Variant Perception

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WHAT DID MOST ENERGY EXPERTS GOT WRONG IN THE FIRST 3-4 MONTH OF HORMUZ CRISIS (including myself). Mostly agree with @WarrenPies here. Would add a few things: wrt (2) - would rephrase it: EV+mass transit actually did not have that much impact - transport demand in May was just 600kbd below pre-war baseline, as per IEA - all the substitution sits there. What was surprising is that out of 2.5mbd of refinery run cuts 1.9mbd hit things other than transport fuels - mostly petchem. Which was combination of pause in petchem stockpiling, petchem destocking and some substitution (coal to chemicals) x.com/ALikhodedov/st… On top of that would add (4) refinery bottleneck was more severe than I anticipated. The way I thought about it - ok - we lose 13mbd of flows via Hormuz of which 1/3 is products. But 2/3 are still crude. So I certainly did not forsee a current situation when products pressure is so much higher. Why did it happen? China run cuts + RU refinery outages + dark transits/Hormuz shuttle are almost exclusively crude - so worsen the crude balance, do not help product balance. And of course almost all the SPR flow is crude. If i remember correctly @UnintendedCons5 actually read this specific part pretty well in the first week of war arguing that crude actually could be at sub 100 levels despite the massive outage and products would be a much bigger problem. He had a different breakdown of things that plugged in the gap that transpired at the end, but the idea was right (I did not get it back then).

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China's inflation leading indicators are peaking, well before Europe's. Why: energy stockpiling and a shift to renewables, plus a lack of fiscal stimulus that kept household demand muted.

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There's a real divergence right now between our leading indicators for core and headline inflation in the US. Headline inflation stays above target in absolute terms, but the impulse and core inflation pressures are peaking

recent vol in inflation LEIs poised to push up stock-bond correlations. It continues a macro environment where bonds are less effective as an equity diversifier gold's meme-like price collapse is an opp to add gold exposure for multi-asset portfolios

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US margin debt as a % of GDP is near all-time highs, but as a % of market cap, it is just getting back towards the middle of the post-2010 range. That said, the speed of the surge does look like Dot Com

Updating the US strategic petroleum reserve (SPR) chart, the drop is pretty stark, back to levels last seen in 1983

Very interesting article from @JoachimKlement open.substack.com/pub/klementoni…

US equity participation continues to broaden out. The Value Line Arithmetic is making higher highs and higher lows. This is NOT what major bubble tops typically look like.

Agree with @thorstenbenner -- the German Chancellor is now speaking clearly about the impact of the second China shock on Germany's automotive industry. It lays the ground for a subsequent shift in policy 1/2

Can we get this big divergence between products and crude for longer than a few weeks until the oil industry closes any arb as everybody and their brothers runs their refinery as hard as they can to print money? Answer: I think so, yes. In general, if there is not enough refining capacity to satisfy product demand while crude remains available, that is what one gets - record refinery cracks. Why do we not have enough of it? Because of geopolitics. Russia lost some 3mbpd of refining capacity. China reduced runs by the same amount, but not so much voluntarily but due to the SoH crisis in combo with a weak domestic market. The latter means the CCP keeps gasoline and diesel prices capped. If crude spikes, Chinese refineries have no margins. Is the CCP willing to do more? Comes down to crude price. Unlikely while the SoH flows remain interrupted with price spikes following such interruptions. No the Houthis joint the party. I have a hard time to see China increase runs here.

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Labor market is pretty neutral right now - not inflationary, not recessionary. Wage growth isn't hot, but it's not collapsing either. Unemployment is sitting right near the natural rate, so there's no obvious pressure building.

Oracle CDS widens back towards the highs

🇨🇳The founder of Moonshot the Chinese company that created Kimi K3 to overthrow Anthropic and OpenAI lead just gave a 40 minute masterclass on their progress. The best explanation I’ve seen on Chinese cheap models. Free game!! Must watch…

Kimi K3 may be an important inflection point for AI. Potentially negative for Anthropic and OpenAI while being net positive for essentially every other company in the world. I mean that very literally. Although the real “Sputnik moment” would be an open-source frontier model that was also token efficient unlike Kimi K3 which is 50-70% more expensive to run than GPT 5.6 per Artificial Analysis. Rationale:   A world where there are only 2-3 dominant frontier labs with 90% inference margins is net negative for every other layer while being awesome for those 2-3 labs. Those labs would become monopsonies for power, data centers, semiconductors and hyperscalers and would obviously vertically integrate over time into all those layers while also completely subsuming the application/software layers.    Anything that lowers margins and increases competition at the model layer is good for every other AI layer: power, semiconductors, hyperscalers, neoclouds and yes even software.   This is why Jensen is so supportive of open-source. An open-source model requires the *exact* same amount of compute to run as a closed frontier model of similar size and architecture. Kimi K3 is roughly the same price as GPT 5.6 Terra on a per token basis, which actually suggests that it is less computationally efficient as I am sure that GPT 5.6 is priced to a higher margin than K3. And given that K3 is a token wastrel, i.e. token inefficient, it is significantly more expensive per task than GPT 5.6 and Grok 4.5, which are much more token efficient. Cost per token and token efficiency (i.e. intelligence density per token) are the drivers of intelligence per unit of cost. The winning AI companies will be those that offer the most intelligence per $ over time.   Lower margin % at the model layer = more margin $ at every part of the infrastructure layer and is a godsend for software. This can happen either through open-source models like K3 at the frontier *or* having a vertically integrated model company like Meta, SpaceX or Google at the frontier. Both outcomes result in a lower margin % at the model layer as vertically integrated model companies don’t really care where the margin $ come from. This is why it was so painful for OpenAI and Anthropic when Google was right there with them from a model competitiveness perspective and why Grok 4.5 and Muse 1.1 were just as important as Kimi K3. 
The reason Kimi K3 is only *potentially* negative for Anthropic and OpenAI is 1) the @ericvishria point that the Claude and ChatGPT products and harnesses may be more important than their models today and 2) the hypothesis that they have much more advanced model checkpoints internally that are already being used for RSI. In the latter scenario, reaching RSI even a few months ahead of other labs might be enough to cement a permanent lead. Time will tell on both points. And likely fairly quickly. Caveat would be that since Kimi K3 is not token efficient and thereby actually more expensive than ChatGPT 5.6, we may need to see a more token efficient open-source model at the frontier or see Grok 5/Composer 4/Muse 2 at multiple points on the Pareto frontier for this potential risk to Anthropic and OpenAI to play out. And I am sure they will both vertically integrate as quickly as possible while continuing the product/harness strength they have shown over the last 8 months.

The slowdown in US wage growth is pretty broad-based, applies to jobs of all skill levels.

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