IDEAS home Printed from https://ideas.repec.org/p/zbw/kitwps/129.html
   My bibliography  Save this paper

Trading stocks on blocks: The quality of decentralized markets

Author

Listed:
  • Notheisen, Benedikt
  • Marino, Vincenzo
  • Englert, Daniel
  • Weinhardt, Christof

Abstract

The trust-free nature of blockchain-based systems challenges the role of traditional platform providers and enables the creation of new, intermediary-free markets. Despite the growing number of such markets, the impact of the blockchain's configuration on market outcomes remains unclear. In this study, we utilize order-level data from realworld financial markets to explore the impact of the blockchain parameters block size and block creation time on the quality of decentralized markets. More specifically, we find that increasing the blocks' capacity improves market activity, while higher block frequencies impose a trade-off between higher turnovers and lower trade sizes. In addition, we identify the block creation time and block size as core drivers of daily and intraday liquidity, respectively. In consequence, improving liquidity goes hand in hand with a higher activity. However, the reciprocal relationship between blockchain parameters and the increasing price impact of a block also indicate that faster and bigger blocks are no silver bullet to scale decentralized markets and may facilitate volatility. In total, we contribute an initial, technology-agnostic assessment of the quality of decentralized markets that aims to guide interdisciplinary researchers and innovative practitioners.

Suggested Citation

  • Notheisen, Benedikt & Marino, Vincenzo & Englert, Daniel & Weinhardt, Christof, 2019. "Trading stocks on blocks: The quality of decentralized markets," Working Paper Series in Economics 129, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  • Handle: RePEc:zbw:kitwps:129
    DOI: 10.5445/IR/1000092485
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/194006/1/1067511253.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.5445/IR/1000092485?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jonathan Chiu & Thorsten V Koeppl, 2019. "Blockchain-Based Settlement for Asset Trading," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1716-1753.
    2. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    3. repec:bla:jfinan:v:58:y:2003:i:6:p:2637-2666 is not listed on IDEAS
    4. Huang, Roger D. & Stoll, Hans R., 1996. "Dealer versus auction markets: A paired comparison of execution costs on NASDAQ and the NYSE," Journal of Financial Economics, Elsevier, vol. 41(3), pages 313-357, July.
    5. Harris, Larry, 2002. "Trading and Exchanges: Market Microstructure for Practitioners," OUP Catalogue, Oxford University Press, number 9780195144703.
    6. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    7. Copeland, Thomas E & Galai, Dan, 1983. "Information Effects on the Bid-Ask Spread," Journal of Finance, American Finance Association, vol. 38(5), pages 1457-1469, December.
    8. Madhavan, Ananth, 1992. "Trading Mechanisms in Securities Markets," Journal of Finance, American Finance Association, vol. 47(2), pages 607-641, June.
    9. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    10. Hendershott, Terrence & Moulton, Pamela C., 2011. "Automation, speed, and stock market quality: The NYSE's Hybrid," Journal of Financial Markets, Elsevier, vol. 14(4), pages 568-604, November.
    11. Daniel Fricke & Austin Gerig, 2018. "Too fast or too slow? Determining the optimal speed of financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 18(4), pages 519-532, April.
    12. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    13. Subrahmanyam, Avanidhar, 1994. "Circuit Breakers and Market Volatility: A Theoretical Perspective," Journal of Finance, American Finance Association, vol. 49(1), pages 237-254, March.
    14. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    15. Benjamin Clapham & Kai Zimmermann, 2016. "Price discovery and convergence in fragmented securities markets," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 12(4), pages 381-407, August.
    16. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    17. Charles Cao & Oliver Hansch & Xiaoxin Wang, 2009. "The information content of an open limit‐order book," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(1), pages 16-41, January.
    18. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    19. Jessel, Benjamin & Marshall, Tommy, 2016. "Get Bold with Blockchain," Journal of Financial Transformation, Capco Institute, vol. 43, pages 15-20.
    20. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    21. Hasbrouck, Joel, 1991. "The Summary Informativeness of Stock Trades: An Econometric Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 571-595.
    22. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    23. Benedikt Notheisen & Jacob Benjamin Cholewa & Arun Prasad Shanmugam, 2017. "Trading Real-World Assets on Blockchain," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(6), pages 425-440, December.
    24. Eric Budish & Peter Cramton & John Shim, 2014. "Implementation Details for Frequent Batch Auctions: Slowing Down Markets to the Blink of an Eye," American Economic Review, American Economic Association, vol. 104(5), pages 418-424, May.
    25. David Yermack, 2017. "Corporate Governance and Blockchains," Review of Finance, European Finance Association, vol. 21(1), pages 7-31.
    26. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    27. Randi Næs & Johannes A. Skjeltorp & Bernt Arne Ødegaard, 2011. "Stock Market Liquidity and the Business Cycle," Journal of Finance, American Finance Association, vol. 66(1), pages 139-176, February.
    28. Pagano, Marco & Roell, Ailsa, 1996. "Transparency and Liquidity: A Comparison of Auction and Dealer Markets with Informed Trading," Journal of Finance, American Finance Association, vol. 51(2), pages 579-611, June.
    29. Michael J. Barclay & Terrence Hendershott & D. Timothy McCormick, 2003. "Competition among Trading Venues: Information and Trading on Electronic Communications Networks," Journal of Finance, American Finance Association, vol. 58(6), pages 2637-2665, December.
    30. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    31. Mingfeng Lin & Henry C. Lucas & Galit Shmueli, 2013. "Research Commentary ---Too Big to Fail: Large Samples and the p -Value Problem," Information Systems Research, INFORMS, vol. 24(4), pages 906-917, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vinay Patel, 2015. "Price Discovery in US and Australian Stock and Options Markets," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 27, July-Dece.
    2. Vinay Patel, 2015. "Price Discovery in US and Australian Stock and Options Markets," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 6-2015, January-A.
    3. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    4. Hagströmer, Björn, 2021. "Bias in the effective bid-ask spread," Journal of Financial Economics, Elsevier, vol. 142(1), pages 314-337.
    5. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.
    6. Medina, Vicente & Pardo, Ángel & Pascual, Roberto, 2014. "The timeline of trading frictions in the European carbon market," Energy Economics, Elsevier, vol. 42(C), pages 378-394.
    7. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.
    8. Haas, Marlene & Khapko, Mariana & Zoican, Marius, 2021. "Speed and learning in high-frequency auctions," Journal of Financial Markets, Elsevier, vol. 54(C).
    9. Philip, R., 2020. "Estimating permanent price impact via machine learning," Journal of Econometrics, Elsevier, vol. 215(2), pages 414-449.
    10. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
    11. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    12. Chordia, Tarun & Sarkar, Asani & Subrahmanyam, Avanidhar, 2005. "The Joint Dynamics of Liquidity, Returns, and Volatility Across Small and Large Firms," University of California at Los Angeles, Anderson Graduate School of Management qt6z81z2wc, Anderson Graduate School of Management, UCLA.
    13. Marlene Haas & Marius Andrei Zoican, 2016. "Beyond the Frequency Wall: Speed and Liquidity on Batch Auction Markets," Post-Print hal-01484805, HAL.
    14. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    15. Aliyev, Nihad & Huseynov, Fariz & Rzayev, Khaladdin, 2022. "Algorithmic trading and investment-to-price sensitivity," LSE Research Online Documents on Economics 118844, London School of Economics and Political Science, LSE Library.
    16. Thierry Foucault & Roman Kozhan & Wing Wah Tham, 2017. "Toxic Arbitrage," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1053-1094.
    17. Markus Baldauf & Joshua Mollner, 2015. "High-Frequency Trading and Market Performance," Discussion Papers 15-017, Stanford Institute for Economic Policy Research.
    18. Wang, Junbo & Wu, Chunchi, 2015. "Liquidity, credit quality, and the relation between volatility and trading activity: Evidence from the corporate bond market," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 183-203.
    19. Jagjeev Dosanjh, 2017. "Exchange Initiatives and Market Efficiency: Evidence from the Australian Securities Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2017, January-A.
    20. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.

    More about this item

    Keywords

    Decentralized markets; Blockchain; Market quality; Market design; Market engineering; FinTech;
    All these keywords.

    JEL classification:

    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • N2 - Economic History - - Financial Markets and Institutions
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:kitwps:129. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/fwkitde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.