Quantifyingtheunquantifiable:geopoliticalrisk
Economic data comes with decades of history to calibrate against — you can look at how markets reacted to the last ten inflation surprises and build a reasonable base rate. Geopolitical events don't offer that luxury. No two conflicts, sanctions regimes, or diplomatic breakdowns unfold the same way twice, and the sample size for any specific type of event is often uncomfortably small. Treating geopolitical risk with the same statistical confidence as economic data isn't rigor — it's a way of hiding real uncertainty behind a number that looks more precise than it is.
A more honest approach combines structured signals that can be tracked systematically — troop movements, sanctions activity, shifts in diplomatic language, changes in official rhetoric — with an explicit acknowledgment of where the model's confidence genuinely runs out. This means building systems that can say "this situation has no strong historical precedent" instead of quietly defaulting to the nearest analogous case and presenting that as a forecast. In a domain this uncertain, the most useful output isn't always a probability. Sometimes it's a clear, well-reasoned account of what's known, what isn't, and what would have to happen for the outlook to shift — leaving the final judgment where it belongs, with a person who can weigh context a model can't.