Two-Step Pin Model to Estimate the Probability of Informed Trading

We meticulously scrutinize the widely acknowledged measures of the Probability of Informed Trading (PIN) and the Volume-Synchronized Probability of Informed Trading (VPIN), initially posited by David Easley et al., which have achieved considerable eminence within the realm of financial academia. Regrettably, these estimations are not exempt from inherent biases that arise due to the palpable disparity between the foundational model constructs and the intricate, ever-evolving reality of contemporary financial markets, particularly in light of the rapid proliferation of high-frequency trading practices.To address these extant limitations, we embark upon a comprehensive reevaluation of the fundamental assumptions underpinning the conventional PIN model. Subsequently, we introduce an innovative Two-Step PIN model, devised to enhance the precision with which we estimate the probability of informed trading. This novel approach not only ameliorates the estimate accuracy but also constitutes a valuable contribution towards resolving critical financial quandaries pertaining to asset pricing, market volatility, and the potential for price manipulation. The present paper, therefore, seeks to bridge the gap between theoretical frameworks and real-world market dynamics, thereby extending the scholarly discourse on the aforementioned financial metrics