Wall Street’s Red Queen problem
“It takes all the running you can do, to keep in the same place.” – The Red Queen; Through the Looking-Glass
Into the mirror
Lewis Carroll’s Through the Looking-Glass imagined a world in which familiar rules ran in reverse. This problem is now increasingly confronting Wall Street—not only in how it reads monetary policy, but in how it reads the equity market itself. The Red Queen’s paradox is an apt description of the present economy. Policymakers raise rates to cool demand but enlarge sovereign interest costs; companies invest heavily just to preserve a widening productivity gap; and countries burdened by debt must grow faster merely to keep fiscal arithmetic from worsening.
In a debt-heavy, technology-intensive economy, investors may have to run faster simply to understand where they stand.
“It takes all the running you can do, to keep in the same place.”
Lewis Carroll’s Red Queen was describing a fantastical world in Through the Looking-Glass. But she might have been describing the 2026 U.S. economy. America has gone down the rabbit hole. Wall Street is peering into the mirror, and the Red Queen has become the central economic constraint.
The old order was built on familiar assumptions. Cheap money encouraged borrowing. Globalisation kept costs low. Capital expenditure was often treated as a drag on shareholder returns. Growth came disproportionately from consumption, leverage and financial engineering. Investors learned to watch the U.S. Federal Reserve, scrutinise liquidity and assume that higher rates would cool inflation, lower real rates would support asset prices, and a late-cycle equity rally was probably speculative excess.
Those assumptions were not irrational. They were calibrated to the world that emerged after the 2008 Global Financial Crisis: an economy of low inflation, low productivity, weak investment and extraordinary central-bank influence.
But that world is fading.
The U.S. now faces a different combination of forces: high public debt, persistent fiscal deficits, strategic competition with China, energy-security demands, ageing infrastructure, fragile supply chains and a vast technological investment cycle centred on artificial intelligence (AI). The economy is no longer shaped solely by monetary policy. It is reshaped by the interaction between fiscal pressure, industrial policy and private-sector capital expenditure. Wall Street’s error is not that it has forgotten economics. It is that it is using yesterday’s economics to interpret a new regime.
The rabbit hole
The rabbit hole is the transition itself.
For most of the past two decades, the U.S. economy relied on an implicit bargain. Consumers borrowed and spent. Companies minimised fixed investment, outsourced production and returned cash through buybacks. The Federal Reserve suppressed the cost of capital whenever demand faltered. Global supply chains delivered cheap goods, and the U.S. dollar’s reserve currency status helped finance the system.
That model delivered asset-price gains, but it did not solve the underlying problem of weak productive capacity. America could consume more without necessarily building more. It could borrow more without necessarily investing more. It could outsource strategic dependencies without fully considering their geopolitical cost.
The shocks of the past several years exposed the limits of that arrangement. Pandemic disruption, energy dislocation, shortages in housing and critical inputs, geopolitical conflict and rivalry with China all demonstrated that an economy cannot be managed indefinitely as if production capacity were an afterthought.
The policy response now associated with the U.S. President Donald Trump administration’s America First agenda is an attempt to reverse that logic. Its aim is not merely to run the economy hotter through fiscal demand. It is to make the economy more productive and strategically self-sufficient: more energy production, more domestic manufacturing, more infrastructure, more investment in advanced technology and more resilient supply chains.
This is a supply-side programme in a world where supply has become a strategic variable.
Its critics are right to point to the risks. Tariffs can raise prices. Deficits can pressure bond markets. A tight labour market can reinforce wage inflation. Industrial policy can misallocate capital. Government support can become an excuse for cronyism.
But those objections do not settle the matter. The essential question is whether America can expand its productive capacity fast enough to offset the inflationary and fiscal pressures that accompany the transition.
If energy output rises, permitting becomes easier, capital investment is expensed more generously and technological diffusion improves productivity; then stronger growth need not produce the same inflationary result as a transfer-fuelled consumption boom.
That is the wager.
The looking glass
The looking glass is the way markets misread that wager.
Investors remain conditioned by former U.S. Federal Reserve chairs Paul Volcker and Ben Bernanke, and the post 2008 eras. They expect a stable mechanical relationship between policy rates, inflation and asset prices. Higher real yields should hurt gold. Tighter monetary policy should reduce inflation. Faster growth should raise the risk of overheating. Higher equity prices should imply elevated valuations and an eventual reversion.
In a lower-debt, bank-centred economy, those relationships worked tolerably well.
But a rate increase now has contradictory effects. It restrains new borrowing, raises hurdle rates for investment and slows rate-sensitive sectors. Yet it also raises the government’s interest bill, enlarges deficits and transfers income to households and institutions that own public debt.
In other words, higher rates do not mean one thing.
They can weaken housing construction while increasing fiscal outlays. They can slow marginal credit formation while raising income for Treasury securities holders. They can cool demand in one part of the economy while creating a new source of spending power in another.
This is the practical meaning of fiscal dominance. It does not mean central banks have ceased to matter. It means monetary policy operates in a world where public debt is large enough to change its effects—and where the political costs of sustained high rates rise rapidly.
Higher borrowing costs cannot manufacture houses, construct transmission lines, expand power generation, produce skilled workers or rebuild supply chains. In fact, they may delay the very investment needed to relieve the supply constraints behind inflation.
That is why the old reflexive formulation—high rates are disinflationary, low rates are inflationary—is becoming inadequate. It confuses a financial variable with the full productive capacity of an economy.
Even the persistence of gold at positive real yields should be read through this lens. It is less a repudiation of monetary theory than a sign that markets are concerned about sovereign balance sheets, future debt management and the choices governments may eventually make between austerity, inflation and managed interest rates.
But gold is only a symptom. The more consequential development is the reorganisation of the real economy around investment.
The Red Queen economy
The Red Queen explains why this investment cycle has a different character from earlier ones.
In Carroll’s world, running is necessary just to remain in place. In today’s economy, countries and companies must invest merely to avoid losing ground.
The U.S. must grow fast enough to prevent debt-service costs from consuming its fiscal capacity. It must build enough energy and computing infrastructure to remain competitive in AI. It must rebuild industrial capacity to reduce strategic dependence on geopolitical rivals. It must raise productivity quick enough to preserve living standards despite demographic and fiscal pressure.
Companies face an analogous challenge. The first firms to master large-scale AI deployment can lower costs, increase output, improve customer service and accelerate product development. Their competitors cannot simply wait for the technology cycle to end. They must invest, adapt or accept a widening productivity gap.
That dynamic makes the present capital-expenditure boom unusually powerful.
AI is often discussed as a speculative narrative, but it is more fundamentally a capital cycle. It requires chips, data centres, electricity generation, cooling systems, grid upgrades, networking equipment, industrial automation and enterprise software. The visible spending on computing hardware is only the front end of a much broader effort to rebuild the production function.
Much of this spending is not discretionary. It is defensive.
A company that refuses to invest because returns are uncertain may preserve near-term free cash flow. But it may also surrender future margins, market share and relevance. In the Red Queen economy, prudence can become a form of stagnation.
This is why the old market preference for asset-light business models and minimal capital expenditure may prove increasingly obsolete. For years, investors rewarded management teams for buybacks, lean balance sheets and low fixed investment. Capex was often viewed as an admission that a business had weak cash conversion or insufficient discipline.
That is a poor framework for an economy rebuilding its technological and industrial foundations.
Some AI investments will fail. Some data-centre capacity will be excessive. Some projects will generate poor returns. But the existence of waste does not invalidate the larger cycle. Every great capital boom—railways, electrification, automobiles, telecoms and the internet—produced overbuilding alongside real transformation.
The relevant question is not whether there will be errors. There will be. It is whether the surviving infrastructure creates a more productive economy and a larger earnings base.
An earnings argument
That brings the equity market into focus.
The prevailing bearish argument treats strong U.S. equity performance as evidence of a liquidity bubble, particularly in technology. There are undoubtedly pockets of excess. Markets rarely price transformative technologies with perfect restraint. But it is a mistake to interpret the entire advance as multiple expansion or speculative enthusiasm.
The more useful framework is structural earnings growth.
The post-2008 era was characterised by weak productivity, low capital intensity and financial engineering. Equity returns depended heavily on falling discount rates, margin preservation and share repurchases. When rates fell, price-to-earnings multiples could rise. When liquidity expanded, asset prices responded.
The emerging regime is different. It rests on a potentially stronger investment base, policy incentives for domestic production and the prospect that technological adoption will eventually raise output per worker.
Full expensing is central to this story. Allowing businesses to deduct the full cost of investment immediately lowers the effective cost of capital and changes corporate decision-making. Projects once deferred because depreciation schedules made their economics unattractive can be brought forward. Investment becomes more immediate, more scalable and more likely to occur in the U.S.
This matters across sectors. It supports advanced manufacturing, energy infrastructure, logistics, communications equipment and enterprise technology—not merely a narrow cluster of technology companies.
The political logic also matters. The U.S. has chosen, implicitly if not always coherently, to prefer growth over fiscal restraint. It is running large deficits outside recession because neither party has embraced a politically credible path to austerity. In such circumstances, the best route to debt sustainability is not simply smaller government borrowing. It is a larger economic denominator: stronger nominal growth, a wider tax base and rising corporate profits.
That strategy is risky. It could fail if deficits rise faster than output, if inflation becomes embedded or if bond investors lose confidence in the trajectory of public finances. But it is not irrational. The alternative— accepting low growth while debt-service costs compound—is not obviously safer.
For equity investors, the implication is straightforward. If earnings are growing faster than consensus expects, static valuation measures will understate the market’s potential. A market can look expensive on trailing earnings even as its future earnings capacity improves.
The case for an S&P 500 at 10,000 by 2027 rests on that premise. It would require earnings approaching US$440 and a valuation multiple near 23 times. That is an ambitious scenario. It depends on sustained capital investment, resilient margins, policy stability and a meaningful conversion of AI spending into productivity.
It should not be treated as a prediction. But it is not fantasy either.
History shows that periods of genuine productivity acceleration can support elevated multiples because investors are paying for a larger, more durable stream of profits. The late 1990s were not merely a story of internet speculation; they were also the culmination of decades of investment in computing, communications and organisational change.
The present cycle may have similar features, with one crucial difference: this time the investment is being explicitly reinforced by strategic competition, energy constraints and industrial policy.
The harder second act
The next phase will be more difficult than the first.
The initial AI trade rewarded scarcity—the suppliers of advanced chips, computing infrastructure and datacentre capacity. The market could price a simple story: demand was intense, supply was limited and earnings estimates were rising rapidly.
The second act is more complicated. Capital spending will remain high, but its growth rate may moderate as the first wave of infrastructure reaches scale. Investors will care less about whether a company has “AI exposure” and more about whether it can convert AI into recurring revenues, lower operating costs and defensible margins.
The winners will be businesses with proprietary data, strong distribution, switching costs, customer trust and deep integration into enterprise workflows. The key bottleneck is no longer only technical capability. It is organizational adoption.
AI can perform many economically valuable tasks. But deploying it across a large company involves compliance, procurement, workflow redesign, employee training and managerial judgement. Productivity is not automatic. It depends on institutions and incentives.
That should make the market more selective, not necessarily more bearish.
A maturing investment cycle separates suppliers of the initial buildout from companies that can monetise the infrastructure. That is healthy. It is the point at which a narrative becomes an earnings cycle.
The race ahead
None of this removes the risks.
Bond markets could revolt against fiscal excess. Inflation could prove more persistent than supply-side optimists expect. Tariffs could do more harm than good. Energy or grid constraints could limit AI deployment. Geopolitical shocks could interrupt trade, investment and confidence. And Washington could mistake a necessary industrial strategy for a license for permanent intervention.
But the greater analytical risk may be assuming that every development must fit the old model.
The old world treated strong growth as an inflation problem, capex as a drag and high rates as a simple cure. The new world is more paradoxical. High rates may exacerbate fiscal strain. Investment may be the means of easing supply constraints. Strong equities may reflect an expanding earnings base rather than a fragile liquidity bubble.
The rabbit hole is the transition from financial stagnation to an economy built around production and investment. The looking glass is Wall Street’s difficulty in recognising that the rules have changed. The Red Queen is the unforgiving reality that countries and companies must run faster simply to avoid falling behind.
America’s challenge is not merely to spend more or grow faster. It is to turn the current investment surge into durable productivity before debt costs, geopolitical competition and institutional inertia close the window.
Wall Street’s challenge is to stop mistaking a changing economic regime for a familiar late-cycle excess.
The mirror has turned. The only question is whether investors can see it before the race has moved on.