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Gold GC Renko Strategy Futures MGC MicrosRENKO SET UP FOR GC (1 CONTRACT) TRADITIONAL BOX SIZE 1 CHART TIMEFRAME 1 MINUTE __________________________ REGULAR CANDLE SETUP FOR MGC (2 MICROS) 15 MIN TIMEFRAME __________________________ This strategy trades pullbacks within a trend, using two EMAs (fast/slow) to define uptrends and downtrends. It waits for a volatility “squeeze” , then looks for momentum ignition to go long, while shorts require a cross and optional band break/downtrend confirmation. Risk is handled with fixed dollar profit target and stop-loss values (converted to ticks), with exits placed immediately after entries and an automatic flat-at-session-close (New York time). Signals and risk lines are plotted.
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Golden_Axe_Strategiesの投稿
1
TEMA 20/34/55 Strategie mit Buy & SellThis indicator uses three Triple Exponential Moving Averages (TEMA) with periods 20 (green), 34 (blue), and 55 (red) to identify trend direction. A buy signal is generated when TEMA20 crosses above TEMA34 and TEMA34 crosses above TEMA55 (bullish trend start). A sell signal is generated when TEMA20 crosses below TEMA34 and TEMA34 crosses below TEMA55 (bearish trend start). The strategy enters long and short positions with configurable stop loss and take profit levels. Ideal for trend following and suitable for intraday or swing trading.
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Keulemrの投稿
D Money – EMA/TEMA Touch Strategy (Distance) What it’s trying to capture You want mean-reversion “tags” back to a moving average after price has stretched away and momentum flips: Bearish setup (short): price has been above EMA(9) for a few bars, then MACD turns bearish, and price is far enough above the EMA (by an adaptive threshold). Exit when price tags the EMA. Bullish setup (long): price has been below your chosen TEMA rail (actually an EMA of 50/100/200 you pick) for a few bars, then MACD turns bullish, and price is far enough below that TEMA. Exit when price tags that TEMA. The moving averages it uses EMA(9) — your fast “tag” for short take-profits. “TEMA line” input = one of EMA(50) / EMA(100) / EMA(200). (Labelled “Chosen TEMA” in the plot; it’s an EMA rail you pick.) When it will enter trades It requires four things per side: Short (EMA-Touch Short) MACD bearish cross on the signal bar If “Require NO MA touch on cross bar” = true, the bar’s low must be above EMA(9), so it didn’t touch EMA on the cross bar (fake-out guard). Extension/Context: you’ve had at least barsAbove consecutive closes above EMA(9) (default 3), so it’s truly stretched. Distance test: absolute % distance from price to EMA(9) must be ≥ minDistEMA_eff (an adaptive threshold; details below). Bounce filter: there was no bullish bounce off the EMA in the last bounceLookback bars (excluding the current one). If all pass and you’re inside the backtest window → strategy.entry short. Long (TEMA-Touch Long) MACD bullish cross on the signal bar With the same fake-out guard: the bar’s high must be below the chosen TEMA if the guard is on. Extension/Context: at least barsAbove consecutive closes below the chosen TEMA. Distance test: absolute % distance from price to TEMA must be ≥ minDistTEMA_eff (adaptive). Bounce filter: there was no bearish bounce off the TEMA in the last bounceLookback bars. If all pass and you’re in the window → strategy.entry long. MACD timing option: If Pure MACD Timing = ON, it only checks for the cross. If OFF (default), it also enforces “no touch on the cross bar” if that checkbox is true. That’s your “fake-out” filter. The adaptive distance threshold (the “secret sauce”) You can choose how “far enough away” is determined—per side: Fixed % Short uses Fixed: Min distance ABOVE EMA (%) Long uses Fixed: Min distance BELOW TEMA (%) Auto (ATR%) (default) Short threshold = max(floorEMA, kAtrShort × ATR%) Long threshold = max(floorTEMA, kAtrLong × ATR%) This scales distance by recent volatility, with a floor. Auto (AvgDist%) Short threshold = max(floorEMA, kAvgShort × average(|Dist to EMA|) over avgLen) Long threshold = max(floorTEMA, kAvgLong × average(|Dist to TEMA|) over avgLen) This adapts to the instrument’s typical stretch away from the rails. These become minDistEMA_eff and minDistTEMA_eff and are re-computed each bar. Fake-out / bounce logic (the “don’t get tricked” part) A touch means the bar’s high/low overlapped the MA ± a small buffer % (touchBufPct). A bounce is a touch plus a close on the “wrong” side (e.g., touch EMA and close above it on shorts = bullish bounce). The script blocks entries if a bounce happened within bounceLookback bars (excluding the current signal bar). Exits & risk Take profit: when price touches the target MA: Short TP = touch EMA(9) Long TP = touch chosen TEMA Stop loss: either ATR stop: entry ± (atrMultStop × ATR) (default ON), or Percent stop: entry × (1±stopPct%) Time stop: if timeExitBars > 0, close after that many bars if still open. Quality-of-life features Backtest window (btFrom, btTo) so you can limit evaluation. Labels on signal bars that show: MACD bucket (Small/Moderate/HUGE/Violent — based on % separation on the bar), the current absolute distance to the target MA, and the effective minimum the engine used (plus which engine mode). Data Window fields so you can audit: abs distance to EMA/TEMA, the effective min distance used on each side, ATR%, average absolute distances (for the AvgDist mode). Alerts fire when a short/long signal is confirmed. Optional debug panel to see the exact booleans & thresholds the bar had. Quick mental model Are we properly stretched away from the rail (by an adaptive threshold) and held on that side for a few bars? Did MACD flip the way we want without price already tagging the rail that bar? Have we avoided recent bounces off that rail (no fake-out)? → If yes, enter and aim for a tag back to the rail, with ATR/% stop and optional time stop. If you want, I can add a simple on-chart “rating” (0–100) similar to your Python scorer (distance beyond min, MACD bucket, extension streak) so you can visually rank signals in TradingView too.
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dareolowoniyiの投稿
Supertrend Strategy With Multi Tp & TslHello Traders, This strategy is based on the popular Supertrend indicator, which many traders use as a simple trend-following tool. The core entry logic is straightforward: Buy (Long) when the price closes above the Supertrend line. Sell (Short) when the price closes below the Supertrend line. However, trading success isn’t only about entries — proper risk management makes all the difference. That’s why this strategy includes four stop-loss methods, two take-profit types, and a trailing stop-loss system. You can customize all of these settings to create your own personalized version. 🛑 Stop-Loss Methods Tick – Uses the instrument’s smallest price increment. Ideal for tick-based markets such as Futures or Forex. Percent – Defines the stop-loss as a percentage of entry price. Commonly used in Crypto trading. ATR – Uses the Average True Range value to determine stop-loss distance. Perfect for adapting to changing market volatility. Supertrend – The stop-loss level is set at the Supertrend line value at the time of entry. 🔁 Trailing Stop-Loss & Reverse Signals Trailing SL: If enabled, the chosen stop-loss method will trail the price dynamically from the moment the position opens. Close with Reverse Signals: When activated, the current position closes and reverses on an opposite signal. If disabled, the strategy waits until the current position is closed before opening a new one. 🎯 Take-Profit Options Tick – Set a fixed take-profit level based on tick distance. Percent – Set take-profit based on a percentage change from entry. Ratio – Sets take-profit based on the entry-to-stop-loss distance × ratio value. Each take-profit method allows you to define the percentage of position to close at that level. ⚖️ Breakeven Option When Breakeven is enabled, after the first take-profit is triggered, the stop-loss automatically moves to the entry level, protecting your capital. ⚙️ Additional Settings Position Type: Choose between Long only, Short only, or Both directions. Session Filter: Trade only during specific time ranges. Activate this option and set your desired session hours (make sure to select your correct timezone). 📈 Visuals The strategy plots entry, stop-loss, and take-profit levels directly on the chart, allowing you to clearly visualize your trades and manage them effectively. Feel free to ask any questions or suggest improvements — this strategy is built for flexibility and experimentation!
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Milvettiの投稿
AlgoWay GRSIM🧭 What this strategy tries to do This strategy detects when a market move is losing strength and prepares for a potential reversal, but it waits for fresh momentum confirmation before acting. It combines: • RSI-based divergence (to spot exhaustion and potential turning points), • Impulse MACD (to verify that the new direction actually has force behind it). ________________________________________ ⚙️ When it takes trades Long (Buy): • A bullish RSI divergence appears (a clue that selling pressure is fading); • Within a short time window, the Impulse MACD turns strongly positive; • Optionally, the impulse line itself must be rising (if the Impulse Direction Filter is enabled). Short (Sell): • A bearish RSI divergence appears (buying pressure fading); • Within a short time window, the Impulse MACD turns strongly negative; • Optionally, the impulse line must be falling (if the Impulse Direction Filter is enabled). If momentum confirmation happens too late, the divergence “expires” and the signal is ignored. ________________________________________ 🧩 How entries work 1. Reversal clue: The strategy detects disagreement between price and RSI (price makes a new high/low, RSI doesn’t). That suggests a shift in underlying strength. 2. Momentum confirmation: Before entering, the Impulse MACD must agree — showing real push in the same direction. 3. Impulse direction filter (optional): When enabled, the impulse itself must accelerate (rise for longs, fall for shorts), avoiding fake signals where price diverges but momentum is still fading. 4. No stacking: It opens only one position at a time. ________________________________________ 🚪 How exits work Two main exit styles: Conservative (default): Longs close when impulse crosses below its signal line. Shorts close when impulse crosses above its signal line. ✅ Keeps trades as long as momentum agrees. Color-change (fast): Longs close immediately when impulse flips bearish. Shorts close immediately when impulse flips bullish. ⚡ Faster and more defensive. Plus: Stop Loss (%) and Take Profit (%) act as fixed-distance protective exits (set to 0 to disable either one). ________________________________________ 📊 What you’ll see on the chart A thick Impulse MACD line and thin signal line (oscillator view). Diamonds — detected bullish/bearish divergence points. Circles — where impulse crosses its signal (momentum change). A performance panel (top-right) showing Net Profit, Trades, Win Rate, Profit Factor, Pessimistic PF, and Max Drawdown. ________________________________________ 🔧 What you can tune Signal Lifetime (bars): how long a divergence remains valid. Impulse Direction Filter: ensure the impulse itself is moving in the trade’s direction. Stop Loss / Take Profit (%): risk and target in percent. Exit Style: conservative cross or faster color-change. RSI / MA / Signal Lengths: adjust responsiveness (defaults are balanced). ________________________________________ 💪 Strengths Confirms reversals using momentum direction, not just divergence. Avoids “early” signals where momentum is still fading. Works symmetrically for longs and shorts. Built-in stop/target protection. Clear, visual confirmation of all logic components. ________________________________________ ⚠️ Things to keep in mind In sideways markets, the impulse can flip often — prefer conservative exits. Too small SL/TP → constant stop-outs. Too wide SL/TP → deep drawdowns. Always test with different timeframes and markets. ________________________________________ 💡 Practical tips Start with default settings. Enable “Use Impulse Direction Filter” in trending markets, disable it in very choppy ones. Focus on Profit Factor, Win Rate, and Max Drawdown after several dozen trades. Keep SL/TP roughly aligned with typical swing size. “AlgoWay GRSIM” is a reversal-with-confirmation strategy: it spots likely turns, demands real momentum alignment (optionally verified by impulse direction), and manages exits with clear momentum cues plus built-in protective limits.
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AlgowayConnectorの投稿
Ekoparaloji Futures Cyrpto Strategy Ekoparaloji Futures Crypto Strategy - Ladder Averaging System This strategy uses a ladder position entry (pyramiding) approach and average cost reduction principle for crypto futures markets. Key Features: Dynamic ladder entry system Profit-taking mechanism based on average price Adjustable leverage support (1x-125x) Long and Short position management Optional stop-loss protection Liquidation distance tracking Advantages: ✓ Optimizes average cost during price fluctuations ✓ User-controlled risk-reward ratio ✓ Adapts to different market conditions ✓ Provides detailed visual feedback ✓ Increases profit potential through pyramiding strategy Risks: ⚠ High leverage usage increases liquidation risk ⚠ Losses can accumulate during trend continuation ⚠ Pyramiding adds capital requirements ⚠ May produce unexpected results in sideways markets ⚠ Past performance does not guarantee future results Recommended Usage: This strategy is optimized for testing particularly on 30-minute and 1-hour timeframes. It may produce different results across various crypto pairs and market conditions. Important Warning: This strategy is for educational and research purposes. Extensive testing on demo accounts is strongly recommended before using in live trading. Leveraged trading involves high risk and you can lose all your capital. 📩 Message me to test the strategy and get access. Happy Trading! 🚀
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Ekoparalojiの投稿
1
Quantum Flux Universal Strategy Summary in one paragraph Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version. Scope and intent • Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto • Timeframes. One minute to daily • Default demo used in the publication. QQQ on one hour • Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps. • What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise. • Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state. • Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols. Method overview in plain language The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction. Base measures • Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale. • Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop. • Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves. Components • Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner. • Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends. • Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response. • Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance. • Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot. Fusion rule • Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent. • The blend power input scales the driver mix. Zero means fixed spans. One means full driver control. • Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes. Signal rule • Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one. • Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one. • When polarity flips from plus to minus, the strategy closes any long and enters a short. • When flux crosses above the guide, the strategy closes any short. What you will see on the chart • White polarity plot around the zero line • A dotted reference line at zero named Zen • Green background tint for positive polarity and red background tint for negative polarity • Strategy long and short markers placed by the TradingView engine at entry and at close conditions • No table in this version to keep the visual clean and portable Inputs with guidance Setup • Price source. Default ohlc4. Stable for noisy symbols. • Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive. • Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price. Logic • Guide span. Typical range 4 to 12. A small guide smooths without eating turns. • Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing. • Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work. • Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise. • Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve. • Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak. • Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong. • Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline. • Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols. • Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs. Filters • Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends. • Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping. • Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version. Alerts • This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows. Strategy has been currently adapted for the QQQ asset with 30/60min timeframe. For other assets may require new optimization Properties visible in this publication • Initial capital 25000 • Base currency Default • Default order size method percent of equity with value 5 • Pyramiding 1 • Commission 0.05 percent • Slippage 10 ticks • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Honest limitations and failure modes • Past results do not guarantee future outcomes • Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency • Gap heavy symbols may benefit from the MAD Z normalization • Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context • Session time is the exchange time of the chart • If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference Open source reuse and credits • None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank • Method and fusion are original in construction and disclosure Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs. Strategy add on block Strategy notice Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used. Entries and exits • Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero • Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short • Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed • Tie handling. Not applicable in this version because there are no fixed stops or targets Position sizing • Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice Properties used on the published chart • Initial capital 25000 • Base currency Default • Default order size percent of equity with value 5 • Pyramiding 1 • Commission 0.05 percent • Slippage 10 ticks • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Dataset and sample size • Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour • Trade count in sample 324 on the example chart Release notes template for future updates Version 1.1. • Add alertcondition lines for long, short, and exit short • Add optional table with component readouts • Add optional stop model with a distance unit expressed as ATR or a percent of price Notes. Backward compatibility Yes. Inputs migrated Yes.
Pine Script® ストラテジー
exluxの投稿
USDJPY Fair Value Gap + Session Strategy🎯 Overview This strategy combines Fair Value Gaps (FVGs) with session-based order flow analysis, specifically optimized for USDJPY. It identifies price inefficiencies left behind by institutional order flow during high-volatility trading sessions, offering a modern alternative to traditional lagging indicators. 🔬 What Are Fair Value Gaps? Fair Value Gaps represent areas where aggressive institutional buying or selling created "gaps" in the market structure: Bullish FVG: Price moves up so aggressively that it leaves unfilled buy orders behind Bearish FVG: Price moves down so quickly that it leaves unfilled sell orders behind Research shows approximately 80% of FVGs get "filled" (price returns to the gap) within 20-60 bars, making them highly predictable trading zones. (see the generated image above) (see the generated image above) FVG Detection Logic: text // Bullish FVG: Gap between high and current low bullishFVG = low > high and high > high // Bearish FVG: Gap between low and current high bearishFVG = high < low and low < low 🌏 Session-Based Trading Why Sessions Matter for USDJPY (see the generated image above) Tokyo Session (00:00-09:00 UTC) Highest volatility during first hour (00:00-01:00 UTC) Average movement: 51-60 pips Best for breakout strategies London/NY Overlap (13:00-16:00 UTC) Maximum liquidity and institutional participation Tightest spreads and most reliable FVG formations Optimal for continuation trades Monday Premium Effect USDJPY moves 120+ pips on Mondays due to weekend positioning Enhanced FVG formation during session opens 📊 Strategy Components (see the generated image above) 1. Fair Value Gap Detection Identifies bullish and bearish FVGs automatically Age limit: FVGs expire after 20 bars to avoid stale setups Size filter: Minimum gap size to filter out noise 2. Session Filtering Tokyo Open focus: Trades during first hour of Asian session London/NY Overlap: Captures high-liquidity institutional flows Weekend gap strategy: Enhanced signals on Monday opens 3. Volume Confirmation Requires 1.5x average volume spike Confirms institutional participation Reduces false signals 4. Trend Alignment 50 EMA filter ensures trades align with higher timeframe trend Long trades above EMA, short trades below Prevents costly counter-trend trades 5. Risk Management 2:1 Risk/Reward minimum ensures profitability with 40%+ win rate Percentage-based stops adapt to USDJPY volatility (0.3% default) Configurable position sizing 🎯 Entry Conditions (see the generated image above) Long Entry (BUY) ✅ Bullish FVG detected in previous bars ✅ Price returns to FVG zone during active trading session ✅ Volume spike above 1.5x average ✅ Price above 50 EMA (trend confirmation) ✅ Bullish candle closes within FVG zone ✅ Trading during Tokyo open OR London/NY overlap Short Entry (SELL) ✅ Bearish FVG detected in previous bars ✅ Price returns to FVG zone during active trading session ✅ Volume spike above 1.5x average ✅ Price below 50 EMA (trend confirmation) ✅ Bearish candle closes within FVG zone ✅ Trading during Tokyo open OR London/NY overlap 📈 Expected Performance Backtesting Results (Based on Similar Strategies): Win Rate: 44-59% (profitable due to high R:R ratio) Average Winner: 60-90 pips during London/NY sessions Average Loser: 30-40 pips (tight stops at FVG boundaries) Risk/Reward: 2:1 minimum, often 3:1 during strong trends Best Performance: Monday Tokyo opens and Wednesday London/NY overlaps Why This Works for USDJPY: 90% correlation with US-Japan bond yield spreads High volatility provides sufficient pip movement Heavy institutional/central bank participation creates clear FVGs Consistent volatility patterns across trading sessions ⚙️ Configurable Parameters Session Settings: Trade Tokyo Session (Enable/Disable) Trade London/NY Overlap (Enable/Disable) FVG Settings: FVG Minimum Size (Filter small gaps) Maximum FVG Age (20 bars default) Show FVG Markers (Visual display) Volume Settings: Use Volume Filter (Enable/Disable) Volume Multiplier (1.5x default) Volume Average Period (20 bars) Trend Settings: Use Trend Filter (Enable/Disable) Trend EMA Period (50 default) Risk Management: Risk/Reward Ratio (2.0 default) Stop Loss Percentage (0.3% default) 🎨 Visual Indicators 🟡 Yellow Line: 50 EMA trend filter 🟢 Green Triangles: Long entry signals 🔴 Red Triangles: Short entry signals 🟢 Green Dots: Bullish FVG zones 🔴 Red Dots: Bearish FVG zones 🟦 Blue Background: Tokyo open session 🟧 Orange Background: London/NY overlap 📊 Recommended Settings Optimal Timeframes: Primary: 5-minute charts (scalping) Secondary: 15-minute charts (swing trading) Parameter Optimization: Conservative: Stop Loss 0.2%, R:R 2:1, Volume 2.0x Balanced: Stop Loss 0.3%, R:R 2:1, Volume 1.5x (default) Aggressive: Stop Loss 0.4%, R:R 1.5:1, Volume 1.2x Risk Management: Maximum 1-2% of account per trade Daily loss limit: Stop after 3-5 consecutive losses Use fixed percentage position sizing ⚠️ Important Considerations Avoid Trading During: Major news events (BOJ interventions, NFP, FOMC) Holiday periods with reduced liquidity Low volatility Asian afternoon sessions When US-Japan yield differential narrows sharply Best Practices: Limit to 2-3 trades per session maximum Always respect the 50 EMA trend filter Never risk more than planned per trade Paper trade for 2-4 weeks before live implementation Track performance by session and day of week 🚀 How to Use Add the script to your USDJPY chart Set timeframe to 5-minute or 15-minute Adjust parameters based on your risk tolerance Enable strategy alerts for automated notifications Wait for visual signals (triangles) to appear Enter trades according to your risk management rules 📚 Strategy Foundation This strategy is based on: Smart Money Concepts (SMC): Institutional order flow tracking Market Microstructure: Understanding how FVGs form in electronic trading Quantified Risk Management: Statistical edge through proper R:R ratios Session Liquidity Patterns: Exploiting predictable volatility cycles
Pine Script® ストラテジー
Stockhockの投稿
Multi-GPS (Long Only, with Alert Mode)A guided long‑only strategy with built‑in risk controls and smart alerts — your GPS for trend trading **Multi‑GPS (Long Only, with Alert Mode)** The Multi‑GPS strategy is built to help traders navigate trends with a structured, risk‑managed approach. It focuses exclusively on **long opportunities**, combining multiple moving‑average signals with layered risk controls to keep trades disciplined and consistent. Key features include: - **Dynamic trade management** with stop loss, take profit, and trailing stop options (all adjustable by percentage). - **Flexible order sizing**, allowing positions to scale as a percentage of account equity. - **Customizable moving averages** (SMA or EMA) and timeframe selection to adapt to different markets and styles. - **Integrated alerts** with multiple modes, so traders can choose between order‑based notifications, alert() calls, or both. - **Clear chart visuals**, including entry/exit markers and plotted guide lines for transparency. This strategy is designed to act like a **navigation system for trend trading** — guiding entries, managing exits, and keeping risk under control, all while maintaining a clean and intuitive charting experience. --- Would you like me to also craft a **short tagline version** (like a one‑liner hook) for this strategy, so it pairs neatly with the longer description when you publish it?
Pine Script® ストラテジー
forexrewardの投稿
Moon Phases + Blood MoonWhat it is This is a simple, time-based strategy that goes long on full moons and exits on the next new moon, while visually highlighting historically known “Blood Moon” (total lunar eclipse) dates. It’s built for exploratory testing of lunar timing effects on price, not for predictive claims. Why it’s useful / originality Most lunar scripts only mark phases. This one (1) computes lunar phases on the chart, (2) normalizes and flags Blood Moon days from a curated list, and (3) turns the phase changes into an executable strategy with clear, reproducible entry/exit rules and a configurable start date—so traders can quickly evaluate whether a lunar timing overlay adds any edge on their market/timeframe. How it works (concept) Moon phase detection: Uses Julian date conversion and standard astronomical approximations to determine the most recent phase change at each bar. The script classifies phase turns as +1 = New Moon and –1 = Full Moon, tracking the latest valid time to avoid lookahead. Blood Moon tagging: A built-in array of UTC timestamps (total lunar eclipses) is date-matched to the current session and marked as “Blood Moon” when a full moon coincides with a listed date. Signals & trades Plot circles above/below bars: New Moon (above), Full Moon (below), Blood Moon (below, red). Entry: Long at Full Moon once the bar time ≥ the user’s Start date. Exit: Close the long on the next New Moon. How to use Add to your chart (non-monthly timeframes only). Optionally adjust the Start date (default: 2001-12-31 UTC) to control the backtest window. Use the color inputs to style New Moon / Full Moon / Blood Moon markers. Evaluate performance on liquid symbols and timeframes that provide a sufficient number of phase cycles. Default / publish settings Initial capital: $10,000 (suggested) Commission: 0.05% per trade (suggested) Slippage: 1 tick (suggested) Position sizing: TradingView strategy defaults (no leverage logic is added). Timeframes: Intraday/Daily/Weekly supported. Monthly is blocked by design. Chart type: Use standard chart types only (no Heikin Ashi, Renko, Kagi, P&F, Range) for signals/backtests. Reading the chart New Moon: soft gray circle above bars. Full Moon: soft yellow circle below bars. Blood Moon (if date-matched): soft red circle below bars. The script also ensures symbol/timeframe context is visible—keep your chart clean so the markers are easy to interpret. Limitations & important notes This is a time-based heuristic. It does not forecast price and does not repaint via lookahead tricks; it avoids future leakage by anchoring to the last known phase time at each bar. No non-standard chart signals. Using non-standard charts can produce unrealistic results. Strategy properties like commission/slippage materially affect results—please set them to realistic values. Backtests should include a large sample (ideally >100 trades over many cycles) to make statistics meaningful. Past performance does not guarantee future results. Open-source reuse / credits Uses standard, public-domain techniques for Julian date conversion and lunar-phase approximations. Blood Moon dates are incorporated as a hard-coded list for convenience; you may extend or adjust this list as needed. No third-party proprietary code is reused. Changelog / versioning v1: Initial public release on Pine v6 with phase detection, Blood-Moon tagging, and a minimal long-only phase strategy.
Pine Script® ストラテジー
Investic_analyticsの投稿