How Ebola‑Triggered Airport Screening Illustrates High‑Dimensional Machine Learning in Trading
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The first imported Ebola case in East Africa sparked immediate health screenings at neighboring airports. For quantitative traders, the rapid policy response is a live case study of how sudden, high‑dimensional information can reshape risk premia and create short‑lived trading opportunities. This article shows how to translate such events into robust machine‑learning signals while avoiding the classic pitfalls of over‑fitting. 1. The Market Shock and the Data Explosion When a fatal Ebola infection was confirmed in Nairobi, governments in the region deployed temperature checks, rapid tests, and travel‑history questionnaires at major hubs....
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