A computing bias in estimating the probability of informed trading |
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Authors: | Hsiou-Wei William Lin Wen-Chyan Ke |
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Institution: | Department of International Business, National Taiwan University, Taipei, Taiwan |
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Abstract: | 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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Keywords: | JEL classification: G12 G14 C13 |
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