PT - JOURNAL ARTICLE AU - Matthias Apel AU - André Betzer AU - Bernd Scherer TI - Point-in-Time Language Model for Geopolitical Risk Events AID - 10.3905/jfds.2022.1.113 DP - 2023 Jan 31 TA - The Journal of Financial Data Science PG - 65--75 VI - 5 IP - 1 4099 - https://pm-research.com/content/5/1/65.short 4100 - https://pm-research.com/content/5/1/65.full AB - In this article, the authors show how to build a real-time geopolitical risk index from news data using textual analysis. The presented method defines a point-in-time dictionary of terms related to political tension. It does not rely on the in-sample definition of a set of n-grams that are likely chosen and updated with hindsight bias. The proposed model can be applied to any topic and is language agnostic. Only a few topic-related words are required to initialize the buildup of a dynamically self-adjusting dictionary. The authors show that their approach can resemble the results of other more supervised methods. The findings indicate how topic identification and news index construction may benefit from a time-dependent dictionary generation.