IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v39y2015icp1-14.html
   My bibliography  Save this article

Testing the mixture of distributions hypothesis on target stocks

Author

Listed:
  • Carroll, Rachael
  • Kearney, Colm

Abstract

We test the mixture of distributions hypothesis (MDH) in which equity trading volumes and return volatilities are derived from an unobservable mixing variable, the speed of information flow to the market. Interpreting the public announcement of a takeover offer as a regime-changing firm-specific informational event, we study the daily trading volumes and price volatilities of 190 US targets from four years before the takeover announcement until the conclusion of the bid. We find strong evidence for MDH-consistent positive volume–volatility relationships before and after takeover announcements that are supportive of the applicability of the MDH in the market for corporate control.

Suggested Citation

  • Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
  • Handle: RePEc:eee:intfin:v:39:y:2015:i:c:p:1-14
    DOI: 10.1016/j.intfin.2015.05.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1042443115000566
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ané, Thierry & Ureche-Rangau, Loredana, 2008. "Does trading volume really explain stock returns volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 216-235, July.
    2. Shalen, Catherine T, 1993. "Volume, Volatility, and the Dispersion of Beliefs," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 405-434.
    3. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    4. James C. Luu & Martin Martens, 2003. "Testing the mixture‐of‐distributions hypothesis using “realized” volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(7), pages 661-679, July.
    5. Dilip Abreu & Markus K. Brunnermeier, 2003. "Bubbles and Crashes," Econometrica, Econometric Society, vol. 71(1), pages 173-204, January.
    6. Fleming, Jeff & Kirby, Chris, 2011. "Long memory in volatility and trading volume," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1714-1726, July.
    7. Keskinturk, Timur & Er, Sebnem, 2007. "A genetic algorithm approach to determine stratum boundaries and sample sizes of each stratum in stratified sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 53-67, September.
    8. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    9. Schwert, G. William, 1996. "Markup pricing in mergers and acquisitions," Journal of Financial Economics, Elsevier, vol. 41(2), pages 153-192, June.
    10. Eric Girard & Rita Biswas, 2007. "Trading Volume and Market Volatility: Developed versus Emerging Stock Markets," The Financial Review, Eastern Finance Association, vol. 42(3), pages 429-459, August.
    11. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    12. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    13. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.
    14. John M. Maheu & Thomas H. McCurdy, 2004. "News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 755-793, April.
    15. Lobato, Ignacio N & Velasco, Carlos, 2000. "Long Memory in Stock-Market Trading Volume," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 410-427, October.
    16. 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.
    17. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
    18. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    19. Harris, Lawrence, 1986. "Cross-Security Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(1), pages 39-46, March.
    20. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    21. Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2010. "Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.
    22. Richardson, Matthew & Smith, Tom, 1994. "A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(1), pages 101-116, March.
    23. Utpal Bhattacharya, 2008. "The Causes and Consequences of Recent Financial Market Bubbles: An Introduction," Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 3-10, January.
    24. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    25. L. Lin & D. Sornette, 2013. "Diagnostics of rational expectation financial bubbles with stochastic mean-reverting termination times," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 344-365, May.
    26. Lee, Bong-Soo & Rui, Oliver M., 2002. "The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence," Journal of Banking & Finance, Elsevier, vol. 26(1), pages 51-78, January.
    27. Hutson, Elaine, 2000. "Takeover targets and the probability of bid success: Evidence from the Australian market," International Review of Financial Analysis, Elsevier, vol. 9(1), pages 45-65, February.
    28. M. F. Omran & E. McKenzie, 2000. "Heteroscedasticity in stock returns data revisited: volume versus GARCH effects," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 553-560.
    29. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    30. Imbens, Guido W. & Lancaster, Tony, 1996. "Efficient estimation and stratified sampling," Journal of Econometrics, Elsevier, vol. 74(2), pages 289-318, October.
    31. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    32. L. Ureche-Rangau & Q. de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets : the chinese stock market," Post-Print hal-00581618, HAL.
    33. Liesenfeld, Roman, 2001. "A generalized bivariate mixture model for stock price volatility and trading volume," Journal of Econometrics, Elsevier, vol. 104(1), pages 141-178, August.
    34. Lamoureux, Christopher G & Lastrapes, William D, 1994. "Endogenous Trading Volume and Momentum in Stock-Return Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 253-260, April.
    35. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    36. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    37. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    38. Bhagat, Sanjai & Brickley, James A & Loewenstein, Uri, 1987. "The Pricing Effects of Interfirm Cash Tender Offers," Journal of Finance, American Finance Association, vol. 42(4), pages 965-986, September.
    39. T. Ane & L. Ureche-Rangau, 2008. "Does Trading Volume Really Explain Stock Returns Volatility ?," Post-Print hal-00260668, HAL.
    40. Jonathan Fletcher & Andrew Marshall, 2014. "Investor Heterogeneity and the Cross-section of U.K. Investment Trust Performance," Journal of Financial Services Research, Springer;Western Finance Association, vol. 45(1), pages 67-89, February.
    41. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    42. Rachael Carroll & Colm Kearney, 2012. "Do trading volumes explain the persistence of GARCH effects?," Applied Financial Economics, Taylor & Francis Journals, vol. 22(23), pages 1993-2008, December.
    43. Gelman, Sergey & Wilfling, Bernd, 2009. "Markov-switching in target stocks during takeover bids," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 745-758, December.
    44. Brigida, Matthew & Madura, Jeff, 2012. "Sources of target stock price run-up prior to acquisitions," Journal of Economics and Business, Elsevier, vol. 64(2), pages 185-198.
    45. Ackert, Lucy F. & Church, Bryan K. & Englis, Basil, 2002. "The asset allocation decision and investor heterogeneity: a puzzle?," Journal of Economic Behavior & Organization, Elsevier, vol. 47(4), pages 423-433, April.
    46. Loredana Ureche-Rangau & Quiterie de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets: The Chinese stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 779-799.
    47. Marta Regulez & Ainhoa Zarraga, 2002. "Common features between stock returns and trading volume," Applied Financial Economics, Taylor & Francis Journals, vol. 12(12), pages 885-893.
    48. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    49. Amit Goyal & Pedro Santa-Clara, 2003. "Idiosyncratic Risk Matters!," Journal of Finance, American Finance Association, vol. 58(3), pages 975-1008, June.
    50. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    51. Hutson, Elaine & Kearney, Colm, 2001. "Volatility in stocks subject to takeover bids: Australian evidence using daily data," Journal of Empirical Finance, Elsevier, vol. 8(3), pages 273-296, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali M. Kutan & Mehmet E. Yaya, 2016. "Armed conflict and financial and economic risk: evidence from Colombia," Risk Management, Palgrave Macmillan, vol. 18(2), pages 159-187, August.
    2. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Liquidity, surprise volume and return premia in the oil market," Energy Economics, Elsevier, vol. 77(C), pages 93-104.
    3. Jakree Koosakul & Ilhyock Shim, 2017. "The beneficial aspect of FX volatility for market liquidity," BIS Working Papers 629, Bank for International Settlements.

    More about this item

    Keywords

    GARCH models; Takeovers; Target stocks; Volume and volatility;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    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:eee:intfin:v:39:y:2015:i:c:p:1-14. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/locate/intfin .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.