Probability of informed trading: a Bayesian approach Online publication date: Mon, 06-Apr-2020
by Leonardo Bosque; Pedro Albuquerque; Yaohao Peng; Cibele Da-Silva; Eduardo Nakano
International Journal of Applied Decision Sciences (IJADS), Vol. 13, No. 2, 2020
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.
Online publication date: Mon, 06-Apr-2020
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