The US Dollar Index (DXY) is a popular tool used by forex traders to assess the value of the US dollar relative to a basket of other major currencies. The DXY is calculated using the weighted average of six major currencies: the euro, yen, pound sterling, Canadian dollar, Swedish krona, and Swiss franc. To use the DXY to trade forex, you can follow these steps: 1.
Monitor the DXY: Keep an eye on the movements of the DXY to get a sense of the overall strength or weakness of the US dollar. You can use technical analysis tools, such as moving averages or trend lines, to identify the direction of the trend. 2. Analyse currency pairs Look for forex pairs that are inversely correlated to the DXY.
This means that when the DXY goes up, the currency pair goes down, and vice versa. For example, the EUR/USD pair is negatively correlated to the DXY, which means that as the DXY goes up, the EUR/USD pair goes down. Plan your trades Once you have identified a currency pair that is inversely correlated to the DXY, you can plan your trades accordingly.
For example, if the DXY is showing signs of weakness, you may want to consider going long on a negatively correlated currency pair, such as the EUR/USD. Manage your risk As with any trading strategy, it's important to manage your risk when using the DXY to trade forex. Make sure to use stop-loss orders to limit your losses in case the market moves against you.
Currency pairs may be influenced by other factors besides the DXY, which may not be a perfect indicator of the US dollar's value. To make informed trading decisions, it is important to combine the DXY with other technical and fundamental analysis tools.
By
Mark Nguyen
Account Manager
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If you have been following the tech story for the last decade, you have been trained to look at a very specific, very small patch of real estate in Northern California. But as we sit here in early 2026, the "connect-the-dots" moment for investors is this: the AI trade has stopped being about shiny software demos in Palo Alto and has started being about the physical industrialisation of compute.
We have entered the "Year of Proof". The world’s largest companies, the hyperscalers, are projected to spend a staggering US$650 billion on capital expenditures this year. But here’s the part most people miss: that money is not staying in Silicon Valley. It’s flowing to the "picks and shovels" players in Idaho, Washington, Colorado and even overseas.
If you want to understand where the actual return on investment (ROI) may be landing this earnings season, you have to look outside the 650 area code. The shift from AI hype to AI industrialisation is changing the map.
The full AI stack: from capex to consulting — GO Markets
Five companies · AI infrastructure play · 2026
The full AI stack: from capex to consulting
Infrastructure builders compared to the implementation bridge across the AI value chain
Note: Hyperscalers shown as 2026 CapEx spend. Accenture shown as cumulative advanced AI bookings ($11.5B through Q1 FY2026), reflecting its role as the adoption layer rather than the infrastructure layer.
Infrastructure (2026 CapEx projected)Implementation bridge (cumulative AI bookings)
Hyperscaler CapEx: Early 2026 analyst estimates, midpoint of ranges. Amazon approx. 100% YoY, Alphabet approx. 100%, Meta approx. 87%, Microsoft approx. 50%.
Accenture: Cumulative advanced AI bookings $11.5B through Q1 FY2026. Q1 AI bookings $2.2B (up 76% YoY), AI revenue $1.1B (up 120% YoY) across 1,300+ clients.
Five companies shaping the next phase of AI
Micron Technology (MU), Boise, Idaho
Micron is the "memory backbone" of the current cycle. While everyone was watching the chip designers, many overlooked the fact that AI chips are far less useful without high-bandwidth memory (HBM). Micron is currently viewed by some analysts as a strong buy because its capacity is reportedly sold out through the end of 2026. Analysts are also eyeing a 457% jump in earnings per share (EPS) as the memory cycle reaches what some describe as a robust peak.
Microsoft (MSFT), Redmond, Washington
Microsoft is the enterprise backbone of this transition. It has moved beyond simple chatbots and is now building what analysts call "Intelligence Factories". While the stock has faced pressure recently over capacity constraints, underlying demand for Azure AI is reportedly still running ahead of capacity. The broader bull case is that Microsoft is moving into "Agentic AI", systems that do not just talk to users but may also execute multi-step business workflows.
Amazon is playing a long-term game of vertical integration. To reduce its reliance on expensive third-party hardware, it’s building its own AI chips in-house. Amazon Web Services (AWS) remains the primary driver of profitability, and the company is using its retail data to train specialised models that many Silicon Valley start-ups may struggle to replicate.
Palantir Technologies (PLTR), Denver, Colorado
If Micron provides the memory and Microsoft the platform, Palantir provides the "operating system" for the modern AI factory. The company has posted strong momentum, with US commercial sales recently growing 93% year over year. It’s often framed as a bridge between raw data and corporate profitability, which remains a key focus for investors in 2026.
Accenture (ACN), Dublin, Ireland
You cannot just "plug in" AI. Businesses often need to redesign processes around it, and that’s where Accenture comes in.
The company is viewed as an implementation bridge, with one analyst arguing that "GenAI needs Accenture" to move from pilot programs to production though the cautionary angle is that the AI story has not fully excited investors here yet because consulting revenue can take longer to show up than chip sales.
What could happen next?
The chart maps the three time horizons likely to shape the next phase of the AI industrialisation trade.
In the near term, markets are still reacting to chipmaker earnings, guidance, and any signs of capacity strain. Over the next month, attention shifts to the real-world inputs behind AI growth, especially power, financing, and infrastructure. By the 60-day window, the key question is whether AI spending is broadening into a wider market re-rating or running ahead of near-term returns.
Across all three periods, the focus is the same: proof. Investors are looking for signs that AI capital expenditure is translating into real demand for energy, land, and industrial capacity. That is why updates from companies tied to power and data centre buildout matter more than ever.
What could happen next — GO Markets
Scenario planning · March 2026
What could happen next
Three time horizons, three scenarios to watch across the AI industrialisation cycle
Next 2 weeks
Chipmaker reports
Possible
Market volatility continues as traders digest the latest reports from chipmakers like Micron
Upside scenario
"Bulletproof" guidance from remaining infrastructure names triggers a sector-wide relief rally
Watch for
Any mention of "capacity constraints" or "supply bottlenecks" in earnings calls
Next 30 days
Energy and rates
Possible
Focus shifts to "real economy" energy players like NextEra that power the data centres
Downside scenario
Rising oil prices from Middle East conflict act as a tax on tech margins, rotating into defensives
Action point
Monitor Fed language on rates. Higher for longer makes $650B capex bills far more expensive to finance
Next 60 days
The great dispersion
Possible
Market rewards companies with real AI revenue and punishes those still stuck in experimentation
Upside scenario
NextEra Energy (NEE) data centre announcements in late April/May trigger a utility renaissance rally
Downside scenario
An "air pocket" in profits occurs where debt-funded investment outpaces revenue gains
Watch
May reports from Texas Pacific Land (TPL) — is data centre land demand still "red hot"?
Action point
Review your portfolio for geographic diversity. The AI story is now a global power race
The psychological trap
The emotional trap many traders fall into right now is recency bias. You have seen NVIDIA and the "Magnificent 7" win for so long that it feels like they are the only way to play this. But the "obvious" trade is often the one that has already been priced in. Before acting, ask yourself: "Am I buying this stock because I understand its role in the physical AI supply chain, or because I’m afraid of missing the next leg of a rally that started two years ago?"
Disclaimer: This content is general information only and should not be relied on as personal financial advice or a recommendation to buy, sell, or hold any financial product. References to companies or themes, including AI-related stocks, are illustrative only. Share and derivative markets can move sharply, and concentrated sectors such as AI and technology may experience elevated volatility, valuation risk, and liquidity risk. If you trade derivatives such as CFDs, leverage can magnify both gains and losses. Past performance is not a reliable indicator of future performance.
After three consecutive years in which mega-cap AI-linked names carried the Nasdaq, the mix of winners may be starting to change.
2026 is the "show me the money" year. Any hint of doubt about whether tech companies were correct to spend nearly US$700 billion on AI last year could have a major impact on market sentiment.
Quick facts
Global AI capex is projected to exceed US$600 billion in 2026.
The total addressable market (TAM) for AI data centre systems is estimated to exceed US$1.2 trillion by 2030.
Nvidia, Microsoft and TSMC are all trading below analyst fair value estimates, despite surging revenues.
Broadcom's AI chip division is targeting US$100 billion in AI revenue by 2027.
What is powering the AI trade?
Multiple macro forces are likely to underpin the AI investment theme through 2026. The direction of US interest rates, the scale of AI infrastructure spending and the geopolitical backdrop are all likely to matter.
Rates and valuations
The Federal Reserve delivered 75 basis points (bps) of rate cuts in 2025, and markets expect another 50 bps in 2026. Lower rates can reduce the discount applied to future tech earnings and typically support growth stocks, including AI-linked names.
Infrastructure spending and earnings expectations
On the spending side, Nvidia CEO Jensen Huang has said data centre operators could spend up to US$4 trillion annually by 2030, and AI capital spending is projected to reach US$571 billion in 2026 alone.
However, markets appear to have already priced in much of this optimism. Analysts are projecting 14% to 16% annual earnings per share (EPS) growth in 2026. That would require S&P 500 stocks outside the Magnificent 7 to roughly double the pace of earnings growth recorded in 2025.
Geopolitics and export controls
Geopolitics could also shape the outlook. US-China export controls on AI chips, along with reduced access to key international buyers, could weigh on data centre growth projections.
Nvidia remains the clearest expression of the AI trade. It holds a wide economic moat thanks to its market leadership in GPUs, hardware, software, and networking tools.
Goldman Sachs and Morgan Stanley both carry price targets near $250 on NVDA, with Goldman's call based on a 2027 revenue forecast of over $380 billion. Bank of America sits in the $275 camp, effectively pricing in more AI upside on 2027 earnings.
At 21.6 times forward earnings, Nvidia is now trading below the broader S&P 500's multiple. Key risks include the overhang from US–China export restrictions and any softening in data centre capex guidance from major cloud providers.
Microsoft (MSFT)
Microsoft is down around 25% from its all-time high. During the second quarter of fiscal year 2026, Azure's revenue increased 39% year over year, and the company holds a US$625 billion backlog of contracted usage still to come.
The gap between the stock's recent performance and its underlying revenue growth has drawn attention from analysts, though elevated valuations across the broader tech sector remain a risk to watch.
While Nvidia makes broad-purpose GPUs, Broadcom is winning business by going bespoke, designing custom AI chips tailored specifically to the needs of individual hyperscalers like Google and Meta.
During Q1 of FY2026, Broadcom's AI semiconductor division grew at a 106% pace to US$8.4 billion, and by the end of 2027 it expects its AI chip revenue to reach more than US$100 billion.
Broadcom trades at a significant premium to the broader market, which could amplify any downside if growth expectations are not met.
TSMC (TSM)
Almost every major AI chip is manufactured by TSMC. The company holds approximately 70% market share in chip foundry, making it the single most critical piece of infrastructure in the entire AI supply chain.
TSMC sales are projected to increase by 30% in 2026, with gross margins expected to remain above 60% as new fabrication capacity comes online.
The primary risk is geopolitical: any escalation in Taiwan Strait tensions could weigh heavily on the stock regardless of its underlying fundamentals.
Vertiv (VRT)
Less prominent than the semiconductor giants, Vertiv provides the power management, cooling, and data centre infrastructure that keeps AI hardware running.
Nvidia, Broadcom, and Vertiv sit at different points in the AI build-out, including compute, custom silicon, networking and physical infrastructure.
Vertiv's revenue is tied to overall AI capex rather than any single chip maker, which gives it a different risk profile to the names above.
Corning (GLW)
Corning's stock rose 84% in 2025 thanks to surging demand from data centres for its fibre optic cables. Its optical communications segment has grown 69% YoY.
At a Price-to-Earnings (P/E) ratio of roughly 37x, Corning trades at a discount to Nvidia and Broadcom while still carrying direct exposure to AI infrastructure spending. However, its valuation depends heavily on continued capex from the major hyperscalers.
Training large-scale AI models is extraordinarily energy-intensive. A typical 1 gigawatt AI data centre facility requires upwards of US$60 billion in capital expenditure, with roughly half going directly to hardware.Utilities exposed to data centre power demand could also be affected by the AI build-out.
International spillover
South Korea's Kospi surged 76% in 2025 due to AI-linked chipmakers like SK Hynix. Japan's Topix, Germany's DAX, and the UK's FTSE 100 also saw gains of more than 20%. Memory supplier Kioxia was the world's best-performing stock, surging 540%.
Data centre infrastructure
Companies like Emcor, which provides critical electrical, HVAC, and power infrastructure to data centres, reported its contracted backlog surged 31.2% year over year to a record US$13.25 billion.These companies can offer different exposure to the AI capex cycle, but they carry their own execution, backlog, margin and valuation risks.
Broadcom trades at about 50x earnings and AMD at 56x. Any disappointment in forward guidance could trigger a sharp contraction in multiples.
The return on investment test
Companies are investing today on the assumption that highly profitable business applications of AI will emerge over time. If the timing or scale of those returns disappoints, the AI trade could face pullbacks.
Index concentration
The 10 largest stocks in the S&P 500 account for about 40% of the index's total value. A rotation out of mega-cap tech could disproportionately affect broad indices.
Efficiency disruption
China's DeepSeek recently published research suggesting large language models may be developed more efficiently than previously assumed. If AI can be built with less compute, demand for GPUs and data centre hardware could fall short of current forecasts.
Bottom line for traders
The AI trade is maturing but far from over. 2026 is shaping up to be a more nuanced chapter, spreading across the full AI value chain.
The US earnings season will be closely watched for evidence that the hundreds of billions being poured into AI infrastructure are beginning to generate the anticipated returns.
All data points referenced in this article were verified against primary sources on 18 March 2026.
Latin America recorded $730 billion in crypto volume in 2025. Across the region, 57.7 million people now own some form of digital currency rankingslatam, a base that is growing faster than anywhere else in the world
As institutional capital arrives and regulation matures, these are the publicly traded names investors are watching closest.
Digital banking · 127M users across Brazil, Mexico and Colombia
Nubank could be one of the most direct listed proxies for LATAM's fintech and crypto boom. The company integrated cryptocurrency trading directly into its Nu app and partnered with Lightspark to embed the Bitcoin Lightning Network for faster and more cost-effective Bitcoin transactions.
In Q3 2025, revenue jumped 42% year-on-year to $4.17 billion, customer deposits rose 37% to $38.8 billion, and gross profit was up 35% to $1.81 billion.
The stock has returned roughly 36% over the past year and tripled the S&P 500's returns over the last three years. The company dominates Brazil, with over 60% of the adult population using Nubank.
Nu Holdings also recently secured conditional approval to launch Nubank N.A., a US national digital bank.However, the announcement triggered a pullback, with investors cautious about capital deployment timelines and expansion costs.
UBS has lowered its price target to $17.20, citing some market caution despite positive operational shifts.
What to watch
Credit quality trends in Brazil and Mexico.
Pace of USDC adoption via Nubank rewards.
US bank charter timeline and early cost disclosures.
2. MercadoLibre (NASDAQ: MELI)
E-Commerce/Fintech · 18 countries across Latin America
MercadoLibre is not a pure crypto play, but Mercado Pago (its fintech arm) has become one of the most important financial rails in LATAM. The company holds around 570 BTC on its balance sheet as a hedge against regional inflation, and has issued its own US dollar-pegged stablecoin, Meli Dólar.
Full year 2025 net revenue from Mercado Pago reached $12.6 billion, up 46% year-on-year, while total payment volume hit $278 billion, up 41%. Fintech monthly active users have grown close to 30% for ten consecutive quarters, and the credit portfolio nearly doubled to $12.5 billion year-on-year.
The catch for MercadoLibre is profitability. Overall margin compression of 5–6% is attributed to persistent investments in free shipping, credit card expansion, first-party commerce, and cross-border trade.
The stock has declined around 14.5% over the past six months, with the market repricing the stock around what management has framed as a deliberate investment phase heading into 2026.
The longer-term case remains compelling. Mercado Pago has introduced crypto-asset management and insurance products across its core markets, positioning it less as an e-commerce company and more as a full-scale digital bank with crypto infrastructure built in.
What to watch
Mercado Pago loan loss trends and credit portfolio quality.
Stablecoin integration and crypto volume through its payment network.
Whether the Argentina credit card launch can reach profitability.
Fintech/Bitcoin treasury · Brazil's first listed Bitcoin treasury company
Méliuz is the most direct equity expression of the corporate Bitcoin treasury trend in LATAM. In early 2025, Méliuz became the first publicly traded company in Latin America to formally adopt a Bitcoin treasury strategy, receiving shareholder approval to allocate cash reserves toward Bitcoin accumulation.
Rather than issuing cheap dollar-denominated debt to buy BTC, Méliuz uses share issuance and operational cash flow. The company also sells cash-secured put options on Bitcoin to generate yield, a playbook borrowed from Japanese Bitcoin treasury firm Metaplanet, keeping 80% of BTC holdings in cold storage
CASH3 essentially acts as a leveraged vehicle for BTC exposure, capturing upside intensely in bull cycles, but generating greater volatility on the way down, especially where debt is involved.
The stock surged approximately 170% in May 2025 following the announcement of the Bitcoin strategy.However, it has since pulled back to its April 2025 levels, broadly tracking Bitcoin's price action and highlighting the stock's volatility.
Pure-play Bitcoin treasury · LATAM's largest corporate Bitcoin holder
Where Méliuz is a fintech business that also holds Bitcoin, OranjeBTC is the opposite: a company whose entire purpose is Bitcoin accumulation.
The company listed on B3 in October 2025 through a reverse merger with education firm Intergraus, marking Brazil's first public debut of a firm whose business model centres entirely on Bitcoin accumulation.
OranjeBTC currently holds over 3,650 BTC and raised nearly $385 million in Bitcoin, with backing from notable investors including the Winklevoss brothers, Adam Back, FalconX, and Ricardo Salinas.
Its $210 million financing round was led by Itaú BBA, the investment arm of Brazil's largest bank, in a significant vote of institutional confidence.
In 2026, OBTC3 has fallen around 32% year-to-date, making it the hardest-hit of the two Brazilian Bitcoin treasury stocks.The stock hit an all-time high of 29.00 BRL on its listing day (October 7, 2025) and an all-time low of 6.06 BRL in February 2026.
It currently trades around 7.06 BRL, a steep discount to its debut, but one that closely mirrors Bitcoin's own pullback from peak levels.
OranjeBTC is the most volatile name on this list and should be treated as a high-beta Bitcoin vehicle. Liquidity is thinner than established names.
What to watch
Bitcoin per share trajectory.
Any capital raises or new BTC purchases.
Potential international listing ambitions.
How the market-value net asset value (mNAV) discount/premium evolves relative to Bitcoin's price.
5. Hashdex — HASH11 (B3: HASH11)
Crypto Asset Management · Brazil's leading crypto ETF issuer
Hashdex offers a different kind of exposure to crypto. Rather than a single company's balance sheet or business strategy, HASH11 is a diversified basket of crypto assets wrapped in the familiarity of a regulated Brazilian ETF structure.
Brazil hosts 22 ETFs offering full or partial exposure to crypto assets, with Hashdex funds attracting 180,000 investors and daily transaction volumes averaging R$50 million.
Hashdex launched the world's first spot XRP ETF (XRPH11) on Brazil's B3 in April 2025, tracking the Nasdaq XRP Reference Price Index and allocating at least 95% of net assets to XRP.
The company also operates single-asset ETFs for Bitcoin (BITH11), Ethereum (ETHE11) and Solana (SOLH11), alongside its flagship HASH11 multi-asset index fund.
In mid-2025, Hashdex launched a hybrid Bitcoin/Gold ETF (GBTC11) that dynamically adjusts allocations between the two assets.
For investors who want diversified crypto market exposure rather than single-asset risk, HASH11 is the most accessible on-ramp through Brazil's regulated equity infrastructure.
However, as a multi-asset crypto index, HASH11 is still subject to the broad performance of digital asset markets. And unlike the equity names on this list, there is no operating business creating independent value.
What to watch
Crypto market sentiment broadly.
Potential expansion of Hashdex products into the US market.
AUM growth as institutional adoption accelerates in Brazil.
Relative performance of HASH11 vs single-asset alternatives.
Institutional infrastructure is still in early innings — Deutsche Börse's Crypto Finance Group entered LATAM in early 2026, and local exchanges have opened over 200 BRL-denominated trading pairs since 2024. The pace of that buildout will set the tone for all five names.
Regulatory progress in Brazil, Mexico, and Chile is the key enabler for the next wave of capital. Any setbacks would hit the higher-beta names like OBTC3 and CASH3 hardest.
Stablecoin volume is the region's most reliable real-time signal. Despite a global slowdown in early 2025, LATAM still recorded $16.2 billion in trading volume between January and May, up 42% year-on-year. Watch whether that momentum holds — a reacceleration lifts all five; a reversal pressures them equally.
Last week was as consequential as advertised. The RBA hiked, the Fed held, and markets barely had time to process any of it before reports emerged that Israel had struck Iran's South Pars gas field.
The week ahead brings fewer central bank decisions, but it may be just as important for markets. Flash PMIs will offer the first broad read on whether the war is already showing up in business confidence. Australia's February CPI is the domestic data point that matters most for the RBA's next move. And the oil market remains the dominant macro variable.
Quick facts
Brent crude spiked above $110 per barrel after Israel struck Iran's South Pars gas field for the first time.
Flash PMIs for Australia, Japan, the eurozone, UK, and the US all land Tuesday.
Australia's February CPI lands Wednesday, the first inflation read since the back-to-back RBA hikes.
Oil: From crisis to emergency
The oil situation deteriorated significantly last week. Brent crude has now surged roughly 80% since the war began on 28 February.
The 18 March strike on Iran's South Pars gas field was the first time upstream oil and gas infrastructure has been targeted.
Iran responded to the strike by threatening to target facilities across Saudi Arabia, the UAE and Qatar. If any of these threats are executed, the global oil shock would escalate from a supply disruption to a direct attack on the region's production capacity.
Analysts are now saying $150 Brent is achievable and $200 is not outside the realm of possibility. The 1970s Arab oil embargo resulted in a quadrupling of prices, and the current shock is already being described in those terms by senior energy executives.
For markets this week, oil is the dominant variable. Any signal of ceasefire, diplomatic progress or resumed Hormuz shipping could likely trigger a correction in oil prices. Any Iranian strike on Gulf infrastructure could send them higher.
Monitor
Daily vessel transit numbers through the Strait of Hormuz.
Iranian retaliation against Gulf infrastructure, a strike on Saudi or UAE facilities would be a major escalation.
When and how American and European IEA reserves reach the market.
Qatar's South Pars disruption is affecting the European LNG market.
Trump statements that could cause intraday oil price movement.
Global Flash PMIs: The first read on an economy at war
Tuesday delivers the S&P Global flash PMI estimates for March across every major economy simultaneously.
This will be the first data set to capture how manufacturers and services firms are responding to $100+ oil, the Strait of Hormuz blockade, and the broader uncertainty created by the war in the Middle East.
The key question for each economy is whether the oil price surge and war uncertainty have dented business confidence, suppressed new orders or pushed input price indices to new multi-year highs.
Given that oil crossed $100 before the survey window closed for most economies, input cost readings could be significantly elevated.
Key dates
S&P Global Flash Australia PMI: Tuesday 24 March, 9:00 am AEDT
S&P Global Flash Japan PMI: Tuesday 24 March, 11:30 am AEDT
HSBC Flash India PMI: Tuesday 24 March, 4:00 pm AEDT
HCOB Flash France PMI: Tuesday 24 March, 7:15 pm AEDT
The RBA hiked for the second meeting in a row on 17 March, lifting the cash rate to 4.10% in a narrow 5-4 vote.
Governor Bullock described it as a "very active discussion" where the direction of policy was not in question, only the timing.
This week will see the release of February's CPI as the first read to capture any of the oil shock. The trimmed mean, which strips out volatile items including fuel, will be the number the RBA watches most closely. A reading above 3.5% could cement the case for a May hike. A softer result could revive the argument for a pause.
ANZ and NAB have both stated expectations of a third hike in May, taking the cash rate to 4.35%.
Key dates
ABS Consumer Price Index (CPI): Wednesday 25 March, 11:30 am AEDT
Monitor
Trimmed mean inflation as the RBA's preferred measure.
Fuel and energy components that could separate the oil shock from domestic price pressure.
Housing and services inflation as sticky components driving the RBA's long-run concern.
Asia dominates the global semiconductor supply. Five companies, spanning Taiwan, South Korea, and Japan, sit at the critical juncture of the AI buildout, controlling everything from fabrication to the equipment that makes chips possible.
Quick facts
TSMC delivered $90 billion in revenue in 2024, with a 59% gross margin and shares up 55% in 2025.
Advantest shares doubled (+102%) in 2025 as AI-driven chip testing demand surged.
SK Hynix is Nvidia's primary HBM supplier, positioning it at the centre of the AI accelerator boom.
1. Taiwan Semiconductor Manufacturing Co. (TSM)
TSMC is the world's largest contract chip manufacturer, producing advanced semiconductors for Apple, Nvidia, AMD, and Qualcomm. As a pure-play foundry, it leads in 5-nanometer (5nm) and 3- nanometer (3nm) chip production, with smaller nodes in development.
The company posted $90 billion in revenue for 2024 with a 59% gross margin and 36% return on equity.
Shares delivered a total return of 55% in 2025, with analysts forecasting a further ~30% revenue increase in 2026, underpinned by its $100 billion US expansion programme.
The key risk for the company is its geopolitical exposure, with Taiwan Strait tensions remaining the sector's most-watched tail risk.
What to watch
US expansion progress: Any delays, cost blowouts, or political friction concerning TSMC's $100 billion Arizona investment could weigh on sentiment.
Customer order visibility: Watch for any guidance updates from Apple, Nvidia, or AMD on chip orders, as TSMC's revenue is highly concentrated among a handful of clients.
Geopolitical developments: Any escalation of Taiwan Strait tensions could trigger sharp moves regardless of fundamentals.
Next-node ramp: Progress on 2nm production and yield rates will be a key signal for TSMC's ability to maintain its technology lead.
2. Samsung Electronics (KR:005930)
Samsung is one of the few companies globally that both designs and fabricates chips at scale. It competes across DRAM, NAND flash, and logic chip segments, and remains a core supplier to global tech giants.
Samsung's wide scope is a strength, but also a complexity. Its memory division faces margin pressure from inventory cycles, while its foundry business continues to lag TSMC in leading-edge yields.
The AI-driven memory boom may provide a tailwind, though execution in HBM production has been slower than local rival SK Hynix.
What to watch
HBM qualification progress: Samsung has been working to qualify its HBM3E chips with Nvidia. Any confirmation of a major supply win could be a meaningful catalyst.
Memory pricing trends: DRAM and NAND spot prices could be an indicator of Samsung's margin trajectory.
Foundry yield improvements: Samsung's logic foundry business has struggled with yields at advanced nodes; any credible progress here could re-rate the division.
Management guidance: Following a period of earnings volatility, clarity on capex plans and divisional targets at upcoming results will be closely watched.
Tokyo-based Advantest makes testing equipment used to verify chips meet performance and quality standards.
It supplies to Samsung, Intel, Nvidia, Qualcomm, and Texas Instruments, allowing it to benefit from chip industry growth broadly, regardless of which foundry wins market share.
Advantest shares doubled in 2025 (+102%), and it raised its sales forecast by 21.8% and earnings forecast by 70.6% for the year ending March 2026.
What to watch
Order backlog updates: Any contraction in Advantest's backlog could be an early warning sign after the strong 2025 run.
AI chip testing demand: As chips grow more complex, testing time per chip increases. Monitor whether AI accelerator volumes from TSMC and Samsung start to drive outsized testing demand.
FY2026 guidance: The next forecast update will be critical in confirming whether 2025's upgrade cycle has further to run.
Tokyo Electron is among the world's largest suppliers of semiconductor production equipment, specialising in deposition, etching, and cleaning tools.
Every major chipmaker, including TSMC, Samsung, and SK Hynix, depends on TEL's systems to scale production.
As chipmakers invest billions to expand capacity, TEL's order book grows. The risk lies in potential US export restrictions on advanced equipment sales to China, which remains one of the primary revenue segments for the company.
What to watch
US export control policy: China accounts for a significant portion of TEL's revenue. Any tightening of equipment export rules is the most immediate risk to watch.
Chipmaker capex announcements: TSMC, Samsung, and SK Hynix's capital expenditure plans for 2026 directly translate into equipment orders. Any cuts could flow through to TEL's order book.
New tool adoption cycles: Monitor whether TEL's next-generation deposition and etch tools are being adopted at leading-edge fabs.
5. SK Hynix (KR:000660)
SK Hynix is the world's second-largest memory chip maker and has emerged as arguably the clearest AI-era beneficiary in the memory space.
It is Nvidia's primary supplier of High Bandwidth Memory (HBM) chips, the specialised memory used in AI accelerators like the H100 and B200.
HBM demand has driven a dramatic re-rating of SK Hynix's revenue profile and market standing. With AI infrastructure spending showing little sign of slowing heading into 2026, the company's HBM franchise could remain a key differentiator.
However, capacity constraints and the risk of Samsung and Micron closing the HBM gap are the primary concerns to watch.
What to watch
Nvidia supply relationship: Any shift in Nvidia's supplier mix toward Samsung or Micron could be a key risk event.
HBM4 development: The race to next-generation HBM is already underway. Watch for updates on SK Hynix's HBM4 readiness and whether it can maintain its lead.
Conventional memory pricing: SK Hynix still derives meaningful revenue from standard DRAM and NAND. Spot price trends could be a gauge of the broader memory cycle.
Bottom line
TSMC, SK Hynix, Samsung, Advantest, and Tokyo Electron collectively control the chokepoints of the AI buildout.
The expected increase in AI infrastructure may support demand, but investors should weigh the risks carefully.
Geopolitical exposure, US export restrictions, and the pace of HBM competition could all move the needle.
If you have been following the tech story for the last decade, you have been trained to look at a very specific, very small patch of real estate in Northern California. But as we sit here in early 2026, the "connect-the-dots" moment for investors is this: the AI trade has stopped being about shiny software demos in Palo Alto and has started being about the physical industrialisation of compute.
We have entered the "Year of Proof". The world’s largest companies, the hyperscalers, are projected to spend a staggering US$650 billion on capital expenditures this year. But here’s the part most people miss: that money is not staying in Silicon Valley. It’s flowing to the "picks and shovels" players in Idaho, Washington, Colorado and even overseas.
If you want to understand where the actual return on investment (ROI) may be landing this earnings season, you have to look outside the 650 area code. The shift from AI hype to AI industrialisation is changing the map.
The full AI stack: from capex to consulting — GO Markets
Five companies · AI infrastructure play · 2026
The full AI stack: from capex to consulting
Infrastructure builders compared to the implementation bridge across the AI value chain
Note: Hyperscalers shown as 2026 CapEx spend. Accenture shown as cumulative advanced AI bookings ($11.5B through Q1 FY2026), reflecting its role as the adoption layer rather than the infrastructure layer.
Infrastructure (2026 CapEx projected)Implementation bridge (cumulative AI bookings)
Hyperscaler CapEx: Early 2026 analyst estimates, midpoint of ranges. Amazon approx. 100% YoY, Alphabet approx. 100%, Meta approx. 87%, Microsoft approx. 50%.
Accenture: Cumulative advanced AI bookings $11.5B through Q1 FY2026. Q1 AI bookings $2.2B (up 76% YoY), AI revenue $1.1B (up 120% YoY) across 1,300+ clients.
Five companies shaping the next phase of AI
Micron Technology (MU), Boise, Idaho
Micron is the "memory backbone" of the current cycle. While everyone was watching the chip designers, many overlooked the fact that AI chips are far less useful without high-bandwidth memory (HBM). Micron is currently viewed by some analysts as a strong buy because its capacity is reportedly sold out through the end of 2026. Analysts are also eyeing a 457% jump in earnings per share (EPS) as the memory cycle reaches what some describe as a robust peak.
Microsoft (MSFT), Redmond, Washington
Microsoft is the enterprise backbone of this transition. It has moved beyond simple chatbots and is now building what analysts call "Intelligence Factories". While the stock has faced pressure recently over capacity constraints, underlying demand for Azure AI is reportedly still running ahead of capacity. The broader bull case is that Microsoft is moving into "Agentic AI", systems that do not just talk to users but may also execute multi-step business workflows.
Amazon is playing a long-term game of vertical integration. To reduce its reliance on expensive third-party hardware, it’s building its own AI chips in-house. Amazon Web Services (AWS) remains the primary driver of profitability, and the company is using its retail data to train specialised models that many Silicon Valley start-ups may struggle to replicate.
Palantir Technologies (PLTR), Denver, Colorado
If Micron provides the memory and Microsoft the platform, Palantir provides the "operating system" for the modern AI factory. The company has posted strong momentum, with US commercial sales recently growing 93% year over year. It’s often framed as a bridge between raw data and corporate profitability, which remains a key focus for investors in 2026.
Accenture (ACN), Dublin, Ireland
You cannot just "plug in" AI. Businesses often need to redesign processes around it, and that’s where Accenture comes in.
The company is viewed as an implementation bridge, with one analyst arguing that "GenAI needs Accenture" to move from pilot programs to production though the cautionary angle is that the AI story has not fully excited investors here yet because consulting revenue can take longer to show up than chip sales.
What could happen next?
The chart maps the three time horizons likely to shape the next phase of the AI industrialisation trade.
In the near term, markets are still reacting to chipmaker earnings, guidance, and any signs of capacity strain. Over the next month, attention shifts to the real-world inputs behind AI growth, especially power, financing, and infrastructure. By the 60-day window, the key question is whether AI spending is broadening into a wider market re-rating or running ahead of near-term returns.
Across all three periods, the focus is the same: proof. Investors are looking for signs that AI capital expenditure is translating into real demand for energy, land, and industrial capacity. That is why updates from companies tied to power and data centre buildout matter more than ever.
What could happen next — GO Markets
Scenario planning · March 2026
What could happen next
Three time horizons, three scenarios to watch across the AI industrialisation cycle
Next 2 weeks
Chipmaker reports
Possible
Market volatility continues as traders digest the latest reports from chipmakers like Micron
Upside scenario
"Bulletproof" guidance from remaining infrastructure names triggers a sector-wide relief rally
Watch for
Any mention of "capacity constraints" or "supply bottlenecks" in earnings calls
Next 30 days
Energy and rates
Possible
Focus shifts to "real economy" energy players like NextEra that power the data centres
Downside scenario
Rising oil prices from Middle East conflict act as a tax on tech margins, rotating into defensives
Action point
Monitor Fed language on rates. Higher for longer makes $650B capex bills far more expensive to finance
Next 60 days
The great dispersion
Possible
Market rewards companies with real AI revenue and punishes those still stuck in experimentation
Upside scenario
NextEra Energy (NEE) data centre announcements in late April/May trigger a utility renaissance rally
Downside scenario
An "air pocket" in profits occurs where debt-funded investment outpaces revenue gains
Watch
May reports from Texas Pacific Land (TPL) — is data centre land demand still "red hot"?
Action point
Review your portfolio for geographic diversity. The AI story is now a global power race
The psychological trap
The emotional trap many traders fall into right now is recency bias. You have seen NVIDIA and the "Magnificent 7" win for so long that it feels like they are the only way to play this. But the "obvious" trade is often the one that has already been priced in. Before acting, ask yourself: "Am I buying this stock because I understand its role in the physical AI supply chain, or because I’m afraid of missing the next leg of a rally that started two years ago?"
Disclaimer: This content is general information only and should not be relied on as personal financial advice or a recommendation to buy, sell, or hold any financial product. References to companies or themes, including AI-related stocks, are illustrative only. Share and derivative markets can move sharply, and concentrated sectors such as AI and technology may experience elevated volatility, valuation risk, and liquidity risk. If you trade derivatives such as CFDs, leverage can magnify both gains and losses. Past performance is not a reliable indicator of future performance.
