon, A., O’Neill, M. (eds) Natural Computing in Computational Finance. Studies in Computational Intelligence, vol 185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-95974-8_7

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  • DOI: https://doi.org/10.1007/978-3-540-95974-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-95973-1

  • Online ISBN: 978-3-540-95974-8

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