The Kansas City Federal Reserve is set to host the 45 th Annual Symposium at Jackson Hole Lodge in Wyoming’s Grand Teton National Park. Some of the countries and world’s most important central bankers, economists, and academics will be meeting to discuss the biggest issues facing the global economy. The key issue on the agenda is of “Reassessing Constraints on the Economy and Policy.” All eyes will be on Jerome Powell, with the chairman of the Federal Reserve expected to speak on Thursday and provide an update on the proceedings of the conference.
At last year’s event Powell was caught out after stating that inflation was transitory, only to see it become a huge long-lasting issue. Therefore, he may try and correct this perception and portray a much more conservative attitude. There is also a view from some analysts that the Fed came across too dovish in the July meeting which led to the market rally.
At this stage the market has priced in a 75-bps increase at the September meeting, however this may change. With key inflation measures slowing somewhat, the question will be whether the fed continue its aggressive interest rate hikes or eases their policy to avoid a potential recession. The market will be hoping that Powell provides some clues for what the Fed plans to do after rates peak.
They will be hoping for clarity over whether the bank will hold the rates at the high levels for some time or lower them straight away to avoid a recession. Market participants should be weary that although Jackson Hole may provide some important context to the future rates, no official policies will be set. The conference will most likely have a relatively small impact on the market, it still has the potential to provide some volatility for both equities and currency if significant attitude shifts are expressed.
The USD is currently at 5 year highs and with some positive catalysts for the currency, it may continue to rise further if the Fed continues to be aggressive in its rate hikes.
By
GO Markets
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The “Magnificent Seven” technology companies are expected to invest a combined $385 billion into AI by the end of 2025.Each of the Seven is trying to carve out its own territory in the AI landscape.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.But with these 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?[caption id="attachment_712288" align="aligncenter" width="554"]
The “Big 4” tech companies' AI spending alone is forecast at $364 billion.[/caption]
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 centerpiece 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.[caption id="attachment_712289" align="aligncenter" width="530"]
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. [caption id="attachment_712301" align="aligncenter" width="996"]
H1 relative performance of the Magnificent Seven stocks. Source: KoyFin, Finimize[/caption]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.[caption id="attachment_712292" align="aligncenter" width="537"]
Tesla’s Optimus robot replicating human tasks[/caption]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 labor 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.
The ASX 200 closed out the 2025 financial year on a high, reaching a new intra-month peak of 8,592 in June and within touching distance of the all-time record. The index delivered a 1.4% total return for the month, rounding off a strong final quarter with a 9.5% return and locking in a full-year gain of 13.8% — its best performance since 2021.This strong finish all came down to the postponement of the Liberation Day tariffs. From the April 7 lows through to the end of the financial year, the ASX followed the rest of the world. Mid-cap stocks were the standout performers, beating both large and small caps as investors sought growth opportunities away from the extremes of the market. Among the sectors, Industrials outperformed Resources, benefiting from more stable earnings and supportive macroeconomic trends tied to infrastructure and logistics.But the clear winner was Financials, which contributed an incredible 921 basis points to the overall index return. CBA was clearly the leader here, dominating everything with 457 basis points on its own. Westpac, NAB, and others also played a role, but nothing even remotely close to CBA. The Industrials and Consumer Discretionary sectors made meaningful contributions, adding 176 and 153 basis points, respectively. While Materials, Healthcare, and Energy all lagged, each detracting around 45 to 49 basis points. Looking at the final quarter of the financial year, Financials were by far the biggest player again, adding 524 basis points — more than half the quarter’s total return of 9.5%. Apart from a slight drag from the Materials sector, all other parts of the market made positive contributions. Real Estate, Technology, and Consumer Discretionary followed behind as key drivers. Once again, CBA was the largest individual contributor, adding 243 basis points in the quarter, while NAB, WBC, and Macquarie Group added a combined 384 basis points. On the other side of the ledger, key underperformers included BHP, CSL, Rio Tinto, Treasury Wine Estates, and IDP Education, which all weighed on quarterly performance.One of the most defining features of the 2025 financial year was the dominance of price momentum as a market driver — something we as traders must be aware of. Momentum strategies far outpaced more traditional, fundamental-based approaches such as Growth, Value, and Quality. The most effective signal was a nine-month momentum measure (less the most recent month), which delivered a 31.2% long-short return. The more commonly used 12-month price momentum factor was also highly effective, returning 23.6%. By contrast, short-term reversals buying last month’s losers and selling last month’s winners was the worst-performing approach, with a negative 16.4% return. Compared to the rest of the world, the Australian market was one of the strongest trades for momentum globally, well ahead of both the US and Europe, despite its relatively slow overall performance.Note: these strategies are prone to reversal, and in the early days of the new financial year, there has been a notable shift away from momentum-based trading to other areas. Now is probably too early to say whether this marks a sustained change, but it cannot be ignored, and caution is always advised.The second big story of FY26 will be CBA. CBA’s growing influence was a key story of FY25. Its weight in the index rose by an average of 2.1 percentage points across the year, reaching an average of 11.5% by June. That helped push the spread between the Financials and Resources sectors to 15.8 percentage points — the widest gap since 2018. Despite the strong cash returns, market valuations are eye-watering; at one point during June, CBA became the world’s most expensive bank on price metrics. The forward price-to-earnings multiple now sits at 18.9 times. This is well above the long-term average of 14.7 and higher than the 10-year benchmark of 16.1. Meanwhile, the dividend yield has slipped to 3.4%, down from the historical average of 4.4%. Earnings momentum remains soft, with FY25 growth estimates still tracking at 1.4%, and FY26 forecast at a moderate 5.4%. This suggests that recent gains have come more from expanding valuation multiples than from actual earnings upgrades, making the August reporting date a catalyst day for it and, by its size, the market as a whole.On the macro front, attention now turns to the Reserve Bank of Australia. The central bank cut the cash rate by 25 basis points to 3.6% at its July meeting. Recent commentary from the RBA has taken on a more dovish tone, with benign inflation data and ongoing global uncertainty expected to outweigh the strength of the labour market. The RBA appears to be steering toward a neutral policy stance, and markets will be watching for further signals on how that shift will be managed. Recent economic data has been mixed. May retail sales were weaker than expected, while broader household spending indicators held up slightly better. Building approvals saw a smaller-than-hoped-for bounce, employment remains strong, but productivity is low. Inflation is now at a 3-year low and falling; all this points to underlying support from the RBA’s easing bias both now and into the first half of FY26.As we move into FY26, the key questions are:
Can fundamentals wrestle back control over momentum?
Will earnings growth catch up to price to justify valuations?
How will policy decisions from the RBA and other central banks shape investor sentiment in an ever-volatile world?
While the early signs suggest a possible rotation, the jury is still out on whether this marks a new phase for the Australian market or just a brief pause in the rally that defined FY25.
While recent data has shown core inflation moderating, core PCE is on track to average below target at just 1.6% annualised over the past three months.Federal Reserve Chair Jerome Powell made clear that concerns about future inflation, especially from tariffs, remain top of mind.“If you just look backwards at the data, that’s what you would say… but we have to be forward-looking,” Powell said. “We expect a meaningful amount of inflation to arrive in the coming months, and we have to take that into account.”While the economy remains strong enough to buy time, policymakers are closely monitoring how tariff-related costs evolve before shifting policy. Powell also stated that without these forward-looking risks, rates would likely already be closer to the neutral rate, which is a full 100 basis points from current levels.
2. The Unemployment Rate anchor
Powell repeatedly cited the 4.2% unemployment rate during the press conference, mentioning it six times as the primary reason for keeping rates in restrictive territory. At this level, employment is ahead of the neutral rate.“The U.S. economy is in solid shape… job creation is at a healthy level,” Powell added that real wages are rising and participation remains relatively strong. He did, however, acknowledge that uncertainty around tariffs remains a constraint on future employment intentions.If not for a decline in labour force participation in May, the unemployment rate would already be closer to 4.6%. Couple this with the continuing jobless claims ticking up and hiring rates subdued, risks are building around labour market softening.
3. Autumn Meetings are Live
While avoiding firm forward guidance, Powell hinted at a timeline:“It could come quickly. It could not come quickly… We feel like the right thing to do is to be where we are… and just learn more.”This suggests the Fed will remain on hold through the July meeting, using the summer to assess incoming data, particularly whether tariffs meaningfully push inflation higher. If those effects prove limited and unemployment begins to rise, the stage could be set for a rate cut in September.
Bitcoin rebounded 7% to touch $94,000 this week as two of the world's largest asset managers doubled down on their conviction that this cycle could break from crypto's boom-bust past.
BlackRock CEO Larry Fink and COO Rob Goldstein declared tokenisation "the next major evolution in market infrastructure,” comparing its potential to the introduction of electronic messaging systems in the 1970s.
Tokenised real-world assets have exploded from $7 billion to $24 billion in just one year, with certain projections expecting tokenised instruments to comprise 10-24% of portfolios by 2030.
Total RWA Value
Grayscale's latest research also put forward the case that this cycle will not follow Bitcoin’s predictable four-year pattern. Their analysis shows this cycle has had no parabolic price surge like previous cycles, and capital is flowing through regulated ETPs and corporate treasuries rather than retail speculation.
Grayscale has boldly predicted Bitcoin will reach new all-time highs next year based on this data, with near-term catalysts including a likely Federal Reserve rate cut and advancing crypto legislation.
AI Boom Creating a Memory Chip Supply Crisis
The AI revolution has had an unexpected ripple effect on conventional memory chips (DRAM).
Post-ChatGPT launch in 2022, chipmakers pivoted aggressively toward high-bandwidth memory (HBM) chips — the components that power AI data centres.
Samsung and SK Hynix, who control roughly 70% of the global DRAM market, transitioned large portions of their production away from conventional chips.
This worked in the short term, but data centre operators are now replacing old servers, and PC and smartphone sales have exceeded expectations (all of which require DRAM).
This saw DRAM supplier inventories fall to just two to four weeks in October, down from 13 to 17 weeks in late 2024.
DRAM spot prices nearly tripled in September this year, while in Tokyo's electronics district, popular gaming memory modules have surged from 17,000 yen to over 47,000 yen in recent weeks.
Google, Amazon, Microsoft, and Meta have all approached Micron with open-ended orders, agreeing to purchase whatever the company can deliver, regardless of price.
Samsung, Micron, and SK Hynix shares have rallied 96%, 168%, and 213% YTD, respectively, thanks to the increased DRAM demand.
Ironically, this recent price surge has seen DRAM chip margins approach those of the advanced HBM chips, meaning non-AI memory could now become equally profitable to produce.
Every trader has had that moment where a seemingly perfect trade goes astray.
You see a clean chart on the screen, showing a textbook candle pattern; it seems as though the market planets have aligned, and so you enthusiastically jump into your trade.
But before you even have time to indulge in a little self-praise at a job well done, the market does the opposite of what you expected, and your stop loss is triggered.
This common scenario, which we have all unfortunately experienced, raises the question: What separates these “almost” trades from the truly higher-probability setups?
The State of Alignment
A high-probability setup isn’t necessarily a single signal or chart pattern. It is the coming together of several factors in a way that can potentially increase the likelihood of a successful trade.
When combined, six interconnected layers can come together to form the full “anatomy” of a higher-probability trading setup:
Context
Structure
Confluence
Timing
Management
Psychology
When more of these factors are in place, the greater the (potential) probability your trade will behave as expected.
Market Context
When we explore market context, we are looking at the underlying background conditions that may help some trading ideas thrive, and contribute to others failing.
Regime Awareness
Every trading strategy you choose to create has a natural set of market circumstances that could be an optimum trading environment for that particular trading approach.
For example:
Trending regimes may favour momentum or breakout setups.
Ranging regimes may suit mean-reversion or bounce systems.
High-volatility regimes create opportunity but demand wider stops and quicker management.
Investing time considering the underlying market regime may help avoid the temptation to force a trending system into a sideways market.
Simply looking at the slope of a 50-period moving average or the width of a Bollinger Band can suggest what type of market is currently in play.
Sentiment Alignment
If risk sentiment shifts towards a specific (or a group) of related assets, the technical picture is more likely to change to match that.
For example, if the USD index is broadly strengthening as an underlying move, then looking for long trades in EURUSD setups may end up fighting headwinds.
Setting yourself some simple rules can help, as trading against a potential tidal wave of opposite price change in a related asset is not usually a strong foundation on which to base a trading decision.
Key Reference Zones
Context also means the location of the current price relative to levels or previous landmarks.
Some examples include:
Weekly highs/lows
Prior session ranges, e.g. the Asian high and low as we move into the European session
Major “round” psychological numbers (e.g., 1.10, 1000)
A long trading setup into these areas of market importance may result in an overhead resistance, or a short trade into a potential area of support may reduce the probability of a continuation of that price move before the trade even starts.
Market Structure
Structure is the visual rhythm of price that you may see on the chart. It involves the sequences of trader impulses and corrections that end up defining the overall direction and the likelihood of continuation:
Uptrend: Higher highs (HH) and higher lows (HL)
Downtrend: Lower highs (LH) and lower lows (LL)
Transition: Break in structure often followed by a retest of previous levels.
A pullback in an uptrend followed by renewed buying pressure over a previous price swing high point may well constitute a higher-probability buy than a random candle pattern in the middle of nowhere.
Compression and Expansion
Markets move through cycles of energy build-up and release. It is a reflection of the repositioning of asset holdings, subtle institutional accumulation, or a response to new information, and may all result in different, albeit temporary, broad price scenarios.
Compression: Evidenced by a tightening range, declining ATR, smaller candles, and so suggesting a period of indecision or exhaustion of a previous price move,
Expansion: Evidenced by a sudden breakout, larger candle bodies, and a volume spike, is suggestive of a move that is now underway.
A breakout that clears a liquidity zone often runs further, as ‘trapped’ traders may further fuel the move as they scramble to reposition.
A setup aligned with such liquidity flows may carry a higher probability than one trading directly into it.
Confluence
Confluence is the art of layering independent evidence to create a whole story. Think of it as a type of “market forensics” — each piece of confirmation evidence may offer a “better hand’ or further positive alignment for your idea.
There are three noteworthy types of confluence:
Technical Confluence – Multiple technical tools agree with your trading idea:
Moving average alignment (e.g., 20 EMA above 50 EMA) for a long trade
A Fibonacci retracement level is lining up with a previously identified support level.
Momentum is increasing on indicators such as the MACD.
Multi-Timeframe Confluence – Where a lower timeframe setup is consistent with a higher timeframe trend. If you have alignment of breakout evidence across multiple timeframes, any move will often be strengthened by different traders trading on different timeframes, all jumping into new trades together.
3. Volume Confluence – Any directional move, if supported by increasing volume, suggests higher levels of market participation. Whereas falling volume may be indicative of a lesser market enthusiasm for a particular price move.
Confluence is not about clutter on your chart. Adding indicators, e.g., three oscillators showing the same thing, may make your chart look like a work of art, but it offers little to your trading decision-making and may dilute action clarity.
Think of it this way: Confluence comes from having different dimensions of evidence and seeing them align. Price, time, momentum, and participation (which is evidenced by volume) can all contribute.
Timing & Execution
An alignment in context and structure can still fail to produce a desired outcome if your timing is not as it should be. Execution is where higher probability traders may separate themselves from hopeful ones.
Entry Timing
Confirmation: Wait for the candle to close beyond the structure or level. Avoid the temptation to try to jump in early on a premature breakout wick before the candle is mature.
Retests: If the price has retested and respected a breakout level, it may filter out some false breaks that we will often see.
Then act: Be patient for the setup to complete. Talking yourself out of a trade for the sake of just one more candle” confirmation may, over time, erode potential as you are repeatedly late into trades.
Session & Liquidity Windows
Markets breathe differently throughout the day as one session rolls into another. Each session's characteristics may suit different strategies.
For example:
London Open: Often has a volatility surge; Range breaks may work well.
New York Overlap: Often, we will see some continuation or reversal of morning trends.
Asian Session: A quieter session where mean-reversion or range trading approaches may do well
Trade Management
Managing the position well after entry can turn probability into realised profit, or if mismanaged, can result in losses compounding or giving back unrealised profit to the market.
Pre-defined Invalidation
Asking yourself before entry: “What would the market have to do to prove me wrong?” could be an approach worth trying.
This facilitates stops to be placed logically rather than emotionally. If a trade idea moves against your original thinking, based on a change to a state of unalignment, then considering exit would seem logical.
Scaling & Partial Exits
High-probability trade entries will still benefit from dynamic exit approaches that may involve partial position closes and adaptive trailing of your initial stop.
Trader Psychology
One of the most important and overlooked components of a higher-probability setup is you.
It is you who makes the choices to adopt these practices, and you who must battle the common trading “demons” of fear, impatience, and distorted expectation.
Let's be real, higher-probability trades are less common than many may lead you to believe.
Many traders destroy their potential to develop any trading edge by taking frequent low-probability setups out of a desire to be “in the market.”
It can take strength to be inactive for periods of time and exercise that patience for every box to be ticked in your plan before acting.
Measure “You” performance
Each trade you take becomes data and can provide invaluable feedback. You can only make a judgment of a planned strategy if you have followed it to the letter.
Discipline in execution can be your greatest ally or enemy in determining whether you ultimately achieve positive trading outcomes.
Bringing It All Together – The Setup Blueprint
Final Thoughts
Higher-probability setups are not found but are constructed methodically.
A trader who understands the “higher-probability anatomy” is less likely to chase trades or feel the need to always be in the market. They will see merit in ticking all the right boxes and then taking decisive action when it is time to do so.
It is now up to you to review what you have in place now, identify gaps that may exist, and commit to taking action!