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Measuring, Forecasting and Explaining Time Varying Liquidity in the Stock Market

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  • Robert F. Engle
  • Joe Lange

Abstract

The paper proposes a new measure, VNET, of market liquidity which directly measures the depth of the market. The measure is constructed from the excess volume of buys or sells during a market event defined by a price movement. As this measure varies over time, it can be forecast and explained. Using TORQ data, it is found that market depth varies positively but less than proportionally with past volume and negatively with the number of transactions. Both findings suggest that over time high volumes are associated with an influx of informed traders and reduce market liquidity. High expected volatility as measured by the ACD model of Engle and Russell (1995) and wide spreads both reduce expected depth. If the asymmetric trades are transacted in shorter than expected times, the costs will be greater giving an estimate of the value of patience.

Suggested Citation

  • Robert F. Engle & Joe Lange, 1997. "Measuring, Forecasting and Explaining Time Varying Liquidity in the Stock Market," NBER Working Papers 6129, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:6129
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Persaud, Avinash, 2002. "Liquidity Black Holes: And Why Modern Financial Regulation in Developed Countries is making Short-Term Capital Flows to Developing Countries Even More Volatile," WIDER Working Paper Series 031, World Institute for Development Economic Research (UNU-WIDER).
    2. Toni Gravelle, 1999. "Liquidity of the Government of Canada Securities Market: Stylised Facts and Some Market Microstructure Comparisons to the United States Treasury Market," CGFS Papers chapters,in: Bank for International Settlements (ed.), Market Liquidity: Research Findings and Selected Policy Implications, volume 11, pages 1-37 Bank for International Settlements.
    3. Apergis, Nicholas & Voliotis, Dimitrios, 2015. "Spillover effects between lit and dark stock markets: Evidence from a panel of London Stock Exchange transactions," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 101-106.
    4. Schmidt, Anatoly B., 2000. "Modeling the birth of a liquid market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 479-485.
    5. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Moorad Choudhry, 2010. "Measuring bond market liquidity: devising a composite aggregate liquidity score," Applied Financial Economics, Taylor & Francis Journals, vol. 20(12), pages 955-973.
    7. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    8. Jun Muranaga, 1999. "Dynamics of Market Liquidity of Japanese Stocks: An Analysis of Tick-by-Tick Data of the Tokyo Stock Exchange," CGFS Papers chapters,in: Bank for International Settlements (ed.), Market Liquidity: Research Findings and Selected Policy Implications, volume 11, pages 1-25 Bank for International Settlements.
    9. Ghysels, Eric & Gourieroux, Christian & Jasiak, Joann, 2004. "Stochastic volatility duration models," Journal of Econometrics, Elsevier, vol. 119(2), pages 413-433, April.
    10. Michael J. Fleming, 2003. "Measuring treasury market liquidity," Economic Policy Review, Federal Reserve Bank of New York, issue Sep, pages 83-108.
    11. Engle, Robert F. & Patton, Andrew J., 2004. "Impacts of trades in an error-correction model of quote prices," Journal of Financial Markets, Elsevier, vol. 7(1), pages 1-25, January.
    12. 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.
    13. Tapia Torres, Miguel Ángel & Escribano Sáez, Álvaro & Pascual, Roberto, 1999. "How does liquidity behave? A multidimensional analysis of NYSE stocks," DEE - Working Papers. Business Economics. WB 6433, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    14. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2009. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 777-792, December.
    15. Robert F. Engle & Asger Lunde, 2003. "Trades and Quotes: A Bivariate Point Process," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(2), pages 159-188.
    16. Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, Reading University.
    17. María-Dolores, Ramón, 1999. "Variaciones en el tipo de intervención del banco de España: Un análisis mediante un enfoque alternativo," DE - Documentos de Trabajo. Economía. DE 3895, Universidad Carlos III de Madrid. Departamento de Economía.

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