Abstract

Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents’ accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents’ accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option.

Highlights

  • For more than a decade, herd behaviour [1, 2] in financial markets has been the subject of much research [3,4,5,6,7], in parallel with research investigating the phenomenon of stock market

  • We introduce two variants of a trader interaction model resulting in stochastic cascade processes and demonstrate a number of stylised facts of financial returns can be captured by incorporating the cascade processes into a simple financial market model

  • A novelty of the model is in its parametrisation by network coupling probability, which can be viewed as an order parameter for herd behaviour

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Summary

Introduction

For more than a decade, herd behaviour [1, 2] in financial markets has been the subject of much research [3,4,5,6,7], in parallel with research investigating the phenomenon of stock marketPLOS ONE | DOI:10.1371/journal.pone.0151790 March 23, 2016A Financial Market Model. For more than a decade, herd behaviour [1, 2] in financial markets has been the subject of much research [3,4,5,6,7], in parallel with research investigating the phenomenon of stock market.

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