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IPOs and what you need to know

This is the point where 'private' becomes 'public'. It gives the market its first real look under the hood of companies like OpenAI, SpaceX and a new wave of ASX hopefuls.

What is an IPO?

An initial public offering (IPO) is when a private company offers its shares to the public for the first time. Before an IPO, shares are usually held only by founders, early employees and private investors but going public opens those shares to a broader market.

For traders, IPOs may be the first opportunity to gain direct exposure to a company's stock. They can create a unique environment of elevated volatility and heightened interest, but they also carry higher risk because price history is limited and sentiment can shift quickly.

US$171.8 billion

Global IPO proceeds in 2025, up 39% year on year

US$3 trillion plus

Combined estimated valuation of top 2026 IPO candidates

1,293

Global listings in 2025, the sharpest rebound since the post-pandemic boom

Upcoming IPOs across global exchanges

CompanyEstimated valuationExchangeStatus
Anthropic
Artificial intelligence
~US$350 billionNasdaqRumoured
Databricks
AI and data
~US$134 billionNasdaqExpected
Firmus Technologies
AI infrastructure
~A$6 billionASXExpected
Greencross
Pet care & veterinary
~A$4 billion plusASXRumoured
OpenAI
Artificial intelligence
~US$850 billionNasdaqExpected
Rokt
E-commerce adtech
~US$7.9 billionNasdaq and ASX CDIExpected
SpaceX
Aerospace and AI
~US$1.5 trillionNasdaqExpected
Stripe
Fintech
~US$140 billionNYSE/NasdaqRumoured
Source: Publicly available company announcements, exchange materials, reputable media reporting and market commentary, as at 21 April 2026. Estimated valuations, exchanges and listing status are indicative only and may change without notice.

US IPO candidates

SpaceX, OpenAI, Anthropic and more

Read more

ASX IPO candidates

Firmus Technologies, Greencross and more

Read more

How a listing works

From boardroom to exchange floor

By listing day, institutional investors have usually already assessed the company. Understanding the six-stage process helps traders see what may already be reflected in the price before the stock opens to the broader market.

Preparation

The company selects an underwriter to assess its finances, corporate structure and market positioning.

Registration

Underwriters conduct due diligence and lodge disclosure documents with the relevant regulator.

Roadshow

Executives pitch to institutional investors and analysts. This is where demand is built and price expectations are set, before retail traders ever see the stock.

Pricing

Based on roadshow feedback, underwriters set the final share price and decide how many shares will be issued.

Listing day

Shares begin trading on the chosen exchange. For most traders, this is the first chance to trade the stock.

Post-IPO

Now public, the company must publish financial results regularly and meet the governance standards of its exchange.

Trading IPOs with CFDs

Why CFDs suit IPO volatility

IPO listing day is often defined by large sentiment swings and thin price history. That combination can make traditional buy-and-hold exposure harder to manage. CFDs let traders take a view on either side of the move, size positions precisely and act quickly as the story develops.

Go long or short

Trade the initial surge or the post-hype correction. CFDs let you take a position in either direction from listing day onward.

Shorter time horizons

IPO volatility tends to compress into the first days and weeks. CFDs are well suited to these shorter, event-driven windows

Built-in risk tools

Stop loss and limit orders can help define your risk beforeentry, which matters when price discovery is still unfolding.

US and Australian market coverage

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News & analysis

Few potential listings carry the market weight of a SpaceX or Starlink IPO. The story is not just whether the company comes to market. It is how a listing could reset valuation benchmarks, shift sector sentiment and affect the publicly traded space economy around it. For traders, the question is not only “when will SpaceX list?” It is which instruments could react, which signals matter before the event and where the risks may sit once price discovery begins.
Announcments
AI
SpaceX IPO lens: Valuation, volatility and the stocks around the story

Few companies in modern market history have attracted the level of sustained anticipation surrounding a potential SpaceX public listing.

GO Markets | SpaceX IPO Trading Playbook - Part 1

The IPO Context

For years, traders and investors have watched private funding rounds push the company’s valuation into territory usually associated with major public companies. Each round has raised the same question: when, whether and how does SpaceX, or its Starlink satellite division, finally come to market? It is part of a wider watchlist of major IPO candidates in 2026.

Because major initial public offering (IPO) events do not always move only the company being listed. They can move the assets around them. The SpaceX story is also a useful lens for understanding the mechanics that matter around major listings: private valuation versus public price discovery, institutional allocation versus open market access, lockup schedules, float structure and the risk of a broken IPO when the offer price proves too demanding.

The mistake is to treat a high-profile IPO as a simple popularity contest, or worse, as a crowded trade where attention gets mistaken for execution quality.

Why mega-cap listings can move more than one market

A major public listing does more than create a new tradeable instrument. It changes the reference point for an entire sector. The impact can be supportive or disruptive. A successful listing may validate investor appetite for the sector. A demanding valuation can also drain attention and capital from listed peers as investors compare multiples, growth profiles and liquidity. Both outcomes can occur across different timeframes.

For CFD traders, the relevant question is not simply whether the company is admired. It is whether the listing changes volatility, liquidity, relative valuation or sentiment in instruments already available to trade.

The Valuation Overhang

Private rounds set reference prices, not public market support. In a mega-cap listing, the risk is not whether the company is admired. It is whether the offer price already capitalises the best version of the story. If the first tradeable price cannot absorb that expectation, the IPO can break quickly.

Allocation friction as a volatility catalyst

Institutional investors participate in book-building before the listing. They may receive an allocation at the IPO offer price, subject to demand, syndicate decisions and allocation rules. Public market and CFD participants usually enter after trading begins, at the open market price available on the platform or exchange. That access gap is not merely a disadvantage. It is a source of volatility.

If the offer is heavily oversubscribed and the float is limited, the opening price may gap above the offer price. If demand is weaker than expected, or if the valuation was set aggressively, the opening trade may struggle to hold the IPO price.

Key mechanics that shape IPO trading

Book-building +

The process where investment banks gather demand from institutional investors to help set the offer price.

Why it matters to traders

The offer price reflects institutional demand before public trading begins. It may differ from the price available once the market opens.

Syndicate allocation +

The distribution of IPO shares among selected institutional investors and eligible participants.

Why it matters to traders

Allocation decisions influence who owns stock at the offer price and how much supply may later reach the open market.

Flotation percentage +

The proportion of the company sold to public investors at listing.

Why it matters to traders

A smaller float can increase scarcity and volatility. A larger float may improve liquidity but may require deeper demand.

Free float +

The shares available for public trading after restricted holdings are excluded.

Why it matters to traders

A low free float can amplify price moves because less stock is available to absorb demand or selling pressure.

Grey market pricing +

Indicative pre-listing pricing in unofficial or conditional markets, where available.

Why it matters to traders

Grey market levels can reveal sentiment before listing, but they are not a guaranteed guide to the opening price.

Indicative price range +

The expected offer price range published before final pricing.

Why it matters to traders

Pricing above or below the range can signal demand strength or weakness, but the first public trade remains the key market test.

Stabilisation +

Actions that may be used by underwriters to support orderly trading after listing, subject to rules and disclosure.

Why it matters to traders

Stabilisation can affect early price behaviour. Traders should read the offer documents rather than assume the tape is purely organic.

Lockup expiry +

The date when insiders or early investors may be able to sell restricted shares.

Why it matters to traders

It is a structural supply event. Even a strong listing can face pressure as lockup expiry approaches.

Broken IPO +

A listing that trades below its IPO offer price soon after launch.

Why it matters to traders

It can signal that the offer valuation was too demanding, market conditions changed or demand was not deep enough.

Valuation overhang +

A situation where a high listing valuation constrains later upside because expectations are already elevated.

Why it matters to traders

Strong companies can still deliver weak trading outcomes if the entry valuation leaves limited room for disappointment.

SpaceX and Starlink as a listing lens

SpaceX is unusual because the broader business spans rocket manufacturing, launch services, satellite internet through Starlink and government or defence-adjacent activity. Those segments can attract different valuation methods, investor bases and risk assumptions.

Starlink has often been discussed as the more likely standalone listing candidate because subscription revenue can be easier for public markets to model than a broader aerospace and launch business. That does not make the valuation simple. Satellite infrastructure is capital intensive, competitive and exposed to regulatory, geopolitical and technology-cycle risks.

For traders, the listing structure matters. A Starlink-only IPO may read more like a communications infrastructure and high-growth technology event. A broader SpaceX listing may be interpreted through aerospace, defence, government contract and frontier technology lenses. The related-market reaction could differ materially depending on which entity, if any, comes to market.

Space economy ecosystem map

SpaceX’s relationship with publicly listed sectors, showing the instruments traders often monitor in response to SpaceX news across launch services, satellite communications, defence contracting and earth observation.

Ecosystem Driver

SpaceX (Private Entity)

Market Access Status No Public Ticker

Launch Competitors

RKLB Rocket Lab USA

Electron · Neutron (2026 platform deployment system framework)

Direct Competitor
BA Boeing

ULA framework partnership infrastructure · SLS platform development

ULA Exposure
LMT Lockheed Martin

ULA infrastructure matrix deployment · Orion development systems

ULA Exposure

Satellite Communications

ASTS AST SpaceMobile

Mobile satellite broadband connectivity frameworks

Starlink Rival
IRDM Iridium Comms

LEO voice and specialized programmatic data architectures

Starlink Rival
SPIR Spire Global

Global weather monitoring systems and critical maritime logistics telemetry

Launch Customer

Defence Contractors

BA Boeing

NASA structural flight operations and primary institutional DoD contracts

Contract Rival
LMT Lockheed Martin

Orion modular space platform execution and core weapon systems matrices

Contract Rival
NOC Northrop Grumman

Cygnus mission logistics transport frameworks and aerospace production lines

Contract Rival

Earth Observation & ETFs

PL Planet Labs

High-cadence programmatic planetary satellite mapping arrays

Launch Customer
UFO Procure Space ETF

Broadly diversified index framework track of global aerospace equity allocation

Sector Index
Reading the diagram: SpaceX sits at the centre of the ecosystem. The strongest reactions to SpaceX news typically come from RKLB (direct launch competitor) and ASTS/IRDM (Starlink competes directly in their broadband market). Defence contractors BA, LMT, and NOC are affected mainly by government contract outcomes.
Data sources & Disclaimers: Sector classifications based on company 10-K filings, SEC filings, and public analyst reports. Constellation Metric: ~6,000 active operational units deployed globally with an estimated baseline user matrix of 4M+ scaling subscribers (subscriber estimate via third-party industry analysis, Bank of America 2024; satellite count from FCC orbital debris filings and SpaceX press releases). Strategic Layout Exposure: BA and LMT hold launch market cross-exposure via their 50% strategic joint ownership structure of United Launch Alliance (ULA) alongside distinct standalone configurations. UFO ETF holdings from Procure Space ETF prospectus. This diagram layout structure is for educational illustration only and does not represent all competitive alignments or complete market execution dynamics.

Preparation, scenarios and risk management

The trader’s watchlist

A major IPO event can affect more than the listing itself. Traders may monitor the surrounding market structure through a focused set of instruments and signals.

Market signal Why it matters for a SpaceX or Starlink listing
Aerospace and satellite communication stocks Tracks sector validation, competitive repricing and capital rotation across listed space-adjacent names.
Nasdaq 100 and US technology sentiment Frames appetite for high-growth, innovation-led listings. Weak technology sentiment can weigh on demand even when the company narrative is strong.
S&P 500 futures and broader US equity tone Shows whether the listing is arriving into a supportive risk environment or a broader equity drawdown.
US dollar index Helps frame global risk appetite and US dollar-denominated market conditions. A stronger US dollar can coincide with more defensive positioning.
US 10-year Treasury yield Tracks valuation sensitivity. Rising yields can pressure capital-intensive, high-growth listings by discounting future cash flows more heavily.
VIX signals and broader volatility conditions Indicates whether the market is likely to support new issuance or demand a larger valuation discount.
Formal filings, roadshow updates and pricing range Provides the direct event path from speculation to tradeable catalyst. Filing detail, indicative range and final pricing can shape first-day expectations.
Comparable IPO performance Shows how recent high-profile listings have traded after pricing. Useful as context, not as a forecast.

Historical volatility in space economy stocks around SpaceX events

Average absolute daily percentage moves for RKLB, ASTS and IRDM across three conditions: normal trading days, SpaceX Starship launch days and the following trading day. All three stocks showed materially elevated volatility on or around SpaceX milestones.

RKLB — Rocket Lab USA
1.76×
Volatility multiplier on SpaceX launch days vs. normal sessions (2023–2024)
Baseline ~3.8% → event day ~6.7%
ASTS — AST SpaceMobile
1.66×
Highest absolute daily volatility of the three across all conditions
Baseline ~5.9% → event day ~9.8%
IRDM — Iridium Comms
2.00×
Most stable of the three; still doubles in volatility on SpaceX event days
Baseline ~1.4% → event day ~2.8%
Baseline (avg. non-event sessions)
SpaceX Starship launch day
Day after SpaceX launch event
Event Date Outcome Result RKLB +1d ASTS +1d IRDM +1d
IFT-1 Apr 20, 2023 Explosion at launch pad — vehicle lost 4 min after liftoff Failure +6.2% +8.4% +2.1%
IFT-2 Nov 18, 2023 Both stages lost; partial hot-stage separation success Failure +3.1% +5.2% +0.8%
IFT-3 Mar 14, 2024 First Starship to reach space; both stages lost on re-entry Mixed −1.5% −2.3% +0.4%
IFT-4 Jun 6, 2024 First successful booster splashdown and ship controlled re-entry Success −3.8% −6.1% −1.9%
IFT-5 Oct 13, 2024 Booster caught by "chopsticks" launch tower arms — historic milestone Success −4.3% −7.8% −2.4%
IFT-6 Nov 19, 2024 Ship successful re-entry; booster failed catch and splashed down in Gulf Mixed +2.1% +1.4% +0.6%

What the data shows: All three stocks experienced materially higher volatility on SpaceX Starship launch days compared with normal trading sessions.

ASTS carried the highest absolute daily moves, both in baseline conditions and around events. That may reflect its early-stage, high-growth profile and direct Starlink competition. IRDM was the most stable of the three, although it still showed a wider daily range around SpaceX event days. For CFD traders, wider ranges can increase the effective cost of entry and exit around major events, particularly where spreads also widen.

Data sources: Volatility baselines are derived from 30-day rolling average absolute daily percentage changes for each stock during 2023 and 2024, compiled from StockAnalysis, TipRanks and Investing.com historical price data. Event day and post-event session reactions are sourced from contemporaneous financial media coverage and public historical price data. SpaceX Starship test flight dates and outcomes are confirmed via Wikipedia and SpaceX official communications. Figures are approximate.

The launch-event scenario map

These scenarios support conditional thinking before price begins moving quickly.

If this condition occurs Traders may monitor Risk to consider
An S-1 filing or equivalent document is submitted Whether related aerospace and technology stocks respond immediately or wait for financial details. First reactions can be sharp and short-lived. A filing can be faded if valuation or risk disclosures disappoint.
The IPO prices above the indicative range Whether opening-day price action confirms or rejects the aggressive valuation. High-end pricing can increase the risk of a broken IPO if open-market demand is not deep enough.
The floatation percentage is low Whether scarcity drives a sharp opening move or creates unstable liquidity. Low free float can amplify upside and downside moves. Spread conditions may deteriorate.
The broader equity market is risk-off near listing Whether institutional demand is strong enough to support the offer price. Risk-off conditions increase the probability of a weak open, delayed listing or rapid post-open reversal.
The lockup expiry approaches after listing Whether insider selling pressure appears and whether key support levels hold. Lockup expiry is a structural source of potential supply. It should not be treated as a surprise event.
SpaceX or Starlink delays or withdraws plans Whether pre-event optimism in related names reverses. Sentiment-driven gains can unwind quickly if the catalyst disappears.

Execution risk checklist

Use this checklist before making any decision around an IPO-related market event. It is not a trading signal. It is a risk review standard.

Execution Infrastructure: Map these scenarios using GO Markets' integrated TradingView charting, track overlap via the Economic Calendar, and test spread assumptions in a demo environment before committing live capital.

Questions investors are asking

What to watch from here

The SpaceX IPO narrative is one of the more consequential market stories in the current environment. Whether or not a listing occurs in the near term, the preparation work is similar: understand the listing structure, monitor related instruments, map the scenario framework and define risk controls before the event arrives.

When ready to move from theory to practice, explore GO Markets IPO education resources, platform tools and demo environment to test the process in real market conditions.

GO Markets
June 1, 2026
which Asian exporters are exposed to US demand, how US tariffs affect Asian exporters, Asian export sectors most at risk, US consumer slowdown impact on Asia, semiconductor demand vs consumer goods demand, Asian textile export risk, AI hardware supply chain outlook, what to watch in Asian export stocks
AI
Psychology
Which Asian sectors are most exposed to US demand?

In the "Year of Proof" 2026, the relationship between the US consumer and the Asian producer has entered a period of sharp divergence. Following the US Supreme Court's decision to invalidate previous emergency tariffs, the transition to the Section 122 regime raised the average effective US tariff rate to 10.3%.

Asia Exporters: Which Sectors Are Most Exposed to US Demand? | GO Markets

For newer investors

The key point is that a slowdown in US orders does not hit all exporters at the same rate. The real impact depends on margin structures, pricing power, customer concentration, and whether a product is tied to retail demand or corporate capital expenditure (capex).

Why US demand matters for Asia

This trade policy shift is landing at a difficult time for traditional exporters. The ongoing blockade of the Strait of Hormuz has pushed Brent crude oil prices above the US$100 mark, dramatically raising transportation and raw material costs.

While some US retailers may be able to shield consumers by temporarily absorbing these costs, Asian manufacturers are feeling pressure on their operating margins.

However, this is not a uniform story. While some sectors are highly sensitive to a pullback in US consumer spending, others are insulated by structural technology cycles and global investment trends.

The highest-risk sectors

Textiles and apparel +
Very High Sensitivity

This is the clearest example of direct US demand exposure. Exporters in Vietnam, Bangladesh, India, Indonesia, and parts of China are tied directly to US retail orders, seasonal buying cycles, and private-label contracts.

If US consumer confidence slips under the weight of persistent inflation, retail orders can be delayed, reduced, or cancelled almost instantly.

The risk is exceptionally high here because the sector operates on paper-thin margins and has virtually zero pricing power. Because textile production is highly labour-intensive, any drop in volume leads to immediate factory underutilisation, turning profitable operations into net losses within a single quarter.

Basic consumer goods +
High Sensitivity

This category includes toys, household goods, simple appliances, furniture, and other discretionary exports from China, Vietnam, Thailand, Malaysia, and Indonesia.

These sectors are highly exposed when US consumers pull back on non-essential spending to cover rising costs for food, utilities, and gasoline.

Furthermore, retail inventory cycles play a major role. If US retailers begin cutting inventory, they can easily pressure suppliers to absorb the cost of the 10% tariff. Since the pass-through rate of tariffs to import prices is currently estimated at 86%, Asian exporters are being forced to swallow the remaining 14% directly out of their operating margins.

The middle of the risk curve

Electronics assembly +
Medium to High Sensitivity

The electronics assembly sector is a more mixed story. Lower-end consumer devices and personal electronics are highly sensitive to US household demand. However, higher-value enterprise-linked components are far more resilient.

The risk is mixed because while consumer demand can weaken quickly, these complex electronics supply chains are incredibly difficult to re-route overnight.

For countries like Malaysia, Thailand, and the Philippines, these exports are often tied to essential replacement cycles rather than purely discretionary spending, giving larger manufacturers more negotiating power against US buyers.

Illustrative framework

Electronics assembly: end-market mix vs earnings sensitivity

Estimated earnings impact from a 10% US consumer demand decline, plotted against share of revenue from consumer device end markets. Bubble size indicates relative sector revenue scale.

Very high exposure High exposure Medium exposure Lower exposure Low direct
Consumer share
Est. earnings impact
Illustrative framework only. Earnings sensitivity estimates are indicative and based on general sector characteristics, not company-specific data. Actual outcomes depend on contract terms, customer concentration, geographic diversification and hedging.
Machinery and industrial goods +
Medium Sensitivity

Industrial machinery is generally insulated from short-term retail consumer spending. The bigger risk here is corporate capex.

If US companies delay capital investments because of ongoing trade-policy uncertainty, machinery orders from Japan, South Korea, China, and Taiwan may weaken.

However, the timing of this slowdown is usually much slower than retail goods. These manufacturers often maintain substantial order backlogs that provide a multi-month buffer against sudden policy shocks.

The lower direct-risk sectors

Semiconductors +
Medium to Low Sensitivity

Semiconductors are less directly tied to US retail inventory cycles. Demand is driven by broader technology cycles, automotive upgrades, and cloud infrastructure.

While chip demand can weaken if global growth slows, advanced node foundries possess incredible pricing power. Taiwan Semiconductor Manufacturing Company (TSMC) proved this by raising its full-year revenue growth forecast to above 30% in US dollar terms, supported by an "extremely robust" appetite for high-performance computing.

The main risk here is not US consumers buying fewer laptops; it is geopolitical friction and supply chain blockades, particularly as the Strait of Hormuz closure disrupts the supply of critical semiconductor gases like helium.

AI hardware and data-centre supply chain +
Low Direct Sensitivity

This is the lowest direct US consumer demand sensitivity in the group. AI hardware is driven by hyperscaler capex budgets rather than everyday retail spending.

With the four major US cloud providers tracking toward over US$700 billion in capex, demand for high-end AI servers remains structurally insulated from short-term consumer wobbles.

The risk for advanced electronics hubs in Taiwan and South Korea is less about US consumers stopping purchases, and more about capex expectations becoming too high or trade policy restrictions expanding into critical technology.

The early warning signs

The first warning sign may not be revenue.

Revenue can lag. Earnings can lag. Even margins can lag if contracts, inventories or hedging arrangements delay the impact.

For Asian exporters, the earlier signals are often operational. These details can matter because export pressure often starts before it becomes obvious in headline earnings.

Weaker order intake
Lower factory utilisation
Rising finished-goods inventory
Shorter production runs
Slower customer payments
More cautious guidance
Delayed capex
Softer commentary from US retailers or brand owners

The emotional trap to watch

Psychology

"Am I trading this because of its historical sector label, or because I have mapped its actual exposure?"

The emotional trap here is recency bias. Traders may be looking at performance from prior periods where technology demand comfortably absorbed trade friction. That history can make it easy to assume the same resilience applies now, even when the underlying conditions have changed.

The combination of inventory destocking, policy uncertainty and shifts in consumer spending patterns can mean that counting on a clean upward line for all Asian exporters is a more dangerous assumption than it may have been previously.

The question to ask before acting: is this view based on what is true now about customer concentration, order book depth and US retail inventory levels, or on what worked in a different environment?

What investors may watch next

To navigate this sector-sensitivity story over the next 30 to 60 days, traders may consider monitoring several key metrics, supported by the economic calendar:

GO Markets
May 25, 2026
AI
Shares
Google TPU chips and NVIDIA: What the AI chip war means for markets

For the past three years, investing in artificial intelligence (AI) infrastructure has followed a relatively simple logic: find the companies building the picks and shovels for the gold rush. At the top of that list sat one name: NVIDIA.

Its chips power many of the world’s AI models. Its software ecosystem keeps developers loyal. Its stock has been one of the most dramatic wealth-creation stories in a generation.

Then Google walked into a conference room in Las Vegas and signalled it was getting serious about making its own silicon available to the world.

Here is what happened, and why it matters for investors.

When Google Draws Its Sword — AI Chip War Analysis | GO Markets
The TPU glossary, key terms
TPU
Tensor Processing Unit. Google’s custom chip built specifically for AI mathematics, not general graphics.
GPU
Graphics Processing Unit. NVIDIA’s chip, originally built for gaming, now the dominant AI training hardware.
Inference
Running a model in the real world. Different, cheaper and increasingly important compared with training.
CUDA
NVIDIA’s software layer. The real competitive moat. Millions of developers are locked in by code, not chips.

What Google announced

At Google Cloud Next 2026 in Las Vegas, Google made two distinct announcements. It confirmed general availability of Ironwood, its seventh-generation TPU, the first purpose-built for what Google calls the “agentic era” of inference at scale. It also previewed its eighth-generation architecture: two purpose-built chips, TPU 8t for large-scale training and TPU 8i for high-speed inference, both targeting TSMC 2nm manufacturing and expected to reach general availability later in 2026.

A TPU is Google’s custom alternative to NVIDIA’s graphics processing unit (GPU). Where a GPU is a general-purpose workhorse, a TPU is a specialist chip built from the ground up for AI calculations. Google has been building them since 2016. The eighth generation is its most ambitious split yet, and the first time the company has designed separate chips for each half of the AI lifecycle.

The TPU 8t training pod reportedly delivers nearly three times the compute of an equivalent Ironwood pod, with double the performance per watt. The TPU 8i inference chip is designed to serve millions of AI agents simultaneously for enterprise customers.

That last part carries a structural implication. On a recent earnings call, CEO Sundar Pichai indicated that as TPU demand grows from AI labs, capital markets firms and high-performance computing applications, Google would begin delivering TPUs to select customers in their own data centres. Google is no longer content to keep its silicon advantage internal.

Google is no longer just a TPU user. It is becoming a TPU vendor, and its biggest customers are already signed up.

Anthropic’s compute strategy

Anthropic, the AI company behind Claude, has confirmed a major infrastructure deal with Google covering access to up to one million Ironwood TPU chips. The commitment is worth tens of billions of dollars and was formally announced by both companies.

Understanding that deal requires understanding Anthropic’s compute strategy in full.

Compute Infrastructure Strategy
Amazon Trainium
Anthropic’s primary cloud and training partner is Amazon. Project Rainier, Anthropic’s frontier model supercluster, runs on Trainium 2 chips across multiple US data centres. Anthropic has committed to up to 5 gigawatts of current and future Trainium capacity.
Google TPU
Confirmed deal for up to one million Ironwood chips, plus 3.5 gigawatts of further TPU capacity from 2027. Anthropic has used Google TPUs since 2023 and described strong price-performance efficiency as the driver for the expansion.
NVIDIA GPU
Third pillar of Anthropic’s diversified infrastructure. NVIDIA GPUs support research, specialist workloads and certain training runs. The multi-platform strategy is deliberate, with no single-vendor lock-in, optimising each dollar of compute.

The multi-platform picture matters because coverage elsewhere has occasionally characterised this Google deal as Anthropic “switching” from NVIDIA. That framing understates the deliberate architecture of Anthropic’s compute strategy. The Google deal is an expansion, not a departure from either AWS or NVIDIA.

Why this matters beyond the benchmark

On a per-chip basis, the current generation comparison is closer than the headlines suggest. Ironwood, now in general availability, delivers approximately 4.6 petaflops of FP8 computing power. NVIDIA’s Blackwell B200 delivers roughly 4.5 petaflops at FP16, although cross-precision comparisons require care, as the two figures are not measured on an identical scale.

But benchmark comparisons miss the bigger story.

At pod scale, where these chips are actually deployed, the gap widens. An Ironwood superpod of 9,216 chips delivers 42.5 exaflops. The eighth-generation TPU 8t pod, at 9,600 chips, targets 121 exaflops at FP4 precision. Google also claims near-linear scaling to one million chips inside a single logical cluster. For hyperscalers running hundreds of thousands of chips simultaneously, pod-level economics matter far more than per-chip benchmarks.

Performance benchmark
Chip comparison: compute and efficiency
Precision note: direct comparison requires caution. Ironwood compute is measured at FP8, NVIDIA B200 at FP16, TPU 8t pod figures at FP4. Halving FP4 figures provides a rough FP8 equivalent. Performance per watt is indexed to NVIDIA H100 baseline 100 and reflects Google’s published claims versus Ironwood, not independent verification. Benchmark results vary by workload and conditions.

The NVIDIA position

NVIDIA currently controls an estimated 81% of the AI data centre chip market, according to IDC. That is an extraordinary concentration of market power, and the near-term demand picture has remained resilient.

Recent analyst expectations have pointed to strong NVIDIA earnings growth, supported by elevated demand for AI infrastructure and broad adoption of the Blackwell platform. NVIDIA has itself guided for a combined US$1 trillion in Blackwell and upcoming Vera Rubin orders across 2026 and 2027.

AMD is developing rack-scale server systems and has gained meaningful ground. Estimates from analysts, including IDC, suggest AMD may now hold approximately 10% of the AI accelerator market, up from low single digits two years ago. Amazon and Google continue to expand custom chip businesses. The combined chip operations at Amazon alone, covering Trainium, Graviton and Nitro, have crossed a US$20 billion annual revenue run rate, growing at triple-digit percentages year over year, with nearly 40% sequential growth in Q1 2026.

The bull case for NVIDIA remains clear: demand has stayed strong, and NVIDIA’s ecosystem remains deeply embedded across the AI compute stack.

The longer-term question is less about near-term earnings and more about pricing power in the next upgrade cycle. Every reporting period in which Google, Amazon and Microsoft gain confidence in their own silicon is another data point in that debate. The incentive structure is powerful: these companies have every reason to reduce dependency on a single supplier, and the capital to act on it.

Market structure
AI data centre chip market share, estimated 2026
Estimated share of AI accelerator revenue. Custom silicon has grown from near zero three years ago. AMD share estimates vary across methodologies. Recent analyst estimates range from 4% to 10%.
Source note: IDC estimates, Silicon Analysis, public disclosures, company filings. Figures are approximations, subject to significant revision depending on methodology and market definition.

Stocks and sectors to watch

For NVIDIA, the near-term earnings story and the longer-term competitive story are pulling in different directions. Strong results may validate the current cycle. But the structural dynamic, where major customers build their own silicon, is unlikely to reverse.

For Alphabet, the Ironwood general availability and eighth-generation preview represent a potential monetisation opportunity well beyond advertising. Google Cloud grew 63% year over year in Q1 2026, among the fastest growth rates of any major hyperscaler. TPU-as-a-service, with confirmed anchor customers including Anthropic and Meta, could extend that runway materially if enterprise inference workloads continue migrating to Google infrastructure.

The less obvious plays are in the supply chain. TPU 8t and 8i are both targeting TSMC 2nm manufacturing, with Broadcom designing the training chip and MediaTek the inference chip. TSMC may remain a critical enabler regardless of which chip architecture gains share in each cycle, as may advanced packaging suppliers, liquid cooling companies and data centre real estate investment trusts (REITs).

Power infrastructure, liquid cooling suppliers and data centre REITs may also be exposed to sustained capital expenditure growth. Combined hyperscaler capital expenditure from the four major cloud providers is tracking toward US$700 billion or more in 2026, nearly double the US$388 billion spent in 2025. That scale of investment, sustained over multiple years, represents a different kind of macro signal.

Supply chain plays: If neither NVIDIA nor Google “wins” the chip war outright, infrastructure may still benefit. TSMC already manufactures both Ironwood and the upcoming eighth-generation chips. Advanced packaging suppliers, liquid cooling companies and data centre REITs may benefit regardless of which chip architecture gains share in each cycle.

CFD trader focus
Key instruments to watch
NASDAQ 100
The primary read-across from major NVIDIA and hyperscaler results. Earnings surprises, in either direction, tend to move the index broadly.
USD/CNH
Captures tariff and trade policy sensitivity. Ongoing uncertainty has kept spreads elevated and positioning cautious.
US10Y
The 4.5% level has served as a reference point for technology valuations. A stronger-than-expected guidance print could be a catalyst worth monitoring.
General commentary only. This is not a trading signal or personal financial advice. CFD trading involves significant risk of loss. Past performance is not indicative of future results.

Where the risks sit

Higher AI infrastructure spending does not automatically translate into stock gains. Several factors complicate a straight line from “chip war” to “buy everything”.

Valuation risk
NVIDIA’s valuation has reflected high expectations for future growth. Any guidance shortfall, margin compression or sign of slower infrastructure demand could trigger a reassessment that would be felt across the sector.
The CUDA moat
NVIDIA’s deepest competitive advantage is not just hardware. It is the software ecosystem that millions of developers build on, and a decade of investment in libraries, tooling and workflows. Google’s TorchTPU initiative is a deliberate attempt to lower that switching cost, but ecosystems are slow to move. This is the risk that is easiest to underestimate.
Execution risk
Google has announced impressive chips before. Ironwood is now generally available. The eighth-generation chips are previewed. Delivering them at scale, on time, to external enterprise customers with commercial-grade service commitments is a different challenge from announcing impressive specifications.
Market share versus revenue
As AMD, Google and Amazon gain share, NVIDIA’s percentage of a rapidly growing market may fall even as its absolute revenue continues to grow. Investors evaluating the competitive thesis should distinguish between share erosion and revenue impact. They are not the same.

What investors might take away

The AI chip war is not a story of one winner and one loser. It is a story of a market that is too large and too strategically important for any single company to own indefinitely.

NVIDIA built its lead through genuine technical excellence and a decade of software investment. That lead is real, and near-term earnings are likely to continue reflecting it.

But the challengers are no longer startups with benchmark slides. They are trillion-dollar companies with their own silicon, their own cloud infrastructure and every incentive to reduce their dependency on a single supplier, along with the capital expenditure commitments to show they are following through.

One way to frame the longer-term question is this: demand for AI compute may not be the primary variable for investors to focus on. Who captures the margin from that demand, and at what valuation multiple, may matter just as much. Those are questions each investor may need to weigh against their own risk profile and objectives.

Scenario Disclaimer: The "Next 30 days" and "Next 3 months" scenarios are illustrative "what-if" models for stress-testing a market thesis and identifying potential catalysts. They do not constitute a house view, forecast, guarantee, or prediction of future market movement. Any Brent price targets, Fed policy references, or other market benchmarks are hypothetical only. Real-world conditions are subject to volatility and unforeseen shifts.

GO Markets
May 20, 2026
what is a K-shaped consumer economy
K-shaped consumer explained for traders
how consumer spending affects CFD markets
CFD trading signals from earnings season
Australian CFD traders US consumer stocks
how credit stress affects consumer stocks
K-shaped economy and AUD/USD
AI
Shares
K-shaped consumer explained: CFD watchlist signals for 2026

The “resilient consumer” line being recycled across earnings calls is doing a lot of work. Index-level data helps it along. Headline retail sales hold. Spending looks firm. Stop reading there and the story looks simple.

But it is not.

Underneath sits a split-screen economy, the K-shape, where one consumer is carried by asset wealth, US large-cap exposure and the AI rally, while another is stuck with the less glamorous arithmetic of petrol, credit card minimums and a car loan that gets harder to service with each statement.

For CFD traders, the average is the problem. What matters is which side of the K a stock, sector or currency pair is exposed to, because that is where margins, earnings guidance, single-stock CFDs, index performance, commodities and FX may start telling a more divided story.

The big "K"

The "K" is just a chart shape. One arm angles up. The other angles down. Apply that shape to households and you get a workable model of who is benefiting from the current cycle, and who is being squeezed by it.

The upper arm, where asset wealth is doing the heavy lifting

The upper arm is asset-rich. These households own homes, hold the bulk of equity exposure and have benefited from the AI-linked rally in US large-cap equities. Net worth has been rising faster than inflation, which means their spending may be less price-sensitive and less reliant on borrowing. Roughly 87 per cent of all US equities sit with the top 10 per cent of households and that concentration matters when markets rally, because the wealth effect lands in fewer pockets than people assume.

The K-shaped consumer One economy, two very different households
Upper arm
Wealth is still growing
+28%
US equity wealth, 12 months
Growth: Big Tech and AI stocks have helped wealth grow
Spending: Higher earners are still spending freely
Demand: Luxury and travel demand remain strong
Lower arm
Budgets are under pressure
2010
Auto loan stress near post-GFC highs
Prices: Much higher than levels seen in 2021
Credit: Card stress is rising across households
Timing: Pressure builds before headline data updates
Bull case
Rate cuts may give some relief
Caution
Stress could weaken broader spending
Disclaimer: This graphic is for general informational purposes only and presents scenario-based commentary, not financial advice or a recommendation to buy, sell or hold any security or financial product. References to equity wealth growth, auto-loan stress, household credit conditions and consumer spending are based on available Federal Reserve and New York Fed data as at May 2026 and may be revised. Historical comparisons and market performance, including AI-related equity gains, are not reliable indicators of future outcomes. Actual consumer, market and economic conditions may differ materially from those implied by the “Bull Case” or “Caution” scenarios.
The lower arm, where pressure shows up first

The lower arm tells a different story. With official US inflation still around 3.7 per cent, lower-income earners are spending more on essentials and falling back on credit. Auto loan delinquencies have climbed to their highest level since 2010.

That is not a recession signal on its own. It is a strain signal. And because strain rarely stays neatly contained, it can start to show up in the spending mix before it shows up in the headline data.

The clue markets cannot ignore

The punchline is this: the top 20 per cent of US earners now account for more than 60 per cent of total retail spend. Once you internalise that, a lot of consumer-stock charts start to make more sense.

USD IN FOCUS

Manage your catalysts

Prepare for upcoming events and review your approach before trading.

We have been here before

Same K-shape, faster upper arm

The split is not new, after all markets have seen versions of this before, because every few cycles, the same uncomfortable pattern comes back into view: one part of the consumer economy keeps moving, while another starts to drag.

Same K-shape,

faster upper arm

The K-shape is not new. What is different in 2026 is the speed and concentration of the upper arm. AI-linked equity wealth has supercharged the asset-rich consumer faster than in any earlier dispersion cycles.

~35%
~40%
~43%
~49%
01 · Dot-com Era

First sustained dispersion

Top 5 per cent income growth ran 4.1 per cent a year. Equity ownership began to concentrate significantly, marking the first modern iteration of the split.

Sources: Moody’s Analytics review of Federal Reserve data via Bloomberg, Sept 2025. Pew Research Center. IMF Finance & Development. Federal Reserve FEDS Notes.

Why the K-shape matters for CFDs

Aggregate data, such as headline retail sales, total consumer credit and broad index moves, averages everyone together. In a single-consumer economy, that average is useful but in a K-shaped economy, the average can mislead. What matters is which side of the K a company sits on and whether the price reflects that.

How the K reaches your screen
Step 01
Customer mix splits
Upper and lower arms spend differently.
Step 02
Earnings diverge
Margins, guidance, and credit profiles split.
Step 03
CFDs reprice
Where the trader sees the move on platform.
A simplified transmission view. Real-world price moves reflect many overlapping macroeconomic drivers.

That changes the way three things behave.

1. Dispersion: Two stocks in the same sector can post very different earnings depending on who their customer is. An index move can mask that. A single-stock CFD does not. A luxury retailer and a value retailer may both sit inside the consumer universe, but they are not trading the same household balance sheet. A premium travel name and a budget operator may both report on travel demand, but the customer mix can make the earnings story very different.

For traders, the sector label is only the first layer. The customer base is the second.

2. Margin pressure: Companies serving the lower arm may be increasingly forced to discount. PepsiCo, for example, has cut prices on certain snack lines by around 15 per cent. Margin compression at the bottom often does not show up in headline beats. It can show up later in guidance.

That is where CFD traders need to be careful with the first read. A company can beat revenue expectations and still guide cautiously if it had to protect volume with promotions, price cuts or weaker margins.

3. Credit signals: Big banks publish their own K-shaped commentary every quarter. JPMorgan’s recent quarterly update flagged that higher-income borrowers are holding up while lower-income cohorts are showing more strain in credit card charge-offs. JPMorgan reported managed revenue of US$50.5 billion in its most recent quarter. The headline is one thing. The K-shaped colour commentary inside the release is another.

That kind of language has, in past cycles, preceded a wider repricing of consumer-facing names. It does not guarantee one this time.

CFD sector examples

One way to analyse the K-consumer theme is to compare companies in pairs rather than looking only at single names. This is not about deciding which stock is good or bad. It is an illustrative way to compare how different customer bases may influence market commentary and price behaviour.

The CFD trader's watchlist
SectorUpper-armLower-armMonitoring
RetailLVMH, HermèsWalmart, TJXPricing power
TravelDelta, MarriottSpirit AirlinesLoad factors
AutosFerrari, PorscheFord, GMFinancing stress
HousingToll BrothersRocket CompaniesAffordability

Source attribution and disclaimer: Data and examples are drawn from S&P Global Market Intelligence, Federal Reserve Distributional Financial Accounts, ASX company announcements, RBA household credit data, PepsiCo’s February 2026 strategic update and Wesfarmers’ 2026 half-year results. Companies are categorised by their primary revenue-generating demographic based on recent annual reporting. The “CFD Trader’s Watchlist” is provided for general information and educational commentary only. Company names are used to illustrate the “K-shaped consumer” theme and are not financial advice, a recommendation, or a solicitation to buy, sell or hold any security, CFD, derivative or other financial product.

How the split reaches APAC screens

For Australian CFD traders, the K-consumer theme can reach local screens through three channels the US names alone do not capture:

1. Direct ASX read-throughs

The APAC tab in the watchlist maps the K onto Australian consumer names. Wesfarmers does most of the heavy lifting, because Kmart and Bunnings sit on opposite arms of the same business. Endeavour and Coles play discretionary against defensive in staples. Flight Centre and Webjet do the same in travel. Macquarie and Latitude split the credit story.

2. The China-luxury feedback loop

The upper arm is not only a US story. LVMH, Hermès and Richemont sit downstream of the high-end Chinese consumer. A softer luxury read in Asia can move broader risk appetite, mining sentiment and AUD/USD before it shows up in US data, which is why luxury can be an early signal.

3. AUD/USD as the macro carrier

A stretched US lower arm may push the Federal Reserve toward a more dovish stance. That could pressure the US dollar and support AUD/USD, depending on commodity sentiment and the RBA. The K-consumer story is not always a retail story. Sometimes it shows up in FX first.

Forward outlook

How the theme could play out

Base

Bank charge-off rates and discretionary retailer guidance start to confirm or unwind the dispersion narrative.

Upside

AI-linked equity gains keep feeding the wealth effect at the top end.

Downside

The next consumer credit report shows further deterioration in lower-income cohorts.

Watch list

Fed commentary on financial conditions, US consumer credit prints, bank earnings language and ASX consumer names.

Base

The K persists into mid-year, with broad indices continuing to mask it.

Upside

Rate cuts begin lifting both arms unevenly, with rate-sensitive, lower-income households getting some relief.

Downside

A sustained Brent move above US$120 pressures mid-tier discretionary spend and forces earnings downgrades.

Watch list

Fed dot plot revisions, oil supply shocks, retailer guidance, China luxury demand, AUD/USD and mining sentiment.

Scenario disclaimer: The “Next 30 days” and “Next 3 months” scenarios are illustrative “what-if” models for stress-testing a market thesis and identifying potential catalysts. They are not a house view, forecast, guarantee, or prediction of future market movement. Any Brent price targets, Fed policy references, or other market benchmarks are hypothetical only.

Continue Reading
Failure paths

Where the framework could break

Upper-arm reversal

If the AI rally rolls over, upper-arm spending could weaken faster than the data has suggested.

China factor

Luxury demand can weaken if China's high-end consumer slows.

Energy reversal

If energy prices fall rather than spike, the lower-arm squeeze eases and the dispersion trade unwinds.

AUD/USD divergence

AUD/USD can move against expectations if commodity prices fall or the RBA deviates from global policy paths.

Already priced in

By the time a theme is widely discussed, much of the move may already be priced into the instruments.

Execution

CFDs are leveraged. Wider dispersion can mean larger gap risk around earnings and tighter conditions for stop placement.

General information only. Scenarios are illustrative. Real-world conditions are subject to volatility and unforeseen shifts.

The bottom line

The K is not a forecast. It is a lens. It forces the question headline data ignores: whose consumer am I actually trading?

For CFD traders, answering that can be the difference between an index move and a single-stock CFD that tells the opposite story.

The next test is threefold:

  1. Earnings: Does upper-arm demand hold as luxury and tech reports land?
  2. Energy: Does Brent stay contained below US$90, or does a spike further squeeze the lower-arm budget?
  3. Credit: Does bank commentary continue to flag the income split JPMorgan called out this quarter?

The work is not to predict the break. It is to decide your response before it happens. By the time the headline lands, the price, and the opportunity, may have already moved.

Next week: Tesla, AI infrastructure and how the same dispersion logic plays out one layer up the stack.

Make your next move count

Stay sharp with watchlists, charts and alerts as conditions change.

GO Markets
May 6, 2026
AI
US Earnings
US earnings preview: Wall Street wants answers from Meta, Amazon and Apple

We have spent the last three instalments of this series mapping the plumbing of the 2026 economy: the banks that anchor the capital, the utilities that supply the electrons, and the chipmakers building the silicon. As the April reporting season moves into its final act, attention shifts to the front door.

Meta, Amazon and Apple sit at the point where the AI buildout meets everyday consumers and businesses.

Why return on investment is now the focus

A hard divide, sometimes called the “Great Dispersion”, is opening between companies that enable AI and companies that monetise it. Meta and Amazon are at the centre of a massive capital expenditure (capex) cycle, against an estimated industry-wide spend of roughly US$650 billion to US$700 billion in 2026.

That is why return on investment (ROI) metrics are front of mind.

  1. Is Meta’s AI-driven ad targeting strong enough to justify its spending programme?
  2. Is Amazon Web Services (AWS) re-accelerating fast enough to support the custom silicon push?
  3. Can Apple hold its premium valuation by showing the iPhone 17 cycle is real, even in a more difficult Chinese market?

In 2026, the question is no longer only who can build the data centres. It is who can turn those investments into sustainable, high-margin profit. With energy markets calmer after the recent ceasefire, technology valuations have had some room to breathe. Now the market wants evidence.

IMPORTANT: REPORTING SCHEDULES CAN CHANGE WITHOUT NOTICE. REPORTING DATES AND RELEASE TIMES ARE FROM COMPANY INVESTOR RELATIONS CALENDARS WHERE MARKED CONFIRMED; OTHERWISE THEY ARE GO MARKETS ESTIMATES. CONSENSUS EPS, REVENUE AND ANALYST-RANGE DATA ARE FROM THIRD-PARTY MARKET CONSENSUS SOURCES, AS OF 20 APRIL 2026 (AEST). COMPANY GUIDANCE, BACKLOG AND OPERATING METRICS ARE FROM THE LATEST COMPANY FILINGS OR RESULTS PRESENTATIONS UNLESS STATED OTHERWISE. FIGURES AND SCHEDULES MAY CHANGE WITHOUT NOTICE.

$META | Q1 2026 REPORTING PERIOD

Meta Platforms, Inc.

NASDAQ | Technology/Advertising | 29 Apr 2026
✓ CONFIRMED

Global Release Countdown (AMC)

00:00:00:00
Reported EPS
US$10.44
Reported Revenue
US$56.31bn
AUSTRALIA/ASIA 30 Apr | 6:05 am
US/LATAM 29 Apr | 4:05 pm
Market intelligence: $META

Analysis: Meta price drivers and scenarios

Ad click improvement (est.)
+3–5%
From AI-driven targeting
2026 capex estimate
~US$135bn
Market estimate range
Silicon strategy
MTIA 2nm
Broadcom co-development
Strategy note

What is MTIA 2nm? This is Meta's "home-grown" AI chip. The 2nm refers to ultra-advanced, high-efficiency technology. By building their own silicon with Broadcom, Meta aims to slash their massive electricity bills and end their total reliance on buying expensive NVIDIA hardware. If this works, it protects Meta's profit margins even if they keep spending billions on AI.

AVG
LOW US$6.30 AVG US$6.69 HIGH US$7.10

Meta has moved from its "Year of Efficiency" into what CEO Mark Zuckerberg calls the "Era of Personal Superintelligence". By April 2026, AI appears to have sharpened the company’s core advertising engine, with some reports suggesting ad click rates rose by around 3% to 5%. But the bigger strategic issue is Meta’s multi-year Broadcom partnership to co-develop custom 2nm MTIA chips, with the aim of reducing reliance on NVIDIA and lowering operating costs over time. The risk is that Meta could beat on earnings and still disappoint if management points to higher spending and a longer payoff period. The real question is whether efficiency gains are keeping pace with the capital expenditure (capex) bill.

Call focus and key signals

The Avocado AI model
Watch for ad click improvements tied to the "Avocado" AI model deployment, currently estimated to be lifting rates by up to 5%.
Signal: Monetisation efficiency
MTIA rollout status
Updates on the custom 2nm MTIA chip rollout with Broadcom will indicate Meta's long term cost structure flexibility.
Watch: Infrastructure independence
Reality Labs losses
Evidence of Reality Labs loss stabilisation would reduce the persistent drag on the overall earnings story.
Watch: Operating loss trend
Capex vs efficiency
The real question for investors is whether efficiency gains are keeping pace with the significant capex bill.
Signal: Spending productivity
Sentiment analysis: Meta Platforms

Interactive scenario analysis: $META

Select earnings outcome
Productive cycle

Spending cycle becomes productive

EPS above US$7.10, double-digit ad growth, and clear early efficiency gains from MTIA. The market may interpret that as a sign the spending cycle is becoming more productive rather than simply more expensive.
EPS level
Above US$7.10
Ad growth
Double digit
Efficiency
MTIA gains
Reaction
Strong rally
Sources & Data Methodology

Sources: Reporting dates and release times are from company investor relations calendars where marked Confirmed; otherwise they are GO Markets estimates. Consensus EPS, revenue and analyst-range data are sourced from Bloomberg and Earnings Whispers, as at 20 April 2026 (AEST). Company guidance, backlog and operating metrics are sourced from the latest company filings or results presentations. Any scenario analysis reflects GO Markets analysis. Figures and schedules may change without notice.

Expanded Coverage

Beyond the chipmakers

As the "show me the money" year unfolds, discover how AI demand is impacting Tesla, NextEra, and Exxon.

Amazon: the capex bet moves to centre stage

Amazon is no longer just a retail story. It is increasingly a cloud and advertising business, with a thin-margin logistics network attached. In 2026, the narrative is centred on what reports have described as a roughly US$200 billion capex plan, aimed largely at building out AWS’s AI infrastructure.

$AMZN | Q1 2026 REPORTING PERIOD

Amazon.com, Inc.

NASDAQ | Technology/Retail | 29 Apr 2026
✓ CONFIRMED

Global Release Countdown (AMC)

00:00:00:00
Reported EPS
US$2.78
Reported Revenue
US$181.5bn
AU/ASIA 30 Apr | 6:00 am
US/LATAM 29 Apr | 4:00 pm
Market Intelligence: $AMZN

Analysis: Amazon price drivers and scenarios

AWS growth threshold
20% YoY
Market floor expectation
2026 Capex plan (est.)
~US$200bn
Largely AWS AI infrastructure
Custom silicon
Trainium 3 and 4
In-house AI chip pipeline
AVG
LOW US$1.50 AVG US$1.69 HIGH US$1.90

Amazon is no longer primarily a retail story. In 2026, the narrative centres on approximately US$200 billion in planned capex, directed largely at building out AWS's AI infrastructure. That is an extraordinary commitment, and the market is watching closely to see whether the returns are following. One metric matters most: AWS growth.

Key signals to watch

AWS growth rate
Anything materially below 20% YoY could reinforce the bear case that spending is running well ahead of returns.
Watch: AWS growth vs 20% floor
Trainium supply commitments
Early supply commitments for Trainium 3 and 4 would signal how quickly the transition to in-house chips is progressing.
Watch: Trainium 3 and 4 progress
Retail margins under tariff pressure
Management commentary on whether Section 122 tariff costs are being absorbed or passed on is vital for the non-AWS story.
Watch: Retail operating margin
Advertising segment momentum
Sustained growth here provides a high-margin earnings cushion if retail margins are squeezed by logistics or tariffs.
Watch: Advertising revenue growth
Sentiment Analysis · Amazon.com Inc.

Interactive scenario analysis: $AMZN

Select earnings outcome
Investment Landing

Spending cycle lands well

EPS above US$1.90 and AWS growth above 24% with firmer retail margins. The market interprets this as proof the massive investment cycle is delivering efficient returns.
EPS Level
Above US$1.90
AWS Signal
Above 24%
Retail Margin
Firmer
Reaction
Positive rally
Sources & Data Methodology

Sources: Reporting dates and release times are from company investor relations calendars where marked Confirmed; otherwise they are GO Markets estimates. Consensus EPS, revenue and analyst-range data are sourced from Bloomberg and Earnings Whispers, as at 20 April 2026 (AEST). Company guidance, backlog and operating metrics are sourced from the latest company filings or results presentations. Any scenario analysis reflects GO Markets analysis. Figures and schedules may change without notice.

Apple: quality still needs proof

Apple has looked like the defensive favourite in hardware, helped by record free cash flow (FCF) of US$43.64 billion and the strength of its Services segment. But the latest debate is whether that defensive status can turn back into growth. Third-party shipment data has indicated a roughly 20% rise in China for iPhone 17, challenging the idea that the market is already mature.

$AAPL | Q2 FY2026 REPORTING PERIOD

Apple Inc.

NASDAQ | Consumer Technology | 30 Apr 2026
✓ CONFIRMED

Global Release Countdown (AMC)

00:00:00:00
Consensus EPS
US$1.91
Consensus Revenue
~US$109.0bn
AU/ASIA 01 May | 6:30 am
US/LATAM 30 Apr | 4:30 pm
Market intelligence: $AAPL

Analysis: Apple price drivers and scenarios

Free cash flow (FCF)
US$43.6bn
Record, prior period
Services run-rate target
~US$30bn
Quarterly revenue approach
China iPhone 17 shipments
+~20%
Third-party data estimate
AVG
LOW US$1.70 AVG US$1.91 HIGH US$1.94

Apple is still widely seen as a quality print, but expectations are higher now. Margin resilience alone is no longer enough. The market wants evidence that Apple Intelligence, the company’s on-device AI platform, can extend the upgrade cycle and support more recurring, high-margin Services revenue over time.

Key signals to watch

iPhone 17 demand in China
China remains the most closely watched variable. Third-party data has pointed to growth of around 20%, but earnings will provide the first company-sourced data point.
Watch: China revenue growth
Services revenue trajectory
Services is approaching a US$30 billion quarterly run rate and carries structurally higher margins. Further acceleration reduces reliance on iPhone cycle volatility.
Watch: Services revenue vs US$30bn
Apple Intelligence rollout
On-device AI is a key upgrade catalyst. Management commentary on adoption, features and international timing will shape refresh cycle expectations.
Watch: Apple intelligence milestones
Gross margin
Apple guided to a 48% to 49% range. Holding near the top signals product mix strength. A result below 48% raises questions about cost pressure.
Watch: Gross margin vs 48% to 49%
Sentiment analysis: Apple Inc.

Interactive scenario analysis: $AAPL

Select report outcome
Growth support

Support for growth narrative

EPS above US$1.94, firmer China iPhone 17 data and gross margin above 49%. The market may interpret that as support for the higher-quality growth narrative and validate the thesis that Apple Intelligence is beginning to drive a meaningful upgrade cycle.
EPS level
Above US$1.94
China demand
Firmer
Gross margin
Above 49%
Reaction
Bullish move
Sources & Data Methodology

Sources: Reporting dates and release times are from company investor relations calendars where marked Confirmed; otherwise they are GO Markets estimates. Consensus EPS, revenue and analyst-range data are sourced from Bloomberg and Earnings Whispers, as at 20 April 2026 (AEST). Company guidance, backlog and operating metrics are sourced from the latest company filings or results presentations. Any scenario analysis reflects GO Markets analysis. Figures and schedules may change without notice.

Thematic risks

What could shift the picture

Three risks could change the narrative, regardless of how the numbers print.

1. Spending without visible returns

Meta and Amazon are both running enormous capex programmes, with payoff periods that stretch well beyond a single quarter. If either company delivers an in line or weaker result while also lifting full year spending guidance, the market may start to see the gap between investment and return as a structural issue rather than a temporary one. That would matter for the sector as a whole, not just for one stock.

2. China as a variable, not a constant

Apple's China story has shown some resilience in third party data, but it remains sensitive to trade policy, consumer confidence and local competition. Any signal from management that demand is softening faster than expected, or that local rivals are gaining meaningful share in the mid range and premium segments, could reset the earnings growth outlook more quickly than consensus currently assumes.

3. The K-shaped consumer backdrop

In a market where higher income consumers are holding up while lower income groups remain under pressure, ad spending patterns and device upgrade cycles can diverge sharply from headline averages. If Meta's ad pricing weakens because smaller businesses pull back, or if Apple's upgrade cycle is concentrated within a narrower demographic, results could disappoint even with broadly stable macro conditions.

Note: These thematic risks may influence sector wide risk appetite independently of headline EPS results.
The bottom line

The 2026 reality check

As this earnings season moves towards its close, the story is shifting away from survival and towards operational execution in the intelligence era.

$META

AI ad efficiency is facing its biggest test yet. Can the Broadcom silicon bet start to show up in margins?

$AMZN

AWS re-acceleration remains the critical signal. A US$200 billion capex push needs a growth rate to match.

$AAPL

Quality still needs proof. Apple Intelligence has to show it can extend the upgrade cycle, not just refresh it.

For Meta, Amazon and Apple, the test is whether heavy investment in silicon, models and infrastructure is turning into measurable cash flow and durable margins. In a more uneven economy, the market appears to be rewarding companies that can show real demand and clearer monetisation. The earnings numbers matter, but management commentary on the return on that investment may matter more.

Your next earnings setup starts here

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GO Markets
April 20, 2026
Microsoft, Alphabet and NVIDIA sit at the centre of the AI infrastructure buildout, from cloud and enterprise software to custom chips and data-centre demand. Their upcoming results may help show whether heavy capital spending is translating into revenue, margins and durable competitive advantage.
AI
US Earnings
Are Microsoft, Alphabet and NVIDIA about to show whether AI is worth the cost?

April's US earnings season is landing in a market that wants more than a good story. JPMorgan has already set a high bar with a strong result, and attention is now shifting to the engine room of the S&P 500: AI infrastructure. Three companies are at the centre of that story.

Why this earnings window matters for AI

Microsoft, Alphabet and NVIDIA are not just participants in the AI cycle, they are building the physical and software architecture that other companies depend on: the chips, the cloud regions, the models and the tools. If this spending is going to deliver returns, the first signs may start to show in their quarterly results over the next few weeks.

Each company represents a different test.

  1. Microsoft: Whether enterprise AI adoption is translating into revenue and margin expansion
  2. Alphabet: Whether owning the full stack, from chips to cloud to distribution, is a durable advantage or simply an expensive position to defend
  3. NVIDIA: Whether the hardware cycle is still holding, accelerating or starting to level out

In 2026, the question is no longer whether AI investment is happening, the capital commitments are substantial and already publicly stated. The question is whether that spending is generating returns quickly enough to justify the scale of those bets.

IMPORTANT: REPORTING SCHEDULES CAN CHANGE WITHOUT NOTICE. REPORTING DATES AND RELEASE TIMES ARE FROM COMPANY INVESTOR RELATIONS CALENDARS WHERE MARKED CONFIRMED; OTHERWISE THEY ARE GO MARKETS ESTIMATES. CONSENSUS EPS, REVENUE AND ANALYST-RANGE DATA ARE FROM THIRD-PARTY MARKET CONSENSUS SOURCES, AS OF 16 APRIL 2026 (AEST). COMPANY GUIDANCE, BACKLOG AND OPERATING METRICS ARE FROM THE LATEST COMPANY FILINGS OR RESULTS PRESENTATIONS UNLESS STATED OTHERWISE. FIGURES AND SCHEDULES MAY CHANGE WITHOUT NOTICE.

$MSFT | Q1 2026 REPORTING PERIOD

Microsoft Corporation

NASDAQ | Technology | 29 Apr 2026
Confirmed

Global Release Countdown (AMC)

00:00:00:00
Consensus EPS
US$4.04
Consensus Revenue
US$81.40bn
AU/ASIA 30 Apr | 6:05 am
US/LATAM 29 Apr | 4:05 pm
Market Intelligence: $MSFT

Analysis: Microsoft price drivers and scenarios

Azure Growth Target
37-38%
Constant currency projection
AI Contribution
+6-8 pts
Azure revenue from AI services
FY26 Capex
US$146bn
Total infrastructure spending
AVG
LOW US$3.86 AVG US$4.04 HIGH US$4.14

Microsoft is being tested on a specific question: can it turn heavy AI spending into margin expansion? A result above US$4.14 could ease concerns over "capex fatigue" and demonstrate whether Azure growth is re-accelerating alongside enterprise AI adoption.

Factors that could move the markets

Azure growth rate
Watch if constant-currency growth re-accelerates above 39%, suggesting AI workloads are filling new capacity rather than sitting idle.
Signal: Capacity Utilisation
Workplace agent adoption
The shift to autonomous agents is central. Clear enterprise uptake in Dynamics 365 supports the high-tier subscription thesis.
Signal: Software Monetisation
Maia 200 cost savings
If the in-house AI chip is lowering inference costs at production levels, gross margins may start to recover from recent compression.
Watch: Gross Margin Recovery
Regulatory backdrop
Ongoing scrutiny of cloud bundling practices remains a potential headwind; management commentary here is vital for the long-term view.
Watch: Bundling Compliance
Sentiment Analysis · Microsoft Corp.

Interactive scenario analysis: $MSFT

Select earnings outcome
AI Scaling Proof

Strong result, backed by real AI progress

EPS above US$4.14 and Azure re-acceleration above 39% could support the view that AI spending is starting to translate into commercial returns. Workplace Agents show measurable ROI and FY26 guidance is raised.
EPS Outcome
Above US$4.14
Cloud Signal
Accelerating
Guidance
Raised
Possible reaction
Strong rally
Sources & Data Methodology

Sources: Reporting dates and release times are from company investor relations calendars where marked Confirmed; otherwise they are GO Markets estimates. Consensus EPS, revenue and analyst-range data are sourced from Bloomberg and Earnings Whispers, as at 16 April 2026 (AEST). Company guidance, backlog and operating metrics are sourced from the latest company filings or results presentations. Any scenario analysis reflects GO Markets analysis. Figures and schedules may change without notice.

Expanded Coverage

Beyond the Chipmakers

As the "show me the money" year unfolds, discover how AI demand is impacting Tesla, NextEra, and Exxon.

From enterprise software to search and cloud

Alphabet has transformed from a search business into a sprawling AI infrastructure play, and this result will test whether that transformation is delivering. The US$185 billion capex forecast for 2026 is extraordinary, close to double last year's spending. EPS is expected to decline slightly year on year, precisely because that infrastructure spending is consuming capital. The question is whether Google Cloud's growth is fast enough to show a credible path back to margin recovery, and whether Ironwood, the seventh-generation custom AI chip, is proving its cost-per-query advantage at scale.

$GOOGL | Q1 2026 REPORTING PERIOD

Alphabet Inc.

NASDAQ | Technology | 29 Apr 2026
Confirmed

Global Release Countdown (AMC)

00:00:00:00
Consensus EPS
US$2.64
Consensus Revenue
US$92.14bn
AU/ASIA 30 Apr | 6:30 am
US/LATAM 29 Apr | 4:30 pm
Market Intelligence: $GOOGL

Analysis: Alphabet price drivers and scenarios

Cloud growth
48% YoY
Compared with last quarter
Ironwood TPU
10x peak
Vs previous-generation chip
2026 Capex
US$185bn
Double last year's spending
AVG
LOW US$2.50 AVG US$2.64 HIGH US$2.80

Alphabet has shifted to being viewed as a broader AI infrastructure play. The question is whether Cloud growth can support a path back to margin recovery while the massive US$185bn infrastructure buildout absorbs capital.

Factors that could move the markets

Google Cloud momentum
Markets are watching if the 48% growth rate holds, specifically among customers using Ironwood TPUs for large-scale AI.
Signal: Enterprise AI Adoption
Search & AI overview
If compute-intensive AI summaries are monetising through ads, it supports core search economics in the AI era.
Focus: Search Economics
Capex & margin trajectory
With free cash flow under pressure from US$185bn capex, markets want to know when infrastructure investment will moderate.
Watch: Spending Ceiling
DOJ antitrust risk
Management commentary on the legal timeline for Chrome or Android divestiture appeals will influence how risk is priced.
Watch: Regulatory Remedies
Sentiment Analysis · Alphabet Inc.

Interactive scenario analysis: $GOOGL

Select earnings outcome
Efficiency Proof

Ironwood efficiency drives upside

EPS above US$2.80 and cloud growth above 45% suggest Ironwood is cutting costs and strengthening Google’s advantage faster than expected.
EPS outcome
Above US$2.80
Cloud Signal
Strong growth
Waymo
Accelerating
Reaction
Sentiment improves
Sources & Data Methodology

Sources: Reporting dates and release times are from company investor relations calendars where marked Confirmed; otherwise they are GO Markets estimates. Consensus EPS, revenue and analyst-range data are sourced from Bloomberg and Earnings Whispers, as at 16 April 2026 (AEST). Company guidance, backlog and operating metrics are sourced from the latest company filings or results presentations. Any scenario analysis reflects GO Markets analysis. Figures and schedules may change without notice.

NVIDIA: the hardware cycle read through

NVIDIA is no longer simply a chip company. It has become what analysts now describe as the central bank of compute, the entity whose product determines how much AI capacity the world can actually deploy.

The upcoming Q1 FY2027 result will test whether the new Vera Rubin R100 GPU architecture, which entered mass production ahead of schedule, is already contributing to revenue, and whether NVIDIA can sustain gross margins above 75% as inference, rather than training, becomes the dominant workload. Inference is more competitive and more price-sensitive than training, so margin resilience here matters.

$NVDA | Q1 2026 REPORTING PERIOD

NVIDIA Corporation

NASDAQ | Semiconductors | 20 May 2026
Confirmed

Global Release Countdown (AMC)

00:00:00:00
Reported EPS
US$1.87
Reported Revenue
US$81.62bn
AU/ASIA 21 May | 6:30 am
US/LATAM 20 May | 4:30 pm
Market Intelligence: $NVDA

Analysis: NVIDIA price drivers and scenarios

Revenue growth
73% YoY
Last quarter benchmark
Data centre share
91%+
Share of total revenue
Rubin R100
In production
Mass production began April 2026
AVG
LOW US$76bn AVG US$78bn HIGH US$81bn+

NVIDIA’s outlook depends on whether Rubin R100 can keep gross margins above 75% as inference becomes a bigger part of demand. Because inference is more price-sensitive than training, margins are the key test.

Factors that could move the markets

Rubin ramp-up
Watch whether Rubin production can scale smoothly without disrupting the Blackwell transition.
Signal: supply chain continuity
Inference margins
The key test is whether NVIDIA can keep gross margins above 75% as inference revenue grows.
Signal: pricing power holds up
Sovereign AI demand
Government-backed investment in Europe and the Middle East could broaden the base beyond hyperscalers.
Signal: market expansion
CUDA regulatory risk
Any US or European scrutiny of NVIDIA’s software advantage could move the stock regardless of the revenue result.
Signal: software moat under review
Sentiment Analysis · NVIDIA Corp.

Interactive scenario analysis: $NVDA

Select earnings outcome
Rubin ramp supports growth

Rubin ramp supports growth

Revenue above US$81 billion may suggest the Rubin ramp is tracking ahead of expectations. That could support the view that AI demand is broadening into sovereign AI and enterprise markets, helping extend visibility into 2027.
Revenue Outcome
Above US$81bn
Gross Margin
Above 75%
Workload
Inference strong
Reaction
Positive read-through
Sources & Data Methodology

Sources: Reporting dates and release times are from company investor relations calendars where marked Confirmed; otherwise they are GO Markets estimates. Consensus EPS, revenue and analyst-range data are sourced from Bloomberg and Earnings Whispers, as at 16 April 2026 (AEST). Company guidance, backlog and operating metrics are sourced from the latest company filings or results presentations. Any scenario analysis reflects GO Markets analysis. Figures and schedules may change without notice.

Why this reporting window matters for the broader market

Microsoft and Alphabet report on the same evening, 29 April, making the overnight session into 30 April one of the most information-dense points of the year for equity markets. For Australian traders, both results should be available by 6:30 am AEST on Thursday 30 April. That means price reactions may already be visible in US futures before the ASX opens.

NVIDIA reports later, in May, but it casts a long shadow over everything in between. The guidance the company gave for Q1 FY2027, US$78 billion in revenue, has set a benchmark the market has been tracking for months. If Microsoft and Alphabet's results suggest AI infrastructure demand has softened, that could reset expectations heading into NVIDIA's call. If both beat expectations and signal accelerating cloud growth, that could lift the floor for what NVIDIA may report.

That interconnection is what makes this cluster different from most earnings windows. The results do not just affect the individual companies. They also signal the health of an investment supercycle that has driven global equity market leadership for the past two years.

What could shift the picture

Three risks could change the narrative regardless of how the numbers print. Each one is worth understanding before the results land.

1

Capex fatigue

If both Microsoft and Alphabet report in line or below expectations while reaffirming enormous spending plans, the market may start pricing the risk that AI monetisation is slower than the spending implies. That is not a stock-specific concern. It would be a broader de-rating event, affecting the valuations of companies across the technology sector that are priced on the assumption that AI returns are coming and coming soon.

2

Regulatory escalation

The FTC investigation into Microsoft, the DOJ case against Alphabet, and emerging EU scrutiny of NVIDIA's CUDA software ecosystem are all active. A material legal development before the earnings calls, whether a new filing, a remedy announcement or a court ruling, could overshadow the financial results entirely. Regulatory risk in this sector is not theoretical. It is live and moving.

3

Competition from custom silicon

Microsoft's Maia 200 chip, Alphabet's Ironwood TPU, Amazon's Trainium and Meta's custom accelerators are all reducing how much the large cloud companies depend on NVIDIA hardware. If any of these companies signals a meaningful shift in its GPU procurement plans during the earnings call, that could create uncertainty around NVIDIA's forward order book, even if its own Q1 FY2027 results beat expectations.

The 2026 Reality Check

$MSFT

AI spend is shifting from cost to competitive advantage. The question is whether margins can follow.

$GOOGL

Vertical integration from chips to search to cloud may prove to be a moat, or an expensive position to defend.

$NVDA

This is the pulse of the AI hardware cycle, and a test of whether Rubin can keep the supercycle alive into 2027.

Bottom Line

Microsoft and Alphabet report on the same evening, 29 April. NVIDIA follows in late May. Together, they may offer the clearest read yet on whether the AI infrastructure buildout is generating returns fast enough to justify the extraordinary scale of capital being committed. The earnings per share (EPS) number is important. What management says about AI monetisation timelines, capex trajectories and competitive positioning may matter more.

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GO Markets
April 16, 2026

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