What moved the ASX 200 in 2025?

In 2025, the ASX 200 closed around 8,621 points and was up approximately 6% year to date (YTD) as of 19 December close. Market direction was most sensitive to Reserve Bank of Australia (RBA) expectations, commodity prices and China-linked demand, and (to a lesser extent) moves in the Australian dollar (AUD). The index recovered from November’s pullback, but remained below October’s record close.

Key 2025 drivers included:

• RBA policy expectations: Sentiment was shaped by shifting views on the timing and extent of rate moves. The November pullback reflected repricing towards a longer pause and higher uncertainty around whether the next move could be a hike rather than a cut, particularly as jobs and inflation data surprised.
• Resources and China sensitivity: With a meaningful resources weight, the index responded to iron ore stability, strong gold prices and relative firmness in base metals. China data and any perceived policy support (including signals from the People’s Bank of China (PBOC)) remained important for the export backdrop. A relatively stable AUD also reduced currency-related noise for exporters.
• Index composition and market structure: The ASX 200’s heavier tilt to materials and banks, and lower exposure to high-growth technology, meant it often lagged tech-led global rallies, but tended to hold up better when AI and growth valuations were questioned.
• Corporate earnings: Reporting season outcomes influenced valuation support. In September’s half-year reporting season, around 33% of ASX 200 companies beat expectations, which helped underpin pricing around current levels.

Current state

The ASX 200 was roughly 5% below its late-October record high close of 9,094 points. After the November retracement, support around 8,400 appeared to hold and buying interest improved. The 50-day EMA near 8,730 (a prior consolidation area) was a commonly watched near-term reference, noting technical indicators can be unreliable.

What to watch in January

• China and commodity demand: Growth, trade and any fresh stimulus inference from the PBOC may affect sentiment.
• Domestic inflation and labour data: CPI and jobs prints are key inputs into RBA expectations.
• Key levels and follow-through: The post-November rebound may need continued demand to sustain momentum.

What moved the Nikkei 225 in 2025?

In 2025, the Nikkei 225 traded around 39,200 points and was up approximately 21% year to date (YTD). Market direction was most sensitive to moves in the Japanese yen (JPY) and Bank of Japan (BOJ) communication, with the index consolidating after multi-decade highs. While broader signals remained constructive, consolidation can resolve either higher or lower.

Key influences included:

• JPY movements and earnings translation: A weaker JPY can boost the reported value of overseas earnings for some exporters, although it may also increase input and import costs. The net impact often depends on company hedging practices and varies by sector, with effects most evident in export-heavy industries such as automotive, industrials and parts of technology manufacturing.
• Gradual BOJ policy transition: The BOJ continued to step away from ultra-easy settings, but tightening was generally cautious. Markets largely priced a slow, conditional normalisation, which helped limit downside, even as policy headlines created bouts of volatility.
• Corporate governance reforms: Ongoing improvements in capital efficiency and shareholder returns supported interest from overseas investors. Share buybacks, stronger balance-sheet discipline and improved return on equity (ROE) contributed to re-rating in parts of the market.
• Global cyclical exposure: The Nikkei moved with shifts in global manufacturing sentiment and expectations for US growth, particularly during risk-on phases associated with AI-related capital spending.

Current state

After pushing to multi-decade highs earlier in the year, the Nikkei spent time consolidating but has remained structurally strong. Price sits above key long-term moving averages, and some technicians watch the 50-day exponential moving average (EMA) as a potential reference level (noting these indicators can be unreliable). Currency swings and shifting BOJ expectations were commonly cited as contributors to much of the second-half volatility, although pullbacks were generally met with buying interest.

What to watch in January for Japan

• JPY volatility: Sharper yen moves, especially if driven by BOJ or Federal Reserve expectations, could quickly change exporter earnings assumptions.
• BOJ communication: Small changes in language on inflation persistence or bond market operations may move sentiment.
• Global growth data: US and China manufacturing and trade prints remain key inputs for an externally focused economy.

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?

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