Advertisement

Heterogeneous Beliefs and Quote Transparency in an Order-Driven Market

  • Polina KovalevaEmail author
  • Giulia Iori
Chapter

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.

Keywords

Abnormal Return Limit Order Order Book Market Order Artificial Market 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Biais, B., Hillion, P., & Spatt, C. (1995). An empirical analysis of the limit order book and the order flow in the Paris Bourse. The Journal of Finance, 50(5), 1655–1689.Google Scholar
  2. Bouchaud, J.-P., Mezard, M., & Potters, M. (2002). Statistical properties of stock order books: empirical results and models. Quantitative Finance, 2(4), 251–256.CrossRefGoogle Scholar
  3. Chiarella, C., Iori, G., & Perelló, J. (2009). The impact of heterogeneous trading rules on the limit order book and order flows. Journal of Economic Dynamics & Control, 33(3), 525–537.CrossRefGoogle Scholar
  4. Chordia, T., Roll, R., & Subrahmanyam, A. (2002). Order imbalance, liquidity, and market returns. Journal of Financial Economics, 65(1), 111–130.CrossRefGoogle Scholar
  5. Hall, A. D., & Hautsch, N. (2006). Order aggressiveness and order book dynamics. Empirical Economics, 30(4), 973–1005.CrossRefGoogle Scholar
  6. Hasbrouck, J., & Saar, G. (2009). Technology and liquidity provision: The blurring of traditional definitions. Journal of Financial Markets, 12(2), 143172.CrossRefGoogle Scholar
  7. Kovaleva, P., & Iori, G. (2014). The impact of reduced pre-trade transparency regimes on market quality.Google Scholar
  8. Lillo, F., & Farmer, J. D. (2004). The long memory of the efficient market. Studies in Nonlinear Dynamics & Econometrics, 8(3), 1–32.CrossRefGoogle Scholar
  9. Lo, A. J. (1991). Long-term memory in stock market prices. Econometrica, 59(5), 1279–1313.CrossRefGoogle Scholar
  10. Lo, I., & Sapp, S. G. (2005). Order submission: The choice between limit and market orders. Working paper 2005–42, Bank of Canada.Google Scholar
  11. Majois, C. (2010). Order aggressiveness and the diagonal effect in experimental double auction markets. Economics Letters, 107(2), 304–309.CrossRefGoogle Scholar
  12. Mike, S., & Farmer, J. D. (2008). An empirical behavioral model of liquidity and volatility. Journal of Economic Dynamics and Control, 32(1), 200–234.CrossRefGoogle Scholar
  13. Ranaldo, A. (2004). Order aggressiveness in limit order book markets. Journal of Financial Markets, 7(1), 53–74.CrossRefGoogle Scholar
  14. Verardo, M. (2009). Heterogeneous beliefs and momentum profits. Journal of Financial and Quantitative Analysis, 44(4), 795–822.CrossRefGoogle Scholar
  15. Yamamoto, R. (2011). Order aggressiveness, pre-trade transparency, and long memory in an order-driven market. Journal of Economic Dynamics and Control, 35(11), 1938–1963.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of EconomicsCity UniversityLondonUK

Personalised recommendations