How Machine‑Learning Risk Models Can React to Sudden Geopolitical Shocks
Research preview
The Saudi‑led coalition’s interception of a Houthi ballistic missile over Khamis Mushait illustrates how quickly a geopolitical event can reshape market risk. For quantitative traders, the challenge is to translate such low‑frequency, high‑impact news into actionable signals while avoiding over‑fitting. This article shows how high‑dimensional regression, regularisation, and debiased machine learning can be used to incorporate real‑time event data into portfolio risk models. From Event Detection to Feature Engineering When a missile is launched, news feeds, satellite alerts, and social‑media chatter generate a burst of data. The first step is to transform this raw stream into quantitative features....
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