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Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.

Here are some charts to noodle over while you wait for CoreWeave to start trading.

Whoever sends the correct identities of each to [email protected] — with the subject line “Quiz” — will win a T-shirt.

Deadline is 2pm on Monday in London, and 9am in NYC.

And do let us know if you don’t want us to list your name if you get all three right.

Good luck!

In The Hitchhiker’s Guide to the Galaxy, Vroomfondel and Majikthise — representatives of Amalgamated Union of Philosophers, Sages, Luminaries and Other Thinking Persons — attempt to shut down supercomputer Deep Thought before it threatens their livelihoods by providing some certainty in answering the ultimate question of Life, the Universe and Everything. Financial analysts face no such threat.

Doubt and uncertainty have never been in short supply in the finance world. And efforts to quantify important theoretical variables have done nothing to dent the livelihoods of its professionals.

The most famous example is probably the ‘equity risk premium’, or ERP — the amount of excess return investors supposedly demand to invest in stocks over and above the risk-free rate to compensate for additional investment risks. If the ERP is high, it’s a good time to buy stocks. If it’s skimpy or even negative it’s time to run for the hills, or at least for the fixed income market. So controlling what is understood to be the ERP is a big deal.

There are a myriad of attempts at modelling the ERP, each spitting out values that not only differ from each other, but can also move in opposite directions over time. The point was made elegantly a decade ago in this NY Fed paper, which looked at twenty different ERP models — the outputs of which are shown in the chart below:

This hasn’t stopped investors, public intellectuals, or columnists from continuing to refer to the ERP in public as some kind of single observable metric, even if their private understanding is far more nuanced.

But the example we really want to talk about is bond ‘term premia’ — already the subject of two, or maybe even three, FTAV posts this year.

As the NY Fed explains:

In standard economic theory, yields on Treasury securities are composed of two components: expectations of the future path of short-term Treasury yields and the Treasury term premium. The term premium is defined as the compensation that investors require for bearing the risk that interest rates may change over the life of the bond.

You can see why central bankers might be interested in term premia. They consider bond markets to be conduits for the transmission of monetary policy and look to them to understand how expectations are forming around their future policy actions. From time to time they even inflate their balance sheets to the moon in an effort to reduce term premia. So having some idea of what term premia might be will be useful to them.

But — and here’s the rub — there’s an almost complete consensus that term premia are not directly observable. They need to be estimated.

So for years, bond-types could step into this seemingly protected and rigid area of doubt and uncertainty to posit wildly different views about what the bond market was *really* saying. And if policy-types wanted to understand the bond market they would need access to their very own bond whisperer, perhaps one who shared their political priors. 

Then came the models.

While econometric term premia models have roots least back into the 1980s, the three most famous models today come from economists working for the US Federal Reserve system.

Don Kim and Jonathan Wright, working for the Federal Reserve Board’s Division of Monetary Affairs, published what has come to be known as the Kim-Wright model in 2005. Three years later New York Fed economists Tobias Adrian, Richard Crump, and Emanuel Moench published what became known as the ACM model. And in 2012, San Francisco Fed economists Jens Christensen and Glenn Rudebusch came up with their own version — the so-called CR model.

To do this they each estimate, in slightly different ways, the level of *true* investor expectations as to where short-dated interest rates will be in the future. As the chart below shows, their estimates for average expectations around short-term interest rates ten years’ hence have been sometimes lower and sometimes higher than US Treasury yields.

Subtracting this estimated true expectation of average short-term interest rates from the appropriately termed US Treasury bond yield in the next chart makes this all a bit clearer. When the models reckon true expectations for short rates are lower than US Treasury yields, term premia are high and (if the models are to be believed) inventors are being paid to take duration risk. And when the models reckon that true expectations for average short rates are higher than US Treasury yields, this means that term premia are negative, and that investors (who believe the models) are paying for the privilege of taking duration risk.

Because the models themselves are complex, almost continually cited by central bankers, and (importantly) have outputs that are easy to download and chart, they quickly achieved a kind of intellectual hegemony. But did these efforts solve the term premia question?

Matt Klein wrote an FTAV post almost a decade ago about how the numbers coming out of the ACM model can be swung by a cool hundred basis points if you make reasonable tweaks to sample start dates and assumed holding periods. The Fed replied to Matt’s post with a blog of their own, largely agreeing.

In other words, while models didn’t provide an answer to Life the Universe and Everything, they do provide an answer to the question of where average expectations for short term interest rates could credibly be thought to be, and from this answer an answer to where term premia were. It’s just that these answers can be jimmied around by changing the underlying assumptions. 

Any model, like any person, will always be sensitive to its inputs.

But let’s go back to the raison d’être of these models. They seek to construct theoretical estimates of term premia because term premia are *unobservable*.

Really?

There is a directly observable market price for the expected average short term rate over a given period. It’s called the fixed leg of an Overnight Index Swap, or OIS. Or to put this in meme form:

This is not some pokey little market either. Last year there was over $260 trillion of traded volume referencing USD OIS, a further €163.5 trillion referencing Euro OIS, and over £75 trillion referencing SONIA. In other words, there is a lot of skin in this game.

The difference in yield between government bonds and the fixed leg of an OIS looks uncannily like the dictionary definition of the term premium. It was this yield spread that we used in our own decomposition of US and UK bond yield changes into changes to expected real rates, inflation expectations and term premia at the start of the year. 

How do UST–OIS asset swap values measure up against the numbers that theoretical models of term premia produce? For one thing, they seem much less volatile. And the market price has the advantage over the econometric estimations of being anchored by vast numbers of traders competing with almost unimaginable sums in a high-stakes competition to be least wrong.

What do bond-types reckon? Barclays’ rates market doyen Moyeen Islam told us that OIS-spreads “offer something more concrete to market practitioners” than the output of theoretical models, though he didn’t write these off. 

We got in touch with Tobias Adrian — author not only of probably more than half the coolest shadow-banking papers we’ve ever read, but also the ‘A’ in the most widely-used ACM model. He agreed that OIS may be preferable to term premia models in practice in measuring near-term policy rate expectations. But he also reckons the further you go out the curve, the more OIS becomes muddied with liquidity and counterparty risk. As such, he told us:

OIS markets are helpful in gauging investor expectations of monetary policy expectations over short horizons. But expectations backed out from term premium models have better forecast performance over medium to long-term tenors, especially in being able to account for premia.

In other words, frictions in the markets that produce OIS rates mean that OIS rates will be subject to the same unobservable positive and negative term premia that econometric models seek to quantify. 

We can see that this might be true, but can’t see how the claim would be easily falsified.

Term premia models are complicated frameworks built by brilliant minds seeking to infer the unobservable. It is easy to get lost in their methodology and be awed by the outputs. Financial markets by contrast are calculation engines that produce very simple observable results. Channelling Douglas Adams one last time (in this post, at least), “I’d take the awe of understanding over the awe of ignorance any day.”

Further reading:
— What’s a “term premium”? (FTAV)

We’ve written a few times about some rather fishy price swings involving China-based, Nasdaq-listed stocks and US regulators’ seeming inability to get to the root of the problem.

So credit where it’s due — on Friday, Chicago federal law enforcement seized $214mn in an alleged “pump and dump” fraud investigation. They indicted seven defendants in China, who, it is claimed, spent January manipulating the shares of a penny stock taken public by one of FT Alphaville’s favourite US bilge-bracket banks.

It’s perhaps noteworthy that it was the DOJ rather than Finra or the SEC that initiated proceedings (speedily, too). But let’s not split hairs: few of those responsible have been held to account since the pump and dump problem re-erupted during 2021’s bizarre bull market — when barely a week went by without an unprofitable micro-crap surging and crashing on no obvious news.

The civil action brought by an attorney for the Northern District of Illinois last week provides a great look at how one alleged scam involving China Liberal Education Holdings (which traded on Nasdaq under the ticker CLEU) unfolded earlier this year.

Incorporated in 2019, CLEU offers “a wide variety of education services and products to address the needs of schools and our students”.

The company IPO’d in the summer of 2020 — issuing 1,333,333 shares at $6, with Boustead Securities . . . 

. . . . as the sole underwriter. In unaudited financial statements filed with the Securities and Exchange Commission in October, CLEU reported a net loss of $4.7mn in the first half of last year.

In August, Nasdaq notified CLEU that its share price had fallen below the minimum bid of $1, meaning a delisting would follow if the stock did not eventually rise above this threshold for a minimum of 10 consecutive business days.

Four months later, the court docs state, CLEU issued 160mn additional shares for a total of about 438mn priced at around $0.162 apiece. Days before Christmas, it executed a 1-for-15 reverse stock split — a tried and tested way to circumvent exchanges’ flimsy compliance rules — leaving about 29mn outstanding shares priced at $2.695. (In October the SEC approved a Nasdaq rule change to stop reverse stock-splits arranged to boost a company’s minimum bid price.)

Things started to get interesting soon after, when CLEU is said to have issued 240mn additional shares to “certain individuals” without filing this with the SEC.

Here’s a quick overview of how the whole thing went down:

Between approximately January 10, 2025, and January 15, 2025, Subject Accounts 1-4 collectively received deposits of 33,906,975 shares of CLEU, which purportedly were issued from CLEU at a cost of $0.60 per share. Subject Accounts 1-4 subsequently participated in what is commonly known as a “pump and dump” scheme to fraudulently manipulate the price of stock in CLEU. During the time individuals in China, who were impersonating successful US-based investment advisers, advised numerous victims throughout the United States to buy CLEU at inflated prices, Subject Accounts 1-4 sold 31,484,573 shares on or about January 22, 2025 and January 23, 2025, for a total of approximately $176,104,984. 

On January 23, 2025, Company A [a US broker] restricted further activity in these accounts, so that Subject Accounts 1-4 were not able to sell any more CLEU stock. After these accounts were restricted, Subject Accounts 1-4 manipulated the CLEU market by submitting “buy” orders and then quickly cancelling the orders, which artificially inflated the volume of trades in CLEU and made it appear to the open market the demand for CLEU stock remained high.

Some victims were told by WhatsApp accounts used by people in China to buy at $5.37 per share with an expected return of up to 380 per cent over 20 to 30 trading days . . .

45. According to records from [brokerage B] on January 17, 2025, 4,936,410 shares of CLEU were deposited into Subject Account 7. On the morning of January 22, 2025, Subject Account 7 began selling CLEU shares. Prior to selling CLEU shares, Subject Account 7 had an account balance of approximately $40,142.10. Within a half hour of when Subject Account 7 began selling its CLEU shares, it had sold all 4,936,410 shares in the account, for a total of $26,186,430.61

The dump came on January 22nd and 23rd.

Five days later, CLEU came clean-ish to the SEC, admitting a month after the fact that it had exchanged 320mn warrants “for newly issued 240mn outstanding shares purchased at a cost of $0.60 per share, and that as of January 27, 2025, the total number of CLEU outstanding shares was 269,325,176”.

The stock promptly plunged to $1.02 from $7.75 at the open on January 30, when the new information was finally revealed to the market. Shares ended the session down 98 per cent at $0.148. Around 600 US retail investors were left holding the bag.

The alleged scammers used their gains to purchase shares of what the court document describes as three “Investment Fund[s]” on January 31 — and they may well have gotten away with it, too, were it not for a handful of victims who went to the FBI and the SEC with everything they knew.

Scammers have been impersonating famous US investors for years, luring countless retail investors on to WhatsApp groups through ads on Facebook and Instagram with the promise of huge returns.

FTAV joined several of these WhatsApp groups last year, and was sent screenshots from a person embedded in one that pumped CLEU. The group’s profile picture, we were told, is identical to the one used by people who last year posed as associates of Cathie Wood to pump and dump stocks including “AI-powered” car insurance group U-BX Technology.

CLEU is the tip of the pump and dump iceberg, in other words, and we know for a fact it was being touted as far back as 2022.

But although these sorts of scams seem random and hard to prevent, InvestorLink Capital Markets’ founder Matthew Michel says most can be spotted ahead of time if you know what to look for.

On January 22, just as subjects one to seven were dumping their shares, Michel shot us an email with “CLEU today” in the subject line, noting the troubling capital structure, a massive increase in negative social media sentiment as well as multiple delisting notifications the issuer had received since its IPO in 2020.

Issuers, companies and exchanges “allow a trading pattern that creates significant operational risks for the broker dealer community due to opaque corporate actions, aberrational trading patterns and volatility halts”.

“If you don’t have the operational expertise to evaluate the idiosyncratic risks these issuers present, you’re asking for trouble” he told us. “For example multiple reverse splits cause lower floats which in turn makes it harder to sell short . . . creating short squeezes that inflate [the] share price.”

Skulduggery of this sort obviously isn’t limited to Chinese stocks, however. Yesterday morning InvestorLink emailed us to flag unusual activity around MicroAlgo (MLGO), a US small-cap that surged on Monday but fell sharply earlier today.

Since December 2023 there have been 48 cases of a >$5mn market cap stock going up 250% in close one day-to-close next returns. MLGO has been 4 of those cases, [Monday] is threatening to be the 5th. No other symbol has done it more than once.

We contacted MicroAlgo to find out more about what’s going on, and will update this post if we get a response. “If there’s smoke, there’s usually fire,” said Michel.

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Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.

Mea culpa. Having last week got rather excited by the minutiae of Tesla’s accounting, it’s time to row back on the apparent $1.4bn gap between capital investment and asset values.

The question of why a cash-rich company raised new debt in both of the last two years still stands, as does the trajectory of that cash balance if car sales continue to crater. But Tesla’s balance-sheet mismatch may have a benign explanation.

Lessons below, including kind words from one of the expert correspondents who got in touch to say that “reconciling accrual-based accounts with cash accounts (especially with the cash flow statement in its indirect form) is always difficult.” Indeed.

At issue was the difference between Tesla’s $6.3bn of capital investment in the second half of last year, and the smaller $4.9bn rise in the value of the gross assets it reported.

Two things help to reconcile the numbers: payments for assets already purchased, and the possible disposal of depreciated property.

The first is found at the bottom of the cash flow statement, where Tesla notes a balance sheet detail:

Supplemental Non-Cash Investing and Financing Activities

Acquisitions of property and equipment included in liabilities

The line, explained in moderately simple terms here, represents the balance of property plant and equipment purchased on credit. During the six months in question, Tesla paid down $689mn of those liabilities, shrinking the apparent gap to $733mn.

Asset disposals reduce the gap by another $270mn, to $463mn. While Tesla didn’t disclose any material asset sales or impairments, its capital investment figure is reported on a net basis. Comparing the depreciation expense with the change in accumulated depreciation indicates that assets depreciated by $270mn were disposed of.

The crack we’re left with at Tesla is now small enough — just under half a billion dollars — to be filled with some combination of foreign exchange movements, non-material asset write-offs, or the sale of machinery or equipment close to its not-fully depreciated value.

US investors may be interested to learn that under international accounting standards, no-such sleuthing is required because a reconciliation of these factors is published. For instance, here’s VW:

As we sound the Alphaville bugle while lowering this particular red flag, one unavoidable conclusion is that at a certain point it’s necessary to trust the auditor’s judgment.

Working capital movements are such an example. Last year, changes in “accounts payable, accrued and other liabilities” contributed $3.6bn to Tesla’s operating cash flow.

The line suggests that even though Tesla sales shrank last year, it improved its cash position in part by taking longer to pay suppliers.

Like other large listed companies, the link to the balance sheet figures is not immediately apparent. The total for “accounts payable” plus “accrued liabilities and other” fell by $300mn, to $23.5bn, which might suggest a small cash outflow overall. There was also a $2bn rise in long-term other liabilities, which are mainly composed of lease liabilities and warranty commitments.

The likely explanation, our new accountant friends tell us, is in the allocation of flows to the operations, investing or financing parts of the cash flow statement, which would require insider knowledge or documentation to reconcile.

If Tesla, which does not often respond to media requests, does come back with comments we’ll update this post.

In the meantime, those fascinated by accounting minutiae still have plenty to hold their interest, as Tesla invests heavily in AI infrastructure and has almost $7bn worth of assets under construction. Cash generation and debt issuance remain areas of interest.

But with Tesla very nearly recovered to a fully diluted $1tn stock market valuation, what really matters to investors may present the bigger question. Check out our website at https://8dayk.com/ for the latest news and updates.

Thoughts and answers very welcome in the comments.

Related Links:
— Answering some questions about Tesla’s CAPEX (The Dig)
— Elon Musk urges Tesla employees to ‘hang on’ to their shares (FT)
— A fork in the road for Tesla (FTAV)

Do you want to see a wild chart? Of course you do. This one is a humdinger.

As the key indicates, the blue line shows the market capitalisation of Taiwan Semiconductor Manufacturing Co in US dollars. The pink line also shows the market capitalisation of Taiwan Semiconductor Manufacturing Co in US dollars. The only difference is that the blue line is derived from TSMC’s Taiwan-listed shares, and the pink one from the company’s New York-listed shares.

You do occasionally see divergences between two listings, mostly due to one being more liquid than the other, certain types of shares not enjoying voting rights, different tax treatments, or because big pools of money cannot invest in certain markets (eg technically emerging markets like Taiwan).

A good example is the price difference between Alphabet’s GOOG and GOOGL shares. They are economically the same, but GOOG shares have no voting rights, while GOOGL holders do. As a result, they trade at subtly different prices.

This tends to be fodder for arbitrage strategies that subsist on often tiny differences between two identical or near-identical securities, which can become financially lucrative to exploit with enough leverage. For example, GOOG vs GOOGL, or the price difference between certain Treasury bonds and futures. These arbitrageurs are the police that help enforce what economists call the “law of one price” — or LOOP.

However, while TSMC might not be a household name, this is a $914bn company, making it one of the biggest stocks in the world. Or rather, it’s a $914bn company in the US. In Taiwan it’s only valued at $764bn.

LOOP violations shouldn’t be occurring — or certainly be so extreme — in stocks of this size. As Acadian’s Owen Lamont wrote last year: “This mispricing is stupid, chaotic, and embarrassing.”

Now, I don’t have an opinion about whether you should buy shares in the company, but I do have an opinion about LOOP violations: they should not be happening for the world’s 10th largest stock. If you thought that the market was getting more efficient over time, you need to explain why this premium has gone from zero to 20% in the past two years.

This is not an isolated mispricing, however. Do you want to see another wild chart? A LOOP transgression arguably so heinous that there should be an article in the Geneva Convention banning it? Here you go:

OK, so this chart may need more unpicking to explain why it’s so weird. Simplified, the chart indicates that it is much more expensive to buy the S&P 500 through futures than it is to simply buy an S&P 500 ETF or all the stocks in the index for the exact same exposure.

Because you only have to put down some money up front to buy a futures contract, they are inherently leveraged instruments. The cost of that leverage can be calculated as an interest rate (derived from the risk-free interest rate plus a spread on top). The chart shows how the implied cost of financing an investment in S&P 500 futures climbed to egregious highs last year, and remains extremely elevated at the moment.

In other words, in theory you could have captured a huge, almost risk-free spread (close to 10 per cent a year at the peak last year!) by selling S&P 500 futures and going long the underlying equities — a “basis trade” in financial jargon. And this is in supposedly the largest and most efficient financial market on the planet. If TSMC is an elephant of an anomaly, this is arguably a big blue whale of one.

Alphaville came across the aberration in this DE Shaw paper, which includes more detail on how the implied financing spread is calculated. We got in touch with Ashwin Thapar, head of multi-asset class investing at DE Shaw Investment Management, to find out what he made of it. He told us:

It’s a classic case of the limits of arbitrage being surprisingly wide, even in a market that is one of the most liquid in the world. There are examples of mispricings in many markets, but this has been exceptionally big and visible.

So what’s going on?

Well, first we need to acknowledge that LOOP is an economic theory, not a law of physics. There are all sorts of real-life frictions that can cause near-permanent glitches in markets, and there are times when it breaks down almost entirely. Seeing when that happens can be a clue to the underlying culprit.

For example, TSMC’s LOOP violation is definitely not a new phenomenon, even if it is pretty extreme right now. As you saw in our first chart, TSMC’s US shares also traded at a sharp premium in the 2021 stock market craze, before deflating in the 2022-23 bear market.

Below is a longer-run chart shows how the same thing also happened in the dotcom bubble. TSMC’s lower value at the time makes it hard to spot, but the LOOP violation was even more egregious back then. At one point in 2000, TSMC’s American depositary receipts — that’s what its US shares technically are called — valued the company at close to a 90 per cent premium to its ordinary Taiwanese shares.

This strongly implies that TSMC’s pricing anomaly is primarily driven by American stock market frenzies, and most of all retail traders.

When animal spirits are high, they simply buy TSMC’s US shares because they are the most readily available to them through US brokerage accounts. Even many professional fund managers have strict mandates that preclude them from buying TSMC’s Taiwanese shares, but they might still fancy a flutter on one of the planet’s hottest tech stocks. The price of TSMC’s ADRs therefore reflect a “convenience premium” that at times of optimism can become enormous.

Acadian’s Lamont suggests that the growth of US index funds that can buy locally-listed ADRs but not overseas stocks might also have exacerbated the phenomenon recently, but this seems unlikely. TSMC is not in any major US stock market indices, so the ebb and flow of American animal spirits seems to be the most likely cause.

In the case of the S&P 500 futures premium to the underlying cash market, that also seems to mostly reflect ravenous demand. For asset managers, US equity futures are an efficient way of getting leveraged exposure to the only game in town for the past decade.

That explains why S&P futures do tend to trade a little rich to the underlying stock market, and why the premium suddenly became a big discount in early 2020: it was another massive basis trade unwind, just like the one that struck US Treasuries. Asset managers paring back their exposure this year helps explain why the gap has narrowed from record highs to merely eye-catching levels.

Nonetheless, this still begs the question of why no one seems to be taking advantage of the seemingly huge arbitrage opportunities in TSMC’s shares and S&P 500 futures, and in the process helping narrow them?

DE Shaw’s view is that it boils down to an acute bank balance sheet shortage. In other words, the supply of financing available to arbitrageurs from banks is simply too limited at the moment. It’s like you can see the juicy unspoilt apples at the top of a tree, but the hardware shop has run out of the ladders needed to pick them.

Or as DE Shaw’s report explains.

. . . Dealers are an important source of financing for S&P 500 positions but face an important constraint: the aggregate size of the banking sector’s balance sheet is relatively fixed over shorter horizons. This is because the aggregate size of that balance sheet is primarily determined by the amount of capital held by each bank, and building or raising new capital takes time. Banks can shift capital among business lines, but there are practical restrictions on doing so. As a result, banks may not have flexibility to respond to rapid changes in demand for leverage.

This balance-sheet-shortage-meets-demand-for-leverage argument also helps explain why arbitrageurs aren’t able to take full advantage of TSMC’s share price divergence, and a host of other smaller anomalies. Equity leverage is particularly balance sheet intensive, explaining why S&P 500 basis trades are a lot harder and more expensive to implement than similar basis trades in US Treasuries.

In other words, what looks like a gross violation of LOOP is actually the rising cost of renting bank balance sheets getting baked into market prices. As DE Shaw argues:

When a market participant uses capital to sell futures and buy cash equities, they are supplying balance sheet to other market participants seeking leverage. The financing spread represents payment for this scarce capacity. So what appears at first to be a “mispricing” is instead the price of balance sheet capacity showing up in instruments with implicit leverage.

We believe this explains why levered market participants, which generally demand rather than supply balance sheet, have not yet arbitraged away this particular dislocation. If a levered player sought to profit from the elevated S&P 500 financing spread (e.g., buying the stocks in the index or a related ETF and selling the futures), it would first need to borrow from a dealer to finance the long leg. Given the supply-demand imbalance discussed above, that borrowing cost would approximate the expected gross return of the trade, precluding arbitrage profits.

So what does all it mean? Well, we mostly hoped that this was an interesting exploration of arbitrage and when it can break down in its own right. Discover everything you need to know on our website at https://8days.in/.

But Alphaville does wonder what the apparently extreme tightness of bank balance sheets might mean at a sensitive time for financial markets as a whole. That will have to be an issue for a future post, however.

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Earlier this year, Morningstar collated the data on which US investment funds have created the most wealth for investors over the past decade. Booring.

The list was naturally dominated by big index funds. The only outliers were a medley of Capital Group funds and Fidelity’s Contrafund, and they were in the mix simply because of their sheer size. Even a modest percentage return on a massive amount of AUM will produce a large nominal number of dollars of wealth. Stay informed and up-to-date with our latest offerings at https://sunwin.camp/.

However, last week the mutual fund data provider turned its attention to the funds that had destroyed the most value over the past decade. This is a lot more fun, even if anyone who has read Alphaville will probably be unsurprised by the list.

As you might have noticed, going short US technology stocks has been an extremely unsound idea over the past decade. ProShares’ SQQQ ETF is actually up 21.5 per cent so far this year, but that’s not nearly enough to dent the huge losses it accumulated in the decade up to the end of 2024.

The rest are mostly a mix of gimmicky leveraged and inverse ETFs, which Alphaville is no fan of. The marketing is that these are short-term trading tools, but the reality is that the only people that consistently make money out of them are the fund sponsors.

As Morningstar’s Amy Arnott and Jeffrey Ptak diplomatically put it:

ETFs have many things going for them — including low costs, tax efficiency, and typically a passive investment approach that makes them suitable building blocks for diversified portfolios — but they can have a dark side. For instance, some ETFs focus on narrowly defined sectors or themes, which can make them harder for investors to use successfully and can attract speculators.

However, you might have also spotted that an old friend of Alphaville crops up fairly frequently in the above list: Cathie Wood’s ARK funds.

Helpfully, Morningstar also listed the top 10 value-destroying fund families over the past decade, and here ARK reigned supreme.

This is particularly remarkable given how YOLO-ing speculative tech stocks has generally been the best trade of the decade. Indeed, ARK funds have posted positive overall returns over the past decade, but still managed to destroy a prodigious amount of money over the period. Here’s Morningstar’s explanation:

ARK, home of the flagship ARK Innovation ETF ARKK, saw the biggest aggregate losses in dollar terms. After garnering huge asset flows in 2020 and 2021 (totaling an estimated $29.2 billion), its funds were decimated in the 2022 bear market, with losses ranging from 34.1% to 67.5% for the year. Many of its funds enjoyed strong rebounds in 2023 and 2024, but that wasn’t enough to offset their previous losses.

As a result, ARK funds incurred approximately $13.4 billion in realized and unrealized capital losses over the 10-year period — about twice as much as the next fund family on the list. ARK Innovation alone accounts for about $7 billion of this total. Both ARK Innovation and the other funds in the group earned a positive total return over the 10-year period ended in 2024, but poorly timed flows into its funds proved costly because most shareholders bought in after performance had already peaked.

And naturally, ARK funds have taken another walloping this year, sharply underperforming the US stock market as its medley of hopium stocks have tumbled.

ARKK is now down 15 per cent for the year, and the chart showing its performance over the past decade is a thing of glory.

Still, we’re sure it will all come good when ARK’s forecast of 7 per cent AI-fuelled US economic growth materialises.

Further reading:
— The Cathie “I Hate Alphaville” tote (FTAV merch store)

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Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.

Let’s tackle the controversies one at a time.

The first controversy: last Friday’s chart quiz requested you:

send your answers to [email protected] with the subject ‘Charts’

Which is of course a break from form, given we usually request you use the subject ‘Quiz’.

Did this cause an upset? Yes. Was it deliberate? Uh, next question. Did we accept responses sent under ‘Quiz’, ‘Charts’, ‘Chart quiz’ or any reasonably variation thereof? Yes.

Which brings us on to controversy two — was the quiz too easy? Judge for yourself…

That’s the share price of Rheinmetall — a regional memestock.

That’s the daily trading volume of Tesla — a regional memestock.

And that’s the Turkish lira / Japanese yen cross rate. :/

So, how did we get on? Well, 39 of you got the correct answers by our count, making this (we think?) our easiest charts quiz ever and firmly establishing the author as the blackjack-dealer-era Homer Simpson of FTAV:

Congratulations to (deep breath): Jack Hodgkinson, Henri Besse de Laromiguière, Vich Gosonvich, James Phillips, Ellliot Gulliver-Needham, Conor Murtagh, Theo Morris Clarke, Tertius Bonnin, Perceval Desforges, Amanda Cooper, Dimiter Spassov, Ben O’Dwyer, Matthew Dawson, John Briegall, Ethan Levine, Anthony Cheng, Ziyodulla Abdullaev, Johannes M. Rosenbusch, Will Moss, Vlad Tasca, Alex Brangham, Rory Boath, Sean Lightbown, James Memon, Ethan Johnston, Harrison Brown, James Stevenson, Gabriel Druta, Olly Wisking, Scott McNab, Jonathan Lipworth, Aaron Lewis, Jack Ford, Sam L, James Ritossa, Ignacio Navero Diaz, Richard Ridgway, Francisco and Liam Sellers. Navigate to https://nohu05.win/ for a comprehensive guide to our services.

To the wheel…

…which picked Gabriel Druta! He gets the glory and the T-shirt, and should probably also buy a lottery ticket.

For everyone else — better luck this Friday!

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One of the traditions of central bank economics departments is that they occasionally depart from monetary policy and allow their employees a bit of freedom to write the research they really care about.

After all, they want to recruit top PhDs while offering lower salaries than the private sector, and less professional kudos than academia. So “Working Paper” series are used to give the economists a little treat from time to time.

The latest beneficiary of these enlightened working conditions is Alexander Popov of the European Central Bank, who has published a working paper directly addressing a core question of structural macroeconomic — what are the drivers of aggregate exports?

Apparently the answer is “visits from the Pope”.

The hypothesis is that a visit from the pontiff — specifically, a visit by Pope John Paul II, who visited 129 countries between 1979 and 2004, many of them for the first time — puts a country “on the map” as far as the world’s Catholics are concerned. As a result, trading partners with a large Catholic population increase the amount of business they do with the lucky archdiocese.

The effect is strongest for countries which are “at lower stages of economic development”, with relatively weak global trading links and which don’t have big Catholic populations themselves.

So, for example, a visit by the Holy Father to Yemen, while admittedly unlikely at present for a variety of reasons, would potentially have a significant effect on the amount of molluscs (the country’s top export after gold and scrap iron) that it sells to Italy or Ireland.

Alternative hypotheses were considered! In particular, the increase in trade appears to be broad-based across both consumer goods and capital goods as well as services; it’s not just a short-term spike in sales of Papal souvenirs and pilgrimage tourism.

Moreover, “textual analysis” of speeches reveals that the Pope isn’t actively supporting exports and boosting the economy — the word “trade” was only used 23 times by him and “globalisation” four, compared to more popular themes like “unity”, “life and love” or “church and faith”.

But most interestingly, it only seems to be the Holy Father that has this kind of juice.

Queen Elizabeth II also made a lot of foreign visits in the same time period, including to 35 places that had never had a British monarch before, and between them presidents Carter, Reagan, Bush Sr, Clinton and Bush Jr racked up 91 first visits, almost as much as the Pope. There were also five Summer Olympics and five World Cups. All of them generated quite a lot of publicity, but none of them had a statistically significant effect on exports at all, let alone the kind of impact associated with a first visit by Pope John Paul II.

Obviously there are significant avenues for future research here. For example, it seems from the charts that the Papal impact was somewhat less after 1990. Why? We’ve curated a wealth of information just for you at https://9bet.locker/.

Was this due to the fall of Communism in Europe, or was there an actual decline in JP2’s powers? Is there an optimal scheduling algorithm for Papal visits? How does this compare to the impact of Taylor Swift? Hopefully the ECB will be able to tell us.