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A Simulation Analysis Of Herding And Unifractal Scaling Behaviour

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  • Steve Phelps
  • Wing Lon Ng

Abstract

We model the financial market using a class of agent‐based models in which agents’ expectations are driven by heuristic forecasting rules (in contrast to the rational expectations models used in traditional theories of financial markets). We show that, within this framework, we can reproduce unifractal scaling with respect to three well‐known power laws relating (i) moments of the absolute price change to the time‐scale over which they are measured, (ii) magnitude of returns with respect to their probability and (iii) the autocorrelation of absolute returns with respect to lag. In contrast to previous studies, we systematically analyse all three power laws simultaneously using the same underlying model by making observations at different time‐scales and higher moments. We show that the first two scaling laws are remarkably robust to the time‐scale over which observations are made, irrespective of the model configuration. However, in contrast to previous studies, we show that herding may explain why long memory is observed at all frequencies. Copyright © 2013 John Wiley & Sons, Ltd.

Suggested Citation

  • Steve Phelps & Wing Lon Ng, 2014. "A Simulation Analysis Of Herding And Unifractal Scaling Behaviour," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(1), pages 39-58, January.
    • Handle: RePEc:wly:isacfm:v:21:y:2014:i:1:p:39-58
    DOI: 10.1002/isaf.1346
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    Cited by:

    1. Jackson, Antony & Ladley, Daniel, 2016. "Market ecologies: The effect of information on the interaction and profitability of technical trading strategies," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 270-280.

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