On February 28, 2026, as the joint US and Israeli attack began, the numbers on the screens started moving in ways that felt clinical, even as the reality on the ground with the tragic deaths of civilian casualties in Iran, felt anything but. Markets, as they say, do not have a moral compass, rather they have a weighing machine and right now, they are weighing the transition of the entire global economy from a "just-in-time" model to a "just-in-case" cycle.

What markets were signalling

On March 2, the index tape stayed cautious while defence rose. Historically, conflicts can speed up restocking and orders but how big it gets (and how fast) still depends on budgets, approvals and delivery bottlenecks.

The Winners

1. Hanwha Aerospace (012450.KS)

Hanwha is one of the more actively traded names linked to the “K-Defence” theme, a company markets increasingly view as a scalable supplier into a tightening global artillery and munitions cycle. Capacity and delivery credibility.

When replenishment becomes urgent, the ability to produce at scale often matters as much as the platform itself. Export demand tied to systems like the K9 Thunder and Chunmoo has reinforced the narrative of durable order flow even when outcomes still hinge on budgets, approvals and delivery timelines.

Key things that can move sentiment: order-book updates, production cadence, and any follow-on export announcements.

‍2. Northrop Grumman (NOC)

Northrop moved into focus as investors repriced exposure to strategic modernisation and large, long-running programs. Defence markets often seen as mission-critical can persist across cycles. It’s less about one quarter and more about whether momentum stays steady if modernisation priorities remain in place (and whether timelines shift if they don’t).

Key variables that can move sentiment: Procurement pace, contract timing, and program-related funding language.

3. RTX Corporation (RTX)

RTX returned to the centre of the tape as investors priced an interceptor replenishment cycle and the economics of high-tempo air defence. Attrition is expensive and when usage rates rise, governments typically have to replenish inventories and, in many cases, fund production expansion which can extend backlog and lift revenue visibility.

Key variables that can move sentiment: Replenishment orders, manufacturing expansion indicators, and delivery throughput.

4. Lockheed Martin (LMT)

Lockheed drew attention as markets focused on missile-defence demand and the question every procurement desk faces in a high-tempo environment: how fast can inventories be rebuilt? If utilisation stays elevated, the winners tend to be the contractors best positioned to scale production and deliver reliably. Lockheed’s missile defence exposure keeps it closely tied to that replenishment narrative.

Key variables that can move sentiment: production ramp signals, unit economics, and budget-driven order cadence.

5. BAE Systems (BA.L)

With an £83.6 billion backlog and a central role in the AUKUS submarine program, BAE moved into focus as parts of Europe signalled higher defence spending ambitions. The stock rose 6.11% to a 52-week high amid a “risk-off” rotation, with traders watching AUKUS milestones and European air and missile defence procurement, including “Sky Shield”.

Key variables that can move sentiment: A potential catalyst is any clear step-up in German spending that lifts order flow across BAE’s European units, while key risks include a sharp spike in UK gilt yields, renewed pound sterling volatility, or “threat of peace” profit-taking.

The Losers: not every ‘war stock’ rises

6. AeroVironment (AVAV)

AeroVironment surged 18% at the open before falling 17% intraday after reports that the US Space Force was reopening a US$1.4 billion contract. The move highlights how procurement processes and contract risk can drive volatility, even in supportive thematic environments.

7. Kratos Defence (KTOS)

Kratos sits in the drone and loitering munition theme that gained attention as the Middle East conflict intensified. The stock still sold off after earnings, highlighting a common defence-sector risk. Kratos announced a large follow-on equity offering in the US$1.2 billion to US$1.4 billion range, the move strengthens the balance sheet and can support future program investment.

For traders focused on short-term “conflict premium” narratives, dilution can quickly change the setup. Even when demand conditions appear supportive, the market may reprice the stock if each shareholder ultimately owns a smaller portion of the business.

8. Intuitive Machines (LUNR)

Some speculative space-tech names lagged as investors appeared to favour companies with more established defence-linked revenue.

9. Boeing (BA)

Boeing was down around 2.5% on the session. While its defence division is meaningful, its commercial business can be more sensitive to aviation demand, airspace disruptions and oil-price moves.

10. Spirit AeroSystems (SPR)

Spirit AeroSystems remains closely tied to the global aircraft production cycle as a major aerostructures supplier. Recent results showed widening losses despite higher sales, reflecting ongoing production cost increases on major aircraft programs. These pressures have weighed on investor confidence in the near-term outlook. The planned acquisition by Boeing may ultimately reshape the company’s position in the supply chain, but execution risk and production stability remain central to how the market prices the stock.

What to watch next

• Escalation vs de-escalation: A shift toward diplomacy or ceasefire discussions can quickly change sentiment around defence stocks.
• Oil and shipping: Energy spikes can tighten financial conditions and pressure cyclical sectors.
• ‍Budgets and awards: Price moves can sometimes precede contract decisions, with clarity arriving when awards are finalised.
• ‍Production capacity: Companies with proven production and delivery track records often attract the most investor attention.
• Supply chain constraints: Rare earths, propulsion and electronics remain potential bottlenecks that can limit how quickly production scales.

The longer term lens

The 2026 Iran conflict is first and foremost a human tragedy. For markets, it may also represent a shift in how national security spending is prioritised within fiscal frameworks. If defence spending remains elevated over a multi year horizon, companies with scalable manufacturing capacity and integrated technology stacks could attract sustained investor attention. That said, markets move in cycles. Structural themes can persist, but they can also reprice quickly when assumptions change. Staying analytical and risk aware remains critical.

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^{References to specific companies, sectors or market movements are provided for general market commentary only and do not constitute a recommendation, offer or solicitation to buy or sell any financial product.Market reactions to geopolitical or macroeconomic events can be volatile and unpredictable, and outcomes may differ materially from expectations.}

2025 has seen a material decline in the fortunes of the greenback. A technical structure breakdown early in the year was followed by a breach of the 200-day moving average (MA) at the end of Q1. The index then entered correction territory, printing a three-year low at the end of Q2.

Since then, we have seen attempts to build a technical base, including a re-test of the end-of-June lows in mid-September. However, buying pressure has not been strong enough to push price back above the technically critical and psychologically important 100 level.

What the levels suggest from here

As things stand, the index remains more than 10% lower for 2025. On this technical view, the index may revisit the 96 area. However, technical levels can fail and outcomes depend on multiple factors.

US dollar index

The key question for 2026

The key question remains: are we likely to see further losses in the early part of next year and beyond, or will current support hold?

We cannot assess the US dollar in isolation and any outlook is shaped by internal and global factors, not least its relative strength versus other major currencies. Many of these drivers are interrelated, but four potential headwinds stand out for any US dollar recovery. Collectively, they may keep downside pressure in play.

Four headwinds for any US dollar recovery

1. The US dollar as a safe-haven trade

One scenario where US dollar support has historically been evident is during major global events, slowdowns and market shocks. However, the more muted response of the US dollar during risk-off episodes this year suggests a shift away from the historical norm, with fewer sustained US dollar rallies.

Instead, throughout 2025, some investors appeared to favour gold, and at other times, FX and even equities, rather than into the US dollar. If this change in behaviour persists through 2026, it could make recovery harder, even if global economic pressure builds over the year ahead.

2. US versus global trade

Trade policy is harder to measure objectively, and outcomes can be difficult to predict. That said, trade battles driven by tariffs on US imports are often viewed as an additional potential drag on the US dollar.

The impact may be twofold if additional strain is placed on the US economy through:

• a slowdown in global trade volumes as impacted countries seek alternative trade relationships, with supply chain distortions that may not favour US growth
  
• pressure on US corporate profit margins as tariffs lift costs for importers
  

3. Removal of quantitative tightening

The Fed formally halted its balance sheet reduction, quantitative tightening (QT), as of 1 December 2025, ending a program that shrank assets by roughly US$2.4 trillion since mid-2022.

Traditionally, ending QT is seen as marginally negative for the US dollar because it stops the withdrawal of liquidity, can ease global funding conditions, and may reduce the scarcity that can support dollar demand. Put simply, more dollars in the system can soften the currency’s support at the margin, although outcomes have varied historically and often depend on broader financial conditions.

4. Interest rate differential

Interest rate differential (IRD) is likely to be a primary driver of US dollar strength, or otherwise, in the months ahead. The latest FOMC meeting delivered the expected 0.25% cut, with attention on guidance for what may come next.

Even after a softer-than-expected CPI print, markets have been reluctant to price aggressive near-term easing. At the time of writing, less than a 20% chance of a January cut is priced in, and it may be March before we see the next move.

The Fed is balancing sticky inflation against a jobs market under pressure, with the headline rate back at levels last seen in 2012. The practical takeaway is that a more accommodative stance may add to downward pressure on the US dollar.

Current expectations imply around two rate cuts through 2026, with the potential for further easing beyond that, broadly consistent with the median projections shown in the chart below. These are forecasts rather than guarantees, and they can shift as economic data and policy guidance evolve.

The “Magnificent Seven” technology companies are expected to invest a combined $385 billion into AI by the end of 2025.

‍Microsoft is positioning itself as the platform leader. Nvidia dominates the underlying AI infra. Google leads in research. Meta is building open-source tech. Amazon – AI agents. Apple — on-device integration. And Tesla pioneering autonomous vehicles and robots.

With such enormous sums pouring into AI, is this a winner-take-all game?

Or will each of the Mag Seven be able to thrive in the AI future?

Microsoft: The AI Everywhere Strategy

Microsoft has made one of the biggest bets on AI out of the Mag Seven — adopting the philosophy that AI should be everywhere.

Through its deep partnership with OpenAI, of which it is a 49% shareholder, the company has integrated GPT-5 across its entire ecosystem.

‍Key initiatives:

• GPT-5 integration across consumer, enterprise, and developer tools through Microsoft 365 Copilot, GitHub Copilot, and Azure AI Foundry
• Azure AI Foundry for unified AI development platform with model router technology
• Copilot ecosystem spanning productivity, coding, and enterprise applications with real-time model selection
• $100 billion projected AI infrastructure spending for 2025

Microsoft’s centrepiece is Copilot, which can now detect whether a prompt requires advanced reasoning and route to GPT-5's deeper reasoning model.

This (theoretically) means high-quality AI outputs become invisible infrastructure rather than a skill users need to learn.

However, this all-in bet on OpenAI does come with some risks. It is putting all its eggs in OpenAI's basket, tying its future success to a single partnership.

Elon Musk warned that "OpenAI is going to eat Microsoft alive"[/caption]

Google: The Research Strategy

Google’s approach is to fund research to build the most intelligent models possible. This research-first strategy creates a pipeline from scientific discovery to commercial products — what it hopes will give it an edge in the AI race.

‍Key initiatives:

• Over 4 million developers building with Gemini 2.5 Pro and Flash
• Ironwood TPU offering 3,600 times better performance compared to Google’s first TPU
• AI search overviews reaching 2 billion monthly users across Google Search
• DeepMind breakthroughs: AlphaEvolve for algorithm discovery, Aeneas for ancient text interpretation, AlphaQubit for quantum error detection, and AI co-scientist systems

Google’s AI research branch, DeepMind, brings together two of the world's leading AI research labs — Google Brain and DeepMind — the former having invented the Transformer architecture that underpins almost all modern large language models.

The bet is that breakthrough research in areas like quantum computing, protein folding, and mathematical reasoning will translate into a competitive advantage for Google.

Today, we're introducing AlphaEarth Foundations from @GoogleDeepMind , an AI model that functions like a virtual satellite which helps scientists make informed decisions on critical issues like food security, deforestation, and water resources. AlphaEarth Foundations provides a… pic.twitter.com/L1rk2Z5DKk

— Google AI (@GoogleAI) July 30, 2025

Meta: The Open Source Strategy

Meta has made a somewhat contrarian bet in its approach to AI: giving away their tech for free. The company's Llama 4 models, including recently released Scout and Maverick, are the first natively multi-modal open-weight models available.

‍Key initiatives:

• Llama 4 Scout and Maverick - first open-weight natively multi-modal models
• AI Studio that enables the creation of hundreds of thousands of AI characters
• $65-72 billion projected AI infrastructure spending for 2025

This open-source strategy directly challenges the closed-source big players like GPT and Claude. By making AI models freely available, Meta is essentially commoditizing what competitors are trying to monetize. Meta's bet is that if AI models become commoditized, the real value will be in the infrastructure that sits on top. Meta's social platforms and massive user base give it a natural advantage if this eventuates.

Meta's recent quarter was also "the best example to date of AI having a tangible impact on revenue and earnings growth at scale," according to tech analyst Gene Munster.

However, it hasn’t been all smooth sailing for Meta. Their most anticipated release, Llama Behemoth, has all but been scrapped due to performance issues. And Meta is now rumored to be developing a closed-source Behemoth alternative, despite their open-source mantra.

Amazon: The AI Agent Strategy

Amazon’s strategy is to build the infrastructure for AI that can take actions — booking meetings, processing orders, managing workflows, and integrating with enterprise systems.

Rather than building the best AI model, Amazon has focused its efforts on becoming the platform where all AI models live.

‍Key initiatives:

• Amazon Bedrock offering 100+ foundation models from leading AI companies,  including OpenAI models.
• $100 million additional investment in AWS Generative AI Innovation Center for agentic AI development
• Amazon Bedrock AgentCore enabling deployment and scaling of AI agents with enterprise-grade security
• $118 billion projected AI infrastructure spending for 2025

The goal is to become the “orchestrator” that lets companies mix and match the best models for different tasks.

Amazon’s AgentCore will provide the underlying memory management, identity controls, and tool integration needed for these companies to deploy AI agents safely at scale.

This approach offers flexibility, but does carry some risks. Amazon is essentially positioning itself as the middleman for AI. If AI models become commoditized or if companies prefer direct relationships with AI providers, Amazon's systems could become redundant.

Nvidia: The Infra Strategy

Nvidia is the one selling the shovels for the AI gold rush. While others in the Mag Seven battle to build the best AI models and applications, Nvidia provides the fundamental computing infrastructure that makes all their efforts possible.

This hardware-first strategy means Nvidia wins regardless of which company ultimately dominates. As AI advances and models get larger, demand for Nvidia's chips only increases.

‍Key initiatives:

• Blackwell architecture achieving $11 billion in Q2 2025 revenue, the fastest product ramp in company history
• New chip roadmap: Blackwell Ultra (H2 2025), Vera Rubin (H2 2026), Rubin Ultra (H2 2027)
• Data center revenue reaching $35.6 billion in Q2, representing 91% of total company sales
• Manufacturing scale-up with 350 plants producing 1.5 million components for Blackwell chips

With an announced product roadmap of Blackwell Ultra (2025), Vera Rubin (2026), and Rubin Ultra (2027), Nvidia has created a system where the AI industry must continuously upgrade to Nvidia’s newest tech to stay competitive.

This also means that Nvidia, unlike the others in the Mag Seven, has almost no direct AI spending — it is the one selling, not buying.

However, Nvidia is not indestructible. The company recently halted its H20 chip production after the Chinese government effectively blocked the chip, which was intended as a workaround to U.S. export controls.

Apple: The On-Device Strategy

Apple's AI strategy is focused on privacy, integration, and user experience. Apple Intelligence, the AI system built into iOS, uses on-device processing and Private Cloud Compute to help ensure user data is protected when using AI.

‍Key initiatives:

• Apple Intelligence with multi-model on-device processing and Private Cloud Compute
• Enhanced Siri with natural language understanding and ChatGPT integration for complex queries
• Direct developer access to on-device foundation models, enabling offline AI capabilities
• $10-11 billion projected AI infrastructure spending for 2025

The drawback of this on-device approach is that it requires powerful hardware from the user's end.  Apple Intelligence can only run on devices with a minimum of 8GB RAM, creating a powerful upgrade cycle for Apple but excluding many existing users.

Tesla: The Robo Strategy

Tesla's AI strategy focuses on two moonshot applications: Full Self-Driving vehicles and humanoid robots.

This is the 'AI in the physical world' play. While others in the Mag Seven are focused on the digital side of AI, Tesla is building machines that use AI for physical operations.

‍Key initiatives:

• Plans for 5,000-10,000 Optimus robots in 2025, scaling to 50,000 in 2026
• Robotaxi service targeting availability to half the U.S. population by EOY 2025
• AI6 chip development with Samsung for unified training across vehicles, robots, and data centers
• $5 billion projected AI infrastructure spending for 2025

This play is exponentially harder to develop than digital AI, and the markets have reflected low confidence that Tesla can pull it off.

TSLA has been the worst-performing Mag Seven stock of 2025, down 18.37% in H1 2025.

However, if Tesla’s strategy is successful, it could be far more valuable than other AI plays. Robots and autonomous vehicles could perform actual labour worth trillions of dollars annually.

The $385 billion Question

The Mag Seven are starting to see real revenue come in from their AI investments. But they're pouring that money (and more) back into AI, betting that the boom is just getting started.

The platform players like Microsoft and Amazon are betting on becoming essential infrastructure. Nvidia’s play is to sell the underlying hardware to everyone. Google and Meta compete on capability and access. While Apple and Tesla target specific use cases.

The $385 billion question is which of the Magnificent Seven has bet the right way? Or will a new player rise and usurp the long-standing tech giants altogether?

‍You can access all Magnificent Seven stocks and thousands of other Share CFDs on GO Markets.