Financial econometric analysis at ultra-high frequency: Data handling concerns
AbstractThe financial econometrics literature on Ultra High-Frequency Data (UHFD) has been growing steadily in recent years. However, it is not always straightforward to construct time series of interest from the raw data and the consequences of data handling procedures on the subsequent statistical analysis are not fully understood. Some results could be sample or asset specific and in this paper we address some of these issues focussing on the data produced by the New York Stock Exchange, summarizing the structure of their TAQ ultra high-frequency dataset. We review and present a number of methods for the handling of UHFD, and explain the rationale and implications of using such algorithms. We then propose procedures to construct the time series of interest from the raw data. Finally, we examine the impact of data handling on statistical modeling within the context of financial durations ACD models.
Download InfoIf 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 51 (2006)
Issue (Month): 4 (December)
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
Other versions of this item:
- Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
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.:
- Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
- BAUWENS, Luc & ROMBOUTS, Jeroen V.K., .
CORE Discussion Papers RP
-1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000.
"A Comparison of Financial Duration Models via Density Forecasts,"
Econometric Society World Congress 2000 Contributed Papers
0810, Econometric Society.
- Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
- Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2004. "A comparison of financial duration models via density forecast," ULB Institutional Repository 2013/136218, ULB -- Universite Libre de Bruxelles.
- BAUWENS , Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2000. "A comparison of financial duration models via density forecasts," CORE Discussion Papers 2000060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- BAUWENS, Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, . "A comparison of financial duration models via density forecasts," CORE Discussion Papers RP -1746, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Boehmer, Ekkehart & Grammig, Joachim & Theissen, Erik, 2007.
"Estimating the probability of informed trading--does trade misclassification matter?,"
Journal of Financial Markets,
Elsevier, vol. 10(1), pages 26-47, February.
- Joachim Grammig & Erik Theissen, 2002. "Estimating the Probability of Informed Trading - Does Trade Misclassification Matter?," Bonn Econ Discussion Papers bgse37_2002, University of Bonn, Germany.
- Joachim Grammig & Erik Theissen, 2003. "Estimating the Probability of Informed Trading - Does Trade Misclassification Matter?," University of St. Gallen Department of Economics working paper series 2003 2003-01, Department of Economics, University of St. Gallen.
- Sofianos, George & Werner, Ingrid M., 2000. "The trades of NYSE floor brokers," Journal of Financial Markets, Elsevier, vol. 3(2), pages 139-176, May.
- Oomen, Roel C.A., 2006. "Properties of Realized Variance Under Alternative Sampling Schemes," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 219-237, April.
- Blume, Marshall E & Goldstein, Michael A, 1997. " Quotes, Order Flow, and Price Discovery," Journal of Finance, American Finance Association, vol. 52(1), pages 221-44, March.
- W. Breymann & A. Dias & P. Embrechts, 2003. "Dependence structures for multivariate high-frequency data in finance," Quantitative Finance, Taylor & Francis Journals, vol. 3(1), pages 1-14.
- Madhavan, Ananth & Sofianos, George, 1998. "An empirical analysis of NYSE specialist trading," Journal of Financial Economics, Elsevier, vol. 48(2), pages 189-210, May.
- 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.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, Elsevier.
- 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.
- 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.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral 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: (Zhang, Lei).
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.