With the bull market and now bear market in gold, I had lost sight (temporarily) of what I am trying to do with GLD/TLT. My thoughts for the last few weeks were all on why was gold so weak. And this is fair enough. But the real issue is why has TLT not been weaker? My thoughts on TLT were reignited when I was reading a Special Report on the treasury market in the Economist. Generally speaking a good report - but one paragraph really exercised me. The writer foolishly believes that central clearing will improve liquidity for treasuries.

I have written a letter to the Economist, explaining why this is wrong, which is below, but I doubt it gets published.

I have been intrigued by clearinghouses for years now, ever since I read about a Nordic power market central clearinghouse going bankrupt back in 2018. It took some digging to work out what went on, but to cut a long story short - clearinghouse have no ability to price risk, and no incentive to do so. So they basically assume tomorrow will look like today, which creates huge momentum trades. The better something is doing, the more leverage they will supply. And in essence, what happened in Nordic power in 2018, is getting primed to happen in treasuries.

You may well say, how can you be sure the treasury market will blow up? Well the good news is we had a dry run in the gilt market already. When Liz Truss shocked the gilt market, it caused UK gilts to diverge radically from other bond markets for a good month or so.

And we almost realised a Treasury blow up during the liberation day tariff sell off in 2025.

So how do clearinghouses cause illiquidity in gilts and treasuries? Well clearinghouse are owned by profit maximising corporates, and so have a naturally tendency to try and maximise volumes. If you look at the middle chart below, you can see that banks used to be borrowers from repo markets, but are now lenders. This chart is 7 years old, but as we have seen above, hedge fund borrowing would have only increased.

Why does this create illiquidity? Well hedge funds buy physical treasuries and then sell futures against them. There is a small arbitrage profit - but with leverage it can be substantial. Pre GFC - you could not use clearinghouses to do this trade, as the cost of initial margin would make this prohibitively expensive. The only way to do it would be to borrow from banks - which is what LTCM did. LTCM was very secretive about how much it had borrowed to do this trade - but once the banks found out the size of the borrowing, they cut lending, positioned themselves the other way, and scalped LTCM.

Theoretically, with central clearing, this should not be possible. All trades are done with the central clearinghouse and require initial margin. However, this ignores another change in regulations - compression. Essentially, clearinghouses will look at your trades, and if they think they are similar enough, will allow you to compress the trades, and return initial margin to you. LCH (the main fixed income clearinghouse) used to boast of the amount of compression it did a year. The last number I have is USD 800 trillion in 2019. Treasury cash futures basis trade should qualify for compression.

In my view, compression trades make clearinghouses as dangerous as banks pre GFC. It removes the excess margin which kept them safe in 2008, and has a nasty side effect of making the market bifurcated - that is in this case, hedge funds on one side, and banks on the other. The banks know all about this - and have been urging reform - but on deaf ears.

Anyway, given the size of the basis trade market, and the relative unattractiveness of US 30 year treasuries, the market looked primed for a big move.

If you read this far, then I can tell you what I think will happen, and why I like short TLT so much. At some point, there will be a shock - tariff increase, big increase in fiscal deficit, something. And Treasuries will fall. The clearinghouse will raise margins, and both lenders and borrowers in the repo market will have pay more initial margin. That is BOTH sides of the market will have to put up cash, meaning that BOTH sides of the market suddenly do not have cash, and the market become illiquid, leading to further falls in treasuries. The treasury market will become very illiquid, and traders will be looking for other ways to hedge their position. TLT being and ETF - can provide liquidity - and I see it trading to a big discount to NAV, as all the hedge fund will need to reduce their physical holdings of treasuries. Of course the Fed will be motivated to act, although Kevin Warsh and Scott Bessent have indicated a tendency to want the Fed to do less - there is a chance they let this play out. That is I expect the treasury market to totally freeze up, and TLT will act as grey market for US 30 year treasuries - which will be much lower than it is today. I would also expect US assets to do poorly in this situation.

Why is weak gold good for this trade? I owned gold as a hedge against the Federal Reserve not allowing the market to clear properly. If gold is falling because the Fed is reducing liquidity - then the risk of a treasury blow up should be rising substantially. Exciting times.

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I think gold still looks interesting - mainly because Donald Trump is still President. This makes owning treasuries seem unattractive, AND makes it likely he will pressure the Fed. That being said, it is some 25% down from it peak, and squarely in bear market territory.

These days people typically talk about passive investing distorting the market - see Michael Green’s work. Personally, I have found market tends to find a way to make money from distortions. If we look at ETF flows into gold, if it was truly distorting, gold should still be at highs!

That being said, there are two style of “passive” investing that I do think distort the market - factor investing and CTAs. Both these styles are dominated by “robots”, who tend not to really think about what they are doing, but follow “rules”. The rules tend to be pretty self explanatory - and you see them in many big funds like Bridgewater was well. We will just look at gold and factor investing for the time being. Factor investors tend to love gold when the US dollar is weak. So I was bearish gold in 2012, and been bullish since 2022 - in part because this “factor” looked to be turning at both these points. Gold this year peaked at the same time time dollar hit its low.

Gold also tends to do well when US rates are falling - but for me this is much more a secondary consideration. If the US is raising rates, but the US dollar is still falling, expect gold to do very well. That being said, gold also peaked when US 2 year yields were at their lows.

There are lots of different assets and different factors, but for gold these are the key. What I can tell you is that factor based investors robots just move money in and out of assets based on these factors. I am 99% certain factor investors were buying gold in 2025 and early 2026, and now they have become sellers. And should dollar weaken, they will likely become buyers again.

Even dumber investors robots are CTAs. Who are basically momentum investors. If you ask a CTA they will tell you they are not a momentum investor, but they are. They will probably claim they have “better stops” than anyone else, but this plainly bullshit. CTAs love buying assets going up, and selling assets going down. Typically they use moving averages to determine buying and selling. My guess they went very long gold in early 2024, and are now fully out of gold as of today, and possibly even short selling.

What happens in markets these days - in my view anyway - is that some factor changes (interest rate cut, oil price surges etc) and the factor investors duly move money around. This causes the CTAs to start buying this new trend, and can push as asset like gold up a long way. But then factors change, and the process goes into reverse. As mentioned above, I like gold, mainly because President Trump is still President. What are the chances that he begins to complain about a strong dollar, or interest rates being too high, between now and the end of his term? 90% seems reasonable. Where is market positioning on a weak dollar? Pretty close to max short on Yen.

And also pretty bearish on the Swiss Franc.

Not so bearish on Euro, but still below recent highs.

The funniest thing about all of this, is that even though I am looking at Euro, Yen and Swiss franc - there is one currency above all that should be linked to the price of gold - and that is the Chinese Yuan. For me a strong Yuan tends to imply a strong gold price. Chinese Yuan has been conspicuously strong.

I find it really hard to be negative on passive ETFs that buy and hold indices - its an efficient way to hold an asset that is designed to go up over the long term (sorry Michael). But I do find it easy to be negative on passive “rules based” investors like factoring investing and CTAs. They are always doing dumb stuff. Basically they seems to have said, “oh dollar has rallied against Yen - sell gold”. When I see Chinese Yuan is still strengthening against the US dollar and has USD 1 trillion trade balance to deploy, and President Trump is still President, I struggle to get bearish gold. CTAs and factor investors are probably short and out of gold, and short Yen and Swiss Franc. Yep - makes no sense to me either - but this has always been the problem with investing using historical data - you are fighting the last war, not this one.

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I have like gold as part of GLD/TLT trade for a long time, and it has been a great trade - but last few months it has been very lacklustre. It has traded right back and now through its 200MDA, which might mean its time to add, or its breaking down. What follows is a stream of consciousness analysis…..

The truth of the matter is that all the price action has been in the gold part of the trade. I think the market got VERY excited about gold when it started to outperform S&P 500. This meant you could be BEARISH (owning gold), and outperform the S&P 500. Sadly, this trade, GLD/SPX, has smashed through the 200MDA to the downside, and as of today has created what “technical analysts” call a dark cross. That is the market is saying you should sell gold to buy SPX.

What’s the problem with gold? In the last few months, and contrary to market expectations earlier this year, markets have started to price in the Federal Reserve ACTUALLY doing its job.

Gold has been far more sensitive to central banks tightening than the long end of the bond market or equities.

Equities have not being bothered by rising bond yields at all. That is financial assets have been very resistant to rising yields.

I guess another way to put even when bonds have a higher yields, investors still prefer equities.

So the problem with gold, is that it has reacted EXACTLY as you would expect to higher bond yields, but equities and long dated bonds (or financial assets) have not. To be fair, some financial assets such at Bitcoin and Private Equity have been weak, but broader indices have been fine.

While I had a good fundamental reason for buying gold - mainly on central banks getting out of treasuries - I did worry about speculative excess. There was only limited signs of excess in gold. Back in 2012, we had seen ETF holdings of gold rise from 20m troy ounces to 80m, and in the 2016 run up it went from 50m ounces to 111m ounces. Both marked tops. So far we have seen a run up from 80m to 98m troy ounces. This was not screaming speculative excess to me.

On the other hand, silver did take on a speculative nature in late 2025 and early 2026.

Looking at flows into a silver mining ETF (SIL US), it definitely became excessive - but has seen some meaningful outflows recently

Unlike most people, I have been bullish and bearish on gold in different parts of my career (my experience is that people choose to be either bullish or bearish gold, and then never change their views). Back in 2012, I was bearish on gold, as I saw Indian Rupee weakness and broad based US dollar strength being bad for gold. Indian are big buyers of gold. However in this market, gold has moved independently of the Indian Rupee.

I had assumed that the most recent bull market in gold has been driven by central bank buying out of China and Eastern Europe. I have no reason to believe that this buying has ended. China still has an annual USD 1 trillion trade surplus that needs to be deployed somewhere, and it is not going to be US treasuries. And here we get to the crux of the problem. Do I believe that the US is about to undergo fiscal austerity? No. Do I think that Donald Trump won’t try and influence monetary policy again? No. These are bullish for gold.

The real problem is whether I think AI trades makes a better hedge than gold on monetary craziness? Now we get to the crux of the problem. In the 1970s, oil and gold was the best hedge on monetary craziness. Are semiconductors a better hedge these days? Is this was SPX/GLD already saying? If the 1970s was about cars and oil, maybe the 2020s are about compute and semiconductors? If we do Philadelphia Semiconductor Index (SOX) v gold chart, then we get a very interesting chart indeed.

What I love about this chart is that it did pick up the when you should have flipped from gold to semis in 2012, and it does give exactly the mixed vibes on gold versus equities that existed for the last few years. And it does pick up the very toppy vibe in semis that exists today. But also suggests that the craziness might not yet be done. But the story seems clear - hyper competition is driving a capex frenzy, that will end in a bust. At that time, a US fiscal deficit of over 10% will likely drive a weaker dollar, higher gold and probably a weaker long end of the treasury market. Just not yet, or that is, the gold trade is still early.

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This is the 4th Chapter of my book, and will live behind the paywall. At some point, I will make it to a single product, but that is in the future.

I started my fund management career as an Emerging Market analyst in 2002. I had wanted to be in emerging markets because I knew that China would be the next big thing. But in 2002, although China was starting to move, the big thing in markets at the time was the “convergence” trade. Essentially, whenever a country was seen as joining the Euro, markets would buy their bonds and currencies, with a view to some eventual convergence.

Convergence was a political rather than an economic trade. To join the EU, you needed to meet some economic measures on fiscal spend, reforms and debt to GDP, but once you were in, you were in. And the ECB would accept all European debt as equal, regardless of underlying economic trends.

I remember in 2005, I travelled to Nuremberg to watch Australia play in the confederation cup, and I started to think the convergence trade might be a problem. I had recently been to Warsaw and Prague for work and Ljubljana and Bratislava for pleasure, and what shocked me was that Nuremberg was much cheaper than all these places.

Does convergence make sense when you are already more expensive than parts of Germany? I didn’t think so, and I started to get nervous about the convergence trade. I put my concerns to the back of my mind, until in late 2007, credit concerns started to rise in the markets.

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When I first starting to think about the idea of a pro-labour theory of markets, I assumed the cost of capital would rise for political reasons. The long period of "pro-capital” policy had lead to the creation of large pools of capital. The first, and most exceptional in my view were foreign reserves. The idea of buying another countries fixed income was a completely foreign idea before 1980. All foreign reserves were gold, but from 1980, led by the Japanese, buying US treasuries became accepted as a “better” form of foreign reserves.

It also happened that from 1980 to 2000 or 2015, owning treasuries was much better than owning gold, which reinforced the idea of owning bonds over gold. This has since reversed.

I saw buying treasuries as foreign reserves as pro-capital policy, as much of the Japanese buying of foreign reserves was meant to keep the Yen weak - that is to keep labour costs low. Competitive devaluations is most clearly a “pro-capital” policy (devaluations reduce labour costs, and boost competitiveness - which favours the owners of capital). In the new pro-labour world, I envisaged governments endeavouring to keep their currencies strong, and hence foreign reserve growth should slow or reverse. Japan shows this trend, but official holdings of treasuries have been falling for a while now. Total official foreign holdings of treasuries has been weak.

I also saw that rising interest rates should begin to kill interest in “alternative asset managers”. These businesses held huge amounts of “dry powder” - but it is hard to square this dry powder with redemptions that most of these businesses are now seeing. The performance of the Invesco Private Equity ETF confirms these problems. That is two big pools of capital - foreign reserves and private equity are already displaying signs of problems.

I also assumed rising wage demands would start to effect the cash piles that had grown in American corporates, the third biggest pool of capital. Microsoft for example had seen cash and equivalents go from USD 25bn in 2007 to USD 140bn in 2021. This cash pile has now fallen to USD95bn or so.

Google claims to have USD120bn of cash and equivalents, but are choosing to raise USD80bn in an equity raise.

Obviously, around USD 100bn of cash equivalents seems to be the line in the sand for Google, and they are already spending everything they make on AI. But they want to spend another USD80bn, so raising equity is the obvious answer.

So to my surprise, rather than wages rising, it has been the price of semiconductors that have been the driver of inflation, or perhaps more correctly, the biggest beneficiary of governments working to halt recessions. For many other firms I look at rising labour costs have drawn on capital reserves, but with big tech, is is spending on semiconductors that has reduced their pool of capital.

And the AI boom has ended one of the enduring features of capitalism. Technology should make things cheaper. But technology itself is no longer becoming cheaper.

From what I can see, the rising cost of capital continues to work its way through the system. It has already stunted the use of debt markets and private equity. It has reduced the size of foreign reserves, and also seen central banks try and reduce the size of their balance sheets. Some how corporates have managed to keep their cost of capital relative to government costs very low, but for how much longer?

Hence corporates are now turning to one final source of capital, equity markets. And here we can see that 2026 is big year for IPOs.

The question then is when or if does a rising cost of capital begin to impact equity markets? Or has it already done so? Gold vs S&P500 has been indicating issues for over a year now.

For big US corporates, they have engaged in “capital wars” with each other to dominate the AI trade. But how much capital is left? And it is making capital expensive for everyone. I can see the political winds shifting to try and get costs lower, but I can not see how that will come via wages or unemployment. At some point, governments will want to see price wars among corporates. I just don’t know when.

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The big news is that Nasdaq fell 4% on Friday, which takes it all the way back to where it was a month ago.

The AI trade has become huge. And it is noticeable that equities have diverged from HYG. When HYG is going down, then equities tend to follow.

But credit spreads remain tight.

The real driver is the market reassessing the likely interest rate path of the Federal Reserve. US 2 year rates sold off on strong data.

So my main view is that a negative shock on bond yields led to a sell off in momentum stocks.

The big problem is that if I look at memory spot pricing, its hard to see any big change in the market. That is AI demand is still pushing prices up. The proposed equity raises seems to encourage that view.

We have seen a big increase in announced IPOs in 2026.

Could this mark a top? Unlike 2000, buybacks will still be greater than issuance.

As a share of nominal GDP, it is a large number, but not outside of historical ranges, but certainly at levels that suggest caution.

This issue here is that AI is now the main driver of growth and inflation. Could the Fed really end the AI boom by raising rates? My guess, given the AI/Cloud cartel that now exists, interest rate policy would be almost totally ineffective. JGB yields for me still reflect government policy that is inflationary rather than deflationary. A real change would be government policy to encourage competition and lower prices - something I do not expect from a Trump Presidency.

The price action of JGBs in the 2000s was starkly different.

My best guess is that the market is worried that new head of the Federal Reserve, Kevin Warsh, could be a Paul Volcker in disguise. With consumer expectation of inflation running at 6%, to my mind short rates in the US should be closer to 8 or 9%.

Politically, I find the Fed being uber hawkish very hard to believe. To me it looks like a position clearing sell off - but not a top. If I saw evidence that AI adoption was slowing, then I think we could read a top.

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The way I work is I try and think about the world we live in, and what are the most likely long term outcomes. As of today, I still think a pro-labour world which drives higher inflation, and an eventually dearth of capital. My favourite way to play this has been GLD/TLT. This has been a great trade - but to paraphrase Monty Python, is seems to be having a bit of a lie down after a long squawk.

I don’t really read much other financial research. I do read Chris Wood, and I also quite like IMF reports. But one person I do pay attention to is Jeff deGraaf from RenMac. Why I like Jeff is that he only looks at charts, and then just publishes the most interesting ones. This chart showing an inflection in industrial metals versus precious metals.

He follows it up with this chart on general industrial metals breaking out..

And then this one on aluminium in particular. Aluminium in particular is related to war in the middle east as this has reduced supply.

I have been surprised by the relative weakness in gold since the war in Iran started, so maybe switching gold to industrial metals makes more sense? I do remember that copper/gold ratio and the US 10 year yield were highly correlated for a long time - but that this relationship broke down in recent years.

Looking at the above chart, you could argue gold is too expensive relative to copper, given the move in bond yields. For me, it just says that gold became a much more attractive reserve asset from 2022, when Russian foreign reserves were frozen. So gold has been much better than copper in recent years. Should I switch? My read of markets is that Central Banks remain far too dovish. And politically, cost of living hurts politicians far more than a bullish stock market helps them. So at some point, central banks will be forced by markets to raise rates (the long end has a huge sell off), or central banks raise short term rates to a high level to prove their inflation fighting skills. See circled part below.

I can not help but think, in either a long bond sell off, or a central bank induced slowdown, gold will outperform copper. I think what I am saying, is that in a free market world, treasury yields and copper/gold would indeed move based on economic activity. In this new pro-labour world of tariffs, and industrial policy, yields reflects lack of faith in central banks and governments, and gold also reflects lack of faith in central banks and governments. How will copper do with 10% on 30 year treasury? I don’t know. Maybe okay? But I think gold could keep going higher.

I guess what I am saying, is that backward looking models make industrial metals look attractive. But political analysis, which I think is more important these days still favours gold.

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I have been generally very bullish on fertility rates rising again. I saw three big changes - first was rising wages, the second was improved reproductive technology, and thirdly was the rise of “work from home” culture, which made raising children easier. The one country that might be the first to show an inflection higher in birth rates was Denmark, which has greatly liberalised its access to reproductive technology. Sadly, month birth data has not really supported this view. Laws were liberalised in 2015, which saw a birth spike, but post Covid birth rates have fallen again.

I also liked Denmark, as Scandinavian nations tend to be quite progressive, with strong maternity rights. Despite this, Danish fertility rates remain low.

My brother forwarded to me a post on Facebook under the account name The Visible Hand which I found interesting. Basically, Visible Hand is arguing that fertility rates are declining because children are no longer a necessity, but a luxury. Whereas a hundred years ago, you needed kids as free labour and potential pension pot, now these needs are met through other means. The comparison he made was to horses. We used to need horses for everything, but as mechanised transport took off, horse population has collapsed, and owning a horse became a luxury/prestige item.

And we can compare this to say the numbers of chickens that exist today. Obviously we still need chickens for sustenance, and so their numbers continue to increase. For anyone familiar with chicken breeding will be familiar with the extreme use of technology to optimise chicken production.

It is an interesting argument, and it does raise the question of free-will. Horse and chicken populations are closely controlled by humans. And after the Malthusian fears of over-population in the 1960s and 1970s, humans made a conscious effort to reduce population growth, most notoriously with China’s one-child policy. But for the last ten years or so, politics has switched from reducing population growth, to promoting it. But as the Danish data shows, with still little to show for it.

As anyone with children knows, raising kids is expensive. And getting more so. Below is an inflation adjusted cost of raising a child from birth to 18. If we divided these numbers by 18, we get that annual cost in 2026 dollars in 1960 was USD 6,000 a child. In 2026, you are looking at USD 20,000. Or in other words, for the money you pay for one child today, you could have raised 3 children back in 1960.

As someone who grew up in the 1970s and 1980s, I can tell you that some of the cost savings came from a blatant disregard of modern health and safety norms, and I don’t think we are going back to a time when 6 years old are allowed to walk home from school unsupervised. The other big change has been the rising cost of housing. Rents have been rising as a share of income for decades.

One of the reason I am still bullish on fertility rates is that women increasingly are freezing their eggs, and then using IVF later in life, presumably when their incomes have risen. In the UK, we have seen a share rise births from frozen embryos, and a decline in births from fresh embryos.

The bullish argument on fertility is that with rising female participation in the work force, the age that couples started families were pushed back, and this naturally reduced fertility rates. But now that IVF is “solving” that problem, fertility rates should rise back above replacement rates, but with a lag.

The bearish argument is that capitalism required more labour in the post World War II period, so humans responded to the low cost of raising children, and relative high wages by producing more humans. And now, as automation and AI reduce the relative wages that labour can command, we are reducing supply, and turning child raising into something akin to raising thoroughbred horses.

When I write both arguments down, both are reasonably convincing. Even from my personal experience. I would liked to have had more children, but after having our second child at nearly 40, one more was a bit daunting. On the other hand, the two children we have are far better educated, travelled and trained than I was at that age. They are also more expensive than I ever was.

I guess what I like about both arguments, is that they both point to a world that is getting “better”. If its the first argument, technology is solving the issue of women having children at an older age - which I like. If it is the second, falling population growth is due to substantially more investment into children, which is creating a “super-generation” of humans. Right now, I would say the evidence is evenly split. As a fund manager, I would argue that the markets are not priced for rising fertility rates, which is what makes it more interesting - but this type of thinking is why most people hate finance people.

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GLD/TLT actually lost 1.7% in May, as gold remains lacklustre, and TLT which looked like it was ready to break down, staged a rally. The US 30 year treasury briefly broke 5%, but came back again.

Coming into the month, it was beginning to look like credit markets were backing away from endlessly financing AI spend at both Softbank and Oracle, both firms closely related to OpenAI. Oracle CDS was perhaps the clearest example of these concerns.

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I had lunch with an old client a few months ago. One thing he said to me was the GLD/TLT was my only idea. A little harsh, but maybe is is the only idea I have been REALLY committed to for the last four years or so. And why not? It WAS a great idea. But since a blow off peak in January it has been going sideways.

The really problematic part at the moment is gold. For the first time since 2024, its threatening to break below its 200MDA.

If I had to put a reason to its weakness, it would be almost exclusively with the movement in short term interest rates in the US. Since the War in Iran, markets have been pricing in a more hawkish Federal Reserve (and changing governor as well).

The 30 year has sold off a little bit, which is why GLD/TLT has held up, but we have not had a decisive move lower.

Now in a pro-labour world, I expect the long dated bonds to LEAD the Fed fund rate higher, as it did in the 1970s.

If that line of thinking holds, then I expect the 2 year treasury yield to move higher from here - back to 4.5%, where there 10 year is now, and possibly 5%. Given that the Atlanta Fed GDPNow forecast if 4%, this does not seem excessive.

Looking at the 2-30 spread on US treasuries, it seems possible that 2 year yields could rise another 1% before forcing the back end 30s higher. The 0.7% higher move in 2 years, has seen gold drop nearly 20%. Could another move of a similar magnitude see gold drop 20% again? That would take gold back to USD3,800 an oz, or where it was late last year. The problem would come if the yield curve flattens, and TLT does not fall. In rough number, that would imply a fall back toward 4 on GLD/TLT.

That is the risk if I just looking at market movements this year. Fed Fund rate expectations rise, gold weakens, and yield curve flattens. Against that, US 30 year yields are already trading at one of the lowest premiums to JGBs ever.

In absolute terms, its only just about 1%.

In percentage terms, the gap has probably never been lower. Typically treasuries have been 200% of JGB yields.

IF the gap between JGBs and treasuries were to revert to historical norms, that implies a US 30 year yield of between 6% and 8%.

So this leaves GLD/TLT in an interesting place. If the Fed tightens, TLT could rally and gold fall - which would be bad for a already sideways moving trade. If the old relationship between JGBs and treasuries reasserts itself, then TLT should fall between 20 and 40% (based on TLT having a duration of about 20).

Normally, I do not like 50-50 bets like this. Maybe JGBs yield trade through US treasury yields? It seems odd - but odd things happen alot in this market now. The big kicker for me is that there is still USD 3.5 trillion of official treasury bond holdings out there. Given the freezing of Russian treasury holding - who is buying this debt?

The largest holder is Japan, which needs to sell treasuries to support its currency, and the second largest holder is the UK, which is probably hedge funds doing basis trade, and the third largest is China, which is a seller.

I think it is possible that GLD, and other precious metal do nothing, especially true given the massive retail participation they drew during their run up. But, GLD/TLT still looks good - but mainly the short TLT side.

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The original thinking behind the Pro-Labour trade was that politicians everywhere were being forced to address imbalances in the economy. The main one was sky high property prices. After the GFC, another property crash was off the political cards more or less. This left politicians with only one choice, raise wages while keeping property prices flat in nominal terms. This issue, as I saw it, was that rising wages would have an upward bias on property prices, so yields would have to be quite high to keep property in check. In the UK, 30 year bonds yields have indeed risen substantially.

And London house prices have stagnated.

And UK wages have surged.

Broadly speaking, this has generally been repeated across the western world. I also assumed private equity would struggle in this world of higher wages and higher interest rates. The Invesco Global Private Equity fund has confirmed that view.

So far so good. I had assumed that higher yields would also put a dampener on equity valuations, like we saw in 2022. On this matter, I could not be more wrong. Using price to sales as a valuation metric, stocks have gotten more expensive, not cheaper.

If you use an equal weight index, you could maybe argue there has been a slight de-rating, but it is pretty flimsy.

The place to be has been semiconductors. If dominates both the S&P 500 and momentum indices.

Weirdly, AI almost now makes a direct connection between wages and semiconductor prices. The higher wages go, the more corporates are incentivised to use compute, rather than labour. Whereas oil was the substitute for labour (or oil prices moved with rising wages) in the 1970s, semis now seem the substitutes for labour in 2020s. Oil rose 1800% during this era, as the market worked out the “right” price for oil.

Semiconductors have done even better than that.

If the analogy between oil and semis hold, then the market breaks only when politicians decided that rising unemployment to break inflation is a political winner. I don’t know when that is.

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In a recent note, I was looking at Softbank and Oracle, and thought they looked the weakest link in the AI financing chain. In simple terms, all the other AI players have access to the cash to compete, while Softbank was relying on margin loans on its ARM and OpenAI holdings. Looking at debt markets, CDS were also signalling weakness.

The law case that Elon Musk had against OpenAI was dismissed, and Softbank shares have surged to new all time highs. I do find it odd that credit and equity markets are saying different things.

Share price surges like this can happen when there is a lot of short interest. There are plenty of examples of this, but Avis Budget Group is a recent example. A slightly messy chart, but the blue line in the upper chart is share price, and the the middle chart shows that short interest built in 2025, leading to a mega short squeeze this year, with stock up 700% at one point.

There is no short interest in Softbank, at least reported short interest. In fact you can see short interest in Softbank was obliterated in the move from 1500 to 7000 in 2025. Of my short selling rules is never short stocks with high short interest, mainly to avoid squeezes like we saw in CAR US. There was no sign of squeeze potential in Softbank.

One reason could be that OpenAI is looking to launch an IPO, and this will greatly add liquidity for Softbank and Oracle, OpenAI partners in Stargate LLC. The problem with that view is that Oracle has barely reacted to news of the potential Open AI IPO..

Thinking about it, there are a few options for what is driving Softbank - the first and most obvious is retail enthusiasm, which given the move in most AI plays this year is understandable.

The second, which is more centred in finance, is that Softbank has taken margin loans out on its ARM and OpenAI stakes. In both cases, the size of the loans could not be easily hedged via ARM or OpenAI directly. Lenders to Softbank may have chosen to directly hedge via Softbank options. This should lead to implied volatility moving above historic volatility . We sort of see that with Softbank. This means Softbank ends up doing the opposite of what I expected - where a doom loop of falling valuations means equity comes under more pressure, the reverse is happening. Rising valuations lead to a rising Softbank share price.

On a completely different thought track, I also thought that OpenAI might be in trouble due to Anthropic taking market share, and/or retail subscribers not accepting price increases. I am subscribed to £20 a month ChatGPT function - which I use with work. It is good at making images, so have cancelled my Shutterstock account, and good at research, and I particularly like how it filters out Google ads from search results. But for writing, and organising, stuff, I felt it was incrementally better, rather than ground breaking. That changed this weekend, when I was working on my golf swing in my back yard, and uploaded a video to ChatGPT to see what is thought. I am still getting to grips with golf - and I am told by friends that I am “armsy”… which is exactly what ChatGPT told me. I was genuinely surprised at how quickly it was able to analyse my swing and give tips. The big one was getting my shoulders to follow through.

After a few drills it had improved my swing measurably. A golf lesson cost £50 - and ChatGPT had done a decent job. Made me think, there is definitely going to be some pricing power for these LLMs.

There were a lot of reasons, I liked the look Softbank being a weakest link - and it may still play out that way. But against that, there should be short interest from options that I cannot track easily, retail meme style investing, which you do not want to short against, and it has hit a new all time high. I have been bearishly minded for the last couple of year, with the breakout of gold versus the S&P 500 - which has normally a good time to be at least cautious. However the last few month has seen half of gold’s outperformance get reversed AND break through the 200MDA.

I never try and fight the market - its a fools errand. And markets were sending mixed messages until very recently. But I am a bit nervous about the signal now. On top of that, I have a new found respect of the capabilities of LLMs (I use LLMs for many things, but video analysis is the first one that I have really been amazed at). I think we would need to see more financial problems at OpenAI before getting really bearish. A price war might do it - but if anything the market is getting prepared for price hikes I think. The macro graph that has really broken out is SPX/TLT - which is at new highs, after having shown some weakness in 2025 and early 2026.

When do sovereign yields rise enough to bother markets? The market WILL tell us - but at the moment, it is saying not now. And within that analysis, betting on renewed Softbank weakness looks tough.

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There was a time when a prospectus was a dime a dozen. As an analyst in the 2000s, my main job was to read them and then go the management lunch, and work out if they were a buy or not. I love a good prospectus - its the only time management has to be clear and up front about risks. But with the rise of private equity and venture capital, IPOs have become much rarer. But today we get to go through a truly interesting prospectus. Above picture is taken directly from the prospectus. You can have a read yourself here. For such a momentous IPO, basically the key feature is that the IPO is needed because the capex into AI is larger than the cash that can be generated from its excellent rocket launch and connectivity businesses.

Not included in the above is that the IPO will allow SpaceX to purchase Cursor USD 60bn. There is quite a hefty termination fee, so obviously Elon is very keen on this deal. Cursor is an AI powered coding company, and was something that Grok was missing when compared to the other big AI companies. It also provides a ready made corporate client list.

I am not going to give you a detailed financial analysis, AI and plenty of other Substacks can and will do that for you. But I will give you my read. Its pretty transparent that you are getting two excellent businesses, the launch business and Starlink, and one speculative venture. The Space business only lifted 2,000 metric tonnes into space, or about 5 International Space Stations (420 tonnes). If a moon base is to be built, this number will have to go up exponentially, and it has a huge cost advantage. Starlink has 10m customers now - and with a ARPR of USD 66 per month is not that expensive. Not hard to foresee 100m subscribers in this business.

AI is a cash sink, but it is meant to be. But its pretty explicit that the AI business is the business that could really surprise to the upside. The theory of space based data centres is very interesting.

So far as expected. But I have two different takes on the SpaceX IPO. First of all, it confirms in many ways, the rising cost of capital theory. The rising cost of capital for governments is beginning to force some changes in capital markets. There is no way not to see equity valuations as expensive relative to government bond yields.

But the credit market has been increasing harsh on companies borrowing for AI. Softbank and Oracle CDS has been showing that.

So we are seeing the return of equity markets as the source of capital. For years the share count for the S&P 500 was falling, but now we have seen a turn as equity gets issued. We are not at dot com levels of issuance yet - but with the IPO pipeline opening up, this should climb higher, especially if government bond yields keep rising.

The second observation I would make on SpaceX IPO, is that Elon Musk really hates Sam Altman. I am using the word HATE, about Sam Altman. I suspect Elon Musk has a driving urge to be number 1, and a overdeveloped sense of vengeance on those that have done him wrong. For me, the SpaceX prospectus make it clear that Elon wants to destroy OpenAI.

So what has he done to make me think that? Not only has agreed to purchase Cursor to have a more competitive product, the prospectus also notes that the entire Colossus facility has been lease out to Anthropic at a cost of USD1.25bn a month.

He also has been relentlessly pushing Grok in twitter - which obviously allows him to compete with ChatGPT on the consumer side, if not competitively yet. All of this raises an interesting questions about the potential OpenAI IPO. With Microsoft moving away from OpenAI, and Elon Musk supporting Anthropic, OpenAI will need to raise a very substantial amount of capital from the market to compete. If Microsoft also looked to sell some of its stake - would this supply overwhelm demand?

I guess what I am saying is that capital has become a competitive weapon - and it still looks like OpenAI is at a disadvantage. Softbank has bounced on the OpenAI IPO announcement.

But its CDS remains strangely unmoved. Credit markets tend to be more “show me the money” type of markets (not always - but can be).

This makes sense to me, as SpaceX IPO is signalling even more capital is going to be invested in this area. As long as growth rates remain good, equities should be okay I guess, but the rising cost of capital is causing equity issuance to pick up. This is a change from the last 10 years or so. Is OpenAI still in trouble? Well if Oracle catches a bid, then we can assume the IPO will solve the capital raising issues. Time will tell.

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Capital flows are a funny thing. Everyone knows they cannot go on forever, but then again, no one wants to miss out on the fun. And for some reason, everyone thinks they can get out before the tide turns.

Usually capital flows need some catalyst to make them change. The most common is central banks raising interest rates, as this usually makes some assets look expensive, and money starts to flow out. The problem is that there can be a substantial lag between rates going up, and changes in capital flows. But in my long career in financial markets, I have been lucky enough to stumble on the most extreme, and most transparent of all capital flows, and was lucky enough to be short when the flows reversed.

Back in 2014, I was made aware of Japanese funds that offered very high dividends to Japanese investors, often over 20%. I wondered how this was possible. The one that most stood out to me was the Japanese listed US REIT funds. A REIT is a Real Estate Investment Trust, a structure that allows the owners of Real Estate to avoid tax as long as all rental income is paid to the underlying investor. They tend to offer high yields, and are very attractive to retirees. They are a well understood investment product. US REITs managed in the US tended to have around 5% dividend yields. These Japanese managed REIT funds had exactly the same investment profile, yet offered yields of 20% or more. Where was this extra 15% coming from?

Intrigued, I dug further into it. Oddly enough, there was no mystery. The managers promised to pay out 20% regardless of what the cash flow was. These had some tax advantages for Japanese investors, but during the first bout of Yen weakness under Abe, the REIT funds were able to make these returns through a combination of Yen weakness and REIT appreciation. This meant they were able to make cash pay outs while not selling any of their REIT positions. This performance caused more money to come into the REIT, which further helped them to meet their cash pay outs.

The largest of the funds, Shinko US REIT saw assets explode from 16bn Yen at the beginning of 2010, to a peak of 1,500bn Yen in early 2015. By then, this one fund owned 10% of the Simon Property Group, then the largest REIT in the US. But its transparency was a problem. It was committed to a 20% dividend yield, which meant if it did not generate the asset gains from stock appreciation, dividend yields or Yen appreciation, then it would become a forced seller. That is the capital outflows that had come from Japanese retail investors would turn, and become capital inflows as managers needed to sell US assets to make Yen dividend distributions.

At the time, this was not only high yielding self feeding fund in Japan. They were funds linked to Brazilian Real, Turkish Lira, and plenty of other REIT funds, all paying Yen yields over 15% or higher. And all needed Yen to keep weakening, or they would become forced sellers. But Yen weakness was getting harder to sustain, and it was mechanically very easy to see when capital flows would turn for these funds.

The market was running record net Yen shorts in 2016, but as the capital flows reversed, Yen strength returned, which caused capital flows increase further, and Yen strengthened from 120 to 100 - destroying many macro funds in the process. Theses capital flow created its own bull market and bear market.

Before I understood markets, I saw what money does to a place. Not in charts. In the streets.

In 1990, I went to China as a teenager. It was my first real exposure to a country that felt like it was moving — not smoothly, not efficiently, but with force. It was full of dust, noise, disorder, half-built structures, and constant activity. It wasn’t “developed” in the Western sense, but it had momentum. People were trying. Trading. Building. Selling. Improvising.

It felt alive.

In 1991, I started a one-year high-school exchange in Kobe, Japan. It was the peak of the bubble economy and Japan at that time felt like the future. The trains were spotless and fast. Cities were dense and hyper-organised. Shops were full. Technology was everywhere. Even the vending machines seemed advanced. Compared to rest of the world at the moment, Japan looked and felt like a civilisation several steps ahead.

I didn’t know it then, but I was looking at two different stages of the same force: Capital Flows.

When money flows into a system, it doesn’t just make prices go up. It changes behaviour.

In Japan during the bubble years, capital had been pouring in for decades. The Plaza Accord (1985) had weakened the US dollar and made investors think long Yen was a winning trade. Capital had subsequently flooded in. Asset prices had risen. Corporate balance sheets were flush. Banks were lending. Property was valuable collateral. Confidence fed more confidence. Companies invested because markets were rewarding growth. Workers spent because wages were rising. Rising asset prices justified more lending.

The system reinforced itself.

The surface story might have been about productivity, culture, or technology. But underneath it was a powerful feedback loop driven by capital. Money flows in, asset prices move higher, higher collateral values support more lending, this creates more activity, which in turns encourages more capital flows. And so the cycle continues until something breaks it.

This feedback loop doesn’t need perfect fundamentals. It needs flows of capital. At some point however those flows will reverse, and the process goes into reverse. More becomes less.

China, when I first saw it, was earlier in the process. Less polish. Less capital per person. But you could feel that something was building. There was a lot of energy without the infrastructure to support it yet. It was a system on the way up: still rough, still chaotic, but propelled forward by the movement of people, trade, and investment.

At the time, I didn’t have a framework. I just had an impression. Some places feel heavy, whereas some places feel like they are being lifted. Later, I would understand this feeling as capital flows.

One of the mistakes investors make is thinking bull markets are rewards for good fundamentals. Sometimes they are. Bull markets are often the cause of improved fundamentals, not the result.

When asset prices rise, companies can raise money more easily. They invest. They hire. They expand. Consumers feel wealthier. They spend more. Governments collect more taxes. Banks lend more willingly.

The rising market creates the conditions that justify its own rise. It becomes self-reinforcing.

You could see it physically in Japan. Property values were so high that balance sheets looked bulletproof. Banks were willing to lend because collateral values kept rising. Corporations invested heavily because capital was available and cheap. The system looked strong because asset prices were strong — and asset prices were strong because the system looked strong.

It’s circular. But it works — until the flows reverse.

What struck me, even as a teenager, was how environments shaped people.

In Japan, confidence was embedded in the infrastructure. Everything worked. Systems were reliable. The country felt efficient and modern. It was easy to believe that this success would continue because the surrounding physical world confirmed the story.

In China, belief came from motion. From visible change. Markets. Construction. Trade. It wasn’t yet polished, but you could see the direction of travel.

If you compare that to places where capital has left, the contrast is stark. Infrastructure decays. Investment slows. Confidence erodes. People become defensive. Risk-taking falls. The environment feels static or brittle. Capital doesn’t just move numbers. It moves psychology. This became one of my core beliefs: Capital flows create their own bull market.

When money moves into a country, sector, or asset class, it sets off a chain reaction. Higher prices improve balance sheets. Improved balance sheets encourage lending. Lending funds expansion. Expansion attracts more capital. Optimism becomes rational because the flow itself is supportive.

This is why markets can look expensive and keep going. Investors who focus only on valuation ask: “How can it still be rising?” Investors who watch flows understand that the system is still being fed.

The reverse is just as powerful. When capital leaves, the loop works in the other direction.

Falling asset prices weaken balance sheets. Lending tightens. Investment slows. Confidence drops. More capital leaves. What looked stable begins to look fragile very quickly.

Bull markets and bear markets are not just about earnings. They are about whether the tide of money is coming in or going out. You don’t need to know the exact level of the tide. But you do need to know the direction in which it is flowing.

My early travels gave me something that spreadsheets could not: a physical sense of what a system under inflow feels like versus one under outflow. Years later, when I analysed markets, I often came back to that instinct.

Does this place feel like Japan at its peak — polished, confident, fuelled by capital? Does it feel like early China — messy but being lifted by flows? Or does it feel like somewhere capital has quietly stopped arriving?

Those questions don’t replace analysis. They simply guide where you look.

Long before fundamentals show up in earnings, capital has already started moving. And when capital moves, markets follow.

Three years ago I wrote a note on How to Read The Economist. A lot of financial people do not take the Economist seriously - there is the famous contra indicator of the cover being the exact wrong thing to do. I do not disagree with this. But as I say above, and in my previously published note, the key to the Economist is to read it backwards.

The first thing you find at the back is the Obituary. I find reading the Obituary is great motivation to try and do great things with my life. In fact one of my goals is to have my Obituary published in the Economist. This does mean I would have to fake my death to know if I have achieved this or not. This raise a few issues, but I will deal with that when I think I have done enough with my life to get a write up.

So when I picked up the paper copy of the Economist on my way to the toilet, rather than read about Indonesia at a Crossroads (again), I started at the back. The Obituary of Raghu Rai, and his photographs of the Bhopal tragedy humbled me. I pondered if that is the standard, then I will never make it. Raghu Rai was not only an excellent photographer but a brave and moral man. I must do better.

After contemplating my shortcomings for awhile, I turned the page from left to right. This took me to the back of the Culture section, which was reviewing the book Project Maven by Katrina Manson on AI and American warfare.

I knew that AI was being used with drones, sometimes to fly autonomously, but from what I had read, Russia was able to keep pace with Ukraine here. But as I read the article, what came clear, is that ability to crunch huge sets of data points was becoming ever more important. The other thing that it makes clear, is that AI starts off making a lot of mistakes, but then learns rapidly.

This seems to be made clear with Ukraine now seemingly turning the corner in the War with Russia. Drones and AI now seem to be much more effective than at the start of the war. This below is taken from another Economist article.

Since the AI boom started I have wondered why American corporations have been willing to accept the huge price increases, particularly when Chinese AI seems to be so much cheaper. I really thought the DeepSeek moment last year would be a motivator for US corporations to drive down prices. Instead pricing has continued to surge. In recent weeks, I have been thinking that the hyperscalers are pushing up prices to try and bankrupt the competition.

But if AI is seen as an extension of the “Department of War” then the above pricing dynamics make much more sense. When the size of the navy was important to America, then building far more ships than anyone else was the most important thing. Prior to Pearl Harbor, the US probably correctly perceived that a huge navy was not really necessary. After Pearl Harbor, a navy that was many times larger than Japan’s was seen as necessary.

A similar dynamic played out with nuclear weapons. Once USSR had nuclear weapons, too much was not enough.

And the US has a good model for bringing on supply - it guarantees payments and profits to encourage private sector investment and innovation. If anyone watched the movie Aviator about Howard Hughes, he was criticised for building a plane that was never flown, but this was perfectly inline with how the US does things. AI as a military trade makes much more sense than a rational economic exercise. But the risk/reward for AI then moves to a political calculation. More on that another time.

Also, if the above analysis is correct, and AI is learning, we should expect US drone strikes to become more and more effective against Iran, just as Ukraine has become more effective against Russia. That would be a real game changer and bearish for oil. It would also effectively imply that Taiwan was also now impregnable, and could only be reunified through peaceful means. Strangely, if that did become the case, it would be bearish for AI trade as rational investing would take over again. Interesting times indeed - and another lesson in why I read the Economist backwards.

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After a blow off move in January, GLT/TLT has been going sideways since then.

As mentioned numerous times, I am more bearish TLT than bullish GLD, but I needed to have GLD just in case the Fed did YCC or something similarly foolish. And in 2024 and 2025, gold has been much the better trade. As is the case with all these relative value trades, the market fell in love with the side that is working - gold and other precious metals. To be fair, they still look to be in an upturn, but back in January every retail trader and fund manager were super long gold, silver and miners.

Gold looks ok, but much more problematically, is has given up a huge amount of relative performance to the S&P 500. That is, holding gold let you outperform the S&P 500 since the beginning of 2025, but you are now down on gold relative to the S&P 500 this year. This year, gold as a bearish trade is not really working.

So should I get rid of gold? Probably not. Gold is reacting to higher interest rates as you would expect. The real mystery is corporate debt. Even with oil up, rates selling off, and private credit not looking great, corporate debt spread remain at lows.

The corporate debt market has learnt to price in a Fed put. And as we have seen, corporates are now borrowing against asset values for capex. That is the Fed put is inflationary. Kevin Warsh and Scott Bessent have spoken against the Fed trying to price everything. If TLT is pricing in a more “free market” Fed - why are equities not? S&P 500 is looking like the mispriced asset here. Fun times.

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I am thinking of going to New York for 10-11 June. If you are an allocator, and would like to meet, then drop me a line.

Below is really a short thesis on AI - why its has blown up so aggressively, and how it could fall apart. Generally speaking, bullish ideas have relatively low value, but short ideas are very valuable indeed. For that reason, this is a paid post only.

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I like Goldman Sachs research. They tend to produce big bits of research with enough raw data for you to make your own decisions. If you wanted a single image to explain the market explosion higher, then these next three graphs would probably be it. In the first graph, it shows that GS thinks “agent” demand for tokens is going to grow demand 13 times more than current token demand by 2030.

My guess is this GS Chart is an extrapolation from the sharp pick up in usage we have seen so far this year. This chart is taken from Openrouter.ai, and only shows volumes going through OpenRouter.

The below graph is showing an inflection in token pricing to be profitable. If correct, this should imply that the AI boom could be self financing, which would be bullish. Intriguingly, the OpenRouter data shows a dip in usage as prices rose - perhaps a sign that there is price sensitivity for AI users. I don’t have enough data to be sure of that conclusion, but something to watch.

Despite this inflection in pricing, Goldman still sees pricing fall. If there is price sensitivity, then falling prices would be necessary for GS forecast volumes to be attained. So the rise in compute pricing is something to watch.

But do these numbers make sense? In 2030, GS estimate monthly consumption of 120,000 trillion tokens at a price of at USD 0.18 per 1m tokens, this would imply monthly spend on tokens would be USD22bn a month, or USD260 billion a year. For context, the world consumes around 100m barrels of oil a day, which at USD 100 a barrel, implies USD 10bn a day, and USD3.65 trillion a year. This implies AI spend would be around 8% of oil spend. I struggle with those numbers, as the amount of investment announce by the hyperscalers and AI labs feel like they are looking for a business that generates far more revenue than that. Nvidia, which produces the chips that basically makes AI possible is forecast to have USD 500bn of revenue in 2028. Spending USD700bn annually for an industry that will generate only USD260bn in revenue does not make sense.

Nvidia sales is basically an inverse of hyperscaler spending.

I think the key question in this analysis is whether prices for AI will keep falling or not. The AI boom is creating software inflation. Or in other words, rising cost pressures for users.

Again from the GS report, they estimate that a AI agent is much cheaper for coding, but already at parity for a call centre and data agent. When I talk to my friend who is building out an agent to replace call centre, the costs for AI seem well below call centre agents - so not sure if this data point is correct.

It is possible that start ups have been subsidized by the cloud giants to drive demand and adoption - so the costs that start ups see if below the actual costs. I think this is what this chart below is trying to say - that in essence token usage and API costs can be very different.

I think what I am seeing is that the AI boom is now pushing cost pressures through the AI and software sector. As the GS model shows, the general assumption is for ever lower prices - offset by higher volumes. But if the GS numbers on call centres and data entry operators are correct, rising prices should put a dent into adoption rates. That being said, I would not think hyperscalers cut spending on lower adoption - I think they cut capex spend if competitors like OpenAI start running out of money, and then cut capex. From the data I have seen - I think that is 50/50 proposition now. But that is a post for another time.

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There was a time, not that long ago, when the cheapest provider would be the corporate winner. Remember the days when online shopping was always the cheapest option? Or when streaming was much cheaper than buying DVDs? This was a period when government enforced competition, which has sadly disappeared. These days, particular in tech world, its how much capital you raise that is the most important factor in determining a winner. A good recent example was Netflix, who during the “streaming wars” massively increased its balance sheet which drove up the cost of content.

Disney tried to compete for a while, but ultimately Netflix won.

And once it won, content prices fell again, and content creators got squeezed. In AI, we are seeing a similar dynamic play out. Masayoshi Son, the founder of SoftBank, virtually invented blitzscaling with an early investment into Alibaba, where he encourage Jack Ma to build quicker, or his capital would go to competitors. In the AI race, we have the hyperscalers, and the AI labs, OpenAI and Anthropic. One of the more intriguing aspects in the current AI boom has been the weakness in some of the AI names CDS. Oracle CDS has been weak.

As has Softbank Group.

Softbank is really more of a concentrated investment firm, with a number of high profile investments with a mixed track record. Alibaba was a great success, WeWork not so much. In recent years, is has been busy turning itself into an AI focused investment vehicle.

As of today, ARM and OpenAI are its two biggest assets.

Softbank was looking to raise capital by taking out a loan backed by its share holding in OpenAI, but saw some push back from lenders.

Softbank also have about USD 20bn of margin loans supported by its holding in ARM. ARM is one of the more expensive tech stocks out there - trading at 45 times EV/Sales.

SoftBank, Oracle, OpenAI some other partners have attempted to blitzscale the AI market with its Stargate project.

Softbank is increasing looking like the “soft flank” in the OpenAI v Anthropic battle for AI supremacy. Softbank has USD 130bn of debt outstanding (not including margin loans against ARM and OpenAI). Most is in USD, but there is a fair bit of Japanese debt as well.

In line with JGBs, the yield on this debt has risen substantially.

Not hard to see why - operating cash flow is poor, but capex is high.

One of the reasons I have been cautious on markets is that I saw capital becoming scarce - and we are now seeing that in the AI space - as these huge corporates keep tapping the market for more and more money. The question is when do bond markets break? When do markets stop asking how much do you want to borrow, and start asking when are you going to pay me back. We may be getting closer than you think.

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Chapter 2 of my book - chapter 1 is here. If you are just here for timely market insights and not details of how and why I think the way I do, feel free to ignore.

It was 2021, and I was reading the Financial Times, when a small article caught my attention. The newly created Chinese digital regulator had called all of the biggest Chinese tech firms in for a meeting. At the time, the COVID tech bull market was raging, and US investors were all talking about FANG (Facebook, Amazon, Netflix and Google). These were the stocks that were going to lead us onwards and upwards. The Chinese equivalent was BAT (Baidu, Alibaba and Tencent). Even though relations between China and the US was deteriorating, everyone was hyped about tech, including Chinese tech.

I did not have particularly strong views either way on tech, but I knew that the Chinese government did not call in companies just for a “chat”. That was not how it worked in China. To me, it sounded like a problem. Curiously, the article did not mention which companies had been called in - just “leading tech companies”. So I spent the next couple of hours searching the internet to find the names of the companies involved. Eventually I found a list of 34 companies.

I started looking through the list - many were high profile companies that we all know - but I was surprised to see almost every Chinese tech company with a US listing was called into the meeting. Some had only just listed, some were just about to list, and some had been around a while. When I looked at market positioning, it was universally positive. When I asked people their thoughts, basically it was along the lines of the US has FANG, China is going to have to support its tech companies to compete, so the regulators will do nothing.

The thing that really got me was that the Chinese regulator was basically saying to the Chinese internet companies, you can not use your platforms to dominate and to promote firms you own or have an interest in. That is you could not use your market power to extract rents from other companies. For me, this sounded incredibly bearish - technology is naturally deflationary without consolidation and collusion. So after two hours work, I decided to put small shorts on all the companies.

As expected, the market was caught off guard completely by the level of regulation that the Chinese government imposed on its internet champions, and the effects on profitability. All of these shorts fell by 50% or more over the next few months.

This was one of my most successful shorting campaigns, but also wake up call. Previously, all my short themes had been built on pure economics, supply and demand and shifting prices. This campaign was built on two hours of research and from reading Chinese politics better than Wall Street. It was realising this, that led me to change my investment style, not because the world had changed, but because the politics of the world had changed.

Markets Are Driven by Politics, Not Economics

Before I ever opened a company report, I lived inside a policy machine.

My mother worked in Parliament House in Canberra. Not as a politician, not in front of cameras, but in the engine room — the research service that fed information directly to ministers. Her job was to answer the questions they were going to be asked in Parliament: What is Australia’s position on the Middle East? On China? On trade? On security? She would research, draft, and write responses that would later be delivered — often word for word — by elected officials.

As a child, I didn’t fully grasp the significance of that. I just knew Mum worked in a big building with flags, and that politics was not something abstract that happened “out there.” It was something people did. Something negotiated. Something constrained.

What I absorbed, as if by osmosis, was that decisions were rarely about what was economically “best.” They were about what was politically possible.

That difference matters.

In economics textbooks, systems move toward equilibrium, towards the most efficient outcome. In politics, systems move toward survival.

Governments don’t optimise. They stabilise. They delay. They trade one problem for another if it buys time. They protect voters, coalitions, and power bases. The outcome might look irrational from an economic perspective, but from a political one, it often makes perfect sense.

Growing up, I heard conversations about policy not in terms of theory, but in terms of trade-offs. If you raise taxes, who do you alienate? If you cut spending, where does the pain show up? If you devalue, who wins and who loses?

This lens stayed with me long before I understood how to use it.

Australia in the 1970s was not a calm political environment. The dismissal of Prime Minister Gough Whitlam in 1975 — the only time an Australian Prime Minister has been removed by the Governor-General — was a constitutional earthquake. It happened in the world I grew up in. These weren’t distant historical events; they were lived reality.

Later, I would admire Paul Keating for pushing through painful reforms that damaged his popularity but strengthened the economy long term. As a child, I didn’t frame it that way. But I saw, through my mother’s work and the atmosphere around us, that leaders often had to choose between economic logic and political survival — and usually chose the latter.

That lesson became crucial in my understanding of the markets.

When I started working in finance, I noticed something odd. Investors talked about governments as if they were rational economic actors. As if central banks pursued pure price stability. As if policymakers allowed recessions to “cleanse excesses.” As if currencies floated freely according to fundamentals. And even when economies and policymakers act “rationally” this was treated as a policy decision as well. Free markets are not an economic inevitability; they are a political choice.

Governments intervene. They distort. They subsidise. They bail out. They cap yields. They suppress volatility. They support asset prices when political stability is threatened. They don’t do this because it is economically elegant. They do it because falling markets mean falling confidence, unemployment, elections lost, social unrest. Even when governments don’t intervene, that is a political decision as well. Markets are not just economic systems. They are political systems with price tags attached.

I saw this clearly during crises.

When markets wobble, investors ask: What are the fundamentals? Policymakers ask: What breaks if we do nothing? Does this help us stay in power or not?

Those are not the same question.

A currency might be overvalued. A banking system might be insolvent. A property market might be a bubble. But if letting it collapse threatens political stability, the authorities will often choose distortion over discipline.

Rates will be cut. Liquidity injected. Rules bent. Losses socialised.

The flip side is crisis. This can also achieve a political aim. To break the power of certain interest groups, for example. Everything is political first, economics second.

If you analyse markets as if they are governed purely by economics, you will repeatedly be surprised. If you analyse them as political systems, the behaviour becomes more predictable. Most fund managers and investors do not, I have noticed, want to take political views.

This awareness shaped how I interpreted policy moves.

When China launched enormous stimulus after 2008, many analysts focused on debt sustainability and misallocation of capital. Those mattered, but the deeper driver was political. Growth had to be maintained to preserve social stability. The leadership could not tolerate a sharp slowdown. Economics came second.

Similarly, in developed markets, central banks repeatedly supported asset prices because falling markets fed directly into consumer confidence, pension funding, and electoral outcomes. The “wealth effect” was not just an economic concept — it was a political stabiliser.

Once you see markets this way, you stop asking: “Is this economically justified?” You start asking: “What is the political constraint?”

That is often the more powerful force.

Now I increasingly take the view that Japan’s lost decades were not a fundamental economic decision, but a political one. The 1980s saw the rise of US-Japan trade tensions, and policymakers chose a policy of benign neglect of Japan, to stabilise the relationship. Now, with the rise of China, Japanese political calculations are changing again. Politics before economics.

This doesn’t mean economics doesn’t matter. Over the long run, imbalances build and eventually assert themselves. But the timing — the path — is shaped by politics. Pain is delayed. Losses are shifted. Incentives are altered.

As an investor, this means you cannot just model growth and valuation. You must model power, incentives, and survival. That instinct came to me not from a trading desk, but from growing up in a household where politics was dissected as a practical activity, not a moral debate.

I learned early that outcomes are negotiated, not optimised. Markets are the same.

So when I say markets are driven by politics, not economics, I don’t mean numbers don’t matter. I mean numbers operate inside political boundaries. Those boundaries move. They bend. Sometimes they break. But they are always there. Understanding that gives you an edge — not because it tells you exactly what will happen, but because it stops you being surprised when “irrational” policy choices override economic logic.

To many investors, government intervention feels like distortion. To me, it feels like the system behaving exactly as it was designed to.

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