The estimation of the probability of informed trading (PIN) model and its extensions poses significant challenges owing to various computational problems. To address these issues, we propose a novel estimation method called the expectation-conditional-maximization (ECM) algorithm, which can...

As online platforms increasingly rely on algorithmic systems to curate, rank, and remove content, concerns about the societal and economic consequences of algorithmic decision-making have intensified, and with them the importance of algorithmic auditing. However, there is a lack of universal,...

To overcome the structural limitations arising from subjectively preset adjustable parameters in the NGBM(1,1) model family and significantly enhance its predictive capability for complex nonlinear systems, this study develops a novel self-adaptive nonlinear discrete grey model...