Title: Probability of informed trading: a Bayesian approach

Authors: Leonardo Bosque; Pedro Albuquerque; Yaohao Peng; Cibele Da-Silva; Eduardo Nakano

Addresses: University of Brasilia, DF, Brazil ' University of Brasilia, DF, Brazil ' University of Brasilia, DF, Brazil ' University of Brasilia, DF, Brazil ' University of Brasilia, DF, Brazil

Abstract: One of the most popular models for measuring information asymmetry of financial assets is the probability of informed trading model (PIN). Its theoretical foundation and its wide possibility of application made PIN a benchmark in insider trading studies. In view of the interpretability of PIN and its parameters, this study aims to evaluate and propose a Bayesian version for the probability of informed trading model. The proposed approach brings the possibility to include expert opinions about PIN parameters and represents a new contribution to the theoretical scope of market microstructure models.

Keywords: probability of informed trading; PIN; Bayesian inference; market microstructure model; private information; information asymmetry.

DOI: 10.1504/IJADS.2020.106415

International Journal of Applied Decision Sciences, 2020 Vol.13 No.2, pp.183 - 214

Received: 21 Dec 2018
Accepted: 27 Apr 2019
Published online: 06 Apr 2020 *

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