IDEAS home Printed from https://ideas.repec.org/a/pep/journl/v8y2003i2p25-53.html
   My bibliography  Save this article

The Information Content in Trades of Inactive Nasdaq Stocks

Author

Listed:
  • Peter Chen

    (Youngstown State University)

  • Kasing Man

    (Syracuse University)

  • Chunchi Wu

    (Syracuse University)

Abstract

In this paper we analyze the frequency and information content of small Nasdaq stock trades and their impacts on return volatility at the intraday interval. We employ an autoregressive conditional duration (ACD) model to estimate the intensity of the arrival and information content of trades by accounting for the deterministic nature of intraday periodicity and irregular trading intervals in transaction data. We estimate and compare the price duration of thinly and heavily traded stocks to assess the differential information content of stock trades. We find that the number of transactions is negatively correlated with price duration or positively correlated with return volatility. The impact of the number of transactions on price duration or volatility is higher for thinly traded stocks. On the other hand, the persistence of the impact on price duration adjusted for intradaily periodicity is about the same for thinly and heavily traded stocks on average.

Suggested Citation

  • Peter Chen & Kasing Man & Chunchi Wu, 2003. "The Information Content in Trades of Inactive Nasdaq Stocks," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 8(2), pages 25-53, Summer.
  • Handle: RePEc:pep:journl:v:8:y:2003:i:2:p:25-53
    as

    Download full text from publisher

    File URL: http://jefsite.org/RePEc/pep/journl/jef-2003-08-2-d-chen.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    2. Dufour, Alfonso & Engle, Robert F, 1999. "Time and the Price Impact of a Trade," University of California at San Diego, Economics Working Paper Series qt62c0h04j, Department of Economics, UC San Diego.
    3. Miller, Merton H & Muthuswamy, Jayaram & Whaley, Robert E, 1994. "Mean Reversion of Standard & Poor's 500 Index Basis Changes: Arbitrage-Induced or Statistical Illusion?," Journal of Finance, American Finance Association, vol. 49(2), pages 479-513, June.
    4. Foster, F Douglas & Viswanathan, S, 1995. "Can Speculative Trading Explain the Volume-Volatility Relation?," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 379-396, October.
    5. Madhavan, Ananth & Richardson, Matthew & Roomans, Mark, 1997. "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 1035-1064.
    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. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
    8. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    9. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
    10. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
    11. Admati, Anat R & Pfleiderer, Paul, 1989. "Divide and Conquer: A Theory of Intraday and Day-of-the-Week Mean Effects," The Review of Financial Studies, Society for Financial Studies, vol. 2(2), pages 189-223.
    12. repec:bla:jfinan:v:44:y:1989:i:5:p:1115-53 is not listed on IDEAS
    13. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    14. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    15. 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.
    16. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    17. Wu, Chunchi & Xu, Xiaoqing Eleanor, 2000. "Return Volatility, Trading Imbalance and the Information Content of Volume," Review of Quantitative Finance and Accounting, Springer, vol. 14(2), pages 131-153, March.
    18. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    19. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    20. Easley, David & O'Hara, Maureen, 1992. "Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
    21. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," The Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    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. Jinliang Li & Chunchi Wu, 2006. "Daily Return Volatility, Bid-Ask Spreads, and Information Flow: Analyzing the Information Content of Volume," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2697-2740, September.
    2. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
    3. Wong, Woon K. & Tan, Dijun & Tian, Yixiang, 2009. "Informed trading and liquidity in the Shanghai Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 66-73, March.
    4. Berkman, Henk & Koch, Paul D., 2008. "Noise trading and the price formation process," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 232-250, March.
    5. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    6. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    7. Jondeau, Eric & Lahaye, Jérôme & Rockinger, Michael, 2015. "Estimating the price impact of trades in a high-frequency microstructure model with jumps," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 205-224.
    8. 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.
    9. Chen, Tao & Li, Jie & Cai, Jun, 2008. "Information content of inter-trade time on the Chinese market," Emerging Markets Review, Elsevier, vol. 9(3), pages 174-193, September.
    10. Wu, Chunchi & Xu, Xiaoqing Eleanor, 2000. "Return Volatility, Trading Imbalance and the Information Content of Volume," Review of Quantitative Finance and Accounting, Springer, vol. 14(2), pages 131-153, March.
    11. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    12. Nikolaus Hautsch, 1999. "Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions," Finance 9904002, University Library of Munich, Germany.
    13. Bowe, Michael & Hyde, Stuart & McFarlane, Lavern, 2013. "Duration, trading volume and the price impact of trades in an emerging futures market," Emerging Markets Review, Elsevier, vol. 17(C), pages 89-105.
    14. Chung, Kee H. & Li, Mingsheng & McInish, Thomas H., 2005. "Information-based trading, price impact of trades, and trade autocorrelation," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1645-1669, July.
    15. Shafiqur Rahman & Chandrasekhar Krishnamurti & Alice Lee, 2005. "The Dynamics of Security Trades, Quote Revisions, and Market Depths for Actively Traded Stocks," Review of Quantitative Finance and Accounting, Springer, vol. 25(2), pages 91-124, September.
    16. repec:bla:jecsur:v:22:y:2008:i:4:p:711-751 is not listed on IDEAS
    17. Ibrahim, Boulis Maher & Kalaitzoglou, Iordanis Angelos, 2016. "Why do carbon prices and price volatility change?," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 76-94.
    18. 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.
    19. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    20. Abad, David & Pascual, Roberto, 2015. "The friction-free weighted price contribution," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 226-239.
    21. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).

    More about this item

    Keywords

    Information Content; Trading; Inactive Stocks; NASDAQ;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:pep:journl:v:8:y:2003:i:2:p:25-53. 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: Craig Everett (email available below). General contact details of provider: https://edirc.repec.org/data/bapepus.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.