IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models

  • Axel Groß-Klußmann
  • Nikolaus Hautsch

We introduce a long memory autoregressive conditional Poisson (LMACP) model to model highly persistent time series of counts. The model is applied to forecast quoted bid-ask spreads, a key parameter in stock trading operations. It is shown that the LMACP nicely captures salient features of bid-ask spreads like the strong autocorrelation and discreteness of observations. We discuss theoretical properties of LMACP models and evaluate rolling window forecasts of quoted bid-ask spreads for stocks traded at NYSE and NASDAQ. We show that Poisson time series models significantly outperform forecasts from ARMA, ARFIMA, ACD and FIACD models. The economic significance of our results is supported by the evaluation of a trade schedule. Scheduling trades according to spread forecasts we realize cost savings of up to 13 % of spread transaction costs.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2011-044.pdf
Download Restriction: no

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2011-044.

as
in new window

Length: 46 pages
Date of creation: Jul 2011
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2011-044
Contact details of provider: Postal:
Spandauer Str. 1,10178 Berlin

Phone: +49-30-2093-5708
Fax: +49-30-2093-5617
Web page: http://sfb649.wiwi.hu-berlin.de
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  2. Foucault, Thierry & Kadan, Ohad & Kandel, Eugene, 2001. "Limit Order Book as a Market for Liquidity," CEPR Discussion Papers 2889, C.E.P.R. Discussion Papers.
  3. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
  4. René Ferland & Alain Latour & Driss Oraichi, 2006. "Integer-Valued GARCH Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(6), pages 923-942, November.
  5. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
  6. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
  7. Taisei Kaizoji & Thomas Lux, 2006. "Forecasting Volatility and Volume in the Tokyo Stock Market: Long Memory, Fractality and Regime Switching," Working Papers wp06-20, Warwick Business School, Finance Group.
  8. Bollen, Nicolas P. B. & Smith, Tom & Whaley, Robert E., 2004. "Modeling the bid/ask spread: measuring the inventory-holding premium," Journal of Financial Economics, Elsevier, vol. 72(1), pages 97-141, April.
  9. HEINEN, Andréas, 2003. "Modelling time series count data: an autoregressive conditional Poisson model," CORE Discussion Papers 2003062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  10. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
  11. Christian Conrad & Berthold R. Haag, 2006. "Inequality Constraints in the Fractionally Integrated GARCH Model," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 413-449.
  12. Bougerol, Philippe & Picard, Nico, 1992. "Stationarity of Garch processes and of some nonnegative time series," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 115-127.
  13. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  14. Menelaos Karanasos & Zacharias Psaradakis & Martin Sola, 2004. "On the Autocorrelation Properties of Long-Memory GARCH Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 265-282, 03.
  15. Diebold, Francis X. & Rudebusch, Glenn D., 1989. "Long memory and persistence in aggregate output," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 189-209, September.
  16. Chung, Kee H. & Van Ness, Bonnie F. & Van Ness, Robert A., 1999. "Limit orders and the bid-ask spread," Journal of Financial Economics, Elsevier, vol. 53(2), pages 255-287, August.
  17. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.
  18. Konstantinos Fokianos & Anders Rahbek & Dag Tjøstheim, 2008. "Poisson Autoregression," Discussion Papers 08-35, University of Copenhagen. Department of Economics, revised Dec 2008.
  19. Oliver Blaskowitz & Helmut Herwartz, 2009. "Adaptive forecasting of the EURIBOR swap term structure," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 575-594.
  20. 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.
  21. Roberto Pascual & David Veredas, 2009. "What pieces of limit order book information matter in explaining order choice by patient and impatient traders?," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 527-545.
  22. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
  23. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-35, November.
  24. Tina Hviid Rydberg & Neil Shephard, 2002. "Dynamics of trade-by-trade price movements: decomposition and models," OFRC Working Papers Series 2002fe04, Oxford Financial Research Centre.
  25. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 422, October.
  26. Taylor, Nicholas, 2002. "The economic and statistical significance of spread forecasts: Evidence from the London Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 26(4), pages 795-818, April.
  27. Lee, Charles M C & Ready, Mark J, 1991. " Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-46, June.
  28. Engle, Robert F & Patton, Andrew J, 2000. "Impacts of Trades in an Error-Correction Model of Quote Prices," University of California at San Diego, Economics Working Paper Series qt6dm6093f, Department of Economics, UC San Diego.
  29. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
  30. Anand, Amber & Chakravarty, Sugato & Martell, Terrence, 2005. "Empirical evidence on the evolution of liquidity: Choice of market versus limit orders by informed and uninformed traders," Journal of Financial Markets, Elsevier, vol. 8(3), pages 288-308, August.
  31. Harris, Lawrence & Hasbrouck, Joel, 1996. "Market vs. Limit Orders: The SuperDOT Evidence on Order Submission Strategy," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 31(02), pages 213-231, June.
  32. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
  33. 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.
  34. Ranaldo, Angelo, 2004. "Order aggressiveness in limit order book markets," Journal of Financial Markets, Elsevier, vol. 7(1), pages 53-74, January.
  35. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  36. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  37. George, Thomas J & Kaul, Gautam & Nimalendran, M, 1991. "Estimation of the Bid-Ask Spread and Its Components: A New Approach," Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 623-56.
  38. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
  39. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," CFS Working Paper Series 2009/18, Center for Financial Studies (CFS).
  40. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
  41. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 177-210.
  42. Chan, K C & Christie, William G & Schultz, Paul H, 1995. "Market Structure and the Intraday Pattern of Bid-Ask Spreads for NASDAQ Securities," The Journal of Business, University of Chicago Press, vol. 68(1), pages 35-60, January.
  43. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 407-17, October.
  44. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
  45. Parlour, Christine A, 1998. "Price Dynamics in Limit Order Markets," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 789-816.
  46. 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.
  47. Freeland, R. K. & McCabe, B. P. M., 2004. "Forecasting discrete valued low count time series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 427-434.
  48. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
  49. Liudas Giraitis & Remigijus Leipus & Peter M. Robinson & Donatas Surgailis, 2004. "LARCH, leverage, and long memory," LSE Research Online Documents on Economics 294, London School of Economics and Political Science, LSE Library.
  50. Glosten, Lawrence R. & Harris, Lawrence E., 1988. "Estimating the components of the bid/ask spread," Journal of Financial Economics, Elsevier, vol. 21(1), pages 123-142, May.
  51. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2011-044. 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: (RDC-Team)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.