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How Do Traders Use the Pivot Points Indicator? How Do Traders Use the Pivot Points Indicator? Pivot points are a popular technical analysis tool for spotting areas where the price is expected to react, i.e. pause or reverse. Calculated using the previous day’s high, low, and close, they’re projected onto the current session to highlight potential support and resistance levels, especially useful for intraday traders. Alongside stock charts, pivot point levels can be used in a wide variety of markets, including forex, commodities, and cryptocurrencies*. As a versatile indicator, pivot points also come in many different types. This article breaks down the definition of pivot points, the variations traders use, and how they can fit into a broader trading strategy. A Deeper Look at Pivot Points A common question in technical analysis is, “What is a pivot point?” Pivot points trading, or pivot point theory, is a popular technical analysis concept used in a range of financial asset classes, including stocks, currencies, cryptocurrencies*, and commodities. The indicator assists traders in gauging overall market trends and determining possible support and resistance barriers. How to Read Pivot Points The pivot point indicator is static—it’s an average of the high, low, and close prices from the previous trading day. It includes three levels: pivot point (P), support (S), and resistance (R). If the price is above the pivot point, it is supposed to target resistance barriers. Conversely, if it’s below the pivot, it could move to support levels. Thus, support and resistance levels serve as targets or stop-loss zones. They remain constant throughout the period, enabling traders to plan ahead. In the EURUSD daily chart below, the price is trading above R2; therefore, market sentiment is assumed to be bullish. R3 indicates the next possible price target. Should a shift below P occur, bearishness arises, and S1 becomes the upcoming support level. Pivots are widely used with trend indicators such as moving averages and Fibonacci tools. In the chart below, Fibonacci retracements could be used to identify intermediate levels of support and resistance within widely placed pivots. How to Calculate Pivot Points? There are four key types of pivots, including standard, Woodie’s, Camarilla, and Fibonacci. While there’s no need to use a pivot points calculator—they’re calculated automatically when implemented on a price chart—it is worth looking at their formulas to understand how they differ from each other. Note the labels for the following formulas: P = pivot point H = high price L = low price C = close price Standard Pivot Points Traders commonly use standard pivot points. Traditional pivots (P) identify potential levels of support (S) and resistance (R) by averaging the previous trading period's high, low, and close prices. P = (H + L + C) / 3 S1 = (2 * P) - H S2 = P - (H - L) R1 = (2 * P) - L R2 = P + (H -L) Although they are popular among traders, they can produce false signals and lead to incorrect trades in ranging markets and during periods of high volatility. Woodie’s Pivot Points Woodie's pivots are similar to standard pivots but include a slight modification to the calculation. In Woodie's method, the close price is assigned more weight. P = (H + L + 2 * C) / 4 R1 = (2 * P) - L R2 = P + H - L S1 = (2 * P) - H S2 = P - H + L However, their extra sensitivity can make them less reliable during choppy markets or when the price lacks a clear direction. Camarilla Pivot Points Camarilla pivots use a set formula to generate eight levels: four support and four resistance. They are based on the previous day’s close and range and multiplied by a certain multiplier. The inner levels (R3 and S3) often act as reversal zones, while R4 and S4 are watched for breakouts. Still, in trending markets, the reversals can fail frequently. R4 = C + (H - L) x 1.5 R3 = C + (H - L) x 1.25 R2 = C + (H - L) x 1.1666 R1 = C + (H - L) x 1.0833 P = (High + Low + Close) / 3 S1 = C - (H - L) x 1.0833 S2 = C - (H - L) x 1.1666 S3 = C - (H - L) x 1.25 S4 = C - (H - L) x 1.5 Fibonacci Pivot Points Fibonacci pivot points are based on the Fibonacci sequence, a popular mathematical concept in technical analysis. They are calculated in the same way as the standard indicator. However, the levels of support and resistance are determined by including the Fibonacci sequence with a close monitoring of the 38.2% and 61.8% retracement levels as the primary price points. P = (High + Low + Close) / 3 S1 = P - (0.382 * (H - L)) S2 = P - (0.618 * (H - L)) R1 = P + (0.382 * (H - L)) R2 = P + (0.618 * (H - L)) Despite their popularity, Fibonacci pivots can become less reliable when the price reacts to other fundamental drivers. Trading with the Pivot Points Although every trader develops their own trading approach, there are common rules of pivot point trading that are expected to improve their effectiveness. Day Trading Day trading with pivot points is usually implemented for hourly and shorter intraday timeframes. As pivot levels are updated daily and calculated on the previous day's high, low, and close prices, this allows traders to react promptly to market changes and adjust their strategies. Some traders prefer Camarilla pivots as their calculation takes into account the volatility of the previous trading period to produce pivot levels closer to the current price. Medium-Term Trading When looking at a medium-term analysis, weekly pivot levels are added to four-hour and daily charts. These are calculated using the previous week's high, low, and close prices, which remain unchanged until the start of the next week. Long-Term Trading For longer-term analysis, traders use monthly pivots on weekly charts. These levels, gathered from the previous month's data, offer a broader picture of market trends and price movements over time. Pivot Point Trading Strategies The pivot points indicator is typically used in two ways – breakout and reversal trading. Breakout Trading Strategy The breakout approach seeks to take advantage of market momentum by entering trades when prices break above or below significant levels of support and resistance. - Bullish Breakout. When levels P and R1 are broken, and the price closes above either, it’s more likely a rise will occur. - Bearish Breakout. When levels P and S1 are broken, and the price closes below either, it’s more likely the price fall will occur. Strong momentum and high volume are two critical factors needed for a solid price movement in both cases. Trading Conditions If a breakout is confirmed, traders enter a trade in the breakout direction. A take-profit target might be placed at the next pivot level. A stop-loss level can be placed beyond the previous level or calculated according to a risk/reward ratio. Traders continuously monitor their trades and adjust their stop-loss levels to lock in potential returns if prices move in their favour. Reversal Trading Strategy The reversal strategy seeks to take advantage of a slowdown in market momentum by entering trades when prices stall at significant levels of support or resistance. - Bullish Reversal. When levels S1 and S2 are not broken and the price stalls above either, a reversal is more likely to occur. - Bearish Reversal. When levels R1 and R2 are not broken and the price stalls below either, a reversal is expected to happen. Note: Reversals are always confirmed by another indicator or a chart pattern. Trading Conditions If a reversal is confirmed, traders consider entering a trade in its direction. The next level may be a take-profit target, which might be trailed to the next level if the market conditions signal a continuation of a price move. A stop-loss level is typically placed below a swing low or above a swing high, depending on the trade direction. Pivot Points and Other Indicators While pivots show where the price may reverse, there’s nothing to say a market won’t trade through these areas. Therefore, traders typically pair them with other technical indicators and patterns. Candlestick and Chart Patterns Traders often combine levels with specific reversal candlestick formations, like three black crows/three white soldiers or engulfing patterns, to confirm a change in market movements. For example, a bullish engulfing candle forming at S1 could reinforce the idea of a reversal at that level. Moving Averages When a pivot aligns with a major moving average, e.g. the 50-period or 200-period EMA, it strengthens the area. As moving averages act as dynamic support and resistance levels, an overlap can signal a strong area where a reversal might occur. RSI and Stochastic Oscillator Momentum indicators like RSI or Stochastic help judge whether the price is likely to bounce or break through a pivot. If it hits support and RSI is oversold, that adds conviction. But if momentum is still strong in one direction, it might get ignored. Considerations Even with strong confluence, these combinations can fail. Markets don’t always respect technical alignment, especially around data releases or sharp movements in sentiment. For instance, in stocks, pivot points may be ignored if an earnings release strongly beats analyst estimates. Instead, they are believed to work when treated as one piece of a broader technical framework. Limitations Pivot points are widely used, but like any tool, they have flaws. They’re based purely on past price data, so they don’t account for news, sentiment shifts, or broader market context. - False signals in ranging markets: The price often oscillates around pivot zones in markets without a clear direction, meaning setups might not follow through. - Less reliable during strong trends: In trending conditions, the price can blow past several levels without reacting. - No built-in volatility filter: The points don’t adapt to changing volatility, so levels might be too close or too far apart to be useful. - Lag in real-time shifts: Since pivots are pre-calculated, they don’t adjust mid-session as new data emerges. Final Thoughts Pivot points are widely used in stock trading as well as in commodity, cryptocurrency*, and currency markets. While they can be useful tools, their limitations cannot be overlooked. It is essential to conduct a comprehensive analysis and confirm the indicator signals with fundamental and technical analysis tools. FAQ What Is a Pivot Point in Trading? The pivot point meaning refers to a technical analysis tool used to identify potential support and resistance levels. It’s calculated using the previous day’s high, low, and close prices, and helps traders find areas where the price may react during the current session. What Is the Best Indicator for Pivot Points? There isn’t one best indicator, but traders often pair pivot points with moving averages, RSI, or candlestick patterns to confirm a potential reversal. The most effective setup usually depends on the strategy and market conditions. What Are the Pivot Points’ R1, R2, and R3? R1, R2, and R3 are resistance levels above the central point. They represent increasingly stronger potential resistance zones where the price may stall or reverse. Which Is Better, Fibonacci or Camarilla? Fibonacci offers wider levels based on retracement ratios, useful in trending markets. Camarilla focuses on tighter reversal zones, which are mostly used for intraday strategies. Each suits different trading styles; neither is objectively better. *Important: At FXOpen UK, Cryptocurrency trading via CFDs is only available to our Professional clients. They are not available for trading by Retail clients. To find out more information about how this may affect you, please get in touch with our team. This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Education
by FXOpen
1
Options Trading Strategies: From Simple to AdvancedPart 1: The Basics of Options Before diving into strategies, let’s review the two core types of options: 1. Call Option (CE) Gives the buyer the right (but not the obligation) to buy an underlying asset at a predetermined price (strike price) within a specific time period. Bullish in nature. 2. Put Option (PE) Gives the buyer the right (but not the obligation) to sell an underlying asset at a predetermined price within a specific time period. Bearish in nature. Each option has a premium (price you pay to buy the option), and that’s the maximum loss a buyer can face. Sellers (or writers), on the other hand, receive the premium but take on higher risk. Part 2: Simple Options Strategies These are basic strategies suitable for new traders. 1. Buying a Call Option (Long Call) When to Use: If you expect the stock/index to rise significantly. Risk: Limited to the premium paid. Reward: Unlimited potential profit. Example: Stock XYZ is trading at ₹100. You buy a 105 Call Option at ₹2 premium. If stock moves to ₹115: Intrinsic Value = ₹10 Profit = ₹10 - ₹2 = ₹8 per share Why It’s Good: Cheap entry, high upside. 2. Buying a Put Option (Long Put) When to Use: If you expect the stock/index to fall. Risk: Limited to the premium paid. Reward: High if stock crashes. Example: You buy a 95 PE when stock is at ₹100, and premium is ₹3. If stock falls to ₹85: Intrinsic Value = ₹10 Profit = ₹10 - ₹3 = ₹7 per share Why It’s Good: Good for bearish bets or portfolio hedging. 3. Covered Call When to Use: You own the stock and expect neutral to moderately bullish movement. Risk: Limited upside potential. Reward: Premium + stock movement (if not called away). Example: You own 100 shares of XYZ @ ₹100. You sell 110 CE for ₹5. If stock rises to ₹110, you sell at that level and keep ₹5 premium. If it stays below ₹110, you keep the shares + premium. Why It’s Good: Generates income from stocks you hold. 4. Protective Put When to Use: You own a stock and want downside protection. Risk: Limited downside. Reward: Unlimited upside. Example: Own 100 shares of XYZ @ ₹100. Buy a 95 PE at ₹3. If stock drops to ₹85, your put becomes worth ₹10, offsetting losses. Why It’s Good: Acts like insurance on your holdings. Part 3: Intermediate Strategies Once you’re comfortable with buying/selling calls and puts, it’s time to explore neutral and range-bound strategies. 5. Bull Call Spread When to Use: You expect a moderate rise in the stock/index. Risk: Limited. Reward: Limited. Structure: Buy 100 CE at ₹5 Sell 110 CE at ₹2 Net Cost: ₹3 Max Profit: ₹10 - ₹3 = ₹7 Max Loss: ₹3 Why It’s Good: Lower cost than buying a call outright. Part 4: Risk Management Tips Never deploy a strategy you don’t understand. Use stop-loss and position sizing to avoid blowing up capital. Be aware of Greeks (Delta, Theta, Vega) — they drive profits/losses. Avoid naked options selling unless you have enough margin and experience. Always review IV (Implied Volatility) before placing straddles or condors. Understand expiry effects — options lose value faster as expiry nears. Part 5: Real-Life Example Let’s say Nifty is trading at 22,000. You expect no major movement till expiry. You execute an Iron Condor: Sell 22100 CE at ₹100 Buy 22300 CE at ₹40 Sell 21900 PE at ₹90 Buy 21700 PE at ₹30 Net Credit = ₹100 - ₹40 + ₹90 - ₹30 = ₹120 Max Loss = Spread width (200) - Net Credit = ₹80 If Nifty stays between 21900 and 22100 — all options expire worthless and you earn full ₹120. Conclusion Options trading is like a chess game — it's not only about direction, but also timing, volatility, and strategy structure. Simple strategies like buying calls and puts are perfect for starters, but intermediate and advanced strategies allow you to profit in any kind of market — bullish, bearish, or neutral. The key lies in choosing the right strategy for the right market condition, managing risks, and being patient. Whether you're hedging your portfolio, generating income, or speculating on big market moves, options provide the tools — but it’s your responsibility to use them wisely. If you’d like charts, payoff diagrams, or examples using live data (like Bank Nifty or stocks), let me know and I can include those too!
NSE:BANKNIFTYEducation
by TechnicalExpress
Basics of Options: Calls and PutsWhat are Options? An option is a financial contract that gives the buyer the right, but not the obligation, to buy or sell an underlying asset (like a stock or index) at a specific price, on or before a specific date. Think of it like booking a movie ticket. You reserve the right to watch a movie at a particular time and seat. But if you don’t go, it’s your choice. You lose the ticket price (premium), but you're not forced to go. Options work similarly. Options are of two basic types: Call Option Put Option Let’s break both down in detail. 1. What is a Call Option? A Call Option gives the buyer the right (but not the obligation) to buy the underlying asset at a pre-decided price (called the strike price) on or before a certain date (called the expiry date). When do traders buy a Call Option? When they believe the price of the underlying stock or index will go up in the future. Example of Call Option (Simple Case) Let’s say you are bullish on Reliance Industries stock, which is currently trading at ₹2,500. You buy a Call Option with: Strike Price: ₹2,550 Premium Paid: ₹30 per share Lot Size: 250 shares Expiry: Monthly expiry (say end of the month) You believe Reliance will go up beyond ₹2,550 soon. If it goes to ₹2,600 before expiry: Your profit per share = ₹2,600 (market price) - ₹2,550 (strike price) = ₹50 Net Profit = ₹50 - ₹30 (premium) = ₹20 per share Total Profit = ₹20 x 250 = ₹5,000 But if Reliance stays below ₹2,550, say at ₹2,500 on expiry, you won’t exercise the option. You lose only the premium (₹30 x 250 = ₹7,500). Key Terminologies in Call Options In the Money (ITM): When the stock price is above the strike price. At the Money (ATM): When the stock price is equal to the strike price. Out of the Money (OTM): When the stock price is below the strike price. 2. What is a Put Option? A Put Option gives the buyer the right (but not the obligation) to sell the underlying asset at a pre-decided price (strike price) on or before the expiry. When do traders buy a Put Option? When they believe the price of the underlying stock or index will fall in the future. Example of Put Option (Simple Case) Assume HDFC Bank is trading at ₹1,600. You are bearish and expect it to fall. You buy a Put Option with: Strike Price: ₹1,580 Premium: ₹20 per share Lot Size: 500 shares Expiry: Monthly If HDFC Bank falls to ₹1,520: You can sell at ₹1,580 even though market price is ₹1,520 Gross profit per share = ₹60 Net profit = ₹60 - ₹20 = ₹40 per share Total profit = ₹40 x 500 = ₹20,000 If HDFC stays above ₹1,580, your put expires worthless. You lose only the premium (₹10,000). Key Terminologies in Put Options In the Money (ITM): Stock price below strike price. At the Money (ATM): Stock price = strike price. Out of the Money (OTM): Stock price above strike price. Who are the Two Parties in an Option Contract? 1. Option Buyer (Holder) Pays the premium Has rights, but not obligations Can exercise the option if profitable Loss is limited to the premium paid 2. Option Seller (Writer) Receives the premium Has obligation to fulfill the contract if the buyer exercises Risk is unlimited for call writers and limited for put writers (if stock price becomes zero) Profit is limited to the premium received Difference between Call and Put Options (Summary Table) Feature Call Option Put Option Buyer’s Expectation Bullish (price will go up) Bearish (price will go down) Right Buy at strike price Sell at strike price Profit Potential Unlimited Limited (until price reaches zero) Risk (for buyer) Limited to premium Limited to premium Seller’s Role Sells call & hopes price won’t rise Sells put & hopes price won’t fall Premium and What Influences It? The premium is the price you pay to buy an option. This is influenced by: Intrinsic Value: Difference between market price and strike price Time Value: More days to expiry = higher premium Volatility: Higher the volatility = higher the premium Interest Rates and Dividends What is Strike Price and Expiry? Strike Price: The price at which you can buy (call) or sell (put) the underlying stock Expiry: The last date till which the option is valid. In India: Weekly expiry for Nifty, Bank Nifty, and FINNIFTY Monthly expiry for stocks
NSE:NIFTYEducation
by TechnicalExpress
Cycles Don’t Lie — But Which One Speaks Here ?Markets love to repeat themselves. But just because something repeats, doesn’t mean it’s predictable — or useful. Let’s break down the main types of market cycles that traders talk about, and more importantly, let’s call out their flaws. No sugarcoating. 🔹 1. Time Cycles These are based on the idea that price behaves in a similar way over specific time intervals — whether it’s 90 days, 4 years, or a custom Fibonacci count. They show up in seasonal patterns, halving cycles (like Bitcoin), or through tools like Gann, Hurst, or even basic cycle lines. The problem? – The exact timing is rarely clean. A 120-day cycle might play out in 87 days next time. – Flat, choppy markets will destroy any cycle-based setup. – Different timeframes show different "cycles," so good luck aligning them. – Most cycle tools are complicated and impractical for real-time decision making. 🔹 2. Psychological Cycles The famous emotional rollercoaster: Hope → Euphoria → Fear → Panic → Capitulation → Depression → Optimism. Every bull and bear market goes through these in some form — in theory. The problem? – It’s almost entirely subjective. Everyone sees a different phase. – You usually recognize the cycle only after it’s over. – Emotions aren’t equal across all assets — BTC retail emotions ≠ S&P500 institutional sentiment. – There’s no precise tool to measure this. You’re mixing vibes with candles. 🔹 3. Structural Cycles (e.g. Wyckoff) This one’s more about price behavior itself — accumulation, markup, distribution, markdown. The idea is that markets rotate through these four structural phases again and again. The problem? – Identifying where you are in the structure is hard in real time. – Markets don’t always follow the Wyckoff textbook. Sometimes they just... go. – It relies heavily on volume — and that doesn’t always align. – Traders love to force a structure where there isn’t one. Confirmation bias, anyone? 🔹 4. Macro Cycles Classic economic boom and bust: Expansion → Peak → Recession → Trough. These cycles move slow but shape everything — interest rates, employment, growth, and eventually, risk assets. The problem? – They’re way too slow to help short-term traders. – Good luck timing the top or bottom of the economy. – Governments and central banks constantly interfere with natural cycles. – Most macro data is lagging, so you’re reacting to history, not forecasting the future. 🔹 5. Liquidity / Volume Cycles This idea tracks capital flow: when liquidity comes in, prices rise. When it dries up, risk assets fall. Simple, right? The problem? – Volume isn’t universal. Crypto volume =/= stock volume =/= forex volume. – You can’t always track capital flow accurately, especially in OTC markets. – Low volume doesn’t always mean weakness — sometimes it’s just summer. – Volume data can be misleading, especially on shady exchanges. 🔹 6. Fractal Cycles Markets repeat — at every level. 5-minute looks like the 4-hour, which looks like the daily. Elliott wave, harmonic patterns, whatever — the idea is that patterns echo across timeframes. The problem? – Pattern recognition can be wildly subjective. – The market doesn’t always care about geometry. Sometimes it’s just noise. – By the time a pattern is “confirmed,” you missed the move. – Focusing too much on pattern symmetry makes you blind to macro/fundamentals. So after breaking all that down, let’s finally get to the chart in front of us. Let’s take a closer look and see which cycle has actually played out here — and more importantly, which one actually helped : As you can see on the chart, before every breakout above the previous all-time high, the market tends to form some sort of bottoming structure or reversal pattern. And once that structure completes, the actual breakout usually leads to a solid price pump. But here’s the key question: Which one of the cycles we talked about earlier does this actually follow? If you ask me, a professional trader will always try to use every tool available — not because any single one gives you the answer, but because combining them gets you closer to what's likely to happen. And that’s what separates a well-rounded trader from a one-dimensional one. Why do I say “one-dimensional”? Because if you insist on looking at the market through a single lens, you’re bound to make bad decisions. We’re not here to prove our personal theories — we’re here to profit from what actually happens in the market, not what we think should happen. In the chart above, we actually see a mix of all the cycles we talked about. But I’d love to hear from you as well — let’s brainstorm together. What do you see here as a trader? And what’s your take on this setup? Bottom Line Yes, markets repeat. But repetition doesn’t equal reliability. Every cycle has its use — and its blind spot. Know the difference. Use what fits your style. And don’t romanticize a model just because it looks clean on a chart from six months ago.
Education
by Kiu_Coin
When Gold Believers Flip – Uncle Jimmy, Silver & New Safe Havens💰📉 When Gold Believers Flip – Uncle Jimmy, Silver, and the New Safe Havens 🧠🔄 Let me tell you a story that says more than any chart ever could. 📜 Meet Uncle Jimmy (from Canada) . He’s not really my uncle, but out of respect, that’s what I call him. A true OG — early stockbroker, big mustache , 20+ apartments, a life built on commissions, charts, and one sacred truth: '' Gold never lies. '' He's bought gold at every dip, every crisis, every whisper of war or inflation. But now? “I’m thinking of selling gold to buy silver.” ( WHAT?! 😳👀💥) That’s it. That’s the moment. 📉 A gold maxi flipping into silver. A generational pivot. And that’s the real divergence the chart doesn’t always show. ⚖️ Macro Sentiment Rotation: 📊 Gold Sitting on crucial support. Breakout potential to $3,465+ remains — but divergences (OBV, CMF) are stacking. A breakdown? Targets stretch down to $3,000 or even $2,716. 🪙 Silver Just hit $38.14 — now eyeing the legendary $49.83 ATH from 1980. Legacy capital rotating in. Silver’s moment? (My chart says 'wait a bit'...divergences!) 💻 NASDAQ/Tech Some now call it the “new safe haven” — not because of bonds, but because of trust in corporate resilience vs. geopolitical chaos. When Nasdaq rises, silver often outperforms gold — risk appetite returns, and so does industrial metal demand. ₿ Bitcoin And then there’s Bitcoin… The safe haven that legacy minds still don’t trust. I told Uncle Jimmy to buy it at: → $4,000 → $18,000 → $45,000 → Even $70,000.... I stopped doing that at some point, he just wouldn't get it, or wouldn't make a move into the 'crypto unknown'. Respect! So...He never did. Maybe Bitcoin just became what gold once was — but for the next generation. Not for Big Jimmy. 🧠 What to Watch: Sentiment is shifting Safe havens are evolving Charts show structure — but stories show psychology Whether you're long metals, crypto, or tech — the key is knowing when beliefs break and rotations begin. Watch price. Listen to sentiment. And never underestimate Uncle Jimmy. What would you tell Jimmy today if he was your uncle? Let me know below! One Love, The FX PROFESSOR 💙 Disclosure: I am happy to be part of the Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis. Awesome broker, where the trader really comes first! 🌟🤝📈
TRADENATIONSB:XAGUSDEducation
by FX_Professor
5
Understanding Wedge Patterns - A Real Bitcoin Case Study🎓📊 Understanding Wedge Patterns - A Real Bitcoin Case Study 🧠📈 Hi everyone, FXPROFESSOR here 👨‍🏫 From this moment forward, I will no longer be posting targets or trade setups here on TradingView. Instead, I’ll be focusing 100% on education only for here in Tradinfview. Why? Because over time I’ve learned that even when traders receive the right charts, most still struggle to trade them effectively. So, from now on, FX Professor Crypto content here will be strictly educational — designed to teach you how to read and react to the markets like a professional. Unfortunately I cannot be posting on Tradingview frequent updates like I do all day. Education is always better for you guys. And i am very happy to share here with you what matters the most. 🧩 In today’s post, we dive into one of the most misunderstood formations: the wedge pattern. Most resources show wedges breaking cleanly up or down — but real price action is messier. 🎥 I recorded a video a few days ago showing exactly how BTC respected a wedge formation. ⚠️ Note: Unfortunately, TradingView doesn’t play the audio of that clip — apologies that you can’t hear the live commentary — but the visuals are clear enough to follow the logic. (there is no advertising of any kind on the video so i hope i don't get banned again - i did make a mistake the last time and will avoid it-the community here is awesome and needs to stay clean and within the rules of TV). Here’s what happened: 🔸 A clean wedge formed over several days 🔸 We anticipated a fake move to the downside, grabbing liquidity 🔸 BTC rebounded off support around a level marked in advance 🔸 Then price re-entered the wedge, flipping support into resistance The lesson? 📉 Often price will exit the wedge in the wrong direction first — trapping retail traders — before making the real move. This is a classic liquidity trap strategy, exercised by the 'market'. 💡 Remember: Wedges often compress price until it "runs out of space" The initial breakout is often a trap The true move tends to come after liquidity is taken The timing of the 'exit' has a lot to do with the direction. In the future we will cover more examples so pay attention. I stayed long throughout this move because the overall market context remained bullish — and patience paid off. Let this be a reminder: it’s not about guessing the direction — it’s about understanding the mechanics. More educational breakdowns to come — keep learning, keep growing. One Love, The FX PROFESSOR 💙 Disclosure: I am happy to be part of the Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis. Awesome broker, where the trader really comes first! 🌟🤝📈
Education
by FX_Professor
2
Options Blueprint Series [Intermediate]: Gold Triangle Trap PlayGold’s Volatility Decline Meets a Classic Chart Setup Gold Futures have been steadily declining after piercing a Rising Wedge on June 20. Now, the market structure reveals the formation of a Triangle pattern nearing its apex — a point often associated with imminent breakouts. While this setup typically signals a continuation or reversal, the direction remains uncertain, and the conflict grows when juxtaposed with the longer-term bullish trajectory Gold has displayed since 2022. The resulting dilemma for traders is clear: follow the short-term bearish patterns, or respect the dominant uptrend? In situations like these, a non-directional approach may help tackle the uncertainty while defining the risk. This is where a Long Strangle options strategy becomes highly relevant.   Low Volatility Sets the Stage for an Options Play According to the CME Group’s CVOL Index, Gold’s implied volatility currently trades near the bottom of its 1-year range — hovering just above 14.32, with a 12-month high around 27.80. Historically, such low readings in implied volatility are uncommon and often precede sharp price movements. For options traders, this backdrop suggests one thing: options are potentially underpriced. Additionally, an IV analysis on the December options chain reveals even more favorable pricing conditions for longer-dated expirations. This creates a compelling opportunity to position using a strategy that benefits from volatility expansion and directional movement. Structuring the Long Strangle on Gold Futures A Long Strangle involves buying an Out-of-the-Money (OTM) Call and an OTM Put with the same expiration. The trader benefits if the underlying asset makes a sizable move in either direction before expiration — ideal for a breakout scenario from a compressing Triangle pattern. In this case, the trade setup uses: Long 3345 Put (Oct 28 expiration) Long 3440 Call (Oct 28 expiration) With Gold Futures (Futures December Expiration) currently trading near $3,392.5, this strangle places both legs approximately 45–50 points away from the current price. The total cost of the strangle is 173.73 points, which defines the maximum risk on the trade. This structure allows participation in a directional move while remaining neutral on which direction that move may be. Technical Backdrop and Support Zones The confluence of chart patterns adds weight to this setup. The initial breakdown from the Rising Wedge in June signaled weakness, and now the Triangle’s potential imminent resolution may extend that move. However, technical traders must remain alert to a false breakdown scenario — especially in trending assets like Gold. Buy Orders below current price levels show significant buying interest near 3,037.9 (UFO Support), suggesting that if price drops, it may find support and rebound sharply. This adds further justification for a Long Strangle — the market may fall quickly toward that zone or fail and reverse just as violently. Gold Futures and Micro Gold Futures Contract Specs and Margin Details Understanding the product’s specifications is crucial before engaging in any options strategy: 🔸 Gold Futures (GC) Contract Size: 100 troy ounces Tick Size: 0.10 = $10 per tick Initial Margin: ~$15,000 (varies by broker and volatility) 🔸 Micro Gold Futures (MGC) Contract Size: 10 troy ounces Tick Size: 0.10 = $1 per tick Initial Margin: ~$1,500 The options strategy discussed here is based on the standard Gold Futures (GC), but micro-sized versions could be explored by traders with lower capital exposure preferences.   The Trade Plan: Long Strangle on Gold Futures Here's how the trade comes together: Strategy: Long Strangle using Gold Futures options Direction: Non-directional Instruments: Buy 3440 Call (Oct 28) Buy 3345 Put (Oct 28) Premium Paid: $173.73 (per full-size GC contract) Max Risk: Limited to premium paid Breakeven Points on Expiration: Upper Breakeven: 3440 + 1.7373 = 3613.73 Lower Breakeven: 3345 – 1.7373 = 3171.27 Reward Potential: Unlimited above breakeven on the upside, substantial below breakeven on the downside R/R Profile: Defined risk, asymmetric potential reward This setup thrives on movement. Whether Gold rallies or plunges, the trader benefits if price breaks and sustains beyond breakeven levels by expiration. Risk Management Matters More Than Ever The strength of a Long Strangle lies in its predefined risk and unlimited reward potential, but that doesn’t mean the position is immune to pitfalls. Movement is key — and time decay (theta) begins to erode the premium paid with each passing day. Here are a few key considerations: Stop-loss is optional, as max loss is predefined. Precise entry timing increases the likelihood of capturing breakout moves before theta becomes too damaging. Same for exit. Strike selection should always balance affordability and distance to breakeven. Avoid overexposure, especially in low volatility environments that can lull traders into overtrading due to the potentially “cheap” options. Using strategies like this within a broader portfolio should always come with well-structured risk limits and position sizing protocols. When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com - This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies. General Disclaimer: The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
COMEX:GC1!Education
by traddictiv
Why Your Chart Might Be Lying to You And (How to Fix It) !Hello Traders 🐺 Ever clicked the “Log” button on your chart and suddenly everything looked different? Yeah, you’re not alone... Most traders ignore it. But understanding the difference between a Linear and Logarithmic chart can literally change how you see price action — especially if you’re into long-term moves or trading volatile markets like crypto. Let’s break it down real simple 👇 🔹 Linear Chart (a.k.a. the default) This is what most charts use by default. It measures price change in absolute terms. Meaning: the distance from $10 to $20 is exactly the same as from $20 to $30 — because in both cases, price moved $10. 🧠 Sounds fair, right? Not always. Here's why... Let’s say a stock goes from $1 to $2 — that’s a 100% gain. But if it goes from $100 to $101 — that’s just 1%. ✅ Linear Chart – Pros Simple and easy to read Good for short-term price action Better for assets with small price ranges Familiar to most beginners ❌ Linear Chart – Cons Misleading in long-term charts Distorts large percentage moves Trendlines become unreliable over time Doesn’t reflect real growth in % terms 🔹 Logarithmic Chart (Log Scale) This one shows percentage-based price movement. Now, going from $10 to $20 (100% gain) and going from $100 to $200 (also 100% gain) look exactly the same on the chart — which actually makes more sense when analyzing growth. It’s super useful when: ✅ You’re analyzing big moves over time ✅ You want to draw accurate trendlines in long-term charts ✅ You're dealing with assets that grew 5x, 10x or more ✅ You care about % gains instead of raw price ❌ Log Chart – Cons Less intuitive for beginners Not useful for low-volatility assets Small price moves may look insignificant here is an example of the same chart but in the Log Scale : As you can see on the chart above there is huge difference in accuracy when you use Log scale for the high volatile asset such as BTC specially in the long term movements . 🆚 So, When Should You Use Each One? Situation Use Linear Use Log Small price changes ✅ ❌ Day trading / scalping ✅ ❌ Long-term analysis ❌ ✅ Parabolic or exponential moves ❌ ✅ Drawing long trendlines ❌ ✅ Final Thoughts If your chart looks weird when you zoom out… If your trendlines don’t quite fit anymore… Or if you’re analyzing something that went 10x… 🔁 Try switching to Log scale — it might just clean up the noise. Small toggle. Big difference. And also remember our golden rule : 🐺 Discipline is rarely enjoyable , but almost always profitable. 🐺 🐺 KIU_COIN 🐺
BITSTAMP:BTCUSDEducation
by Kiu_Coin
2
Time to Wait and Watch **"The $133K zone remains Bitcoin’s key resistance level.** If Bitcoin fails to break this resistance for any reason and forms a **reversal candle** in this area, I expect a **correction phase** to begin, with the market entering **panic sell mode.** **First support** lies at **$110K.** Further support levels are **$100K, $92K, and $88K** respectively. If the price drops to the **$74K zone**, it’s time to **sell everything you’ve got** (yes, even your kidneys!) and **buy Bitcoin.** However, if **$133K is broken to the upside**, we’re heading for **$140K, $150K, and $170K**… and **then** the real **panic selling** begins."
BITSTAMP:BTCUSDEducation
by Victor_79
Why To Draw Before You Trade ?Hello fellow traders and respected members of the trading community, In a fast paced market dominated by automation and algorithms, we often forget the value of simply picking up a tool and drawing on our charts. Let’s revisit why this fundamental habit still holds the power to sharpen our edge and elevate our decision-making. Why We Should Draw and Trade? Turning Charts Into Clarity Introduction-: In an age of auto-generated indicators, black-box algorithms, and AI-driven signals, many traders are drifting away from one of the most fundamental trading tools: manual chart drawing. But what if the very act of drawing is not just an old habit—but a powerful trading edge? This publication explores why actively drawing on charts and trading based on visual context can elevate your market understanding and execution like nothing else. 1. What Does It Mean to “Draw and Trade? Drawing isn’t just technical analysis it’s interactive thinking. When you draw, you're mapping the structure of the market using tools like Trendlines Support & Resistance zones Chart Patterns (Head & Shoulders, Flags, Triangles, etc.) Supply & Demand levels Gaps, Fibonacci levels, and more Once the chart is marked, you’re no longer entering trades blindly you’re entering with context, clarity, and confidence. 2. The Psychology Behind Drawing Manual drawing engages your focus, discipline, and decision-making. You don’t just predict, you process and It forces you to slow down helping reduce impulsive trades. Drawing anchors your emotions and keeps you mindful. The act of drawing becomes a psychological filter—helping you trade from structure, not stress. 3. Why It Beats Indicator Only Trading? Indicators are reactive. Drawing is proactive. Here’s the difference: Indicators show what already happened Drawing lets you prepare for what could happen You learn to-: Anticipate breakouts, fakeouts, and reversals, Understand market structure and Develop your own strategy not depend on someone else's signal. In short you become the strategist, not just a follower. 4. The “Chart Time” Advantage Just like pilots need flight hours, traders need chart hours. Drawing charts manually gives you those hours. You start to see patterns that repeat and notice behavior shifts before they show on indicators. Build a visual memory of how the market moves and It’s this visual experience that separates analysts from traders. 5. Real-World Edge: Case Studies Wyckoff Distribution: Mapping the structure—BC, AR, ST, UT, LPSY—helps anticipate smart money exits. Gap Zones: Marking an old breakaway gap can help predict future rejection or support Demand Zones + Fib Confluence: Drawing reveals high-probability reversal zones most indicators miss Each drawing becomes a trade-ready story with logic and risk control. 6. From Drawing to Discipline Drawing is not just prep it’s planning. You trade with a clear plan and pre-identified entry/exit zones this reduced emotional interference and It becomes your personal visual rulebook. No noise no randomness just structure driven action. 7. Final Thoughts: The Trader’s Mind vs. The Machine Yes, AI and indicators are useful. But your most powerful edge? Your mind. Your eyes. Your experience sharpened through drawing. If you want to evolve from a reactive trader to a consistent performer, here’s the golden rule: Stop watching. Start drawing. Trade what you see, not what you hope. I hope you will like this post, Thanks for giving your valuable time for reading. Regards- Amit
NASDAQ:NVDAEducation
by AMIT-RAJAN
1
The Pullback Panic? Your Whole Plan Dies?!!!!!One red candle is all it takes to destroy your entire plan. Why do we panic so fast? Why do we exit too early before a rally? And worse: why do we FOMO back in at the worst possible time? Hello✌️ Spend 3 minutes ⏰ reading this educational material. 🎯 Analytical Insight on Dogecoin: BINANCE:DOGEUSDT is approaching the key psychological level of 0.20, which also aligns with a strong daily support and the final Fibonacci retracement zone 🧭. Despite recent volatility, it continues to hold its mid-range Fib level, suggesting potential accumulation. If this support holds, a rebound toward the 0.30 resistance — a move of around 27% remains on the table 🎯. Now , let's dive into the educational section, 🧠 The Victim Mindset in Crypto Markets Here’s the uncomfortable truth. Most traders believe they’re making rational decisions but in reality, they’re reacting emotionally to past pain. One bad experience during a correction makes us fear all pullbacks. Missing one big rally creates constant FOMO. We can’t handle drawdowns but we accept buying tops again and again. It’s not just you. This is how most retail traders operate and whales know it. 🐳 How Whales Profit From Our Fear Whales never buy during hype. They buy during fear. Mini pullbacks, shakeouts and false breakdowns are designed for one thing. To make you exit so they can enter. A red candle, a small wick, maybe a fake support break. We sell out of fear, they buy the dip. We FOMO back in too late. Pullbacks are not just price moves. They are psychological traps. 📈 How to Break This Cycle You don’t need to predict the future. You need to understand yourself. Ask if this correction is technical or emotional. Use confirmation from volume, OI and divergence. Enter after traps, not inside them. Question your feelings before every move. You are not trading the chart. You’re trading your mind reacting to the chart. 📊 TradingView Tools to Escape the Fear Greed Cycle TradingView gives you access to several practical indicators that can help protect your capital from emotional decision-making. 🔹 Fear and Greed Index (Crypto) Simple but powerful. When the index drops below 30, most traders are in panic mode. That is exactly where whales accumulate, while we run away. 🔹 Open Interest Heatmaps When open interest rises but price stays flat, it often signals an upcoming shakeout. One scary-looking red candle and the weak hands are gone. 🔹 Volume Profile and VPVR Perfect for distinguishing between healthy corrections and manipulative dumps. If price pulls back but buying volume remains strong, it's not a real sell-off. It’s a trap. 🔹 Divergence Indicators like MACD or RSI If RSI rises during a pullback, there’s a hidden bullish divergence. Exiting may be the worst thing to do. 🔹 Liquidity Maps These show where stop losses and liquidation clusters are located. Often before any major move up, the market takes a detour to liquidate these levels. Use these tools to stop reacting emotionally and start trading rationally. 📍 Final Thoughts Small corrections are not the enemy. Your emotional reaction to them is the real threat. Before you panic-exit, ask yourself if this fear is justified or just mental conditioning. The market always gives second chances but we rarely wait for them. ✨ 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
13
The Edge Of The Fork - The Joker In Your PocketWOW! \ \ First of all, I want to say THANK YOU for all the boosts, follows, and comments. You guys & gals give me the energy to continue this journey with you.\ \ Today, I want to show you that what we’ve learned with horizontal lines can also be applied to "Medianlines," or Forks. Listen, I don’t want you to blow your brain with all the rules. Not at the beginning of this journey, and not later on either. Don’t ask yourself: * when to use which Fork * which swing to measure * when to trade * where to set your stop * what if... bla bla bla That’s not fun — that’s stress. I don’t like stress — nobody does. So let’s just chill and have fun here. That’s my personal reason for doing all this Trading thing. I want to have fun — the money will take care of itself, just like the destination of a trail takes care of itself, as long as I keep putting one foot in front of the other. And that’s simple, right? So let’s do it exactly the same way. Just simple steps, connecting some dots, and BAM! — You’re there before you even know it §8-) \ Let’s jump to the chart:\ Today, you’ll find out why Medianlines/Forks are a cousin of the horizontal Channel — but NOT the same. Where are they different? Forks are different because they’re capable of projecting the most probable path of price. And that’s a HUGE difference. Yes, you can apply the full rule set of Forks to a horizontal Channel. But the Channel CANNOT project the most probable path of price. I hear you, I hear you: "No one and nothing can foresee the future. How is it even possible that Forks can?" \ Here’s why:\ There’s a thing called "Statistical Importance." And it means that if something happens very often in the same way, we have a higher chance of seeing the same behavior again in the future. And that’s what the inventor, Allan Andrews, discovered — and he created the rules around his findings. \ A high probability that price will move in the direction of the projected path, as long as it stays within the boundaries of the Medianlines/Fork.\ That’s the whole "magic" behind Medianlines/Forks. And the same applies to the "Behavior of Price" within and around Medianlines. That’s really all there is to it. Look at the chart and compare the Channel and the Fork: 1. Price reaches the Centerline about 80% of the time 2. HAGOPIAN → price goes farther in the opposite direction than where it came from 3. HAGOPIAN’s rule fulfilled 4. Price reaches the Centerline again 5. Price reaches the other extreme 6. Price reaches the Centerline about 80% of the time You’ll see the same behavior inside the Fork! That’s beautiful, isn’t it? §8-) And here’s a little Joker in your pocket — if you know the difference between the Channel and the Forks! Do you know what it is? Yep! You’d automatically know the direction to trade — giving you another 10% edge right out of the box — LONG TRADES ONLY. Because the Fork projects the most probable path of price to the upside, not down. That's all folks §8-) Like this lesson? With a simple boost and/or a little comment, you load my Battery so I can continue my next step on the trail with you. Thank you for spending your time with me §8-)
COMEX:GC1!Education
by HowToChart
Trading Divergences With Wedges in ForexTrading Divergences With Wedges in Forex Divergence trading in forex is a powerful technique for analysing market movements, as is observing rising and falling wedges. This article explores the synergy between divergence trading and wedges in forex, offering insights into how traders can leverage these signals. From the basics to advanced strategies, learn how you could utilise this approach effectively, potentially enhancing your trading skills in the dynamic forex market. Understanding Divergences In forex trading, the concept of divergence plays a pivotal role in identifying potential market shifts. A divergence in forex, meaning a situation where price action and a technical indicator like the Relative Strength Index (RSI) or Moving Average Convergence Divergence (MACD) move in opposite directions, often signals a weakening trend. This discrepancy is a valuable tool in divergence chart trading, as it may indicate a possible reversal or continuation of the current trend. There are two primary types of divergence in forex—regular and hidden. Regular divergence occurs when the price makes higher highs or lower lows while the indicator does the opposite, often signalling a reversal. Hidden divergence, on the other hand, happens when the price makes lower highs or higher lows while the indicator shows higher highs or lower lows, typically suggesting a continuation of the current trend. Trading Rising and Falling Wedges Rising and falling wedges are significant patterns in forex trading, often signalling potential trend reversals. A rising wedge, formed by converging upward trendlines, often indicates a bearish reversal if it appears in an uptrend. Conversely, a falling wedge, characterised by converging downward trendlines, typically reflects a bullish reversal if it occurs in a downtrend. Traders often look for a breakout from these patterns as a signal to enter trades. For rising wedges, a downward breakout can be seen as a sell signal, while an upward breakout from a falling wedge is often interpreted as a buy signal. When combined with divergences, this chart pattern can add confirmation and precede strong movements. Best Practices for Trading Divergences Trading divergence patterns in forex requires a keen eye for detail and a disciplined, holistic approach. Here are key practices for effective trading: - Comprehensive Analysis: Before trading on divergence and wedges, be sure to analyse overall market conditions. - Selecting the Right Indicator: Choose a forex divergence indicator that suits your trading style. Common choices include RSI, MACD, and Stochastic. - Confirmation Is Key: It’s best to watch for additional confirmation from price action or other technical tools before entering a trade. - Risk Management: Traders always set stop-loss orders to manage risk effectively. Divergence trading isn't foolproof; protecting your capital is crucial. - Patience in Entry and Exit: Be patient as the divergence develops and confirm with your chosen indicators before entering or exiting a trade. Strategy 1: RSI and Wedge Divergence Traders focus on regular divergence patterns when the RSI is above 70 (overbought) or below 30 (oversold), combined with a rising or falling wedge pattern. The strategy hinges on identifying highs or lows within these RSI extremes. It's not crucial if the RSI remains consistently overbought or oversold, or if it fluctuates in and out of these zones. Entry - Traders may observe a regular divergence where both the price highs/lows and RSI readings are above 70 or below 30. - After the formation of a lower high (in an overbought zone) or a higher low (in an oversold zone) in the RSI, traders typically watch as the RSI crosses back below 70 or above 30. This is accompanied by a breakout from a rising or falling wedge, acting as a potential signal to enter. Stop Loss - Stop losses might be set just beyond the high or low of the wedge. Take Profit - Profit targets may be established at suitable support/resistance levels. - Another potential approach is to exit when the RSI crosses back into the opposite overbought/oversold territory. Strategy 2: MACD and Wedge Divergence Regarded as one of the best divergence trading strategies, MACD divergence focuses on the discrepancy between price action and the MACD histogram. The strategy is particularly potent when combined with a rising or falling wedge pattern in price. Entry - Traders typically observe for the MACD histogram to diverge from the price. This divergence manifests as the price reaching new highs or lows while the MACD histogram fails to do the same. - The strategy involves waiting for the MACD signal line to cross over the MACD line in the direction of the anticipated reversal. This crossover should coincide with a breakout from the rising or falling wedge. - After these conditions are met, traders may consider entering a trade in anticipation of a trend reversal. Stop Loss - Stop losses may be set beyond the high or low of the wedge, which may help traders manage risk by identifying a clear exit point if the anticipated reversal does not materialise. Take Profit - Profit targets might be established at nearby support or resistance levels, allowing traders to capitalise on the expected move while managing potential downside. Strategy 3: Stochastic and Wedge Divergence Stochastic divergence is a key technique for divergence day trading in forex, especially useful for identifying potential trend reversals. This strategy typically employs the Stochastic Oscillator with settings of 14, 3, 3. Entry - Traders may look for divergence scenarios where the Stochastic readings are above 80 or below 20, mirroring the RSI approach. - This divergence is observed in conjunction with price action, forming a rising or falling wedge. - Entry may be considered following a breakout from the wedge, which signals a potential shift in market direction. Stop Loss - Setting stop losses just beyond the high or low of the wedge might be an effective approach. Take Profit - Profit targets may be set at key support/resistance levels. The Bottom Line Divergence trading, coupled with the analysis of rising and falling wedges, offers a comprehensive approach to navigating the forex market. By integrating the discussed strategies with sound risk management and market analysis, traders may potentially enhance their ability to make informed decisions in the dynamic world of forex. This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
Education
by FXOpen
8
Liquidity Sweep + FVG + RSIThis BCH/USDT 2H chart illustrates a textbook example of a liquidity sweep and reversal, backed by RSI confluence. Price repeatedly tested a horizontal resistance level, eventually triggering a breakout trap — enticing late buyers just before reversing. The false breakout swept buy-side liquidity, trapping retail longs above resistance. Immediately after, price dropped back below the key level and formed a Fair Value Gap (FVG) — a common area where smart money re-enters positions. This signaled distribution rather than continuation. Adding to the bearish confluence, RSI showed overbought conditions during the sweep, reinforcing that momentum was exhausted. Once liquidity was taken and RSI began dropping, a strong bearish move followed. 📉This setup combines multiple Smart Money Concepts: 🔁Liquidity engineering 🔁Breakout trap 🔁Fair Value Gap re-entry 🔁RSI confirmation
Education
by tradersboat
1
Your Technical Analysis Improved, But Your Account Didn't. Why?You're learning more. Your charts look cleaner. But somehow... your losses just keep getting worse? If that feels familiar, this breakdown might explain exactly why. Hello✌️ Spend 3 minutes ⏰ reading this educational material. 🎯 Analytical Insight on Solana: BINANCE:SOLUSDT is testing a key trendline and daily support that aligns with Fibonacci levels 🔍. A clear break above the psychological resistance at $210 could trigger at least a 16% rally, targeting $230 🚀. Now, let's dive into the educational section, 🧬 The Precision Trap The better your analysis gets the narrower your entries become. You start avoiding trades unless every single box is ticked. But guess what Markets don’t tick boxes. They break them. Overanalysis creates tighter stops smaller buffers and a mind that’s too afraid to pull the trigger. 💰 The Hidden Greed in Smart Trades Better analysis often brings a false sense of confidence. You expect more precision more profit. This turns into silent greed masked as logic. Suddenly you risk bigger positions because this one is obvious. But pros don't risk more when they’re more confident. They risk consistently. 💭 The Mind That Blocks Your Profits You didn’t lose because you didn’t know. You lost because you knew too much and became a slave to it. When your brain seeks confirmation not clarity it sabotages trades that were ready to work. Don't let analysis chain you to hesitation. 🔄 Analysis or Addiction Ask yourself honestly Are you using your analysis to take action or to avoid it Charts should guide you not paralyze you. If you need six signals to feel safe you’re not analyzing you’re hiding. 🧃 Every Chart Has a Bias What looks like a sell to you might be a buy to someone else. Why Perspective. Some buy the bounce others short the breakdown. So if your top-tier analysis still leads to losses maybe it's time to stop upgrading tools and start upgrading your lens. 🧨 The Overanalysis Spiral Your brain can’t juggle thirty signals. But most traders try anyway. This doesn’t make you smarter. It makes you slower more anxious and emotionally drained. Good trading isn’t about more info. It’s about clearer action. 🧱 The Mind That Won’t Let You Win The more you lean on your indicators the more you fear breaking their rules. You skip solid trades just because one tool says maybe not yet. At that point it’s not risk management. It’s dependency. Let tools guide not dominate you. 🛠️ TradingView Tools That Help Or Hurt Your Mindset It’s not about what tools you use. It’s how you use them. Here are a few tools that when used right can actually improve both your decision-making and emotional control: Session Volume and VWAP Don’t just chase setups blindly. Check price versus VWAP. Often entries you feel are great are just late reactions to intraday rebalancing. RSI and Auto Divergence Don’t focus on RSI values alone. Use divergence indicators that highlight hidden bullish or bearish signals. Many traders miss moves by ignoring the tension RSI reveals. Long Short Position Tool Try using this for mental reps. Plot fake trades. Watch how the market behaves without risking capital. Over time you’ll train your brain not just your account. These tools won’t fix your psychology but they’ll mirror it. And that’s where real change begins 🎯 Final Thoughts Great analysts don’t trade everything they understand. They understand what not to trade. If better charts aren't bringing better results stop upgrading your screen and start rewiring your mindset. ✨ 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
18
What does the future hold for Pi Network?Pi Network Coin (PI) is the native cryptocurrency of the Pi Network, a decentralized blockchain project designed to make cryptocurrency mining and usage accessible to everyday people via mobile devices. Unlike traditional cryptocurrencies like Bitcoin that rely on energy-intensive mining hardware, Pi Network allows users to mine PI coins on their smartphones using a lightweight, mobile-friendly process that does not drain battery life or require costly equipment. What Could make Pi Network Grow (Factors affecting price) Short-term price is highly volatile, influenced by token unlock schedules, exchange trading volumes, and speculative sentiment. Medium-to-long term potential depends on the speed and success of Mainnet open trading launch, exchange listings on major platforms, and real-world PI ecosystem adoption including DeFi and decentralized applications. Risks stem from regulatory uncertainties, possible high selling pressure from early miners, and slow token utility development. Positive catalysts include expanding app ecosystem, mainstream exchange listings, and growing merchant/payment acceptance. As of late July 2025, the PI price is subject to these dynamic factors, with market price hovering around $0.0006–$0.73 depending on exchange and trading pair, showing both significant upside if adoption accelerates and downside from current bearish technical pressures.
Education
by SpaceDayMarkets
People don't like the truth! Let's be honest, people don't like honesty. They prefer ideas that affirm their own beliefs. When I read articles and posts from newer traders, it's often from a place of "all in" diamond hands and the notion that things go up forever. I've been a trader for over 25 years now, and the game isn't about making a quick buck, it's about making money over and over again. This got me thinking, the issue is when you deal with a small account you require leverage, small timeframes and of course the "shit" or bust mindset. If you lose a thousand dollars, $10,000 even $100,000 - what does it matter? That's no different than a game of poker in Vegas. The idea of being 80% in drawdown, is alien to me. The idea of one trade and one win is also a crazy notion. Instead of playing with the future, there is an easier way to work. This isn't about slow and boring, it's about psychology and discipline. 10% returns on a million-dollar account isn't all that difficult. Instead of aiming for 300x returns on an alt coin (due to the account size being tiny) You can make less of a percentage gain with a larger account size. In terms of psychology - the word " HOPE " is used, way too often, it's used when you hope a stock or the price of Bitcoin goes up, it's used when you hope the position comes back in your favour, it's used when you want your 10,000 bucks to double. This isn't trading, it's gambling. The truth is, it's not the winners that make you a good trader. It's the way you deal with the losses. Once you learn proper risk management, a downtrend in a market move is a 1-2% loss coupled with a new opportunity to reverse the bias. As a disciplined trader, the game is played differently. Let's assume you don't have $100k spare - prop firms are a great option, OPM = other people's money. Remove the risk and increase the leverage, all whilst trading with discipline. The market goes through many phases, cycles and crashes. You don't always need something as catastrophic to take place, but if you are all in on a position. You need to understand that losses can be severe and long-lasting. When everyone sees an oasis in the desert, it's often a mirage. You only have to look at the Japanese lesson in 1989, when the Nikkei was unstoppable-until it wasn't. For that short space in time, everyone was a day trader, housewives to taxi drivers. Everyone's a genius in a Bull market. Then comes the crash. The recovery time on that crash? 34-years!!! I have covered several aspects of psychology here on TradingView; When it comes to trading, if you are able to keep playing. It's a worthwhile game. If you are gambling, it's a game whereby the house often wins. Right now, stocks are worth more than their earnings. Gold is up near all-time highs, crypto, indices the same. All I am saying is if you are all in. Be careful! Disclaimer This idea does not constitute as financial advice. It is for educational purposes only, our principal trader has over 25 years' experience in stocks, ETF's, and Forex. Hence each trade setup might have different hold times, entry or exit conditions, and will vary from the post/idea shared here. You can use the information from this post to make your own trading plan for the instrument discussed. Trading carries a risk; a high percentage of retail traders lose money. Please keep this in mind when entering any trade. Stay safe.
FOREXCOM:SPX500Education
by Mayfair_Ventures
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
8
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
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 HowToChart
7
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
6
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
10