FOREX NEWS

According to the Chinese Lunar calendar, the 17th of February 2026 marked the start of the year of the horse. Traders searching for an edge may ask themselves what this could possibly mean for financial markets, after all, as a certain Mr. John Pierpont Morgan once said: “millionaires don’t use astrology, billionaires do”. Strong words, and while there is no historical evidence of the famous financier ever uttering such a phrase, it goes without saying that investors can be a very superstitious bunch. The year of the horse comes around every twelve years, so there should be enough data points to establish at least a partial picture. So how does our four-legged friend measure up to the rest of the roster? Lunar performance of the S&P 500 A fast, but skittish and fickle animal, the horse is hardly the kind of beast investors would want to represent their portfolios, but let us not be too hasty. How have markets fared during previous years of the horse? Using the S&P 500 as a benchmark, we can run the numbers for every lunar year dating back to the late 1920s, which is when Standard & Poor’s began publishing daily index data. The 23rd of January 1928 ushered in the year of the dragon, which would last until the 9th of February 1929, and so on and so forth, lunar year by lunar year until 16th of February 2026, which concluded the year of the snake. We can calculate the annual return for each period, and then average the results across each animal, as displayed below: As per the above chart, at 6.2% the horse is a relatively safe bet, firmly in the middle of the pack. Reliable, but nothing exceptional. The clear winner is the pig, providing an average return of over 15%. The next year of the pig will come around in 2031, so mark your calendars for that. The clear loser is the snake, which is the only animal to yield an average negative return at -1%. Had it not been for the impressive surge in stocks last year, the year of the snake would look even worse. Of course, even with a century of data, each animal has only 8 or 9 data points with which to pad their resumé, so outlying years will heavily skew the results. In fact, the first year of the horse for which we have records, starting on the 30th of January 1930, would experience much of the fallout from the great Wall Street crash of 1929, resulting in a 22% loss for the S&P 500 during that period. 2002 would be another rough year, with the horse bearing the brunt of the dot-com bubble burst, Enron fraud and September 11th attacks, during which the SPX would shed 23%. In contrast, our noble stead would also witness some of the strongest bull markets in history, such as the peacetime boom of 1954, which would yield a massive 37% return. Quantifying volatility The year of the horse seems to go from one extreme to the other, covering some of the most volatile periods in financial markets. Not only that, but such years typically exhibit large price ranges as well as far greater volatility than average. In fitting with their nature, horse years have historically offered plenty of action to traders. By crunching the numbers, we can in fact quantify this phenomenon. If we take the tops and bottoms for each given period and divide by the mean, we obtain a measure of the spread in prices for each lunar year. Sure enough, by this metric, the horse is a wild beast indeed, offering large trading ranges over the course of its reign. Only the tiger provides a wider playing field. Trading ranges are one element, but we can go deeper. To properly understand the trading conditions of a particular period, we need to quantify the market volatility during such times. To do this, we calculate the standard deviation (σ) of daily closing prices across each lunar cycle. This tells us how spread out the different prices are within the range itself. Essentially, this is a measure of how chaotic each year has been. After calculating the standard deviation (σ) for each year, we then divide by the mean (μ) of that period, thereby normalising results and accounting for the huge growth observed in the S&P 500 index over the past century. This gives us the coefficient of variation, a quantifiable measure of the trading volatility within each given year. Finally, we average the coefficient of variation for each Chinese zodiac animal, expressed as a percentage, summarised below: Several observations. Firstly, the horse is a consistently volatile year, beaten only by the ox. Secondly, there does not appear to be a clear relationship between performance and volatility, which is an interesting result in and of itself. Thirdly, with a low of 5.1% and a high of 8.3%, the spread between coefficients is meaningfully large. Our current data set is far from ideal. To obtain a statistically significant result, we would need to roughly double our sample size, which we cannot do without waiting around for another century. The above results are in fact solid enough to suggest a trend, but not robust enough to demonstrate one. Lunar performance of the Nikkei 225 Of course, the S&P 500 is only one index, for one stock market, in one country. Hard to establish global trends with such a limited data set. How do other markets fare according to the Chinese Lunar calendar? Unfortunately, this is where we rapidly encounter a problem. For most markets, the data simply do not exist over a meaningful time frame. Given the twelve-year cycle, a couple of decades of price information is just not enough. We can look up the daily close for the S&P 500 all the way back to 1928 without issue, but the same cannot be said for much else. We do have one overlooked exception however: the Japanese Nikkei 225, for which we have daily records stretching back to 1949. Repeating the same steps as above, we obtain the average results for each Chinese zodiac animal: The first point to note is the wider spread of average returns compared to the S&P 500. The dragon, rat and rabbit can all boast average returns of over 20%, while the horse, sheep, dog, ox and tiger all fail to offer more than 5%. The second point of interest is the fact that our poor horse ranks rock bottom in terms of average returns. If previous results are anything to go by, investors would do well to get out of Japanese stocks as soon as possible. As with the S&P 500, we can also calculate the volatility for each period, using the same methodology as above: Once again, several observations. Firstly, the horse may be on the higher side, but this time is no longer an outlier. The dragon and snake are both more volatile, while the rat is in a league of its own. Secondly, unlike the S&P 500, there does appear to be a link between performance and volatility within the Japanese index. Thirdly, with a low of 5.3% and a high of 12.2%, this time the spread between coefficients is in fact statistically significant. Interestingly, this suggests that changes in performance in the Nikkei 225 across lunar years are not random. Of course, this time around the sample size is even smaller than it was for the S&P 500, making the results extra sensitive to outliers. Nevertheless, a pattern has cautiously presented itself. Final thoughts Analysing the S&P 500 and Nikkei 225 indices according to Chinese lunar cycles reveals some interesting bits of information. The Japanese stock market appears to be more heavily tied to the lunar calendar than its American counterpart, with the dragon, rat and pig being particularly beneficial years. There is a possible explanation to this in how the two financial markets have historically performed. US markets have typically followed shorter, more frequent credit cycles, thereby smoothing over the results. On the other hand, the Japanese economy has followed much more prolonged boom and bust cycles, often lasting decades, with which the lunar cycle has happened to coincide. Either way, if historical patterns are anything to go by, US markets are set for a volatile year. Turning to Benjamin Franklin this time: “by failing to prepare, you are preparing to fail”. Buckle up. → Read the annexe

I’ve been trading for 15 years now, so I guess you could call me an old sweat - the kind of trader who has seen more ups and downs in the markets than most people have had hot dinners. I’ve watched trends come, go, come back again, disappear completely, and then show up five years later pretending they were never really gone. At some point in every new forex trader’s journey, they stumble across the magical term Expert Advisor, or as the cool kids call it, an EA. In simple terms, an EA is a little automated program that trades your account for you. No clicking, no overthinking, no panicking when your trade goes 20 pips against you, the robot does the heavy lifting while you sit back and watch the dollar’s drop into your account. For many beginners, this sounds like the ultimate shortcut. No need to learn charts. No need to understand risk. No need to wonder where the market is going, because your shiny new robot “knows things.” Amazing, right? Well… brace yourself, because I’m about to burst a few hopeful trading bubbles. Most EAs don’t work. There, I said it. Now let’s get into the fun part, why this is the case. Let’s be honest: the moment humans discovered that a robot could potentially make money for them while they slept, ate, watched the Disney channel, or pretended to “work from home,” EAs were always going to explode in popularity. Forex attracts a certain type of person, the dreamer, the hustler, the “I’m one good trade away from quitting my job” optimist. So, when a shiny little software program promises to do all the hard thinking, remove emotions, and generate consistent profits… well, that’s like handing candy to a toddler. They’re taking it, no questions asked. EAs became popular for a few simple reasons: So yes, the popularity makes sense. But now that we’ve praised them, let’s take a look at what they actually do well, because although many disappoint, not all EAs are entirely useless. Let’s give EAs the credit they deserve. While many fall short of their heroic marketing promises, they do offer some genuine advantages. In fact, there are areas where robots outperform humans by a mile, mainly because humans are emotional, impatient, overly optimistic, under-caffeinated, and occasionally just downright chaotic. Here are the key benefits: So yes, EAs do have some solid advantages. But (and it’s a big but) …For every trader who uses an EA successfully, there are thousands watching their account blow faster than you can say “Martingale.” Which brings us to the fun part. (a.k.a. The Part Nobody Mentions on the Sales Page) * EAs sound incredible on paper, like a magical money-printing elf that never sleeps and never complains. But in reality, many of them behave more like a toddler with scissors: unpredictable, dangerous, and absolutely guaranteed to cause chaos when left unsupervised. Let’s break down the real-world downsides. So yes , EAs have disadvantages. Quite a few. But the biggest question is the one most traders ask: “Why do so many EAs fail?” And oh boy… there’s a whole section for that. Most EAs don’t work. Not because forex is impossible. Not because robots are stupid. Not because the universe hates your trading dreams. They fail for a much simpler reason: they’re not built for the real market. Let’s break down exactly why. 1. They Are Over-Optimised to Look Good (But Only in the Past) EA developers love to “curve-fit” strategies. This means: …until the backtest looks flawless. This creates an EA that performs beautifully on historical data and catastrophically on real data. It’s like training for a marathon on a treadmill and then wondering why you collapse on an actual road. 2. They Can’t Handle News Events Most EAs fall apart during: Unless specifically coded to avoid high-impact events, and most aren’t, they will happily open a trade two seconds before Jerome Powell speaks and then blow your account with pride. 3. They Don’t Adapt to Volatility Changes Volatility is not constant. Ranges expand and contract. Markets trend, then consolidate, then reverse. Most EAs use fixed parameters like: That might work on Monday an absolutely destroy the account by Friday. 4. They Fail in Unfamiliar Market Conditions If the EA was built in a trending year, it usually dies in a ranging year. If it was built in a quiet market, it usually dies in a volatile one. If it was built in 2020… well, nothing worked properly in 2020. Robots don’t do improvisation. 5. Most EAs Don’t Understand Price Action They follow signals. Not structure. Not liquidity. Not manipulation. Not market psychology. If you’ve ever watched an EA blindly buy into resistance or sell into demand, you’ve probably felt the urge to unplug your entire computer and start a new life. 6. They Often Use Dangerous Money Management The biggest offender: Martingale. “Double the lot size every time you lose,” they say.“ What could possibly go wrong?” they say. Everything. Everything can go wrong. And it usually does. Grid systems are no better; they work beautifully until they don’t… and then it's account-wipe-out time. 7. They’re Built by People Who Want to Sell the EA, Not Use It Ask yourself this: If you created a robot that could generate 200% profit a year with minimal drawdown…Would you sell it for £49 online? Exactly. Most EA sellers don’t use their own robots. They earn money from selling the EA, not from trading it. That alone is a flashing neon sign the size of London saying: “Be careful.” 8. Most Traders Don’t Actually Know How to Use Them Properly Even a decent EA can fail if: A good EA still needs a good human behind it. So yes… most EAs fail. Spectacularly, in some cases. But don’t worry, the article doesn’t end in total doom. Because despite everything, some traders do use EAs successfully, me included! Alright, let’s bring some balance back, not all robots are destined for the scrap heap. Despite the horror stories, blown accounts, and the occasional EA that behaves like a drunk intern randomly pressing buy and sell…there are traders who use EAs profitably. But here’s the twist: They don’t treat EAs like magic money machines. They treat them like tools. Tools that must be tested, supervised, adjusted, and kept on a short leash, much like a teenager with car keys. Let’s walk through what the successful EA traders do differently. 1. They Use EAs to Automate Good Strategies, Not Create Them A good trader develops or understands the underlying strategy first. Then they automate it. If the strategy is solid manually, the robot simply makes it consistent. If the strategy is rubbish manually, the EA just burns through the account faster, with admirable efficiency. 2. They Test EAs in Forward Conditions, Not Just Backtests Successful EA users don’t fall for the shiny backtest graph. They want to know: They run the EA in demo first, then small live accounts, before scaling it. No shortcuts. No blind hope. No dreaming. 3. They Understand the Robot’s Weaknesses Every EA has a weakness. Trend-followers die in ranges. Grid bots die in strong trends. Scalpers die during spreads widening. Profitable EA traders know exactly when to run their EA and when to pause it. They don’t just leave it running 24/5 hoping for the best. 4. They Use Proper Risk Management (Unlike Most EA Sellers) Smart EA traders: In other words, they treat their EA like it actually trades real money (because it does). 5. They Combine Human Analysis with Automation The best results often come from a hybrid approach: Robots aren’t good at thinking. Humans aren’t good at staying consistent. Together? They can work surprisingly well. 6. They Use EAs for Specific Tasks, Not Total Accounts Smart traders don’t give an EA full custody of their account like handing a 5-ear old the family credit card. They use EAs for tasks such as: This controlled approach preserves the trader’s skill and keeps the robot in its lane. 7. They Avoid “Commercial” EAs Most profitable EA traders don’t buy their bots on Telegram, MQL5 , or shady websites promising 400% returns. Instead, they: The real edge isn’t in buying an EA. It’s in understanding how to use one. So yes, while most EAs fail, some traders do use them smartly and successfully. But traders also need to know the warning signs…because for every good EA, there are a hundred disasters waiting to happen. If you’ve ever browsed EA marketplaces, you’ve likely seen promises so ridiculous they make Nigerian prince emails look trustworthy. To protect yourself (and your account), here are the biggest red flags, the signs that an EA is basically a financial hand grenade disguised as a friendly robot. 1. “99% Win Rate!” This is the classic. If an EA has a 99%-win rate, it’s almost always: These systems win tiny trades repeatedly…until that one losing trade wipes out months, or even years, of gains. It’s not a trading strategy; it’s a slow-motion disaster. 2. No Stop-Loss in the Strategy If your EA doesn’t use a stop-loss, congratulations: You’ve just installed a bomb on your trading account. Robots that never accept a loss eventually take one so huge it makes your screen look like a horror film. 3. “Guaranteed Profits” or “Never Loses” If Warren Buffett can’t guarantee profits…If banks can’t guarantee profits…If hedge funds can’t guarantee profits… …but the guy selling you an EA for £79 can? Absolutely not. 4. Backtests Look Too Perfect Smooth equity curve. Tiny drawdown. No losing streaks. Every trade in profit. This means the developer curve-fitted the EA so tightly to past prices that it basically memorised historical data. Put it in a new environment and it panics like a tourist trying to order food in a foreign language. 5. The Equity Curve Goes Straight Up… …but the balance curve is flat. This means the EA is floating massive losing positions but hasn’t closed them yet. It’s the EA version of shoving debt under the carpet. Eventually, you have to open the door, and it won’t be pretty. 6. It Trades 24/5 on Every Pair No sensible EA trades: These “universal EAs” don’t exist. Markets behave differently, EURUSD is not GBPJPY, and USDJPY is not XAUUSD. If the EA claims to master everything, it’s lying. No two trading days are the same and finding an EA that works in all market conditions is like finding the Holy Grail. 7. Little or No Verified Live Results A MyFXBook with: …is as trustworthy as a politician before an election. If there’s no verified live performance on a real account, stay cautious. 8. The Seller Has No Real Trading Background If someone can build a profitable EA, they’re usually: If the seller has nothing but a flashy Instagram full of rented cars and hotel lobbies…Let’s just say it’s not a good sign. 9. It Uses “Secret Algorithms” or “Institution-Grade Logic” Translation: “It’s just a moving average crossover but we gave it a fancy name.” If it’s so secret, why are they selling it? 10. Ridiculously High Monthly Returns Anything promising: …isn’t a trading robot. It’s a countdown timer to account destruction. Professional funds aim for 10–20% per year. And they have teams with PhDs. By now it’s clear that EAs are not magical printing machines created by benevolent forex angels. But they’re also not worthless. Like many tools in trading, they have their place… as long as traders know when and how to use them. So, let’s break it down, nice and simple. When EAs Can Be Useful 1. When You Already Have a Solid Strategy If you have a proven, thoroughly tested approach, an EA can automate it so you avoid: The robot becomes your assistant, not your replacement. 2. When You Need Consistency If you know your biggest weakness is sticking to rules, an EA keeps you disciplined. No more emotional nonsense. No more tinkering mid-trade. No more “let me just move this stop-loss a tiny bit.” 3. When You Want to Remove Busywork EAs are fantastic for boring-but-important tasks like: Basically, all the stuff humans find tedious, robots love. 4. When You Treat Them Like Risky Employees A good EA trader is like a good manager: EAs shouldn’t have full responsibility. Think of them as interns: Helpful, but absolutely not ready for the keys to the company. 1. When You Expect Them to Make You Rich Without Effort If your plan is: …save yourself the pain. It doesn’t work quite like that. 2. When the EA Uses Martingale or Grid Trading It will work beautifully…until the market trends strongly…then your account will explode more violently than popcorn in a microwave. 3. When You Don’t Understand the Strategy Behind It If you can’t explain: …then you shouldn’t let it touch your money. 4. When You Don’t Use Risk Management EAs need: Taking a reckless EA and adding reckless risk is basically setting your trading account on fire. 5. When Market Conditions Change A trending EA fails in ranges. A range EA fails in trends. A scalper fails during volatile spreads. Robots aren’t built to adapt. That’s your job. Expert Advisors are neither heroes nor villains, they’re tools. Useful in the right hands. Dangerous in the wrong ones. If you’re looking for a shortcut to success, an EA won’t save you. If you’re looking to enhance your trading, automate good processes, and remove emotional nonsense, an EA can genuinely help. The key is understanding the strategy, managing the risk, and remembering one universal truth: As we move into the new era of Ai there is no doubt EAs will advance in their ability to make your trading journey more successful. I have seen, and indeed I am testing new EAs myself which have been created by Ai. Let’s just say the future looks bright, but even the best Ai systems are not quite there yet. Big banks and financial institutions are investing large amounts of money into Ai so they must know something we don’t right? If a robot could truly create guaranteed wealth, it wouldn’t be available for purchase, its creator would be on a yacht somewhere, sipping something expensive. Use EAs wisely and keep your expectations realistic. Always remember in trading, there’s no substitute for skill, experience, and a healthy dose of scepticism.

Markets are on edge because of a potential escalation of hostilities in Iran. The United States continued to amass military assets around the Middle East and Europe over the past couple of days, appearing to move into position ahead of a future conflict. Negotiations between the two parties have not broken down by any means, in fact, Oman’s foreign minister confirmed that talks between the US and Iran would go ahead in Geneva on Thursday, but investors are understandably adopting cautious stances going into this week. . Oil markets have been particularly vulnerable to the ebb and flow of geopolitical sentiment, with the most recent developments pushing the Brent Crude benchmark to a six-month high of $71 per barrel last week. The problem is not so much the lack of oil being extracted from Iranian oil fields, but the threat of disruption to oil flows in and out of the Persian Gulf. Predictably, tensions in the region are affecting precious metals, with gold and silver rising confidently in the early hours of this morning. Gold managed to push north of $5,170 per ounce as the week got underway, while silver climbed over $87, maintaining last Friday’s momentum, which saw the white metal surge almost 8%. On the other hand, cryptocurrencies woke up on the wrong side of the bed this morning, with Bitcoin testing lows of $64,000 and dragging everything else down alongside it. Bitcoin is currently in a rough situation after the mining algorithm sharply increased difficulty by 15% last week, which, paired with relatively low prices, has impacted miner profitability. In light of the current dynamic, some miners are having to sell part of their war chest in order to cover operating losses. One miner, Bitdeer Technologies, sold all its remaining Bitcoin last week, amounting to around 940 BTC, leaving the company’s treasury completely empty. Meanwhile, behind the scenes, US banks and crypto companies are finally starting to near some form of agreement, which should, in theory, signal a green light for the long-delayed Clarity Act. #CrudeOil #Bitcoin #PreciousMetals

The volatility in precious metals showed no signs of abating last week, with silver in particular continuing to undergo wild swings in both directions. Thursday’s forced capitulation event erased any remaining good will for the white metal, resulting in a weekly close of around $77.40 per ounce despite visiting highs of $86 in preceding sessions. Silver is off to a rough start this Monday morning, immediately falling 3% before most traders could even get out of bed. A similar story for gold, which was unable to cling on to $5,000 this morning and is showing a distinct lack of enthusiasm on the buy side. Very little is happening over in cryptocurrencies, with Bitcoin remaining flat so far today. The newly coined “AI scare trade” finally ran out of targets last Friday, leaving markets with no prevailing narrative with which to drive them. US indices all closed flat at the end of last week, settling in early for the long weekend ahead. All in all, it was a disappointing week for US stocks, many of which experienced heavy selling pressure as one after the other, different sectors fell victim to AI fearmongering. Wealth management, insurance, transport, logistics and property all took their turn in the crosshairs, leaving investors with the obvious question of what comes next? Technology companies were the most affected, leaving the Nasdaq Composite 2.1% worse off compared to the week prior, while the S&P 500 and Dow Jones shed 1.4% and 1.2% respectively. The economic calendar is a little sparse over the next couple of days, but will pick up as the week progresses. Tuesday will deliver the latest on the UK labour situation, followed by Canadian inflation figures later in the day. UK inflation follows on Wednesday, before giving way to the FOMC minutes from January. Last but not least, Friday will deliver a slew of data releases, including Japanese inflation figures, US fourth quarter GDP growth, and finally the December PCE Price Index. The earnings calendar meanwhile has little to offer this week, with the exception of Walmart (WMT), which will publish before market open on Thursday. Crucially, the New York Stock Exchange and Nasdaq are closed today in commemoration of Washington’s Birthday, while Chinese markets will remain closed until next Monday in celebration of the Chinese New Year. The lack of market participants is likely to affect volatility today and throughout the rest of the week, especially in precious metals. Extra caution is advised. #XAUUSD #XAGUSD #AIAgent #RADEXMARKETS

Many beginners learn a small library of strategies before asking whether the trading style itself suits them. Someone with a full-time job may attempt screen-heavy day trading, while an impatient trader chooses positions that take months to develop. In my experience, losses often begin with this mismatch of individual time availability and personalities, rather than with the actual trading strategy itself. This guide explains the seven main types of forex traders, how they operate, the time and temperament each requires, and how to decide which type you should be. Forex traders commonly fall into seven types: scalpers, day traders, swing traders, position traders, news traders, algorithmic traders and copy traders. Each type differs in its holding period, trade frequency and required screen time, so your choice should reflect your available time, temperament and capital, not simply which style sounds most profitable. Not sure which trading rhythm suits you? Test different styles under realistic market conditions before risking real capital. A forex trader is someone who buys and sells currency pairs in the foreign exchange market seeking to profit from exchange-rate movements, whether trading independently as a retail participant or as part of an institutional desk. Forex is the world's largest financial market, with global over-the-counter foreign exchange turnover averaging approximately $9.6 trillion per day in April 2025, according to the final results of the Bank for International Settlements Triennial Survey. Its participants range from central banks and commercial banks to investment funds, multinational companies and individual traders. This article focuses on the different ways retail traders approach the market. Two traders can study exactly the same EUR/USD chart and reach similar conclusions yet trade the opportunity at completely different rhythms. One might hold the position for three minutes, while another remains in it for three months, and that is where the idea of trader types comes from. The different types of traders in forex are commonly grouped according to their holding periods, trade frequency and methods of analysis. There is no single official classification, some guides identify four or five types, but the seven below provide a more complete picture by including modern approaches such as algorithmic and copy trading. The ranges in this table are practical guidelines rather than rigid rules. A trader's actual routine will vary according to the strategy, currency pair and market conditions. At one end of the scale, scalpers attempt to collect very small price movements repeatedly and may spend hours watching rapidly changing charts. Day traders work at a slightly slower rhythm but still close every position before their trading day ends. Swing traders hold positions beyond a single session and aim to capture a larger section of a market move. Position traders zoom out even further, making relatively few decisions and allowing fundamental themes or long-term trends time to develop. The remaining types are defined less by holding period and more by how decisions are made. News traders specialise in economic releases, algorithmic traders use programmed rules, and copy traders replicate positions opened by another trader. Each type has its own time demands, costs and psychological pressures. The following sections explain how each trader works, who the style may suit and what its less obvious costs can be, with links to more detailed strategy guides where available. A day trader is someone who opens and closes every position within the same trading day, holding no open trades overnight. Day traders typically keep positions open for anywhere from a few minutes to several hours and may take between one and ten trades during an active session, depending on their strategy. The style relies heavily on short-term technical analysis. Day traders commonly use price action, support and resistance, market trends, chart patterns and indicators to identify intraday opportunities. They must also watch the economic calendar because an unexpected interest-rate decision or employment figure can quickly undo an otherwise sensible technical setup. Day trading generally suits people who: The price of that flexibility is a substantial time commitment. Even if a trader only focuses on the London–New York overlap, preparing, watching for setups, managing positions and reviewing results can consume a large part of the day. Frequent decisions also create more opportunities for fear, frustration and overtrading to creep in. In my experience, when someone without the available hours attempts to day trade, they rarely become an efficient part-time trader. They usually miss the planned entry, chase the move later and then try to manage a fast-moving position between meetings, phone calls or whatever else they should have been doing. Day trading is best treated as a structured routine rather than something squeezed into spare moments. Read more: Forex day trading strategies for beginners: The UK trader's guide 2026 Scalping is day trading at its most compressed. Positions may remain open for only a few seconds or minutes, with a scalper potentially placing dozens of trades during an active session to capture a series of very small price movements. For many new traders scalping is their first introduction into Forex trading. Because each target is small, the margin for error is equally small. A slightly wider spread, delayed order or poor fill can turn an otherwise profitable setup into a losing one. Scalpers therefore tend to favour highly liquid currency pairs, active trading sessions, fast execution and accounts with competitive spreads and commissions. Scalping may suit traders who: The style is often presented as exciting because results appear quickly. What receives less attention is that a scalper must repeat the same process accurately while prices move rapidly and the temptation to overtrade sits permanently within clicking distance. Trading costs are particularly important. If a trader targets five pips but pays one pip through the spread and commission, 20% of the intended movement has already been consumed before slippage is considered. Repeat that across dozens of trades and a strategy can be right surprisingly often while the account still moves in the wrong direction. The higher the trading frequency, the faster costs and small execution mistakes eat into potential returns. Scalping requires more than quick reactions; it requires precise risk control, consistent execution and the discipline to stop when suitable conditions are no longer present. Read more: Scalping trading strategies: How beginners can make quick profits Swing traders hold positions from overnight to several weeks, aiming to capture one substantial leg of a price movement rather than every small fluctuation along the way. They usually establish the broader direction on daily charts before using four-hour or hourly charts to refine entries and exits. Unlike day traders and scalpers, swing traders do not need to watch each candle form. A planned routine might involve checking the market before work, reviewing positions in the evening and setting price alerts for important levels. Swing trading may suit people who: For most working beginners, this is often the most realistic place to start. It provides enough trading activity to build experience without requiring someone to spend the entire London session staring at EUR/USD and pretending their other responsibilities have mysteriously disappeared. The trade-off is overnight exposure. Economic announcements, political developments and changes in market sentiment can move a currency pair while the trader is away from the screen. Weekend gaps create an additional risk because the market may reopen beyond a stop-loss level, causing the trade to close at the next available price rather than the price requested. Swing traders therefore need appropriate position sizes, wider but carefully planned stop-losses and enough patience to let a setup develop. The slower routine does not remove risk, it simply changes the way that risk must be managed. Read more: What is forex swing trading? A complete guide 2026 Position traders hold trades for weeks, months or occasionally longer, aiming to benefit from major trends rather than short-term price movements. They study weekly and monthly charts, combine technical analysis with economic fundamentals, and use daily charts when they need greater precision for an entry or exit. A position trader might form a view based on interest-rate expectations, inflation trends, economic growth or a central bank's longer-term policy direction. Once the position is open, an ordinary piece of market noise on a five-minute chart is unlikely to change that broader view. Position trading may suit traders who: This style produces the fewest trades but takes the widest view of each one. It can be less emotionally frantic than short-term trading, although watching a carefully researched position remain in a temporary loss for several weeks requires a different kind of discipline. The hidden costs are swap charges and locked-up capital. An overnight financing charge may appear small on a single day, but it can become significant when a trade remains open for months. Capital committed to one long-term position is also unavailable for other opportunities unless the trader takes on additional exposure. Patience alone is therefore not enough. Position traders need appropriate sizing, a clear fundamental reason for remaining in the trade and a defined point at which the original idea is considered wrong. Read more: What is position trading? A beginner's guide to strategies News traders specialise in the sharp price movements that occur around major economic releases and political events. Common examples include central-bank interest-rate decisions, inflation reports, employment figures such as US Nonfarm Payrolls, elections and unexpected policy announcements. Their working rhythm differs from the other styles because it follows the economic calendar rather than a fixed daily routine. A news trader may spend hours preparing for an event but hold the resulting position for only a few seconds, minutes or hours. News trading may suit people who: Pending orders and stop-losses can form part of the risk plan, but neither guarantees execution at the requested price. When a major release surprises the market, liquidity can disappear, spreads may widen and prices can jump between available levels. The eventual fill may therefore be several pips away from the price shown on the screen. This gives news trading the highest execution risk of the seven types. A trader can correctly predict the market's direction and still receive a poor result because slippage, widened spreads or a rapid reversal alters the trade before it can be managed. News traders must control risk before the announcement rather than attempting to invent a plan while the price is moving. Fast reactions help, but disciplined preparation matters far more. Read more: FOREX NEWS Algorithmic traders convert their trading rules into computer programs that analyse markets and execute orders automatically. The system might enter a trade when a particular combination of price, volatility and indicator conditions occurs, then manage the stop-loss and exit without waiting for manual approval. The main advantages are speed, consistency and discipline. An algorithm does not hesitate because the previous trade lost money, chase a price because it fears missing out or widen a stop-loss in the hope that the market will eventually come back. It simply follows the instructions it has been given, which is useful only when those instructions are sound. Algorithmic trading may suit people who: The apparent freedom from screen time can be misleading. An algorithm may trade without supervision for part of the day, but developing it requires historical data, back testing, realistic assumptions about spreads and slippage, and testing under live market conditions. Technical failures and poor-quality data can also affect performance. Algorithms remove emotion from individual executions; they do not remove emotion from the person managing the system. After several losses, a trader may still switch off a valid strategy at precisely the wrong moment or keep an ineffective one running because its old back test looked impressive. Strategy decay is the longer-term cost. Market volatility, liquidity and participant behaviour change, so an edge that worked historically may gradually weaken or disappear. Algorithmic traders must continue monitoring results, retesting assumptions and maintaining their systems rather than treating automation as permanent passive income. Read more: Algorithmic trading: How to get started for traders Copy traders do not make every trading decision themselves. Instead, they select another trader or signal provider and use a platform that automatically replicates that provider's positions in their own account, normally in proportion to the capital allocated. This creates the lowest practical barrier to entry among the seven types. The follower does not need to analyse every chart or be present when a position is opened, but the homework has not disappeared, it has simply changed from choosing a strategy to choosing a person. Copy trading may suit people who: A strong recent return is not enough to judge a provider. Copy traders should examine the length of the trading record, maximum drawdown, use of leverage, average holding period, consistency and whether losses are being hidden inside positions that remain open. Ten calm months followed by one spectacular account collapse is not the consistency anyone had in mind. The most important point is that copying someone's trades does not copy their risk tolerance. A provider may be comfortable with a 30% drawdown, use far more leverage than the follower realises or hold losing trades for longer than the follower can financially or emotionally accept. Providers can also change their style, increase their risk or experience a prolonged loss of form. When that happens, the follower's account shares the consequences. Copy trading still requires position limits, diversification, regular monitoring and a clear point at which copying should stop. Read more: What is copy trading? How beginners can get started Choosing a type of forex trader is not about identifying which style earns the most, it is about matching your available time, temperament and capital. If those three do not fit the trading rhythm, even a good strategy becomes difficult to execute consistently. Start with the hours you actually have, not the hours you hope to find once trading becomes exciting. If you can dedicate several uninterrupted hours to an active market session, day trading may be realistic. Scalping requires the same availability but adds a need for continuous concentration and much faster decisions. If you work full time and can check charts once or twice a day, swing trading usually provides a more sustainable rhythm. Someone who can only conduct a detailed review a few times a week may be better suited to position trading. News traders need to be available at specific times rather than all day. This can appear convenient, but important releases do not always fit neatly around work, family or sleep. Algorithmic and copy trading require less time during execution, although developing a system or screening providers still demands proper preparation. Time alone does not settle the choice. You also need a style that fits the way you make decisions and respond to uncertainty. A trader who becomes bored waiting several weeks for a position to develop is unlikely to follow a position-trading plan faithfully. That person may exit too early, interfere with trades or create extra setups simply to feel active. At the other extreme, someone who struggles with frequent small losses may find scalping emotionally exhausting. A scalper can follow the plan correctly, lose several trades in a row and still need to take the next valid setup without hesitation. Consider how you naturally behave: The right style should challenge you without requiring you to become a completely different person every time the market opens. Capital is not simply a question of having a large or small account. The important issue is whether the account can support the style's position sizes, stop-loss distances, trading costs and likely periods of drawdown. High-frequency traders are especially sensitive to spreads, commissions and slippage. A small cost repeated dozens of times can remove a meaningful part of the strategy's expected return. Swing and position traders place fewer trades, but they normally use wider stop-losses and may pay overnight swap charges. Their capital can also remain committed for weeks or months, reducing the amount available for other opportunities. News traders must allow for poor fills and price gaps, while algorithmic traders may face data, software and hosting costs. Copy traders need enough capital to reproduce a provider's positions at sensible sizes without using excessive leverage. This table provides a starting point rather than a permanent label. A trader with a full-time job, for example, might normally swing trade but occasionally plan a news trade when a major announcement occurs outside working hours. In my experience, most beginners choose the wrong type on their first attempt. The most common mismatch is trying to day trade without having the hours available, usually because short-term trading appears to offer faster progress. Switching styles is calibration, not failure. A typical trader might begin with day trading, discover that the screen time is unrealistic, move to swing trading and find that the slower pace produces better decisions. Another may find discretionary decisions stressful and gradually move towards a rule-based or algorithmic approach. A reasonable demo trial should last long enough to experience wins, losses and quiet market conditions, not merely one good afternoon: The exact numbers matter less than keeping consistent records. If a style cannot be followed on a demo account when no real money is at risk, it is unlikely to become easier once profits and losses are real. The best type of forex trader is the one whose routine you can realistically repeat, not the one with the most exciting name or the most impressive screenshots. There is no single best forex timeframe for everyone, the timeframe should follow the trader type, with shorter holding periods generally requiring smaller chart intervals. A useful principle is to establish market direction on a higher timeframe first and then use a lower timeframe to refine the entry. The ranges below are common starting points rather than fixed rules: Scalpers spend most of their working time on minute charts. They may use a 15-minute chart to identify the immediate direction before moving to a five-minute or one-minute chart for the actual entry. Day traders typically take a slightly broader view. A one-hour chart can reveal the intraday trend and major support or resistance levels, while a 15-minute or five-minute chart provides more precise entry and exit signals. Smaller timeframes produce more apparent opportunities, but they also contain more market noise. A movement that looks significant on a one-minute chart may be almost invisible on an hourly chart. Short-term traders are also more sensitive to spreads, commissions, slippage and execution delays because their profit targets tend to be smaller. Moving to a shorter timeframe does not automatically create a better strategy, it simply increases the speed at which decisions and costs arrive. Swing traders commonly use daily charts to determine the broader direction and hourly or four-hour charts to plan entries and exits. This combination removes much of the intraday noise while still providing enough detail to manage a position. For example, a trader might identify an established GBP/USD uptrend on the daily chart, wait for the price to pull back towards support and then use the four-hour chart to look for evidence that buyers are returning. This is usually the easiest rhythm to sustain for people who can only check the market once or twice a day. Price alerts and pending orders can reduce the need for continuous monitoring, although every position still needs a planned stop-loss and exit. Position traders use weekly and monthly charts to identify long-term trends, economic cycles and major price levels. Daily charts can then help them avoid entering at an obviously poor point within that wider move. Longer timeframes generally produce fewer signals, but they also filter out much of the short-term noise that dominates minute and hourly charts. A central-bank policy trend that develops over several months will normally matter more to a position trader than one unexpectedly strong economic release. The challenge is patience. A valid setup may take weeks to appear, and the resulting position may require months to reach its target. Low decision frequency sounds relaxing until the trader realises that doing nothing is often the actual job. News, algorithmic and copy traders do not fit neatly into a standard timeframe ladder. News traders organise their activity around the economic calendar. They may use hourly or daily charts to understand the broader market context, but the price reaction to an interest-rate decision, inflation report or employment release is usually monitored on one-minute and five-minute charts. Algorithmic traders use the timeframe specified by the system. A high-frequency program may process price changes in fractions of a second, while another algorithm may trade daily trend signals. The timeframe should be supported by back testing and realistic execution data rather than chosen because shorter charts appear more active. Copy traders inherit the timeframe of the signal provider. If the provider scalps, the follower receives short-term exposure; if the provider holds positions for weeks, the follower also faces overnight risk and swap charges. The copy trader's responsibility is to confirm that the provider's rhythm, drawdown and holding period match their own risk capacity. Choosing a timeframe therefore begins with deciding how you can realistically trade, not by opening a chart and selecting whichever interval happens to look most profitable. Each trader type attempts to profit from a different part of a currency move and at a different trading frequency. Scalpers may collect several tiny movements, while position traders wait for a much larger trend; however, none of these methods guarantees a profit, and the costs and risks change with the chosen style. Scalpers and day traders attempt to accumulate returns from relatively small price movements. A scalper might target only a few pips per trade, while a day trader may aim to capture a larger intraday trend between established support and resistance levels. Both styles depend on repetition and disciplined risk control. A short-term trader does not need every position to succeed, but the average gain from winning trades must be sufficient to cover losing trades and transaction costs over a meaningful sample. For example, imagine a scalping strategy that wins six out of ten trades. If every winner earns five pips but each loser costs six pips after fees and slippage, the high win rate still does not create a profitable result. Frequency can magnify a genuine edge, but it magnifies poor mathematics just as efficiently. Spreads and commissions are the biggest opponents on this path. The higher the trading frequency, the faster those costs bite into the gross return. This is why short-term traders pay close attention to liquidity, active market sessions and execution quality. Swing and position traders attempt to capture a larger section of a market move. Rather than collecting many small changes, they place fewer trades and aim for a greater potential reward relative to the amount risked on each position. A swing trader might buy EUR/USD after a pullback within an established uptrend and hold the trade for several days. A position trader could hold the same pair for months because they expect a longer-term difference between US and eurozone interest-rate policy to drive the exchange rate. These traders do not need unusually high trade frequency or an exceptionally high win rate if their successful positions are meaningfully larger than their losses. A strategy that wins four out of ten times can still have positive expectancy if the average winner is sufficiently large and risk is kept consistent. The price of this wider view is prolonged uncertainty. Swing and position traders must tolerate floating losses, overnight gaps and periods when the market makes little progress. They may also incur swap charges for holding leveraged positions overnight. Fewer trades therefore do not mean easier trades. The decision frequency is lower, but each position often requires more patience, a wider stop-loss and greater tolerance for temporary fluctuations. News traders attempt to profit when new information forces the market to reprice a currency quickly. The important factor is not simply whether an economic figure is strong or weak, but how it compares with expectations and what it changes about future interest rates or economic growth. These surprises can create sharp opportunities, but they also concentrate execution risk. The moment with the greatest potential movement is often the same moment when spreads widen, prices gap and slippage becomes most severe. Algorithmic traders pursue a repeatable rule-based or statistical edge. A system might exploit momentum, mean reversion, price relationships or recurring market behaviour. Its profitability depends on whether the tested edge remains valid after realistic spreads, commissions and execution delays are included. The challenge is that algorithms decay. Markets change, other participants adapt and once-reliable patterns can weaken. Consequently, the trader must monitor live results and maintain the system rather than assuming an old back test will continue producing the same outcome. Copy traders rely on the judgement and execution of another trader. Their potential return comes from the provider's decisions, but their own contribution is selecting that provider, controlling the allocation and recognising when the risk profile has changed. In other words, copy trading removes the need to choose each individual position but not the need to manage the account. The follower's real strategy is careful provider screening and ongoing risk control. Trading style directly affects which risks matter most and how quickly they can damage an account. A risk plan should therefore reflect how often positions are opened, how long they remain active and how the trades are executed. Whatever the trader type, the shared baseline is a clear per-trade risk cap and disciplined use of stop-losses. The precise limits will vary, but no style removes the need to decide how much can be lost before the position is opened. Forex traders are commonly divided into seven types: scalpers, day traders, swing traders, position traders, news traders, algorithmic traders and copy traders. Some classifications use fewer categories, but these seven cover the main traditional and modern trading styles. Swing trading is often a realistic starting point because it allows more time for analysis and does not require constant screen monitoring. Position trading may suit particularly patient beginners, while copy trading can help newcomers observe other traders but still requires careful provider selection and risk control. There is no single best type of trader. The most suitable style is the one that matches your available time, temperament, capital and tolerance for risk. No trader type is automatically more successful than another. Traders are more likely to achieve consistent results when they use disciplined risk management, follow a tested plan and choose a style they can execute reliably. There is no genuinely easy forex strategy, although swing and position trading can be simpler to manage because they involve fewer decisions and allow more time for analysis. Simpler does not mean safer or guaranteed to be profitable. Scalpers and day traders generally favour liquid periods such as the London–New York overlap, when spreads are often more competitive and market activity is higher. Swing and position traders are less dependent on a particular hour because their trades remain open for much longer. Yes. Short-term styles require traders to be active during particular market sessions or economic releases, while longer-term traders can review charts and manage positions on a more flexible schedule. Choose according to the time you can genuinely commit, how quickly you prefer to make decisions and whether your capital can support the style's costs. For many people with full-time jobs, swing trading is more practical than attempting to day trade between other responsibilities. Yes, traders can combine styles if each strategy has separate rules, risk limits and records. However, avoid opening several trades based on the same market idea and mistakenly treating them as diversified positions. You know before I decided to write this article, I asked myself which type of trader am I? The simple answer is: a bit of all of them. When I first started trading my time was limited as I had a full-time job and family commitments. Over the years I have become a full-time trader, so I have had more time to focus on the charts and adopt my trading styles. The seven main types of forex traders differ in their holding periods, trade frequency, decision-making methods and required time commitment. Choosing between them should depend on your available time, temperament and capital, not on which style appears to offer the fastest or largest profits. If your first choice proves unsuitable, switching to another trading style is sensible calibration rather than failure. Knowing which type of trader you are gives your strategies, risk rules and daily routine a structure you can realistically follow. Before committing real capital, trial the most suitable rhythms on a demo account and use your trading records to decide which one genuinely fits. Lee W. is a seasoned professional trader with over 10 years of experience. Passionate about sharing valuable expertise and unique market insights, Lee W. now serves as an external and independent market analyst for RADEX MARKETS. Reviewed by RADEX MARKETS Risk Warning: Trading derivatives and leveraged products carries a high level of risk, including the risk of losing substantially more than your initial investment. Related concepts:

Gold and silver fell foul of aggressive market conditions on Thursday afternoon, with both metals undergoing sharp declines as a result of what looks like a forced liquidation event. The sudden drop in prices occurred over a short 30-minute interval, during which gold lost 2% and silver fell almost 8%. Gold would go on to lose $160 over the course of the session, closing the day around $4,920 per ounce. The volatility in silver remains much higher however, with the white metal suffering double-digit losses and closing at $75 per ounce by Thursday evening. The downward move appears to be connected to a market-wide selloff as investors at large reduce their exposure ahead of US inflation figures later today. Cryptocurrencies continued to bleed yesterday, while oil prices shed around $2 per barrel amid mounting concerns of a global supply glut. Yet another industry is facing the wrath of AI takeover, this time the more traditional freight and logistics sector. We mentioned a couple of days ago that different industries are being put under pressure by the threat of replacement by AI tools, and it seems that markets have found their latest victim. Software companies were the first to be targeted, followed by financial management and insurance brokerage firms, but yesterday it was the turn of the transport sector. Freight company Universal Logistics (ULH) fell 10% yesterday, while shares in CH Robinson (CHRW) had plummeted over 14% by the daily close. All it took was an announcement from Algorhythm Holdings (RIME), an understated Florida-based company who has claimed that their new AI freight scaling tool would allow transport companies to massively scale their operations without incurring any additional labour costs. The relatively unknown company rose 30% yesterday as investors piled on the bandwagon. Further afield, the wider tech sector remains fragile in the current environment, with Cisco Systems (CSCO) falling 12% on Thursday despite meeting earnings expectations. Meta (META) and Amazon (AMZN) both fell over 2% yesterday, while Apple (AAPL) lost 5%. US indices all closed in the red as a result, with the Nasdaq Composite falling the furthest. The January non-farm payroll report vastly surpassed expectations on Wednesday, doubling estimates and revealing 130k new positions for the first month of the year. The unemployment rate also unexpectedly ticked down to 4.3%, further strengthening the image of the US labour market. With the latest report out of the way, markets are now turning their attention towards the January CPI drop, scheduled for later today. Inflation figures are projected to fall to 2.5% year-over-year, an improvement over the previous month but still above the Fed’s target. When coupled with a robust job market, sticky inflation leaves the Fed with no justifiable path forward to cut rates on the dollar. Interest rate traders are in agreement and are now firmly anticipating a rate hold in March. With that said, the next FOMC meeting is still over a month away and a lot can happen between now and then. #gold #silver #CPI