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Pre-trade transparency on the Italian Stock Exchange: a trade size model on panel data

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  • C. Lucarelli
  • M. E. Bontempi
  • C. Mazzoli
  • A. G. Quaranta

Abstract

The purpose of this study was to analyze the effects that have been caused by changes in pre-trade transparency upon the behavior of stock traders. We used a trade size model and tested it before, during and after the period when the Italian Stock Exchange introduced a 20-level order book with disaggregated orders. Tick by tick data of the whole set of stocks (up to 277) listed on the Italian Stock Exchange were studied through fixed-effects panel models, within intra day (every 30 minutes and 150 minutes) and daily time frames. Our results indicate that order flows, bidask spreads, levels of risk and some information events differentially affect trade sizes when investors receive better information prior to negotiation. Both (intra day) informed and uninformed traders operating in a more transparent market became more reticent, with reduced trades sizes and higher orders cancellations. Moreover, it appears that the higher degree of order book disclosure permits traders to downsize their level of risk aversion; i.e. it reduces the uncertainty that would otherwise result in disrupted trading activity under conditions of information opacity.

Suggested Citation

  • C. Lucarelli & M. E. Bontempi & C. Mazzoli & A. G. Quaranta, 2009. "Pre-trade transparency on the Italian Stock Exchange: a trade size model on panel data," Working Papers 678, Dipartimento Scienze Economiche, Universita' di Bologna.
  • Handle: RePEc:bol:bodewp:678
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    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    4. Biais, Bruno, 1993. "Price Information and Equilibrium Liquidity in Fragmented and Centralized Markets," Journal of Finance, American Finance Association, vol. 48(1), pages 157-185, March.
    5. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    6. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," CERT Discussion Papers 0706, Centre for Economic Reform and Transformation, Heriot Watt University.
    7. Thierry Foucault & Sophie Moinas & Erik Theissen, 2007. "Does Anonymity Matter in Electronic Limit Order Markets?," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1707-1747, 2007 28.
    8. Hasbrouck, Joel, 2007. "Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading," OUP Catalogue, Oxford University Press, number 9780195301649, Decembrie.
    9. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2000. "Commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 56(1), pages 3-28, April.
    10. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    11. Brennan, Michael J & Subrahmanyam, Avanidhar, 1998. "The Determinants of Average Trade Size," The Journal of Business, University of Chicago Press, vol. 71(1), pages 1-25, January.
    12. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    13. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    14. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    15. Amihud, Yakov & Mendelson, Haim, 1980. "Dealership market : Market-making with inventory," Journal of Financial Economics, Elsevier, vol. 8(1), pages 31-53, March.
    16. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    17. Chan, Yue-Cheong, 2000. "The price impact of trading on the stock exchange of Hong Kong," Journal of Financial Markets, Elsevier, vol. 3(1), pages 1-16, February.
    18. Frank Kleibergen & Mark E Schaffer & Frank Windmeijer, 2007. "RANKTEST: Stata module to test the rank of a matrix," Statistical Software Components S456865, Boston College Department of Economics, revised 29 Sep 2020.
    19. Forster, Margaret M. & George, Thomas J., 1992. "Anonymity in securities markets," Journal of Financial Intermediation, Elsevier, vol. 2(2), pages 168-206, June.
    20. Ekkehart Boehmer & Gideon Saar & Lei Yu, 2005. "Lifting the Veil: An Analysis of Pre‐trade Transparency at the NYSE," Journal of Finance, American Finance Association, vol. 60(2), pages 783-815, April.
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