A note of techniques that mitigate floating-point errors in PIN estimation

Wen-Chyan Ke, Hueiling Chen and Hsiou-Wei William Lin

Finance Research Letters, 2019, vol. 31, issue C

Abstract: This study aims at the estimation of the probability of informed trading (PIN), which may fail for stocks with high levels of trading activities due to a computer's floating-point exception (FPE). In this paper, we discuss two solutions of adopting scaled trade counts and reformulating the likelihood to estimate PIN for actively traded stocks. This study shows that, although scaled data mitigates the impact of the FPE, the effectiveness of scaled data, however, appears to underperform when users adopt the unsuitable expression of the likelihood function. In contrast, the remedy of reformulating the likelihood is more stable.

Keywords: PIN; Maximum likelihood; Scaled trade counts; Floating-point exception (search for similar items in EconPapers)
JEL-codes: C13 C60 G14 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:31:y:2019:i:c:s1544612318302289

DOI: 10.1016/j.frl.2018.12.017

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