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The recent confirmation of a second Ebola case in Kenya, just days after the first fatality, underscores how unexpected shocks can ripple through economies and markets. For quantitative traders, such events provide a vivid reminder that models built on many predictors can look perfect in‑sample yet fail when reality changes abruptly. This article connects the Ebola episode to core lessons from high‑dimensional machine‑learning coursework, showing how to safeguard trading strategies against hidden over‑fitting. 1. The Ebola Event as a Real‑World Stress Test The second Ebola patient was a close relative of the first victim and was already under quarantine when the infection was detected....