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Heterogeneous Beliefs and Quote Transparency in an Order-Driven Market

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Nonlinear Economic Dynamics and Financial Modelling

Abstract

This chapter investigates the interrelation between pre-trade quote transparency and stylised properties of order-driven markets populated by traders with heterogeneous beliefs. In a modified version of Chiarella et al. (2009) model we address the ability of the artificial stock market to replicate the empirical phenomena detected in financial markets. Our framework captures negative skewness of stock returns and volatility clustering once book depth is visible to traders. Further simulation analysis reveals that full quote transparency contributes to convergence in traders’ actions, while exogenous partial transparency restriction may exacerbate long-range dependencies.

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Notes

  1. 1.

    Although in reality traders may extract additional value from the information on the visible quotes, such as the ID of potential counterparties and guess any hidden volumes, we show below that even tracking the buy-sell imbalance alone generates some interesting patterns.

  2. 2.

    This model bears close resemblance to the framework described in Chiarella et al. (2009) with the imbalance factor in place of chartist. For this reason we only delineate here the key aspects of the traders’ decision-making routine, highlighting the role of order book imbalance. Interested readers are referred to Chiarella et al. (2009) for the demand function derivations and further details on order placement mechanism.

  3. 3.

    All agents have a zero weight of imbalance component \(\nu _2^i=0, \forall i\) in Eq. (2).

  4. 4.

    Higher volatility does not affect the expectations of the trader directly, but alters the region of admissible prices defined by \(p_m\) and \(p^*\). The subinterval of buy prices becomes shorter than the subinterval of sell prices proportional to the total interval length \(p_M-p_m\) when the spot volatility is high. Consequently, it is more likely that the current market price of the security lies in the subinterval of selling prices (above \(p^*\)), and if the trader intends to purchase the asset, he submits a passive buy limit order.

  5. 5.

    In terms of graphical analysis, Fig. 3a and b depict clustering in returns series under the transparent and quasi-transparent regimes, compared to the more monotonous variability of returns in the dark market in Fig. 3c.

  6. 6.

    The results across the two market specifications with some quote visibility are reasonably similar; thus, we present just the estimates for the transparent case.

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Author information

Authors and Affiliations

  1. Department of Economics, City University, Northampton Square, London, EC1V 0HB, UK

    Polina Kovaleva & Giulia Iori

Authors
  1. Polina Kovaleva
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  2. Giulia Iori
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Correspondence to Polina Kovaleva .

Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Bologna, Bologna, Italy

    Roberto Dieci

  2. UTS Business School, University of Technology, Sydney, Sydney, New South Wales, Australia

    Xue-Zhong He

  3. Amsterdam School of Economics, University of Amsterdam, Amsterdam, The Netherlands

    Cars Hommes

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Kovaleva, P., Iori, G. (2014). Heterogeneous Beliefs and Quote Transparency in an Order-Driven Market. In: Dieci, R., He, XZ., Hommes, C. (eds) Nonlinear Economic Dynamics and Financial Modelling. Springer, Cham. https://doi.org/10.1007/978-3-319-07470-2_10

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