How do dividend adjustments work on my Index CFD position?
Lachlan Meakin
20/9/2021
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Cash stock indices such as the Dow 30, FTSE 100 and ASX 200 are made up of constituent stocks which is where their price is derived from. These constituent stocks of an index will periodically pay dividends to shareholders, causing a drop in that stocks price and impacting the overall value of the index. With GO Markets this index adjustment will be made at the open of the index on the ex-dividend date of the underlying stock(s).
This price drop in the index will affect the PnL on an open index CFD trade, to compensate this, there will be credit or debit that will be included in the swap that is made around 00:00 server time. If you have a long index position you PnL will be negatively affected so you will receive a credit in the same amount as the dividend adjustment. If you have a short index position you PnL will be positively affected so you will receive a debit in the same amount as the dividend adjustment.
It’s an important point to remember that index traders do not profit or loss from these adjustments. It is a zero sum situation where any PnL change has a corresponding debit or credit to compensate. Example 1: You have a buy position on the ASX200 contract of 10 lots at 00:00 server time.
The next trading day multiple companies go ex-dividend resulting in a 20 point drop in the ASX200 at the open. The swap on this position will be credited $200 AUD (20 points * $10 per point exposure). The ASX200 will open 20 points lower than it would have without the adjustment.
As a result, the PnL on the buy position is $200 worse off, which was compensated for by the swap credit you received. Example 2: You have a sell position on the FTSE100 contract of 10 lots at 00:00 server time. The next trading day multiple companies go ex-dividend resulting in a 15 point drop in the FTSE100 at the next open.
The swap on this position will be debited £150 GBP (15 points * £10 per point exposure). The FTSE100 will open 15 points lower than it would have without the adjustment. As a result, the PnL on the sell position is £150 better off, which was compensated for by the swap debit you received. (Please note, as dividends are combined with normal financing adjustments, the swap will not be exactly the same as the dividend only) You can view the trading hours and upcoming swap/dividend adjustments in the specifications of an instrument.
Example of ASX200 before a 20 point adjustment below:
By
Lachlan Meakin
Head of Research, GO Markets Australia.
Disclaimer: Articles are from GO Markets analysts and contributors and are based on their independent analysis or personal experiences. Views, opinions or trading styles expressed are their own, and should not be taken as either representative of or shared by GO Markets. Advice, if any, is of a ‘general’ nature and not based on your personal objectives, financial situation or needs. Consider how appropriate the advice, if any, is to your objectives, financial situation and needs, before acting on the advice. If the advice relates to acquiring a particular financial product, you should obtain our Disclosure Statement (DS) and other legal documents available on our website for that product before making any decisions.
2025 has seen a material decline in the fortunes of the greenback. A technical structure breakdown early in the year was followed by a breach of the 200-day moving average (MA) at the end of Q1. The index then entered correction territory, printing a three-year low at the end of Q2.
Since then, we have seen attempts to build a technical base, including a re-test of the end-of-June lows in mid-September. However, buying pressure has not been strong enough to push price back above the technically critical and psychologically important 100 level.
What the levels suggest from here
As things stand, the index remains more than 10% lower for 2025. On this technical view, the index may revisit the 96 area. However, technical levels can fail and outcomes depend on multiple factors.
US dollar index
Source: TradingView
The key question for 2026
The key question remains: are we likely to see further losses in the early part of next year and beyond, or will current support hold?
We cannot assess the US dollar in isolation and any outlook is shaped by internal and global factors, not least its relative strength versus other major currencies. Many of these drivers are interrelated, but four potential headwinds stand out for any US dollar recovery. Collectively, they may keep downside pressure in play.
Four headwinds for any US dollar recovery
1. The US dollar as a safe-haven trade
One scenario where US dollar support has historically been evident is during major global events, slowdowns and market shocks. However, the more muted response of the US dollar during risk-off episodes this year suggests a shift away from the historical norm, with fewer sustained US dollar rallies.
Instead, throughout 2025, some investors appearedto favour gold, and at other times, FX and even equities, rather than into the US dollar. If this change in behaviour persists through 2026, it could make recovery harder, even if global economic pressure builds over the year ahead.
2. US versus global trade
Trade policy is harder to measure objectively, and outcomes can be difficult to predict. That said, trade battles driven by tariffs on US imports are often viewed as an additional potential drag on the US dollar.
The impact may be twofold if additional strain is placed on the US economy through:
a slowdown in global trade volumes as impacted countries seek alternative trade relationships, with supply chain distortions that may not favour US growth
pressure on US corporate profit margins as tariffs lift costs for importers
3. Removal of quantitative tightening
The Fed formally halted its balance sheet reduction, quantitative tightening (QT), as of 1 December 2025, ending a program that shrank assets by roughly US$2.4 trillion since mid-2022.
Traditionally, ending QT is seen as marginally negative for the US dollar because it stops the withdrawal of liquidity, can ease global funding conditions, and may reduce the scarcity that can support dollar demand. Put simply, more dollars in the system can soften the currency’s support at the margin, although outcomes have varied historically and often depend on broader financial conditions.
4. Interest rate differential
Interest rate differential (IRD) is likely to be a primary driver of US dollar strength, or otherwise, in the months ahead. The latest FOMC meeting delivered the expected 0.25% cut, with attention on guidance for what may come next.
Even after a softer-than-expected CPI print, markets have been reluctant to price aggressive near-term easing. At the time of writing, less than a 20% chance of a January cut is priced in, and it may be March before we see the next move.
The Fed is balancing sticky inflation against a jobs market under pressure, with the headline rate back at levels last seen in 2012. The practical takeaway is that a more accommodative stance may add to downward pressure on the US dollar.
Current expectations imply around two rate cuts through 2026, with the potential for further easing beyond that, broadly consistent with the median projections shown in the chart below. These are forecasts rather than guarantees, and they can shift as economic data and policy guidance evolve.
Source: US Federal Reserve, Summart of Economic Projections
The “Magnificent Seven” technology companies are expected to invest a combined $385 billion into AI by the end of 2025.
Microsoft is positioning itself as the platform leader. Nvidia dominates the underlying AI infra. Google leads in research. Meta is building open-source tech. Amazon – AI agents. Apple — on-device integration. And Tesla pioneering autonomous vehicles and robots.
The “Big 4” tech companies' AI spending alone is forecast at $364 billion.
With such enormous sums pouring into AI, is this a winner-take-all game?
Or will each of the Mag Seven be able to thrive in the AI future?
Microsoft: The AI Everywhere Strategy
Microsoft has made one of the biggest bets on AI out of the Mag Seven — adopting the philosophy that AI should be everywhere.
Through its deep partnership with OpenAI, of which it is a 49% shareholder, the company has integrated GPT-5 across its entire ecosystem.
Key initiatives:
GPT-5 integration across consumer, enterprise, and developer tools through Microsoft 365 Copilot, GitHub Copilot, and Azure AI Foundry
Azure AI Foundry for unified AI development platform with model router technology
Copilot ecosystem spanning productivity, coding, and enterprise applications with real-time model selection
$100 billion projected AI infrastructure spending for 2025
Microsoft’s centrepiece is Copilot, which can now detect whether a prompt requires advanced reasoning and route to GPT-5's deeper reasoning model.
This (theoretically) means high-quality AI outputs become invisible infrastructure rather than a skill users need to learn.
However, this all-in bet on OpenAI does come with some risks. It is putting all its eggs in OpenAI's basket, tying its future success to a single partnership.
Elon Musk warned that "OpenAI is going to eat Microsoft alive"[/caption]
Google: The Research Strategy
Google’s approach is to fund research to build the most intelligent models possible. This research-first strategy creates a pipeline from scientific discovery to commercial products — what it hopes will give it an edge in the AI race.
Key initiatives:
Over 4 million developers building with Gemini 2.5 Pro and Flash
Ironwood TPU offering 3,600 times better performance compared to Google’s first TPU
AI search overviews reaching 2 billion monthly users across Google Search
DeepMind breakthroughs: AlphaEvolve for algorithm discovery, Aeneas for ancient text interpretation, AlphaQubit for quantum error detection, and AI co-scientist systems
Google’s AI research branch, DeepMind, brings together two of the world's leading AI research labs — Google Brain and DeepMind — the former having invented the Transformer architecture that underpins almost all modern large language models.
The bet is that breakthrough research in areas like quantum computing, protein folding, and mathematical reasoning will translate into a competitive advantage for Google.
Today, we're introducing AlphaEarth Foundations from @GoogleDeepMind , an AI model that functions like a virtual satellite which helps scientists make informed decisions on critical issues like food security, deforestation, and water resources. AlphaEarth Foundations provides a… pic.twitter.com/L1rk2Z5DKk
Meta has made a somewhat contrarian bet in its approach to AI: giving away their tech for free. The company's Llama 4 models, including recently released Scout and Maverick, are the first natively multi-modal open-weight models available.
Key initiatives:
Llama 4 Scout and Maverick - first open-weight natively multi-modal models
AI Studio that enables the creation of hundreds of thousands of AI characters
$65-72 billion projected AI infrastructure spending for 2025
This open-source strategy directly challenges the closed-source big players like GPT and Claude. By making AI models freely available, Meta is essentially commoditizing what competitors are trying to monetize. Meta's bet is that if AI models become commoditized, the real value will be in the infrastructure that sits on top. Meta's social platforms and massive user base give it a natural advantage if this eventuates.
Meta's recent quarter was also "the best example to date of AI having a tangible impact on revenue and earnings growth at scale," according to tech analyst Gene Munster.
H1 relative performance of the Magnificent Seven stocks. Source: KoyFin, Finimize
However, it hasn’t been all smooth sailing for Meta. Their most anticipated release, Llama Behemoth, has all but been scrapped due to performance issues. And Meta is now rumored to be developing a closed-source Behemoth alternative, despite their open-source mantra.
Amazon: The AI Agent Strategy
Amazon’s strategy is to build the infrastructure for AI that can take actions — booking meetings, processing orders, managing workflows, and integrating with enterprise systems.
Rather than building the best AI model, Amazon has focused its efforts on becoming the platform where all AI models live.
Key initiatives:
Amazon Bedrock offering 100+ foundation models from leading AI companies, including OpenAI models.
$100 million additional investment in AWS Generative AI Innovation Center for agentic AI development
Amazon Bedrock AgentCore enabling deployment and scaling of AI agents with enterprise-grade security
$118 billion projected AI infrastructure spending for 2025
The goal is to become the “orchestrator” that lets companies mix and match the best models for different tasks.
Amazon’s AgentCore will provide the underlying memory management, identity controls, and tool integration needed for these companies to deploy AI agents safely at scale.
This approach offers flexibility, but does carry some risks. Amazon is essentially positioning itself as the middleman for AI. If AI models become commoditized or if companies prefer direct relationships with AI providers, Amazon's systems could become redundant.
Nvidia: The Infra Strategy
Nvidia is the one selling the shovels for the AI gold rush. While others in the Mag Seven battle to build the best AI models and applications, Nvidia provides the fundamental computing infrastructure that makes all their efforts possible.
This hardware-first strategy means Nvidia wins regardless of which company ultimately dominates. As AI advances and models get larger, demand for Nvidia's chips only increases.
Key initiatives:
Blackwell architecture achieving $11 billion in Q2 2025 revenue, the fastest product ramp in company history
New chip roadmap: Blackwell Ultra (H2 2025), Vera Rubin (H2 2026), Rubin Ultra (H2 2027)
Data center revenue reaching $35.6 billion in Q2, representing 91% of total company sales
Manufacturing scale-up with 350 plants producing 1.5 million components for Blackwell chips
With an announced product roadmap of Blackwell Ultra (2025), Vera Rubin (2026), and Rubin Ultra (2027), Nvidia has created a system where the AI industry must continuously upgrade to Nvidia’s newest tech to stay competitive.
This also means that Nvidia, unlike the others in the Mag Seven, has almost no direct AI spending — it is the one selling, not buying.
However, Nvidia is not indestructible. The company recently halted its H20 chip production after the Chinese government effectively blocked the chip, which was intended as a workaround to U.S. export controls.
Apple: The On-Device Strategy
Apple's AI strategy is focused on privacy, integration, and user experience. Apple Intelligence, the AI system built into iOS, uses on-device processing and Private Cloud Compute to help ensure user data is protected when using AI.
Key initiatives:
Apple Intelligence with multi-model on-device processing and Private Cloud Compute
Enhanced Siri with natural language understanding and ChatGPT integration for complex queries
Direct developer access to on-device foundation models, enabling offline AI capabilities
$10-11 billion projected AI infrastructure spending for 2025
The drawback of this on-device approach is that it requires powerful hardware from the user's end. Apple Intelligence can only run on devices with a minimum of 8GB RAM, creating a powerful upgrade cycle for Apple but excluding many existing users.
Tesla: The Robo Strategy
Tesla's AI strategy focuses on two moonshot applications: Full Self-Driving vehicles and humanoid robots.
This is the 'AI in the physical world' play. While others in the Mag Seven are focused on the digital side of AI, Tesla is building machines that use AI for physical operations.
Tesla’s Optimus robot replicating human tasks
Key initiatives:
Plans for 5,000-10,000 Optimus robots in 2025, scaling to 50,000 in 2026
Robotaxi service targeting availability to half the U.S. population by EOY 2025
AI6 chip development with Samsung for unified training across vehicles, robots, and data centers
$5 billion projected AI infrastructure spending for 2025
This play is exponentially harder to develop than digital AI, and the markets have reflected low confidence that Tesla can pull it off.
TSLA has been the worst-performing Mag Seven stock of 2025, down 18.37% in H1 2025.
However, if Tesla’s strategy is successful, it could be far more valuable than other AI plays. Robots and autonomous vehicles could perform actual labour worth trillions of dollars annually.
The $385 billion Question
The Mag Seven are starting to see real revenue come in from their AI investments. But they're pouring that money (and more) back into AI, betting that the boom is just getting started.
The platform players like Microsoft and Amazon are betting on becoming essential infrastructure. Nvidia’s play is to sell the underlying hardware to everyone. Google and Meta compete on capability and access. While Apple and Tesla target specific use cases.
The $385 billion question is which of the Magnificent Seven has bet the right way? Or will a new player rise and usurp the long-standing tech giants altogether?
You can access all Magnificent Seven stocks and thousands of other Share CFDs on GO Markets.
Over the past 3 months Nvidia has moved through ranges that some stocks don’t do in years, in some cases decades. Having lost over 35 per cent in the June to August sell off, it quickly bounced over 40 per cent in the preceding 20 days once it hit its August low as we build positions ahead of its results. These results delivered Nvidia style numbers with three figure growth on the sales, net profit and earnings lines but this did not appease the market, seeing it fall 22 per cent in a little over 8 days.
Which brings us to now – a new 16 per cent drive as Nivida reports it’s struggling to meet demands and that the AI revolution is translating faster than even it expected. This got us thinking – Where are we right “Now” in the AU players? Thus, it’s time to dive into the drivers for the Nvidia and Co.
AI players. Supersonic As mentioned, Nvidia’s results have been astonishing – and it still has time to do a US$50 billion buyback. It collected the award for becoming the world’s largest company in the shortest timeframe in the post-WWII era, think about that for one second – that’s faster than Amazon, Microsoft, Apple, Google, Shell, BP, ExxonMobil, TV players of the 60s and 70s.
So the question is how does it keep its speed and trajectory? Well that comes from what some are calling the ‘supersonic’ scalers. These are the players like Google, Amazon, Meta and Microsoft that are the users and providers of the AI revolution.
These are the players that have spent hundreds billions thus far on the third digital revolution. Let us once again put that into perspective, the amount of spending is (inflation adjusted) the same as what was spent during the 1960’s on mainframe computing and the 1990’s distribution of fibre-optics. So we have now seen that level of spending in AI the next step is ‘usage’ and that is the inflection point we find ourselves at.
Currently AI is mainly used to train foundational models and chatbots – which is fine but not long-term financially stable. It needs to move into things like productions – that is producing models for corporate clients that forecast, streamline and increase productivity. This is the ‘Grail’ This immediately raises the bigger question for now – can this Grail be achieved?
The Voices To answer that – let us present some arguments from some of AI’s largest “Voices” On the AI potential and the possibility of a profound and rapid technological revolution, Sam Altman, CEO of OpenAI, has claimed that AI represents the "biggest, best, and most important of all technology revolutions," and predicts that AI will become increasingly integrated into all aspects of life. This reflects a belief in AI's far-reaching influence over time. The never subtle McKinsey and Co. has projected that generative AI could eventually contribute up to $8 trillion to the global economy annually.
This figure underscores the massive economic potential of AI. The huge caveat: McKinsey's predictions are never real-world tested and inevitably fall flat in the market. This kind of money is what makes AI so attractive to players in Venture Capital.
For the VC watchers out there the one that is catching everyone’s attention is VC accelerator Y Combinator which is fully embracing the technology. Just to put Y Combinator into context, according to Jared Heyman’s Rebel Fund, if anyone had invested in every Y Combinator deal since 2005 (which would have been impossible just to let you know), the average annual return would have been 176%, even after accounting for dilution. Furthermore to the VC story - AI has accounted for over 40 per cent of new unicorns (startups valued at $1 billion or more) in the first half of 2024, and 60 per cent of the increase in VC-backed valuations.
So far in 2024, U.S. unicorn valuations have grown by $162 billion, largely driven by AI’s rapid expansion, according to Pitchbook data. So the Voices certainly believe it can be achieved. But is this a good thing?
The Good, the Bad and the Ugly AI is advancing at such a rapid pace that existing performance benchmarks, such as reading comprehension, image classification and advanced maths, are becoming outdated, necessitating the creation of new standards. This reflects the fast-moving nature of AI progress. For example, look at the success of AlphaFold, an AI-driven algorithm that accurately predicts protein structures.
Some see this as one of the most important achievements in AI’s short history and underscores AI’s transformative impact on science, particularly in fields like biology and healthcare. This is the Good. Then there is the 165-page paper titled "Situational Awareness" by Aschenbrenner which has predicted that by 2030, AI will achieve superintelligence and create a $1 trillion industry.
Also, a positive, but will consume 20 per cent of the U.S. power supply. These incredible predictions emphasise the enormous scale of AI and the impact it will have on industry, infrastructure and people. The latest Google study found that generative AI could significantly improve workforce productivity.
The study suggests that roughly 80 per cent of jobs could see at least 10 per cent of tasks completed twice as fast due to AI, which has implications for industries such as call centres, coding, and professional writing. This highlights AI's capacity to streamline tasks and enhance efficiency across various fields. However it also raises the massive concern around job security, job satisfaction and the socio-economic divide as the majority of those affected by AI ‘productivity’ are in mid to low scales.
Then we come to Elon Musk’s new AI startup, xAI, which raised $6 billion at a valuation of $24 billion this year. The company is planning to build the world’s largest supercomputer in Tennessee to support AI training and inference. This all sounds economically and financially exciting but it has a darker side.
These are the kinds of AI ventures that have seen ‘deep-fake’ creations. For example Musk himself shared a deep-fake video of Vice President Kamala Harris. This is the ugly side of AI and reflects the broader cultural and ethical issues surrounding AI-generated content.
Furthermore – we should always be forecasting both the good and the bad for investment opportunities. These issues are already attracting regulations and compliance responses. How impactful will these be?
And will it halt the AI driven share price appreciation? It is a very real and present issue. Where does this leave us?
The share price future of Nvidia and Co is clearly dependent on the longer-term achievement of the AI revolution. As shown, the supersonic players in technology and venture capital are betting big on AI, with predictions that it will reshape the global economy, industries, and even basic societal structures. However, there is still uncertainty about the exact timeline for these changes and how accurately the market is pricing in AI's potential.
The AI ecosystem is moving at breakneck speed, with new developments outpacing benchmarks and productivity gains reshaping jobs, but whether all these projections that range from trillion-dollar economies to superintelligence materialises remains to be seen. Thus – for now – Nvidia and Co’s recent roller-coaster trading looks set to continue.
The global initial public offering (IPO) market saw a resurgence in 2025. Proceeds increased 39% to US$171.8 billion across 1,293 listings, the sharpest annual rebound since the post-pandemic boom.
That momentum is now building into 2026 for what some financial analysts speculate could be the biggest IPO year in history.
A handful of mega-cap private companies, including SpaceX, OpenAI, and Anthropic, are exploring going public this year, with combined valuations that could exceed US$3 trillion.
2025 IPO market data
Top IPO candidates in 2026
1. SpaceX - US$1.5T valuation
SpaceX revenue reportedly hit US$15 billion in 2025, with analysts projecting an increase to US$22-24 billion in 2026. The company has been cash-flow positive for years, driven largely by its Starlink satellite broadband network.
Following its February 2026 all-stock acquisition of Elon Musk's AI company xAI, the combined entity also encompasses Grok AI and the social media platform X (Twitter).
Leading financial analysts have reported SpaceX is targeting a mid-2026 listing. Its next funding round is estimated to raise around US$50 billion, putting its initial market cap at US$1.5 trillion, which would make it the second-highest IPO valuation of all time.
This valuation would mean SpaceX would trade at 62–68 times projected 2026 sales. A steep premium that requires massive growth assumptions around Starlink and longer-term space-based AI ambitions.
2. OpenAI - US$850B valuation
OpenAI, the company behind ChatGPT, now reports more than 800 million weekly active users of its groundbreaking AI product.
Originally a nonprofit research lab, it has restructured into a for-profit entity developing large language models for consumer, enterprise, and developer applications.
OpenAI is reportedly targeting a Q4 2026 IPO, finalising a US$100 billion-plus funding round (its largest ever), which would put its valuation at US$850 billion.
However, OpenAI still needs to overcome some near-term hurdles to achieve the potential associated with such a high valuation.
It projects US$14 billion in losses in 2026 and does not expect profitability before 2029. It is facing intensified competition from Google Gemini and other AI startups cutting into its market share, and Elon Musk has filed a lawsuit against the company seeking up to US$134 billion in damages.
3. Anthropic - US$350B valuation
While OpenAI has leaned into consumer products, Anthropic has built its business around enterprise adoption. Roughly 80% of its revenue comes from business customers, and eight of the Fortune 10 are now Claude users.
Anthropic closed a US$30 billion funding round in February 2026 at a US$350 billion valuation, more than double its US$183 billion valuation from five months earlier.
Anthropic’s annualised revenue has been growing at 10x per year since 2024, well outpacing OpenAI’s growth of 3.4x per year. If this trend continues, Anthropic revenue could pass OpenAI by mid-2026. However, since July 2025, Anthropic’s growth rate has slowed down to 7x per year.
Anthropic projected growth if revenue trend continues | Epoch.ai
Anthropic has engaged law firm Wilson Sonsini to begin IPO preparations, and the recent appointment of former Microsoft CFO Chris Liddell to its board signals a governance push ahead of a potential late-2026 listing.
The company is not yet profitable, but its enterprise-heavy revenue mix and rapid growth trajectory make it one of the most closely watched IPO candidates this year.
4. Stripe - US$140B valuation
Stripe processed US$1.4 trillion in total payment volume in 2024, roughly 1.3% of global GDP. Half the Fortune 100 now use Stripe, and recent moves into stablecoins and AI-to-AI "agentic commerce" payments are expanding its addressable market.
Stripe remains one of the most anticipated fintech IPOs globally, but the company has shown a lack of urgency to list in the past. Co-founder John Collison said at Davos in January 2026 that Stripe was "still not in any rush."
Rather than pursuing an IPO, Stripe has conducted tender offers every six months at rising valuations, providing employee liquidity without surrendering control.
These frequent tenders effectively function as a private-market alternative to going public. However, a traditional IPO is still on the cards in 2026, with the company's February tender offer valuing it at US$140 billion or more, and profitability since 2024 removing one of the key barriers to listing.
5. Databricks - US$134B valuation
Databricks completed a US$5 billion funding round in February 2026 at a US$134 billion valuation.
The company's annualised revenue exceeded US$5.4 billion in January 2026, growing a massive 65% year-on-year, with AI products generating US$1.4 billion.
CEO Ali Ghodsi has said the company is prepared to go public "when the time is right," with most analysts expecting a H2 2026 listing. At US$134 billion, Databricks is valued at more than twice publicly traded rival Snowflake (~US$58 billion).
Bottom line
2026 has the potential to be the biggest IPO year by valuation in history. With the most likely candidates, SpaceX and Databricks, matching the total valuation of all 2025 IPOs on their own.
If major AI players like OpenAI and Anthropic, as well as world-leading payment fintech Stripe, also list before the end of the year, 2026 could see over US$3 trillion in total value added to global markets through IPOs alone.
Markets move into the week ahead with inflation data across Australia and Japan, alongside elevated geopolitical tensions that continue to influence energy prices and broader risk sentiment.
Australia Consumer Price Index (CPI): Inflation data may influence the Reserve Bank of Australia (RBA) policy path, with the Australian dollar (AUD) and local yields sensitive to any surprise.
Japan data cluster: Tokyo CPI (preliminary) plus industrial production and retail sales provide an inflation-and-activity pulse that could shape Bank of Japan (BoJ) normalisation expectations.
Eurozone & Germany CPI: Flash inflation readings will test the disinflation narrative and influence ECB rate-cut timing expectations.
Oil and geopolitics: Brent crude has posted its highest close since 8 August 2025 amid renewed Middle East tensions, reinforcing energy-driven inflation risk.
Australia CPI: RBA expectations to change?
Australia’s upcoming CPI release will be closely watched for signals on whether inflation is stabilising or proving more persistent than expected.
A stronger-than-expected print could be associated with higher yields and a firmer AUD as rate expectations adjust. A softer outcome could support expectations for a steadier policy stance.
Key dates
Inflation Rate (MoM): 11:30 am Wednesday, 25 February (AEDT)
Japan’s late-week releases combine Tokyo CPI (preliminary) with industrial production and retail sales, offering a broader read on price pressures and domestic demand.
Tokyo CPI is often watched as a timely signal for national inflation dynamics and BoJ debate. Industrial output and retail spending add context on activity.
Surprises across this cluster can drive sharp moves in the JPY, particularly if results shift perceptions around the pace and persistence of BoJ normalisation.
Key dates
Tokyo CPI: 10:30 am Friday, 27 February (AEDT)
Industrial Production: 10:50 am Friday, 27 February (AEDT)
Retail Sales: 10:50 am Friday, 27 February (AEDT)
Monitor
JPY sensitivity to inflation surprises
Bond yield moves in response to activity data
Equity reactions if growth momentum expectations shift
Energy and safe-haven flows
Oil prices have climbed to their highest close since 8 August 2025 amid renewed Middle East tensions.
Recent reporting on heightened regional military activity and shipping-risk headlines near the Strait of Hormuz has reinforced energy security as a market focus. The Strait of Hormuz remains a widely watched chokepoint for global energy flows.
Higher oil prices can feed into inflation expectations and influence bond yields. At the same time, geopolitical uncertainty can support the USD through safe-haven demand and relative rate positioning.
Flash inflation readings from Germany and the broader eurozone (HICP) will test whether the region’s disinflation trend remains intact.
Germany’s release can influence expectations ahead of the aggregated eurozone figure. If core inflation proves sticky, expectations around the timing and pace of potential European Central Bank easing could shift.
Key dates
Germany Inflation Rate: 12:00 am Saturday, 28 February (AEDT)
From tech disruptors to defence contractors, some of the market's most talked-about companies start their public journey through an initial public offering (IPO). For traders, these initial public listings can represent a unique trading environment, but also a period of heightened uncertainty.
Quick facts
An IPO is when a private company lists its shares on a public stock exchange for the first time.
IPOs can offer traders early access to high-growth companies, but come with elevated volatility and limited price history.
Once listed, traders can gain exposure to IPO stocks through direct share purchases or derivatives such as contracts for difference (CFDs).
What is an initial public offering (IPO)?
An IPO is when a company offers its shares to the public for the first time.
Before performing an IPO, shares in the company are typically only held by founders, early employees, and private investors. Going public makes the shares available to be purchased by anyone.
Depending on the size of the company, it will usually list its public shares on the local stock exchange (for example, the ASX in Australia). However, some large-valuation companies choose to only list on a global stock exchange, like the Nasdaq, no matter where their main headquarters is located.
For traders, IPOs are generally the first opportunity to gain exposure to a company’s stock. They can create a unique environment with increased volatility and liquidity, but also carry heightened risk, given the limited price history and sensitivity to sentiment swings.
Why do companies go public?
The biggest driver to perform an IPO is to access more capital. Listing on a public exchange means the company can raise significant funds by selling shares.
It also provides liquidity for existing shareholders. Founders, early employees, and private investors often sell a portion of their existing holdings on the open market, realising the returns on their years of support.
Beyond the monetary benefits, going public means companies can use their stock as currency for acquisitions and offer equity-based compensation to attract talent. And a public valuation provides a transparent benchmark, which is useful for strategic positioning and future fundraising.
However, it does come with trade-offs. Public companies must comply with ongoing disclosure and reporting obligations, and pressure from public shareholders can become a barrier to long-term progress if many are focused on short-term performance.
While the specifics vary by jurisdiction, going from a private company to a public listing generally involves the following stages:
1. Preparation
The company first selects the underwriter (typically an investment bank) to manage the offering. Together, they assess the company's financials, corporate structure, and market positioning to determine the best approach for going public. It is the heavy planning stage to make sure the company is actually ready to go public.
2. Registration
Once everything is prepared, the underwriters conduct a thorough due diligence check and then lodge the required disclosure documents with the relevant regulator. These documents give a detailed disclosure to the regulator about the company, its management, and its proposed offering. In Australia, this is typically a prospectus lodged with ASIC; in the US, a registration statement filed with the SEC.
3. Roadshow
Executives at the company and underwriters will then present the investment case to institutional investors and market analysts in a “roadshow”. This showcase is designed to gauge demand for the stock and help generate interest. Institutional investors can register their interest and valuation of the IPO, which helps inform the initial pricing.
4. Pricing
Based on feedback from the roadshow and current market conditions, the underwriters set the final share price and determine the number of shares to be issued. Shares are allocated on the ‘primary market’ to investors participating in the offer (before the stock is listed publicly on the secondary market). This process sets the pre-market price, which effectively determines the company’s initial public valuation.
5. Listing
On listing day, the company’s shares begin trading on the chosen stock exchange, officially opening the secondary market. For most traders, this is the first point at which they can trade the stock, either directly or through derivatives such as Share CFDs.
6. Post-IPO
Once listed, the company becomes subject to strict reporting and disclosure requirements. It must communicate regularly with shareholders, publish its financial results, and comply with the governance standards of the exchange on which it is listed.
IPO risks and benefits for traders
How do traders participate in IPOs?
For most traders, participating in an IPO comes once shares have listed and begun trading on the secondary market.
Once shares are live on the exchange, investors can buy the physical shares directly through a broker or online exchange, or they can use derivatives such as Share CFDs to take a position on the price without owning the underlying asset.
The first few days of IPO trading tend to be highly volatile. Traders should ensure they have taken appropriate risk management measures to help safeguard against potential sharp price swings.
The bottom line
IPOs mark when a company becomes investable to the public. They can offer early access to high-growth companies and create a unique trading environment driven by elevated volatility and market interest.
For traders, understanding how the process works, what drives pricing and post-IPO performance, and how to weigh potential rewards against the risks of trading newly listed shares is essential before taking a position.
