IDEAS home Printed from https://ideas.repec.org/p/cte/wbrepe/7084.html
   My bibliography  Save this paper

Stock market microstructure in Spain: a note

Author

Listed:
  • Peña, Juan Ignacio

Abstract

This note addresses some microstructure consequences of the Spanish Stock Exchange Reform on measures of systematic risk of daily asset returns. The Reform modified the trading system, clearing and settlement procedures among other changes. This note focuses on how these events affected systematic risk measures and autocorrelations in a sample of selected stocks. After the Reform significant decreases in autocorrelations and lower biases in the betas are found, suggesting that the Reform had increased market's operational efficiency. However, Banks sector have special features which are explained in terms of trade mechanisms.

Suggested Citation

  • Peña, Juan Ignacio, 1994. "Stock market microstructure in Spain: a note," DEE - Working Papers. Business Economics. WB 7084, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    • Handle: RePEc:cte:wbrepe:7084
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/bitstream/handle/10016/7084/wb942703.pdf?sequence=1
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    2. Cohen, Kalman J. & Hawawini, Gabriel A. & Maier, Steven F. & Schwartz, Robert A. & Whitcomb, David K., 1983. "Friction in the trading process and the estimation of systematic risk," Journal of Financial Economics, Elsevier, vol. 12(2), pages 263-278, August.
    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. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    2. Christoph Kaserer & Niklas Wagner & Ann-Kristin Achleitner, 2005. "Managing Investment Risks of Institutional Private Equity Investors — The Challenge of Illiquidity," Springer Books, in: Michael Frenkel & Markus Rudolf & Ulrich Hommel (ed.), Risk Management, edition 0, pages 259-277, Springer.
    3. Chenglu Jin & Thomas Conlon & John Cotter, 2023. "Co-Skewness across Return Horizons," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1483-1518.
    4. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    5. De Moor, Lieven & Sercu, Piet, 2013. "The smallest firm effect: An international study," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 129-155.
    6. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    7. Chirok Han & Jin Seo Cho & Peter C. B. Phillips, 2011. "Infinite Density at the Median and the Typical Shape of Stock Return Distributions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 282-294, April.
    8. Perron, Pierre & Chun, Sungju & Vodounou, Cosme, 2013. "Sampling interval and estimated betas: Implications for the presence of transitory components in stock prices," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 42-62.
    9. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    10. Christopher Baker & Kanshukan Rajaratnam & Emlyn James Flint, 2016. "Beta estimates of shares on the JSE Top 40 in the context of reference-day risk," Environment Systems and Decisions, Springer, vol. 36(2), pages 126-141, June.
    11. Michel Dubois & Cem Ertur, 1997. "The cost of equity and exchange listing evidence from the French stock market," Working Papers hal-01527157, HAL.
    12. Georgios Mantsios & Stylianos Xanthopoulos, 2016. "The Beta intervalling effect during a deep economic crisis - evidence from Greece," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 9(1), pages 19-26, April.
    13. Mukherjee, Raja & Paul, Satya & Shankar, Sriram, 2018. "Equity home bias—A global perspective from the shrunk frontier," Economic Analysis and Policy, Elsevier, vol. 57(C), pages 9-21.
    14. Chelley-Steeley, Patricia L. & Steeley, James M., 2014. "Portfolio size, non-trading frequency and portfolio return autocorrelation," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 56-77.
    15. S. Sanfelici & M. E. Mancino, 2008. "Covariance estimation via Fourier method in the presence of asynchronous trading and microstructure noise," Economics Department Working Papers 2008-ME01, Department of Economics, Parma University (Italy).
    16. Albert Corhay & Alireza Tourani Rad, 1993. "Return Interval, Firm Size And Systematic Risk On The Dutch Stock Market," Review of Financial Economics, John Wiley & Sons, vol. 2(2), pages 19-28, March.
    17. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    18. Joachim Gassen & Hollis A. Skaife & David Veenman, 2020. "Illiquidity and the Measurement of Stock Price Synchronicity," Contemporary Accounting Research, John Wiley & Sons, vol. 37(1), pages 419-456, March.
    19. Fulvio Corsi & Francesco Audrino, 2012. "Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 591-616, September.
    20. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.

    More about this item

    Keywords

    Market microstructure;

    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:cte:wbrepe:7084. 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: Ana Poveda (email available below). General contact details of provider: http://www.business.uc3m.es/es/index .

    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.