When something happens in the world, whether a war, a blockade or a shipping lane closing, it eventually shows up in oil prices, grocery bills, and the value of what you own. This page explains how we work out the size of that effect, how confident we are in each number, and what we still cannot tell you. No background in finance required.
A conflict on the other side of the world does not affect your savings by magic. It travels along particular routes: it pushes the oil price up, it makes shipping slower and dearer, it raises the cost of food, it moves currencies, it changes what governments spend on defence.
We map each situation as a set of those routes. For every route, we ask one question: when this route is under pressure, how much does each kind of investment typically move? Oil companies tend to gain when oil spikes. Airlines tend to suffer, because fuel is one of their biggest costs. Shipping firms gain when freight rates jump. We measure those typical movements from real market history, then add them up across everything you own.
Two situations are live on the platform. The Strait of Hormuz, the narrow sea passage most of the world's oil tankers pass through, works mainly through oil and shipping. The Taiwan Strait works mainly through computer chips, and has no oil route at all. They are deliberately different, because geopolitical risk is not one single thing that moves everything the same way.
If you enter what you own, the sums are done on your own device. Nothing is uploaded, stored, or sent to us. You can disconnect from the internet after the page loads and it will still work.
Some of our numbers come from measuring what actually happened in a real crisis. Others are careful estimates of something that has never happened. Those deserve very different levels of confidence, and we label which is which rather than presenting them as equally solid.
| Label | What it means | Used for |
|---|---|---|
| MEASURED | The event actually happened, and we measured how markets really responded | Hormuz / Iran |
| ESTIMATED | This has never happened, so there is nothing to measure. The figures are reasoned estimates, anchored to published research | Taiwan Strait |
| ROUGH DRAFT | A first pass that has not been checked against anything. Never shown to you | – |
Three rules keep these labels honest. A new situation never inherits another one's label. It has to earn its own. A label can only be upgraded by evidence, meaning something actually happened and we measured it. And every situation has a scheduled re-check date and a written list of things that would force us to redo the numbers, both shown on the page.
If you prefer the technical terms: these labels are empirical, unpriced and draft in the underlying model, and appear that way in the published source code.
The Strait of Hormuz was closed by war from 28 February to the ceasefire on 8 April 2026. Oil went from about $70.90 a barrel before the war to a peak of $138.20 on 7 April, then came back down. The fighting stopped; the crisis did not. Fewer ships pass through than before, insurance for those that do is still expensive, and our main working assumption treats today's uneasy truce as the normal state, rather than a hypothetical war.
Because this really happened, we did not have to guess. We took 41 investments, looked at their weekly prices from 2020 to 2026, and measured how each one moved during the crisis.
There is a trap here, and avoiding it is the most important decision in the whole model. Markets are always moving for reasons that have nothing to do with the crisis, including interest rate changes, an artificial-intelligence boom, ordinary business cycles. If you simply measure how much oil companies rose during the war, you capture all of that too, and you overstate the war's effect.
So for every measurement, we subtract what the whole stock market did over the exact same days. If energy shares rose 25% while the market as a whole rose 6%, we record the war's effect as 19%, not 25%. That single subtraction is what separates the crisis signal from everything else happening at the time.
| Type of investment | Affected through | We predicted | What really happened |
|---|---|---|---|
| Gulf oil producers | oil price | +4.9% | +3.3% |
| Energy companies | oil price | +19.6% | +19.4% |
| Oil tanker operators | shipping costs | +24.8% | +25.1% |
| Utilities | seen as a safe haven | +9.3% | +10.1% |
| Airlines | fuel costs, fewer flights | −8.7% | −9.9% |
| Luxury goods | people spend less | −17.9% | −19.7% |
We tested the model against the full 2026 war, the real event, which it had not been shown while being built. On average it was off by about 2.5 percentage points per category. That is the honest margin of error, and it travels with every figure on the platform.
The previous version of the model was off by 19 points. It had been built by assuming the Ukraine war was a good stand-in for a Middle East oil crisis, and it dramatically overstated how badly everything would be hit. We replaced it, and the change is on the record.
That replacement is the rule, not the exception: when reality disagrees with the model, the model changes. We cut our airline estimate by more than three times when the real fuel-cost damage turned out milder than assumed. We had grouped commodity funds with gold, expecting them to behave similarly; in the war they rose 24.5% while gold managed 0.9%, so we separated them. We had assumed developing-country investments would suffer; in both wars we measured, the ones that export raw materials gained more than the ones that import them lost, so we changed the sign. Corrections like these are not embarrassments to be buried. They are how the thing gets more accurate.
Taiwan has never been blockaded. The world's supply of advanced computer chips has never been cut off by conflict. So unlike Hormuz, there is no real event to measure, and rather than hide that, we made it the headline finding for this situation.
What we found: we tested five past scare episodes to see whether markets had ever priced this risk in. They had not. During the December 2025 Chinese military escalation, which was the most serious in decades, chipmaker shares rose 20.6% relative to the market. The artificial-intelligence boom did not merely drown out the fear, it reversed it. The August 2022 Pelosi visit produced the only genuine fear response we could find, and it was small: chipmakers fell 8.3%. A major earthquake that physically damaged chip factories in 2024, and the real chip shortage of 2021, left no usable trace at all. Every test, with its dates and verdict, is published on the platform.
What we estimated instead: our figures are anchored to published research from Bloomberg Economics, dated February 2026. It puts a year-long blockade at a 5.0% hit to the world economy. A war it puts at 9.6%, or roughly $10.6 trillion in the first year. We then worked out how each kind of investment would likely fare, based on how much of its business depends on Taiwan. These are reasoned estimates of something that has never occurred. They are useful for comparing your exposure and for thinking through what would matter. They are not a forecast, and we label them that way everywhere they appear.
The two situations above go quiet for long stretches. Nothing is exploding this month, so those pages sit still. The DELAX Global Strain Index exists for exactly those weeks. It answers a different question. Is the world under more pressure than usual right now, or less? And it moves every day, whether or not any particular crisis is active.
Zero means normal. Not zero pressure. Normal pressure, meaning the level that has been typical across the years we have measured.
Above zero means tighter than usual. Below zero means easier than usual. A reading of +1 means conditions sit one ordinary-sized swing above normal. That is noticeably elevated, but the sort of thing that happens from time to time. A reading of +2 or beyond is genuinely unusual, the kind of pressure seen only a handful of times in a generation.
It is deliberately not a mark out of 100. A score out of 100 implies there is a known worst case, and there isn't one. Conditions can always get tighter than they have ever been before.
How it is built. We take five things that get measured constantly, and for each one we ask the same question. Compared with its own history, is today's figure unusually high or unusually low? Then we average those five answers into a single number.
| What we look at | Where it comes from | Updated | Share |
|---|---|---|---|
| Oil price (Brent crude) | US Energy Information Administration | Daily | One fifth |
| US consumer prices | Federal Reserve economic data | Monthly | One fifth |
| World food prices | Federal Reserve economic data | Monthly | One fifth |
| Natural gas price | Federal Reserve economic data | Daily | One fifth |
| Conflict in the news | Geopolitical Risk index, Federal Reserve Board | Weekly | One fifth |
No single one of the five can dominate. Each is capped, so even an extraordinary move in one input cannot swamp the other four.
We compare each thing against the longest run of trustworthy history we have for it, rather than forcing them all into the same window. For the four price measures that means back to 2015. For the conflict measure it means back to 1985.
The reason matters. Judging today's conflict level against only the last ten years would leave out the September 11 attacks, the 2003 invasion of Iraq and the Gulf War. Those are the events that tell you what a genuinely high reading looks like. Leave them out and the recent past looks calmer than it really is, which makes every new flare-up appear more extreme than it deserves. We would rather each input be judged against everything we reliably know about it, and say plainly that the windows differ, than use one short window that flatters the numbers.
It measures pressure, not danger. Four of the five inputs are prices that have already been recorded. The fifth counts how much of the world's news is about conflict. Together they describe the strain that exists today.
It does not predict. Nothing in it looks forward. The index describes conditions now. It does not tell you what happens next, and we will never claim it does.
Parts of it move slowly. Two inputs are updated once a month and one once a week, so on many days the number moves because oil or gas moved. We would rather say that plainly than let the name imply more than the number delivers.
Where the conflict measure comes from, and why it is not ours. We spent weeks building our own. It counted how many news articles mentioned conflict, and we tested it before trusting it. Those tests taught us two things, and both of them ended the project.
We tracked news coverage of the Ukraine invasion from February to December 2022. Coverage peaked at 32.7% of all news being monitored, then fell to 7.6% by the end of that period, under a quarter of its peak. The war was still fully underway the whole time.
So a measure built on how much coverage a war is getting would have reported that Ukraine risk had mostly gone away by the end of 2022, when nothing on the ground had improved. The world stops reporting on a war long before the war stops.
The second problem was ours alone. Our version searched for words like Hormuz, Iran and oil tanker. That is a list about one waterway, not about the world. It would have gone quiet during a crisis in Taiwan or the Red Sea, and it would have counted the Gulf twice over, because trouble in the Gulf already reaches this index through the oil price. An index called Global cannot be built on a search for one strait.
So we use an established measure instead. The Geopolitical Risk index is built by two economists at the Federal Reserve Board, Dario Caldara and Matteo Iacoviello. It reads ten major newspapers going back to 1985 and counts articles across eight kinds of trouble, including threats of war, military build-ups, nuclear threats and acts of terrorism. It is published openly, free for anyone to use, and the method behind it was reviewed and published in one of the leading economics journals.
It counts shares, not totals. The world publishes far more news than it did in 1985. A measure that simply counted conflict articles would show the world getting steadily more dangerous purely because more news exists. This one reports conflict coverage as a proportion of all coverage, which cancels that out.
We use its thirty-day average, not its daily figure. The daily figure can sit seventeen percent away from its own monthly average, which would let a single news cycle visibly swing our headline number. The rest of the index moves slowly, and we would rather the conflict input moved at a comparable pace than have one input drive nearly all the movement on its own.
Source: Caldara, Dario and Matteo Iacoviello (2022), “Measuring Geopolitical Risk”, American Economic Review 112(4), pp. 1194–1225. Data published under a Creative Commons licence and downloaded from matteoiacoviello.com.
If any input is missing, we publish nothing. The index is not quietly recalculated around a gap. If one of the five cannot be read on a given day, the number is withheld and the space stays empty rather than showing a figure built on four inputs while describing itself as built on five.
The headline number stays free, permanently. The most respected gauges of this kind, including the Chicago Federal Reserve's financial conditions index and the Geopolitical Risk index we now draw on, are all free to look up, and that is exactly why people trust and cite them. A paid tier adds the breakdown by component, the full history, and alerts when the number crosses a threshold.
Open the Exposure Desk and enter what you own. You will get a figure for how your particular mix would be affected, broken down by which route the damage travels along and which holding is hit hardest. Everything is calculated on your own device.
On the dashboard, switch between Hormuz and Taiwan with the same holdings loaded. An oil crisis barely touches a technology-heavy portfolio; a Taiwan blockade transforms it. Then switch between the outcomes. Each one shows how likely we think it is, in numbers and in plain words.
The question box on the dashboard takes plain questions like "how exposed am I if Taiwan is blockaded?" and answers using the current figures. It will tell you what changed, why it matters to you, and what to watch next. It will not tell you to buy or sell anything.
Every figure carries a label. MEASURED means it came from a real event. ESTIMATED means it is reasoned, because the event has never happened. On the Taiwan view you can see every past scare we tested and what each one showed. Beside each label is the date we last reviewed it and when it is next due.
The 2026 Hormuz war lasted six weeks. A closure lasting a year could damage company profits in ways a six-week shock never did. Our measurements describe what has happened, not every possibility that hasn't.
There is no free, constantly-updated source for shipping rates, real-time global economic output, or defence budgets. Where we have had to estimate, we say so on the figure itself. Our weakest area is the effect on developing-country currencies: in both wars we measured, gains and losses largely cancelled out.
The Taiwan figures describe something that has never occurred. They are built for comparing exposure and thinking through consequences, not for precision. Treat the extreme scenarios as rough magnitudes.
We measure and explain exposure. We do not tell you what to buy or sell, and nothing here should be read as a personal recommendation. If you want advice about your own situation, speak to someone qualified and regulated to give it.
A number you cannot question is a number you are taking on faith. Everything above can be checked: the events are public, the investments are widely traded, the dates are stated, the outside research is named, and the core method is one subtraction, namely what this investment did minus what the whole market did. Where we have been wrong, the correction is written down. If you think one of our figures is still wrong, this page gives you what you need to make that argument.