Journal of Information Technology

, Volume 32, Issue 3, pp 283–296 | Cite as

High-frequency trading and its role in fragmented markets

Research Article

Abstract

Securities trading underwent a major transformation within the last decade. This transformation was mainly driven by the regulatory induced fragmentation and by the increase of high-frequency trading (HFT). On the basis of the electronic market hypothesis, which poses that coordination costs decline when markets become automated, and the efficient market hypothesis in its semi-strong form, we study the effect of HFT on market efficiency in the European fragmented market landscape. In doing so, we further incorporate the realm of financialization, which criticizes the increase in transaction speed. By conducting a long-term analysis of CAC 40 securities, we find that HFT increases market efficiency by leveling midpoints between Euronext Paris and Bats Chi-X Europe. On the basis of a cross-country event study, we analyze the effect of the German HFT Act. We observe that the midpoint dispersion of blue chip securities between the two leading venues Deutsche Boerse and Bats Chi-X Europe increased. We conclude that HFT increases market efficiency in the European market landscape by transmitting information between distant markets.

Keywords

electronic market hypothesis high-frequency trading market efficiency regulation securities trading 

References

  1. Aalbers, M. B. (2015). Corporate Financialization. In N. Castree (Ed.), The International Encyclopedia of Geography: People, the Earth, Environment, and Technology. Oxford: Wiley.Google Scholar
  2. Amihud, Y. (2002). Illiquidity and Stock Returns: Cross-Section and Time-Series Effects. Journal of Financial Markets, 5(1), 31–56.CrossRefGoogle Scholar
  3. Bakos, J. Y. (1991). A Strategic Analysis of Electronic Marketplaces. MIS Quarterly, 15(3), 295–310.CrossRefGoogle Scholar
  4. Baltagi, B. H., and Wu, P. X. (1999). Unequally Spaced Panel Data Regressions with AR(1) Disturbances. Econometric Theory, 15, 814–823.CrossRefGoogle Scholar
  5. Beccetti, L., Ferrari, M., and Trenta, U. (2014). The Impact of the French Tobin Tax. Journal of Financial Stability, 15, 127–148.CrossRefGoogle Scholar
  6. Brogaard, J., Hendershott, T., and Riordan, R. (2014). High-Frequency Trading and Price Discovery. The Review of Financial Studies, 27(8), 2267–2306.CrossRefGoogle Scholar
  7. Busch, D. (2016). MiFID II: Regulating High Frequency Trading, Other Forms of Algorithmic Trading and Direct Electronic Market Access. Law and Financial Market Review, 10(2), 72–82.CrossRefGoogle Scholar
  8. Carrion, A. (2013). Very Fast Money: High-Frequency Trading on the NASDAQ. Journal of Financial Markets, 16(4), 680–711.CrossRefGoogle Scholar
  9. Chan, K. C., Fong, W.-M., Kho, B.-C., and Stulz, M. R. (1996). Information, Trading and Stock Returns: Lessons from Dually-Listed Securities. Journal of Banking & Finance, 20(7), 1161–1187.CrossRefGoogle Scholar
  10. Chen, H., Chen, H., and Valerio, N. (2003). The Effects of Trading Halts on Price Discovery for NYSE Stocks. Applied Economics, 35(1), 91–97.CrossRefGoogle Scholar
  11. Chlistalla, M. (2011). High Frequency Trading—Better Than its Reputation. [WWW Document] http://www.dbresearch.de/PROD/DBR_INTERNET_EN-PROD/PROD0000000000269468.PDF.
  12. Chlistalla, M., and Lutat, M. (2011). Competition in Securities Markets: The Impact on Liquidity. Financial Markets and Portfolio Management, 25(2), 149–172.CrossRefGoogle Scholar
  13. Daniel, E., and Klimis, G. M. (1999). The Impact of Electronic Commerce on Market Structure: An Evaluation of the Electronic Market Hypothesis. European Management Journal, 17(3), 318–325.CrossRefGoogle Scholar
  14. Degryse, H., de Jong, F., and van Kervel, V. (2015a). The Impact of Dark Trading and Visible Fragmentation on Market Quality. Review of Finance, 19(4), 1587–1622.CrossRefGoogle Scholar
  15. Degryse, H., Tombeur, G., and Wuyts, G. (2015). Two Shades of Opacity: Hidden Orders Versus Dark Trading. Working Paper.Google Scholar
  16. Ende, B., Gomber, P., Lutat, M., and Weber, M. C. (2010). A Methodology to Assess the Benefits of Smart Order Routing. IFIP Advances in Information and Communication Technology, 341, 81–92.CrossRefGoogle Scholar
  17. European Commision. (2016). Taxation of the Financial Sector. [WWW Document]. https://ec.europa.eu/taxation_customs/taxation-financial-sector_en
  18. European Commission. (2004). Directive 2004/39/EC of the European Parliament and of the Council. [WWWDocument] http://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2004:145:0001:0044:EN:PDF
  19. European Commission. (2014). Directive on Markets in Financial Instruments (MiFID 2). [WWW Document] http://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=CELEX:32014L0065&from=EN
  20. European Securities and Markets Authority. (2014). Economic ReportHigh-Frequency-Trading Activity in EU Equity Markets. Retrieved September 30, 2014, [WWW Document] https://www.esma.europa.eu/sites/default/files/library/2015/11/esma20141_-_hft_activity_in_eu_equity_markets.pdf
  21. European Securities and Markets Authority (2016a). Order Duplication and Liquidity Measurement in EU Equity Markets. [WWW Document] https://www.esma.europa.eu/ sites/default/files/library/2016-907_economic_report_on_duplicated_orders.pdf
  22. European Securities and Markets Authority. (2016b). ESMA MiFID Database. [WWW Document] https://www.esma.europa.eu/databases-library/registers-and-data
  23. European Securities and Markets Authority. (2016c). MiFID (II) and MiFIR. [WWW Document] https://www.esma.europa.eu/policy-rules/mifid-ii-and-mifir.
  24. Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383–417.CrossRefGoogle Scholar
  25. Fama, E. F. (1991). Efficient Capital Markets: II. The Journal of Finance, 46(5), 1575–1617.CrossRefGoogle Scholar
  26. Fama, E. F., and MacBeth, J. D. (1973). Risk, Return, and Equilibrium: Empirical Tests. The Journal of Political Economy, 81(3), 607–636.CrossRefGoogle Scholar
  27. Fidessa. (2016). Fidessa Fragmentation Index. [WWW Document] http://fragmentation.fidessa.com/.
  28. Foucault, T., and Menkveld, A. J. (2008). Competition for Order Flow and Smart Order Routing Systems. The Journal of Finance, 63(1), 119–158.CrossRefGoogle Scholar
  29. Friederich, S., and Payne, R. (2015). Order-to-trade Ratios and Market Liquidity. Journal of Banking & Finance, 50, 214–223.CrossRefGoogle Scholar
  30. German High Frequency Trading Act. (2013). Gesetz zur Vermeidung von Gefahren und Missbräuchen im Hochfrequenzhandel in der Fassung der Bekanntmachung vom 14.5.2014. [WWW Document] http://bvai.de/fileadmin/PDFs/DE/Reg._Rahmenbedingungen_Stellungnahmen/Hochfrequenzhandelsgesetz/HFT-Gesetz-final.pdf
  31. Gerig, A. (2012). High-Frequency Trading Synchronizes Prices in Financial Markets. Working Paper.Google Scholar
  32. Gomber, P., and Gsell, M. (2006). Catching Up with Technology—The Impact of Regulatory Changes on ECNs/MTFs and the Trading Venue Landscape in Europe. Competition and Regulation in Network Industries, 1(4), 535–557.CrossRefGoogle Scholar
  33. Gomber, P., Haferkorn, M., Lutat, M., and Zimmermann, K. (2013). The Effect of Single-Stock Circuit Breakers on the Quality of Fragmented Markets. Lecture Notes in Business Information Processing, 135, 71–87.CrossRefGoogle Scholar
  34. Gomber, P., Haferkorn, M., and Zimmermann, K. (2016). Securities Transaction Tax and Market Quality—The Case of France. European Financial Management, 22(2), 313–337.CrossRefGoogle Scholar
  35. Gosnell, T. F., Keown, A. J., and Pinkerton, J. M. (1996). The Intraday Speed of Stock Price Adjustment to Major Dividend Changes: Bid-ask Bounce and Order Flow Imbalances. Journal of Banking & Finance, 20(2), 247–266.CrossRefGoogle Scholar
  36. Groenewold, N., and Kang, K. C. (1993). The Semi-strong Efficiency of the Australian Share Market. Economic Record, 69(4), 405–410.CrossRefGoogle Scholar
  37. Haferkorn, M., and Zimmermann, K. (2015). The German High Frequency Trading Act. In 18th Annual Conference of the Swiss Society for Financial Market Research (SGF 2015). Zurich, Switzerland.Google Scholar
  38. Haferkorn, M., Zimmermann, K., and Siering, M. (2013). The Impact of IT-Based Trading on Securities Markets. In 11th International Conference on Wirtschaftsinformatik (WI2013). Leipzig, Germany.Google Scholar
  39. Hagstroemer, B., and Norden, L. (2013). The Diversity of High-Frequency Traders. Journal of Financial Markets, 16(4), 741–770.CrossRefGoogle Scholar
  40. Hamburger, M. J., and Platt, E. N. (1975). The Expectations Hypothesis and the Efficiency of the Treasury Bill Market. The Review of Economics and Statistics, 57(2), 190–199.CrossRefGoogle Scholar
  41. Hameed, A., and Ahsraf, H. (2009). Stock Market Volatility and Weak-Form Efficiency: Evidence from an Emerging Market. International Journal of Business and Emerging Markets, 1(3), 249–263.CrossRefGoogle Scholar
  42. Harris, L. (2003). Trading and Exchanges: Market Microstructure for Practitioners. New York: Oxford University Press.Google Scholar
  43. Hasbrouck, J., and Saar, G. (2013). Low-Latency Trading. Journal of Financial Markets, 16(4), 646–679.CrossRefGoogle Scholar
  44. He, P. W., Jarnecic, E., and Liu, Y. (2015). The Determinants of Alternative Trading Venue Market Share: Global Evidence from the Introduction of Chi-X. Journal of Financial Markets, 22(1), 27–49.CrossRefGoogle Scholar
  45. Hendershott, T., Jones, C. M., and Menkveld, A. (2011). Does Algorithmic Trading Improve Liquidity? The Journal of Finance, 66(1), 1–33.CrossRefGoogle Scholar
  46. Herfindahl, O. (1950). Concentration in the Steel Industry. New York, US: Columbia University.Google Scholar
  47. Hess, C. M., and Kemerer, C. F. (1994). Computerized Loan Origination Systems: An Industry Case Study of the Electronic Markets Hypothesis. MIS Quarterly, 18(3), 251–275.CrossRefGoogle Scholar
  48. Huang, R. D., and Masulis, R. W. (2003). Trading Activity and Stock Price Volatility: Evidence from the London Stock Exchange. Journal of Empirical Finance, 10(3), 249–269.CrossRefGoogle Scholar
  49. Hudson, R., Dempsey, M., and Keasey, K. (1996). A Note on the Weak form Efficiency of Capital Markets: The Application of Simple Technical Trading Rules to UK Stock Prices-1935 to 1994. Journal of Banking & Finance, 20(6), 1121–1132.CrossRefGoogle Scholar
  50. Hvozdyk, L., and Rustanov, S. (2016). The Effect of Financial Transaction Tax on Market Liquidity and Volatility: An Italian Perspective. International Review of Financial Analysis, 45, 62–78.CrossRefGoogle Scholar
  51. Jain, P. C. (1988). Response of Hourly Stock Prices and Trading Volume to Economic News. The Journal of Business, 61(2), 219–231.CrossRefGoogle Scholar
  52. Jarnecic, E., and Snape, M. (2014). The Provision of Liquidity by High-Frequency Participants. Financial Re- view, 49(2), 371–394.CrossRefGoogle Scholar
  53. Khan, A. Q., and Ikram, S. (2010). Testing Semi-strong form of Efficient Market Hypothesis in Relation to the Impact of Foreign Institutional Investors’ (FII’s) Investments on Indian Capital Market. International Journal of Trade, Economics and Finance, 1(4), 373.CrossRefGoogle Scholar
  54. Kirilenko, A. A., Kyle, A. S., Samadi, M., and Tuzun, T. (2014). The Flash Crash: The Impact of High Frequency Trading on an Electronic Market. [WWW Document] http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1686004
  55. Kolari, J. W., and Pynnönen, S. (2010). Event Study Testing with Cross-Sectional Correlation of Abnormal Returns. Review of Financial Studies, 23(11), 3996–4025.CrossRefGoogle Scholar
  56. Lagoarde-Segot, T. (2015). Diversifying Financial Research: Final Remarks. International Review of Financial Analysis, 41, 28–30.CrossRefGoogle Scholar
  57. Lagoarde-Segot, T. (2016). Financialization: Towards a New Research Agenda. International Review of Financial Analysis. doi:10.1016/j.irfa.2016.03.007.Google Scholar
  58. Lattermann, C., Loos, P., Gomolka, J., Burghof, H.-P., Breuer, A., Gomber, P., et al. (2012). High Frequency Trading—Costs and Benefits in Securities Trading and its Necessity of Regulations. Business & Information Systems Engineering, 4(2), 93–108.CrossRefGoogle Scholar
  59. Lease, R. W., Ronald, C., Masulis, and Page, J. R. (1991). An Investigation of Market Microstructure Impacts on Event Study Returns. The Journal of Finance, 46(4), 1523–1536.CrossRefGoogle Scholar
  60. Leuthold, R. M., and Hartmann, P. A. (1979). A Semi-strong form Evaluation of the Efficiency of the Hog Futures Market. American Journal of Agricultural Economics, 61(3), 482–489.CrossRefGoogle Scholar
  61. Lexology (2012). French Financial Transactions Tax. [WWW Document] http://www.lexology.com/library/detail.aspx?g=733ecb9c-cdc7-4c0e-b581-affd78f8c874.
  62. Longstaff, F. A., and Wang, A. W. (2004). Electricity Forward Prices: A High-Frequency Empirical Analysis. The Journal of Finance, 59(4), 1877–1900.CrossRefGoogle Scholar
  63. Madhavan, A. (2000). Market Microstructure: A Survey. Journal of Financial Markets, 3(3), 205–258.CrossRefGoogle Scholar
  64. Malinova, K., Park, A., and Riordan, R. (2013). Do Retail Traders Suffer from High Frequency Traders? Working Paper Google Scholar
  65. Malone, T. W., Yates, J., and Benjamin, R. I. (1987). Electronic Markets and Electronic Hierarchies. Communication of the ACM 30(6): 484–497. doi:10.1145/214762.214766
  66. McInish, T. H., and Wood, R. A. (1992). An Analysis of Intraday Patterns in Bid/Ask Spreads for NYSE Stocks. The Journal of Finance, 47(2), 753–764.CrossRefGoogle Scholar
  67. Menkveld, A. J. (2013). High Frequency Trading and the New Market Makers. Journal of Financial Markets, 16(4), 712–740.CrossRefGoogle Scholar
  68. Menkveld, A. J., and Zoican, M. A. (2014). Need for Speed? Exchange Latency and Liquidity. Working Paper.Google Scholar
  69. Meyer, S., Wagener, M., and Weinhardt, C. (2015). Politically Motivated Taxes in Financial Markets: The Case of the French Financial Transaction Tax. Journal of Financial Services Research, 47(2), 177–202.CrossRefGoogle Scholar
  70. Odgen, J. P. (1990). Turn-of-Month Evaluations of Liquid Profits and Stock Returns: A Common Explanation for the Monthly and January Effects. The Journal of Finance, 45(4), 1259–1272.CrossRefGoogle Scholar
  71. Riordan, R., and Storkenmaier, A. (2012). Latency, Liquidity and Price Discovery. Journal of Financial Mar- kets, 15(4), 416–437.CrossRefGoogle Scholar
  72. Schlag, C., and Stoll, H. (2005). Price Impacts of Options Volume. Journal of Financial Markets, 8(1), 69–87.CrossRefGoogle Scholar
  73. Security Exchanges Commission. (2005). Regulation NMS. [WWW Document] https://www.sec.gov/rules/final/34-51808.pdf.
  74. Snow, J. (1855). On the Mode of Communication of Cholera. London, UK: John Churchill.Google Scholar
  75. Storkenmaier, A., Wagener, M., and Weinhardt, C. (2012). Public Information in Fragmented Markets. Financial Markets and Portfolio Management, 26(2), 179–215.CrossRefGoogle Scholar
  76. STOXX (2015). EURO STOXX 50 ® Volatility (VSTOXX ® ). [WWW Document] https://www.stoxx.com/index-details?symbol=V2TX.
  77. White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817–838.CrossRefGoogle Scholar
  78. Wooldridge, J. M. (2002). Econometric Analysis of Cross Section and Panel Data. London, England: The MIT Press Cambridge.Google Scholar
  79. Wooldridge, J. M. (2009). Introductory Econometrics: A Modern Approach. San Diego, U.S.: South-Western College Publishing.Google Scholar
  80. Zhang, F. (2010). High-Frequency Trading, Stock Volatility, and Price Discovery. Working Paper. Google Scholar

Copyright information

© Association for Information Technology Trust 2017

Authors and Affiliations

  1. 1.Goethe University FrankfurtFrankfurt am MainGermany

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