Walking along the Chicago River in the first week of October, the smell of corn was everywhere. It was harvest season, and the whole of Illinois’ corn was converging on this one muddy river. James Curtis, a grain merchant, arrived at the river bank each morning before dawn and moved between his storage units, checking what had arrived overnight.

This year the harvest was particularly plentiful and good-quality all around Illinois, driving prices per bushel 30% lower. After assessing the quality of each load, Curtis negotiated prices: “$1,200 for 3,000 bushels”, said the farmer. “Mine”, shouted Curtis. In the afternoon, he retreated to his office above the elevator, a small room that smelled of sawdust and ink, and read his correspondence. A letter from his agent Thomas Hale sat on his desk. Hale wrote that corn supply in Buffalo was becoming increasingly scarce as the Rochester mills were running at full capacity. If that rate of consumption continued through winter, stocks would be thin by March. He had also spoken to two of the Rochester mill buyers stationed in Buffalo, both of whom were looking to secure corn for the spring. One had indicated they could take a sizeable consignment with delivery in April, at the right price. Curtis then folded the letter, picked up his coat and walked to the Marine Bank on Lake Street.

The manager, a man named Graves, listened to everything without interrupting. At last, he asked how much more Curtis intended to purchase before the season closed: 30,000 bushels. There was a long pause in which the only sound was the distant noise of the river and the street below, and then Graves agreed to an extension of the credit line at a 10% interest rate. Six weeks earlier, Curtis had sat across from Graves in that same office and asked for a credit line to buy corn for the season.

By late March, as the ice broke in the Chicago harbor, Curtis sent his first shipments east across Lake Michigan and wrote to Hale asking for a market update. The reply came two weeks later carrying unexpected news: Buffalo was softer than either of them had expected. As they did every spring, Chicago merchants had anxiously rushed their corn east the moment the harbor opened, after months of carrying costs and interest payments. While the Rochester mills were used to absorbing it, this year was different. The harvest in Ohio was so abundant that its corn had been moving east by road and canal all winter, so that by the time Curtis’ shipments started arriving, warehouses were already well-stocked. The season proceeded to register the lowest corn prices Buffalo had seen in years, and Curtis, along with many other Chicago merchants who had held corn through the winter, closed his books in June at a loss.

The grain trade in 1850 operated across hundreds of miles through multiple layers of intermediaries, with information moving by letter, and no mechanism to gage supply and demand across regions. The biggest issue Curtis faced was at what price corn would sell in spring. If he could agree on a selling price before the corn was bought, he wouldn’t be exposed to the Ohio harvest or any other external forces.

By September 1850, before the first wagon had appeared on the riverbank, Curtis instructed Hale to approach the Rochester mill buyers and find one willing to commit to a price for April delivery before the harvest began. Within a fortnight, Hale wrote back with terms from a mill owner named Aldrich: 20,000 bushels of corn at 40 cents a bushel, delivery in April. Curtis wrote back agreeing to the terms, folded the letter and walked to the Marine Bank. For the first time, the conversation with Graves was straightforward as he was asking to lend against corn already sold, to a buyer already named and at a price already fixed. Graves studied the letter, asked a few questions about Aldrich’s commercial reputation, and agreed to a larger and cheaper credit line than the previous year. Within a few years contracts of this kind were common enough that merchants were buying and selling them before delivery and a secondary market started to emerge.

The institution that would eventually transform these private bilateral agreements into standardized exchange-traded instruments had already been founded in April 1848 by 82 Chicago merchants. In its early years, the Board of Trade of the City of Chicago (CBOT) functioned mainly as a commercial association, a place where merchants gathered to resolve disputes, discuss harbor infrastructure, and agree on common practices. Through the 1850s, however, the CBOT laid the foundation for standardised contracts by establishing uniform grain grades — No. 1, No. 2, No. 3 — certified by exchange-appointed inspectors whose decisions were binding on all members. A contract was interchangeable with any other contract of the same specification and could be bought and sold between merchants who had never met. In February 1859, the Illinois legislature granted the CBOT a formal corporate charter, backing with law what had previously run on reputation and trust.

In May 1865, the CBOT became the first futures exchange by restricting trading to exchange members, standardizing every contract specification — lot sizes, grades, delivery months, delivery locations — and requiring both parties to post a margin deposit before a trade was valid. Before, to-arrive contracts were based on trust. If prices moved sharply against a seller between October and April, they had every incentive to default and accept the legal consequences which were slow, expensive, and uncertain. With the introduction of a margin deposit, the risk of either party defaulting was significantly reduced.

What emerged from those rule changes is what we now call a futures contract, in which the only variable left to negotiate was the price. Contracts could now change hands dozens of times before delivery, each buyer and seller transacting with the exchange. This resulted in the emergence of speculators, whose sole purpose was to profit from price changes and who would close out their positions prior to delivery. While speculators were viewed with deep suspicion, they were critical in providing liquidity. Every time a merchant like Curtis needed to sell a forward commitment, he needed someone willing to take the other side of the trade, and speculators did exactly that. By the 1870s, fewer than one in ten futures contracts resulted in actual physical delivery.

What followed was an expansion in scope that Curtis, standing on the riverbank in 1849, could not have imagined. Agricultural futures spread from corn and wheat to cotton, butter, and eggs before the end of the century. When the United States abandoned the gold standard in 1971 and currencies began to float, the Chicago Mercantile Exchange recognised that exchange rate risk was structurally identical to corn price risk and launched currency futures. Interest rate futures followed in 1975, while equity index futures in 1982. In 1981, Eurodollar futures became the first contract settled in cash rather than physical delivery, breaking the last remaining connection between a futures contract and any underlying. Today, futures contracts trade on most exchanges worldwide across asset classes ranging from crude oil and natural gas to government bonds and equity indices.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

The clock strikes 6am and the alarm starts ringing. Navinder Singh Sarao gets out of bed, ready for another day of work. He stumbles, half asleep, to his desk at the corner of his childhood bedroom located within his parents’ home in Hounslow, West London. A wiggle of the mouse and six screens light up. Nav scrolls through overnight news, followed by any market movements. The topic taking everyone’s attention at the moment is the possible default on Greek sovereign debt, and any subsequent bailout. Markets are opening weak, with sovereign spreads wider, premiums on Credit Default Swaps higher, and European stocks 4% lower.

This is exactly the kind of day Nav operates best in, one of fear and volatility. At 11:17am he starts placing large limit sell orders on S&P futures — 200, 400, 900-lots — outsizing nearly everything else in the market. In Hounslow, sprinklers go off to water the garden on a peaceful sunny day. Meanwhile in Athens, there are riots outside parliament.

As the day progresses, the order book becomes increasingly imbalanced. Market liquidity is drying up and buyers are stepping back. The sell orders which Nav has been placing account for nearly a third of all visible selling pressure on the exchange. At 2:30pm, the Dow is down over 300 points. The VIX has surged more than 20% since the open. Liquidity in S&P futures has been cut almost in half. In Overland Park, Kansas, a mutual fund company called Waddell & Reed is about to execute a trade.

**

Four years earlier, Nav had been making money for someone else. Fresh out of Brunel University he joined Futex, a proprietary firm on the outskirts of London. While other trainees were still losing money in a simulated environment, Nav was making tens of thousands of pounds on live markets.

As time went on, Nav grew increasingly dissatisfied with having to share his profits with his employer. So, in early 2008, at 28 years old and with a net worth of £2 million, he handed in his notice and left. He decided to set up a trading station in his childhood bedroom of his parents’ house. His strategy was simple but executed ferociously. He would place large sell limit orders on S&P futures, always a few ticks above the market. Other traders would see the selling pressure and prices would drift lower. Meanwhile, Nav would buy and then cancel the sell orders. He repeated this practice, known as spoofing, thousands of times a day. By 2010, he had created an algorithm to automate this.

**

It’s now 2.32pm, and one of Waddell & Reed’s fund managers decides it’s time to hedge the $75 billion portfolio – mostly invested in US equities – and enters a sell order of 75,000 S&P futures worth roughly $4.1 billion. In a market already thin and heavily skewed to the sell side, there are no buyers for such a size. When Waddell & Reed’s algorithm starts selling, the high frequency market maker who has been hit offloads the position on to someone else, who then passes it on to someone else. The same contracts are passed around between firms at rapidly falling prices as nobody wants to hold the risk. Doing so generates large volumes, and because Waddell & Reed’s algorithm is programmed to sell 9% of whatever volume has traded in the previous minute, it creates a snowball effect of selling.

At 2:42pm the market goes into freefall. The Dow drops 600 points in five minutes. $1 trillion in market value gets wiped out. Accenture’s stock goes from $40 to $30, then $20, then…1 cent. Apple shares, on the other hand, soar to $100,000. Prices stop making sense, the market breaks down, and it becomes absolute chaos. At around 2:45pm the Chicago Mercantile Exchange (CME) triggers a five second trading pause on S&P futures. When trading resumes, buyers return and prices stabilise.

By 3pm the market recovered most of the loss and the Dow closed down 348 points on the day. The Flash Crash was over, but it would take years for anyone to fully understand what had just happened. The early theory was a fat finger — a trader somewhere who had typed billions instead of millions, subsequently sending the market into a tailspin. Attention turned to high frequency trading firms, whose algorithms had clearly played a role in the freefall, though whether as a cause or a consequence remained up for debate.

Five months later, a joint report by the Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) pointed the finger at Waddell & Reed. The CME pushed back — a trade of that size, they argued, was entirely routine and could not have caused what happened on its own. Many in the market agreed. Nobody, at that moment, was looking at Hounslow.

While the finger-pointing continued, regulators moved quickly. Within months of the crash, US exchanges introduced circuit breakers on individual stocks — automatic pauses triggered if a price moved too far, too fast. Spoofing was criminalised in July 2010, just two months after the crash. In the past, the practice had existed in a legal grey, with regulators largely powerless to act.

Despite spoofing being now a crime, the authorities lacked the tools to detect it. Nav, who had made $880k on the day of the Flash Crash, carried on spoofing the E-mini as if nothing had happened. He accumulated a fortune that would eventually reach $70 million, but most of it was lost by handing it to fraudsters. It was only in 2014, when the CFTC developed surveillance tools sophisticated enough to identify market manipulation patterns, that analysts traced the activity back to him. Nav was arrested in April 2015 for fraud and market manipulation and a year later pleaded guilty to wire fraud and spoofing. In 2020, Judge Kendall sentenced him to a year of home confinement.

Markets had crashed many times before, but May 6th, 2010 exposed the world to a new kind of danger, one where automated systems interacting in a fragile and illiquid market could spiral out of control. The regulatory responses that followed were meaningful but incomplete, and markets have remained vulnerable to crashes of the same nature: the US Treasury flash crash in October 2014, the ETF flash crash in August 2015 and the Sterling flash crash in October 2016.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

Tesla, the company well known for making electric vehicles, is one such company with a P/E of 370. This puts it as one of the top S&P 500 companies by P/E ratios. Even against high-growth US tech stocks — Nvidia, Apple, Google — it screens high. BYD is the closest automotive comparison, and that trades at a fraction of Tesla’s multiple. From the chart below, it’s clear that P/E ratios of traditional car manufacturers are vastly different. A simple glance would suggest that EV manufacturers trade at a 10x premium. What stands out most, however, is the divergence between Tesla’s and BYD’s P/E ratios over the past two years. At a ~$1.25 trillion market cap, investors are largely paying for business units beyond car manufacturing.

Bank of America’s sum-of-the-parts model assigns Tesla’s core automotive business 12% of its total implied value. At the current market cap, that is roughly $150 billion. For context, GM and Ford’s market caps are $67 and $47 billion respectively. Meanwhile Toyota — the world’s largest car manufacturer by volume, with total revenues more than four times Tesla’s entire automotive segment — is valued at approximately $275 billion. Tesla’s U.S. market share peaked at 4.3% in 2023 and has declined every year since (see chart below), while BYD has overtaken it as the world’s largest battery electric vehicle manufacturer.

Policy has moved in the wrong direction too. Since Trump’s re-election, federal purchase incentives have been eliminated, EV mandates revoked, and fuel economy standards rolled back – removing a key tailwind for the industry. Leaving aside the debate over how much premium Tesla’s car business deserves, investors are not buying this stock for the cars.

Tesla’s energy generation and storage unit is the company’s strongest segment, with revenues up 27% in 2025 and gross margins of ~30% across the year. Yet BofA’s model assigns it just 6% of Tesla’s total implied value, or approximately $75 billion. This still leaves over $1 trillion in valuation that must be justified entirely by three businesses that are either pre-revenue or in early pilot phase: Robotaxi, which accounts for 45% of the implied value (~$562 billion), Full Self-Driving (FSD) subscriptions 17% (~$213 billion), and Optimus 19% (~$238 billion).

Robotaxi consists of creating a fleet of self-driving cars that work like Uber. Tesla began paid rides in Austin in June 2025 and plans to expand to seven additional U.S. cities in the first half of 2026. Revenue estimates for the upcoming years vary greatly, but consensus is that breakeven will not be reached until sometime in 2027 and even then the fleet will still be tiny compared to its valuation. Weeks before Cybercab production was due to begin, Tesla lost the engineer who built its Robotaxi software backbone — an 11-year veteran whose departure raises questions about near-term execution.

FSD is Tesla's driver-assistance software, which — once fully autonomous — would allow any Tesla vehicle to operate without human input. Tesla currently charges $99 per month following the move to subscription-only in February 2026, and had 1.1 million paid subscribers globally as of Q4 2025. That's $1.3bn in annualized revenue against a $213bn implied valuation (a 163x multiple), which implies that the subscriber base would need to grow more than tenfold just to approach a conventional tech valuation.

Optimus is the most speculative of the three. It is a humanoid robot designed initially for factory automation, with longer-term ambitions in consumer and commercial applications. Musk has said 80% of Tesla’s long-run value will come from this programme. Production has slipped to late 2026, with meaningful revenue not expected before late 2027.

If you are buying Tesla shares as an automotive investment, only 12% of the business justifies that. The rest is a bet on a tech company that has yet to prove itself, and at the current valuation risks are tilted to the downside. There exists a scenario in which Robotaxi scales slower than expected, FSD monetisation disappoints, and Optimus is still years away than Musk suggests. Given that the current share price requires a smooth rollout of each business, we think Tesla will struggle to maintain its valuation.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

The Kelly criterion was developed in 1956 by John Larry Kelly Jr. at Bell Labs. Kelly noticed that the mathematics of optimal signal transmission over noisy channels was structurally identical to the mathematics of optimal betting. The result was a formula for bet sizing that maximises long-run growth. If you have an edge, bet a fraction of your stake equal to that edge divided by the odds. Bet less and you leave growth on the table. Bet more and you go broke. Overbet a winning strategy and you reduce long-run growth.

When you decide on the size of your bet, you are making two decisions at once. You are deciding how much you stand to gain if you are right (growth decision), and you are deciding how big of a loss you take if you are wrong (survival decision). Losses and gains are asymmetric, so the recovery from a large loss requires a disproportionate gain just to get back to where you started. For example, if you lose 50% of your capital then you need a 100% return just to break even. Kelly formalises this by optimising for long-run growth rather than single-bet returns. Pierre Andurand’s fund illustrates this precisely: the -55% drawdown in 2023 nearly erased two years of exceptional returns (see table below). Over the full period, the S&P 500 marginally outperformed, but with materially lower volatility.

Sitting sober at the blackjack table, Thorp understood something: the Kelly criterion was not only a gambling tool. It was a framework for any decision made under uncertainty with an identifiable edge. In 1962 he published Beat the Dealer, the first rigorous account of how probability and position sizing could beat a casino. In 1969 he founded what became Princeton Newport Partners, one of the first quantitative hedge funds, applying the same logic to markets. The fund returned 18.2% annually after fees over nearly two decades, without a single losing quarter.

The book reached well beyond the gambling community. Bill Gross, then a psychology student at Duke University, read it and went to Las Vegas to test the theory. He turned $200 into $10,000 over a single summer, sizing his bets in strict proportion to his edge. In 1971 he co-founded PIMCO, which grew into the world’s largest bond fund. He ran it the same way he had run his blackjack stake. “Here at PIMCO it doesn’t matter how much you have, whether it’s $200 or $1 trillion,” he said. “Professional blackjack is being played in this trading room from the standpoint of risk management and that is a big part of our success.”

In practice, applying Kelly to markets is harder. In markets, investors rarely know their true probability of profiting from a trade, and conviction tends to inflate that estimate. Even when applied correctly, uncertain inputs make overbetting the default risk. Additionally, a portfolio built entirely on Kelly’s criterion may be subject to high levels of volatility which oftentimes hurts a fund manager’s credibility. While Kelly is designed to prevent you from going bust, short term periods of large losses are still consistent with a winning strategy. Thorp knew these caveats and typically applied half to three-quarters Kelly in practice. Most hedge fund managers today follow the same logic: those who use Kelly typically apply a fractional version.

The overlap between markets and probabilistic thinking extends well beyond Kelly: Steve Cohen, founder of hedge fund Point 72, has credited poker with teaching him to take risks, and Annie Duke, a World Series of Poker champion, now consults for hedge funds on decision-making under uncertainty.

The question Thorp was asking at that blackjack table in 1961 was not whether he had an edge. He knew he did. The question was how much to bet on it. That question led to a book, a hedge fund, and an inspiration to a generation of fund managers. It is also a question most people almost never ask, in markets or anywhere else. The instinct is often to focus on whether you are right, rarely on how much to bet that you are right.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

A Fed hold is widely anticipated, while markets are pricing in a cut in June and a 50% probability of a second cut by year-end. Powell’s tone is expected to be cautious — vigilant on inflation persistence from the oil shock, but stopping short of a hawkish pivot. The policy statement will likely reflect elevated inflation risks and a prolonged data-dependent approach, with no major departures from recent language. Notably, next week will almost certainly be the last meeting chaired by Powell. Some expect incoming chair Warsh to be more dovish given Trump’s pressure for cuts. However, we think this may not be the case.

The ECB is also expected to hold. Compared to the Fed, however, the market is currently pricing in more than one hike by year-end (with the hike to be delivered in September). This marks a decisive shift from prior to the conflict – rates were priced to be on hold throughout the whole year – due to Europe’s sensitivity to energy shocks which drive inflation higher. Recent comments by Governing Council members underline how the ECB will act decisively in a timely manner should energy prices be reflected into CPI medium-term estimates. Pre-war, the tone was neutral to dovish, with more of the concerns around growth. No changes are expected on the ongoing Quantitative Tightening and on the structural portfolio.

With inflation in Q4 projected to be 0.5-0.6% higher due to energy prices, the BoE is now also expected to hold. The February meeting had a narrow 5-4 hold vote split, which was dovish and closer than expected (economists had anticipated a clearer 7-2 hold). This surprise led the market to price a full cut in March. Recent events have therefore marked a material shift in rate expectations. The market is now pricing in no cuts at all for the remainder of the year. Regarding balance sheet normalisation, no changes are expected; the pace of ongoing normalisation may be reduced if rate holds persist.

Overall, the market had been anticipating neutral/cuts rate decisions across G3 central banks for this year. The Iran war has shifted expectations to the hawkish side. As with any situation like this, market expectations can change on a day-to-day basis. Stay tuned.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

The United States has not fought a war on its own soil since the Civil War ended in 1865. This geographic insulation is arguably the single most important factor. When conflict breaks out in Europe or the Middle East, US corporate earnings, supply chains, and physical infrastructure are almost never directly affected. This contrasts sharply with European markets, which have historically exhibited far greater sensitivity to conflict. When North Korea invaded the South in June 1950, West German and broader European equity markets sold off sharply — investors were pricing in the possibility of a Soviet-backed push through Central Europe. The Dow Jones, by contrast, absorbed the shock almost immediately and was up over 16% twelve months later.

The looming risk, or outbreak of war, increases spending in the defence sector both domestically and internationally. When spending on defence increases, payrolls, capex and R&D all increase, providing support to the US economy. The Korean War rearmament programme contributed materially to the sustained post-war economic expansion. The post-9/11 buildup drove a prolonged period of elevated defence outlays. Additionally, the three world’s largest defence contractors, Lockheed Martin, Raytheon and Northrop Grumman are all American. Russia's invasion of Ukraine triggered the largest rearmament of NATO allies in a generation, with the overwhelming majority of supply coming from US-manufactured systems. The Israel-Gaza conflict reinforced this dynamic further: Israel accelerated procurement of F-35s, precision munitions and Iron Dome replenishment — almost exclusively sourced from American manufacturers — while Gulf states, rattled by Iranian proxy activity across the region, responded with a wave of US arms purchases. Saudi Arabia and the UAE together committed to tens of billions of dollars in new US defence contracts in the years following October 7^th 2023. The subsequent escalation involving Iran in 2026 has cemented American defence contractors as the primary financial beneficiaries of Middle Eastern instability, as regional powers doubled down on US military systems.

Perhaps the most underappreciated reason US equities look through wars is more structural: a substantial portion of equity demand is almost entirely indifferent to geopolitics. Every month, hundreds of billions of dollars flow automatically into US equities through 401(k) contributions, pension fund allocations, and target-date funds. The institutionalisation and automation of retirement savings over the past four decades has created a recurring US equity bid that is mostly indifferent to geopolitics. This dynamic is not confined to American savers. Pension funds, sovereign wealth funds and institutional investors worldwide use US equity indices as their primary global equity benchmark, providing a consistent bid in the market.

Finally, geopolitical shocks trigger a flight to safety with the main beneficiary being the US Dollar. Although there was much talk about de-dollarisation during Trump’s second term in office, the Iran war has proven once again that, during periods of uncertainty, global investors see US markets as safest. As in the past, investors rotate out of risk assets and into dollar-denominated instruments: US Treasuries, money market funds, and ultimately US equities themselves. This dynamic was visible following the Gulf War, September 11th, and the invasion of Ukraine: in each case the dollar strengthened materially in the weeks following the shock, compressing the risk premium on US assets relative to the rest of the world. For a foreign investor holding US equities, dollar appreciation provides an additional layer of return on top of any market performance. War-driven dollar strength therefore supports US equity valuations.

While media outlets constantly report on bombings, casualties and spark fear, markets — especially US equities — have largely looked through all this. Since WWII, US equities have, on average, returned 6% in the 12 months following US active deployment. Even in the first 60 trading days, US equity markets have, with one exception, held their ground or risen (see chart below). The US fights its wars abroad, benefits economically from the rearmament they trigger, and attracts capital when uncertainty spikes. Geography, defense spending, the dollar’s reserve status, and the continuous buying flows from passive vehicles are all supportive for US equities.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

Over long horizons, performance concentrates in assets that occupy the structural centre of their respective systems. The relevant question is therefore not which asset may temporarily outperform, but why the benchmark asset so often delivers the most durable risk-adjusted returns.

The answer lies in structural centrality. Assets at the core benefit from embedded demand, deeper liquidity and lower displacement risk. Peripheral alternatives may offer cyclical upside, but they carry a higher probability of obsolescence, illiquidity or structural loss of capital.

Assets such as the S&P 500, gold and Bitcoin function as global reference points within their ecosystems. They anchor pricing, flows and performance measurement. Their benchmark status rests on, among others, three key properties: flow concentration, survival across regimes and asymmetric transmission.

Flow concentration

Benchmarks are embedded in mandates, risk models and performance evaluation frameworks. Passive vehicles replicate them mechanically, derivatives markets are deepest around them, and hedging activity is structured through them. Investors seeking liquidity, scalability and minimal tracking error therefore gravitate toward the benchmark first. Over time, this institutional framework becomes self-reinforcing: performance attracts flows, flows increase weight, and greater weight further entrenches benchmark status. In that sense, benchmark centrality does not merely reflect past dominance but rather it helps to sustain it.

The S&P 500 illustrates this clearly. Broad, low-cost S&P 500 replication vehicles reached scale well before comparable MSCI World trackers. Early benchmark flows therefore concentrated in the S&P 500. As US equities subsequently outperformed, their weight within the MSCI World Index increased mechanically. A larger US weight within global indices in turn directed a greater share of passive allocation back toward US equities. First-mover advantage and relative performance reinforced one another.

Survival Across Regimes

Assets at the structural core of a system endure repeated regime shifts without losing relevance. They survive crises, policy transitions, technological cycles and speculative manias that eliminate peripheral competitors. The S&P 500 has absorbed wars, inflation shocks, banking crises and multiple sector rotations while continuously reconstituting itself around the dominant firms of each era. Gold has persisted across monetary regimes, from the classical gold standard to Bretton Woods to fiat systems, retaining its role as a reserve asset and collateral anchor. Bitcoin has survived successive boom-and-bust cycles that extinguished large segments of the broader crypto ecosystem, yet each cycle has reinforced its relative dominance.

Asymmetric Transmission

Benchmarks also function as the marginal price-setters within their systems. A 1% move in the S&P 500 transmits materially into major European and Japanese indices for example, with cross-market betas rising during stress. The reverse transmission is considerably weaker. Shocks originating in the core propagate outward; shocks in the periphery rarely reprice the centre. Gold anchors relative pricing across the precious metals complex. Bitcoin anchors liquidity and sentiment within crypto.

These benchmark characteristics are not unique to financial markets. In other ecosystems, value and liquidity similarly concentrate in the reference asset. Within collectible markets, flagship items such as first-edition Charizard cards often trade at a persistent premium and exhibit greater price resilience than comparable cards. In art, capital clusters around blue-chip names whose works function as the benchmark for the category. In prime real estate, global capital gravitates toward a small number of cities. The benchmark asset becomes the focal point for valuation, trading and capital allocation, and that focal status compounds over time.

Benchmark dominance reflects embedded flows, survival across regimes and asymmetric transmission. Peripheral assets may outperform cyclically, but over long horizons capital concentrates where liquidity is deepest and displacement risk is lowest. Accordingly, benchmarks offer structurally superior risk-adjusted returns.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

Performance in the S&P 500 has been heavily concentrated in the Magnificent Seven, meaning index returns are increasingly driven by a small number of mega-cap technology stocks. While the S&P 500 remains near record highs, gold’s relative outperformance reflects continued demand for protection against concentration risk, geopolitical uncertainty and risk-off episodes – a dynamic that can persist under the current regime.

1. Balance-Sheet Normalisation, Continued Equity Strength

For years, global equities tracked the expansion of G4 central-bank balance sheets. That relationship weakened after late 2022. Balance sheets continued to normalise, yet risk assets recovered and advanced.

Forward earnings expectations stabilised. Excess liquidity remained elevated. GDP growth and labour markets proved resilient. AI-driven enthusiasm concentrated growth expectations in a narrow group of large firms, sustaining MSCI World performance, largely driven by US equities, despite tighter policy.

2. Equities in a Higher Real-Rate Regime

US real yields rose from roughly –1% in 2021 to 2.5% in 2023 before easing toward 1.8%. Historically, such a repricing would have imposed a sustained headwind for valuations. For most of 2022, it did.

The subsequent equity recovery indicates markets adjusted to a higher real-rate regime. With real yields now easing, US equities face a less demanding backdrop. To the extent the decline reflects improved inflation dynamics rather than weaker activity, it should remain supportive for valuations.

3. Credit Risk Premia Remain Contained

High-yield spreads signal no acute financial strain. Despite the sharp rate repricing since 2022, credit risk premia remain contained by historical standards. Episodes of volatility have followed geopolitical or policy headlines rather than a sustained deterioration in growth or funding conditions. Default expectations are limited, and markets are not pricing material funding stress in the near term.

4. Intra-EMU Fragmentation Risk Remains Limited

Despite French political uncertainty, QT, and tariff-related tensions, intra-EMU spreads have tightened. Wider moves have failed to gain traction. With inflation close to target and limited political disruption, the direction of travel continues to favour tighter spreads.

5. Gold’s Relative Outperformance

Gold continues to outperform relative to the S&P 500 even as indices hover near record highs. This is consistent with stretched equity valuations, debt sustainability concerns, geopolitical risk and elevated concentration in US equities. Retail flows into gold reinforce the trend.

6. Concentration in S&P 500 Returns

   

   

Source: Apollo

The top ten companies account for roughly 40% of S&P 500 market capitalisation. The Magnificent Seven have generated a disproportionate share of returns over the past year.

In such an environment, maintaining equity exposure while adding gold becomes a coherent allocation response to concentration risk and AI-bubble concerns.

7. Implications

Credit and intra-EMU spreads continue to signal stability, while expansionary fiscal policy, lower real yields and strong earnings expectations support equities. At the same time, geopolitical uncertainty, elevated concentration in the S&P 500 and persistent debate around an AI bubble sustain demand for gold. In this configuration, gold’s relative outperformance against the S&P 500 can persist.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

According to the latest Bank of Japan estimates, GDP growth is expected to reach 1.0% in 2026 and 0.8% in 2027, while core-core inflation is projected at 2.2% and 2.1% respectively. The unemployment rate continues to hover around 2.6%, underscoring persistent labour-market tightness. At the same time, the Bank of Japan is proceeding with policy normalisation—slowing JGB purchases and delivering incremental rate hikes—while Prime Minister Takaichi has pivoted decisively toward a more expansionary fiscal agenda. Recent announcements include additional spending on free education, targeted support for strategic sectors such as semiconductors and AI, a suspension of the food tax, and an increase in defence spending from 1.4% to 3% of GDP. In the snap election of 8 February, the LDP secured 316 of the 465 seats in the lower house, and 354 together with the Japan Innovation Party. The scale of the victory materially strengthens the government’s ability to implement its fiscal programme with limited parliamentary resistance.

Japanese rates have been repricing steadily over the past four years, driven by higher term premia and a slow normalisation of BoJ policy. That process has intensified more recently amid concerns over PM Takaichi’s proposed fiscal expansion. According to a study by Allianz Research, Japan’s debt-to-GDP ratio—currently around 200%—could rise to roughly 228% by 2050 if both the food-tax suspension and higher defence spending are implemented, and to over 250% if yields remain at levels implied by current forward rates. While these levels may appear elevated, Japan’s position as a net external creditor provides a medium-term stabilising channel: domestic investors can gradually rebalance away from foreign assets and towards JGBs, helping to cap upside pressure on long-end yields. That said, despite the scale of the recent sell-off, near-term risks remain skewed towards further repricing. Assuming trend growth of around 1% and inflation near 2%, a 10-year JGB yield around 3% appears broadly consistent with the macro backdrop. Additionally, given that many hedge funds have structurally short JGB basis positions (ie. long future vs cash bonds), shocks that lead to higher rates may be exacerbated by position unwinds by hedge funds. While the 30-year sector—having briefly spiked to nearly 4% before retracing to around 3.5%—should find support from real-money demand and lighter issuance, pressure in the 5- to 10-year sector is likely to intensify amid heavier supply. We may therefore see a continued flattening in 10s30s.

Turning to equities, Japanese stocks remain fundamentally supported by the expansionary fiscal stance, which is positive for earnings and supportive of domestic demand. Recent strength has been driven by robust earnings in AI-related firms and semiconductor companies, alongside renewed retail buying, pushing the Nikkei to fresh highs. From a technical perspective, however, valuations appear stretched. Much like in the US and other developed markets, Japanese equities look increasingly vulnerable to adverse geopolitical headlines. The Nikkei 225 is currently trading around 23% above its 200-day moving average. In relative, FX-adjusted terms, it has outperformed the S&P 500 by 22% and the MSCI World by 18% over the past year (See charts below). While this relative strength may appear bullish, the data suggest risks remain skewed to the downside, with recent performance more consistent with a temporary phase of relative outperformance.

On FX, while never officially acknowledged, USDJPY around 160 appears to represent a de facto intervention threshold for policymakers. The most recent episode of suspected intervention occurred on 23 January, when USDJPY fell sharply from around 159 to 153, potentially reflecting a coordinated effort between the BoJ and the Fed. From the BoJ’s perspective, as highlighted in the most recent Summary of Opinions, “the pass-through to prices of higher import prices caused by the yen’s depreciation has become more pronounced,” raising the risk that CPI disinflation slows or even reverses should the yen weaken further. A depreciating yen also feeds into higher term premia and expectations of a more aggressive normalisation path, exacerbating pressure on JGBs. From the Fed’s perspective, a sell-off in JGBs tends to spill over into US Treasuries, with most estimates suggesting that a 10bp move in JGB yields lifts UST yields by around 3bp. In addition, a weaker yen partially offsets the impact of the 15% tariffs imposed by the US on Japan last year. Taken together, these dynamics argue for USDJPY continuing to trade within a range, with the upper bound anchored around 160.

Overall, the outlook remains one of a constructive macro backdrop, ongoing but incomplete rates repricing, fundamentally supported—if stretched—equities, and a yen likely to remain range-bound.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

The geopolitical landscape has become increasingly fragile: Trump’s latest efforts to acquire Greenland risked turning into an open rupture with Europe. On January 17, Trump threatened new 10% trade tariffs “on any and all goods” on a number of European countries, including the UK, if these did not support his plans to take over Greenland. However, Trump’s actions towards Venezuela, followed by his stated intention to acquire Greenland, have deeply shaken European leaders and once more demonstrated how the threat of tariffs under the Trump administration is always looming.

The tariffs were initially set to take effect on February 1, rising to 25% from June if no deal were reached. In response, the EU has moved to reactivate measures previously put on hold after the July trade agreement, including $93 billion worth of retaliatory tariffs. The bloc could also activate its Anti-Coercion Instrument (ACI), which allows for restrictions on access to the EU market across trade in goods and services, foreign direct investment, financial markets, and property rights. While not currently intended, this remains an option of last resort.

Latest economic data point to the resilience of the US economy, with household spending increasing to 0.5% m/m (0.3% previously), while both headline and core PCE came in in line with expectations at 2.8%. Although the labour market is sending mixed signals, the overall picture suggests that the Fed’s wait-and-see policy is well calibrated. At the same time, as the Fed seeks to preserve its independence, it is unlikely to cut more than what is already projected unless strictly necessary. The December dot plot shows that the Fed is expected to cut once this year, while the market is pricing in almost two cuts. A serious threat or imposition of tariffs, leading to a tariff war with the EU, may therefore lead to a market repricing: the short end may drift higher on the back of fewer expected cuts, while the long end may come under more pressure, causing a bear steepening of the curve. The moves may be exacerbated by retail or fast money investors selling US rates aggressively, as observed in April 2025. As suggested by a recent study by the San Francisco Fed, the imposition of tariffs would initially increase unemployment and decrease inflation, acting as a brake on the demand side of the economy (see charts below). Over time, the economy adjusts: unemployment returns to its original level or even declines slightly, while inflation picks up and peaks three years after the initial change in tariffs. At a time when public borrowing is increasing at worrisome levels and the Fed needs to prove its independence by not giving in to Trump’s calls for cuts, an imposition of tariffs with EU retaliation may lead to an aggressive repricing in US rates, especially at the longer end of the curve.

The ECB finds itself in a rather different position. Headline euro area CPI stands at 1.9% (with core still at 2.3%), while unemployment is at 6.3%, near historical lows. Regarding the latest threat of tariffs, ECB President Lagarde stated that this would affect euro area inflation only minimally, given that inflation is already under control. What is more concerning for the ECB is the impact on economic activity that tariffs would bring, as Governing Council member Nagel recently noted in an interview. While the ECB is currently at a neutral rate of 2%, an imposition of US tariffs may push it to loosen its monetary policy stance in order to support growth, potentially leading to a widening in US–European rates (see chart below).

In a more extreme case of tariff escalation, the EU could consider purchasing less of, or even selling, US Treasuries in retaliation. This, if it were to happen, would be gradual, but it would imply that it becomes harder for investors to absorb an increasing supply of US government debt. As pointed out by economist Erik Nielsen, the euro area alone runs a current account surplus of EUR 400–450bn per year, a large share of which is invested in US Treasuries. Following recent episodes of geopolitical tension, there is an increasing number of European policymakers and economists suggesting that part of this surplus should be redirected from foreign investments towards domestic European markets, with a particular focus on defence. A large buyer of US Treasuries may therefore gradually scale back.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now

This publication focuses in greater detail on the US economy. While US equity valuations appear stretched from a technical perspective (see chart below), the fundamental backdrop remains supportive, underpinned by (i) a looser monetary policy stance from the Fed and (ii) strong economic growth driven by expansionary fiscal policy. This Goldilocks scenario, however, is akin to walking on thin ice. Should geopolitical risks, debt-sustainability concerns, or labour-market weakness materialise, a meaningful correction in equity markets may likely follow.

Shortly after ending quantitative tightening in November, the Fed announced on December 10 that, in order to maintain an ample supply of reserves over time, it would resume purchases of Treasury bills at a pace of USD 40bn per month until April, after which the pace will be reduced. This measure is supportive for markets, as it injects liquidity, lowers borrowing costs, and may signal reduced concern about undershooting the inflation target. Although the starting conditions differ, this episode of “technical QE” is similar in nature and scale to the programme implemented between October 2019 and March 2020, when the Fed purchased Treasury bills at a pace of USD 60bn per month to stabilise short-term funding markets (see chart below).

According to the Fed’s December projections, the US economy is expected to grow by 2.3% this year and 2.1% next year. Recent data from the Weekly Economic Index (WEI)—a composite of ten weekly economic indicators—together with services PMI data that surprised to the upside at 54.4, reinforce the narrative of a strong and resilient economy. The Congressional Budget Office estimates that 0.9% of this year’s growth will be attributable to the One Big Beautiful Bill Act (OBBBA).

A key concern, however, is the scale of additional federal borrowing implied by OBBBA, which adds pressure to Treasuries—already trading heavy—and increases rates volatility. In a paper published in November, Auerbach and Gale estimate that the debt-to-GDP ratio (defined as debt held by the public) will rise to 183% by 2054 under OBBBA as currently legislated, and to 199% if temporary tax and spending provisions are made permanent. These projections compare with a current debt-to-GDP ratio of roughly 100%, and with a pre-OBBBA CBO projection of 154% for 2054. They further estimate the fiscal gap—the permanent tax or spending adjustment required to stabilise the debt-to-GDP ratio at its current level—at approximately 3.4% of GDP if OBBBA is extended. Overall, growth generated by OBBBA appears likely to represent a short-term boost at the cost of significant long-term fiscal strain.

An additional source of concern is the growing decoupling between economic growth and a labour market that has continued to weaken. Investors had been awaiting January’s jobs report for greater clarity on labour-market conditions. The latest release, however, leaves the market broadly unchanged: monthly job creation came in below expectations (50k versus 70k), while the unemployment rate edged lower to 4.4%. Hourly earnings growth and labour-force participation were in line with expectations. Overall, the report leaves the FED in a wait-and-see position, reinforcing the view that policy is currently well calibrated.

While US equities are currently benefiting from the combination of looser monetary policy and highly expansionary fiscal policy, the equilibrium is fragile. A renewed focus on US debt sustainability, a further deterioration in labour-market conditions, and/or another escalation in geopolitical risks may likely trigger a sharp correction, pushing equity markets into a cold plunge.

If you enjoyed this article and found it insightful, subscribe for free below.

Subscribe now