How High‑Dimensional Machine Learning Can Reveal Market Risks During Prolonged Geopolitical Crises
Research preview
The war that began on October 7, 2023 has generated a humanitarian catastrophe and heightened uncertainty across global markets. For quantitative traders, the event offers a real‑world laboratory to test big‑data techniques that can separate transient sentiment spikes from lasting structural shifts in asset prices. From Raw News Streams to Predictors The first step in any data‑driven crisis model is to transform unstructured information into numeric features. Newswire counts, social‑media sentiment scores, and satellite‑derived activity metrics can each be turned into daily time‑series....
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