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Faraz Perfect Structure XL / XS (Trend-Filtered)Faraz’s Perfect Structure XL/XS identifies premium trend continuation and reversal setups using a three-filter system: structural breakouts using dynamic swing-based support/resistance, trend confirmation via 200-EMA slope, momentum validation through RSI and MACD. Signals only trigger when all factors align, eliminating noise, chop, and false signals. Designed for traders who want clean, high-probability long (XL) and short (XS) entries.
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fsaleem03の投稿
EMA 50/200 Pullback + RSI (BTC/USDT 15m - 2 Bar Logic)I recognize that combining indicators requires clear justification on how the components interact Therefore the new scripts description will explicitly detail the strategys operational logic Objective The strategy is a Trend Following Pullback System designed for high frequency time frames 15m Synergy The EMA50 EMA200 defines the primary Trend Direction Trend Filter It then utilizes a 2 Bar Pullback Logic to find an entry point where the price has momentarily reversed against the trendline and the RSI 14 serves as a Momentum Filter RSI greater than 50 for Long RSI less than 50 for Short to minimize false signals
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nookloves26の投稿
EMA Cross Strategy v5 (30 lots) (15 min candle only)- safe flip🚀 EMA Cross Strategy v5 (30 Lots) (15 min candle only)— Safe Flip Edition Fully Automated | Fast | Reliable | Battle-tested Welcome to a clean, powerful, and automation-friendly EMA crossover system. This strategy is built for traders who want consistent trend-based entries without the risk of unwanted pyramiding or doubled positions. 🔥 How It Works This strategy uses a fast EMA (10) crossing a slow EMA (20) to detect trend shifts: Bullish Crossover → LONG (30 lots) Bearish Crossover → SHORT (30 lots) Every opposite signal safely flips the position by first closing the current trade, then opening a fresh position of exactly 30 lots. No doubling. No runaway position size. No surprises. Just clean, mechanical trend-following. 📈 Why This Strategy Stands Out Unlike basic EMA crossbots, this version: ✔ Prevents unintended pyramiding ✔ Never over-allocates capital ✔ Works perfectly with webhook-based automation ✔ Produces stable, systematic entries ✔ Executes directional flips with precision 🔍 Backtest Highlights (1-Year) (Backtests will vary by instrument/timeframe) 1,500+ trades executed Profit factor above 1.27 Strong trend performance Balanced long/short behavior No margin calls Consistent trade execution This strategy thrives in trending markets and maintains strict discipline even in choppy conditions. ⚙️ Automation Ready Designed for automated execution via webhook and API setups on supported platforms. Just connect, run, and let the bot follow the rules without hesitation. No emotions. No overtrading. No fear or greed. Pure logic.
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kulkarniabhishek38の投稿
1
Golden Cross 50/200 EMATrend-following systems are characterized by having a low win rate, yet in the right circumstances (trending markets and higher timeframes) they can deliver returns that even surpass those of systems with a high win rate. Below, I show you a simple bullish trend-following system with clear execution rules: System Rules -Long entries when the 50-period EMA crosses above the 200-period EMA. -Stop Loss (SL) placed at the lowest low of the 15 candles prior to the entry candle. -Take Profit (TP) triggered when the 50-period EMA crosses below the 200-period EMA. Risk Management -Initial capital: $10,000 -Position size: 10% of capital per trade -Commissions: 0.1% per trade Important Note: In the code, the stop loss is defined using the swing low (15 candles), but the position size is not adjusted based on the distance to the stop loss. In other words, 10% of the equity is risked on each trade, but the actual loss on the trade is not controlled by a maximum fixed percentage of the account — it depends entirely on the stop loss level. This means the loss on a single trade could be significantly higher or lower than 10% of the account equity, depending on volatility. Implementing leverage or reducing position size based on volatility is something I haven’t been able to include in the code, but it would dramatically improve the system’s performance. It would fix a consistent percentage loss per trade, preventing losses from fluctuating wildly with changes in volatility. For example, we can maintain a fixed loss percentage when volatility is low by using the following formula: Leverage = % of SL you’re willing to risk / % volatility from entry point to stop loss And when volatility is high and would exceed the fixed percentage we want to expose per trade (if the SL is hit), we could reduce the position size accordingly. Practical example: Imagine we only want to risk 15% of the position value if the stop loss is triggered on Tesla (which has high volatility), but the distance to the SL represents a potential 23.57% drop. In this case, we subtract the desired risk (15%) from the actual volatility-based loss (23.57%): 23.57% − 15% = 8.57% Now suppose we normally use $200 per trade. To calculate 8.57% of $200: 200 × (8.57 / 100) = $17.14 Then subtract that amount from the original position size: $200 − $17.14 = $182.86 In summary: If we reduce the position size to $182.86 (instead of the usual $200), even if Tesla moves 23.57% against us and hits the stop loss, we would still only lose approximately 15% of the original $200 position — exactly the risk level we defined. This way, we strictly respect our risk management rules regardless of volatility swings. I hope this clearly explains the importance of capping losses at a fixed percentage per trade. This keeps risk under control while maintaining a consistent percentage of capital invested per trade — preventing both statistical distortion of the system and the potential destruction of the account. About the code: Strategy declaration: The strategy is named 'Golden Cross 50/200 EMA'. overlay=true means it will be drawn directly on the price chart. initial_capital=10000 sets the initial capital to $10,000. default_qty_type=strategy.percent_of_equity and default_qty_value=10 means each trade uses 10% of available equity. margin_long=0 indicates no margin is used for long positions (this is likely for simulation purposes only; in real trading, margin would be required). commission_type=strategy.commission.percent and commission_value=0.1 sets a 0.1% commission per trade. Indicators: Calculates two EMAs: a 50-period EMA (ema50) and a 200-period EMA (ema200). Crossover detection: bullCross is triggered when the 50-period EMA crosses above the 200-period EMA (Golden Cross). bearCross is triggered when the 50-period EMA crosses below the 200-period EMA (Death Cross). Recent swing: swingLow calculates the lowest low of the previous 15 periods. Stop Loss: entryStopLoss is a variable initialized as na (not available) and is updated to the current swingLow value whenever a bullCross occurs. Entry and exit conditions: Entry: When a bullCross occurs, the initial stop loss is set to the current swingLow and a long position is opened. Exit on opposite signal: When a bearCross occurs, the long position is closed. Exit on stop loss: If the price falls below entryStopLoss while a position is open, the position is closed. Visualization: Both EMAs are plotted (50-period in blue, 200-period in red). Green triangles are plotted below the bar on a bullCross, and red triangles above the bar on a bearCross. A horizontal orange line is drawn that shows the stop loss level whenever a position is open. Alerts: Alerts are created for:Long entry Exit on bearish crossover (Death Cross) Exit triggered by stop loss Favorable Conditions: Tesla (45-minute timeframe) June 29, 2010 – November 17, 2025 Total net profit: $12,458.73 or +124.59% Maximum drawdown: $1,210.40 or 8.29% Total trades: 107 Winning trades: 27.10% (29/107) Profit factor: 3.141 Tesla (1-hour timeframe) June 29, 2010 – November 17, 2025 Total net profit: $7,681.83 or +76.82% Maximum drawdown: $993.36 or 7.30% Total trades: 75 Winning trades: 29.33% (22/75) Profit factor: 3.157 Netflix (45-minute timeframe) May 23, 2002 – November 17, 2025 Total net profit: $11,380.73 or +113.81% Maximum drawdown: $699.45 or 5.98% Total trades: 134 Winning trades: 36.57% (49/134) Profit factor: 2.885 Netflix (1-hour timeframe) May 23, 2002 – November 17, 2025 Total net profit: $11,689.05 or +116.89% Maximum drawdown: $844.55 or 7.24% Total trades: 107 Winning trades: 37.38% (40/107) Profit factor: 2.915 Netflix (2-hour timeframe) May 23, 2002 – November 17, 2025 Total net profit: $12,807.71 or +128.10% Maximum drawdown: $866.52 or 6.03% Total trades: 56 Winning trades: 41.07% (23/56) Profit factor: 3.891 Meta (45-minute timeframe) May 18, 2012 – November 17, 2025 Total net profit: $2,370.02 or +23.70% Maximum drawdown: $365.27 or 3.50% Total trades: 83 Winning trades: 31.33% (26/83) Profit factor: 2.419 Apple (45-minute timeframe) January 3, 2000 – November 17, 2025 Total net profit: $8,232.55 or +80.59% Maximum drawdown: $581.11 or 3.16% Total trades: 140 Winning trades: 34.29% (48/140) Profit factor: 3.009 Apple (1-hour timeframe) January 3, 2000 – November 17, 2025 Total net profit: $9,685.89 or +94.93% Maximum drawdown: $374.69 or 2.26% Total trades: 118 Winning trades: 35.59% (42/118) Profit factor: 3.463 Apple (2-hour timeframe) January 3, 2000 – November 17, 2025 Total net profit: $8,001.28 or +77.99% Maximum drawdown: $755.84 or 7.56% Total trades: 67 Winning trades: 41.79% (28/67) Profit factor: 3.825 NVDA (15-minute timeframe) January 3, 2000 – November 17, 2025 Total net profit: $11,828.56 or +118.29% Maximum drawdown: $1,275.43 or 8.06% Total trades: 466 Winning trades: 28.11% (131/466) Profit factor: 2.033 NVDA (30-minute timeframe) January 3, 2000 – November 17, 2025 Total net profit: $12,203.21 or +122.03% Maximum drawdown: $1,661.86 or 10.35% Total trades: 245 Winning trades: 28.98% (71/245) Profit factor: 2.291 NVDA (45-minute timeframe) January 3, 2000 – November 17, 2025 Total net profit: $16,793.48 or +167.93% Maximum drawdown: $1,458.81 or 8.40% Total trades: 172 Winning trades: 33.14% (57/172) Profit factor: 2.927
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Especulador96の投稿
6
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model. Strategy Logic Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically. To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions. Exit logic includes: A take-profit at 3× the ATR distance A stop-loss at 1.5× the ATR distance An optional early exit if RSI crosses above 70, signaling overbought conditions Technical Details Trend Filter: 200 EMA – must be rising and price must be above it Entry Signal: RSI dips below 40 during an uptrend Volatility Filter: ATR must be above a user-defined minimum threshold Stop-Loss: 1.5× ATR below entry price Take-Profit: 3.0× ATR above entry price Exit on Overbought: RSI > 70 (optional early exit) Backtest Settings Initial Capital: $10,000 Position Sizing: 5% of equity per trade Slippage: 1 tick Commission: 0.075% per trade Trade Direction: Long only Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD This model is tuned for positive P&L across trending environments and volatile markets. Educational Use Only This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
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AIScriptsの投稿
2
RSI BREAKOUT SIGNALSThis BB + RSI Breakout indicator is designed to help traders identify potential buy and sell opportunities based on price movements relative to the Donchian channel (or Bollinger-type channel) and momentum conditions. It calculates the highest high and lowest low over a user-defined length to form a dynamic channel, and then it checks whether the current price breaks above the upper band (for a buy signal) or below the lower band (for a sell signal). To avoid repeated signals in a row, the indicator uses a state system: after a buy signal occurs, it will not generate another buy until a sell occurs, and vice versa. When a buy signal is triggered, it automatically calculates a take-profit price a certain percentage above the buy candle and displays this price below the candle as a “TP” label. Sell signals are displayed above the candle, and any previous TP label is cleared. The indicator updates in real time, so the signals move with the chart, giving a clear and lag-free visualization of entry points and potential profit targets.
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gabrielcoracinidesouza07の投稿
2
BTC EMA 5-9 Flip Strategy AutobotThis strategy is designed for fast and accurate trend-following trades on Bitcoin. It uses a crossover between EMA 5 and EMA 9 to detect instant trend reversals and automatically flips between Long and Short positions. How the strategy works EMA 5 crossing above EMA 9 → Long EMA 5 crossing below EMA 9 → Short Automatically closes the opposite trade during a flip Executes trades only on candle close Prevents double entries with internal position-state logic Fully compatible with automated trading via webhooks (Delta Exchange) Why this strategy works EMA 5–9 is extremely responsive for BTC’s volatility Captures trend reversals early Works best on 15-minute timeframe Clean, simple logic without over-filtering reduces missed opportunities Performs well in both uptrends and downtrends Automation Ready This strategy includes alert conditions and webhook-ready JSON for automated execution. This is a fast-reacting BTC bot designed for intraday and swing crypto trend trading.
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kulkarniabhishek38の投稿
2
SP500 Session Gap Fade StrategySummary in one paragraph SPX Session Gap Fade is an intraday gap fade strategy for index futures, designed around regular cash sessions on five minute charts. It helps you participate only when there is a full overnight or pre session gap and a valid intraday session window, instead of trading every open. The original part is the gap distance engine which anchors both stop and optional target to the previous session reference close at a configurable flat time, so every trade’s risk scales with the actual gap size rather than a fixed tick stop. Scope and intent • Markets. Primarily index futures such as ES, NQ, YM, and liquid index CFDs that exhibit overnight gaps and regular cash hours. • Timeframes. Intraday timeframes from one minute to fifteen minutes. Default usage is five minute bars. • Default demo used in the publication. Symbol CME:ES1! on a five minute chart. • Purpose. Provide a simple, transparent way to trade opening gaps with a session anchored risk model and forced flat exit so you are not holding into the last part of the session. • Limits. This is a strategy. Orders are simulated on standard candles only. Originality and usefulness • Unique concept or fusion. The core novelty is the combination of a strict “full gap” entry condition with a session anchored reference close and a gap distance based TP and SL engine. The stop and optional target are symmetric multiples of the actual gap distance from the previous session’s flat close, rather than fixed ticks. • Failure mode it addresses. Fixed sized stops do not scale when gaps are unusually small or unusually large, which can either under risk or over risk the account. The session flat logic also reduces the chance of holding residual positions into late session liquidity and news. • Testability. All key pieces are explicit in the Inputs: session window, minutes before session end, whether to use gap exits, whether TP or SL are active, and whether to allow candle based closes and forced flat. You can toggle each component and see how it changes entries and exits. • Portable yardstick. The main unit is the absolute price gap between the entry bar open and the previous session reference close. tp_mult and sl_mult are multiples of that gap, which makes the risk model portable across contracts and volatility regimes. Method overview in plain language The strategy first defines a trading session using exchange time, for example 08:30 to 15:30 for ES day hours. It also defines a “flat” time a fixed number of minutes before session end. At the flat bar, any open position is closed and the bar’s close price is stored as the reference close for the next session. Inside the session, the strategy looks for a full gap bar relative to the prior bar: a gap down where today’s high is below yesterday’s low, or a gap up where today’s low is above yesterday’s high. A full gap down generates a long entry; a full gap up generates a short entry. If the gap risk engine is enabled and a valid reference close exists, the strategy measures the distance between the entry bar open and that reference close. It then sets a stop and optional target as configurable multiples of that gap distance and manages them with strategy.exit. Additional exits can be triggered by a candle color flip or by the forced flat time. Base measures • Range basis. The main unit is the absolute difference between the current entry bar open and the stored reference close from the previous session flat bar. That value is used as a “gap unit” and scaled by tp_mult and sl_mult to build the target and stop. Components • Component one: Gap Direction. Detects full gap up or full gap down by comparing the current high and low to the previous bar’s high and low. Gap down signals a long fade, gap up signals a short fade. There is no smoothing; it is a strict structural condition. • Component two: Session Window. Only allows entries when the current time is within the configured session window. It also defines a flat time before the session end where positions are forced flat and the reference close is updated. • Component three: Gap Distance Risk Engine. Computes the absolute distance between the entry open and the stored reference close. The stop and optional target are placed as entry ± gap_distance × multiplier so that risk scales with gap size. • Optional component: Candle Exit. If enabled, a bullish bar closes short positions and a bearish bar closes long positions, which can shorten holding time when price reverses quickly inside the session. • Session windows. Session logic uses the exchange time of the chart symbol. When changing symbols or venues, verify that the session time string still matches the new instrument’s cash hours. Fusion rule All gates are hard conditions rather than weighted scores. A trade can only open if the session window is active and the full gap condition is true. The gap distance engine only activates if a valid reference close exists and use_gap_risk is on. TP and SL are controlled by separate booleans so you can use SL only, TP only, or both. Long and short are symmetric by construction: long trades fade full gap downs, short trades fade full gap ups with mirrored TP and SL logic. Signal rule • Long entry. Inside the active session, when the current bar shows a full gap down relative to the previous bar (current high below prior low), the strategy opens a long position. If the gap risk engine is active, it places a gap based stop below the entry and an optional target above it. • Short entry. Inside the active session, when the current bar shows a full gap up relative to the previous bar (current low above prior high), the strategy opens a short position. If the gap risk engine is active, it places a gap based stop above the entry and an optional target below it. • Forced flat. At the configured flat time before session end, any open position is closed and the close price of that bar becomes the new reference close for the following session. • Candle based exit. If enabled, a bearish bar closes longs, and a bullish bar closes shorts, regardless of where TP or SL sit, as long as a position is open. What you will see on the chart • Markers on entry bars. Standard strategy entry markers labeled “long” and “short” on the gap bars where trades open. • Exit markers. Standard exit markers on bars where either the gap stop or target are hit, or where a candle exit or forced flat close occurs. Exit IDs “long_gap” and “short_gap” label gap based exits. • Reference levels. Horizontal lines for the current long TP, long SL, short TP, and short SL while a position is open and the gap engine is enabled. They update when a new trade opens and disappear when flat. • Session background. This version does not add background shading for the session; session logic runs internally based on time. • No on chart table. All decisions are visible through orders and exit levels. Use the Strategy Tester for performance metrics. Inputs with guidance Session Settings • Trading session (sess). Session window in exchange time. Typical value uses the regular cash session for each contract, for example “0830-1530” for ES. Adjust if your broker or symbol uses different hours. • Minutes before session end to force exit (flat_before_min). Minutes before the session end where positions are forced flat and the reference close is stored. Typical range is 15 to 120. Raising it closes trades earlier in the day; lowering it allows trades later in the session. Gap Risk • Enable gap based TP/SL (use_gap_risk). Master switch for the gap distance exit engine. Turning it off keeps entries and forced flat logic but removes automatic TP and SL placement. • Use TP limit from gap (use_gap_tp). Enables gap based profit targets. Typical values are true for structured exits or false if you want to manage exits manually and only keep a stop. • Use SL stop from gap (use_gap_sl). Enables gap based stop losses. This should normally remain true so that each trade has a defined initial risk in ticks. • TP multiplier of gap distance (tp_mult). Multiplier applied to the gap distance for the target. Typical range is 0.5 to 2.0. Raising it places the target further away and reduces hit frequency. • SL multiplier of gap distance (sl_mult). Multiplier applied to the gap distance for the stop. Typical range is 0.5 to 2.0. Raising it widens the stop and increases risk per trade; lowering it tightens the stop and may increase the number of small losses. Exit Controls • Exit with candle logic (use_candle_exit). If true, closes shorts on bullish candles and longs on bearish candles. Useful when you want to react to intraday reversal bars even if TP or SL have not been reached. • Force flat before session end (use_forced_flat). If true, guarantees you are flat by the configured flat time and updates the reference close. Turn this off only if you understand the impact on overnight risk. Filters There is no separate trend or volatility filter in this version. All trades depend on the presence of a full gap bar inside the session. If you need extra filtering such as ATR, volume, or higher timeframe bias, they should be added explicitly and documented in your own fork. Usage recipes Intraday conservative gap fade • Timeframe. Five minute chart on ES regular session. • Gap risk. use_gap_risk = true, use_gap_tp = true, use_gap_sl = true. • Multipliers. tp_mult around 0.7 to 1.0 and sl_mult around 1.0. • Exits. use_candle_exit = false, use_forced_flat = true. Focus on the structured TP and SL around the gap. Intraday aggressive gap fade • Timeframe. Five minute chart. • Gap risk. use_gap_risk = true, use_gap_tp = false, use_gap_sl = true. • Multipliers. sl_mult around 0.7 to 1.0. • Exits. use_candle_exit = true, use_forced_flat = true. Entries fade full gaps, stops are tight, and candle color flips flatten trades early. Higher timeframe gap tests • Timeframe. Fifteen minute or sixty minute charts on instruments with regular gaps. • Gap risk. Keep use_gap_risk = true. Consider slightly higher sl_mult if gaps are structurally wider on the higher timeframe. • Note. Expect fewer trades and be careful with sample size; multi year data is recommended. Properties visible in this publication • On average our risk for each position over the last 200 trades is 0.4% with a max intraday loss of 1.5% of the total equity in this case of 100k $ with 1 contract ES. For other assets, recalculations and customizations has to be applied. • Initial capital. 100 000. • Base currency. USD. • Default order size method. Fixed with size 1 contract. • Pyramiding. 0. • Commission. Flat 2 USD per order in the Strategy Tester Properties. (2$ buying + 2$selling) • Slippage. One tick in the Strategy Tester Properties. • Process orders on close. ON. Realism and responsible publication • No performance claims are made. Past results do not guarantee future outcomes. • Costs use a realistic flat commission and one tick of slippage per trade for ES class futures. • Default sizing with one contract on a 100 000 reference account targets modest per trade risk. In practice, extreme slippage or gap through events can exceed this, so treat the one and a half percent risk target as a design goal, not a guarantee. • All orders are simulated on standard candles. Shapes can move while a bar is forming and settle on bar close. Honest limitations and failure modes • Economic releases, thin liquidity, and limit conditions can break the assumptions behind the simple gap model and lead to slippage or skipped fills. • Symbols with very frequent or very large gaps may require adjusted multipliers or alternative risk handling, especially in high volatility regimes. • Very quiet periods without clean gaps will produce few or no trades. This is expected behavior, not a bug. • Session windows follow the exchange time of the chart. Always confirm that the configured session matches the symbol. • When both the stop and target lie inside the same bar’s range, the TradingView engine decides which is hit first based on its internal intrabar assumptions. Without bar magnifier, tie handling is approximate. Legal Education and research only. This strategy is not investment advice. You remain responsible for all trading decisions. Always test on historical data and in simulation with realistic costs before considering any live use.
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exluxの投稿
2
Moving Average Band StrategyOverview The Moving Average Band Strategy is a fully customizable breakout and trend-continuation system designed for traders who need both simplicity and control. The strategy creates adaptive bands around a user-selected moving average and executes trades when price breaks out of these bands, with advanced risk-management settings including optional Risk:Reward targets. This script is suitable for intraday, swing, and positional traders across all markets — equities, futures, crypto, and forex. Key Features ✔ Six Moving Average Types Choose the MA that best matches your trading style: SMA EMA WMA HMA VWMA RMA ✔ Dynamic Bands Upper Band built from MA of highs Lower Band built from MA of lows Adjustable band offset (%) Color-coded band fill indicating price position ✔ Configurable Strategy Preferences Toggle Long and/or Short trades Toggle Risk:Reward Take-Profit Adjustable Risk:Reward Ratio Default position sizing: % of equity (configurable via strategy settings) Entry Conditions Long Entry A long trade triggers when: Price crosses above the Upper Band Long trades are enabled No existing long position is active Short Entry A short trade triggers when: Price crosses below the Lower Band Short trades are enabled No existing short position is active Clear entry markers and price labels appear on the chart. Risk Management This strategy includes a complete set of risk-controls: Stop-Loss (Fixed at Entry) Long SL: Lower Band Short SL: Upper Band These levels remain constant for the entire trade. Optional Risk:Reward Take-Profit Enabled/disabled using a toggle switch. When enabled: Long TP = Entry + (Risk × Risk:Reward Ratio) Short TP = Entry – (Risk × Risk:Reward Ratio) When disabled: Exits are handled by reverse crossover signals. Exit Conditions Long Exit Stop-Loss Hit (touch-based) Take-Profit Hit (if enabled) Reverse Band Crossover (if TP disabled) Short Exit Stop-Loss Hit (touch-based) Take-Profit Hit (if enabled) Reverse Band Crossover (if TP disabled) Exit markers and price labels are plotted automatically. Visual Tools To improve clarity: Upper & Lower Band (blue, adjustable width) Middle Line Dynamic band fill (green/red/yellow) SL & TP line plotting when in position Entry/Exit markers Price labels for all executed trades These are built to help users visually follow the strategy logic. Alerts Included Every trading event is covered: Long Entry Short Entry Long SL / TP / Cross Exit Short SL / TP / Cross Exit Combined Alert for webhook/automation (JSON-formatted) Perfect for algo trading, Discord bots, or automation platforms. Best For This strategy performs best in: Trending markets Breakout environments High-momentum instruments Clean intraday swings Works seamlessly on: Stocks Index futures Commodities Crypto Forex ⚠️ Important Disclaimer This script is for educational purposes only. Trading involves risk. Backtest results are not indicative of future performance. Always validate settings and use proper position sizing.
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ravi_matrixの投稿
7
FX Swing — Compact Auto-Sizing (Fixed)A compact Forex swing-trading strategy that combines higher-timeframe EMA trend bias, EMA pullback confirmation, and RSI momentum filtering. It automatically sizes positions using either risk-percentage or fixed-risk, adapts pip values for JPY and non-JPY pairs, and generates clear SL/TP levels with partial take-profit exits. The script also sends structured JSON alerts for webhooks or WhatsApp automation, making it ideal for fast, disciplined, and risk-controlled swing entries.
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Shrihari78の投稿
1
MOMO – Imbalance Trend (SIMPLE BUY/SELL)MOMO – Imbalance Trend (SIMPLE BUY/SELL) This strategy combines trend breaks, imbalance detection, and first-tap supply/demand entries to create a clean and disciplined trading model. It automatically highlights imbalance candles, draws fresh zones, and waits for the first retest to deliver precise BUY and SELL signals. Performance On optimized settings, this strategy shows an estimated 57%–70% win-rate, depending on the asset and timeframe. Actual performance may vary, but the model is built for consistency, discipline, and improved decision-making. How it works Detects trend structure shifts (BOS / Break of Trend) Identifies displacement (imbalance) candles Creates supply and demand zones from imbalance origin Waits for first tap only (no second chances) Confirms direction using trend logic Generates clean BUY/SELL arrows Automatic SL/TP based on user settings Features Clean BUY/SELL markers Auto-drawn supply & demand zones Trend break markers Imbalance tags Smart first-tap confirmation Customizable stop loss & take profit Works on crypto, gold, forex, indices Best on M5–H1 for day trading Note This strategy is designed for day traders who want clarity, structure, and zero emotional trading. Use it with discipline — and it will serve you well. Good luck, soldier.
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mohamed030402の投稿
2
Fractional Candlestick Long Only Experimental V10Fractional Candlestick Long-Only Strategy – Technical Description This document provides a professional English description of the "Fractional Candlestick Long Only Experimental V6" strategy using pure CF/AB fractional kernels and wavelet-based filtering. 1. Fractional Candlesticks (CF / AB) The strategy computes two fractional representations of price using Caputo–Fabrizio (CF) and Atangana–Baleanu (AB) kernels. These provide long-memory filtering without EMA approximations. Both CF and AB versions are applied to O/H/L/C, producing fractional candlesticks and fractional Heikin-Ashi variants. 2. Trend Stack Logic Trend confirmation is based on a 4-component stack: - CF close > AB close - HA_CF close > HA_AB close - HA_CF bullish - HA_AB bullish The user selects how many components must align (4, 3, or any 2). 3. Wavelet Filtering A wavelet transform (Haar, Daubechies-4, Mexican Hat) is applied to a chosen source (e.g., HA_CF close). The wavelet response is used as: - entry filter (4 modes) - exit filter (4 modes) Wavelet modes: off, confirm, wavelet-only, block adverse signals. 4. Trailing System Trailing stop uses fractional AB low × buffer, providing long-memory dynamic trailing behavior. A fractional trend channel (CF/AB lows vs HA highs) is also plotted. 5. Exit Framework Exit options include: stack flip, CF
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wojluczの投稿
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Qullamagi EMA Breakout Autotrade (Crypto Futures L+S)Title: Qullamagi EMA Breakout – Crypto Autotrade Overview A crypto-focused, Qullamagi-style EMA breakout strategy built for autotrading on futures and perpetual swaps. It combines a 5-MA trend stack (EMA 10/20, SMA 50/100/200), volatility contraction boxes, volume spikes and an optional higher-timeframe 200-MA filter. The script supports both long and short trades, partial take profit, trailing MA exits and percent-of-equity position sizing for automated crypto futures trading. Key Features (Crypto) Qullamagi MA Breakout Engine – trades only when price is aligned with a strong EMA/SMA trend and breaks out of a tight consolidation range. Longs use: Close > EMA10 > EMA20 > SMA50 > SMA100 > SMA200. Shorts are the mirror condition with all MAs sloping in the trend direction. Strict vs Loose Modes – Strict (Daily) is designed for cleaner swing trades on 1H–4H (full MA stack, box+ATR and volume filters, optional HTF filter). Loose (Intraday) focuses on 10/20/50 alignment with relaxed filters for more frequent 15m–30m signals. Volatility & Volume Filters for Crypto – ATR-based box height limit to detect volatility contraction, wide-candle filter to avoid chasing exhausted breakouts, and a volume spike condition requiring current volume to exceed an SMA of volume. Higher-Timeframe Trend Filter (Optional) – uses a 200-period SMA on a higher timeframe (default: 1D). Longs only when HTF close is above the HTF 200-SMA, shorts only when it is below, helping avoid trading against dominant crypto trends. Autotrade-Oriented Trade Management – position size as % of equity, initial stop anchored to a chosen MA (EMA10 / EMA20 / SMA50) with optional buffer, partial take profit at a configurable R-multiple, trailing MA exit for the remainder, and an optional cooldown after a full exit. Markets & Timeframes Best suited for BTC, ETH and major altcoin futures/perpetuals (Binance, Bybit, OKX, etc.). Strict preset: 1H–4H charts for classic Qullamagi-style trend structure and fewer fake breakouts. Loose preset: 15m–30m charts for higher trade frequency and more active intraday trading. Always retune ATR length, box length, volume multiplier and position size for each symbol and exchange. Strategy Logic (Quick Summary) Long (Strict): MA stack in bullish alignment with all MAs sloping up → tight volatility box (ATR-based) → volume spike above SMA(volume) × multiplier → breakout above box high (close or intrabar) → optional HTF close above 200-SMA. Short: Mirror logic: bearish MA stack, tight box, volume spike and breakdown below box low with optional HTF downtrend. Best Practices for Crypto Backtest on each symbol and timeframe you plan to autotrade, including commissions and slippage. Start on higher timeframes (1H/4H) to learn the behavior, then move to 15m–30m if you want more signals. Use the higher-timeframe filter when markets are strongly trending to reduce counter-trend trades. Keep position-size percentage conservative until you fully understand the drawdowns. Forward-test / paper trade before connecting to live futures accounts. Webhook / Autotrade Integration Designed to work with TradingView webhooks and external crypto trading bots. Alert messages include structured fields such as: EVENT=ENTRY / SCALE_OUT / EXIT, SIDE=LONG / SHORT, STRATEGY=Qullamagi_MA. Map each EVENT + SIDE combination to your bot logic (open long/short, partial close, full close, etc.) on your preferred exchange. Important Notes & Disclaimer Crypto markets are highly volatile and can change regime quickly. Backtest and forward-test thoroughly before using real capital. Higher timeframes generally produce cleaner MA structures and fewer fake breakouts. This strategy is for educational and informational purposes only and does not constitute financial advice. Trading leveraged crypto products involves substantial risk of loss. Always do your own research, manage risk carefully, and never trade with money you cannot afford to lose.
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