Larry McDonald — The Bond Market's Biggest Contrarian Trade

TLT is a fund holding US government bonds that mature 20 or more years from now. Because they pay a fixed amount for so long, their price swings hard when interest rates move: rates up, price down — and TLT has lost money for four straight years, the worst stretch for long bonds in at least 40.

That is exactly why McDonald is turning positive. Everyone already knows the reasons to hate long bonds — huge government borrowing, big tech issuing hundreds of billions of new debt, socialist politics in the US, France and the UK. When a bear case is that famous, he reckons it is "80 to 90% priced in." Positioning data (what futures traders actually hold, and every bull/bear survey) shows record pessimism, and in 2017–21 it was the exact opposite: TLT was one of the most popular funds in the market and everyone lost money owning it.

His trigger is counterintuitive: a burst of inflation from energy and food would push yields up one more time — and that final squeeze on an already-broke bottom 70% of consumers is what tips the economy into recession. In a recession, rates fall and these bonds rally hard. So the last leg down is the buying opportunity, not the reason to stay away. Note he says "start at least thinking about buying" — this is the turn in his view, not a table-pounding call.

ZROZ owns "zero coupon" Treasury bonds — bonds that pay no interest along the way and instead are bought at a deep discount and repay full face value in 25+ years. With no interest payments to cushion you, all the value sits at the far end, which makes the price extraordinarily sensitive to interest rates.

That sensitivity is the whole point. It is the most geared way to own his "supernova" outcome: if hot inflation forces a fast recession and long rates then collapse, ZROZ moves far more than an ordinary bond fund. The flip side is symmetrical — if yields keep rising, it falls hardest. He names it as one instrument in a set (with TLT and IVOL), not as a stand-alone position.

IVOL is not a bet on rates going up or down. It is a bet on the shape of the yield curve — the gap between short-term rates (say the 2-year) and long-term rates (the 10- or 30-year). It profits when that gap widens, which is called "steepening."

The steepening he expects happens if the Fed cuts short-term rates (because the economy is weakening) while long rates stay high (because of inflation and the flood of government and corporate borrowing). The fund has been badly beaten up — "hammered," in his word — precisely because that has not happened yet. He puts a number on the upside: "IVOL could be up 15, 20% total return if you get a good steepening."

This is the same 2s30s steepener trade he has run through IVOL since June — the difference now is that he is pairing it with outright long-duration bets rather than treating duration itself as untouchable.

VIXY rises when the stock market's expected volatility — the "fear gauge" — jumps. It is portfolio insurance you can buy in a normal brokerage account.

Two things make it attractive right now: insurance is cheap relative to the risk (three "treacherous" inflation reports are coming), and a lot of investors are sitting on 16–18% gains for the year. His rule is to spend about 1% of those gains on protection.

But he is emphatic that this is a rental, not a marriage. Funds like this must reset their futures positions every single day, which quietly bleeds value over time — "there's a real decay." He frames it as a tactical trade for September and October specifically, then out.

Schlumberger is the biggest oil-services company — it does not own the oil, it supplies the technology, data and equipment that oil producers need to find and pump it.

Asked what makes him optimistic, this is the first thing he names: "we've been max long, we're still long the Schlumberger… the oil service stocks. The picture the next five years is still phenomenal." It stays a core hard-asset holding, consistent with his view since June that oil services own irreplaceable subsurface data.

The nuance in this appearance is that the position is now a large gain he wants to defend — hence the hedges elsewhere in the book rather than selling the winners.

CNR is a coal producer. Coal is exactly the kind of unloved, physical, cash-generating business at the centre of his hard-asset thesis — and it powers the electricity grid the AI build-out is straining.

He points to it as a call that worked: "this is our big trade a year ago on the show. Our coal CNR is up 32% over the last year," alongside copper names up 82% and gold miners up 50%. Big tech, meanwhile, is up 4–5%.

Note the posture shift. He is not selling — "by no means have we been bearish" — but after a run like that, "now you want to protect those gains," which is what the bank puts and the VIXY rental are for.

EMLC owns government bonds from emerging-market countries, issued in those countries' own currencies (Brazilian reais, Mexican pesos and so on) rather than in dollars. So you earn their much higher interest rates and also gain or lose on their currencies against the dollar.

He uses it as a scoreboard, not a recommendation: EM local-currency bonds have returned "like 15% a year the last three four years" while US Treasuries lost money. "If it was a fight, they would stop."

The point behind the comparison is that "safe" is not the same as "profitable" — the US long bond has been the risky asset, and the countries investors call risky have paid better. It is context for why he now finds the beaten-up US long bond interesting rather than a call to buy EM debt here.

FAZ goes up roughly three times as much as bank stocks go down, on a single day. It is the leveraged, inverse way to bet against the financial sector.

He lists it as one route for people who want that bet, and immediately attaches the warning: "it's a levered ETF, you got to be careful." The same decay problem applies as with VIXY — the fund is rebalanced daily, so in a choppy market it can lose money even if banks eventually fall. A tactical trade at most, never a hold.

His own preference for expressing the same view is a one-year put option on XLF or Bank of America: the cost is known up front, the clock is long enough for the thesis to play out, and there is no daily decay.

Here SpaceX appears as a borrower, not as a stock view. His argument is that banks have quietly changed what they do — "style drift" — by lending aggressively to the biggest names in AI and space to keep their business.

Why a bank finds it tempting: these companies carry gold-plated (double-A) credit ratings on the cash flow they are expected to produce, so a loan secured against that future cash looks safe. The danger is that the cash is still in the future, and the loans are already on the books today.

So this is a comment on bank risk-taking, not a judgement on SpaceX's business.

Same role as SpaceX in his argument: one of the borrowers the banks are "trying to appease." OpenAI is privately held, so there is nothing to buy or sell here.

The takeaway is about the lenders. When banks stretch outside their normal territory to keep a marquee client, that stretch is where the next credit accident usually starts.

XLF is the main fund tracking US financial stocks — the banks, brokers and insurers as a group. This is his hedge of choice for a market correction.

The case has three legs. Positioning: "everyone on Wall Street is massively long the financials," priced for Fed-appointee-and-deregulation good news that has been public for two years. Valuation: record price-to-book on the biggest banks. Hidden exposure: the off-balance-sheet loans to data centers, plus mark-to-market losses on the long-dated corporate bonds they hold.

How he'd do it: buy a one-year put option on XLF — a contract that pays off if the sector falls, costing only the premium — sized at 1–3% of a portfolio. Options on banks are unusually cheap right now, which is the whole reason the trade is attractive.

Bank of America is the single-name version of the same bet, and the one he names twice. Puts on it are "really cheap," so a one-year put is his specific suggestion.

What triggered the view: the investor in his chat who made clients around a billion dollars in the 2008 subprime crisis, and who had been "a raging bull" on banks for two years, has flipped bearish on it. That is the two-to-three-unconnected-managers shift he trades on.

The underlying worry is that the bank sits at record price-to-book while holding both duration losses on bonds and the off-balance-sheet AI/data-center loans — and is buying credit insurance on its own borrowers, which tells you what it thinks of them.

Price-to-book compares a bank's share price to the accounting value of what it owns. JPMorgan and Bank of America are both at record price-to-book — investors have never paid more for a dollar of these banks' assets.

His objection is that the good news justifying that price — a friendly Fed governor, deregulation — "has been out there for 2 years," while the risks are not in the price at all: bond losses, data-center lending, and a wave of investors all leaning the same way.

This is a warning on crowding and valuation rather than a claim that JPMorgan is a bad bank.

Goldman is named as part of the flip: the formerly bullish investor is now "bearish on Bank of America, bearish on Goldman, bearish on the financials as a whole."

The logic is sector-wide rather than Goldman-specific — cheap options, crowded positioning, and exposure to the credit that has been written against the AI build-out.

LQD holds bonds issued by big, highly-rated companies — the "safest" tier of corporate debt. Which is why its behaviour matters: this is the top slice of the credit "sandwich" he watches.

Compared against the S&P 500 it is "rolling over hard," because the flood of new borrowing to build data centers lands right here — hundreds of billions of new bonds from the hyperscalers over 12–24 months, all competing for the same buyers.

Read it with the bottom of the sandwich — the riskiest CCC-rated bonds "blowing out wider every day" and a weak market for bank loans. Stress at both ends at once, while stocks sit near highs, is his tell that this is "late 2006," the year before the trouble surfaced.

KKR is a private-equity and private-credit giant: it lends to companies outside the banking system, in loans that rarely trade and are therefore valued by estimate rather than by market price.

His signal is a chart comparison — KKR against the financial sector — and it "smells to high heaven": the private-credit names are badly underperforming the banks. When the lenders closest to the murkiest loans move first, he treats it as evidence of "real credit deterioration" rather than a sector rotation.

Blue Owl runs business development companies — funds that lend directly to mid-sized businesses. Same family as KKR, and "same thing with Blue Owl": the chart is behaving badly.

The mechanism he describes is simple and repeatable: when lenders are "falling all over each other" to lend into a hot area, standards drop, weaker borrowers get funded, and defaults spike a year or two later. He says that has already happened in private credit — and is now happening again in data-center financing.

MAGS is a fund holding just the seven biggest US tech companies. He uses it to score the rotation he has been calling for two years — and the score is lopsided.

Up only 4–5% for the year, it is losing to gold miners, copper names and coal names. "It's just really pathetic… all the companies that control hard assets are absolutely destroying big tech."

His explanation is "return on invested capital mystery meat": investors cannot see what the trillions being spent on AI will actually earn, or when. He expects the "crazy investing" to stop or slow within a couple of months.

Meta is his worked example of how the AI build-out got financed once the cash-burn became too visible. Directors get uncomfortable watching cash pour out, so the spending was moved off the balance sheet — structured through outside entities so it does not show up as company debt: "just look at Meta, 30 billion of off-balance sheet financing up to 600 billion" in two to three years.

The debt does not vanish; it moves to the banks that funded it. And those banks are now buying credit default swaps — insurance that pays out if the borrower fails — on their own Mag-7 borrowers. When a lender insures against the customer it just lent to, that is the tell.

Everything then hangs on one date: when spending turns into actual free cash flow. "If that's in 2030, 29, okay. If that's in 2031, 32, 33, Houston, we have a problem."

Microsoft is named alongside Meta for the same reason: capital spending on AI data centers has been burning cash so fast it has made boards "very very very very uncomfortable."

Banks were happy to lend against these companies' top-rated future cash flow. But the loan exists today and the cash flow does not yet — so if the turnaround date keeps slipping, the risk transfers straight onto the lenders, and the crowded, record-priced bank stocks are where he expects it to show up.