How a Geopolitical Analyst Predicts the Outcome of War | Odd Lots
What this covers
Andrew Bishop, global head of policy research at Signum Global, joins Joe Weisenthal to explain how geopolitical analysts forecast conflicts and their market consequences—not by predicting single outcomes, but by assembling rigorous processes that decompose chaos into manageable sub-probabilities. The conversation centers on the Israel-Iran conflict, US policy under Trump, and the mechanics of what makes analysis useful to traders betting on oil, grain, currencies, and travel stocks when geopolitics shifts. Bishop argues that the scarcity of historical data makes statistical modeling impossible; instead, analysts must break complex scenarios into independent variables, assign probabilities to each, and compound them to identify tail risks that emerge not from any single likely scenario but from the aggregate of many low-probability paths.
The episode ranges across how leaders actually behave (the "logic of political survival" framework, with limits), why grand theories fail in the short term despite holding over years, and how to diagnose what went wrong when predictions miss—as Bishop did when underweighting Trump's appetite to intervene militarily in Iran. It covers the patterns that fade once they become famous (like Trump's track record of backing down), the risks of proximity to power (Treasury Secretaries don't know what Trump will do next), and why prediction markets, despite their appeal, often constrain analysis by fixing dates that don't match the actual decision points. The conversation also touches Taiwan, the underappreciated threat of a blockade over invasion, and why the collapse in oil prices when the war ended was actually predictable if you focused on timing peak fear rather than war duration. Throughout, Bishop emphasizes that clients value the analysis primarily as scenario rehearsal—like memorizing a race track before driving it—rather than as a single forecast.
Andrew Bishop argues that geopolitical risk analysis provides value not through predicting specific outcomes with high accuracy, but by helping financial clients map scenario trees and prepare decision-making frameworks for multiple contingencies, while emphasizing process-based reasoning over grand theories and the difficulty of constraining scenarios in unpredictable environments.
- Clients use geopolitical analysis like F1 drivers memorizing tracks—preparing mentally for multiple decision points (Is Israel striking? Is it symbolic or major? Will US intervene?) rather than betting on single predictions
- Most probability assignments work by breaking problems into sub-questions and checking that probabilities sum correctly to detect logical flaws, not by Monte Carlo simulation or historical data
- The value comes from the analytical process and nimbleness (constantly reassessing patterns), not from intelligence access or country expertise alone
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The 'logic of political survival' framework explains leader behavior — leaders place their own power and advantage ahead of everything, which is why Netanyahu would never agree to a hostage deal that risks his coalition just to satisfy Trump — but the framework is not foolproof, as shown by Hamas surrendering hostages twice despite the leverage logic predicting otherwise.
“the logic of political survival right like leaders will always put their own advantage ahead of anything”
Assigning probabilities to sub-events before publishing serves as an internal logic check: if the cumulative math doesn't add up to 100, it signals you are overstating or understating some aspect of the dynamic, even though the value is logical rather than mathematical.
“if the math doesn't add up, that can highlight a problem in your logic”
An overarching grand theory like 'Trump's trade policy is all about China' can be accurate over four years yet useless in the short term, because for the first three months the administration was obsessed with Mexico and Canada — so analysts should avoid grand theories and assess each prediction individually (fox vs hedgehog).
“that is totally accurate over the course of four years it is totally useless in the short term”
A base case scenario can be market-constructive while the aggregate of all non-base-case scenarios produces a more likely market-negative outcome — clustering non-base scenarios revealed this in a Uruguay election analysis.
“if you aggregated all the non-base case scenarios you actually had a more likely outcome of a market negative bottom line”
When a prediction is wrong, the productive response is to diagnose why — in the Iran case Bishop was too focused on Israeli military capabilities and not enough on Trump's political appetite to intervene — yielding a lesson that there is no single 'one rule to rule them all' and analysts must constantly reassess.
“you basically have to try to figure out why you got it wrong, right? And from there you can typically learn something for the next time”
Because there are many independent ways to reach a given outcome, compounding the probabilities of independent variables can tip the cumulative odds past 50% even when no single scenario is your modal (most likely) scenario — for example, US intervention in Iran exceeded 50% overall even with a low probability assigned to Trump wanting to intervene.
“because there are so many ways of getting to an outcome, you can get tipped over 50 without it being your your modal scenario”
A Chinese move against Taiwan within five years is expected, but it is more likely to be a blockade than an amphibious invasion; the underappreciated risks are that a blockade could be rolled out literally overnight with no buildup, and that a sustained bloodless 'anaconda squeeze' blockade of 3-6 months could be far worse for markets than a one-month war regardless of outcome, because of the prolonged disruption to business operations.
“it's more likely to be a blockade for example than an actual amphibious invasion”
Intel-based geopolitical analysis (insider information from Congress, golf with officials, etc.) does not make for good predictions because even insiders like the Treasury Secretary did not know whether Trump would back down on tariffs, and Assad did not know if he would be toppled — proximity to power does not confer foresight.
“it doesn't make for good predictions, right? Because Scott Besson himself didn't know on April 8 whether Trump was going to back down the next day”
True black swans almost never happen; the events that blow up are usually visible well in advance (e.g., months of Russian buildup before invading Ukraine, pandemics ranked top-5 in WEF risk reports for 15 years before COVID) — the real difficulty is predicting the details (timing, location) and knowing how to trade them, not anticipating the event category.
“the whole black swan thing is irrelevant. Like black swans almost never happen. The stuff that blows up in our face is stuff that is visible pretty far ahead”
Predicting geopolitical outcomes is actually harder than flipping a coin or throwing darts, because most situations have far more than two possible scenarios, making accurate probability assignment extremely difficult.
“It's actually harder than just throwing darts or flipping a coin because most situations have far more than two scenarios”
Most geopolitical situations have far more than two possible outcomes (unlike coin flips with 50-50 odds), making prediction much harder than random chance despite how it appears
“It's actually harder than just throwing darts or flipping a coin because most situations have far more than two scenarios, right? So it really is a very very difficult thing to do to predict all geopolitical outcomes”
Studies showing geopolitical risk doesn't move markets are short-sighted because they typically measure the S&P over the long term, whereas the firm's clients trade short-term and in niche assets (travel/tourism, oil and gas, Israeli shekel) where geopolitical events produce major sharp volatility.
“most of these studies typically look at S&P in the long term. And our clients obviously are not trading the S&P in the long term”
Trump's pattern of backing down (the 'taco' phenomenon) — backing down in roughly 21 of 23 documented threats — was a valid pattern, but it was already fading by the time it became a popular label, illustrating an 'Economist cover' effect where the pattern becomes less true once widely recognized, requiring constant reassessment.
“I think Trump had backed down in 21 out of 23 threats or something like that”
Geopolitical regime changes (e.g., shift to a multipolar world, US abandoning the hegemon role) do happen but unfold much more slowly than financial-market regime changes, giving more time to price them in; even the isolationist, pacifist-leaning Trump intervening militarily in Iran demonstrates how slow that process is.
“the regime changes happen but they happen much more slowly and so you have a lot more time to bake them in”
It is better to have rigorous analysis with a wrong call than a correct call with bad analysis, because good process is repeatable while a lucky correct call without process is just throwing darts.
“even if you get the call wrong, it's better to have good analysis and a call wrong rather than the other way around”
Identifying Trump's motivation in each specific case is key to prediction: if he is after tariff revenue he cannot back down (you can't collect revenue if you retreat), whereas transactional motivations like fentanyl or immigration concerns with Mexico made him likely to back down once he could claim he had acted — and the same country can be targeted by completely different motivations at different times.
“if you think he's after tariff revenue then he's by definition not going to back down. You can't get revenue if you back down”
Changing historical context (fast-moving events, shifting relationships, limited historical precedent) means that geopolitical analysts are working with even smaller datasets than usual, increasing the temptation to 'make it up as you go,' which is where analysis becomes unreliable.
“the fact that so much stuff is changing so fast means that you have even less historical background or historical data which as we said earlier you're already starting with very very small data sets, right? And so the temptation there is to kind of just make it up as you go and that's where things get dicey.”
Clustering non-base-case scenarios can reveal that the aggregate probability of non-base outcomes is higher than the base case, which is important for clients evaluating tail risks; example: a Uruguay election where the base case was market-constructive but all non-base scenarios aggregated to a higher probability of market-negative outcome.
“A second that can be quite interesting and problem, you know, not problematic but useful for the user is clustering. Right? So we had a recent scenario or recent situation with an election I think it was in Uruguay where the base case was perhaps market constructive but if you aggregated all the non-base case scenarios you actually had a more likely outcome of a market negative bottom line right”
Prediction markets are currently of limited use to clients mainly because of low liquidity, and they are more useful to the analyst than to the end user because their rigidity — fixing predictions to specific falsifiable dates — narrows their value when the truly relevant cutoff (e.g., a Trump visit) differs from the market's stated date.
“the rigidity of the prediction markets and it's a trade-off, right? Because the the reason they do them that way is so that they can be easily falsifiable”
The collapse of oil prices when the Israel-Iran war ended was a counterintuitive outcome that many clients actually anticipated, because the relevant question was timing the peak fear level — likely when Iran retaliates for whatever the US does — so prices dropping on the news of the war's end was not surprising to savvy clients.
“what they were trying to figure out was when is this going to end or not end, but when is it going to culminate, right? When is going to be the peak fear level?”
A useful lesson early in an analyst's career is to not get overly excited by every new headline, citing the perennially overhyped 'death of the dollar' stories (first gas contract settled in euros) and the BRICS narrative, which has promised a 'glorious future' for nearly 20 years without materializing.
“the zero hedge type headline about how the first gas contract was denominated or settled in euro instead of dollar... the bricks have had a glorious future for you know almost 20 years”
Rapidly changing geopolitics makes analysis harder because it shrinks the already-tiny historical data set — e.g., the long-established 'axis of convenience' read on the Russia-China relationship became genuinely unclear after the 2022 Ukraine invasion — and the temptation to 'make it up as you go' is where analysis gets dangerous.
“so much stuff is changing so fast means that you have even less historical background or historical data”
Trump allows his advisers to say anything, including the craziest statements, as long as they do not reduce his optionality — he benefits from them going to extremes provided he doesn't get cornered by their comments, which is why parsing his spokespeople literally (e.g., 'sign the executive order' vs 'implement the tariffs') can be predictively useful.
“they are allowed to say anything, including the craziest stuff, as long as they don't reduce his optionality”
Clients value the analysis primarily not for the outcome prediction itself (for which they could use prediction markets) but for the rehearsal of all possible scenarios in advance — like an F1 driver memorizing every turn of the track before a race so they are pre-prepared to react when events unfold.
“they're an F1 driver, and we're helping them on the sort of, you know, the training tracks”
China could blockade Taiwan with no warning (rolling it out overnight rather than with visible military buildup), making it radically harder to prepare for; a bloodless blockade lasting months could be worse for markets than a short war because continuous economic disruption is more damaging than acute disruption
“the Chinese could roll it out literally overnight. So I think what is underappreciated is we're not going to get any buildup. We're going to wake up one morning and it's going to be done. So that's one problem. A second problem is a bloodless blockade that lasts, you know, 3 months or 6 months that is essentially a continuous anaconda squeeze on Taiwan and the Taiwanese economy could actually be far worse from a purely market perspective. Forget about, you know, normative aspects. far worse than a one-month war regardless of the outcome, right? Because it's the length of the disruption for business operations that that could be most problematic.”
Technical knowledge (e.g., missile ranges, weapons capabilities) is necessary for geopolitical forecasting but need not be held in-house: the firm breaks a big issue into sub-questions and sources answers from open source or external experts while never outsourcing the actual analysis or predictions.
“you do need it, but you can break it down and not make it part of your core business model”
Black swan events (sudden, unpredictable crises) almost never materialize; instead, the crises that blow up are visible far in advance (Russian military buildup before Ukraine, pandemic warnings in global risk reports for 15 years) but analysts and clients struggle to predict the exact timing and details
“I always say like the whole black swan thing is irrelevant. Like black swans almost never happen. The stuff that blows up in our face is stuff that is visible pretty far ahead like not necessarily far ahead of time but that is pretty obvious and the difficulty is for the analyst predicting the details right like in what month is Putin going to invade or whatever or what part of Ukraine is he going to invade...there were four or five months of Russian buildup in in front of Ukraine...And another example is CO. People talked about CO as a black swan. I mean if you read any of those you know world economic reform global risk reports for the past like 15 years pandemics were always top 10 like or even top five.”
A second principle Andrew learned from Cliff Cupckin was that it's better to have good analysis and a wrong call than the opposite: good analysis with a wrong call teaches you something and improves next time, whereas a right answer by luck tells you nothing and is equivalent to random guessing.
“good analysis. Like basically the key is to have a rigorous and an analytical process and even if you get the call wrong, it's better to have good analysis and a call wrong rather than the other way around. Right? Because otherwise you could just be throwing darts and you you'd be getting elections, you know, 50% right half the time.”
Netanyahu would never agree to a hostage deal because it would risk his coalition and losing power, as predicted by Bueno de Mesquita's political survival logic, yet Hamas has given up hostages twice, showing that no framework is failproof and analysts must stay humble and nimble
“leaders will always put their own advantage ahead of anything and that's why you know you've got situations where like Netanyahu is never going to agree to a hostage deal because it would risk his coalition. And why would he risk his coalition or, you know, why would he risk losing power just to satisfy Trump? That's where it gets interesting though, is none of these rules is failroof, right? Because using that logic, one of the push backs I got on on our ceasefire calls in the past was why would Hamas ever give up the leverage of hostages, right? And that sounds like a conversation and the truth is they've given up hostages twice now, right?”
Prediction markets currently lack enough liquidity to be useful for professional investors, even when they're large; more importantly, they're rigid in their cutoff dates and event definitions, narrowing their value because the relevant decision trigger might be an event (like a leader's visit) rather than a calendar date
“short answer is that I'm aware of no. And the main reason is still liquidity despite the fact that it's getting bigger as you say. What's really interesting of course is that that would disintermediate the market's reaction function. So, I'm looking back at a note. This is just a random one that I found in my inbox...So, I'm reading a June 16th note...prediction markets will tell you where the tariff level is going to end up on July 31st, right? But what if the cutoff that's relevant is not July 31st? what if it's, you know, a completely different date because Trump is visiting like let's say that it's it's a ceasefire in Gaza and the cutoff date is Trump's visit to Saudi Arabia or whatever. So the point is the rigidity of the prediction markets and it's a trade-off, right?”
Most studies showing geopolitical risks don't affect markets focus on S&P 500 long-term performance, but professional clients actually trade short-term in niche assets (travel, tourism, oil/gas, Israeli shekel) where geopolitical events create substantial volatility that traders can capitalize on
“most of these studies typically look at S&P in the long term. And our clients obviously are not trading the S&P in the long term, right? They're trading in the short term. And you've got some pretty violent sharp moves up and down for a lot of these assets. And they're also trading obviously more niche assets. So I'm thinking of the travel and tourism industry or I'm thinking of the oil and gas industry, Israeli shekele, you know, things that are far more niche.”
Joe Weisenthal questions whether he understands how geopolitical analysts use data and reasoning to arrive at systematic conclusions about war outcomes, unlike Fed policy analysis where the chain of reasoning (Fed statements → reaction function → forecasted rate path) is more transparent
“I have a sort of I think intuitive understanding of how they they're like, 'Oh, there's going to be three cuts in the next year.' And then I generally have a sort of intuitive understanding of how they might arrive at that. Okay. We look at statements from the Fed about what they're looking for in terms of achieving disinflation. We look at the trajectory of the US economy and then we say okay we combine the Fed statement their sensitivity etc the reaction function that's the term I'm looking for with the data and then we arrive at a forecast when it comes to something like a war I do not really have an intuitive understanding of how the geostrategic or geopolitical analysts...how do they arrive at conclusions”
The primary value geopolitical risk analysis provides to financial clients is not accurate outcome prediction, but rather helping them mentally rehearse multiple scenario branches (like is Israel striking? symbolic or major? will US intervene? will it last 3 days or 3 weeks?) so they're prepared to make rapid trading decisions when events unfold, similar to how an F1 driver memorizes track loops before racing
“the main reason is like they're an F1 driver, and we're helping them on the sort of, you know, the training tracks, right? like on the on the the training loops before the actual race to literally memorize every single turn and know when they can accelerate, when they've got to cut a corner, etc. So that when the events start unfolding, they're already prepared to, you know, hit the brakes or accelerate depending on what's happening.”
Probabilities in geopolitical scenario analysis work by breaking a question into sub-events, assigning probabilities to each, and checking that they sum to reasonable totals as a logic check—not by Monte Carlo simulation or historical data—because there simply aren't enough historical case studies of similar geopolitical events to build predictive statistical models
“there's I I could give you a fancy answer about Monte Carlo simulations etc. But the reality is neither we nor as far as I'm aware anyone in the sort of market actually models this stuff and the few that do use predictive analytics rather than historical data. And the reason is there just aren't that many case studies to go off of.”
Trump allows his advisers maximum leeway to say anything, including 'the craziest stuff,' as long as they don't reduce his optionality or corner him into a position, implying Trump values maintaining decision flexibility above consistency or ideology
“he is allowed to say anything, including the craziest stuff, as long as they don't reduce his optionality, right? So, he benefits from them going nuts as long as he doesn't get cornered by their comments.”
Signum's competitive advantage is not in intelligence access (which is legally problematic and doesn't yield better predictions anyway) or country expertise alone, but in the rigor of analytical process following Phil Tetlock's principle that 'it's not about who you are, it's how you proceed'
“where we think our value ad is is on the process. And we've basically adopted like a few principles. One is the Phil Tetlock principle that I I mentioned earlier which is it's not really about who you are it's how you proceed right so it's precisely what is your model like what is your process”
On the US-Israel relationship, Bishop predicts the relationship will change slowly (over 20-30 years, like most regime changes in alliances) rather than suddenly, and even Trump—known as pacifist and skeptical of global military footprint—intervened in Iran, suggesting that the shift away from US hedgemony will be slower than the 'multipolar world' rhetoric suggests
“I think there's a a big difference with financial markets which is the regime changes happen but they happen much more slowly and so you have a lot more time to bake them in right...those only happen every 20 or 30 years or that the US may not want to be the hedgeimon at some point that it may not have the same appetite to be a global police. And so for example, you know, the Tucker Carlson wing of the Republican party very loud against this idea...At some point that could be a dominant strain of thought...But going back to how it's a slow process, I think Trump was a really and like literally what happened over the past month was a very very good test case for that, right? And the fact that Trump himself who is known to be not just isolationist but also pacifist...The fact that even he intervened I think tells us something about how slow that process is going to be.”
Insider intelligence (like conversations with congressional officials or military strategists) is problematic for geopolitical prediction for two reasons: (1) it raises legal risks around MNPI (material non-public information), and (2) even insiders with privileged access don't reliably know future decisions—Scott Besson didn't know on April 8 whether Trump would back down the next day despite working directly on the issue, and Assad was uncertain whether he would be toppled.
“intel, in addition to, you know, potentially if you've got MNPI, etc., that that gets legally dubious. In addition to that problem, it doesn't make for good predictions, right? Because Scott Besson himself didn't know on April 8 whether Trump was going to back down the next day. He knew he was working on him, but he didn't know. Assad was not sure whether he was going to be toppled or not.”
Trump's tariff approach in early 2025 appeared focused on Mexico and Canada in January-April (driven by fentanyl/immigration concerns), not China, making a grand theory that 'Trump's trade policy is about China' useless for short-term prediction despite being correct over his full four-year term (China ended up with 45% tariffs vs 10% for others)
“this narrative that Trump's trade approach is all about China right that is totally accurate over the course of four years it is totally useless in the short term because if I told you that Trump's trade policy was going to be all about China, which in hindsight is correct, right? China's got a 45% tariff. Everyone else has a 10% tariff. But if I told you that on January 19th and you were, you know, running a hedge fund, you would have been very, very surprised that the first 3 months of the Trump administration were all obsessed with Mexico and Canada.”
Trump backed down from approximately 21 out of 23 explicit threats during his first term, establishing a pattern of making threats but not following through, though this pattern became less predictive as of early 2025 since Trump adapted his behavior after the pattern was identified
“Trump had backed down in 21 out of 23 threats or something like that, right? So, the first thing is you can identify patterns.”
Trump's advisers (Bessent, Lutnik) typically freelance and don't repeat Trump's exact positions, but Carolyn Levitt was precise in saying the executive order would be 'signed' (not 'implemented'), a distinction that proved accurate since Trump signed but didn't immediately implement tariffs, suggesting taking Trump's literal language is more predictive than the common advice to 'take him seriously but not literally'
“if you take Carolyn Levitt, one thing that really sort of struck us was I think it was on before the February 1 deadline rather than the March one, but I could be confusing them. She said there in that press conference the day before on the Friday, she said there is absolutely nothing that Canada and Mexico can do to prevent the president from signing the executive order tomorrow. Signing the executive order. They never said they were going to actually implement the terrorist, right? And I know that sounds like a little cute or Yeah. But there there is something to that effect.”
The question of whether Trump will escalate tariffs or delay with 60 countries involved is nearly impossible to frame because you'd theoretically need 60 individual predictions, and the distinction between 'escalating and delaying' vs 'escalating and implementing on July 15th' is ambiguous, making Trump's tariff behavior harder to analyze than even war scenarios
“if you take July 8 for example you can't really and and we've you know we've struggled with this everyone does it's hard to make a call on whether he is going to escalate or postpone his deadline because there are 60 countries involved. So first of all you theoretically would have to make 60 individual calls right or predictions. Second thing is what if he says, you know, we're escalating the tariffs, but they're kicking in on July 15th. Is that a punt or is that him actually having increased the tariffs and so on and so forth? So, I mean, the short answer, Tracy, is there is no perfect way of doing it. And that's actually been one of the issues with Trump is that framing the initial question is almost as hard as predicting his behavior.”
Oil prices barely moved after the Israel-Iran conflict, and oil actually fell when Iran retaliated, which seems counterintuitive but clients familiar with Signum's analysis expected this because they were prepared for where the peak fear point would hit
“oil's pretty much flat from pre-Israel Iran war. VIX barely picked up...there's this big, you know, talking point and it was true again last month or two weeks ago whenever um uh the Israel Iran war ended. There's sort of this like oil collapses, right? And that's a counterintuitive outcome. A lot of our clients were actually expecting that.”
Geopolitical risk analysts sometimes put 30% probabilities on everything when uncertain, which trivializes the analysis; better to engage in rigorous scenario mapping that separates more likely from less likely paths even if perfect prediction is impossible
“I do not really have an intuitive understanding of how the geostrategic or geopolitical analysts whose notes flood our inboxes from time to time always during bad periods how do they arrive at conclusions therefore X we think the the war is going to end this way...And actually some of them put numbers probabilities on specific outcomes. So I think if I was a geopolitical analyst I would just put 30% chance on everything. That seems reasonable.”
When predictions are wrong, value still comes from getting other dimensions of the scenario correct (Bishop's team was right on regime change, Hormuz chokepoint, Iran attacking oil, etc.) and from learning to reweight factors for next time rather than abandoning the framework
“there's a couple answers to that. Well, there's several. The the first couple are deflection. The third is the real answer. Um, so one is in any of these situations, you've got lots of different predictions, right? So, for example, we didn't expect that Trump would actually go in and bomb Ford out because we expected the Israelis to do it on their own. But we were on the right side of the regime change call. We were on the right side of the Hormuz call.”
Tracy notes that despite Bishop's confidence about Taiwan's future, many people have been confidently predicting China-Taiwan conflict for years and it hasn't happened, suggesting humility about timing predictions
“I have a confession to make, which is I read all of those geopolitical analyses, but I always kind of wonder what I'm supposed to do with that information...on the other hand, there are people like me who have been saying with great confidence that this is going to happen for a while and it doesn't. So maybe that's that's some hope for you”
One key principle Andrew learned from Cliff Cupckin at Eurasia Group was not to get overly excited by every new headline, particularly claims like 'the BRICS are going to end the dollar' or 'the first gas contract was denominated in euros instead of dollars,' because these narratives have been circulating for 15-20 years without materializing.
“not getting overly excited by every new headline. Right. So I think when especially when you're at the beginning of your journey advice for everyone. Yes. I mean to me the best example of that is the zero hedge type headline about how the first gas contract was denominated or settled in euro instead of dollar you know or or just the bricks more generally. I I you started working when I was 22. I'm 39 now. the bricks have had a glorious future for you know almost 20 years.”
The relationship between Russia and China prior to 2022 was understood as an 'axis of convenience' (allies but not trusting each other) but this framework broke down post-Ukraine invasion, with uncertainty remaining whether they're now permanently aligned or still transactional, illustrating how historical patterns become useless when underlying conditions shift
“the relationship between Russia and China pre Ukraine war or pre2022 version of the Ukraine war. For 15 years before that, there had been an established talking point amongst pretty much all political analysts, which was it's an alliance. It's an axis of convenience, right? They get along, they work together, but they don't really trust each other. They don't really love each other. And so you you knew that when push comes to shove, when they had to like put their interest above the other, etc. You knew which way it was going to go. That was very unclear for the first like year. And and frankly, some could argue it's still unclear post Russia invasion, right?”
For the Iran-Israel scenario in mid-June, the U.S. intervention probability was derived by starting with 100%, subtracting the ~20% chance Iran capitulates diplomatically, leaving ~80%, then subtracting the odds Israel can finish the job militarily on its own (bombing or ground operation), and then adding back the possibility Trump intervenes for political opportunity even if not militarily necessary
“if you're trying to answer the question is the US going to intervene in the war and bomb for right. Yeah. To me, the odds of that would be you start with 100 and then you take out whatever the odds are that Iran is going to capitulate at the diplomatic table. So, you know, we can talk about how how you can come up with that view, but the idea is are the Iranians going to take the diplomatic offramp that Trump is giving them on that Friday in Geneva, right? So, those odds might be low, but they're not zero. So, you get to say 20%. Now that leaves you with 80%. Of that the question becomes is Israel going to basically finish the job on its own”
Bishop's final June 16th takeaways concluded that the overwhelming majority of scenarios end in a negotiated Iranian capitulation with no meaningful damage to global oil supply or Gulf assets, which proved a useful market-relevant conclusion even though US intervention (assigned 25%) did occur.
“The overwhelming majority of scenarios end in a negotiated Iran capitulation with no meaningful damage done to global oil supply or Gulf assets”
Most years, geopolitical risk is cited as a concern by analysts and investors even when tensions are low, making it a cliché that loses credibility; only certain years does geopolitical tension become real hostility with measurable market impact.
“You know, it's funny. Most years people like, what do you, you know, the beginning of the year, end of the year, things are going good, and it's like, what are you concerned about? It's like, I'm concerned about geopolitical tension. It's just one of these clichés.”
China may have a price at which it would cut off drone-component supplies to Russia, but that price is so far beyond what the US would be willing to pay (e.g., lifting export controls) that the question is moot in practice.
“even if there were a price, we are so far from being willing to pay that price that it's not going to it's never going to see the light of day”
Ozan Tarhan, a Deutsche Bank analyst, forwarded Signum research notes to Tracy Aloway, which led her to start reading and valuing Signum's commentary.
“I think I started first becoming aware of your commentary recently because uh Ozan Tarman, who we've had on the podcast over at Deutsche Bank, he started forwarding some of your notes over”
In June 2025, Bishop's base case was that the overwhelming majority of Israel-Iran war scenarios would end in negotiated Iranian capitulation with no meaningful damage to global oil supply or Gulf assets, which he characterizes as a good conclusion to have published given how events actually played out.
“he says, 'The overwhelming majority of scenarios end in a negotiated Iran capitulation with no meaningful damage done to global oil supply or Gulf assets.' I think that's a pretty good conclusion that at the end of the day, cuz if you figure people care about the markets and oil supply, more or less a useful conclusion to have been able to make on June 16th.”
Ian Bremer and Eurasia Group are credited as the 'founding house of political risk' as a consulting discipline
“I joined Signum from Eurasia Group uh which is sort of the you know the the founding house of of political risk.”
Petro Poroshenko, then an MP at the Maidan events Bishop witnessed, later became Ukraine's leader and famously held up a grenade at the Davos conference panel to demonstrate the brutality of the regime
“Similarly, we had back then he was an MP uh Petro Porchenko who later became the leader of the country, smuggled in a grenade from the Maidan revolutions into the conference hall and sort of held it up to show how the brutality of the regime was working.”
About 60-65% of Signum's clients are financial investors trading specific assets over short horizons, while 35% are corporates concerned with longer-term operational and policy risk, requiring different analytical frames
“about 60 65% of our clients are financial investors, right? That Joe mentioned or or alluded to. Uh about 35% or so are corporates and they obviously use us in very different ways”
Signum breaks down large geopolitical questions into sub-questions and sources the technical knowledge (like missile ranges) through research without maintaining an in-house expert, mixing open-source and expert interview approaches
“You do need technical knowledge but you don't need to have it inhouse. So we don't ever outsource any of our analysis like no one external has ever come up with a prediction for us or written any of our notes. But what we do is we break down a big issue into sub questions and then we go out and try to find the answer. And some of that will be in open source. Some of that will be trying to speak with an expert on XYZ missile range.”
Charles Meyers founded Signum Global Advisors in 2018, blending his banking/emerging markets background with expertise in U.S. politics, and hired Bishop to build out global analysis beyond the U.S.
“Signum is a political and geopolitical risk advisory firm that was founded in 2018 by a gentleman named Charles Meyers who was the vice chairman of Evercore ISI before founding Signum. And Charles had a career in banking with a focus on emerging markets, but was always sort of one foot in US politics as a fundraiser, as an adviser to candidates, etc. And he founded Signum essentially to try to meld his instincts about how markets work with his knowledge about US politics. And from there, he hired me to help build out the sort of global analysis beyond the US.”
Bishop joined Signum from Eurasia Group, where he served as deputy head of research and worked closely with Cliff Cupchin (the firm's chairman), learning principles like not getting overly excited by every headline and using rigorous analytical process
“I joined Signum from Eurasia Group uh which is sort of the you know the the founding house of of political risk. I was there for four years. I first joined Eurasia because I'd met Ian Bremer through a previous job at the World Economic Forum. So at the Davos organization and I joined as sort of right-hand man to their chairman Cliff Cupchin who really taught me a lot in that firm in that role. I ended up as deputy head of research”
At the World Economic Forum, Bishop worked on a global risk scenarios project about Ukraine's future (2013-2014) that was interrupted by the Maidan revolution, giving him firsthand exposure to frontier market volatility when half the board members and interviewees fled or were imprisoned
“One of the projects we worked on, for example, was about the future of Ukraine. And that was in 2013 2014. So the project was literally interrupted by the Maidan revolution. Half the people on the board of the project and half the people we interviewed were you know either fleeing or put in prison and I remember we were doing a a panel to to actually introduce parts of the findings in Davos and the prime minister of Ukraine his plane was he was basically disinvited on the day that the panel was taking place.”
Tracy notes that Robert Armstrong at FT had a major hit with coining the 'TACO' acronym to describe Trump's pattern of making threats but backing down, and Bishop's team published a table showing the same pattern weeks earlier but without catchy marketing
“So Robert Armstrong had sort of this huge success with the taco label. That was amazing marketing, but I have to say we were a little jealous because I think he wrote that in early May and in early April we put out a table with basically every one of the Trump threats. I think there were like 23 or so. Doesn't matter if you don't market it. It's all about that acronym.”
I always say what I'm concerned about is geopolitical tension — it's a cliché people fall back on when things seem fine.
“what are you concerned about? It's like, I'm concerned about geopolitical tension. It's just one of these clich”
7030 is the new 6040 — analysts who want to sound confident but are unsure now state 70% odds instead of the old 60%.
“it used to be that if you were unsure but wanted to sound smart, you say 6040. But these days you say 70. 7030 is the new 6040.”
China could theoretically have a price at which it would curtail drone supplies to Russia (e.g., if the US offered export control relief), but currently the US is nowhere near willing or able to pay that price, so the question is moot and will never surface as a real negotiating point.
“my answer to that would be in a way that one is actually not that hard because even if there were a price, we are so far from being willing to pay that price that it's not going to it's never going to see the light of day.”
Andrew's work at the World Economic Forum's Global Risk team involved traveling to frontier and emerging markets, meeting with government officials, opposition parties, and business/think tank communities to understand countries' economic futures, and then producing 10-20 year scenario analyses meant not to predict the future but to force countries to rethink their business models and policies.
“the job I had there was really fun because essentially you know the the organization is best known for Davos. But the team I was in which was their global risk team basically send their team members throughout most frontier and emerging markets to meet with government officials, get a sense of where their head was at in terms of their country's sort of economic future, future economic policies, etc. then meet with the opposition and the business community and think tank community and essentially write up scenarios about the future of that country at a sort of 10 to 20 year outlook. Not trying to get it right, not trying to predict it, but trying to essentially force the country to think twice about its business model.”