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The Budapest liquidity measure and the price impact function

Author

Listed:
  • Gyarmati, Ákos
  • Lublóy, Ágnes
  • Váradi, Kata

Abstract

During the 2007/2008 global economic crisis, market liquidity became an important issue both on the field of theoretical finance and in practice. In theory market liquidity is usually being modeled with price impact functions. In this study we show how the price impact function can be estimated from order book data. Our estimation is based on the Budapest Liquidity Measure (BLM) which is a liquidity measure that captures the transaction cost nature of liquidity. The main outcome of this paper is a method with which market participants can easily estimate price impact functions. This is of major importance, as the price impact function can be a useful tool during a dynamic portfolio optimization process. The price impact functions can help investors in their trading decisions.

Suggested Citation

  • Gyarmati, Ákos & Lublóy, Ágnes & Váradi, Kata, 2012. "The Budapest liquidity measure and the price impact function," MPRA Paper 40339, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:40339
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    References listed on IDEAS

    as
    1. Martin D.D. Evans & Richard K. Lyons, 2017. "Order Flow and Exchange Rate Dynamics," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 6, pages 247-290, World Scientific Publishing Co. Pte. Ltd..
    2. P. Weber & B. Rosenow, 2005. "Order book approach to price impact," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 357-364.
    3. Sergei Maslov & Mark Mills, 2001. "Price fluctuations from the order book perspective - empirical facts and a simple model," Papers cond-mat/0102518, arXiv.org.
    4. Lublóy, Ágnes & Gyarmati, Ákos & Váradi, Kata, 2012. "Virtuális árhatás a Budapesti Értéktőzsdén [Virtual price effects on the Budapest stock exchange]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 508-539.
    5. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2006. "Institutional Investors and Stock Market Volatility," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 461-504.
    6. Challet, Damien & Stinchcombe, Robin, 2001. "Analyzing and modeling 1+1d markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 300(1), pages 285-299.
    7. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June.
    8. Vasiliki Plerou & Parameswaran Gopikrishnan & Xavier Gabaix & H. Eugene Stanley, 2001. "Quantifying Stock Price Response to Demand Fluctuations," Papers cond-mat/0106657, arXiv.org.
    9. Kutas, Gábor & Végh, Richárd, 2005. "A Budapest Likviditási Mérték bevezetéséről. A magyar részvények likviditásának összehasonlító elemzése a budapesti, a varsói és a londoni értéktőzsdéken [Introduction of the Budapest Liquidity Mea," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 686-711.
    10. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. "An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    11. J. Doyne Farmer & Laszlo Gillemot & Fabrizio Lillo & Szabolcs Mike & Anindya Sen, 2004. "What really causes large price changes?," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 383-397.
    12. Kempf, Alexander & Korn, Olaf, 1999. "Market depth and order size1," Journal of Financial Markets, Elsevier, vol. 2(1), pages 29-48, February.
    13. Maslov, Sergei & Mills, Mark, 2001. "Price fluctuations from the order book perspective—empirical facts and a simple model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 234-246.
    14. Marcus Lim & Richard Coggins, 2005. "The immediate price impact of trades on the Australian Stock Exchange," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 365-377.
    15. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    16. Niemeyer, Jonas & Sandås, Patrik, 1995. "An Empirical Analysis of the Trading Structure at the Stockholm Stock Exchange," SSE/EFI Working Paper Series in Economics and Finance 44, Stockholm School of Economics.
    17. Carl Hopman, 2007. "Do supply and demand drive stock prices?," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 37-53.
    18. Barclay, Michael J. & Warner, Jerold B., 1993. "Stealth trading and volatility : Which trades move prices?," Journal of Financial Economics, Elsevier, vol. 34(3), pages 281-305, December.
    19. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2003. "Master curve for price-impact function," Nature, Nature, vol. 421(6919), pages 129-130, January.
    20. Marc Potters & Jean-Philippe Bouchaud, 2002. "More statistical properties of order books and price impact," Science & Finance (CFM) working paper archive 0210710, Science & Finance, Capital Fund Management.
    21. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2010. "The Price Impact of Order Book Events," Papers 1011.6402, arXiv.org, revised Apr 2011.
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    More about this item

    Keywords

    market liquidity; price impact function; liquidity measure;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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