Hostname: page-component-7b9c58cd5d-hpxsc Total loading time: 0 Render date: 2025-03-16T16:21:19.259Z Has data issue: false hasContentIssue false
  • English
  • Français

Price efficiency and trading behavior in limit order markets with competing insiders

Published online by Cambridge University Press:  14 March 2025

Thomas Stöckl
Thomas Stöckl*
Affiliation:
Department of Banking and Finance, Innsbruck University, Universitätsstrasse 15, 6020 Innsbruck, Austria
*
thomas.stoeckl@uibk.ac.at
Get access Rights & Permissions [Opens in a new window]

Abstract

We study price efficiency and trading behavior in laboratory limit order markets with asymmetrically informed traders. Markets differ in the number of insiders present and in the subset of traders who receive information about the number of insiders present. We observe that price efficiency (i) is the higher the higher the number of insiders in the market but (ii) is unaffected by changes in the subset of traders who know about the number of insiders present. (iii) Independent of the number of insiders, price efficiency increases gradually over time. (iv) The insiders’ information is reflected in prices via limit (market) orders if the asset’s value is inside (outside) the bid-ask spread. (v) In situations where limit and market orders yield positive profits, insiders clearly prefer market orders, indicating a strong desire for immediate transactions.

Keywords

InsiderCompetitionAsset marketPrice efficiencyTrading behaviorExperimental economics

JEL classification

G12: Asset Pricing • Trading Volume • Bond Interest Rates G14: Information and Market Efficiency • Event Studies • Insider Trading C92: Laboratory, Group Behavior D82: Asymmetric and Private Information • Mechanism Design
Type
Original Paper
Information
Experimental Economics , Volume 17 , Issue 2 , June 2014 , pp. 314 - 334
Copyright
Copyright © 2013 Economic Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Electronic Supplementary Material The online version of this article (doi:https://doi.org/10.1007/s10683-013-9369-5) contains supplementary material, which is available to authorized users.

References

Anand, A., Chakravarty, S., & Martell, T. (2005). Empirical evidence on the evolution of liquidity. Journal of Financial Markets, 8, 289–309. 10.1016/j.finmar.2005.03.001CrossRefGoogle Scholar
Barner, M., Feri, F., & Plott, C. R. (2005). On the microstructure of price determination and information aggregation with sequential and asymmetric information arrival in an experimental asset market. Annals of Finance, 1, 1–36. 10.1007/s10436-004-0005-4CrossRefGoogle Scholar
Bloomfield, R. J., O’Hara, M., & Saar, G. (2005). The “make or take” decision in an electronic market: evidence on the evolution of liquidity. Journal of Financial Economics, 75, 165–199. 10.1016/j.jfineco.2004.07.001CrossRefGoogle Scholar
Bossaerts, P., Frydman, C., & Ledyard, J. (2013). The speed of information revelation and eventual price quality in markets with insiders: comparing two theories. Review of Finance, forthcoming, 1–22. doi:10.1093/rof/rfs049.CrossRefGoogle Scholar
Bruguier, A. J., Quartz, S. R., & Bossaerts, P. (2010). Exploring the nature of “trader intuition”. The Journal of Finance, 65(5), 1703–1723. 10.1111/j.1540-6261.2010.01591.xCrossRefGoogle Scholar
Camerer, C., & Weigelt, K. (1991). Information mirages in experimental asset markets. The Journal of Business, 64, 463–493. 10.1086/296548CrossRefGoogle Scholar
Chakravarty, S., & Holden, C. W. (1995). An integrated model of market and limit orders. Journal of Financial Intermediation, 4, 213–241. 10.1006/jfin.1995.1010CrossRefGoogle Scholar
Easley, D., & O’Hara, M. (1987). Price, trade size, and information in securities markets. Journal of Financial Economics, 19, 69–90. 10.1016/0304-405X(87)90029-8CrossRefGoogle Scholar
Fischbacher, U. (2007). z-tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171–178. 10.1007/s10683-006-9159-4CrossRefGoogle Scholar
Friedman, D., Harrison, G. W., & Salmon, J. W. (1984). The informational efficiency of experimental asset markets. Journal of Political Economy, 92(3), 349–408. 10.1086/261233CrossRefGoogle Scholar
Goettler, R. L., Parlour, C. A., & Rajan, U. (2009). Informed traders and limit order markets. Journal of Financial Economics, 93, 67–87. 10.1016/j.jfineco.2008.08.002CrossRefGoogle Scholar
Gould, M. D., Porter, M. A., Williams, S., McDonald, M., Fenn, D. J., & Howison, S. D. (2013). Limit order books (Working paper). arXiv: 1012.0349v4 [q-fin.TR]. 1 Apr 2013.Google Scholar
Greiner, B. (2004). Forschung und wissenschaftliches Rechnen 2003, An online recruitment system for economic experiments. GWDG Bericht 63. Gesellschaft fuer Wissenschaftliche Datenverarbeitung, Goettingen, 79–93.Google Scholar
Grossman, S. J., & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. The American Economic Review, 70, 393–408.Google Scholar
Harris, L. (1998). Optimal dynamic order submission strategies in some stylized trading problems. Financial Markets, Institutions & Instruments, 7(2), 1–76. 10.1111/1468-0416.00019CrossRefGoogle Scholar
Holden, C. W., & Subrahmanyam, A. (1992). Long-lived private information and imperfect competition. The Journal of Finance, 47(1), 247–270. 10.1111/j.1540-6261.1992.tb03985.xGoogle Scholar
Huber, J., Angerer, M., & Kirchler, M. (2011). Experimental asset markets with endogenous choice of costly information. Experimental Economics, 14, 223–240. 10.1007/s10683-010-9264-2CrossRefGoogle Scholar
Huck, S., Norman, H.-T., & Oechssler, J. (2004). Two are few and four are many: number effects in experimental oligopolies. Journal of Economic Behavior & Organisation, 53, 435–446. 10.1016/j.jebo.2002.10.002CrossRefGoogle Scholar
Kaniel, R., & Liu, H. (2006). So what orders do informed traders use?. Journal of Business, 79(4), 1867–1913. 10.1086/503651CrossRefGoogle Scholar
Kirchler, M., Huber, J., & Stöckl, T. (2012). Thar she bursts—reducing confusion reduces bubbles. The American Economic Review, 102(2), 865–883. 10.1257/aer.102.2.865CrossRefGoogle Scholar
Kyle, R. A. (1985). Continuous auctions and insider trading. Econometrica, 53, 1315–1335. 10.2307/1913210CrossRefGoogle Scholar
Meulbroek, L. K. (1992). An empirical analysis of illegal insider trading. The Journal of Finance, 47(5), 1661–1699. 10.1111/j.1540-6261.1992.tb04679.xCrossRefGoogle Scholar
Nöth, M., & Weber, M. (1996). Insidererkennung in experimentellen märkten. Zeitschrift für Betriebswirtschaftliche Forschung, 48, 959–982.Google Scholar
Palfrey, T. R., & Wang, S. W. (2012). Speculative overpricing in asset markets with information flows. Econometrica, 80(5), 1937–1976. 10.3982/ECTA8781Google Scholar
Parlour, C. A., & Seppi, D. J. (2008). Limit order markets: a survey. Handbook of financial intermediation and banking, Amsterdam: Elsevier Science 63–96. 10.1016/B978-044451558-2.50007-6CrossRefGoogle Scholar
Petersen, M. A. (2009). Estimating standard errors in finance panel data sets: comparing approaches. The Review of Financial Studies, 22(1), 435–480. 10.1093/rfs/hhn053CrossRefGoogle Scholar
Plott, C., & Sunder, S. (1982). Efficiency of experimental security markets with insider information: an application of rational-expectations models. Journal of Political Economy, 90, 663–698. 10.1086/261084CrossRefGoogle Scholar
Schnitzlein, C. R. (2002). Price formation and market quality when the number and presence of insiders is unknown. The Review of Financial Studies, 15(4), 1077–1109. 10.1093/rfs/15.4.1077CrossRefGoogle Scholar
Smith, (1982). Markets as economizers of information: experimental examination of the ‘hayek hypothesis’. Economic Inquiry, 20, 165–179. 10.1111/j.1465-7295.1982.tb01149.xCrossRefGoogle Scholar
Supplementary material: File

Stöckl supplementary material

ckl supplementary material
Download Stöckl supplementary material(File)
File 1.7 MB