Predicting Stock Index Changes
提出一种模型驱动的方法，结合指数规则和市值等参数的演化模型，预测股票指数成分股的加入或剔除，并以2021年德国DAX和MDAX指数改革为例进行案例研究。
The addition or deletion of companies to or from a stock index has major consequences, with a change in demand from index-tracking investors and funds constituting the most obvious one. Numerous event studies since the 1980s have evidenced the existence of abnormal returns and trading volumes (<italic>index effect</italic>) around the announcement and actual change dates for stock indexes. This article presents a model-driven approach to predicting changes in the index membership itself. Index rules are combined with models for the evolution of parameters such as market capitalization that drive a company’s potential inclusion or exclusion. Special attention is paid to the inherent model risk. The 2021 revision of Germany’s blue-chip and mid-cap indexes, DAX and MDAX, both in terms of the number of index members and admission criteria, serves as a case study.