Filtration enlargement‐based time series forecast in view of insider trading
这篇综述梳理了滤波扩张模型在内幕交易研究中的应用，并提出了将理论结果转化为可检验假设的可行方法，通过公开数据（如股价）推断内幕信息，最后用模拟数据做了实证演示。
Abstract This survey reviews filtration enlargement models in view of insider trading. Although filtration enlargement aptly models insiders' informational advantage, the theoretical results have not attracted the attention of the empiricists, owing mainly to the lack of a bridge transforming the results to testable hypotheses, and/or the absence of econometrics method linking the hypotheses and the data. This survey provides a feasible avenue to estimate insider information and to detect trading from a relatively sophisticated theoretical model, where the dynamics of publicly available data (e.g., stock price) implies insider information before the information is completely digested. We complete the survey with an empirical illustration based on simulated data.