A computing bias in estimating the probability of informed trading
This 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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- 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.
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- 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.
- Duarte, Jefferson & Young, Lance, 2009. "Why is PIN priced?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 119-138, February.
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