Bid‐Ask Spread Estimators: Current State, Gaps, and Future Research Agendas

This study provides a comprehensive systematic review and bibliometric analysis of 125 peer‐reviewed articles on bid‐ask spread estimators published between 1987 and 2025. Using the PRISMA framework, we map the intellectual evolution of the field, identifying a significant shift from foundational parametric models to data‐driven approaches. While early research focused on simple covariance‐based metrics, the field has recently been transformed by significant technical advances. Our network analysis identifies five major thematic clusters ranging from market dynamics and liquidity definitions to microstructure in high‐frequency and volatile environments. We highlight a critical research priority: utilizing high‐frequency data to validate low‐frequency models for reliable application in unobserved contexts, such as emerging markets and decentralized finance (DeFi). The findings underscore the enduring relevance of estimators in construction of long‐span historical series and noise‐adjusted liquidity measures. Future research must bridge existing methodological silos by integrating behavioral finance perspectives and advancing real‐time analytics for fragmented, high volatile global markets.