Bid‐Ask Spread Estimators: Current State, Gaps, and Future Research Agendas
系统综述了1987至2025年间125篇关于买卖价差估计量的论文，识别出从参数模型到数据驱动方法的演变，并指出利用高频数据验证低频模型、整合行为金融等未来研究方向。
ABSTRACT 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.