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Japanese Candlestick Cheat Sheet – Part OneSingle-Candle Formations That Speak Before you dream of profits, learn the one language that never lies: price. Indicators are just subtitles — price is the voice. Japanese candlesticks are more than just red and green bars — they reflect emotion, pressure, and intention within the market. This series will walk you through the real psychology behind candlestick patterns — starting here, with the most essential: 🕯️ Single-candle formations — the quiet signals that often appear before big moves happen. If you can’t read a doji, you’re not ready to understand the market’s hesitation. If you ignore a hammer, you’ll miss the moment sentiment shifts. Let’s start simple. Let’s start strong. This is Part One of a five-part series designed to build your candlestick fluency from the ground up. 1. DOJI Bias: Neutral What is the Doji pattern? The Doji candlestick pattern forms when a candle’s open and close prices are nearly identical, resulting in a small or nonexistent body with wicks on both sides. This pattern reflects market equilibrium, where neither buyers nor sellers dominate. Dojis often appear at trend ends, signaling potential reversals or pauses. As a fundamental tool in technical analysis, Dojis help traders gauge the psychological battle between buyers and sellers. Proper interpretation requires context and experience, especially for spotting trend shifts. Meaning: Indicates market indecision or balance. Found during trends and may signal a reversal or continuation based on context. LONG-LEGGED DOJI Bias: Neutral What is the Long-Legged Doji pattern? The Long-Legged Doji captures a moment of intense uncertainty and volatility in the market. Its long wicks represent significant movement on both sides, suggesting that neither buyers nor sellers have control. This back-and-forth reflects the psychology of market participants wrestling for control, which often foreshadows a shift in sentiment. When traders see a Long-Legged Doji, it highlights the need to monitor for potential changes in direction. They can appear within trends, at potential reversal points, or at consolidation zones. When they form at the end of an uptrend or downtrend, they often signal that the current trend may be losing momentum. Meaning: The prominent wicks indicate volatility. Buyers and sellers pushed prices in opposite directions throughout the session, ultimately reaching an indecisive close. SPINNING TOP Bias: Neutral What is the Spinning Top pattern? A Spinning Top is a candlestick with a small body and long upper and lower wicks, indicating that the market has fluctuated significantly but ultimately closed near its opening price. This pattern often points to a moment of indecision, where both buyers and sellers are active but neither dominates. Spinning Tops are commonly found within both uptrends and downtrends and can suggest that a trend is losing momentum. For traders, a Spinning Top provides a valuable insight into market psychology, as it hints that the prevailing sentiment may be weakening. While Spinning Tops alone aren’t always definitive, they can serve as a precursor to larger moves if the following candles confirm a shift in sentiment. Meaning: Shows indecision between buyers and sellers. Common in both up and downtrends; signals potential reversal or pause. HAMMER Bias: Bullish What is the Hammer pattern? A Hammer candlestick appears at the end of a downtrend, with a small body and a long lower wick. This shape reflects a moment when sellers pushed prices lower, but buyers managed to absorb the selling pressure and drive prices back up before the close. This pattern is particularly important for spotting potential reversals, as it indicates that buyers are beginning to reassert control. Hammers reveal the underlying psychology of a market where buying confidence is emerging, even if sellers have dominated for a while. To successfully trade this pattern, it’s essential to confirm the reversal with subsequent candles. Meaning: Showing rejection of lower prices. Signals potential bullish reversal, especially if followed by strong buying candles. INVERTED HAMMER Bias: Bullish What is the Inverted Hammer pattern? The Inverted Hammer forms at the bottom of a downtrend, with a small body and long upper wick. This pattern shows that buyers attempted to push prices higher, but sellers ultimately brought them back down by the close. The Inverted Hammer is an early sign of buyer interest, hinting that a trend reversal may be underway if subsequent candles confirm the shift. Interpreting the Inverted Hammer helps traders understand where sentiment may be shifting from bearish to bullish, often marking the beginning of a recovery. Recognizing these patterns takes practice and familiarity with market conditions. Meaning: Showing rejection of higher prices. Can signal bullish reversal if confirmed by subsequent buying pressure. DRAGONFLY DOJI Bias: Bullish What is the Dragonfly Doji pattern? The Dragonfly Doji has a long lower wick and no upper wick, forming in downtrends to signal potential bullish reversal. This pattern reveals that sellers were initially in control, pushing prices lower, but buyers stepped in to push prices back up to the opening level. The Dragonfly Doji’s unique shape signifies that strong buying support exists at the lower price level, hinting at an impending reversal. Recognizing the psychology behind a Dragonfly Doji can enhance a trader’s ability to anticipate trend changes, especially in markets where support levels are being tested. Meaning: Found in downtrends; suggests possible bullish reversal if confirmed by a strong upward move. BULLISH MARUBOZU Bias: Bullish What is the Bullish Marubozu pattern? The Bullish Marubozu is a large, solid candle with no wicks, indicating that buyers were in complete control throughout the session. This pattern appears in uptrends, where it signals strong buying momentum and often foreshadows continued upward movement. The absence of wicks reveals that prices consistently moved higher, with little resistance from sellers. For traders, the Bullish Marubozu offers a glimpse into market psychology, highlighting moments when buyer sentiment is particularly strong. Learning to identify these periods of intense momentum is crucial for trading success. Meaning: Showing complete buying control. Found in uptrends or at reversal points; indicates strong buying pressure and likely continuation of the trend. SHOOTING STAR Bias: Bearish What is the Shooting Star pattern? The Shooting Star appears at the top of an uptrend, characterized by a small body and a long upper wick, indicating a potential bearish reversal. Buyers initially drove prices higher, but sellers took over, bringing prices back down near the open. This shift suggests that buyers may be losing control, and a reversal could be imminent. Interpreting the Shooting Star gives traders valuable insights into moments when optimism begins to fade, providing clues about a potential trend shift. Meaning: Indicating rejection of higher prices. Signals a potential bearish reversal if followed by selling pressure. HANGING MAN Bias: Bearish W hat is the Hanging Man pattern? The Hanging Man candle forms at the top of an uptrend, with a small body and long lower wick. This pattern suggests that sellers attempted to drive prices down, but buyers regained control. However, the presence of a long lower shadow hints that sellers may be gaining strength, potentially signaling a bearish reversal. The Hanging Man pattern reflects market psychology where buyers might be overextended, making it a valuable tool for identifying potential tops in trends. Meaning: Signals potential bearish reversal if confirmed by selling candles afterward. GRAVESTONE DOJI Bias: Bearish What is the Gravestone Doji pattern? With a long upper wick and no lower wick, the Gravestone Doji reveals that buyers pushed prices up, but sellers eventually regained control. Found in uptrends, it suggests that a bearish reversal could be near, as the upper shadow indicates buyer exhaustion. The Gravestone Doji often appears at market tops, making it a valuable indicator for those looking to anticipate shifts. Understanding the psychology behind this pattern helps traders make informed decisions, especially in markets prone to overbought conditions. Meaning: Showing rejection of higher prices. Found in uptrends; signals potential bearish reversal if followed by selling activity. BEARISH MARUBOZU Bias: Bearish What is the Bearish Marubozu pattern? The Bearish Marubozu is a large, solid bearish candle without wicks, showing that sellers held control throughout the session. Found in downtrends, it signals strong bearish sentiment and suggests that the trend is likely to continue. The lack of wicks reflects consistent downward momentum without significant buyer support. This pattern speaks about market psychology, offering traders insights into moments of intense selling pressure. Recognizing the Bearish Marubozu can help you align with prevailing trends and avoid buying into weakening markets Meaning: Showing strong selling pressure. Found in downtrends; signals continuation of the bearish trend or an intensifying sell-off. 👉 Up next: Double-candle formations – where price meets reaction.
TRADENATION:XAUUSDEducation
by Mihai_Iacob
19
Japanese Candlestick Cheat Sheet – Part Two- 2 candle patternsTwo-Candle Patterns That Signal Shifts in Sentiment Single candles whisper… But two candles talk to each other — and when they do, they often reveal the first signs of a reversal or continuation. In this second part of the series, we go deeper. From engulfings to haramis, tweezer tops to piercing lines — these patterns don’t just look good on charts… they capture the psychological tug-of-war between buyers and sellers. Price doesn’t lie. And two candles in a row can say: “Something just changed.” Learn to spot them early. Learn to listen when the chart speaks. This is Part Two of your practical guide to mastering candlestick formations. BULLISH KICKER Bias: Bullish What is the Bullish Kicker pattern? The Bullish Kicker forms when a strong bullish candle follows a bearish one with no overlap between the two, indicating a sudden shift in sentiment. This pattern is a powerful indicator of a reversal as buyers take control. The sharp contrast between the bearish and bullish candles reflects a dramatic shift in market psychology, where bears are caught off-guard and forced to cover their positions. Bullish Kickers are rare but extremely telling, providing a clear signal that sentiment is favoring buyers. Recognizing such decisive patterns can be a game-changer. Meaning: Found after downtrends or sell-offs; suggests a sudden shift in sentiment, indicating strong buying interest and potential trend reversal. BULLISH ENGULFING Bias: Bullish What is the Bullish Engulfing pattern? The Bullish Engulfing pattern occurs when a large bullish candle fully engulfs the previous smaller bearish candle, signaling a potential trend reversal. This pattern highlights a moment when buyers overpower sellers, often marking the beginning of upward momentum. Psychologically, it suggests that buyer confidence is returning, and sellers are losing their grip. For traders, understanding Bullish Engulfing patterns can provide crucial entry points into emerging trends. Learning to identify and trade such patterns is essential for capturing momentum and new trends. Meaning: Typically found in downtrends, this pattern signals a potential bullish reversal as buyers overpower sellers, often indicating a shift toward upward momentum. BULLISH HARAMI Bias: Bullish What is the Bullish Harami pattern? The Bullish Harami consists of a small bullish candle within a preceding larger bearish one, indicating a pause in downward momentum and hinting at a potential reversal. This pattern shows that sellers are beginning to weaken as buyers cautiously test the waters. The Harami reflects a shift in sentiment from bearish to neutral, often marking a transitional phase in the market. Interpreting the Bullish Harami helps traders spot moments when sentiment is shifting, potentially signaling the start of a trend change. Meaning: Seen in downtrends, it suggests indecision, with possible bullish reversal if the following candles confirm buying strength, indicating a weakening bearish trend. PIERCING LINE Bias: Bullish What is the Piercing Line pattern? The Piercing Line forms when a bullish candle opens below the previous bearish candle’s low but closes over halfway into it. Found in downtrends, this pattern reflects strong buying pressure as buyers step in at lower prices, creating a potential bullish reversal. The Piercing Line pattern suggests that sentiment may be shifting as buyers gain confidence. This pattern’s strength lies in its psychological impact, revealing moments when buyers are willing to take risks. Recognizing these signs early can provide valuable insights for traders looking to time entries. Meaning : Found in downtrends, this pattern suggests a possible bullish reversal if buying continues, as sellers lose control to buyers. TWEEZER BOTTOM Bias: Bullish What is the Tweezer Bottom pattern? The Tweezer Bottom pattern is characterized by two consecutive candles with nearly identical lows, one bearish and one bullish. This pattern often signals the end of a downtrend, as the matching lows suggest a strong support level where buyers are stepping in. The Tweezer Bottom highlights market psychology at work, with sellers unable to push prices lower, reflecting renewed buying interest. Tweezer Bottoms are ideal for traders looking to identify support zones and potential reversal points. By understanding this pattern’s significance, traders can make informed decisions. Meaning: Found in downtrends, it signals potential reversal, showing strong support at the matching low, suggesting buyers are stepping in. BEARISH KICKER Bias: Bearish What is the Bearish Kicker pattern? The Bearish Kicker is the inverse of the Bullish Kicker, forming when a strong bearish candle follows a bullish one without overlap, indicating a sharp sentiment shift. This pattern often marks a sudden reversal, with sellers taking control after an initial bullish period. Psychologically, Bearish Kickers are powerful, signaling that buyers are caught off-guard and losing momentum. Recognizing Bearish Kickers provides traders with insights into sudden shifts in market dynamics, helping them avoid buying into weakening trends. Meaning: Found after uptrends; indicates a sudden sentiment shift, signaling potential trend reversal and intensified selling pressure. BEARISH ENGULFING Bias: Bearish What is the Bearish Engulfing pattern? The Bearish Engulfing pattern forms when a large bearish candle engulfs the previous smaller bullish candle, suggesting a potential reversal in an uptrend. This pattern signals that sellers have regained control, often marking the start of downward momentum. The Bearish Engulfing reveals a psychological shift, as selling pressure overtakes buying interest. This pattern is a powerful tool for traders who aim to catch trend reversals, allowing them to align with emerging downward momentum. Meaning: Typically found in uptrends, this pattern signals a potential bearish reversal as sellers overpower buyers, often indicating a downward momentum shift. BEARISH HARAMI Bias: Bearish What is the Bearish Harami pattern? The Bearish Harami consists of a small bearish candle contained within a larger preceding bullish one, reflecting indecision and a potential trend reversal. Found in uptrends, it hints that buyers are losing strength, while sellers are cautiously testing the market. This pattern highlights moments when buyer momentum begins to wane, suggesting caution. Interpreting the Bearish Harami allows traders to spot potential shifts in sentiment, helping them manage risk and time their exits. Meaning: Seen in uptrends, it suggests indecision with a potential bearish reversal if following candles confirm, indicating a weakening bullish trend. DARK CLOUD COVER Bias: Bearish What is the Dark Cloud Cover pattern? The Dark Cloud Cover appears when a bearish candle opens above the previous bullish candle but closes over halfway into it, reflecting a shift in control from buyers to sellers. This pattern suggests that bullish momentum may be fading, hinting at a potential reversal. Dark Cloud Cover patterns reveal moments when sentiment shifts from optimism to caution. For traders, understanding this pattern helps them anticipate reversals at the top of uptrends. Meaning: Found in uptrends; signals potential bearish reversal if selling continues, as buyers lose control to sellers. TWEEZER TOP Bias: Bearish W hat is the Tweezer Top pattern? The Tweezer Top is formed by two candles with matching or nearly matching highs, typically one bullish and one bearish. This pattern signals potential resistance, as sellers are consistently pushing back against the same level. The Tweezer Top reflects a moment of seller strength, often marking the end of an uptrend. Recognizing Tweezer Tops helps traders spot resistance zones and potential reversal points, allowing them to avoid buying into weakening trends or even shorting the asset. Meaning: Found in uptrends, it signals potential reversal, showing strong resistance at the matching high, suggesting selling pressure. 🧭 Final Thought Two-candle formations often appear at key turning points — right where most traders hesitate or get trapped. Learn to read them not just as patterns, but as conversations between candles — one pushing, the other reacting. And if this is your first time reading the series, don’t miss Part One – where we covered single-candle signals like dojis, hammers, and marubozus — the very foundations of candlestick reading.
TRADENATION:XAUUSDEducation
by Mihai_Iacob
11
Feed Your Ego or Feed Your Account- Your Choise🧭 From Rookie to Realization I’ve been trading since 2002. That’s nearly a quarter of a century in the markets. I’ve lived through it all: • The early days, when the internet was slow and information was scarce • The forums, the books, the overanalyzing • The obsession with finding “the perfect system” • And later… the dangerous phase: needing to be right, because I have a few years of experience and I KNOW At one point, I thought that being a good trader meant calling the market in advance — proving I was smarter than the rest. But the truth is: the market doesn't pay for being right. It pays for managing risk, always adapting and executing cleanly. ________________________________________ 😤 The Psychological Trap Most Traders Fall Into There’s one thing I’ve seen consistently over the last 25 years: Most traders don’t trade to make money. They trade to feel right. And this need — this psychological craving to validate an opinion — is exactly what keeps them from growing. You’ve seen it too: • The guy who’s been screaming “altcoin season” for 2 years • Who first called it when EGLD was at 80, TIA, and others that kept dropping • But now that something finally moves, he says: “See? I was right all along, altcoin season is here” He’s not trading. He’s rehearsing an ego story, ignoring every failed call, every drawdown, every frozen position. He doesn’t remember the trades that didn’t work — only the one that eventually did. This is not strategy. It’s delusion dressed up as conviction. ________________________________________ 📉 The Market Doesn’t Care What You Think Here’s the reality: You can be right in your analysis — and still lose money. You can be wrong — and still come out profitable. Because the market doesn’t reward your opinion. It rewards how well you manage risk, entries, exits, expectations, and flexibility I’ve seen traders who were “right” on direction but blew their accounts by overleveraging. And I’ve seen others who were wrong on their first two trades — but adjusted quickly, cut losses, and ended green overall in the end. This is what separates pros from opinionated amateurs. ________________________________________ 📍 A Real Example: Today’s Gold Analysis Let’s take a real, current example — my own Gold analysis from this morning. I said: • Short-term, Gold could go to 3450 • Long-term, the breakout from the weekly triangle could take us to 3800 Sounds “right,” right? But let’s dissect it: Short-term: ✅ I identified 3370 as support If I buy there, I also have a clear invalidation level (below 3350) If it breaks that and hits my stop? 👉 I reassess — because being “right” means nothing if the trade setup is invalidated And no, it doesn’t help my PnL if Gold eventually reaches 3450 after taking me out. Long-term: ✅ The weekly chart shows a symmetrical triangle Yes — if we break above, the measured move targets 3800 But… If Gold goes below 3300, that long-term scenario is invalidated too. And even worse — if Gold trades sideways between 3000 and 3500 for the next 5 years and finally hits 3800 in 2030, that “correct call” is worth nothing. You can't build a career on "eventually I was right." You need precision, timing, risk management, and the ability to say: “This setup is no longer valid. I’m out.” ________________________________________ 💡 The Shift That Changed Everything It took me years to realize this. The day I stopped needing to be right was the day I started making consistent money. I stopped arguing with the market. I stopped holding losers out of pride. I stopped needing to "prove" anything to anyone — especially not myself. Now, my job is simple: • Protect capital • Execute with discipline • Let the edge do its job • And never fall in love with my opinion ________________________________________ ✅ Final Thought – Let Go of Being Right If you’re still stuck in the “I knew it” mindset — let it go. It’s not helping you. It’s costing you. The best traders lose small, admit mistakes fast, and stay emotionally neutral. The worst traders hold on to “being right” while their account burns. The market doesn’t owe you respect. It doesn’t care if you called the top, bottom, or middle. It pays the ones who trade objectively, flexibly, and without ego. After almost 25 years, this is the one thing I wish I had learned sooner: Don’t try to win an argument with the market. Just get paid. Disclosure: I am part of TradeNation's Influencer program and receive a monthly fee for using their TradingView charts in my analyses and educational articles.
TRADENATION:XAUUSDEducation
by Mihai_Iacob
10
HOW-TO: Auto Harmonic Screener - UltimateXHello Everyone, In this video, we have discussed on how to use our new Auto Harmonic Screener - UltimateX. We have covered the following topics. Difference between Auto Harmonic Screener - UltimateX (Current script) and Auto Harmonic Pattern - UltimateX and how to use both the scripts together Difference between Auto Harmonic Screener - UltimateX (Current script) and the existing screener Auto Harmonic Pattern - Screener which is built on request.security calls. We have discussed how the limitations of old script and how using the new script with Pine screener utility will help overcome those problems. We have gone through the indicator settings (which are almost similar to that of Auto Harmonic Pattern UltimateX Short demo on how to use the script with Pine Screener Also check our existing video on How to use the new Pine Screener Utility.
Education
by Trendoscope
3
Altcoin Season:It All Comes Down to One Thing—Liquidity RotationHello Traders 🐺 Let’s be real—everything about “altcoin season” comes back to one key concept: liquidity rotation. You’ve probably heard that term thrown around, but what does it actually mean ? And more importantly, how do we use it? No matter what market cycle we’re in—bullish or bearish—each cycle is made up of several internal phases. And during those phases, tracking where smart money is flowing becomes crucial. But let’s break it down even further. Take a look at the chart. Before the last altcoin season kicked off, something interesting happened: the Bitcoin Dominance Index (BTC.D) had a significant rally. As the name suggests, this index tracks Bitcoin’s share of the overall crypto market cap. So when CRYPTOCAP:BTC.D is rising, that means Bitcoin is sucking up a larger share of the liquidity—smart money is flowing into BTC first. This is critical to understand, because Bitcoin Dominance is one of the clearest indicators to tell you which phase of the cycle we're in and where the money is heading next. Now here’s the key question: Why do we associate a drop in BTC Dominance with the start of altcoin season? It all goes back to the literal meaning of Bitcoin Dominance. If BTC.D is approaching 100%, nearly all the money is concentrated in Bitcoin alone. But when this dominance starts dropping, it signals that capital is beginning to rotate out of BTC and into altcoins. And here's where it gets spicy: When BTC.D approaches a key resistance level—like it's doing right now—and at the same time we see bearish divergences across multiple timeframes... that’s our cue. Combine that with technical analysis, and suddenly you've got yourself a roadmap most beginners are completely blind to. That’s why 80% of traders end up feeding the profits of the other 20%. The harsh truth? Markets are wealth transfer mechanisms—from the impatient to the patient. Every bad entry, every panic sell, ends up padding the wallet of someone who planned the rotation in advance. Let’s not complicate things too much though. Just look at what’s happening right now: BTC Dominance hit a major resistance level, showed strong bearish divergences (as I mentioned in earlier posts), and what happened next? Boom—altcoins started pumping hard this past week. To everyone who stayed with me through this phase and positioned themselves early—congrats. You earned this. But here’s the bigger picture: We're still at the beginning of the altcoin cycle. Like I explained before, it all happens in phases: Bitcoin Season – Smart money enters Bitcoin first. Ethereum Season – Then liquidity flows into ETH. Large-Cap Altcoins – After that, big-name altcoins start moving. Altcoin Season (Full Risk-On) – Finally, capital floods into low-cap alts—the wild phase. And that last phase? That’s when things get crazy. That’s where irrational exuberance lives. That’s where dreams are made—or broken—depending on your timing and plan. So yeah, buckle up. We're not done yet. And as always remember : 🐺 Discipline is rarely enjoyable , but almost always profitable. 🐺 🐺 KIU_COIN 🐺
CRYPTOCAP:BTC.DEducation
by Kiu_Coin
2
The More You Believe You Know The More You LoseThe moment you see your first green position something changes Suddenly your brain convinces you you’ve got this But the market doesn’t punish bad traders it punishes the ones who think they’re too good to lose You don’t lose because you’re unskilled You lose because you believe you’ve mastered the game Hello✌️ Spend 3 minutes ⏰ reading this educational material. 🎯 Analytical Insight on Ripple: BINANCE:XRPUSDT remains undervalued at current levels, showing strong volume near a key daily support zone that aligns closely with a major Fibonacci retracement. This confluence suggests a potential shift in momentum. If buyers hold this level, a move toward the $4 area is on the table, representing an estimated 15% upside. 📈 Watch for confirmation through sustained volume and price reaction at support. ⚡ Now , let's dive into the educational section, 🎯 The Confidence Trap One of the most dangerous mental states for a trader is early victory That moment after a couple of green trades when you start feeling like you’ve figured the market out That’s when the market does to you what you used to do to clueless beginners From that point forward your decisions aren’t based on analysis they’re based on this thought I already know how this works. 🧠 How Your Mind Tricks You You win once Your brain says “Told you you’re good” You win again It says “Go heavier now” You lose It says “Fix it now You’ve done it before” This cycle leads to overtrading and emotional revenge You’re no longer trading the market you’re defending the version of yourself you believe you’ve become 🔄 The Market Doesn’t Send Signals It Sends Lessons When the market moves against you it’s doing the right thing It’s breaking down your ego so you can finally start seeing the chart for what it is not what your confidence wants it to be 🧱 Experience Can Kill Learning Many failed traders are not beginners they’re the ones with years of bias built up At some point they stop learning Every chart starts looking the same That’s when their final trade shows up 🕳 The Ego Pitfall If your mind tells you “I know this” it’s time to be extra cautious That means you’re trading with a rigid mindset And in crypto markets the rigid get destroyed 📉 High Leverage = High Confidence = High Risk Nobody gets reckless on 2x leverage But once you start feeling pro you go 20x 50x or more And when the market flips the same ego that won you your first big gain is the one that wipes out your entire account. 📊 How TradingView Tools Can Save You In this mental trap three tools from TradingView can seriously help Replay Bar Tool Go back in time and relive previous market conditions This tool shows you exactly where your bias failed and where your overconfidence blinded you It helps kill that false feeling of mastery OBV (On Balance Volume) A simple yet powerful volume indicator If price rises but OBV is falling the uptrend is fake If price drops but OBV is climbing sellers are weak and a reversal might be near This gives volume context beyond candles Volume Spike Watch out for sudden surges in volume If volume explodes but price barely moves someone big is moving in silence It’s often the prelude to fakeouts traps or major directional shifts These spikes scream pay attention Risk-to-Reward Tool Don’t let your “confidence” make you forget basic math This tool gives you the true ratio of what you’re risking versus what you’re chasing It doesn’t care how good you feel it shows you if the trade makes sense 🧊 Humility Is the Only Edge That Lasts Humility means accepting you might always be wrong It means checking yourself with objective tools It means saying “maybe” instead of “definitely” It means lasting longer than the rest 🔚 Final Words If you’re sure you’ve mastered the market pause The best traders second-guess themselves often not because they’re weak but because they know confidence fades but risk never does ✨ Need a little love! We pour love into every post your support keeps us inspired! 💛 Don’t be shy, we’d love to hear from you on comments. Big thanks , Mad Whale 🐋 📜Please make sure to do your own research before investing, and review the disclaimer provided at the end of each post.
Education
by MadWhale
Angle of Ascent: what it means, how to use it.Angle of Ascent is a visual pattern that forms on a chart when stocks are running with momentum or velocity. Drawing a line along an up trending price action helps you see the Angle of ascent. Also Chaikins Osc and EMA MFI indicators are extremely helpful in warning a day ahead of time that the Angle of Ascent is too steep to sustain. This is an exit signal for profit taking at or near the highest high of a swing style run. Angle of Ascent is also used on Weekly Charts to determine how far a stock can run before resistance from previous highs will stall that stock and cause a minor to intermediate correction. Recognizing when an angle of ascent has become too steep to sustain and using these indicators will help you hold a swing run but also help you exit before a retracement or correction starts. The professional side of the market uses penny spreads, millisecond routing to the ques of the market, and can easily front run retail traders orders. Reminder: retail brokers are required to light your order before sending to the PFOF Payment for Order Flow Market Maker of their choice. The Digital Stock Market moves at a much faster pace with subtle nuances such as Angle of Ascent. As you become an advanced level trader to a semi-professional trader, or potentially a full time professional trader, these details matter more than when you are just learning stock trading. Trade Wisely Martha Stokes CMT
NYSE:CATEducation
by MarthaStokesCMT-TechniTrader
Why Swing Trading and Scalping Are Opposite Worlds"It's not about the strategy. It's about who you are when the market puts pressure on you." Most traders fail not because they don’t learn “strategies” — but because they pick a style that doesn't match their temperament. And nothing creates more damage than confusing swing trading with scalping/intraday trading. Let’s break them down. For real... ________________________________________ 🔵 1. Swing Trader – Chasing Direction, Not Noise A swing trader does not touch choppy markets. He’s not here for the sideways grind. He wants momentum. If there’s no clear trend, he doesn’t trade. He shifts between assets depending on where real movement is. • USD weakens → he buys EUR/USD and waits • Gold breaks → he enters and lets the move develop Swing trading means positioning with the macro flow, not chasing bottoms and tops. ✅ He trades based on H4/Daily or even Weekly charts ✅ He holds for hundreds of pips. ✅ He accepts contrarian candles in the process. ________________________________________ 🔴 2. Scalper/Intraday Trader – The Asset Specialist A true scalper doesn’t chase trends. He hunts inefficiencies — quick spikes, fakeouts, liquidity grabs. ✅ Loves range conditions ✅ Lives inside M5–M15 ✅ Often trades only one asset he knows like the back of his hand He doesn’t care what EUR/USD will do this week. He cares what it does in the next 30 minutes after a breakout. Scalping is not chaos. It's cold execution with a sniper mindset. 📡 He reacts to news in real time. He doesn’t predict — he exploits. ________________________________________ 🧾 Key Differences – Swing Trader vs. Scalper ________________________________________ 🎯 Primary Objective • Swing Trader: Captures large directional moves over several days. • Scalper/Intraday: Exploits short-term volatility, aiming for quick, small gains. ________________________________________ 🧭 Market Conditions Preference • Swing Trader: Needs clean, trending markets with clear momentum. • Scalper/Intraday: Feels comfortable in ranging markets with liquidity spikes and noise. ________________________________________ 🔍 Number of Instruments Traded • Swing Trader: Monitors and rotates through multiple assets (e.g. XAUUSD, EURUSD, indices, BTC, he's going where the money is). • Scalper/Intraday: Specializes in 1–2 instruments only, knows their behavior in every session. ________________________________________ ⏰ Time Spent in Front of the Charts • Swing Trader: Waits for clean setups, may hold positions for days or weeks. • Scalper/Intraday: Constant screen time, executes and manages trades actively. ________________________________________ 📰 Reaction to News • Swing Trader: Interprets the macro/fundamental impact and positions accordingly. • Scalper/Intraday: Reacts live to data releases, wicks, and intraday volatility. ________________________________________ 📉 When They Struggle • Swing Trader: Fails in choppy or directionless markets. • Scalper/Intraday: Loses edge when the market trends explosively. ________________________________________ 🧠 Psychological Requirements • Swing Trader: Needs patience, confidence in the big picture, and acceptance of drawdown. • Scalper/Intraday: Needs absolute discipline, emotional detachment, and razor-sharp focus. ________________________________________ ✅ Bottom line: They are two different games. Don’t try to play both on the same chart with the same mindset. ________________________________________ ✅ Final Thoughts – Your Edge Is in Alignment, Not Imitation You don’t pick a trading style because it “sounds cool.” You pick it because it aligns with: • Your schedule • Your attention span • Your tolerance for uncertainty If you hate watching candles all day – go swing. If you hate waiting for days – go intraday. If you keep switching between both – go journal your pain and come back later. P.S. Recent Example: I'm a swing trader. And this week, Gold has been stuck in a range. What do I do? I wait. No rush, no overtrading. Just patience. Once the range breaks, I’m ready — in either direction. But I don’t close after a quick 50–100 pip move. That’s not my game. I aim for 700+ pips whether it breaks up or down,because on both sides we have major support and resistance levels that matter. That’s swing trading: 📍 Enter with structure, hold with confidence, exit at significance. Not every move is worth trading — but the big ones are worth waiting for. Disclosure: I am part of TradeNation's Influencer program and receive a monthly fee for using their TradingView charts in my analyses and educational articles.
TRADENATION:XAUUSDEducation
by Mihai_Iacob
2
Does Everyone Remember Why The Bubble Popped in Y2K?I heard on Bloomberg Television this morning that they didn't have any recollection of a good reason for the stock market bubble of 1995-2000 to pop. I was stunned that a portfolio manager of such standing had the guts to say that he didn't understand why the market topped in 2000. This is how history gets re-written by people who didn't pay attention and didn't learn from the past, so how can we trust anything that we read, see, hear today? People don't remember. Why don't people remember? I think that is the fodder for someone to write a book, which isn't the point of this publication today. What I think "market history" means to us is that there is a fair and unbiased reporting of history and what TradingView does by keeping people's published charts online and not deleting bad forecasts is very refreshing. When TradingView started, I knew immediately that this model was the way to go. It was easy for people to "delete a Tweet" about their "buy recommendation" that didn't pan out. It was easy for people to "lie by omission" by removing the bad forecasts and keeping the ones that worked. I can add a couple of other points about the Y2K top: One of them was the SEC chairman Arthur Levitt starting the idea of a rule in December 1999 for "Fair Disclosure". This eliminated anyone getting any special information ahead of the crowd and assured a 'level playing field.' There was another Government Regulation to limit the speed of dial up internet access to 53K from the stated 56K speed. This was in 2000. The chart published is the close of March 31, 2000 when the Gov't announced their ANTI-TRUST CASE AGAINST MICROSOFT with the stock at $53.13. On Monday, NASDAQ:MSFT opened at $47.22 closed at $45.44, -7.69 that day and proceeded to drop to $20.13 over the ensuing bear market. $53.13 to $20.13 is a massive $33 point drop.
NASDAQ:MSFTEducation
by timwest
80% Of Time - A Trading Edge You Don't Want To MissDo you want to know why trading with median lines, also known as pitchforks, can be so successful? It’s simple: Prices swing from one extreme back to the middle. From the middle, they often swing to the other extreme. What do we see on the chart? - The upper extreme - The center - The lower extreme So far, so good. Now let’s follow the price and learn a few important rules that belong to the rulebook of median lines/pitchforks, and with which you can make great trades. Point 1 The price starts and is sold off down to… Point 2 ...and from there starts to rise again, up to… Point 3 ...which is the center. And here we have a rule that is very important and one that you need to be aware of in trading to be successful: THE PRICE RETURNS TO THE CENTER IN ABOUT 80% OF ALL CASES If we know this, then we can stay in a trade with confidence. Point 4 The price climbed even higher but missed the upper extreme. This is the “Hagopian Rule” (named after the man who discovered it). And the rule goes: If the price does not reach the next line (upper extreme, lower extreme, or center), then the price will continue moving in the opposite direction from where it originally came. Phew...that’s a mouthful ;-) But yes, we actually see that the price does exactly this. From point 4, where the price missed the upper extreme, the price not only goes back to the center but continues and almost reaches the lower extreme! Now if that isn’t cool, I don’t know what is! And what do we have at point 5? A "HAGOPIAN"! What did we just learn? The price should go higher than the center line. Does it do that? Oh yes! But wait! Not only does the Hagopian Rule apply. Remember? "The price returns to the center line in about 80% of the cases." HA! Interesting or interesting? So, that’s it. That’s enough for now. Now follow the price yourself and always consider which rule applies and whether it’s being followed. How exactly do you trade all this, and what are the setups? ...one step at a time. Don’t miss the next lesson and follow me here on TradingView. Wishing you lots of success and fun!
COINBASE:BONKUSDEducation
by Tr8dingN3rd
Why emotionless trading is out (and what to do instead)Curious about what self-compassionate trading really means? Let’s do a little thought experiment together. Imagine you just closed a losing trade. You’re feeling disappointed and unmotivated. You invite two friends over to your home and tell them what happened. Which friend would you rather talk to? 🙋🏽‍♀️ Friend 1 says: "What a failure you are. Why were you even stressed out? That’s so silly. Couldn’t you see this trade was going to be a loss? You should just give up—what’s the point of trying? I don’t understand how you could mess up the way you did. Let’s spend the afternoon going through everything you did wrong." ...Or would you prefer: 🙋🏽‍♀️ Friend 2 who says: "I can see you’re feeling sad and disappointed about that last trade. I’m really sorry it didn’t go your way. But you know what? Losses are a part of trading—we all go through them. You’ll have another chance tomorrow. I can tell you’re doing your best. Let’s do something kind for ourselves today, and tomorrow you’ll get back to it. Don’t give up—I’m proud of you for chasing your dreams." 🤔 So, who would you choose? I know this little experiment might sound a bit dramatic—but be honest, wouldn’t we all prefer Friend 2 ? And isn’t Friend 1 sounding suspiciously like that inner critic of yours? For the longest time, trading advice has told us to "get rid of emotions" and stay completely “stress-free.” I wish it were that simple… The truth is, trying to trade without emotions is like talking to yourself like Friend 1 . Not only is it impossible —it also builds a harsh, critical inner dialogue that damages both your confidence and motivation. The reality is: we don’t have full control over our thoughts and emotions. They show up whether we want them to or not. If we could choose our emotional state, we’d all stay calm and focused every time we trade. But that’s not how the human mind works. Instead of fighting our emotions, we can learn to open up to them—without judgment. Self-compassionate trading means treating yourself like Friend 2 . It’s about acknowledging when things are tough, and being kind to yourself when stress or anxiety shows up. It’s about replacing harsh self-talk with encouragement, warmth and understanding. 👩🏽‍🔬 Some people think self-compassion is soft, ”girly”, or even “too emotional.” But guess what? It’s backed by tons of solid research. Studies show that self-compassion helps reduce self-criticism and improve motivation. It’s also an effective tool for managing tough emotions and reducing stress and anxiety. Self-compassionate trading is a win-win approach—it helps you stay grounded and resilient while building a meaningful trading journey. So why not give it a try? 👇 💡 Pro Tip: Next time you close a losing trade, find yourself in a losing streak, or just feel anxious about your performance—ask yourself: “What would I say to a good friend who’s going through the same thing?” Then offer that same kindness and support to yourself. Happy (self-compassionate) trading! 💙 / Tina the Trading Psychologist
OANDA:XAUUSDEducation
by Tina_TradingPsychologist
The Dangers of Holding Onto Losing Positions...One of the most common — and costly — mistakes in trading is holding onto a losing position for too long. Whether it's driven by hope, ego, or fear, this behavior can damage your portfolio, drain your capital, and block future opportunities. Successful trading requires discipline, objectivity, and the willingness to accept when a trade isn’t working. Understanding the risks behind this behavior is essential to protecting your capital and evolving as a trader. -- Why Traders Hold Onto Losing Trades -- It’s not always poor strategy or lack of experience that keeps traders locked in losing positions — it’s often psychology. Several cognitive biases are at play: 1. Loss Aversion Loss aversion refers to our instinctive desire to avoid losses, often stronger than the desire to realize gains. Traders may hold onto a losing position simply to avoid the emotional pain of admitting the loss, hoping the market will eventually turn in their favor. 2. Overconfidence When traders are overly confident in their analysis or trading thesis, they can become blind to changing market conditions. This conviction may cause them to ignore red flags and hold on out of sheer stubbornness or pride. 3. The Sunk Cost Fallacy This is the belief that since you’ve already invested money, time, or effort into a trade, you need to keep going to “get your investment back.” The reality? Past investments are gone — and continuing the position often compounds the loss. These mental traps can distort decision-making and trap traders in unproductive or damaging positions. Being aware of them is the first step toward better judgment. -- The True Cost of Holding Losing Positions -- Holding onto a bad trade costs more than just the money it loses. It impacts your entire trading strategy and limits your growth. Here’s how: 1. Opportunity Cost Capital tied up in a losing trade is capital that can’t be used elsewhere. If you keep $8,000 in a stock that’s fallen from $10,000 — hoping it rebounds — you're missing out on placing that money in higher-performing opportunities. Inactive capital is wasted capital. 2. Deeper Compounding Losses A 20% loss doesn’t sound catastrophic until it becomes 30%… then 40%. The deeper the loss, the harder it becomes to break even. Holding out for a recovery often makes things worse — especially in markets with high volatility or downtrends. 3. Reduced Liquidity Successful traders rely on flexibility. When your funds are tied up in a losing position, you limit your ability to respond to new opportunities. In fast-moving markets, this can be the difference between success and stagnation. Recognizing these costs reframes the decision from “holding on until it turns around” to “preserving capital and maximizing potential.” Consider this simple XAUUSD (Gold) weekly chart example. If you base a trading strategy solely on the Stochastic oscillator (or any single indicator) without backtesting and ignoring the overall trend, focusing solely on overbought signals for reversals, you'll quickly see the oscillator's frequent inaccuracies. This approach will likely lead to substantial and prolonged losses while waiting for a reversal that may never occur. -- Signs It’s Time to Exit a Losing Trade -- The hardest part of trading isn’t opening a position — it’s closing a bad one. But if you know what to look for, you’ll know when it’s time to let go: 1. Emotional Attachment If you find yourself feeling “married” to a trade, it’s a warning sign. Traders often assign meaning or identity to a position. But trading should be based on data and strategy, not sentiment. 2. Ignoring or Adjusting Your Stop Loss Stop Loss orders exist for a reason: to protect your capital. If you habitually move your stop further to avoid triggering it, you’re letting hope override risk management. 3. Rationalizing Losses Statements like “It’ll bounce back” or “This company always recovers” can signal denial. Hope is not a strategy. When you catch yourself justifying a bad position without objective reasoning, it’s time to reevaluate. Consider also reading this article: -- How to Cut Losses and Move Forward -- Cutting a loss isn’t a failure — it’s a skill. Here are proven techniques that help you exit with discipline and confidence: 1. Use Stop Losses — and Respect Them Set a Stop Loss at the moment you enter a trade — and stick to it. It takes the emotion out of the exit and protects your downside. Moving the stop is the fastest path to deeper losses. 2. Trade With a Plan Every trade should be part of a bigger strategy that includes risk tolerance, entry/exit points, and profit targets. If a position hits your predetermined loss threshold, exit. Trust your system. 3. Apply Position Sizing and Diversification Never risk more than a small percentage of your capital on a single trade. Keep your portfolio diversified across different instruments or sectors to avoid one position derailing your progress. 4. Review and Reflect Post-trade analysis is vital. Review both wins and losses to learn what worked — and what didn’t. This practice sharpens your strategy and builds emotional resilience over time. -- Why Cutting Losses Strengthens Your Portfolio -- There’s long-term power in letting go. Here’s what cutting losses early can do for you: 1. Preserve Capital The faster you cut a losing trade, the more capital you retain — and the more opportunities you can pursue. Capital preservation is the foundation of longevity in trading. 2. Reduce Emotional Stress Sitting in a losing trade weighs heavily on your mindset. The stress can cloud your judgment, increase risk-taking, or cause hesitation. Exiting early reduces this emotional drag and keeps you clear-headed. 3. Reallocate to Better Setups Exiting losing trades frees up both capital and mental energy for higher-probability opportunities. This proactive approach builds momentum and reinforces the idea that it’s okay to be wrong — as long as you act decisively. Consider also reading this article: -- Final Thoughts: Discipline Over Denial -- Holding onto losing trades may feel like you're showing patience or commitment — but in reality, it's often denial wrapped in hope. Trading is about probabilities, not guarantees. The most successful traders aren’t the ones who win every trade — they’re the ones who manage losses with discipline. Letting go of a bad trade is a show of strength, not weakness. It’s a deliberate choice to protect your capital, stay agile, and refocus on trades that serve your goals. The market doesn’t owe you a comeback — but with a clear head and disciplined approach, you can always find your next opportunity. ✅ Please share your thoughts about this article in the comments section below and HIT LIKE if you appreciate my post. Don't forget to FOLLOW ME; you will help us a lot with this small contribution.
EIGHTCAP:XAUUSDEducation
by FOREXN1
1
SYM Trade Breakdown – Robotics Meets Smart Technical's🧪 Company: Symbotic Inc. ( NASDAQ:SYM ) 🗓️ Entry: April–May 2025 🧠 Trade Type: Swing / Breakout Reversal 🎯 Entry Zone: $16.28–$17.09 ⛔ Stop Loss: Below $14.00 🎯 Target Zone: $50–$64+ 📈 Status: Strong Rally in Motion 📊 Why This Trade Setup Stood Out ✅ Macro Falling Wedge Reversal After nearly two years of compression inside a falling wedge, price finally tapped multi-year structural support and fired off with strength. This wasn’t just a bottom — it was a structural inflection point. ✅ Triple Tap at Demand Zone Symbotic tapped the ~$17 area multiple times, signaling strong accumulation. Volume and momentum picked up with each successive test, showing institutional interest. ✅ Clean Break of Trendline Price broke through the falling resistance trendline decisively, confirming the bullish reversal and unleashing stored energy from months of sideways structure. 🔍 Company Narrative Backdrop Symbotic Inc. isn't just any tech stock. It’s at the forefront of automation and AI-powered supply chain solutions, with real-world robotics deployed in major retail warehouses. That kind of secular growth narrative adds rocket fuel to technical setups like this — especially during AI adoption surges. Founded in 2020, Symbotic has quickly become a rising name in logistics and warehouse automation, serving the U.S. and Canadian markets. With robotics in demand and investors chasing future-ready tech, the price action aligned perfectly with the macro theme. 🧠 Lessons from the Trade ⚡ Compression = Expansion: Wedges like this build pressure. When they break, the moves are violent. 🧱 Structure Never Lies: The $17 zone was no accident — it was respected over and over. 🤖 Tech Narrative Boosts Confidence: Trading is easier when the fundamentals align with the technicals. 💬 What’s Next for SYM? If price holds above the wedge and clears the $64 resistance, we could be looking at new all-time highs in the next cycle. Watching for consolidation and retests as opportunity zones. #SYM #Symbotic #Robotics #Automation #AIStocks #BreakoutTrade #FallingWedge #SwingTrade #TechnicalAnalysis #TradingView #TradeRecap #SupplyChainTech
NASDAQ:SYMEducation
by Adlercon333
Survive first. Thrive later.🧠 Trading Psychology x Risk Management "If you can't survive being wrong, you don't deserve to be right." 💬 A calm chart… A ruthless truth. Most traders obsess over being right. But the market only rewards those who manage being wrong. Risk control isn’t just technical — it’s emotional. Survive first. Thrive later. — MJTrading Psychology Always Matters: Click on them for notes in the caption... #MJTrading #ChartDesigner #TradingPsychology #RiskManagement #MindfulTrading #CapitalPreservation #SmartMoney #XAUUSD #ForexDiscipline #15minChart #GoldAnalysis #MentalEdge #Gold
EIGHTCAP:XAUUSDEducation
by MJElahifx
1
How to Evaluate Companies with a Fundamental Dashboard**Tutorial: How to Evaluate Companies with a Fundamental Dashboard (Example: Nokia)** This tutorial explains how to use a custom-built dashboard in TradingView to evaluate companies based on key financial dimensions: **Valuation**, **Profitability**, and **Solvency & Liquidity**. --- 🛠 **How to Use This Tool** This dashboard is meant to be an educational visual filter for fundamental analysis. Here’s how you can use it: 1. Add the script to any stock chart in TradingView. 2. Choose your preferred data period: annual (FY) or quarterly (FQ). 3. Adjust the thresholds in the script settings to reflect your investment approach. 4. The dashboard displays 17 key financial ratios grouped into three categories. 5. Each metric is evaluated visually with ✔️ (meets threshold) or ❌ (falls short). 6. Use this dashboard to identify companies worth deeper analysis — not to make automatic decisions. --- 📊 **Understanding the Dashboard Sections** ### 🔹 Valuation Metrics Used to assess whether a stock appears undervalued based on price-to-value fundamentals: - Earnings Yield - EV/EBIT, EV/FCF - P/B Ratio - Free Cash Flow Yield - PEG Ratio ### 💰 Profitability Metrics Evaluate how efficiently the company turns revenue into profit: - ROIC, ROE - Operating, Net, and Gross Margins - Revenue Growth ### 🔒 Solvency & Liquidity Assess financial strength and balance sheet resilience: - Debt/Equity, Debt/EBITDA - Current Ratio, Quick Ratio - Altman Z-Score --- 📍 **Case Study: Nokia (Ticker: NOK)** This tutorial applies the dashboard to Nokia to demonstrate how to interpret results: - ✅ **Valuation is strong**: Most metrics meet or exceed typical value thresholds. - ⚠️ **Profitability shows weaknesses**: ROIC and revenue growth fall below expectations. - 💪 **Solvency is healthy**: Debt is under control, though Altman Z-Score signals some risk. This example helps show how the tool highlights strengths and red flags at a glance. --- 🎯 **Key Takeaway** This dashboard is not a signal generator — it’s a thinking aid. Its purpose is to help investors explore company fundamentals visually and consistently. The thresholds are customizable, and the tool encourages deeper due diligence. --- ⚠️ **Educational Disclaimer** This tutorial is for educational purposes only. It does **not** provide investment advice or recommendations. It is intended to demonstrate how to use a script to organize and interpret fundamental financial data. Always do your own research and exercise independent judgment before making any financial decisions.
NYSE:NOKEducation
by jtomasfg
Market Travel: An Adaptive Framework for Tracking Structure🧭 Understanding Market Travel: An Adaptive Framework for Tracking Structure Manually Market structure can be one of the most challenging patterns to read. There are tools and methods to help interpret it, but none are absolute. As market speed and volatility shift, so does its behavior. That’s why it’s important to move beyond rigid definitions and start understanding how price travels through the market. What Is Travel? “Travel” is a concept I developed through personal study and chart work. As price moves, it naturally forms pullbacks—temporary dips toward the weak side—and breaks—moves that close beyond the strong side. These are the two critical phases that form the backbone of market structure. While most people focus on static patterns, I’ve found more value in learning how price travels through its pullbacks and breaks. These movements aren’t random—they follow clear behavioral patterns. Once you learn to identify these, structure becomes easier to read across timeframes. The Three Modes of Travel I've observed three types of travel that occur between the dip and the break: 1. Pure Sentiment Travel This is the cleanest and most decisive form of travel. Price moves in one dominant direction with little to no opposing candles. For example, in a daily uptrend, the pullback might consist entirely of bearish 4H candles. As soon as a strong bullish candle appears, that typically signals the return toward the trend’s strong high. 2. Stacking Travel Stacking is more nuanced. Price moves with alternating bullish and bearish candles, but the dominant sentiment stays in control. Let’s say price is dipping in a daily uptrend. On the 1H chart, you may see a bearish sequence that includes a few bullish candles. These bullish candles don’t invalidate the bearish structure because they fail to close above the pivot high formed between the last bullish leg and the beginning of the bearish move. As long as that high is respected, the bearish stacking is valid. Once price breaks that high (or, in a bullish stacking case, breaks the pivot low), the stacking order is broken, and that signals a reversal back toward the dominant direction. 3. Shifting Travel Shifting travel looks similar to stacking but is constantly flipping between bullish and bearish stacking. Each shift creates a new high or low within the shifting structure. These micro-structures form lower lows or higher highs as sentiment switches back and forth. Once price breaks its own shifting structure (e.g., breaks a bearish sequence with a bullish close), this typically signals the end of that leg of travel and a reversal toward the dominant higher timeframe trend. How to Apply Travel Across Timeframes These three types of travel operate in a hierarchy: - Shifting travel (LTF) respects stacking travel (MTF) - Stacking travel (MTF) respects pure travel (HTF) - Pure sentiment travel (HTF) is the master mode that resets the others When you identify a new pure sentiment shift on the higher timeframe, that becomes your reset point. From that candle forward, you should begin fresh stacking and shifting analysis on your lower timeframes. Workflow example: 1. Spot a pure sentiment shift on the HTF (e.g., bullish daily candle after a clean bearish pullback) 2. From that pivot low, begin tracking stacking travel on the MTF 3. Use shifting travel on the LTF to navigate inside the stacking structure If stacking or shifting behavior breaks unexpectedly, that usually means market speed is changing—and you may need to reassign which timeframes serve as HTF, MTF, and LTF. Why This Works This framework gives you a fixed point of structure—the dip and the break—but allows you to adapt to the behavior in between. Instead of just reacting to breakouts, you're learning how price moves to get there. That’s what gives you the edge: not just reading where price is, but how it’s traveling to get there. Final Thoughts This adaptive travel model helps break down market structure into something both trackable and flexible. Try observing these travel types in real time and let me know how it works for you. Tools & Resources If you’d like to access my Pure Order Flow indicator and more exclusive tools, visit my TradingView profile: @The_Forex_Steward I’ve built an arsenal of indicators designed to support this framework across different markets and styles. If this breakdown helped, don’t forget to boost the post so others can benefit from it too!
Education
by The_Forex_Steward
The Empirical Validity of Technical Indicators and StrategiesThis article critically examines the empirical evidence concerning the effectiveness of technical indicators and trading strategies. While traditional finance theory, notably the Efficient Market Hypothesis (EMH), has long argued that technical analysis should be futile, a large body of academic research both historical and contemporary presents a more nuanced view. We explore key findings, address methodological limitations, assess institutional use cases, and discuss the impact of transaction costs, market efficiency, and adaptive behavior in financial markets. 1. Introduction Technical analysis (TA) remains one of the most controversial subjects in financial economics. Defined as the study of past market prices and volumes to forecast future price movements, TA is used by a wide spectrum of market participants, from individual retail traders to institutional investors. According to the EMH (Fama, 1970), asset prices reflect all available information, and hence, any predictable pattern should be arbitraged away instantly. Nonetheless, technical analysis remains in widespread use, and empirical evidence suggests that it may offer predictive value under certain conditions. 2. Early Empirical Evidence The foundational work by Brock, Lakonishok, and LeBaron (1992) demonstrated that simple trading rules such as moving average crossovers could yield statistically significant profits using historical DJIA data spanning from 1897 to 1986. Importantly, the authors employed bootstrapping methods to validate their findings against the null of no serial correlation, thus countering the argument of data mining. Gencay (1998) employed non-linear models to analyze the forecasting power of technical rules and confirmed that short-term predictive signals exist, particularly in high-frequency data. However, these early works often omitted transaction costs, thus overestimating potential returns. 3. Momentum and Mean Reversion Strategies Momentum strategies, as formalized by Jegadeesh and Titman (1993), have shown persistent profitability across time and geographies. Their approach—buying stocks that have outperformed in the past 3–12 months and shorting underperformers—challenges the EMH by exploiting behavioral biases and investor herding. Rouwenhorst (1998) confirmed that momentum exists even in emerging markets, suggesting a global phenomenon. Conversely, mean reversion strategies, including RSI-based systems and Bollinger Bands, often exploit temporary price dislocations. Short-horizon contrarian strategies have been analyzed by Chan et al. (1996), but their profitability is inconsistent and highly sensitive to costs, timing, and liquidity. 4. Institutional Use of Technical Analysis Contrary to the belief that TA is primarily a retail tool, it is also utilized—though selectively—by institutional investors: Hedge Funds: Many quantitative hedge funds incorporate technical indicators within multi-factor models or machine learning algorithms. According to research by Neely et al. (2014), trend-following strategies remain a staple among CTAs (Commodity Trading Advisors), particularly in futures markets. These strategies often rely on moving averages, breakout signals, and momentum filters. Market Makers: Although market makers are primarily driven by order flow and arbitrage opportunities, they may use TA to model liquidity zones and anticipate stop-hunting behavior. Order book analytics and technical levels (e.g., pivot points, Fibonacci retracements) can inform automated liquidity provision. Pension Funds and Asset Managers: While these institutions rarely rely on TA alone, they may use it as part of tactical asset allocation. For instance, TA may serve as a signal overlay in timing equity exposure or in identifying risk-off regimes. According to a CFA Institute survey (2016), over 20% of institutional investors incorporate some form of technical analysis in their decision-making process. 5. Adaptive Markets and Conditional Validity Lo (2004) introduced the Adaptive Markets Hypothesis (AMH), arguing that market efficiency is not a binary state but evolves with the learning behavior of market participants. In this framework, technical strategies may work intermittently, depending on the ecological dynamics of the market. Neely, Weller, and Ulrich (2009) found technical rules in the FX market to be periodically profitable, especially during central bank interventions or volatility spikes—conditions under which behavioral biases and structural inefficiencies tend to rise. More recent studies (e.g., Moskowitz et al., 2012; Baltas & Kosowski, 2020) show that momentum and trend-following strategies continue to deliver long-term Sharpe ratios above 1 in diversified portfolios, particularly when combined with risk-adjusted scaling techniques. 6. The Role of Transaction Costs Transaction costs represent a critical variable that substantially alters the net profitability of technical strategies. These include: Explicit Costs: Commissions, fees, and spreads. Implicit Costs: Market impact, slippage, and opportunity cost. While early studies often neglected these elements, modern research integrates them through realistic backtesting frameworks. For example, De Prado (2018) emphasizes that naive backtesting without cost modeling and slippage assumptions leads to a high incidence of false positives. Baltas and Kosowski (2020) show that even after accounting for bid-ask spreads and market impact models, trend-following strategies remain profitable, particularly in futures and FX markets where costs are lower. Conversely, high-frequency mean-reversion strategies often become unprofitable once these frictions are accounted for. The impact of transaction costs also differs by asset class: Equities: Higher costs due to wider spreads, especially in small caps. Futures: Lower costs and higher leverage make them more suitable for technical strategies. FX: Extremely low spreads, but high competition and adverse selection risks. 7. Meta-Analyses and Recent Surveys Park and Irwin’s (2007) meta-analysis of 95 studies found that 56% reported significant profitability from technical analysis. However, profitability rates dropped when transaction costs were included. More recent work by Han, Yang, and Zhou (2021) extended this review with data up to 2020 and found that profitability was regime-dependent: TA performed better in volatile or trending environments and worse in stable, low-volatility markets. Other contributions include behavioral explanations. Barberis and Thaler (2003) suggest that TA may capture collective investor behavior, such as overreaction and underreaction, thereby acting as a proxy for sentiment. 8. Limitations and Challenges Several methodological issues plague empirical research in technical analysis: Overfitting: Using too many parameters increases the likelihood of in-sample success but out-of-sample failure. Survivorship Bias: Excluding delisted or bankrupt stocks leads to inflated backtest performance. Look-Ahead Bias: Using information not available at the time of trade leads to unrealistic results. Robust strategy development now mandates walk-forward testing, Monte Carlo simulations, and realistic assumptions on order execution. The growing field of machine learning in finance has heightened these risks, as complex models are more prone to fitting noise rather than signal (Bailey et al., 2014). 9. Conclusion Technical analysis occupies a contested but persistent role in finance. The empirical evidence is mixed but suggests that technical strategies can be profitable under certain market conditions and when costs are minimized. Institutional investors have increasingly integrated TA within quantitative and hybrid frameworks, reflecting its conditional usefulness. While TA does not provide a universal arbitrage opportunity, it can serve as a valuable tool when applied adaptively, with sound risk management and rigorous testing. Its success ultimately depends on context, execution discipline, and integration within a broader investment philosophy. References Bailey, D. H., Borwein, J. M., Lopez de Prado, M., & Zhu, Q. J. (2014). "The Probability of Backtest Overfitting." *Journal of Computational Finance*, 20(4), 39–69. Baltas, N., & Kosowski, R. (2020). "Trend-Following, Risk-Parity and the Influence of Correlations." *Journal of Financial Economics*, 138(2), 349–368. Barberis, N., & Thaler, R. (2003). "A Survey of Behavioral Finance." *Handbook of the Economics of Finance*, 1, 1053–1128. Brock, W., Lakonishok, J., & LeBaron, B. (1992). "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns." Journal of Finance, 47(5), 1731–1764. Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (1996). "Momentum Strategies." Journal of Finance, 51(5), 1681–1713. De Prado, M. L. (2018). Advances in Financial Machine Learning, Wiley. Fama, E. F. (1970). "Efficient Capital Markets: A Review of Theory and Empirical Work." Journal of Finance, 25(2), 383–417. Gencay, R. (1998). "The Predictability of Security Returns with Simple Technical Trading Rules." Journal of Empirical Finance, 5(4), 347–359. Han, Y., Yang, K., & Zhou, G. (2021). "Technical Analysis in the Era of Big Data." *Review of Financial Studies*, 34(9), 4354–4397. Jegadeesh, N., & Titman, S. (1993). "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency." *Journal of Finance*, 48(1), 65–91. Lo, A. W. (2004). "The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective." *Journal of Portfolio Management*, 30(5), 15–29. Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). "Time Series Momentum." *Journal of Financial Economics*, 104(2), 228–250. Neely, C. J., Weller, P. A., & Ulrich, J. M. (2009). "The Adaptive Markets Hypothesis: Evidence from the Foreign Exchange Market." *Journal of Financial and Quantitative Analysis*, 44(2), 467–488. Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014). "Forecasting the Equity Risk Premium: The Role of Technical Indicators." *Management Science*, 60(7), 1772–1791. Park, C. H., & Irwin, S. H. (2007). "What Do We Know About the Profitability of Technical Analysis?" *Journal of Economic Surveys*, 21(4), 786–826. Rouwenhorst, K. G. (1998). "International Momentum Strategies." *Journal of Finance*, 53(1), 267–284. Zhu, Y., & Zhou, G. (2009). "Technical Analysis: An Asset Allocation Perspective on the Use of Moving Averages." *Journal of Financial Economics*, 92(3), 519–544.
SP:SPXEducation
by EdgeTools
What do we need to know before investing?If you are thinking about investing money for the potential returns it offers, you should know that it may go well, but that there are always risks. That’s why we are going to give you some basic tips to bear in mind before making any investment decision. How much money are you going to invest? First of all, you need to decide how much money you want to put towards your financial investments. The markets are subject to change The financial markets are constantly fluctuating. The term volatility is the most commonused term to describe and measure the uncertainty provided by changes to theprices of financial assets. Additionally, there are times in the market when the prices are more pronounced and every now and then there are crisis periods and asset prices fall dramatically. Investing in financial markets means that we have to assume that our investments will always be subject to these types of fluctuations. If you are going to invest in the financial markets the money that you invest must be money that you will not need during the investment term. That’s why, investing in order to obtain short term gains is inevitably associated with high risk. Furthermore, the larger our intended gains, the larger the associated risk. Always bear in mind that the greater the expected returns, the greater the assumed risk. Once again, be sure that you do not need the money that you are going to invest, as it may have losses. The opposite can be said of long term investments, where the capacity to wait and overcome falls in the market means that you can assume more risk with your investments. With a long term vision you will avoid having to experience any possible losses with your investment period due to any eventual liquidity needs. How much risk are you willing to take on? Before investing it is important to know the risk you can assume. Every investor has their own risk tolerance level that they need to be aware of. Risks and returns go hand in hand, because for more returns you also need to take on more risk, and vice versa. It is also good to know that just as with normal market conditions, those assets with a higher risk tend to suffer more fluctuations with their prices than those assets with less risk. Therefore, in general terms: When the forecasts for the financial markets are favourable and the market goes up, those assets with higher expected returns generally perform excellently. Whenever the financial markets are going through uncertain times, those assets with higher expected returns, and therefore more risk, tend to perform worse. You must start from a strong financial position To invest you need to be at a point where your accounts are well under control, including your debts. We do not mean to say that if you have any outstanding credit you cannot invest, but it is essential that everything is in order and that you are in a situation where you can fulfil your financial obligations. On the other hand, to build long term wealth, it is important that you assign part of your income to your savings, meaning that you have to invest with the money left over after making your payments while also saving part of what you earn. It is important to keep a composed outlook Now we know that investing bears its own risks and that the market is subject to change, it is essential to be composed when investing. When investing it is important to think positively, as if you don’t really believe that things will work out, why invest? It is one thing to be cautious, and to know how much money to invest and what level of risk tolerance to assume, and another to think negatively each time there is a drop in the market. In reality, investing is a combination of caution and composure. Diversification is the key to success Somebody with less investment experience may make the mistake of putting all of their investment budget into just one thing. However, it is much better to have diverse investments, as while some investments may not quite work out as you would have liked them to, some do even better. Losses are normal, and so are returns We previously said that when investing it is important to stay calm, and that is true. In this regard, you also have to bear in mind that it is normal for some investments in your portfolio to not perform as well as you had expected. We cannot predict the behaviour of the financial markets or of certain assets. We can also unexpectedly find ourselves with some assets that don’t perform as well as we had hoped. That is why we recommend, in addition to not risking more than you can invest, to diversify your investments well. We have already said that investment involves risk, which is why it is good to know that if you are willing to invest, you are also willing to take on risks. If you are prepared to take on this risk, you can be successful in your investments. Did you like it? Share with your friends by HollyMontt
BITSTAMP:BTCUSDEducation
by hollymontt
How to Trade Doji Candles on TradingViewLearn to identify and trade doji candlestick patterns using TradingView's charting tools in this comprehensive tutorial from Optimus Futures. Doji candles are among the most significant candlestick formations because they signal market indecision and can help you spot potential trend reversal opportunities. What You'll Learn: • Understanding doji candlestick patterns and their significance in market analysis • How to identify valid doji formations • The psychology behind doji candles: when buyers and sellers fight to a draw • Using volume analysis to confirm doji pattern validity • Finding meaningful doji patterns at trend highs and lows for reversal setups • Timeframe considerations for doji analysis on any chart period • Step-by-step trading strategy for doji reversal setups • How to set stop losses and profit targets • Real example using E-Mini S&P 500 futures on 60-minute charts This tutorial may help futures traders and technical analysts who want to use candlestick patterns to identify potential trend reversals. The strategies covered could assist you in creating straightforward reversal setups when market indecision appears at key price levels. Learn more about futures trading with Tradingview: optimusfutures.com Disclaimer: There is a substantial risk of loss in futures trading. Past performance is not indicative of future results. Please trade only with risk capital. We are not responsible for any third-party links, comments, or content shared on TradingView. Any opinions, links, or messages posted by users on TradingView do not represent our views or recommendations. Please exercise your own judgment and due diligence when engaging with any external content or user commentary. This video represents the opinion of Optimus Futures and is intended for educational purposes only. Chart interpretations are presented solely to illustrate objective technical concepts and should not be viewed as predictive of future market behavior. In our opinion, charts are analytical tools—not forecasting instruments. Market conditions are constantly evolving, and all trading decisions should be made independently, with careful consideration of individual risk tolerance and financial objectives.
CME_MINI:ES1!Education
by OptimusFutures
The Ineffectiveness of Day Trading: A Critical Review of EmpiricThe Allure of Quick Profits Day trading has gained considerable popularity as an investment strategy among retail investors, particularly following technological advances in electronic trading platforms and commission-free brokerage services. This analysis examines the available empirical evidence from various markets and time periods to evaluate the economic viability of day trading as an investment strategy. The most comprehensive study on the subject comes from Barber et al. (2011), who analyzed the behavior of over 360,000 day traders in Taiwan. Their results show that over 80 percent of day traders lose money, and less than 1 percent can achieve consistently profitable results. These findings align with similar studies from other markets and confirm the systematic unprofitability of day trading for the vast majority of participants. Day trading represents a systematically unprofitable investment strategy for retail investors, rooted in cognitive biases (Kahneman & Tversky, 1979), excessive transaction costs, and market microstructure inefficiencies (O'Hara, 1995). Long-term passive investment strategies demonstrate superior risk-adjusted returns with significantly lower resource requirements. What the Research Shows The research landscape on day trading is clear and consistent across various markets. A systematic review of the most important studies follows established standards of financial market research. The inclusion criteria for relevant studies encompass empirical investigations with substantial sample sizes (more than 1,000 traders), minimum observation periods of 12 months, and quantitative performance measures. The available literature is based on millions of trading accounts from various developed markets. The historical development of day trading shows clear parallels to technological developments in the financial sector. Before deregulation through Electronic Communication Networks by the SEC in 1997, it was impossible for retail investors to trade directly in the market. With the rise of online brokers like E*TRADE and Ameritrade, day trading became accessible to the mass public for the first time. This technical opening coincided with aggressive marketing that promoted free trades, low fees, and success stories of individual traders. Empirical Findings Evidence from various markets shows consistent patterns. Barber et al. (2011) document that 84.3 percent of 360,000 analyzed day traders in Taiwan suffered losses, with a median return of minus 8.7 percent. Similar studies from the United States confirm loss rates exceeding 90 percent of participants. Jordan and Diltz (2003) conclude that even experienced day traders are hardly able to beat the market after costs in the long term. The long-term results are even more sobering: only a fraction of all day traders remain profitable over extended periods, while a significant portion abandons the activity within two years. The transaction cost analysis is based on realistic market conditions. A calculation example illustrates the structural challenges: with an assumed daily trading volume of $50,000 and eight round trips per day, substantial costs arise from commissions (approximately 0.1% per trade), bid-ask spreads (averaging 0.02-0.05%), and market impact (about 0.01% for smaller volumes). Annual Cost Calculation Example: - 252 trading days × 8 trades = 2,016 trades/year - Commission costs: 2,016 × $2.50 = $5,040 - Spread costs: $50,000 × 0.03% × 2,016 = $30,240 - Total costs: approximately $35,000 or 70% of daily trading volume This cost structure means that day traders must achieve gross returns of well over 70 percent annually just to break even, while passive investors bear annual costs of only 0.1 to 0.3 percent (Bogle, 2007). Behavioral Analysis and Cognitive Biases Behavioral research explains why day trading remains attractive despite poor success prospects. Odean (1999) shows that overconfident investors trade excessively and thereby reduce their expected returns. The disposition effect documented by Shefrin and Statman (1985) leads traders to realize gains too early and hold losses too long. Kahneman and Tversky's (1979) Prospect Theory explains systematic biases in decision-making under uncertainty. Loss aversion leads to losses weighing psychologically heavier than equivalent gains, resulting in irrational holding of losing positions. The gambler's fallacy manifests in the erroneous assumption of many day traders that past losses make future gains more likely. Recency bias leads to overweighting recent events. These psychological factors reinforce each other and create a vicious cycle of irrational decisions. Comparative Analysis: Day Trading versus Passive Strategies A comparison with established investment strategies illustrates the systematic disadvantages of day trading. Malkiel (2011) documents long-term returns of diversified portfolios at 6-8 percent real, while Barber and Odean (2000) show that frequent trading systematically reduces returns. Historical data shows that the S&P 500 Index achieved an average annual return of 10.2 percent with 15.8 percent volatility over 30 years (Sharpe ratio: 0.65). Day traders, in contrast, typically exhibit negative Sharpe ratios as losses dominate amid high volatility. The time investment differs dramatically: day trading requires 40-50 hours of weekly attention, while passive investing demands less than one hour per week. Studies also show health burdens from the constant stress of active trading. Market Microstructure and Professional Trading Market structure systematically favors institutional players. High-frequency trading firms possess latency advantages in the microsecond range, while retail traders operate with delays exceeding 100 milliseconds. They utilize co-location services and process data volumes inaccessible to private investors. Market-making operations profit from bid-ask spreads and exchange rebate programs. They operate under different regulatory frameworks and have access to dark pools and proprietary technology. Day trading mathematically represents a zero-sum game that becomes negative after costs. Since the sum of all trading gains and losses equals zero, but transaction costs are positive, the expected return for all participants collectively is necessarily negative. Alternative Investment Strategies Academic literature comprehensively documents the superiority of passive strategies. Bogle (2007) demonstrates through long-term data that low-cost index funds consistently achieve better net returns than active strategies. Passive Strategy Calculation Example: An investment of €10,000 in a low-cost ETF (0.15% TER) with 7% annual returns yields approximately €37,000 after 20 years. To achieve this result, day traders would need to consistently earn over 15% gross returns after costs—a scenario that is empirically nearly impossible. Factor-based investing offers additional improvements: Fama and French (1992) documented excess returns for value and size factors that are systematically and cost-effectively accessible. Limitations of the Evidence The research landscape has certain constraints. Survivorship bias in datasets may underestimate actual losses, as unsuccessful traders disappear from samples more quickly. Additionally, definitions of day trading vary between studies. External validity is influenced by changing market structures. Algorithmic trading and new financial instruments may alter established patterns. Nevertheless, the fundamental problems of high costs and systematic behavioral biases persist. Conclusion The empirical evidence is clear: day trading represents a loss-making activity for the vast majority of participants. The combination of high transaction costs, systematic behavioral biases, and structural market disparities makes consistent profitability nearly impossible. While isolated success stories exist, they represent statistical outliers rather than replicable strategies. The scientific evidence speaks unequivocally in favor of long-term, low-cost, and diversified investment strategies as superior alternatives to day trading. Those who nonetheless engage in day trading should be aware that they are not only competing against the market, but against mathematical and psychological realities that practically preclude a high probability of success. References Barber, Brad M., Yi-Tsung Lee, Yu-Jane Liu, and Terrance Odean. "Do Individual Day Traders Make Money? Evidence from Taiwan." *Review of Financial Studies* 24, no. 8 (2011): 2892-2922. Barber, Brad M., and Terrance Odean. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors." *Journal of Finance* 55, no. 2 (2000): 773-806. Bogle, John C. *The Little Book of Common Sense Investing*. Hoboken: Wiley, 2007. Fama, Eugene F., and Kenneth R. French. "The Cross-Section of Expected Stock Returns." *Journal of Finance* 47, no. 2 (1992): 427-465. Jordan, Douglas J., and J. David Diltz. "The Profitability of Day Traders." *Financial Analysts Journal* 59, no. 6 (2003): 85-94. Kahneman, Daniel, and Amos Tversky. "Prospect Theory: An Analysis of Decision under Risk." *Econometrica* 47, no. 2 (1979): 263-291. Malkiel, Burton G. *A Random Walk Down Wall Street*. 10th ed. New York: Norton, 2011. Odean, Terrance. "Do Investors Trade Too Much?" *American Economic Review* 89, no. 5 (1999): 1279-1298. O'Hara, Maureen. *Market Microstructure Theory*. Oxford: Blackwell Publishers, 1995. Shefrin, Hersh, and Meir Statman. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence." *Journal of Finance* 40, no. 3 (1985): 777-790.
Education
by EdgeTools
Fat Tails: Why Mean Reversion is a Rarity in Financial MarketsIn financial markets, volatility is a measure of how much asset prices change over time. Traditionally, finance assumes that asset returns fit neatly into a "bell-shaped" normal distribution curve. This implies that prices usually stay close to their average, and extreme surges or drops (beyond three standard deviations) are very rare, with approximately a 0.3% probability. However, reality consistently refutes these expectations, showing that powerful fluctuations occur much more frequently in markets. This is the phenomenon of "fat tails".   What are "Fat Tails"? "Fat tails" occur when the probability of large price changes (up or down) is significantly higher than predicted by a normal distribution. Instead of a neat "bell-shaped" curve, we see distributions with "thick tails," like Lévy, Pareto, or Cauchy distributions. Such distributions are characterized by "excess kurtosis" (kurtosis > 3). Kurtosis is a statistical measure that shows the "peakedness" of a distribution and the "thickness of its tails." If kurtosis > 3, the tails are "heavier" than those of a normal distribution, and the peak is often higher—meaning that small deviations from the mean also occur more frequently, but extreme events are not as rare as they seem. These distributions better describe how markets behave, especially volatile ones like cryptocurrencies, where extreme movements happen 5-10 times more frequently than normal distribution models would predict.   For example, in October 1987 (Black Monday), the Dow Jones index plummeted by 22% in a single day—an event that a normal distribution would estimate as practically impossible. In 2020, WTI crude oil prices turned negative (–$40 per barrel), which also doesn't fit standard models. And Bitcoin, throughout its history, has repeatedly shown daily movements of ±20%, which is 50–100 times more frequent than a Gaussian distribution would predict. Imagine two graphs: Gaussian Bell Curve (Normal Distribution): Most events fall within ±3σ, and extremes are almost imperceptible. Fat-Tailed Distribution (e.g., Pareto): The "tails" are thick, and rare events (like crises) stand out like icebergs. These cases illustrate why classical risk models like VaR often fail. Let's explore how science attempts to address this problem. What Does This Mean for Risk? "Fat tails" change the rules of the game for risk management. Nassim Taleb, a prominent voice on this topic, argues that they invalidate conventional methods of financial analysis. Standard estimates of the mean, variance, and typical outliers of financial returns become unreliable. Models like VaR (Value at Risk), which rely on a normal distribution, often underestimate how badly things can go wrong. They are simply unprepared for "black swans"—rare but devastating events that can crash the market. As Taleb stated, "ruin is more likely to come from a single extreme event than from a series of bad episodes".   "Tail risk" is when an asset or portfolio experiences a significant change in value (more than three standard deviations from its current price) due to an unusual and unexpected event. Such events not only impact prices but can also trigger panic, liquidity issues, and spill over into other markets.   Although "fat tails" seem obvious, some economists (e.g., proponents of the efficient market hypothesis) argue that extreme events are merely rare but explainable deviations. They contend that if all factors (geopolitics, liquidity changes) are properly accounted for, the distribution isn't as "heavy-tailed" as it appears. However, the crises of 2008 and 2020 demonstrated that even the most sophisticated models often underestimate tail risk.   How Does Science Address "Fat Tails"? To grapple with these tails, researchers have developed several approaches: Extreme Value Theory (EVT): This method focuses specifically on the "tails" of the distribution to better predict extreme events. EVT helps to more accurately estimate risks and VaR, especially when a normal distribution clearly doesn't apply, and data more closely resembles Fréchet or Pareto distributions. Jump-Diffusion Models: These models explicitly incorporate sudden, discontinuous price changes, or "jumps," in addition to continuous diffusion movements. Robert Merton, as early as 1976, proposed combining smooth price movements with Poisson jumps to better describe the market. Jumps are interpreted as "abnormal" price variations caused by important news or systemic shocks.   Intraday Data Analysis: Barndorff-Nielsen and Shephard (2004) developed a method to decompose total price variation into a continuous component and a jump component using high-frequency data. This helps to more accurately forecast how much the market can fluctuate. GARCH Models: These models capture "volatility clustering"—the tendency for periods of high volatility to be followed by more high volatility, and periods of calm by more calm.   But if "fat tails" are so prevalent, why do many still believe in "mean reversion"? Here's the catch... Why Mean Reversion Doesn't Work The idea of "mean reversion" is that asset prices or returns will eventually revert to their long-term average. It's popular in finance, but with "fat tails," it's not so simple: Unstable Mean: In markets with "fat tails," the "mean" itself is constantly shifting. If the average value is unstable, then talking about reverting to it becomes less predictable and meaningful. Moreover, in such distributions, the sample mean often doesn't align with the theoretical mean.   Extreme Events Dominate: A single powerful fluctuation can turn everything upside down. Instead of "returning to normal," the market can enter a new regime of high volatility for an extended period.   Jumps Are Not Just Noise: Significant price changes due to news or shocks are not temporary outliers that can be easily smoothed out. They represent serious risks that cannot simply be waited out.   Volatility Clustering: Markets tend to "get stuck" in periods of high or low fluctuations. After a strong move, the market may not calm down but continue to fluctuate, which breaks the idea of mean reversion. Interestingly, "fat tails" arise not only from fundamental reasons but also from irrational crowd behavior. When the market falls, investors massively sell assets, exacerbating the crisis (a positive feedback effect). This explains why tails are "heavier" in cryptocurrencies—there are more speculators and fewer institutional players stabilizing the market.   Conclusion Mean reversion works only in "calm" times when the market behaves predictably. But in reality, "fat tails" and powerful fluctuations are not rare, but a part of financial market life. To cope with this unpredictability, more sophisticated models and risk approaches are needed. Understanding "fat tails" is key to managing risks in the chaotic financial world.
NASDAQ:NVDAEducation
by flibusters
Blueprint to Becoming a Successful Gold Trader in 2025🚀 Blueprint to Becoming a Successful Gold Trader in 2025 A strategic, step-by-step plan to master gold trading by combining institutional concepts, cutting-edge automation, and the best prop funding opportunities for XAUUSD. ________________________________________ 🏦 Broker Selection (Gold-Specific) • 🔍 Choose Brokers Offering Raw Spread XAUUSD Accounts: Seek brokers with raw/zero spread gold trading or tight gold spreads (0.10-0.30 average) with deep liquidity. • ⚡ Prioritize Ultra-Fast Execution for Metals: Confirm broker servers are in NY4/LD4 and latency is optimized for gold volatility spikes. • 🛡️ Verify Regulation & Execution: ASIC, FCA, FSCA preferred; check for proof of XAUUSD execution quality (Myfxbook/FXBlue verified). • 📊 MetaTrader 4/5 Gold Support: Ensure MT4/5 platform offers tick-chart precision for gold and supports custom EAs/indicators. • 💳 Flexible Withdrawals/Payouts: Crypto, Wise, and Revolut compatibility for fast, secure funding. ________________________________________ 🎯 Gold Trading Strategy (ICT + Supply/Demand Zones) • 🧠 Master Gold-Adapted ICT Concepts: o Liquidity runs and stops at London/NY session highs/lows o XAUUSD-specific Order Blocks (OBs), FVGs, and Market Structure Breaks (MSB) • 📍 Map Institutional Supply-Demand Zones: Gold reacts violently to these—align SD zones with ICT Order Blocks for best confluence. • 📐 Precision Entries: Only enter after liquidity sweeps at key XAUUSD levels (H4/D1), avoiding choppy retail entries. • 📈 Time & Price for XAUUSD: Focus exclusively on London Open (8:00 GMT) and NY Open/Gold Fixing (13:20 GMT)—peak volatility windows. • 📆 Weekly Preparation: Annotate D1/H4 gold charts every Sunday with clear OBs, liquidity points, and SD zones for the week. ________________________________________ 💰 Prop Funding for Gold Trading • 🥇 Select Firms Offering XAUUSD with Tight Rules: Choose FTMO, The Funded Trader, MyFundedFX, or similar with high leverage and XAUUSD trading enabled. • 📑 Pass Evaluation with Gold-Only Strategy: Use high-probability, low-frequency XAUUSD trades—1-3 setups per week, strict risk parameters. • 🎯 Risk Management: Max 1% risk/trade, stop trading after 2 consecutive losses—protect account and pass evaluations. • 📊 Analytics Monitoring: Use prop dashboards (FTMO Metrics, FundedNext stats) to review XAUUSD trade stats and adjust. • 📚 Diversify Funded Accounts: Split funded capital among multiple firms to hedge against firm-specific risk and maximize payouts. ________________________________________ ⚙️ Automating Gold Trading (MT4/5 EAs & Bots) • 🛠️ Hire MQL4/5 Developers for XAUUSD EAs: Code bots focused on gold-specific ICT (OBs, FVGs, London/NY volatility). • 🤖 Develop EAs for Gold: o OB/FVG/Market Structure detection on XAUUSD o Supply/Demand zone algo entries o Gold breakout EAs for session openings • 📌 Trade Management Automation: o Entry, stop loss, partial TP, BE, trailing for gold’s high volatility o Dynamic lot-sizing by daily ATR • 📡 VPS Hosting Near Broker’s Gold Server: Use NY4/LD4 VPS for lowest latency (ForexVPS, Beeks). • 📈 Quarterly Forward-Testing: Optimize EAs in demo before live trading, retest on every major gold volatility shift (FOMC, CPI). ________________________________________ 📲 Leveraging Bots & AI in 2025 • 📊 Integrate with MT4/5 Analytics Tools: Use myfxbook, QuantAnalyzer for detailed gold trade breakdowns. • 🔮 AI-Based Gold Forecasting: Layer in machine learning models (e.g., TensorTrade, TradingView AI) to anticipate session volatility and direction. • 🔔 Real-Time Alert Bots: Set up Telegram/Discord bots for instant notification of ICT-based XAUUSD signals. • 🧑‍💻 Manual Oversight: Always review high-impact news (NFP, CPI, FOMC) and override automation when macro risk spikes. • 🔄 Continuous Bot Updates: Retrain your EAs monthly on latest XAUUSD price action to maintain edge. ________________________________________ 🗓️ Daily Gold Trader Routine • 🌅 Pre-Session (30 mins): Review annotated gold charts, key session highs/lows, OB/FVG/SD levels, and upcoming news. • 💻 During Session: Monitor bot execution, validate setups manually, manage risk during NY/London overlap. • 📝 Post-Session (15 mins): Journal gold trades, note reasoning for entry/exit, emotional state, and lessons learned. • 📆 Weekly Review: Assess overall gold trading stats and EA performance, adjust strategy as needed. • 📚 Continuous Learning: Stay updated on ICT, gold market fundamentals, and new trading tech. ________________________________________ 📌 Final Success Advice for 2025 • 🔍 Specialize in XAUUSD/Gold—Don’t Diversify Randomly: Depth > Breadth—become a true gold trading expert. • 🚩 Keep Adapting Your Gold Trading EAs: Markets change—so must your bots and playbooks. • 🧘 Stay Patient, Disciplined, and Selective: Gold rewards precision and patience, not overtrading. • 💡 Embrace AI & Automation: Leverage every tool: AI, analytics, and custom EAs for a real 2025 trading edge.
OANDA:XAUUSDEducation
by ProjectSyndicate
30
Entering Green Markets or Getting Close to Liquidation?They told you it’s a green market, time to buy... but something’s off. Most major losses begin with a green candle, not a red one! Before jumping in, ask yourself: why does everything suddenly look so clear? Hello✌ Spend 3 minutes ⏰ reading this educational material. 🎯 Analytical Insight on Bitcoin: Strong volume confirming daily trendline and Fibonacci support signals a potential 8% upside, with a key target near $128,000 📈. This confluence could offer a solid entry opportunity for BINANCE:BTCUSDT traders 🧭. Now , let's dive into the educational section, 📉 Green Doesn’t Always Mean Safe Many traders jump into green candles, feeling they’re missing out. But most pumps end where excitement begins. The market isn’t always bullish it’s often just using collective emotion against you. 🧠 They’re Targeting Your Mind, Not Just Your Capital Whales don’t need your money they need your mind first. The moment you think you're "too late" and must enter now, is often when they’re selling. 💡 You’re Fueling Their Profits, Not Your Trade Those who bought early are waiting for someone like you. If you enter now, you're not beating the market you’re just helping others close in profit. 🔍 Why Most Liquidations Happen After Green Moves Contrary to belief, major liquidations often come after green runs. That’s when confidence is high, stops are forgotten, and greed kicks in perfect timing for a rug-pull. 📊 History Doesn’t Repeat It Rhymes (Loudly) Go back and look at Bitcoin’s chart since 2017. Nearly every major drop followed a smooth-looking pump. It’s not a warning. It’s a recurring pattern. 🎯 Hidden TradingView Tools for Spotting Green Traps The market looks bullish. But the truth is, many pumps are just emotional traps built to bait late entries. TradingView has tools that, if used right, help you spot these traps before you step into them: ✅ Volume Profile (Fixed Range): Use this to identify where the most trading volume occurred. If price rises on weak volume, be suspicious. It could be a fakeout or engineered pump by whales. ✅ RSI + Manual Divergence Drawing: RSI seems simple, but traps often hide when RSI climbs while price action lags. TradingView allows manual drawing spot bearish divergence before the fall. ✅ On-Balance Volume (OBV): If price is rising and OBV is flat or falling, warning lights should flash. A rally without money inflow is often a visual illusion. ✅ Session Volume HD (from Public Library): See when most liquidity enters. Many fake bullish moves happen during the Asia session when volume is low and price is easier to manipulate. ✅ Multi-Timeframe Analysis: If you're looking at the 15-min chart while the 4-hour sits in resistance, you may just be playing into a bull trap. Cross-reference your timeframes. 🧭 How to Avoid the Green Traps Watch volume, not just candle color Wait for level confirmations, not hype Use TradingView’s combo indicators Always ask: who profits if I enter right now? ✅ Final Thoughts Not every green candle is hope sometimes it’s bait. The market is after your emotions, not your charts. Step back, zoom out, and use the right tools before you act. ✨ Need a little love! We pour love into every post your support keeps us inspired! 💛 Don’t be shy, we’d love to hear from you on comments. Big thanks , Mad Whale 🐋 📜Please make sure to do your own research before investing, and review the disclaimer provided at the end of each post.
Education
by MadWhale
34