Modeling Trade Direction
AbstractThe problem of classifying trades as buys or sells is examined. I propose estimated quotes for midpoint and bid/ask tests and a modeling approach to classification. Prevailing quotes are estimated using flexible approximations to the distribution for delays of quotes relative to trade timestamps. Classification is done by a generalized linear model which includes improved versions of midpoint, tick, and bid/ask tests. The model also considers the relative strengths of these tests, can account for market microstructure peculiarities, and allows for autocorrelations and cross-correlations in trade direction. The correlation modeling corrects for pseudoreplication, yielding more accurate standard errors and fixed effect estimates. Further, the model estimates probabilities of correct classification. The model is compared to various trade classification methods using a sample of 2,836 domestic US stocks from an unexplored, recent, and readily-available dataset. Out of sample, modeled classifications are 1-2% more accurate overall than current methods; this improvement is consistent across dates, sectors, and locations relative to the inside quote. For Nasdaq and NYSE stocks, 1% and 1.3% of the improvement comes from using relative strengths of the various tests; 0.9% and 0.7% of the improvement, respectively, comes from using some form of estimated quotes. For AMEX stocks, a 0.4% improvement is attributed to using a lagged version of the bid/ask test. I also find indications of short- and ultra-short-term alpha.
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.
Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 10209.
Date of creation: Aug 2008
Date of revision:
market microstructure; trade classification; generalized linear mixed model; ultra-high-frequency data analysis;
Other versions of this item:
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
This paper has been announced in the following NEP Reports:
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.:
- Kauermann G. & Carroll R.J., 2001. "A Note on the Efficiency of Sandwich Covariance Matrix Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1387-1396, December.
- M. Hashem Pesaran, 2004.
"Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure,"
CESifo Working Paper Series
1331, CESifo Group Munich.
- M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
- Stoll, Hans R. & Schenzler, Christoph, 2006. "Trades outside the quotes: Reporting delay, trading option, or trade size?," Journal of Financial Economics, Elsevier, vol. 79(3), pages 615-653, March.
- Hans R. Stoll, 2006. "Electronic Trading in Stock Markets," Journal of Economic Perspectives, American Economic Association, vol. 20(1), pages 153-174, Winter.
- Peterson, Mark & Sirri, Erik, 2003. "Evaluation of the biases in execution cost estimation using trade and quote data," Journal of Financial Markets, Elsevier, vol. 6(3), pages 259-280, May.
- Boehmer, Ekkehart, 2005. "Dimensions of execution quality: Recent evidence for US equity markets," Journal of Financial Economics, Elsevier, vol. 78(3), pages 553-582, December.
- Olivier Vergote, 2005. "How to Match Trades and Quotes for Nyse Stocks?," Center for Economic Studies - Discussion papers ces0510, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
- Henker, Thomas & Wang, Jian-Xin, 2006. "On the importance of timing specifications in market microstructure research," Journal of Financial Markets, Elsevier, vol. 9(2), pages 162-179, May.
- 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.
- Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
- Keim, Donald B & Madhaven, Ananth, 1996. "The Upstairs Market for Large-Block Transactions: Analysis and Measurement of Price Effects," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 1-36.
- Ellis, Katrina & Michaely, Roni & O'Hara, Maureen, 2000. "The Accuracy of Trade Classification Rules: Evidence from Nasdaq," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(04), pages 529-551, December.
- Steven Caudill & Beverly Marshall & Jacqueline Garner, 2004. "Improved trade classification rules: Estimates using a logit model based on misclassified data," Atlantic Economic Journal, International Atlantic Economic Society, vol. 32(3), pages 256-256, September.
- Odders-White, Elizabeth R., 2000. "On the occurrence and consequences of inaccurate trade classification," Journal of Financial Markets, Elsevier, vol. 3(3), pages 259-286, August.
- George C. Chacko & Jakub W. Jurek & Erik Stafford, 2008. "The Price of Immediacy," Journal of Finance, American Finance Association, vol. 63(3), pages 1253-1290, 06.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.