• ISSN: 2010-023X
    • Frequency: Bimonthly
    • DOI: 10.18178/IJTEF
    • Editor-in-Chief: Prof.Tung-Zong (Donald) Chang
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library , EBSCO, and Ulrich's Periodicals Directory
    • E-mail: ijtef@ejournal.net
IJTEF 2014 Vol.5(5): 392-396 ISSN: 2010-023X
DOI: 10.7763/IJTEF.2014.V5.404

The Sensitivity to Trade Classification Algorithms for Estimating the Probability of Informed Trading

Wen-Chyan Ke
Abstract—This study examines the impact of trade classification algorithms on estimating the probability of informed trading (PIN). This study finds that the algorithms themselves may not substantially influence the PIN estimates but the poor performances of these algorithms may have the great impact on the PIN estimates. Moreover, the new proposed adjustment, Q-Method, seems to mitigate the bias caused by the trade misclassification. In addition, the pattern of its estimates responds to the important economic events. With the estimated misclassification rate from Q-Method, this study also finds that the performances of these algorithms are getting poor in recent years.

Index Terms—Informed trading, market microstructure, trade misclassification.

W.-C. Ke is with the Department of Finance and Cooperative Management National Taipei University, No. 151, University Rd., San-Shia District, New Taipei City 23741, Taiwan (e-mail: wenchyan@gm.ntpu.edu.tw).

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Cite: Wen-Chyan Ke, "The Sensitivity to Trade Classification Algorithms for Estimating the Probability of Informed Trading," International Journal of Trade, Economics and Finance vol.5, no.5, pp. 392-396, 2014.

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