Market news & insights

Top 5 Benefits of a MT4 Demo Trading Account A MT4 Demo trading account is a virtual trading account that allows you to make virtual trades with play money. Demo trading accounts replicate Live trading accounts, but it removes the risk of losing your own trading capital until you are comfortable trading with real money. Most Forex brokers now offer a trial period of their Metatrader 4 demo account to those who want to familiarise themselves with a trading platform.

A Demo trading account is an ideal way to learn about a platform and how to place and manage trades. In a way, a Demo trading account is your ‘L’ plate when you’re just starting or learning to trade. At GO Markets, we provide the MetaTrader 4 (MT4) platform for a trial period of 30 days.

In this article, we will outline the major benefits of using a Demo trading account before going “Live”. These benefits include: 01. A Demo Trading Account is Free There is no cost to download and access a Demo trading account from your broker.

The only thing you need to provide is your name and email address and other relevant contact details. This is to make sure that you can also get support from your FX broker or provider in case you have any question about the Demo trading account or the platform. 02. Theory Into Practice If you’re new to FX trading, there is a lot to learn, especially about the mechanics of how an FX trade works.

For example, you need to know the different lot sizes, what is leverage and how you can use it for your trading, margin requirements, order types, and stop losses. Using a Demo trading account is the best way to put what you have learnt into practice. This will help you gauge your level of understanding before you commit real money.

Gaining any level of confidence in FX trading, no matter how small, always begins on a Demo trading account. 03. Familiarise Yourself With The Trading Platform If you’re a new trader, one of the most important things to do is to familiarise yourself with a trading platform. This is because a trading platform is your vital tool to execute your trades.

The more familiar you are to your chosen trading platform, the better and more efficient you could be with your trading. You also have to consider that different Forex brokers offer different trading platforms. So, it is important that you choose a trading platform that suits your trading style.

Alternatively, if you’re an existing trader and you’re moving from one broker to another, you may be required to use a different trading platform to one that you are used to. Once again you will need to familiarise yourself with the new platform. This process may take time, and a Demo trading account is the best way to get used to a platform without making costly mistakes. 04.

Testing a Trading Strategy There is a saying that goes, “Plan the trade, and trade the plan.” Planning your trades and sticking to your trading plans are vital if you are set on becoming a successful trader. However, it could be easier said than done. Planning your trades and executing your plans accordingly takes time and discipline.

And this is where a Demo trading account could be helpful as you need time to develop and adjust your trading plan and strategy. So whether you are trading manually or using an Expert Adviser, it is best to test your trading strategy on a Demo trading account. A Demo trading account allows you to test and refine your trading strategies without committing real money until you are happy with the results. 05.

Testing Trading Tools Most brokers now provide additional trading tools as a value add to their trading platform. For example, GO Markets provides the MT4 Genesis, which is a comprehensive suite of trading tools. Before using any additional trading tools, it’s highly recommended to test them out on a Demo trading account.

This will help you become more familiar with the tools and determine which ones are the most suitable and helpful for your trading needs. Considering all the benefits we’ve discussed, one thing to remember is that a Demo trading account does not fully prepare you for when you decide to trade for real. Despite all the benefits of Demo trading, it’s also important to note, that there are some drawbacks. » Different Trading Psychology – No matter how long you practice on a Demo trading account, there is no substitute for Live trading.

The main reason is the different psychology when using a Demo trading account compared to a Live trading account. Your mind acts differently once you are no longer practicing with “play” or “virtual” money, and you start trading with your hard earned cash. Where you may have traded larger lot sizes on a Demo trading account without too much concern, it may be harder to pull the trigger on a Live trading account.

Where a losing trade did not matter so much on a Demo trading account, it may be harder to accept a similar loss on a Live account. You may have been confident of your trading strategy on the Demo trading account, but now you’re about to go Live, you’re not so sure. » Risk Management – When downloading a Demo trading platform, beginners can choose how much virtual money they can play with. If the Demo trading goes well, this could easily lead to a false psychological expectation that placing large trades and making large profits is easy.

This leads to poor risk management practices that can carry over to Live trading. This usually leads to a poor trading performance. Demo trading is an important part of becoming a successful trader.

To get the most out your Demo trading I suggest the following: (1) Hone your skills and refine your trading strategy, and most importantly, learn from your mistakes. (2) If you intend to eventually start trading a Live account with a minimum balance of $500, open a Demo trading account with $500. Choose a starting balance on your Demo trading account similar to an amount that you would start on a Live trading account. (3) Treat Demo trading as if it’s the real deal. Try to feel all the emotions of trading – how it feels to have both winning and losing trades. (4) Stick with Demo trading until you are confident enough to trade Live.

At GO markets we offer a 30-day trial of our MT4 platform to both potential. Please click here to start your trial period today. Clients who open and fund a Live trading account with a minimum of $200, are able to get access to a “non-expiring” Demo account.

Please note that trading Forex and Derivatives carries a high level of risk, including the risk of losing substantially more than your initial investment. Also, you do not own or have any rights to the underlying assets. You should only trade if you can afford to carry these risks.

Our offer is not designed to alter or modify any individual’s risk preference or encourage individuals to trade in a manner inconsistent with their own trading strategies. See our MT4 tutorial videos here. Rom Revita | Sales Manager Rom is the Sales Manager at Go Markets Pty Ltd and manages the day-to-day running of the Sales, Support and Marketing teams.

He has been with the company since 2013 and is also one of our two appointed Responsible Managers, helping to ensure that the company follows all AFSL regulatory requirements. Rom has extensive financial markets experience and originally comes from an equities & derivatives trading background. He has served on the Trading & Sales Desk with several large broking houses, and now specialises in Margin FX and CFDs.

Connect with Rom: [email protected]

Artificial Intelligence (AI) is no longer a futuristic concept; it is a rapidly evolving reality reshaping industries, including financial markets. For traders, understanding how AI impacts price action and adopting strategies to adapt to these changes are critical to staying competitive. This article aims to explore AI's current capabilities, its profound influence on price action, but also offer some thoughts on how traders can potentially thrive during current and future changes that may impact markets.

What is Artificial Intelligence? Artificial Intelligence refers to the ability of machines to simulate human intelligence and perform tasks such as learning, reasoning, problem-solving, and planning. AI can be broadly categorized into three types: Artificial Narrow Intelligence (ANI): Specialized AI systems designed to perform specific tasks (e.g., chatbots, fraud detection, and algorithmic trading).

Artificial General Intelligence (AGI): A hypothetical stage where AI matches human cognitive abilities, capable of learning and reasoning across diverse tasks. Artificial Superintelligence (ASI): An even more speculative stage where AI surpasses human intelligence in every way. Currently, ANI dominates the landscape and drives innovations across industries.

For financial markets, ANI forms the foundation for tools and algorithms that enhance trading efficiency, accuracy, and decision-making. What is Machine Learning? Machine learning (ML) is one of the most important technologies underpinning AI and its potential applications in the trading world and so is worth just a little more explanation.

In simple terms, it may enable machines to learn from data, identify patterns, and make predictions or decisions without requiring explicit programming for each scenario. Let’s look briefly at the key elements, types and applications of ML that may have trading relevance. Key Elements of Machine Learning Data: Machine learning relies on large datasets, such as historical market prices, trading volumes, and economic indicators.

Algorithms: These are mathematical rules and calculations used to analyse data and make predictions. They range from simple regressions to complex deep learning models. Feedback Loops: Feedback allows ML models to learn from successes and failures, continually improving their accuracy over time.

Types of Machine Learning Supervised Learning: Machines are trained using labeled datasets, such as identifying bullish or bearish patterns in historical data. Unsupervised Learning: Machines find hidden patterns or anomalies in unlabeled data, such as clustering similar market behaviors. Reinforcement Learning: Machines learn through interaction with an environment, receiving rewards or penalties for actions, making it particularly useful for dynamic trading environments.

Applications in Trading Machine learning drives key advancements in trading, including: Predicting price movements using historical and real-time data. Optimizing portfolio allocations. Detecting anomalies or potential fraud.

Automating decision-making processes based on market conditions. Understanding machine learning is essential because it forms the backbone of many AI-driven trading tools that are reshaping financial markets. Concepts like enhanced trend identification, predictive analytics, and scenario planning all stem from machine learning’s ability to process vast datasets and adapt to changing market conditions.

AI’s Current and Future Capabilities in Trading As the evolution of AI expands into most areas that impact on our world, trading is no exception, AI applications in the financial world span a wide spectrum of uses but most fall into three main categories. This comprise: Fraud Detection: Identifying irregularities in financial transactions. Predictive Analytics: Anticipating price movements based on historical patterns and real-time inputs.

Advanced Decision Support: Assisting traders by analyzing complex datasets and suggesting optimal actions. As ANI technology advances, it is expected to refine these capabilities further, enabling: Enhanced sales forecasting for financial products. Real-time risk management tools.

The development of more personalized trading recommendations. In the long term, these advancements are likely to create a trading environment driven by increasingly sophisticated AI systems. AI’s Impact on Price Action Price action—the study of historical price movements to predict future trends—is foundational to many trading strategies.

AI's integration into trading may begin reshaping this traditional paradigm in several potential ways: Enhanced Trend Identification AI’s speed and accuracy in identifying trends far outpace traditional methods: Faster Recognition: Algorithms can process vast datasets in real-time, detecting emerging trends before they are visible to manual analysis. Greater Accuracy: AI can filter out noise and focus on genuine market movements, providing more reliable insights. Predictive Analytics AI’s predictive capabilities extend traditional market forecasting: Forecasting: Using historical data and complex algorithms, AI predicts market shifts with varying confidence levels.

Scenario Analysis: Simulating multiple market conditions, AI helps traders prepare for diverse outcomes. Changing Trend Lifecycles AI-driven strategies could alter the nature and duration of market trends: Accelerated Trends: Rapid AI-driven trades may shorten the lifecycle of trends, making them more volatile and less predictable. Increased Volatility: High-speed trades based on AI predictions can lead to significant price swings in short timeframes.

Behavioural Impacts AI is likely to influence trader behaviour and market dynamics: Herding Behavior: Similar AI-driven insights can lead to collective actions, amplifying price movements. Strategy Diversification: To remain competitive, traders must develop diverse and creative strategies. Challenges and Risks While AI offers tremendous potential, it also introduces challenges traders must navigate: Increased Market Volatility AI’s speed and efficiency can exacerbate short-term market volatility.

Sudden price movements may trigger stop-losses more frequently, disrupting traditional risk management strategies. Flash Crashes Algorithmic trading can lead to flash crashes—sudden, sharp price declines caused by cascading AI-driven trades. These events create liquidity risks and potential financial losses.

Over-Reliance on AI Dependence on AI systems could lead traders to overlook market fundamentals, exposing them to algorithmic biases and failures. Reduced Effectiveness of Traditional Tools As AI reshapes market behaviour, traditional tools like moving averages may lose reliability, forcing traders to adopt more dynamic approaches. Ethical and Regulatory Concerns AI introduces challenges around transparency, data bias, and compliance with evolving regulations, requiring constant vigilance.

How to Adapt and Thrive To improve the chances of potential better outcomes in a new more AI-driven market, traders must adopt proactive strategies that embrace rather than push away likely changes in the traditional ways of looking at markets. These may include: Review and Refine Your Strategies Evaluate how AI might impact your existing methods, particularly those reliant on lagging indicators. Incorporate real-time data analysis tools to complement traditional approaches.

Action: Conduct stress tests on your strategies under simulated high-volatility scenarios to ensure resilience. Leverage AI for Competitive Advantage Explore AI-powered platforms for market analysis, trade recommendations, and risk management. Develop custom AI models tailored to your trading style.

Example: Use machine learning to identify unusual trading volumes across multiple markets, providing actionable insights into potential opportunities. Strengthen Risk Management Practices Adapt stop-loss levels dynamically based on real-time volatility metrics. Diversify portfolios to reduce exposure to single-market risks.

Action: Incorporate scenario analysis tools to prepare for unexpected market conditions, such as flash crashes or sudden policy changes. Stay Informed and Educated Keep up with advancements in AI and its applications in trading by attending webinars, reading industry reports, and engaging with experts. Experiment with AI tools in demo accounts to understand their capabilities and limitations.

Example: Test AI-based predictive analytics platforms to evaluate their effectiveness in your trading strategies. Harness Human Creativity and Judgment Combine AI-driven insights with personal market knowledge to develop hybrid strategies. Focus on areas where human intuition, creativity, and adaptability can complement AI’s analytical power.

Action: Use AI as a decision-support tool, relying on your judgment for execution and fine-tuning strategies. Conclusion AI is transforming financial markets, presenting both opportunities and challenges for traders. While its speed, accuracy, and predictive power can disrupt traditional methods, those who adapt their strategies and leverage AI’s potential stand to thrive.

By refining approaches, strengthening risk management, and staying informed, traders can navigate the complexities of AI-driven markets and position themselves for success. The future of trading is here. Embrace the change, adapt your strategies, and unlock the potential of AI to gain an edge in an increasingly competitive market.

Introduction: Understanding the Impact of Entry Errors Trade entry is a critical moment that is undoubtedly contributory to the success or failure of a trade (although exits remain an additional key component of course). Whilst many traders focus much energy and effort on entries, the importance of a well-planned and so called ‘high probability entry’ is often underestimated. Poor entries can put traders at an immediate disadvantage, increasing risk exposure, reducing profit potential, and fostering a cycle of emotional and often questionable decision-making at this critical point of any trade.

This article delves into the most common entry mistakes traders make, why these errors occur, and, more importantly, how to avoid them. Many of these are insidious but if remain unchecked can lead to disappointment in trading outcomes, and at worst, may result in significant trading losses if they are not addressed over time. Through developing a greater understanding of the psychological pitfalls, potential technical missteps, and strategic errors made behind poor entries, traders can take actionable steps to enhance their consistency and performance in the markets.

Whether you're a beginner or an experienced trader, mastering your trade entry process can have a profound impact on your long-term trading outcomes and ultimate success or otherwise. The great news is that many of these are not “hard” fixes. Although by no means an exhaustive list, and often connected, these TEN errors in our experience appear to be the most common, Use these areas covered below as a checklist, making notes on any aspect that may resonate you’re your behaviour and of course subsequently take appropriate action as needed. #1.

Chasing Price Implications: Chasing price happens when traders enter impulsively after a sharp price movement in a particular direction. This is often driven by FOMO (Fear of Missing Out), and typically results in buying at overextended levels where a trend is already very established and may have almost run its logical technical course. This often results in a trade reversing or at best price exhaustion and little or no positive outcome over time.

Price reversal will often, even with the appropriate risk management in place result in repeated losses. Solutions: Develop a disciplined approach by waiting for either retracements to logical support levels, with of course evidence either of a bounce upwards, or even a breach of a new key level, or previous swing high (or low if “going short”). Either of these approaches may result in achieving a more favourable entry.

Also many trading platforms, including MT4 and MT% GO Markets platforms can use notification alerts to identify when the price reaches these levels, which is a useful feature that may assist in making sure robust decision-making occurs on a consistent basis. Additionally pending orders may also be used as part of your effective entry toolbox, set with more “cold” logic rather than being driven by emotional excitement of price velocity that may often be short-lived. #2. Ignoring Market Context Implications: Ignoring the broader market environment leads to trades that contradict prevailing trends or key market conditions.

T his oversight often results in entering trades with low probability, increasing the likelihood of stops being triggered. For long-term success, aligning trades with the dominant market forces is not only logical but appears from any research performed to be generally higher probability of at least some period of time where it is more likely that price will move in your desired direction. Failure to do so on a regular basis, can leave traders feeling like they're always on the wrong side of the market.

Example: A trader shorts the S&P 500 during a small pullback, not realising the index is in a strong uptrend on the daily chart. The pullback ends, and the uptrend resumes, quickly hitting the stop-loss. Solutions: Perform a multi-timeframe analysis before entering a trade.

Use higher timeframes (e.g., daily if trading an hourly timeframe) to understand the broader trend and ensure the trade aligns with it. Incorporate trend-following tools like moving averages or trendlines to validate entries is of course a common method to help substantiate this approach. #3. Over-Leveraging Positions Implications: Over-leveraging magnifies both potential profits and losses, but the latter can have devastating consequences.

Even small adverse price movements can wipe out significant portions of an account, leading to margin calls (and so taking “exit control” away from the trader) or even complete account depletion. This often traps traders in a cycle of "chasing losses," further compounding mistakes. Solutions: Implement strict position sizing rules.

For example, risk no more than 1-2% of your account on a single trade by adjusting your position size relative to your stop-loss distance. Your maximum ‘Risk per trade’ should be based on your Tolerable risk % of Account size per trade (e,g, 1%) x Entry price to Stop-loss distance. #4. Entering Without a Stop-Loss Implications: Trading without a stop-loss exposes traders to uncontrolled risk.

It fosters a dangerous mindset of "hoping" the market will work in their favour, often leading to mounting losses. A single large loss can undo months of profitable trading, shaking both confidence and capital and so have longer term psychological implications such as loss aversion, which can further distort good decision-making. Solutions: Use stop-loss orders based on logical technical levels, such as below a recent swing low.

Although less pertinent to entry but equally important through the life of a trade is potential use of trailing stops can also help lock in profits as the price moves favourably, protecting against reversals and of course profit targets based on logical potential technical pause or reversal points. #5. Over-Reliance on Indicators Implications: Indicators are helpful tools but are often misused when relied upon as the sole basis for trade decisions. Many indicators are lagging by nature, meaning they reflect past price movements rather than anticipating future ones.

Blind reliance on indicators can lead to late or false entries, especially in trending or volatile markets. Price action and associated volume should be treated as the primary decision making points with indicators used for confluence, Example: A trader buys a stock because RSI indicates oversold conditions, but the stock continues to decline as the market remains in a strong downtrend. Solutions: Combine indicators with price action and market context.

For example, use RSI or MACD as confirmation for setups rather than primary signals. Always validate indicator signals with chart patterns, price range within a specific candle, and/or key levels of support/resistance. #6. Trading News Events Implications: News events often create sharp volatility, which can lead to slippage, widened spreads, and unexpected losses.

Trading without a structured plan during (and arguably before) such events exposes traders to heightened risk, especially in fast-moving markets. Examples: A trader enters a position before a Federal Reserve announcement, expecting dovish remarks. Instead, hawkish comments cause a rapid market reversal, leading to a significant loss.

It is worth noting that it doesn’t even have to be an adverse announcement to that which was expected to disappoint. If one believes, as is often cited, that everything that is known or expected is already “priced in” then even an expected number or news release can fail to provide a potentially profitable price move. Also of course, equally as dangerous to capital is not to be aware of significant market events at all.

To enter prior to these from a place of ignorance that they are even happening is potentially as damaging to capital.. Solution: Use a trading calendar to track upcoming high-impact news events. If trading news is part of your strategy, place pending orders above and below key levels to capitalise on breakouts while controlling risk. #7.

Trading Impatience Implications: Entering trades prematurely often leads to setups that fail or require larger stop-losses to accommodate unnecessary volatility. This behaviour stems from a need to "be in the market," and this “itchy trigger finger” which is in essence a compromise of discipline arguably can increase the likelihood of losses. Example: A trader buys a stock before confirmation of a breakout, only to see the price reverse and remain in a sideways trend for a prolonged period of time not only failing to see that specific trade do well but also arguably adds opportunity risk as that money invested could be in a trade that has indeed set up to confirm a change of sentiment, Solution: Establish clear entry criteria and wait for confirmation, such as a candle closing above resistance.

Articulate these clearly and unambiguously within your trading plan, #8. Misjudging Risk-Reward Ratios Implications: Poor risk-reward ratios undermine profitability. Even with a high win rate, losses can quickly outweigh gains if the potential reward doesn't justify the risk.

Either a failure to have defined acceptable levels articulated within your plan or ignoring (based on previous price action) potential pause or reversal points are the two main causes. Example: A trader risks $500 to make $200 on a trade. Over several trades, a few losses wipe out multiple winning trades.

Solutions: Ensure a minimum risk-reward ratio is stated for example 2:1 before entering. For instance, if risking $100, target a profit of at least $200 to maintain positive expectancy. #9. Over-Trading Implications: Over-trading leads to increased transaction costs, emotional exhaustion, and reduced focus on high-quality setups.

This is often driven by revenge trading or overconfidence after a winning streak. Example: A trader takes several trades in a single session after a loss, compounding mistakes and ending the day with a larger drawdown. Solutions: Set a daily trade limit and focus on quality over quantity.

Use a trading journal to reflect on your trades and identify patterns of over-trading. #10. Ignoring Correlation Between Assets Implications: Trading multiple correlated assets amplifies risk, as adverse moves in one asset can lead to simultaneous losses across others. Hence, even if say a 2% maximum risk is assigned to a single trade, if trades are highly correlated then that risk is multiplied potentially by the number of trades open.

Example: A trader goes long on EUR/JPY, AUDJPY and GBP/JPY and a sharp JPY rally causes losses in all three positions. Solutions: Use correlation matrices to assess relationships between instruments and diversify by trading uncorrelated assets. For instance, balance a forex position with a commodity trade.

Summary: Trade entry mistakes are often rooted in a combination of emotional decision-making, poor planning or preparation, and over-reliance on tools or strategies without proper context. By identifying these common errors and implementing structured solutions, traders can greatly enhance their ability to execute high-quality trades. The key to success lies in discipline, patience, and a willingness to adapt and learn from mistakes.

Start reviewing your entry process today, be honest with any of the above that may resonate with you (As awareness is always the first step in improvement) and give yourself the chance to potentially transform your trading outcomes over time.

Yellowcake - a commodity that is loved and loathed all in the same breath. The questions we have been asking are - which is right and what’s the outlook? Because as traders and investors that dilemma is key, there is a gap here and that leads to volatility and incorrect pricing in the short and long term some may want to jump on.

Recent developments in the uranium market suggest we may be witnessing the beginning of a significant shift. After a prolonged period of downward pressure on prices, two key events over the past two weeks have kicked yellowcake back into the minds of traders. First is the geopolitical supply shock, the second are signals of increased long-term demand.

That is music to us in economics as this is a pure supply and demand thematic and suggests a potential reversal. Together, they could usher in a new phase of steady price appreciation, reminiscent of the market's bullish run in 2023. Point 1: Demand Side: U.S.

Energy Policy Could Lay the Foundation for Long-Term Growth The first major factor influencing uranium demand stems from the U.S. political landscape. The election of President-elect Donald Trump introduces a new energy agenda, one that could reshape the trajectory of nuclear power in the United States. While Trump's campaign rhetoric and early post-election messaging have heavily emphasised fossil fuel expansion - check last week’s piece on the "drill, baby, drill" thematic - it’s clear that nuclear power also holds a significant place in his vision for America’s energy future.

Trump has repeatedly voiced support for nuclear energy, particularly for small modular reactors (SMRs). These advanced nuclear technologies are seen as the next generation of clean energy solutions, offering modular, scalable power generation with enhanced safety and efficiency. In recent speeches and interviews, Trump has highlighted (in his view) nuclear energy is part of the solution needed in achieving sustainability, lower carbon emissions, and enhancing U.S. energy independence.

That last point is actually his biggest driver here being an America First ideal. This policy focus could mark a critical inflection point for uranium demand globally. While nuclear infrastructure projects are long-term endeavours and won’t generate immediate demand for uranium, the signals are clear: the U.S. government may soon prioritise nuclear energy investments in ways we haven’t seen in decades.

It also comes at a time when the likes of France and to some extent greater Europe moves in this direction. Either way as these plans materialise, uranium’s importance as a strategic resource will only grow. Moreover, Asia is also shifting its focus to this energy source as well.

Asian countries are increasing their reliance on nuclear energy to meet ambitious carbon neutrality targets. This international momentum could compound the effects of U.S. policy changes, creating a robust foundation for sustained uranium demand over the next decade. Point 2 Supply Side: Part 1 Russia’s Export Restrictions Tighten the Market The second major development is far more immediate and impactful.

That changes on the supply side of the equation. Last week, Russia announced new restrictions on the export of enriched uranium to the United States, escalating geopolitical tensions and significantly disrupting global supply chains. This move mirrors the U.S.’s earlier ban on Russian uranium imports, imposed in May 2023 as part of broader sanctions against Russia.

Historically, Russia has been a critical player in the global uranium market, supplying enriched uranium to numerous countries, including the United States. In 2023 alone, Russia accounted for 28 per cent of U.S. enriched uranium imports, a substantial share of the market. Although U.S. sanctions effectively ended these imports by August 2023, waivers remain in place for select companies, allowing limited purchases from Russian suppliers until 2028 such as Centrus Energy and Constellation Energy.

What isn’t clear is whether any imports have actually taken place under this exemption since the sanctions were tightened. Either way Russia’s new export restrictions will exacerbate existing supply chain constraints and are likely to push U.S. utilities to seek alternative sources of enriched uranium. This, in turn, should drive increased activity in both spot and futures markets as energy providers scramble to secure long-term supply agreements.

The ripple effects of these restrictions may also spill over into global markets, further tightening the balance of supply and demand. Part 2 Wider Supply Challenges: A Tighter Market Ahead The second part of the supply side equation is that Russia isn’t the only player and recent production reports, and other geopolitical issues are also driving shortages in uranium For example: Niger’s Production Halt: Orano, a major uranium producer, recently placed Niger’s only operational mine into “care and maintenance” code for moth balling due to logistical challenges. The catch with putting mines into care and maintenance is that once its down it takes months (sometimes years) to return to full capacity.

So it’s not just a here and now story. Be aware this mine, which has an annual capacity of 2,000 tonnes of uranium (tU), accounts for approximately 3 per cent of global supply. The halt underscores the fragility of the uranium supply chain in politically unstable regions.

Junior Miners Struggling: Smaller uranium miners are cutting their production targets for 2024 and 2025 due to a combination of slower-than-expected ramp-ups, lower ore grades, and resistance from local communities. Collectively, these issues have removed an estimated 2,600 tU from projected global supply—roughly 4 per cent of the market. Offsetting Gains Insufficient: While Cameco has announced a 1-million-pound (365 tU) increase in its 2024 production guidance thanks to improved performance at its McArthur River mine, these gains are insufficient to offset broader supply losses.

With supply tightening, producers struggling to meet commitments in the spot market, the pressure is building on the supply that is in circulation – and that is a price enhancer. Where does this leave Uranium? These developments create a powerful pinch point in the uranium market.

There is a promising long-term demand story evolving driven by potential shifts in U.S. energy policy and global momentum toward nuclear energy. On the flip-side, immediate supply constraints, driven by geopolitical tensions and production challenges, are tightening the market. The convergence of these factors could mark the start of a new cycle characterised by sustained price increases.

While it’s too early to definitively declare a bull market, the conditions are becoming increasingly favourable. For investors, this shifting landscape presents an opportunity. If supply disruptions persist, the uranium market could experience a strong rebound in the coming months.

Prices in both the spot and term markets are likely to reflect this tightening balance, creating a more attractive risk-reward dynamic for those positioned to take advantage of the trend. Big caveat - the uranium market is notoriously volatile and can see +/- 20 per cent moves in days or weeks. But the current setup suggests a potential turning point that could define the market's trajectory for years to come.

Why you need to understand this market concept to improve your trading: Market Correlation For new traders and experienced traders, it can be daunting trying to find the best assets to trade. Whether it be equities, foreign exchange or indices, traders should be trying to have as many factors pointing in their favour as possible when entering a trade. These factors can include, the general trend of the individual asset, the price action at the time of entering the trade, candlestick patterns, use of technical indicators, among many others.

However, one thing that all traders should know about and understand is correlation. What is Correlation? Correlation is the pattern or relationship of how one asset performs relative to another asset.

In statistics, there are mathematical measures of correlation including covariance, correlation coefficients and other terms to describe the relationship of one asset to another. These methods can also be used to quantify asset correlations. A correlation between assets can be positive negative or uncorrelated.

Understanding which relationship between different assets can help provide some indication of the way in which an assets price will go. Below is a diagram that shows how the return of assets can be plotted against each other and the potential relationship. For example, imagine that there are two gold companies Gold company A Gold company B Assume that the price of their shares is perfectly, positively, correlated.

This means that when gold company A’s share price rises by 1% company B’s share price will also rise by 1%. This same price action will occur in reverse if the price of company A falls by 1%. Now in practice no two assets are perfectly correlated.

However, two or more assets may be very strongly correlated. Therefore, identifying how correlated certain assets are and how the price of one impact on the other can be a powerful tool. What creates correlation?

Strong correlation between assets usually occurs because the price of the different assets is material impacted by very similar factors. For instance, two companies in Australia may be more correlated than one company in Australia and one company in the USA. This is because geographically the Australian companies will be affected the local economic conditions.

This may include things such as inflation, taxation policies and other geographical specific conditions. Other factors that can influence the correlation include similarity of the assets or a company’s business operations, being in the same sector or a range of other factors. For example, see the correlation between the ‘Big 4’ banks in Australia below.

It can be seen due to how similar the businesses are and the conditions of which they operate in the pattern on returns are almost identical. Index correlation An important phenomenon to understand is the law of averages and big numbers. Essentially, if large companies are grouped together then they act as a good proxy for the overall market or a specific sector.

This essentially is what an ETF or and Index is. Therefore, as it represents how most individual companies are performing, most companies will be to a degree correlated to the overall market index or relevant sector index or ETF. Size matters Another important thing to understand about how correlation works is that smaller assets or companies will tend to correlate towards the performance of the major players within the sector.

For instance, in the technology sector, smaller technology company’s such as zoom will likely be correlated to larger companies such as Apple and Microsoft by virtue of being in the same sector. Correlations do not just occur in equities and are prevalent in FOREX and commodities. Correlation can be found between growth assets such as the Nasdaq Index which is a technology heavy Index and growth currencies such as the AUD or NZD.

Similarly, more stable assets such as the Dow Jones will likely be more correlated to commodities such as oil, they represent more stable industry and manufacturing sectors. How does it improve your trading? By simply being aware of the direction of the correlated assets, a trader is better able to trade with underlying trend and momentum.

This is vital when trying to optimise edge and improve trading accuracy. It can also equally show when a stock is underperforming or overperforming. For instance, if the general trend of a sector leader is trading 5% higher over a certain period, and a smaller company in the sector is trading at 10% higher it is outperforming the ‘sector’ and understanding why this occurs is an important step into deciphering what is driving price action.

Having a good understanding of how assets correlate can also help find potential trading opportunities earlier than others. This is because by following a sector it becomes easier to see which assets still may have room to shift their price. Ultimately, if a trader can develop their identification of patterns of correlation and the reasons for the relationships between different assets it can provide a trader with a much stronger and accurate edge.

China’s recent shift in economic policy and its potential for fiscal stimulus reflect an evolving approach to support economic stability. Following previous monetary easing measures, including a reduction in the Reserve Ratio Requirement and interest rate cuts in late September, China’s National People’s Congress (NPC) Standing Committee has now approved a local government debt restructuring plan. This plan allows for up to RMB 10 trillion (~US$2.54 Trillion) in debt adjustments, including a one-time increase of RMB 6 trillion in the special debt ceiling over 2024-2026, and an additional RMB 800 billion in special bond quotas annually from 2024 to 2028.

These measures align with expectations, the catch – it’s estimated to add just 0.1 per cent to China’s GDP. Naturally this left the market disappointed and saw Chinese equities shredded. But it's more than the lack of direct demand-side stimulus.

It’s the vague guidance on the use of bonds for banking sector recapitalisation as well as poor outlining on housing inventory buy-backs, and idle land. It's all a bit, ‘nothing’. Now we admit market expectations had been high, so price falls were inevitable, but the metals prices post-meeting were telling from both a short- and longer-term perspective.

First support for the housing market may be limited in the near term, given that primary home sales for top developers turned positive up 15 per cent year-on-year from June last year and home prices rose slightly 0.4 per cent in 50 cities September to October. Second is a possible trade war and having some powder dry as it gears up for the next four years of a Trump 2.0 administration. Fiscal Stimulus is clearly going to be part of this.

And already we have seen Finance Minister Lan Foan, in comments to the South China Morning Post discussing this very point. He pointed out that China’s Ministry of Finance has a readiness for fiscal expansion starting in 2025 and that China’s current debt-to-GDP ratio (68%) provides fiscal headroom, especially in comparison to Japan (250%) and the U.S. (119%). So is that suggesting it’s a ‘when’ not an ‘if’?

From a trader and markets perspective the answer may come at the Central Economic Work Conference in December is expected to outline specific fiscal measures for 2025, potentially focusing on reducing housing inventory, boosting infrastructure, and enhancing social welfare and consumption. The market consensus is for between RMB 2-3 trillion in fiscal expansion over the next one to two years, likely with an initial emphasis on infrastructure investment over consumption support. We should point out this could be a “fourth strike and you’re out” territory as expectations for delivery since Gold Week celebrations have been 0-3, a fourth miss might see the markets completely ignoring what has been promised.

However if it does eventuate looking historically, such investment-heavy stimulus cycles have bolstered demand for steel and other raw materials. China’s past stimulus responses, particularly during the 2018-19 U.S. tariff period, included fiscal stimulus and currency depreciation, indicating that fiscal policy could adjust in response to global economic factors. However, China’s approach to fiscal expansion this time may differ slightly from past cycles: Reason 1: Steel Demand: Prior fiscal expansions, such as during 2009-2010 and the 2018-19 tariff period, drove strong steel demand growth.

Investment in steel-intensive infrastructure, for example, boosted annual steel demand by approximately 200 million tons (a 30 per cent increase) between 2016 and 2019, raising the steel intensity of GDP by 7 per cent. Given China’s high cumulative steel stock—estimated at around 8.5 tons per capita (approaching developed-nation averages of 8-12 tons per capita)—the scale of future infrastructure investment may be more limited, as large physical projects are increasingly complete and the need for new largest scale projects is moderating. Reason 2: Shift To Consumption and Social Welfare: Since 2018 China has subtly and gradually shifted fiscal efforts toward consumer support and social welfare to address deflation risks.

This shift is likely to accelerate, as policy moves to an emphasis on stimulating internal demand through social spending. Now historically China has often favoured investment-driven stimulus to support GDP growth targets, which could mean another infrastructure-led, steel-intensive approach if economic conditions demand it, albeit possibly on a smaller scale than in the past, but again 0-3 on promises, there are risks it doesn’t materialise this time around. The next part of the story for commodities and a China stimulus story is the impending trade war.

China is clearly facing headwinds for its exports, given the likely policy changes from the second Trump administration. The biggest issues are the 10 per cent tariff on all imports and up to 60 per cent on Chinese goods. The timing and specifics of the tariffs are uncertain, but using his 2016-2020 timelines as a guide it's likely to be one of the first programs enacted and new tariffs could emerge as early as the first half of 2025.

Currently, more than 20 per cent of China’s steel production is tied to exports—11 per cent directly and 12 per cent indirectly through products like machinery and vehicles—any new tariffs on Chinese goods would likely impact steel output and, subsequently, iron ore demand. During the 2018-19 tariff period, China’s direct steel exports to the U.S. declined, but this was balanced by growth in indirect steel exports via manufactured goods and bolstered by domestic infrastructure demand which is hard to see this time around. 2025 strategies China might deploy to counteract any new tariffs could include currency depreciation, reciprocal tariffs, re-routing exports to new markets, and increased fiscal and monetary stimulus. Interestingly the U.S. comprises only 1 per cent of China’s direct steel export market, it the larger share for indirect exports, particularly machinery ~20 per cent that is the issue.

Since 2018, China has expanded its steel-based goods exports by focusing on emerging markets—a resilience that will likely be tested further if tariffs intensify next year. So where does this leave iron ore? Current iron ore prices, hovering around US$100 per tonne, seem to reflect current market fundamentals pretty accurately.

The substantial net short positions in SGX futures, which were prevalent prior to the late-September stimulus, have notably diminished in the past 6 weeks China’s recent policy adjustments have mitigated the downside risks for steel demand for the remainder of 2024. This is coupled with solidifying demand indicators and restocking activities, which may bolster seasonal price strength as the year concludes. Nevertheless, the potential impact of a seasonal price rally may be constrained by relatively high port stock levels, which presently stand at about 41 days of supply which again underscores why price around US$100 a tonne is accurate.

Looking ahead to 2025, the Ministry of Finance in China signalling forthcoming fiscal expansion suggests a potential upside risk. However, potential new tariffs from the U.S. may pose challenges to steel export volumes, potentially counteracting the positive effects of domestic fiscal measures. China’s response to such tariffs—potentially through currency depreciation, trade redirection, or additional fiscal and monetary stimulus—will be crucial in mitigating these pressures.

But this would be a zero-sum game effect. Thus any upside risks are counted by downside risks – this leads us to conclude that China is not going to be the White Knight of the past. And that 2025 is going to be a tale of two competing forces that sees pricing see-sawing around but finding equilibrium at current prices.

This also leads us to point to equities – iron ore and cyclical plays have benefited strongly over the past 24 months on higher prices and the long COVID tail. 2025 appears to be the year that tail ends and a new phase will begin.