A computing bias in estimating the probability of informed trading
AbstractThis study identifies a factor that leads to a bias in estimating the probability of informed trading (PIN), a widely-used microstructure measure. It is shown that, along with the numerical maximization of the likelihood function for PIN, the floating-point exception (i.e., overflow or underflow) may eliminate feasible solutions to the actual parameters in the optimization problem. Approximately 44% of PIN estimates for recent stock market data may have been subject to a downward bias that is more pronounced for active stocks than for inactive stocks. This study develops a remedy to mitigate the resulting bias.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Financial Markets.
Volume (Year): 14 (2011)
Issue (Month): 4 (November)
Contact details of provider:
Web page: http://www.elsevier.com/locate/finmar
Floating-point exception Informed trading Market microstructure;
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