Paradigm Shift: Embracing Holism in Causal Modeling for Investment Applications
探讨了在经济学和金融领域，传统经济理论需演变以容纳不同类型的因果输入，并基于结构因果模型（SCM）提出一个框架，帮助投资者利用经验、理论和基本面信息构建更实用的因果模型。
This article explores the broader implications of causal modeling within the realms of economics and finance. The authors argue that traditional economic theories must evolve to accommodate different types of “causal inputs” if they are to navigate the increasing complexity of modern economies. Specifically, the causal relations implied by (often not explicitly causal) economic and investment theories, as well as real-time, forward-looking views on the causal relations between economic and market variables, can add significant value to the causal models that drive investment decision making. To demonstrate the approach being advocated, the authors build on a well-known framework utilizing structural causal models (SCMs) and present an SCM that incorporates the aforementioned types of causal inputs, enabling investors with the formal means to develop causal models that utilize the totality of empirical, theoretical, and fundamental information they have at their disposal. By acknowledging that the causal dynamics in economies and markets are too complicated to “figure out” completely, investors can focus on building ecumenical causal models that are able to utilize disparate types of causal information and thereby potentially increase their practical investment value.