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Foresight Signals
Economics × Management Theory Weekly

Jul 12 – Jul 18, 2026

English translation of the Korean original, prepared with AI assistance. Korean original

Not investment advice — these are resources for learning and forming your own view.

The single tension running through this week’s markets is whether monetary policy can do anything when supply shocks are hitting on several fronts at once. On the macro side, the US and Iran exchanged actual airstrikes around the Strait of Hormuz, and oil jumped to a one-month high. Even as Trump proposed and then withdrew a 20% toll on cargo through the strait, the market quickly priced a supply-disruption risk premium into oil. This shock came not from rising demand but from blocked production and supply. However hawkish new Fed Chair Warsh’s Senate testimony and the July rate decision may be, they are not enough to suppress supply-side inflation, and that reality is unsettling market participants. On the growth side, AI semiconductor stocks held strong gains through volatility and led big tech portfolios. But IBM plunged 25% in the wake of the shift in AI spending, and analysis suggested that ‘AI rebranding’ does not lead to sustained valuation gains. That put the gap between crowded growth expectations and actual cash flow back under scrutiny. Political uncertainty layered on top of both. The death of Senator Lindsey Graham, the Democrats’ failed strategy in Maine and Trump’s pressure on companies to cut prices all lowered policy predictability at once. In short, supply shocks, policy uncertainty and a re-examination of AI valuations collided this week. Next week, watch the Fed’s July rate decision meeting and the course of the Iran negotiations.

Deep dive — one theory Economics

Why Rates Cannot Solve the Hormuz Shock: The Middle East Energy Crisis Through an Aggregate Demand and Aggregate Supply Lens

Theory
Aggregate Demand - Aggregate Supply (AD-AS)
Origin
No single proposer. The concept of aggregate demand has its roots in Keynes's General Theory (1936), and it later became the framework of standard macroeconomics textbooks.
In short
A country's output and price level are determined together where the force of buying (aggregate demand) meets the force of producing and selling (aggregate supply), so which side a shock comes from completely changes the outcome. If a boom comes from stronger buying, output and prices rise together. If a shock comes from blocked production, as with war or an oil price surge, output falls while prices actually rise. This uncomfortable combination, in which economic activity and prices move in opposite directions, is stagflation.
Limits
However, this picture holds only over the short run. Once enough time has passed for prices and wages to adjust fully, output is ultimately set by what the country can actually produce, and the force of buying only pushes up prices. It is also worth remembering that the scale is too coarse for examining the circumstances of individual industries or firms.

The aggregate demand and aggregate supply framework is especially useful now because it asks first which side the shock came from. Whether the Fed raises or cuts rates, its tools can only pull or push the force of buying (aggregate demand), so they are structurally limited against a shock caused by blocked production. When an oil price surge stokes inflation and the central bank raises rates, the economy sinks further while supply stays blocked. The pain is doubled and no remedy works. The 1970s oil shocks followed exactly this path, which is why the market is now recalling that memory.

This week's situation, with the US carrying out actual airstrikes on Iran and the safety of passage through the Strait of Hormuz in doubt, is a textbook supply-side shock. As the risk of blocking a strait that carries about 20% of the world's oil shipments became real, Brent crude jumped to a one-month high. That price rise came not from rising demand but from a threatened supply route. In this phase, the aggregate supply curve shifts left, so output falls and prices rise, producing stagflationary pressure at the same time. Whatever signal new Fed Chair Warsh sends, the July rate decision alone can hardly relieve that pressure. If oil re-enters the inflation channel, consumer purchasing power is squeezed further, and higher business costs weigh on investment as well. The result is a double layer of downward pressure on the economy.

Fellow alumni should take away one generalization from this lens. If you chase central bank signals without first checking whether the shock originates in demand or supply, your portfolio response can point in entirely the wrong direction. When supply-side shocks dominate, a rate hike hits growth stocks while energy and real assets actually strengthen, a reversal in cross-asset correlations. It is worth remembering that this is a moment to rebuild the logic of sector allocation itself.

Source story: US launches another round of strikes on Iran as ceasefire teeters

Cases by layer 6

Macro environment · Monetary Policy Transmission Mechanism

Warsh and US Inflation Will Set Tone for July Fed Decision

Newly installed Fed Chair Kevin Warsh appeared before the Senate Banking Committee and gave formal testimony on the current economic situation and the direction of interest rates. The market is trying to pick up clues to the July rate decision and forward guidance on future monetary policy from this testimony. It came right after oil prices surged on the Iran-related geopolitical shock, so market attention is especially high.

Monetary policy transmission theory applies to this scene because expectations of a change in the policy rate move market rates and exchange rates before an actual rate hike does. When a single line of Warsh's testimony moves long-term Treasury yields and the dollar index at once, that is the first stage of the transmission channel, the moment the expectations channel opens. This week also comes right after oil surged on Strait of Hormuz tensions. During the lag before the policy rate reaches the real economy, supply-side inflation pressure builds up in the economy first.

This news is usually read as an event about what the Fed chair said. Through the transmission lens, though, the more important question is how far that channel is open right now. Inflation caused by an oil surge cannot be contained by suppressing demand. Raising rates only adds to the real burden on consumers and businesses without resolving the supply chain disruption, and that is what this theory reveals. However forceful Warsh's remarks are, the fact that the transmission channel works only half as well against a supply shock is the real root of this week's market uncertainty.

Through this lens, the crux of Warsh's testimony is not the level of interest rates but which channel the Fed will lean on during a supply shock. If a hawkish signal comes, long-term Treasury yields rise and growth stock valuations are cut. Supply-side inflation remains, however, and keeps squeezing corporate costs, so two headwinds blow at once. In this phase, where the transmission channel is only half open, a reversal in cross-asset correlations is likely, with bonds, growth stocks and the energy sector each moving in a different direction.

Takeaway — When running a portfolio, before predicting the direction of interest rates from Fed signals alone, you need a habit of first checking whether the transmission channel can reach the real economy given the nature of the current shock. In a phase dominated by supply shocks, a rate hike cannot stop energy and real assets from strengthening and only pushes growth stocks down further, producing an asymmetric result.

Bloomberg Markets

Macro environment · Comparative Advantage

The Mother of All Economic Shocks Is Chinese Mercantilism

A Bloomberg Opinion piece argued that China's excessive state-led industrial policy and overcapacity are delivering a structural shock to global markets and undermining the principle of fair competition. Chinese manufacturers sustained by state subsidies are exporting below cost, and the comparative advantage of other countries' industries is being artificially reversed.

Comparative advantage theory fits this article because the theory assumes that trade benefits both sides when the opportunity cost of production differs across parties. But when China lowers its opportunity cost artificially through state subsidies, other countries lose comparative advantage even in goods they can actually produce better. Ricardo's premise, that the gains from trade come from what is given up, does not hold in the face of subsidies. The global division of labor designed around comparative advantage is therefore shaken to its roots.

This news is usually read as a political clash in the US-China trade conflict. Through the comparative advantage lens, a more fundamental problem appears. As the subsidy race intensifies, the logic of division of labor, in which each country concentrates resources on fields where it is truly competitive, breaks down. Resources worldwide come to flow toward less efficient uses, and that pattern hardens. Since the whole pie ends up shrinking, this is not a simple bilateral conflict but the larger problem of lost efficiency in the global division of labor.

Through this lens, the real danger of Chinese mercantilism is not any one country's deficit. It is the chain reaction as the logic of resource allocation by comparative advantage is neutralized and countries are drawn into a race of subsidies and tariffs to protect industries in which they have no real competitiveness. Support for Intel (article 15) and the gallium production project (article 74), where the US and its allies pour industrial subsidies into critical minerals and semiconductors, can be read in the same context.

Takeaway — When viewing supply chain restructuring as an investment opportunity, looking only at which country production moves to is not enough. To judge long-term profitability properly, you also need to look at where real comparative advantage remains once the subsidy race ends.

Project Syndicate

Industry · Theory of Constraints (TOC)

A New Foe Has Emerged for Data Centers: Farmers

Reports emerged that the expansion of AI data centers is eating into farmland and that their heavy water consumption is causing severe water shortages in nearby farming areas. Food security and AI infrastructure growth are colliding over the same water resources, and regulatory risk for data centers is coming to the fore.

The Theory of Constraints fits this article because the output of the whole system of AI infrastructure expansion is converging on the availability of a single resource: water. Data centers need large volumes of water for cooling. Drawing that water at the same time from the middle of farming areas chokes the upstream system, agriculture, first, and the effects then spread to food prices and local backlash. However much chips and power are added, if the water bottleneck is not resolved, the output of the whole system stops at the level that bottleneck allows.

This news is usually read as an environmental regulation risk or an ESG issue. Through the Theory of Constraints lens, though, there is a more practical message: investing more in anything other than the bottleneck does not raise total output. Big tech is pouring tens of billions of dollars of data center capex into the sector. But if the physical bottlenecks of water and power are not resolved, all of that investment may deliver only half its value. That is what this lens reveals.

Through this lens, the real bottleneck in AI infrastructure investment is not chip supply or the power grid but securing cooling water and selecting sites. New York State's discussion of a data center pause (article 96) and this farm water conflict are two faces of the same bottleneck. If regulators begin to shut this bottleneck, the pace at which tens of billions of dollars of capex convert into operating capacity slows sharply.

Takeaway — When investing in AI infrastructure companies, look beyond chip and server makers' order volumes. Check also their ability to clear the physical bottlenecks of site permits, access to water rights and power grid connections. That gives a more accurate sense of when returns will actually be realized.

WSJ Markets

Industry · Game Theory

Banks’ Record Bond Short Sparks Quest for Answers

Reports emerged that major global banks are building record bond short positions. These are bets that interest rates will rise or bond prices will fall, which means selling pressure is building directly in the bond market.

Game theory fits this situation because each bank makes its own short-selling decision while estimating the positions of other institutions, and the collective result feeds back directly into bond market prices. The participants are a small number of large global banks, and each one's position choice immediately affects the others' returns through market prices. The 'best choice' of each individual bank, aggregated, is converging on a Nash equilibrium path that amplifies selling pressure across the market.

This news is usually read as a directional bet that banks expect interest rates to rise. Through the game theory lens, though, a more unsettling picture appears. Each bank may be acting on a logic of preemption, feeling it must take its position before the others build large short positions first. In that case, speculation about rivals' moves, not the actual rate outlook, becomes the main driver of position building. Bond market volatility then amplifies in a self-fulfilling way, regardless of fundamental valuation, and an unstable equilibrium forms.

Through this lens, today's record bond short selling may not reflect unusually strong conviction among banks about the rate outlook. It may instead be the product of a strategic race for preemption in which banks watch each other's positions. As a result, bond prices fall faster than fundamentals warrant. An unstable structure is building in which, once one side starts to unwind its position, a sharp reversal in the opposite direction could follow.

Takeaway — When adjusting the duration of a bond portfolio, it is dangerous to read the size of banks' short positions only as a directional signal. You also need to consider the nonlinear risk that those positions could be sharply unwound when the Nash equilibrium breaks down.

Bloomberg Markets

Company · Signaling Theory

How AI rebrands fail to deliver a lasting share price boost

An analysis by the Financial Times found that many companies that pivoted their business to AI-related themes or changed their names failed to achieve sustained share price gains. The key point is that the boost to the share price was short-lived and the valuations did not hold over the long term.

Signaling theory fits this article precisely because AI rebranding fails the key condition of a signal: that it be sufficiently costly. For a signal to be credible, it must be more expensive for imitators. Changing a company name or adding AI to investor relations materials is a low-cost action that even companies with no real AI capability can easily take. There is no 'cost difference' that would let the market tell genuine AI transformation companies from those that merely changed their names, so the signal had limited force from the start.

This news is usually read as an 'AI bubble warning' or a 'trap of thematic investing'. Through the signaling theory lens, though, a more structural problem appears. The market is fooled in the short term only while the cost of verifying a signal is high. When earnings seasons repeat and actual AI revenue and margins are disclosed, the truth of the signal comes out and the share price returns to where it was. This is the process by which the market eventually separates 'costly signals' from 'cheap talk'.

Through this lens, the group of AI-rebranded stocks will face a 'signal verification' event each earnings season, and the pattern of share price corrections will repeat. By contrast, companies with a high share of real AI revenue, which have built up costly signals that are hard to imitate, such as R&D investment and talent acquisition, have grounds for their valuation premium to persist.

Takeaway — When selecting AI-themed stocks, use as your criterion not how much a company says it is AI but whether it has hard-to-imitate costly signals backing the claim, such as R&D, patents and real AI-based revenue. That is how to avoid the rebranding trap.

Financial Times

Company · Disruptive Innovation

IBM shares plunge 25% as customers shift spending to AI

IBM's share price plunged 25% in a single day. The cause was that customers cut existing server and storage spending and concentrated their budgets on building AI infrastructure, which hit revenue in IBM's traditional IT solutions division directly.

Disruptive innovation theory fits IBM's situation because AI startups and cloud-native players, though not yet fully on par with IBM on traditional enterprise IT performance metrics, are quickly drawing IBM's mainstay customers along other axes: cost, flexibility and scalability. For decades IBM offered products and services optimized for large, high-margin enterprise customers, and it faithfully did what those customers wanted. It therefore had little incentive to move down first into the low-priced, new-technology corner of AI infrastructure. Christensen's paradox worked exactly as described.

This news is usually read as a story of management failure, with IBM falling behind in the AI transition. Through the disruptive innovation lens, though, the more important point is that IBM was not foolish. This outcome followed from rationally serving the demands of its most profitable customers. This is not IBM's problem alone. It is a structural vulnerability shared by every legacy IT company optimized for high-margin mainstream customers.

Through this lens, IBM's 25% plunge is not a one-off earnings shock. It signals that the mainstream customer base is leaving for AI infrastructure much faster than expected. Legacy IT, ERP and data management vendors in the same structural position also face the risk of similar earnings shocks. If AI-native competitors' performance is already improving faster than mainstream customers' demands are rising, the defection accelerates.

Takeaway — When reviewing an enterprise software portfolio, the first gate to avoid a repeat of IBM's case is to check, in earnings materials, whether the company's core customers are shifting budgets toward AI infrastructure and whether management is disclosing the pace of that shift candidly.

Financial Times

Other signals this week 18

Macro environment
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