eliotho

couldn't have said it any better

it came from the data (UN Comtrade) that notably doesn't include sanctioned oil flows (Iran, etc). On top of that, China's reserve levels are a state secret, yet, the model's framework is BYOD (Bring Your Own Data) which gives the depletion timeline for free. Also, the model is more of a sensible baseline than a prediction

Thanks! Two answers (repeated in other comments): UN Comtrade data doesn't include sanctioned oil (Iran), and nobody (except their government) knows China's actual stockpile. The model is more of a sensible baseline/stress testing tool than a prediction, the cool part is that anyone can BTON (bring their own numbers) and rerun their scenarios

Thanks, added to list of possible UX improvements

Yes, and the network setting is flexible enough to allow smaller supply chains where nodes don't have price setting power

the models, proofs and writing are mine (with some AI assistance for proofreading/formatting). AI was mostly used in the visualization and the rerunning of multiple scenarios of the numerical examples

This pipeline predates the data but its oil is routed to Bab-el-Mandeb which is in the network. That being said, the numbers are more of a sensible baseline as the actual flows for many countries are unknown/sanctioned.

France imports 0 oil directly through Hormuz, but when the Strait closes, all other countries start raising their safety stock which increases oil prices. This makes France's stockouts very expensive mostly due to price (not flows). Which is contagion without direct connection.

Think of the 2008 crisis where companies that had nothing to do with Credit Default Swaps were exposed to the crash due to network effects, potentially crashing the whole economy.

Then, the government intervened by bailing the banks out. Here, it's not really clear if there is even an effective intervention.

this is an interesting market design question: the point is that tapering would require everyone knowing everyone else's depletion clocks. As they are unknown (sanctioned trade, non-public state figures), the opacity is the game itself (that I called game of chicken in other comments). Surely the main players are trying hard to guess each other's numbers by every mean possible

This is an interesting insight, as usable reserves < reported reserves the clocks in the model are optimistic

Fair catch, the data predates the reroute. Although this pipeline is routed to Bab-el-Mandeb which is in the network

That's actually the intended behavior: while reserves are silently being spend is when the crisis is brewing. Although the main point is that nobody knows China's reserves, but this allows to calibrates scenarios based on what you believe is plausible

Thank you! Much appreciated. On the suspense, we are all riding the same train :$

And this is what the model price formation assumes, and in fact, the silent mechanism that makes the crisis worse. Reserves silently deplete for each country, and each epoch where they exhaust is when the price rebalancing occurs IN A SUDDEN SPIKE, affecting other nodes that are not even connected to Hormuz, which is one of the conclusions of the paper. Either directly or indirectly all countries feel the pain: the question is who can stand the game of chicken the longer before intervening

There are two versions of the model: -The one rendered by default (called Endogenous), with endogenous price that affects the demands according to the price elasticity slider. Reflecting how reactive are the nodes demand wrt price -With fix price (called Fixed): that in the oil market doesn't apply, but it's an interesting baseline to consider oil purely as flow. And as a modeling tool, this allows the model to capture small supply chains that don't have price setting power.

Thank you. Yes, in desktop there is one (that might still be going a little bit too fast), but in mobile it might not be that easy to find. Perhaps I will slow down the speed in mobile by default and change the location (should be in the bottom right corner, the 2 wk/s can be changed to 1 wk/s)

This works as the same feature reversed. Will think of a way of adding something like this

Fair point. Actually this is both a semantics oversight on my part and also expected behaviour. at 100% retained there's no shock, but the model's countries target consumption plus a large safety buffer, and some can't fill that target even in peacetime, so they draw reserves at baseline, the shock scenarios show the additional damage relative to that baseline

Much appreciated, server seems to be (fingers crossed) going strong so far

This is a nice idea. I will build this a feature on the scenarios menu. And it would give an estimate of how much time doing this buys China under different configurations

Which is the interesting game-theoretic aspect of the whole conflict. China really hasn't revealed their hand

Exactly, which is what makes the simulation interesting because nobody really knows China's reserves clock.

But with the tool, you can put your guess number and see that the game of chicken also has an expiration date for them

Thanks, the modeling is similar math to the financial banking networks paper by Eisenberg and Noe Systemic Risk in Financial Systems (used as a stress tool by regulators after the 2008 financial crisis). My adaptation is combining this with the inventory management part in my article: https://arxiv.org/abs/2607.17491

For the importer nodes those are IEA mandates. In the specific China case, the UN Comtrade data doesn't report sanctioned oil (Iran)

and the interesting thing is that the common factor is that all these crises (oil, financial, gas) spread silently until a node collapses and there is a domino effect over the whole network

That's kind of the point because it hasn't been totally 100% closed. There's both sanctioned and unsanctioned oil flowing, which is the point of the scenarios in the simulation. Also it's more of a simulation/stress tool at a sustained closure than a prediction one

>What concrete predictions does your model make?

Well, the model is less of a prediction and more of a stress testing tool. But under the hypothetical closure scenarios it shows the timing the oil reserves of distant countries exhaust, as well as the systemic effects on pricing (the France paradox).

>What developments in pricing/other would indicate that your model is wrong or incomplete? The model has a stylized way of incorporating pricing as a function of the total supply. In practice, when countries ration their oil that's beyond the scope of the model. That being said, the implied pricing trajectory is estimated and could be tested (the staircase graph showing prices constant while countries absorb the shock with their reserves and rebalanced whenever there is a reserve depletion).

>Nice website regardless, but I'm a bit skeptical that the dynamics of the global oil/energy market can be accurately predicted. Thank you! Indeed, but I think having at least a stylized testing tool might be useful for policymakers :$ (assuming decisions are ever data-driven lol)