지금 시작

상대강도지수 (RSI)

GS Sneaky Snake (RSI Order Blocks) [Bit2Billions]🐍 The GS Sneaky Snake is a specialized institutional supply and demand engine that brings Volumetric Order Block (OB) Analysis into the Relative Strength Index (RSI). Designed to identify "Hidden" accumulation and distribution zones, it treats the RSI as a traded asset by generating RSI Candles and scanning them for high-volume pivots. By mapping these momentum-based order blocks back to price, GS Snake reveals the precise levels where the "Smart Money" is building positions before a major trend expansion. --- 📝 What It Does GS Snake performs a sophisticated multi-step analysis: it first reconstructs standard price action into RSI Candles and then applies a RANSAC Smart Length Engine to find the most statistically significant pivot points. It identifies institutional Order Blocks based on volume-weighted signatures and tracks their mitigation (absorption) in real-time. The engine calculates the Volumetric Density of each zone, telling you exactly how much "firepower" (Billions/Millions of volume) is sitting at specific momentum levels. --- 📊 Visual Details & Indications The visual architecture is built for surgical precision and clarity: 🕯️ RSI Candles: The pane displays full OHLC RSI candles (Teal = Bullish / Red = Bearish), allowing you to see the "wicks" and internal structure of momentum. 📦 Volumetric Order Blocks: Emerald Green Zones: Bullish Order Blocks (Institutional Support). Crimson Red Zones: Bearish Order Blocks (Institutional Resistance). * These zones expand to the right as price approaches them, acting as live target areas. 📊 Volume Velocity Markers (BLB/BRB): Small internal boxes within the order blocks that project the speed of volume absorption. 🏷️ Metric Callouts: Each block features a label showing the Raw Volume (e.g., "1.5B") and its Percentage Share (%) of the total volume in the lookback period. 📉 Dynamic Midline: A dashed center line inside each zone marking the "Equilibrium" or fair value of the order block. ☁️ Background RSI Fills: Standard green, yellow, and red horizontal zones provide the macro RSI context (Overbought/Oversold). --- 🚀 Key Features ⚡ RANSAC Smart Length: A self-optimizing engine that tests 5 different lookback windows (5 to 160 bars) to find the "best-fit" structural pivots for the current market volatility. 🔢 Multi-Zone Tracking: Keep up to 20 active or historical institutional zones on your chart simultaneously. 🎯 "Strongest Only" Filter: An option to declutter your chart by showing only the single order block with the absolute highest volume concentration. 🪄 RSI-to-Price Mapping: Proprietary coordinate conversion allows these momentum zones to be projected accurately as a Price Chart Overlay. 🛡️ Absolute Mitigation Logic: Automatically identifies when a zone has been "tapped" or fully breached by price wicks, alerting you to level exhaustion. --- 💡 Why This is Useful Standard Order Blocks on a price chart can be manipulated. GS Snake finds Order Blocks in the Momentum Space. If institutions are loading orders without significantly moving price (Absorption), it will show up as a high-volume Snake OB in the RSI pane. This allows traders to enter *before* the price breakout occurs, leading to much tighter stop-losses and higher R:R ratios. --- 💎 Why It Is Different & Unique GS Snake is unique because it uses a Probabilistic Statistical Model (RANSAC) to determine its lookback period. While other indicators use fixed settings, GS Snake "thinks" by evaluating which timeframe currently has the highest correlation with price action. Combining this with Volumetric Weighting—where zones are ranked by the actual volume transacted—creates a "Heatmap of Institutional Intent" that standard SMC tools lack. --- 🛠️ How to Use 1. Monitor the Squeeze: Watch for a high-volume Volumetric Order Block to form in the RSI pane. 2. Confirm the Weight: Look for zones with a high "Volume %" (e.g., >40%). These are the primary "Whale" levels. 3. The Entry: When the RSI candles pull back into a Green (Bullish) OB, look for a "Fresh Bull Cross" or a rejection wick. 4. Targeting: Use the Equilibrium Midline of the opposite side's Order Block as your first take-profit target. 5. Stop-Loss: Place your SL just below the bottom of the Bullish OB (or above the top of the Bearish OB). --- ⚖️ Disclaimer This script is an open-source tool designed for educational and institutional analytical purposes. Transparency: Proprietary RSI Candle and Volumetric OB systems by Bit2Billions. Compliance: It is a significant functional derivative and original work. Risk Warning: Order blocks represent historical areas of interest; they are not guarantees of future support or resistance. Always use sound risk management.
Pine Script® 인디케이터
bit2billions의
GS Crocodile (RSI Trend | Divergence) [Bit2Billions]🐊 The Ghost Crocodile is an advanced, multi-dimensional momentum and trend analysis engine. This indicator goes beyond a standard RSI line by cross-examining relative strength through various mathematical layers, including smoothing moving averages, volatility bands, algorithmic trendline charting, and an integrated Ichimoku Cloud matrix. Equipped with an advanced telemetry dashboard, it synthesizes live momentum metrics to display macro structural bias and precise localized reversal setups using clean visual labels. 💻 What It Does 1. 📊 Multi-Variant RSI Smoothing: Filters out raw market noise by routing relative strength through your choice of 6 smoothing variations (SMA, EMA, SMMA, WMA, VWMA, or Bollinger Bands). 2. 🎨 Dynamic Grid Zones: Segregates the oscillator background into structured grid blocks (0-40, 40-60, 60-100) using color matrices to instantly identify key momentum zones. 3. 📈 Automated RSI Trendlines: Programmatically charts localized pivot highs and lows directly within the momentum spectrum and tracks structural breaks in real time. 4. ☁️ RSI Ichimoku Cloud: Transposes Equilibrium trading rules onto momentum space, utilizing Tenkan, Kijun, Span A, and Span B values to determine macro trend stability. 5. 🔍 Multi-Type Divergence Engine: Scans automatically for both Regular Bullish/Bearish and Hidden Bullish/Bearish anomalies to pinpoint major turning points or trend continuation setups. 6. 🔄 Dual-Spectrum Force Overlay: Allows you to mirror the entire complex oscillator geometry directly onto your main price chart as a transparent duplicate overlay, eliminating the need to look away from your candles. 🎨 Chart Visuals & Indication Details A. Oscillator Pane & Main Chart Overlay: * 🟢🔴 RSI Line: -> Green Color: Indicates the RSI is trading above its smoothing baseline (Bullish Momentum). -> Red Color: Indicates the RSI is trading below its smoothing baseline (Bearish Momentum). * 📈 RSI-Based MA: -> Green: Plotted when the underlying baseline momentum favors the upside. -> Red: Plotted when the baseline shifts toward downside depreciation. * 🗺️ Background Horizon Grids: -> Olive / Khaki Cloud (Ichimoku): Rendered between Span A and Span B. An Olive Cloud represents bullish structural alignment, while a Khaki Cloud signals bearish structural alignment. -> Top Zone (60 - 100): Filled with a Soft Green Gradient, marking strong bullish acceleration spaces. -> Mid Zone (40 - 60): Filled with a Soft Yellow Gradient, defining baseline consolidation or market transition spaces. -> Bottom Zone (0 - 40): Filled with a Soft Red Gradient, highlighting deep bearish exhaustion and oversold accumulation spaces. * 💥 Bollinger Bands Boundary: -> Rendered as an Upper Red Line and a Lower Bright Green Line wrapped around the RSI MA to visually outline real-time volatility thresholds. B. Divergence Signal Labels: Clear textual markers are generated on the exact pivot candle offset when divergences are confirmed: * 🟢 "Bull" (Green Label): Regular Bullish Divergence. Price forms a lower low while the RSI registers a higher low (Seller Exhaustion / Reversal Trap). * 🔴 "Bear" (Red Label): Regular Bearish Divergence. Price forms a higher high while the RSI registers a lower high (Buyer Exhaustion / Reversal Trap). * 🔵 "H-Bull" (Teal Label): Hidden Bullish Divergence. Price forms a higher low while the RSI maps a lower low (Strong Trend Continuation Setup). * 🟠 "H-Bear" (Orange Label): Hidden Bearish Divergence. Price forms a lower high while the RSI maps a higher high (Strong Short Continuation Setup). C. Algorithmic Trendlines: * 🔴 Red Dotted Lines: Plotted across local RSI pivot highs. When the RSI breaks above this boundary, the line locks into a solid Red line, signaling an upside momentum breakout. * 🟢 Green Dotted Lines: Plotted across local RSI pivot lows. When the RSI breaks below this boundary, the line locks into a solid Green line, signaling a downside momentum breakdown. 📊 Advanced Crocodile Intelligence Dashboard Features Positioned interactively on the Middle Left section of your chart, this technical telemetry panel updates live with the following analytical vectors: * 🎯 Final Bias: Synthesizes all variables to print an immediate absolute trend condition - BULLISH (Green), BEARISH (Red), or NEUTRAL (Yellow). * ⚡ L/S Score: Displays a unified power ratio representing Long Strength vs Short Strength out of 100 (e.g., 75/100). * 💎 RSI Value: The live mathematical RSI calculation. Turns Green if above 50 and Red if below 50. * 🔮 RSI Source: Tracks the current value configuration feeding the core momentum engine. * ⛓️ MA State: Mentions structural relation - "RSI Above MA" (Green) or "RSI Below MA" (Red). * 📏 MA Distance: The exact numerical gap layout between the RSI line and its moving average baseline. * 🌪️ BB State: Signals structural volatility conditions - "Inside BB", "Lower BB Reclaim" (Green), or "Upper BB Rejection" (Red). * 📈 BB Position: Percentage reading indicating precisely where the RSI sits within its volatility bands (0% = Bottom Band, 100% = Top Band). * 🌤️ Ichimoku RSI: Displays macro momentum cloud status - Bullish (Green), Bearish (Red), or Neutral (Yellow). * 📢 Divergence: Flashes the exact name of the structural pattern the second an active anomaly is identified. * 🧮 Trendlines H/L: Tracks the quantity of active resistance and support trendlines currently monitored by the engine. * 🔨 Broken TL H/L: Provides a real-time count of momentum trendlines that have successfully logged valid structural breakouts. * 🧠 Brain Plan: Reads live telemetry combinations to print automated, context-specific technical action plan suggestions. 💡 How to Use It (Trading Strategies) 1. 🗺️ Trend Confluence Execution: Cross-reference the dashboard's "Final Bias" with the "Ichimoku Cloud." If the bias is labeled BULLISH and the RSI is sustained cleanly above an Olive Cloud, prioritize high-probability long execution structures. 2. 🌪️ Volatility Reversion setups: Keep a close eye on the dashboard "BB Position." If it pushes beyond 100% or beneath 0%, wait for a "Lower BB Reclaim" or "Upper BB Rejection" layout change to capture sharp mean-reversion swings. 3. 🚀 Momentum Breakout Plays: Monitor the RSI Trendlines. When a long-standing Red Resistance Dotted Line confirms a breakout and locks into a Solid Red line, the probability of an aggressive expansion on the price chart increases significantly. 4. 🎯 Structural Confluence: When a distinct Divergence Label triggers right as price taps into key higher-timeframe areas (like support/resistance blocks or order blocks), verify that the dashboard Long/Short score confirms the direction before taking the setup. ⚡ Why This Is Useful, Different and Unique * 🧠 Traditional RSI applications often leave traders guessing whether a reading over 70 means "exhausted overbought market" or "strong bullish trend expansion." Ghost Crocodile clears this confusion by wrapping Bollinger Bands and an Ichimoku Cloud directly over the RSI, calibrating relative strength against historic volatility. * 💥 Features a Dual Spectrum system, keeping your charting workspace modular. You can seamlessly project complex oscillator behaviors straight onto price bars as an automated visual copy. * 🤖 Mapping manual trendlines introduces personal charting bias. This indicator utilizes explicit programmatic criteria to anchor, track, and measure breaks on momentum lines with mathematical consistency. 📌 License & Open-Source Terms • Open-Source Script © 2026 • Similarities to other public scripts arise solely from shared market methodologies and universally known charting concepts. 📌 Respect & Transparency Built with respect for the TradingView and trading communities. Any similarities to existing tools are conceptual in nature and can be addressed openly and constructively. 📌 FAQs * Alerts can be configured manually * Compatible with all major markets and timeframes * Predictive modules are designed to assist analysis, not guarantee outcomes ⚠ Disclaimer This indicator is designed for educational and informational purposes only. It does not provide financial advice, trading recommendations, or guaranteed outcomes. All trading decisions remain the sole responsibility of the user.
Pine Script® 인디케이터
bit2billions의
[3Commas] AMZN RSI Oversold Doubling DCA - Long IndicatorAMZN RSI Oversold Doubling DCA — Long Indicator 🔷 What it does: This is a signal-only indicator that mirrors an AMZN dip-buying workflow with an aggressive doubling-martingale safety ladder. It tracks one virtual long position at a time, opened only when AMZN prints a deep oversold reading on 4-hour RSI. Five safety orders fire at fixed deviations from base entry (−2%, −5%, −9.5%, −16%, −25%) with sizes doubling on every rung. Exit is a fixed 3% Take Profit from average entry. The indicator computes running average entry, deployed capital, open PnL, and lifetime realized PnL — all derived from honest fill-by-fill bookkeeping. Every event emits a webhook-ready JSON alert payload for direct DCA Bot consumption. - Selective oversold entry: 4h RSI < 28. - Non-uniform fixed-deviation safety ladder: −2%, −5%, −9.5%, −16%, −25% from base entry. - Doubling safety-order sizes: 1k / 2k / 4k / 8k / 16k USDT from a $500 base. - Tight 3% Take Profit from the averaged-down entry — quick deal close once price stabilizes. - Honest virtual bookkeeping: Open PnL and lifetime Total PnL displayed live on the chart. 🔷 Who is it for: - Swing traders running a DCA Bot on AMZN who want to buy deep oversold dips. - Bot operators who want a chart-driven signal source that emits per-event JSON ready for a DCA Bot. - Traders who can absorb a doubling martingale up to ~31.5% of equity deployed per trade in exchange for a high deal-close rate. - Operators tracking staged position management — entry, up to five staged safety fills, and a single exit — directly on the chart without the strategy-tester overhead. 🔷 How does it work: Entry Filter: A 4-hour RSI(14) is sampled via request.security with lookahead disabled (no repaint). The entry gate fires when RSI is below 28 (deep oversold) at host-bar close, filtering out shallow dips. Base Entry: When the gate is satisfied, the indicator marks a virtual long entry, captures the base entry price, and seeds the cost-basis ledger with the configured base order size (default 500 USDT). Safety Order Ladder (Fixed Deviations, Doubling Sizes): After base fill, the indicator monitors price deviation against the position. Each safety order has its own fixed deviation from base entry — not a cumulative ladder. AO1 fills at close ≤ base × 0.98 (−2%); AO2 at −5%; AO3 at −9.5%; AO4 at −16%; AO5 at −25%. USDT sizes double from a 1,000 first AO: 1,000 / 2,000 / 4,000 / 8,000 / 16,000. Each fill updates the running cost-basis and dispatches its own webhook payload. Honest Virtual Bookkeeping: Total cost and qty are updated incrementally on every event, so the avg entry, deployed capital, Open PnL, and Total PnL displayed in the status table reflect the actual broker-equivalent position state — no shortcut from base entry, no synthetic averaging. Lifetime Total PnL: When the position closes for profit, the realized PnL from that cycle accumulates into a lifetime counter. The status table displays both Open PnL (current cycle, resets on exit) and Total PnL (lifetime, persists across the chart history) — giving traders a real-time read on cumulative performance without a backtest engine. Exit: A fixed 3% Take Profit above the running average entry. When close hits the TP target, the close webhook fires, realized PnL accumulates, and the virtual position resets. 🔷 Why it's unique: - Selective Oversold Entry: The deal opens only on a deep 4h RSI < 28 print, so capital is committed at genuinely stretched conditions rather than on every dip. - Non-Uniform Fixed-Deviation Ladder: Most published DCA tools use formula-based ladders (step × multiplier). This one exposes each AO deviation as a direct input, allowing an asymmetric ladder (2% / 5% / 9.5% / 16% / 25%) where deeper safety orders trigger only on serious adverse moves and the lowest rung sits a full 25% below base. - Doubling Martingale: 1 / 2 / 4 / 8 / 16 / 32 size progression scales position capital exponentially if the position runs adverse, but is hard-bounded by the 5-rung ladder. - Lifetime PnL Tracking: Open PnL and Total PnL are displayed live on the chart — Open resets per cycle, Total persists across the entire chart history. The indicator gives strategy-tester-equivalent insight without running a backtest. - Per-Event Webhook Ledger: Up to seven discrete events per cycle (entry + 5 AO fills + TP), each with its own JSON alert payload. One TradingView alert with "Any alert() function call" drives a DCA Bot end-to-end. 🔷 Considerations Before Using the Indicator: Sample Size: The companion strategy's backtest produced 22 closed trades — below the ≥100 floor typically used for statistical confidence. The 90.91% win rate and high profit factor reflect favorable conditions over the test window and the averaging mechanic, not a deterministic edge. Treat them as indicative of how the ladder behaves, not a forward-performance guarantee. Aggressive Capital Deployment: If all five safety orders fill, total deployed capital reaches 31,500 USDT = ~31.5% of the default reference equity. The doubling martingale amplifies both upside on recovery and risk if the lower bound breaks. Match the indicator's per-AO allocation to your bot's configuration to keep the avg-entry display honest. No Stop Loss: There is no exit signal on adverse moves below AO5 (−25% from base). If price keeps falling, the virtual position holds unhedged until either price recovers to the 3% TP target or the user intervenes. Risk is structurally capped on the bot side by the bounded position ladder; if a hard exchange-side stop is required, configure it on the bot directly. Martingale Tail Risk: A doubling ladder that bottoms out at −25% is built for mean-reverting moves. A sustained directional collapse below −25% leaves the full virtual position open with no further averaging available — the single largest risk in any martingale DCA. Choose assets and regimes where deep-but-recoverable dips are the norm. Cross Detection Granularity: Entries and AO fills are evaluated on bar close. A bar that spikes through a level and returns within the same bar may be missed by design — this matches realistic polling behavior and avoids over-signaling on intra-bar wicks. Live vs Historical State: The virtual position state is rebuilt from chart history each time the indicator is recompiled. If the indicator is added mid-deployment or the live bot diverges from the signal stream (manual interventions, partial fills), the indicator state may not match the live bot. Toggle the indicator off and on to reset. Backtesting Note: This is an indicator, not a strategy. There is no built-in P&L tester — but the live Total PnL counter in the status table gives a running approximation. For full metrics over a ~9.4-month sample (22 closed trades, 90.91% win rate, 0.20% max drawdown, profit factor 21.997, +0.81% net return), use the companion strategy version on identical parameters. 🔷 How to Use It: 🔸 Add the indicator to an AMZN / USDT chart on 4h. 🔸 Review the RSI entry level, the five AO deviations and sizes, and the Take Profit percentage. Defaults are calibrated for AMZN 4h — recalibrate when the asset's volatility regime shifts. 🔸 Set Base Order Size and AO sizes to match your bot's configuration (the indicator's avg-entry display becomes meaningful when virtual sizing matches real sizing). 🔸 In the DCA Bot Webhook group, paste the Bot ID, Email Token, and Pair (QUOTE_BASE format, e.g., USDT_AMZN). 🔸 Create an alert on the indicator with "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field. The indicator will emit JSON payloads for entry, each safety order, and TP exit — formatted for direct DCA Bot consumption. 🔷 INDICATOR SETTINGS Base Order Size (USDT): Virtual order size for the avg-entry / open-PnL computation. AO1–AO5 Deviation (%): Fixed distance from base entry where each safety order becomes eligible. Non-uniform by design, reaching −25% at AO5. AO1–AO5 Size (USDT): Virtual USDT amount of each safety order. Doubles at each rung by default. RSI Timeframe / Length / Less Than: 4h RSI filter for the base entry. Take Profit (%): Fixed distance above the running average entry where the virtual long closes. Active Window: Optional date filter — when ON, the indicator only fires signals between From and To dates. DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload. Visualization: Toggle AO Ladder, Avg / TP plot lines, fill labels, signal triangles, status table. Brand Watermark: Configurable text, position, size, and transparency. 👨🏻‍💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented. __ The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Pine Script® 인디케이터
3Commas의
[3Commas] AMZN RSI Oversold Doubling DCA - Long StrategyAMZN RSI Oversold Doubling DCA — Long Strategy 🔷 What it does: This is a long-only DCA strategy with a selective oversold entry and an aggressive martingale safety-order ladder. A long entry opens only when the 4-hour RSI falls below 28 (deep oversold). Five safety orders then fire at fixed deviations from base entry (−2%, −5%, −9.5%, −16%, −25%) with sizes doubling on every rung ($1,000 → $2,000 → $4,000 → $8,000 → $16,000). Exit is a fixed 3% Take Profit from average entry. No trailing, no Stop Loss. - Single base order with up to five safety orders on a non-uniform fixed-deviation ladder reaching −25% below base. - Aggressive size doubling: 1 / 2 / 4 / 8 / 16 / 32 unit progression from a $500 base. - Tight 3% Take Profit from average entry — the averaging ladder pulls the average down so a small recovery closes the deal in profit. - Single entry filter: deeply oversold 4h RSI — a clean, selective trigger. - Every entry, safety order, and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption. 🔷 Who is it for: - Swing traders looking for long exposure on AMZN when it prints deep oversold readings on the 4h. - DCA-style traders who want a disciplined averaging ladder that only deepens on serious adverse moves. - Bot operators who want to drive a DCA Bot via webhook with per-event JSON payloads tagged for each base / safety order / exit action. - Traders comfortable with a doubling martingale ladder deploying up to ~31.5% of equity per trade in exchange for a high deal-close rate. 🔷 How does it work: Entry Filter: A 4-hour RSI(14) is sampled via request.security with lookahead disabled (no repaint). The entry gate fires when RSI is below 28 (deep oversold) at host-bar close, filtering out shallow dips. Base Order: Sized at 500 USDT default (0.5% of 100k capital). Configurable as Market (default) or Limit at the bar's close. Safety Order Ladder (Fixed Deviations, Doubling Sizes): After the base fill, the strategy monitors price deviation against the base entry. Each safety order has its own fixed deviation from base — not a cumulative ladder. AO1 fires when close ≤ base × 0.98 (−2%); AO2 at −5%; AO3 at −9.5%; AO4 at −16%; AO5 at −25%. Sizes double from a 1,000 USDT first AO: 1,000 / 2,000 / 4,000 / 8,000 / 16,000. Exit: A fixed 3% Take Profit above the running average entry. When close hits the TP target, the position closes at market. No trailing, no Stop Loss. Why the Ladder Works: Each doubling safety order weights the average entry heavily toward the lowest fills. After several rungs fill, the average sits well below base, so a modest 3% bounce off the lows is enough to close the whole deal in profit — the core mechanic of a doubling DCA bot. 🔷 Why it's unique: - Selective Oversold Entry: The deal opens only on a deep 4h RSI < 28 print, so capital is committed at genuinely stretched conditions rather than on every dip. - Non-Uniform Fixed-Deviation Ladder: Most published DCAs use formula-based ladders (step × multiplier). This one exposes each AO deviation as a direct input, allowing an asymmetric ladder (2% / 5% / 9.5% / 16% / 25%) where deeper safety orders trigger only on serious adverse moves and the lowest rung sits a full 25% below base. - Doubling Martingale: 1 / 2 / 4 / 8 / 16 / 32 size progression is more aggressive than typical 1.05–1.5× compounding. Capital deployed scales exponentially if the position runs adverse, but is hard-bounded by the 5-rung ladder. - Tight Recovery Target: The 3% Take Profit on the averaged-down entry closes deals quickly once price stabilizes, keeping the win rate high and holding times short relative to the depth of the ladder. - DCA Bot Integration: Every event (base, AO 1–5, exit) emits a fully-formed JSON alert payload. Connect one alert to a DCA Bot's webhook URL and the strategy drives the bot end-to-end without any glue layer. 🔷 Considerations Before Using the Strategy: Sample Size: The backtest produced 22 closed trades — below the ≥100 floor typically used for statistical confidence. The 90.91% win rate and high profit factor reflect favorable conditions over the test window and the averaging mechanic, not a deterministic edge. Treat these numbers as indicative of how the ladder behaves, not as a forward-performance guarantee. Extend the test window or run the strategy across multiple assets to build a larger sample before committing capital. Aggressive Capital Deployment: If all five safety orders fill, total deployed capital reaches $31,500 = ~31.5% of default 100k equity — above TradingView's typical 5–10% per-trade band. Size the base and AO inputs down to dial per-trade risk into a safer range. The doubling martingale amplifies both upside (when price recovers) and risk (if the lower bound breaks). No Stop Loss: There is no exit on adverse moves below the −25% AO5. If price keeps falling below the lowest safety order, the position holds unhedged until either price recovers to the 3% TP target or the user intervenes. The structural risk cap is the bounded 5-rung position ladder; if a hard exchange-side stop is required, layer it on the bot directly. Martingale Tail Risk: A doubling ladder that bottoms out at −25% is built for mean-reverting moves. A sustained directional collapse below −25% leaves the full position open with no further averaging available — the single largest risk in any martingale DCA. Choose assets and regimes where deep-but-recoverable dips are the norm. Commission Calibration: The default 0.06% commission is calibrated for Bitget perpetual taker conditions. If running on a different venue, update the commission input accordingly. 🔷 STRATEGY PROPERTIES Symbol: BITGET:AMZNUSDT.P (Perpetual) — portable to any AMZN / USDT pair. Timeframe: 4H Test Period: August 26, 2025 — June 5, 2026 (~9.4 months). Initial Capital: 100,000 USDT. Order Size per Trade: 0.5% of Capital base + 5 safety orders with size doubling. Max Capital Deployed: $31,500 per trade (~31.5% of equity). Commission: 0.06% per trade. Slippage: 3 ticks. Margin for Long Positions: 100%. Indicator Settings: Default Configuration. Base Order: 500 USDT, Market by default (Limit toggle available). Take Profit: 3.0% above average entry (no trailing). Stop Loss: None — bounded position size is the structural risk cap. Entry Filter: 4h RSI(14) Less Than 28. Safety Orders: 5 with fixed deviations −2% / −5% / −9.5% / −16% / −25% from base entry; sizes 1k / 2k / 4k / 8k / 16k USDT. Strategy: Long Only. 🔷 STRATEGY RESULTS ⚠️ Remember, past results do not guarantee future performance. Net Profit: +807.71 USDT (+0.81%) Max Equity Drawdown: 199.15 USDT (0.20%) Total Closed Trades: 22 Percent Profitable: 90.91% (20 / 22) Profit Factor: 21.997 🔷 How to Use It: 🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, the five AO deviations and sizes, the RSI entry level, and the Take Profit percentage. Defaults are calibrated for AMZN 4h — recalibrate when the asset's volatility regime shifts. 🔸 Results Review: The backtest produced 22 closed trades — a modest sample. Treat the metrics as indicative of the ladder's behavior, not a forward-performance guarantee. Confirm that the trade frequency and the doubling ladder's max deployment fit your risk tolerance before deploying capital. 🔸 Create alerts to trigger the DCA Bot: Add one alert on the strategy using "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field, and fill the Bot ID, Email Token, and Pair inputs on the script. The strategy will emit JSON payloads for entry, each safety order, and exit — formatted for direct DCA Bot consumption. 🔷 INDICATOR SETTINGS Base Order Size (USDT): USDT amount opened on the long entry. Use LIMIT for Base: Toggle between Market (default) and Limit at bar close. AO1–AO5 Deviation (%): Fixed distance from base entry where each safety order becomes eligible. Non-uniform by design, reaching −25% at AO5. AO1–AO5 Size (USDT): USDT amount of each safety order. Doubles at each rung by default. RSI Timeframe / Length / Less Than: 4h RSI filter for the base entry. Take Profit (%): Fixed distance above average entry where the long closes for profit. DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload. Visualization: Toggle AO Ladder, Avg / TP plot lines, fill labels, status table. Brand Watermark: Configurable text, position, size, and transparency. 👨🏻‍💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented. __ The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Pine Script™ 전략
3Commas의
Katana Signal AUDCAD Entry IndicatorThis indicator visualises the entry logic behind Katana EA v1.4 — an MT4 Expert Advisor I developed privately in 2022 and have been running on a live account ever since. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW THE SIGNAL WORKS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Entry is triggered only when TWO conditions align on the prior closed bar (shift=1, no repainting): BUY signal: • RSI reaches oversold extreme • Parabolic SAR is below the prior bar's low SELL signal: • RSI reaches overbought extreme • Parabolic SAR is above the prior bar's high Both conditions must be true simultaneously. Single-indicator entries are filtered out. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHY AUDCAD ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ AUD and CAD are both commodity-linked currencies that move together the majority of the time. When they temporarily diverge — due to oil price moves, RBA/BOC policy divergence, or risk sentiment shifts — mean-reversion setups have strong structural reasons to work. This makes AUDCAD one of the cleanest pairs for this type of strategy. The correlation rarely breaks permanently, which limits the risk of runaway adverse moves. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DISPLAY SETTINGS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ • BUY signal → green triangle below bar • SELL signal → red triangle above bar • Parabolic SAR → grey dots (standard display) • Background highlight on signal bars (can be disabled) • Info table top-right: SAR direction, current signal status Strategy parameters are optimised internally and not exposed — this prevents unintended parameter changes that could degrade performance. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ MT4 AUTOMATION ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This indicator shows the entry signals visually. The automated version (Katana EA v1.4) executes these entries on MT4 with: • Dynamic lot sizing — auto-scales with account balance • Martingale position scaling (max 8 positions) • Hard stop-loss + 8-hour cooldown after each SL event • Active hours filter (London + New York session only) 51-month backtest results (Mar 2022 – May 2026): ✓ Net profit: +6,717% on ¥150,000 starting capital ✓ Win rate: 96.5% per trade cycle ✓ Profit factor: 1.54 ✓ Stop-losses: 33 in 51 months ✓ Modelling quality: 90% (Every Tick, 60M+ real tick data) Includes: 2022 Ukraine war oil spike, Trump tariffs, Middle East conflict periods. Free 14-day trial + full licence: payhip.com/b/j4d6F Licence delivery & support: Telegram @KaTa4649 ⚠ Requires broker with 500:1 leverage (XM Global recommended) ⚠ Not compatible with US / Canada / UK retail accounts ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ RECOMMENDED SETUP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ For visual analysis: use on AUDCAD 1H or 4H For the automated EA: runs on AUDCAD M5 Broker: XM Global Standard Account (JPY or USD) Min capital: ¥150,000 or $1,000 USD
Pine Script® 인디케이터
visibleBoa82138의
RSI + SMA Crossover Gradient MTF TableA multi-timeframe RSI indicator with SMA smoothing, crossover gradient fill, and a live MTF table. FEATURES: - RSI with custom SMA smoothing line - Crossover Gradient Fill — color darkens as RSI moves away from cross point (bullish/bearish) - MTF Table showing 1m, 5m, 15m, 1H, 4H timeframes simultaneously - Each row shows: RSI value, SMA value, Diff (RSI−SMA), Slope direction, and Market State - Market States: H-Bull, Bull, Bear, H-Bear based on RSI/SMA position relative to 50 - Table size adjustable (tiny to huge) — mobile friendly - Table position fully customizable HOW TO USE: - RSI above SMA = Bullish momentum (green gradient) - RSI below SMA = Bearish momentum (red gradient) - H-Bull = Strong bull (both RSI & SMA above 50) - H-Bear = Strong bear (both RSI & SMA below 50) - Use MTF table to confirm trend across timeframes before entering a trade
Pine Script® 인디케이터
eaglegroup의
Relative Strength Index RSI FREE , Multi-Timeframe MTF //BPSMulti-timeframe RSI with up to three timeframes plotted simultaneously plus a 10-timeframe trend-confluence dashboard. 📊 WHAT IT SHOWS • Up to 3 RSI lines on chart from independent timeframes • 10-timeframe dashboard (D → 1m) with RSI values + direction arrows • Configurable overbought / oversold / middle levels • Confluence signals when 2 or 3 TFs agree (BULL ▲ / BEAR ▼) • Optional background highlight on trend confluence 🎯 HOW TO USE • Trade in direction of higher TF — only long when 4h+ RSI > 50 • Wait for confluence — all 3 TFs agreeing = high-probability setup • Look for RSI divergence on HTF combined with oversold on LTF for entries • Use as a filter, not a trigger — pair with structure breaks 🔑 KEYWORDS RSI, Relative Strength Index, Multi-Timeframe RSI, MTF RSI, RSI Divergence, Overbought, Oversold, Confluence, RSI Dashboard, Wilder, Momentum Oscillator
Pine Script® 인디케이터
bestpinescripts의
DivergenceLineLabelOutput_UtilitiesDivergenceLineLabelOutput_Utilities is a shared Pine v6 output library for scripts that already have their own oscillator, pivot, structure, or divergence logic but want a reusable divergence-rendering layer. It centralizes the parts of the workflow that tend to get rewritten across oscillator scripts: • HH / LH / HL / LL / EQ structure resolution • regular / hidden divergence state checks • same-structure context state checks • divergence and context color routing • standardized divergence/context label text • price-pane and oscillator-pane line helpers • price-pane and oscillator-pane label helpers • confirmed-object slot visibility helpers • live-preview line and label helpers • native-pane and price-pane pivot context box helpers On the example chart, the confirmed divergence lines, live preview lines, divergence labels, context labels, and pivot context boxes are all materially driven by this library. This library is intentionally focused on output and object management. It does not calculate RSI, MACD, VFI, volume flow, pressure, or any other oscillator. It does not confirm pivots or decide which pivots are valid. Calling scripts remain responsible for their own oscillator engine, pivot engine, comparison logic, colors, visibility modes, and signal interpretation. How to use Import the library near the top of your script in global scope, alongside any other imports, before you start calling its helpers. Typical placement: //@version=6 indicator(...) or strategy(...) import MYNAMEISBRANDON/DivergenceLineOutput_Utilities/1 as DivUtils Replace /1 with the latest published version if a newer version is available. This library expects the calling script to already know the price pivot, oscillator pivot, prior pivot reference, structure state, and output settings it wants to use. The library then handles the reusable line, label, live-preview, slot-budget, and box output layer. ➖Structure + Divergence State Helpers➖ These helpers convert pivot comparisons into structure tags and divergence/context states. divStructure(curr, prev, isHigh) Resolves HH, LH, HL, LL, or EQ from a current pivot and previous pivot. Parameters: curr (float): Current pivot value prev (float): Previous pivot value isHigh (bool): True for high-side comparison, false for low-side comparison Returns: Structure string divState(priceStruct, oscStruct) Resolves regular and hidden divergence states from price and oscillator structure tags. Returns: regularBear, regularBull, hiddenBear, hiddenBull, anyDivergence divContextState(priceStruct, oscStruct) Resolves same-structure context states from price and oscillator structure tags. Returns: highContinuation, highFade, lowContinuation, lowLift, anyContext divColor(priceStruct, oscStruct, regularBearColor, regularBullColor, hiddenBearColor, hiddenBullColor, highContinuationColor, lowContinuationColor, highFadeColor, lowLiftColor, fallbackColor) Routes a divergence or context pair to the matching caller-supplied color. Returns: Resolved color ➖Style + Label Helpers➖ These helpers keep divergence output styling consistent across scripts. divLineStyle(styleIn) Converts user-facing line-style text into Pine line-style enums. Parameters: styleIn (simple string): Solid, Dashed, or Dotted Returns: Pine line style divLabelSize(sizeIn) Converts user-facing label-size text into Pine label-size enums. Parameters: sizeIn (simple string): Tiny, Small, Normal, Large, or Huge Returns: Pine label size divContrastText(bg) Chooses black or white text based on background brightness. Parameters: bg (color): Background color Returns: Readable contrast text color divLabelText(divType, divSide, priceStruct, oscStruct, formatMode) Builds standardized divergence label text. Parameters: divType (simple string): Usually Reg or Hid divSide (simple string): Usually Bull or Bear priceStruct (string): Price structure tag oscStruct (string): Oscillator structure tag formatMode (simple string): Full, No Prefix, or Type Only Returns: Formatted label text ➖Confirmed Line Helpers➖ These helpers create and manage confirmed divergence or context lines. clearLines(lines, colors) Deletes all lines in an array and clears the matching color array. pushOscLine(lines, colors, show, active, x1, y1, x2, y2, lineColor, lineTransp, lineWidth, lineStyle, maxLines) Pushes a confirmed oscillator-pane line into line/color arrays. pushPriceLine(lines, colors, show, active, x1, y1, x2, y2, lineColor, lineTransp, lineWidth, lineStyle, maxLines) Pushes a confirmed price-pane line into line/color arrays using force_overlay=true. Note: Price helpers draw on the main chart from overlay=false oscillator scripts. Oscillator helpers draw in the script’s native pane. ➖Confirmed Label Helpers➖ These helpers create and manage confirmed divergence or context labels. clearLabels(labels, colors) Deletes all labels in an array and clears the matching color array. pushOscLabel(labels, colors, show, active, xIndex, y, labelText, styleText, lineColor, labelTextOnly, labelBgTransp, labelSize, maxLabels) Pushes a confirmed oscillator-pane label into label/color arrays. pushPriceLabel(labels, colors, show, active, xTime, labelText, ylocText, styleText, lineColor, labelTextOnly, labelBgTransp, labelSize, maxLabels) Pushes a confirmed price-pane label into label/color arrays using force_overlay=true. Note: For price-pane labels, xTime uses bar time and ylocText controls whether the label appears above or below the price bar. ➖Confirmed Slot Visibility Helpers➖ These helpers allow scripts to keep confirmed lines and labels stored while only showing the most recent visible slots. applyLineSlots(lines, colors, visibleSlots) Applies a visible slot budget to confirmed line arrays without deleting older objects. applyLabelSlots(labels, colors, visibleSlots, labelTextOnly, labelBgTransp) Applies a visible slot budget to confirmed label arrays without deleting older objects. Example: • Max Regular Lines = 1 - Live regular active = live regular only - No live regular = latest confirmed regular only • Max Regular Lines = 2 - Live regular active = live regular + latest confirmed regular - No live regular = latest two confirmed regular lines ➖Live Preview Line Helpers➖ These helpers create, update, or delete live divergence preview lines. syncLiveOscLine(ln, show, x1, y1, x2, y2, lineColor, lineWidth, lineStyle) Creates, updates, or deletes a live oscillator-pane line. syncLivePriceLine(ln, show, x1, y1, x2, y2, lineColor, lineWidth, lineStyle) Creates, updates, or deletes a live price-pane line using force_overlay=true. ➖Live Preview Label Helpers➖ These helpers create, update, or delete live divergence preview labels. syncLiveOscLabel(lbl, show, xIndex, y, labelText, styleText, lineColor, labelTextOnly, labelBgTransp, labelSize) Creates, updates, or deletes a live oscillator-pane label. syncLivePriceLabel(lbl, show, xTime, labelText, ylocText, styleText, lineColor, labelTextOnly, labelBgTransp, labelSize) Creates, updates, or deletes a live price-pane label using force_overlay=true. ➖Pivot Context Box Helpers➖ These helpers provide lightweight box utilities for scripts that want to frame confirmed pivot zones. divPivotBoxBounds(pivotValue, innerPct) Resolves a thin box around a pivot value using an inner percentage. Returns: top, bottom, ok syncNativeBox(bx, show, left, right, top, bottom, fillColor, borderColor, borderStyle, borderWidth) Creates, updates, or deletes a native-pane pivot context box. syncPriceBox(bx, show, left, right, top, bottom, fillColor, borderColor, borderStyle, borderWidth) Creates, updates, or deletes a price-pane pivot context box using force_overlay=true. ➖Divergence Model➖ Regular Bearish Divergence: Price makes HH while oscillator makes LH. Regular Bullish Divergence: Price makes LL while oscillator makes HL. Hidden Bearish Divergence: Price makes LH while oscillator makes HH. Hidden Bullish Divergence: Price makes HL while oscillator makes LL. ➖Structure Context Model➖ High-side continuation: Price makes HH while oscillator also makes HH. High-side fading: Price makes LH while oscillator also makes LH. Low-side continuation: Price makes LL while oscillator also makes LL. Low-side lifting: Price makes HL while oscillator also makes HL. Structure context is not divergence. It shows same-structure agreement between price and oscillator. ➖Important Notes➖ This library is an output utility layer only. It does not: • calculate an oscillator • confirm pivots • choose pivot anchors • decide whether a divergence is valid • decide trade direction • decide final signal logic Calling scripts remain responsible for: • oscillator calculation • pivot confirmation • price/oscillator comparison logic • visibility settings • color choices • max-line and max-label budgets • final visual interpretation For overlay=false oscillator scripts, Price + Oscillator / Price Only / Oscillator Only / Hide output modes work well. For overlay=true price-pane scripts, Price Only / Hide output modes usually make the most sense.
Pine Script® 라이브러리
MYNAMEISBRANDON의
Katana Signal AUDCAD Mean-Reversion Entry IndicatorThis indicator visualises the entry logic behind Katana EA v1.4 — an MT4 Expert Advisor I developed privately in 2022 and have been running on a live account ever since. ━━━━━━━━━━━━ HOW THE SIGNAL WORKS ━━━━━━━━━━━━ Entry is triggered only when TWO conditions align on the prior closed bar (shift=1, no repainting): BUY signal: • RSI reaches oversold extreme • Parabolic SAR is below the prior bar's low SELL signal: • RSI reaches overbought extreme • Parabolic SAR is above the prior bar's high Both conditions must be true simultaneously. Single-indicator entries are filtered out. ━━━━━━━━ WHY AUDCAD ━━━━━━━━━ AUD and CAD are both commodity-linked currencies that move together the majority of the time. When they temporarily diverge — due to oil price moves, RBA/BOC policy divergence, or risk sentiment shifts — mean-reversion setups have strong structural reasons to work. This makes AUDCAD one of the cleanest pairs for this type of strategy. The correlation rarely breaks permanently, which limits the risk of runaway adverse moves. ━━━━━━━━ DISPLAY SETTINGS ━━━━━━━━━ • BUY signal → green triangle below bar • SELL signal → red triangle above bar • Parabolic SAR → grey dots (standard display) • Background highlight on signal bars (can be disabled) • Info table top-right: SAR direction, current signal status Strategy parameters are optimised internally and not exposed — this prevents unintended parameter changes that could degrade performance. ━━━━━━━━━ MT4 AUTOMATION ━━━━━━━━━━ This indicator shows the entry signals visually. The automated version (Katana EA v1.4) executes these entries on MT4 with: • Dynamic lot sizing — auto-scales with account balance • Martingale position scaling (max 8 positions) • Hard stop-loss + 8-hour cooldown after each SL event • Active hours filter (London + New York session only) 51-month backtest results (Mar 2022 – May 2026): ✓ Net profit: +6,717% on ¥150,000 starting capital ✓ Win rate: 96.5% per trade cycle ✓ Profit factor: 1.54 ✓ Stop-losses: 33 in 51 months ✓ Modelling quality: 90% (Every Tick, 60M+ real tick data) Includes: 2022 Ukraine war oil spike, Trump tariffs, Middle East conflict periods. Free 14-day trial + full licence: payhip.com/b/j4d6F Licence delivery & support: Telegram @KaTa4649 ⚠ Requires broker with 500:1 leverage (XM Global recommended) ⚠ Not compatible with US / Canada / UK retail accounts ━━━━━━━━━ RECOMMENDED SETUP ━━━━━━━━━━━━ For visual analysis: use on AUDCAD 1H or 4H For the automated EA: runs on AUDCAD M5 Broker: XM Global Standard Account (JPY or USD) Min capital: ¥150,000 or $1,000 USD
Pine Script® 인디케이터
visibleBoa82138의
Normalized Candles RSI [Jamallo]🔹 Intro The Normalized Candles RSI is a quantitative momentum and volatility indicator designed to transform raw, trending price action into a stationary 0-100 oscillator. By passing price data through a Fractional Differencing engine and a dynamic Z-Score normalization layer, it strips away market drift and presents pure, bounded candlestick momentum. This stationary price structure is then directly overlaid with a traditional RSI and Divergence engine for highly confluent signals. 🔹 Break down Fractional Differencing (FFD): Transforms non-stationary price data into a stationary series while retaining deep historical memory (controlled by the "d" parameter). This prevents the data loss associated with standard period-to-period differencing. Normalization Engine: Applies a rolling Z-Score to the differenced data, which is then passed through a Sigmoid compression function. This mathematically forces the resulting candlesticks into a strict 0-100 range without repainting. RSI & Divergence Engine: Overlays a classic RSI with optional smoothing moving averages and Bollinger Bands. Built-in regular bullish and bearish divergence detection algorithms automatically scan for momentum exhaustion relative to the price. 🔹 Visual Guide: Indicator Anatomy The true power of this indicator lies in its visual mapping. As shown in the snapshot, the indicator pane perfectly merges the structure of raw price action directly with a classic RSI oscillator. 1:1 Structural Mapping: Notice how the normalized candles in the middle pane mirror the raw price action in the main chart exactly (highlighted by the "1:1 with overlay candle sticks" annotation). You get the exact same highs, lows, and structural candlestick patterns, but stripped of drift and mathematically squashed into a stationary box. Normalized Candles + Standard RSI: If you look at a standard RSI (bottom pane), you only see a floating line. By overlaying the normalized candles (middle pane), you can see exactly how the physical candlestick bodies and wicks behave relative to the RSI's 0-100 bounds and its smoothing moving average (the yellow line). Actionable Context: When a localized top or bottom forms, you aren't just guessing based on a purple line peaking. You can see the actual candlestick structure exhausting itself, forming wicks and reversal patterns right against the upper (70+) or lower (30-) overextended boundaries. 🔹 Settings Parameters - Diff Order (d) (0.01 - 0.99): The fractional differencing order. Higher values make the series more stationary but remove more historical memory. - Z-Score Lookback: The rolling window used to calculate the mean and standard deviation for the 0-100 normalization engine. - Sigmoid Compression Scale: Controls the elasticity of the 0-100 bounds. A higher value results in softer compression at the extremes, while a lower value makes it compress faster. - RSI Settings & Smoothing: Standard parameters for the RSI length, smoothing moving averages (SMA, EMA, VWMA, etc.), Bollinger Bands, and the divergence lookback constraints. 🔹 Credits & Acknowledgements The core RSI and Divergence engine utilized in this script is adapted from TradingView's built-in Relative Strength Index indicator code.
Pine Script® 인디케이터
Jamallo22의
Flow & Value ■Flow & Value ■Description ■NOTICE / DISCLAIMER This architecture is NOT a conventional technical analysis tool relying on a combination of superficial, lagging indicators. It is a highly advanced algorithmic volume allocation and multi-state logic simulation engine, specifically designed to extract mathematical edges through the aesthetics of subtraction. It functions as a rigorous state machine, evaluating the convergence of momentum, market structure anomalies, and liquidity distribution under live tick conditions. ■EXECUTIVE SUMMARY This script is deployed as a technical benchmark for developers building institutional-grade algorithmic dashboards directly on TradingView charts. By stripping away visual noise and focusing purely on deterministic calculations (predictive RSI reversal matrices, FVG confluence, and pro-rata volume distribution), the "Flow & Value Matrix" demonstrates the limits of Pine Script v6 in tracking historical Expected Value (EV) and dynamic session anchoring. SYSTEM USAGE (How-To / Execution Flow) Initialization: Apply the script to a high-liquidity chart. The engine immediately begins aggregating historical session data, mapping the background gradient matrix, and initializing the UI dashboard at the specified screen corner. State Evaluation (Wait Phase): The system continuously evaluates the absolute price requirements for the chosen oscillator (RSI) to reach anomaly levels on the subsequent bar. These levels are plotted dynamically. As long as the price remains outside structural imbalance zones, the UI maintains a neutral "Wait" state. Confluence Trigger (KILLZONE Phase): When the algorithm detects a geometric intersection between the predictive RSI target and a Higher Timeframe Fair Value Gap (FVG), the state transitions to "KILLZONE". This acts as a strictly mechanical alert for a high-probability mean-reversion setup. Expected Value Tracking: The internal backtesting engine evaluates historical touch-points of these target vectors against user-defined Take Profit and Stop Loss parameters, updating the EV% dynamically. A positive EV% provides mathematical confirmation of a localized edge. CONFIGURATION & FILTERING OPTIONS Dynamic Session Anchoring: Bypassing standard fixed-bar lookbacks, the engine utilizes array-based indexing to detect exact timeframe shifts (e.g., Daily or Weekly opens). This aligns the 3D volume profile matrix precisely with institutional liquidity cycles. Volatility Variance Engine: An integrated dual-band squeeze detection protocol filters out signals generated in low-volatility environments, warning the user of TP-reach failure risks. Proximity Scaler: Users can adjust the ATR multiplier to expand or contract the logical detection range of the confluence zones. SYSTEM CAPABILITIES AND LIMITATIONS Capabilities: Deterministic Price Targeting: The script calculates exact numeric thresholds required for momentum reversals prior to the bar closing, eliminating the lagging nature of traditional oscillators. Visual Synthesis of Financial Volume Data: The depth and opacity of the rendered gradient profile track live traded volume metrics pro-rata, projecting high-volume nodes (POC) in simulated 3D space. Clean State Machine Transitions: By categorizing market phases into explicit states, the UI enforces strict mechanical discipline. Limitations (Imposed by Platform API Restrictions): Lack of Sub-Minute Tick Data: TradingView does not expose raw intra-bar tick data to standard indicator scripts. The engine relies on an advanced pro-rata overlap algorithm to estimate volume distribution across price bins, which remains a mathematical approximation. Hardware Object Limits and Clipping: TradingView enforces a strict platform ceiling of 500 max labels and 500 max boxes per indicator. If the historical session depth (Number of Historical Profiles) or price bin resolution (Row Count) is scaled excessively high, the internal compiler will automatically clip and delete older visual objects. This is an absolute platform limitation, not a script defect. ARCHITECTURE & QUANTITATIVE LOGIC (Technical Specifications) Volume Allocation Engine (Pro-Rata Range Overlap Distribution) Instead of simple volume summation based on close prices, the script calculates the exact geometric intersection between each bar's High-Low range and the discrete price bins. Let bar high be $H$, bar low be $L$, and volume be $V$. For a bin with bounds GETTEX:BIN \_Top$ and GETTEX:BIN \_Bot$: If $H > L$: $Overlap = \max(0, \min(H, Bin\_Top) - \max(L, Bin\_Bot))$ $Ratio = \frac{Overlap}{H - L}$ NYSE:DV = V \times Ratio$ This loop maps across the dynamically anchored session arrays, building an institutional-grade profile matrix. Predictive Momentum Targets (Algebraic Reversal) The engine algebraically expands the RMA formula to solve for the required price variation. To reach a specific target (e.g., 70): $Target\_RS = \frac{RSI\_Target}{100.0 - RSI\_Target}$ By reversing the smoothing logic, the absolute price coordinate is locked and rendered dynamically. EV Simulation State Logic SEED_ALEXDRAYM_SHORTINTEREST1:EV \% = (Win\_Rate \times TP\%) - ((1.0 - Win\_Rate) \times SL\%)$ This discrete simulation runs continuously in the background, proving the statistical viability of the current parameter configuration. INPUT PARAMETERS REFERENCE & CRITICAL WARNINGS Group 1 & 2: Timeframe and RSI Core Macro Timeframe (htf_res): Defines the anchor for FVG anomaly detection. RSI Length / OB / OS: Configures the predictive algebraic thresholds. Group 4: Footprint Profile Settings Profile Anchor Mode (prof_mode): Toggles between static bar counts and dynamic timeframe/session arrays. Price Row Count (row_count): The resolution of the profile. CRITICAL WARNING: Setting Row Count above 50 while simultaneously increasing the Number of Historical Profiles will exponentially increase Box array generation. This will instantly exhaust TradingView's platform cap of 500 max boxes, triggering an automated visual clipping fault and deleting older profile clusters. Always balance row resolution against history depth to preserve object allocation safety. ======================================================= Flow & Value 注意／免責事項 本アーキテクチャは、遅行指標を組み合わせた表面的なテクニカル分析ツールではありません。価格アクションから不純物を徹底的に削ぎ落とす「引き算の美学」に基づき、数学的な優位性を抽出するために設計された高度な出来高按分および多状態ロジックシミュレーションエンジンです。モメンタムの逆算、市場構造の欠陥（FVG）、および流動性分布の収束をライブティック条件下で評価する厳格な状態遷移モデルとして機能します。 エグゼクティブ・サマリー 本スクリプトは、TradingView上で機関投資家レベルのアルゴリズム・ダッシュボードを構築する開発者に向けた技術的ベンチマークです。予測的RSI反転マトリックス、FVGコンフルエンス、およびプロラタ出来高按分という決定論的な計算のみに焦点を絞ることで、Pine Script v6におけるヒストリカル期待値（EV）の追跡と動的セッションアンカーの限界を実証します。 システム実行手順（インタラクティブ実行フローの詳細） 初期化: スクリプトを高流動性チャートに適用します。エンジンは即座に過去のセッションデータの集計を開始し、バックグラウンドにグラデーションマトリックスをマッピングし、画面の指定位置にUIダッシュボードを初期化します。 状態評価（待機フェーズ）: オシレーター（RSI）が次足で異常値に到達するために必要な「絶対価格」を常に逆算・評価し、動的なラインとして描画します。価格が市場の構造的インバランス（FVG）の外部にある限り、UIは中立的な「Wait」状態を維持します。 コンフルエンスターゲット（KILLZONEフェーズ）: 予測的RSIターゲットと上位足のFVGによる幾何学的な重複（インターセクション）を検知すると、状態は「KILLZONE」へと遷移します。これは高い勝率が見込める平均回帰セットアップの厳格な機械的アラートとして機能します。 期待値（EV）トラッキング: 内蔵のバックテストエンジンは、ターゲットベクターへの過去の到達履歴を、ユーザーが定義したTP（利確）およびSL（損切）パラメーターと照合し、EV%を動的に更新します。この値がプラスであることは、局所的なエッジの数学的証明となります。 構成およびフィルタリングオプション 動的セッションアンカー: 単純な指定バー数のルックバックをバイパスし、配列インデックスベースの処理により特定の時間足（日足や週足のオープン）の切り替わりを正確に検知します。これにより、3Dボリュームプロファイルが実際の機関流動性サイクルと完全に同期します。 ボラティリティ分散エンジン: ボリンジャーバンドとケルトナーチャネルを利用したデュアルスクイーズ検知プロトコルにより、低ボラティリティ環境下でのシグナルをフィルタリングし、TP未達リスクを警告します。 近接スケーラー: ATR乗数を調整することで、コンフルエンスゾーンの論理的な検知範囲を拡大または縮小することが可能です。 システムの技術的限界（達成可能な事項と不可能な事項） 達成可能な事項: 決定論的な価格ターゲティング: ローソク足が確定する前に、モメンタムが反転するために必要な正確な数値閾値を計算し、従来オシレーターの遅行性を排除します。 市場出来高データの視覚的融合: グラデーションプロファイルの奥行きと不透明度は、実際の取引高にプロラタ（比例配分）で連動し、取引密集帯（POC）をシミュレートされた3D空間上に投影します。 クリーンな状態遷移: 相場のフェーズを明確な状態（State）に分類することで、UIを通じて厳格な機械的規律を強制します。 プラットフォームの制限により不可能な事項: サブミニッツ・ティックデータの取得: TradingViewは、標準のインジケータースクリプトに対してローソク足内部の生ティックデータを提供していません。当エンジンは高度なプロラタ・オーバーラップ・アルゴリズムに依存して各価格帯への出来高分配を推定していますが、これはあくまで数学的な近似値となります。 オブジェクト上限による描画の消去（クリッピング）: TradingViewの絶対的な仕様制限により、1つのインジケーターが保持できるオブジェクト数はラベル500個、ボックス500個が上限です。過去のセッション表示数（Number of Historical Profiles）や価格帯の解像度（Row Count）を過剰に高く設定した場合、制限を超えた古い描画オブジェクトから自動消去されます。これはスクリプトの欠陥ではなくプラットフォームの仕様限界です。 アーキテクチャおよび定量的ロジック（技術仕様） 出来高按分エンジン（プロラタ値幅オーバーラップ配分ロジック） 終値に基づく単純な出来高の加算ではなく、各バーの高値・安値レンジと、事前定義された価格帯ビンとの幾何学的な重複を計算し、プロラタ処理を行います。バーの高値を $H$、安値を $L$、出来高を $V$、ビンの上限を GETTEX:BIN \_Top$、下限を GETTEX:BIN \_Bot$ とします。 $H > L$ の場合： $Overlap = \max(0, \min(H, Bin\_Top) - \max(L, Bin\_Bot))$ $Ratio = \frac{Overlap}{H - L}$ NYSE:DV = V \times Ratio$ このループを動的アンカー配列全体に対して実行し、クォンツクオリティのマトリックスを生成します。 予測的モメンタムターゲット（代数的反転計算） エンジンはRMAの数式を代数的に展開し、指定したターゲット（例：70）に到達するために必要な変動幅を導出します。 $Target\_RS = \frac{RSI\_Target}{100.0 - RSI\_Target}$ 平滑化ロジックをリバースエンジニアリングすることで、絶対価格座標をロックしチャート上に固定します。 EVシミュレーション状態ロジック SEED_ALEXDRAYM_SHORTINTEREST1:EV \% = (Win\_Rate \times TP\%) - ((1.0 - Win\_Rate) \times SL\%)$ この離散シミュレーションがバックグラウンドで継続的に実行され、現在のパラメーター構成の統計的妥当性を証明します。 全入力パラメーターの仕様と重大な警告 グループ1 & 2: Timeframe and RSI Core Macro Timeframe (htf_res): FVG異常検知のアンカーとなる上位足を定義します。 RSI Length / OB / OS: 予測的代数閾値を構成します。 グループ4: Footprint Profile Settings Profile Anchor Mode (prof_mode): 静的なバー指定と、動的な時間足/セッション配列指定を切り替えます。 Price Row Count (row_count): プロファイルの解像度です。【重大な警告】 解像度（Row Count）を50以上に設定しつつ、同時に過去のセッション表示数（Number of Historical Profiles）を増やした場合、Box配列の生成が指数関数的に増加します。これによりTradingViewのシステム上限である「500個のBox制限」を瞬時に突破し、自動消去（クリッピング）バグが誘発され古いプロファイルが消失します。オブジェクトアロケーションの安全性を確保するため、解像度と履歴の深さは必ずトレードオフのバランスを維持して運用してください。
Pine Script® 인디케이터
ALT_analyst의
RSI Candlestick Trend SuiteRSI Candlestick Trend Suite This indicator presents the Relative Strength Index (RSI) as candlesticks instead of a traditional line, providing a different perspective on momentum behavior and trend development. The script combines several RSI-based analytical tools into a single oscillator panel: • RSI Candlestick Visualization * Displays RSI values as candle structures. * Highlights momentum expansion and contraction. * Improves visibility of short-term RSI direction changes. • Moving Average Overlay * Supports SMA, EMA, WMA, VWMA, and SMMA (RMA). * Can be used to identify RSI trend direction and momentum shifts. • Bollinger Bands on RSI * Optional Bollinger Bands calculated directly from RSI values. * Adjustable standard deviation multiplier. * Optional filled band visualization. • RSI-Based Supertrend * Applies a Supertrend calculation to RSI candle data rather than price. * Helps identify momentum trend changes within the oscillator. * Customizable ATR length and multiplier settings. • Buy and Sell Markers * Optional signals generated when the RSI Supertrend changes direction. This indicator is designed to assist with momentum analysis, trend identification, and RSI-based market structure observation. It may be used alongside other forms of technical analysis and risk management techniques. The script is intended for educational and analytical purposes only and should not be considered financial advice. Short Description RSI candlestick visualization with moving averages, optional Bollinger Bands, and an RSI-based Supertrend for momentum and trend analysis.
Pine Script® 인디케이터
Onuriano의
[3Commas] BCH Heikin Ashi RSI Fade - Short Indicator BCH Heikin Ashi RSI Fade — Short Indicator 🔷 What it does: This is the signal-only companion to the BCH Heikin Ashi RSI Fade Short strategy. It tracks a virtual short position and fires webhook-ready alerts on three events — entry, Take Profit, and Stop Loss — without running a backtest engine. A virtual short is opened when the 15-minute Heikin Ashi prints a defined number of consecutive bullish candles AND the long-window RSI is above a soft-bias threshold on the same timeframe. The trade is then closed on a fixed Take Profit OR a fixed Stop Loss; no trailing, no averaging, no discretionary management. - Tracks one virtual short at a time, sized at a configurable base order (default 280 USDT, used only for the on-chart PnL display). - Dual confirmation entry: RSI(100) on 15m > 46 AND 7 consecutive Heikin Ashi bullish candles on 15m. - Hard exit pair: TP at −2.1% from entry, SL at +2.5%. - Every entry and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption. 🔷 Who is it for: - Bot operators who want to drive a DCA Bot configured for one-shot short deals directly from TradingView alerts, without a strategy backtest object on the chart. - Traders who want a clean, mechanical short signal with no averaging and no discretionary management once in trade. - Swing traders looking for systematic short exposure on BCH when local upward thrusts overrun. - Operators who prefer a lightweight signal overlay with a live status table over a full strategy tester. 🔷 How does it work: RSI Bias Filter: A long-window RSI(100) is sampled from the 15-minute timeframe via request.security with lookahead disabled (no repaint). The threshold (default 46) sits just below the midline, so the filter is satisfied during prolonged bullish drift — exactly the regime where fading strength has the highest expectancy. When RSI falls below 46, the bias is considered to have flipped bearish and the indicator stops arming new shorts. Heikin Ashi Streak Trigger: A 15-minute Heikin Ashi stream is sampled in parallel, and the indicator counts the number of consecutive same-direction HA candles using ta.barssince. When the bullish streak reaches the configured length (default 7), the trigger is armed. The default Bullish direction defines the fade-the-strength mode; switching to Bearish converts the logic into a trend-follow short. Entry: When BOTH conditions are true at bar close and no virtual position is open, the indicator records the entry price, computes the TP and SL levels, fires the entry alert, and marks a SHORT label and triangle on the chart. Exit: On each bar close while in position, the indicator checks close against the TP and SL levels. The first level reached closes the virtual short, fires the close alert, marks a TP or SL label, and accumulates realized PnL. This close-based detection matches what a polling bot sees at bar close. 🔷 Why it's unique: - Dual-Signal Confirmation: A smoothed RSI(100) filters the regime bias while Heikin Ashi times the entry. RSI on a 100-bar window changes slowly and Heikin Ashi reacts to the immediate streak, so the two conditions cannot be satisfied by the same short-lived noise — every entry requires alignment of both. - Fade-or-Follow Switch: A single input flips the HA direction filter between Bullish (fade strength, default) and Bearish (follow trend). The same engine handles two opposing signal archetypes. - Live Status Table: An on-chart table shows position status, entry price, TP/SL levels, live RSI and HA streak values, and an entry-armed flag — so the current state of the virtual position is always visible at a glance. - DCA Bot Integration: Each event emits a fully-formed JSON alert payload tagged with the action type, so the indicator can drive a DCA Bot configured for one-shot deals directly through TradingView alerts. 🔷 Considerations Before Using the Indicator: Signal-Only Design: This is an indicator, not a strategy. It does not place orders or run a backtest engine — it tracks a virtual position purely to time alerts and display state. The base order size input is virtual and feeds only the on-chart PnL display; real position sizing happens on the bot. Market & Timeframe: Calibrated for BCHUSDT on the 15-minute timeframe. The RSI-and-Heikin-Ashi combination is portable to other liquid crypto pairs that respect mean-reversion behavior, but the filter thresholds (RSI level, HA streak length) should be reviewed before redeployment. Live shorting requires a margin or perpetual venue. Reference Performance: Because behavior mirrors the companion strategy 1:1, the strategy's backtest is a useful reference. Over a 177-trade backtest on BCHUSDT 15m (November 19, 2025 — June 3, 2026), the matching strategy logic returned +0.88% with a 0.52% maximum equity drawdown, 61.02% of trades profitable (108 / 177), and a profit factor of 1.169. The 177-trade sample is above the ~100-trade floor for statistical relevance. The value proposition is structural risk capping over a meaningful sample, not aggressive alpha. Trending Markets: In strong sustained uptrends, the indicator will continue to arm short entries and will register stop-outs as price grinds higher. This is by design — the logic is positioned for ranges and rotations, not breakouts. The RSI(100) > 46 filter limits exposure to confirmed bullish regimes only, which is where fading has an edge; a regime change to a stronger trend will require manual oversight or a wider Stop Loss. Past Performance: Past results do not guarantee future performance. Always demo-test before deploying live capital, and size as one part of a diversified portfolio. 🔷 How to Use It: 🔸 Adjust Settings: Open the indicator inputs and review the Base Order Size (virtual), the RSI filter (timeframe / length / condition / level), and the Heikin Ashi filter (timeframe / streak length / direction). Defaults are calibrated for BCHUSDT 15m — recalibrate per asset before deploying. 🔸 Fill the Webhook Fields: Enter your DCA Bot's Bot ID, Email Token, and Pair (QUOTE_BASE) into the DCA Bot Webhook inputs. These values are injected into every alert payload. 🔸 Create the alert: Add one alert on the indicator using "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field. The indicator will emit JSON payloads for short entry and close — formatted for direct DCA Bot consumption. 🔷 INDICATOR SETTINGS Base Order Size (USDT): Virtual size used only for the status-table / PnL display. Real sizing happens on the bot. RSI Timeframe / Length / Condition / Level: RSI bias filter applied to the host symbol. HA Timeframe / Streak / Direction: Heikin Ashi consecutive-candle trigger. Direction defines fade (Bullish) vs follow (Bearish) mode. Take Profit (%) / Stop Loss (%): Fixed distance exits from entry. DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload. Visualization: Toggle Avg Entry / TP / SL plot lines, fill labels, signal triangles, and the status table (status, entry price, TP/SL levels, live RSI and HA streak, entry-armed flag). Brand Watermark: Configurable text, position, size, and transparency. 👨🏻‍💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented. __ The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Pine Script® 인디케이터
3Commas의
[3Commas] BCH Heikin Ashi RSI Fade - Short StrategyBCH Heikin Ashi RSI Fade — Short Strategy 🔷 What it does: This is a short-only strategy that fades an extended Heikin Ashi bullish streak, confirmed by a long-window RSI bias filter on the same timeframe. A short entry is opened when the 15-minute Heikin Ashi prints a defined number of consecutive bullish candles AND the smoothed RSI is above a soft-bias threshold — the combination targets exhausted bullish thrusts on BCH that have run far enough to invite a pullback. The exit is a fixed Take Profit OR a fixed Stop Loss; no trailing, no averaging, no second-guessing. - Single base order, sized at 2.8% of equity by default. - Dual confirmation entry: RSI(100) on 15m > 46 AND 7 consecutive Heikin Ashi bullish candles on 15m. - Hard exit pair: TP at −2.1% from average entry, SL at +2.5%. - Every entry and exit emits a webhook-ready JSON alert payload for direct DCA Bot consumption. 🔷 Who is it for: - Swing traders looking for systematic short exposure on BCH when local upward thrusts overrun. - Traders who want a clean, mechanical short setup with no averaging and no discretionary management once in trade. - Bot operators who want to drive a DCA Bot configured for one-shot short deals via webhook. - Risk-conscious operators — at default settings the worst-case per-trade loss is ~0.07% of equity (well inside the 5–10% per-trade risk band). 🔷 How does it work: RSI Bias Filter: A long-window RSI(100) is sampled from the 15-minute timeframe via request.security with lookahead disabled (no repaint). The threshold (default 46) sits just below the midline, so the filter is satisfied during prolonged bullish drift — exactly the regime where fading strength has the highest expectancy. When RSI falls below 46, the bias is considered to have flipped bearish and the strategy stops looking for new shorts. Heikin Ashi Streak Trigger: A 15-minute Heikin Ashi stream is sampled in parallel, and the strategy counts the number of consecutive same-direction HA candles using ta.barssince. When the bullish streak reaches the configured length (default 7), the trigger is armed. The default Bullish direction defines the fade-the-strength mode; switching to Bearish converts the strategy into a trend-follow short. Entry: When BOTH conditions are true at host-bar close, a short position is opened at the base order size. The base order is configurable as Market (default) or Limit at the bar's close. Exit (OCO): Take Profit and Stop Loss are issued as a paired OCO order through strategy.exit. The first level reached closes the position and automatically cancels the other side — no trailing, no partial exits. 🔷 Why it's unique: - Dual-Signal Confirmation: A smoothed RSI(100) filters the regime bias while Heikin Ashi times the entry. RSI on a 100-bar window changes slowly and Heikin Ashi reacts to the immediate streak, so the two conditions cannot be satisfied by the same short-lived noise — every entry requires alignment of both. - Fade-or-Follow Switch: A single input flips the HA direction filter between Bullish (fade strength, default) and Bearish (follow trend). The same engine handles two opposing strategy archetypes. - Bounded Trade Risk: With a single base order and a hard Stop Loss, the maximum loss per trade is exactly base size × SL%. At defaults that is ~7 USDT on 10,000 — structural risk capping without any complex sizing logic. - DCA Bot Integration: Each event emits a fully-formed JSON alert payload tagged with the action type, so the strategy can drive a DCA Bot configured for one-shot deals directly through TradingView alerts. 🔷 Considerations Before Using the Strategy: Market & Timeframe: Calibrated and tested on BCHUSDT 15m. The RSI-and-Heikin-Ashi combination is portable to other liquid crypto pairs that respect mean-reversion behavior, but the filter thresholds (RSI level, HA streak length) should be reviewed before redeployment. Live shorting requires a margin or perpetual venue; the spot chart is used here for signal generation and backtesting. Performance Profile: This is a low-volatility, defensive short. Over the 177-trade backtest the strategy returned +0.88% with a 0.52% maximum equity drawdown — a return-to-DD ratio near 1.7, with a profit factor of 1.169. The value proposition is structural risk capping over a meaningful sample, not aggressive alpha. Size accordingly within a diversified portfolio. Trending Markets: In strong sustained uptrends, the strategy will continue to fire short entries and will incur stop-outs as price grinds higher. This is by design — the strategy is positioned for ranges and rotations, not breakouts. The RSI(100) > 46 filter limits exposure to confirmed bullish regimes only, which is where fading has an edge; a regime change to a stronger trend will require manual oversight or a wider Stop Loss. Sample Size & Parameters: The full-period backtest produced 177 closed trades, above the ~100-trade floor for statistical relevance. If a redeployment on another pair produces fewer than ~100 trades, either extend the period or lower the HA streak length to 5, and re-save the relaxed value as the new default so the publication continues to satisfy the "Default Properties match" rule. Commission & Slippage: Defaults are set to 0.055% commission and 3 ticks slippage, matching the source bot's configured fee rate. Update both inputs to match your exchange's actual fees before relying on the backtest numbers. Past Performance: Past results do not guarantee future performance. Always demo-test before deploying live capital, and size the strategy as one part of a diversified portfolio. 🔷 STRATEGY PROPERTIES Symbol: BINANCE:BCHUSDT — strategy is portable to any BCH / USDT pair (live shorting on a margin or perpetual venue). Timeframe: 15M Test Period: November 19, 2025 — June 3, 2026 (~6.5 months). Initial Capital: 10,000 USDT. Order Size per Trade: 280 USDT (single base order, no averaging). Max Capital Deployed: 280 USDT per trade (~2.8% of equity). Worst-Case Loss per Trade: ~7 USDT (~0.07% of equity). Commission: 0.055% per trade. Slippage: 3 ticks. Margin for Short Positions: 100% (leverage 1x). Indicator Settings: Default Configuration. Base Order: 280 USDT, Market by default (Limit toggle available). Take Profit: 2.1% below average entry (no trailing). Stop Loss: 2.5% above average entry (close trade). RSI Filter: 15m RSI(100) > 46. Heikin Ashi Filter: 15m Heikin Ashi, 7 consecutive bullish candles. Strategy: Short Only. 🔷 STRATEGY RESULTS ⚠️ Remember, past results do not guarantee future performance. Net Profit: +87.53 USDT (+0.88%) Max Equity Drawdown: 52.55 USDT (0.52%) Total Closed Trades: 177 Percent Profitable: 61.02% (108 / 177) Profit Factor: 1.169 🔷 How to Use It: 🔸 Adjust Settings: Open the strategy inputs and review the Base Order Size, RSI filter (timeframe / length / level), and the Heikin Ashi filter (timeframe / streak length / direction). Defaults are calibrated for BCHUSDT 15m — recalibrate per asset before deploying. 🔸 Results Review: Run a full-period backtest and confirm Max Drawdown stays inside your personal risk band. Validate that the closed-trade count is statistically meaningful (≥ 100 is a reasonable floor). Use realistic commission and slippage for your exchange. 🔸 Create alerts to trigger the DCA Bot: Add one alert on the strategy using "Any alert() function call". Paste the DCA Bot's webhook URL into the alert's Webhook field, and fill the Bot ID, Email Token, and Pair inputs on the script. The strategy will emit JSON payloads for short entry and exit — TP, SL, or manual close — formatted for direct DCA Bot consumption. 🔷 INDICATOR SETTINGS Base Order Size (USDT): USDT amount opened on the short entry. Use LIMIT for Base: Toggle between Market (default, more conservative for backtest) and Limit at bar close. RSI Timeframe / Length / Condition / Level: RSI bias filter applied to the host symbol. HA Timeframe / Streak / Direction: Heikin Ashi consecutive-candle trigger. Direction defines fade (Bullish) vs follow (Bearish) mode. Take Profit (%) / Stop Loss (%): Fixed distance exits from average entry. DCA Bot Webhook: Bot ID, Email Token, and Pair fields injected into every alert payload. Visualization: Toggle Avg Entry / TP / SL plot lines, fill labels, status table (status, avg entry, TP/SL levels, live RSI and HA streak, entry-armed flag, cumulative realized net profit). Brand Watermark: Configurable text, position, size, and transparency. 👨🏻‍💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented. __ The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Pine Script™ 전략
3Commas의
CC RSI by CCnati_AICC RSI by CCnati_AI — Publish Description ================================================================ CC RSI is a standardized implementation of the Relative Strength Index configured to be used with CC Stoch RSI and CC OBV by CCnati_AI as a three-indicator momentum suite. Rather than leaving settings open to interpretation, this script locks RSI at length 14 with a 14-period SMA overlay and bands at 70/50/30. The high-contrast pure green and yellow color scheme is optimized for readability on both desktop and mobile screenshots. The value of this publication is consistency — when all users in a shared analysis workflow run identical settings and colors, chart screenshots become an unambiguous common language for collaborative analysis regardless of timeframe or asset class.
Pine Script® 인디케이터
CCnati_AI의
RSI Candle Coloring**RSI Candle Coloring** Visualize momentum strength instantly — without glancing at a separate RSI panel. This indicator dynamically recolors each candlestick based on the current RSI value, letting you read overbought and oversold conditions directly from the price chart. Both the RSI period and threshold levels are fully adjustable to fit your trading style. --- **🎨 Color Zones** 🔴 RSI ≥ 70 — Overbought / Strong Bullish Momentum 🟠 RSI 60–69 — Bullish Bias / Approaching Overbought ⚪ RSI 41–59 — Neutral / Consolidation Zone 🔵 RSI 31–40 — Bearish Bias / Approaching Oversold 🟢 RSI ≤ 30 — Oversold / Strong Bearish Momentum --- **⚙️ How It Works** RSI is calculated using the standard closing price over a configurable lookback period (default: 14). Each candle is then replotted via plotcandle with a color mapped to its RSI reading. Wick and border colors remain neutral gray to keep the focus on momentum signals. --- **🔧 Inputs** • RSI Period — Lookback length for RSI calculation (default: 14) • Overbought Level — Upper threshold for deep red coloring (default: 70) • Oversold Level — Lower threshold for deep green coloring (default: 30) --- **📌 Use Cases** • Instantly identify overbought and oversold conditions on the price chart • Spot momentum shifts and neutral consolidation zones at a glance • Combine with support/resistance levels or moving averages for entry/exit confirmation • Works as a cleaner alternative to a traditional RSI subplot --- **📝 Notes** • Works on any symbol and timeframe • Candles are redrawn using plotcandle — disable your chart's default candles to avoid overlap (uncheck "Candles" in chart settings) • The 60 and 40 intermediate thresholds are fixed by design to create a consistent 5-zone color gradient; only the overbought and oversold extremes are user-adjustable
Pine Script® 인디케이터
fdq677k9km의
RSI Sequential Exhaustion & Divergence**RSI Sequential Exhaustion & Divergence — Multi-Factor Oscillator** **What it is** A single RSI-based reversal oscillator for spotting momentum exhaustion, then filtering and grading those signals so only the better-supported ones stand out. It is one integrated tool, not a pile of separate indicators sharing a pane. **What it plots** - The RSI line with a glow/gradient style coloured by momentum side, plus overbought/oversold/midline levels and an optional zone fill. - Sequential Exhaustion signal arrows (▲/▼) at qualifying turns. - Regular and hidden price–RSI divergence as lines and small labels, de-cluttered so the pane stays readable. - A compact 5-row dashboard: Signal (direction · conviction % · age), RSI state, Confluence score, Context (trend/range + volatility state), and a Data-health read. - An optional calibration panel and a set of hidden data-window outputs (EXP_*) for chaining into other scripts. **Why these components are combined (and how they work together)** Each part is here to fix a specific weakness of the part before it, so the result is one filtered, graded signal: 1. A bare RSI overbought/oversold reading whipsaws, and naive divergence over-fires. So the script uses two *structured* exhaustion cues instead: **Sequential Exhaustion** (the RSI makes three consecutive deeper pushes into an extreme zone and the fourth bar turns back out — a defined trigger, not just "RSI is low"), and a **divergence engine** that adds an independent reversal cue and is de-cluttered with a cooldown plus a minimum-gap filter. 2. Both cues are counter-trend by nature, and counter-trend entries fail in two situations: strong directional trends, and volatility cascades. To handle the first, an **HTF trend-bias filter** and an **ADX regime filter** suppress signals when a higher timeframe or strong ADX says the trend is intact. To handle the second, a **volatility-cluster filter** (a self-exciting intensity built from returns) proportionally raises the bar for new signals exactly when clustering makes mean-reversion most dangerous — and because it is price-only, it also works on volume-less symbols. 3. To tell which surviving signals are worth more, a **Confluence grade (0–5)** fuses five reasonably-independent reads of the same bar (HTF bias, ranging regime, a recent divergence, volume, and the RSI momentum turn). **Multi-timeframe agreement (3×/5×/15×)** is deliberately kept *separate* and applied as a conviction *multiplier* rather than blended into the score, because it is the one genuinely independent check — full agreement boosts conviction, contradiction damps it. 4. To stay honest about whether any of this is working on your symbol, a **calibration tracker** logs every signal and, after a fixed horizon, records whether price actually followed through (a move of at least X·ATR in the signal's direction), reporting a measured *past* hit-rate by grade tier with a Wilson 95% confidence interval. A **data-integrity read** (bar range, HTF-feed freshness, volume reliability) surfaces an OK / DEGRADED / CRITICAL status so the tool never silently scores on bad data. **What is original here** The individual techniques — RSI, divergence, ADX, ATR, volume reads, self-exciting intensity, Wilson intervals — are publicly documented. The original work is the integration: a structured RSI-exhaustion trigger gated by a proportional volatility-cluster filter, graded by a confluence score that is scaled by independent higher-timeframe agreement, and continuously audited by a built-in self-calibration tracker that reports honest past follow-through by tier. Components were chosen so each covers a distinct weakness; redundant filters were left out to keep one clear signal. **How to use** 1. Add it to a chart. Defaults suit intraday index/futures; direction works on any symbol, while the volume confluence factor needs real traded volume. 2. Take signals in the direction the context filters allow. Prefer a higher conviction % and stronger higher-timeframe agreement; treat low-grade cues as noise (raise "Min confluence to allow signal" to suppress them). 3. Respect the volatility-cluster warning — it marks regimes where mean-reversion is most likely to fail. 4. Use the optional calibration panel as a sanity check on the tool's own past signals, never as a forward prediction. 5. Spot vs futures: a cash/spot index has no real volume. "Volume Mode" auto-detects this, and you can borrow a traded-volume series from a related futures contract; the "Data" row shows the active mode. **Notes** All signals and divergence confirm on closed pivots and do not repaint. Divergence labels appear "Pivot Right" bars after the turn, which is inherent to honest pivot detection. **Disclaimer** For education and information only. This is not financial, investment, or trading advice and guarantees no outcome. Signals describe current and past conditions; they do not predict the future. The calibration figures describe past behaviour only — they are not a backtest or a probability of future results. Volume-based readings depend on the data feed and are unreliable on instruments without real volume. Trading carries substantial risk of loss; you are solely responsible for your own decisions and risk management. Consider consulting a licensed professional.
Pine Script® 인디케이터
Market_Logic_India의
RSI-T (RSI + Time) RSI-T RSI with Time Parameter Technical White Paper & User Guide Dimitrios Kataliakos May 2026 Based on the theory: "Market as Expanding Dough" (Agora os Diogkoumeno Zymari) Table of Contents Table of Contents 1 1. Executive Summary 1 2. Theoretical Foundation 1 2.1 The Market as Expanding Dough 1 2.2 Time as a Curvature Factor 1 2.3 Regime Classification 1 3. Mathematical Definition 1 3.1 Core Formula 1 3.2 Parameters 1 3.3 Derived Metrics 1 4. Timeframe Analysis 1 4.1 Timeframe Weight 1 4.2 Recommended Settings by Timeframe 1 4.3 Multi-Timeframe Confluence 1 5. User Guide 1 5.1 Installation (TradingView) 1 5.2 Reading the Indicator 1 5.3 Trading Rules 1 Rule 1: Regime Identification First 1 Rule 2: Do Not Short Persistent Bull 1 Rule 3: Do Not Buy Persistent Bear 1 Rule 4: Momentum Zone is Decision Zone 1 Rule 5: Watch the Divergence 1 5.4 Practical Examples 1 6. Backtest Strategy 1 6.1 Strategy Logic 1 6.2 Risk Management 1 6.3 Pine Script Strategy 1 6.4 Metrics to Evaluate 1 7. Limitations & Future Work 1 7.1 Known Limitations 1 7.2 Future Development 1 8. Appendix 1 8.1 Files Included 1 8.2 Version History 1   1. Executive Summary The RSI-T (RSI with Time) is a technical indicator that extends the classic Wilder RSI by adding a third parameter: the duration of time price action remains in an extreme zone. While the standard RSI measures the magnitude of recent price changes, it fails to capture the persistence of momentum regimes. The RSI-T solves this by quantifying how long the RSI stays above or below threshold levels, providing traders with a tool that distinguishes between transient spikes and sustained directional moves. The indicator is derived from the economic theory of markets as expanding systems, where price does not tend toward equilibrium but rather expands unevenly, creating zones of compression and expansion. The RSI-T operationalizes this concept by treating the time spent in extreme RSI territory as a measure of regime strength. 2. Theoretical Foundation 2.1 The Market as Expanding Dough Traditional economic theory assumes markets tend toward equilibrium. The theory underlying RSI-T proposes an alternative model: the market behaves like expanding dough, where nominal prices continuously inflate, but the expansion is uneven across time and sectors. This creates regions of rapid expansion (bubbles, momentum regimes) and compression (consolidations, mean-reversion zones). The three analytical layers of this model are: • Geometry (Curvature): How price curves in space, measured through momentum and convexity. This corresponds to the RSI dimension of the indicator. • Temperature (Volatility): The thermal energy of the market, measured through implied and realized volatility. This informs the threshold sensitivity. • Cohesion (Liquidity): The structural integrity of price action, related to order flow and market microstructure. This provides context for regime classification. 2.2 Time as a Curvature Factor The critical insight of RSI-T is that time spent at extremes is itself information. When the RSI remains above 70 for one bar, it may be a transient spike. When it remains above 70 for eight consecutive bars, the market has entered a different regime entirely. Standard RSI treats both situations identically. RSI-T does not. In the dough metaphor, this corresponds to a region that is not just expanded, but has been expanding for a sustained period. The longer the expansion persists, the more the local structure of the market has reorganized around the new price level, and the less likely a simple mean-reversion is to occur. This is consistent with empirical findings in momentum literature: assets that have been trending tend to continue trending, and the duration of the trend is a stronger predictor of continuation than the magnitude alone. 2.3 Regime Classification The RSI-T framework classifies market states into distinct regimes based on the combination of RSI level and time at extreme: Regime RSI Condition Time Condition NEUTRAL Between oversold and overbought Counter = 0 MOMENTUM_BULL RSI > Overbought threshold 2 to N-1 bars MOMENTUM_BEAR RSI < Oversold threshold 2 to N-1 bars PERSISTENT_BULL RSI > Overbought threshold N or more bars PERSISTENT_BEAR RSI < Oversold threshold N or more bars Where N is the persistence threshold (default: 5 bars). In the persistent regimes, traditional mean-reversion signals (e.g., sell when RSI > 70) are weakened or inverted.   3. Mathematical Definition 3.1 Core Formula The RSI-T value is calculated as: RSI_T = clamp( RSI + (bars_at_extreme × time_weight × direction), 0, 100 ) Where: • RSI = Standard Wilder RSI(close, period) • bars_at_extreme = consecutive bars where RSI > threshold_OB or RSI < threshold_OS • time_weight (α) = scaling factor per bar of persistence (default: 1.2) • direction = +1 if RSI > threshold_OB, -1 if RSI < threshold_OS, 0 otherwise • clamp() = constrains result to 3.2 Parameters Parameter Default Range Description period 14 5 – 50 RSI lookback period (Wilder smoothing) threshold 70 / 30 55–90 / 10–45 Overbought / Oversold boundary time_weight (α) 1.2 0.0 – 5.0 Signal boost per bar at extreme max_boost 20 5 – 40 Maximum cumulative boost (cap) persist_bars (N) 5 2 – 20 Bars required for persistent regime 3.3 Derived Metrics • Divergence = RSI_T − RSI: Measures the total impact of the time parameter. When divergence is zero, RSI-T equals classic RSI. When divergence is large, the time dimension is providing significant additional information. • Time Counter (bars_extreme): The raw number of consecutive bars spent above/below the threshold. This is the primary regime classifier. • Regime Label: Categorical classification (NEUTRAL, MOMENTUM_BULL, MOMENTUM_BEAR, PERSISTENT_BULL, PERSISTENT_BEAR) derived from the combination of RSI level and time counter.   4. Timeframe Analysis The RSI-T works across all timeframes, but its interpretation changes because the time counter has different weight depending on bar duration. 4.1 Timeframe Weight Timeframe 1 Bar = 5 Bars (Persistent) = Interpretation 1 minute 1 minute 5 minutes Micro-momentum, scalping noise common 5 minutes 5 minutes 25 minutes Intraday momentum phases 15 minutes 15 minutes 1.25 hours Session-level regime shifts 1 hour 1 hour 5 hours Intraday trend confirmation 4 hours 4 hours 20 hours Multi-session directional bias Daily 1 day 1 week Swing-level regime classification Weekly 1 week 5 weeks (~1 month) Position-level trend strength Monthly 1 month 5 months Macro regime identification 4.2 Recommended Settings by Timeframe Timeframe Period Time Weight Persist Bars 1–5 min 14 0.5 – 0.8 8 – 12 15–60 min 14 0.8 – 1.2 5 – 8 4H / Daily 14 1.0 – 1.5 4 – 6 Weekly 14 1.5 – 2.0 3 – 5 Monthly 14 2.0 – 3.0 3 – 4 The general principle: shorter timeframes need more bars to confirm persistence (more noise to filter), while longer timeframes establish regimes faster because each bar carries more weight. 4.3 Multi-Timeframe Confluence The highest-conviction signals occur when multiple timeframes agree. For example, if the daily RSI-T shows PERSISTENT_BULL and the weekly RSI-T enters MOMENTUM_BULL, this represents a multi-timeframe momentum alignment that significantly increases the probability of trend continuation. Conversely, if the daily is in PERSISTENT_BULL but the weekly RSI-T is declining from a recent extreme, this divergence between timeframes suggests the persistent regime may be nearing exhaustion.   5. User Guide 5.1 Installation (TradingView) 1. Open TradingView and navigate to the chart of your chosen instrument. 2. Click Pine Editor at the bottom of the screen. 3. Click New and select New indicator. 4. Delete all existing code and paste the RSI-T Pine Script (v6) code. 5. Click Add to chart. The RSI-T panel appears below the price chart. 6. Adjust parameters via the Settings gear icon on the indicator. 5.2 Reading the Indicator Blue line: Classic RSI. This is the baseline reference. Orange/Red line: RSI-T. When this diverges from the blue line, the time parameter is active and providing additional information. Histogram (bottom): Scaled time counter showing the number of bars spent at the extreme zone. Green background: Persistent bull regime. The RSI has been above the overbought threshold for N or more bars. Red/orange background: Persistent bear regime (red) or momentum bear/bull (orange/blue). Blue background: Momentum bull. RSI above overbought for 2 to N-1 bars. Early-stage momentum zone. 5.3 Trading Rules Rule 1: Regime Identification First Before making any trading decision, identify the current regime from the background color. In NEUTRAL regime, traditional RSI-based mean-reversion strategies apply normally. In MOMENTUM or PERSISTENT regimes, mean-reversion signals are weakened or inverted. Rule 2: Do Not Short Persistent Bull When the RSI-T shows persistent bull (green background), do not initiate short positions based on overbought readings. The persistence signal indicates that the market has reorganized around the uptrend and further upside is more likely than immediate reversal. Wait for the regime to reset (counter returns to zero) before considering mean-reversion trades. Rule 3: Do Not Buy Persistent Bear The inverse of Rule 2. When persistent bear is active (red background), do not buy dips based on oversold readings. The selling pressure has established itself as a regime, not a transient condition. Rule 4: Momentum Zone is Decision Zone The blue/orange background (momentum zone, 2 to N-1 bars) is where decisions are made. This is the transitional phase where the market is testing whether it will establish a persistent regime or revert. Tighter stops and smaller positions are appropriate here. Rule 5: Watch the Divergence When RSI-T diverges significantly from classic RSI (large divergence value), the time dimension is dominating. A sudden collapse of this divergence (counter drops to zero) often precedes sharp reversals, as the accumulated time pressure releases. 5.4 Practical Examples Scenario RSI-T Reading Action RSI at 75, counter = 1 Momentum bull (blue bg) Standard caution, normal position sizing RSI at 75, counter = 7 Persistent bull (green bg) Do NOT short. Trailing stop on existing longs RSI at 42, counter = 0 Neutral Normal analysis applies. No regime signal RSI at 25, counter = 6 Persistent bear (red bg) Do NOT buy dips. Wait for regime exit RSI at 72, counter drops from 5 to 0 Regime exit Alert: potential reversal. Tighten stops   6. Backtest Strategy 6.1 Strategy Logic The RSI-T Strategy for backtesting converts the indicator into actionable entries and exits. The core logic uses regime transitions as signals: Long Entry: • RSI-T crosses above the overbought threshold AND the time counter reaches the momentum threshold (2 bars), confirming directional commitment. • Alternative: Enter when the regime transitions from NEUTRAL to MOMENTUM_BULL (catching the early phase of a potential persistent move). Long Exit: • The time counter resets to zero after being in persistent bull (regime exit signal). • Alternative: RSI-T crosses below the midline (50) from above. Short Entry: • RSI-T crosses below the oversold threshold AND the time counter reaches the momentum threshold. Short Exit: • Time counter resets to zero after persistent bear, or RSI-T crosses above midline. 6.2 Risk Management • Position size: 10% of equity per trade (adjustable in strategy settings). • Stop loss: Based on ATR multiplier (default 2x ATR-14) to account for regime volatility. • Trailing stop: Activates once position reaches 1.5x risk in profit. • No pyramiding by default (can be enabled for persistent regime continuation). 6.3 Pine Script Strategy A complete Pine Script v6 strategy file (rsi_t_strategy_v6.pine) is provided alongside this document. The strategy includes configurable parameters for entry/exit rules, position sizing, stop-loss, and trailing stop. It can be applied to any instrument and timeframe in TradingView for historical backtesting. 6.4 Metrics to Evaluate When backtesting the RSI-T strategy, focus on the following metrics to validate the theoretical framework: • Win Rate in Persistent vs. Momentum vs. Neutral regimes (the theory predicts higher win rates in persistent regimes for trend-following entries). • Average trade duration across regimes (persistent regime trades should be longer and more profitable). • False signal rate: How often does momentum (blue background) fail to convert to persistent (green background)? • Regime exit accuracy: What percentage of regime exits (counter reset) are followed by actual reversals within N bars? • Comparison vs. classic RSI strategy (same entry rules without the time parameter) to isolate the value added by the time dimension.   7. Limitations & Future Work 7.1 Known Limitations • The RSI-T is a lagging indicator by nature. The time counter requires bars to accumulate before signaling persistence, meaning the earliest phase of a move is not captured. • In choppy or range-bound markets, the counter may produce false starts, briefly entering momentum zone before resetting. The persist_bars threshold helps filter these but cannot eliminate them entirely. • The linear time_weight model (each bar adds the same boost) may not be optimal. Markets may exhibit non-linear acceleration, where the 10th bar at extreme is more significant than the 3rd. • The indicator does not incorporate volume, volatility, or cross-asset information. It is purely price-derived. 7.2 Future Development • Non-linear time weighting: Exponential or logarithmic boost curves that better reflect the accelerating nature of regime establishment. • Volatility-adjusted thresholds: Dynamic overbought/oversold levels that adjust based on current implied volatility (high-vol environments may require wider thresholds). • Fast/Slow RSI divergence: Comparing RSI-T across different periods (e.g., RSI-T(7) vs RSI-T(21)) to measure regime acceleration, as described in the original theory. • Cross-asset regime correlation: Using the RSI-T regime of correlated assets (e.g., SPX for individual stocks) as a confirmation layer. • Machine learning optimization: Using historical data to optimize time_weight and persist_bars parameters per asset class and market regime. 8. Appendix 8.1 Files Included File Description rsi_t_v6.pine RSI-T indicator for TradingView (Pine Script v6) rsi_t_strategy_v6.pine RSI-T backtest strategy for TradingView (Pine Script v6) rsi_t_indicator.py RSI-T Python implementation for custom backtesting 8.2 Version History Version Date Changes 1.0 May 2026 Initial release: RSI-T indicator, strategy, white paper Copyright © 2026 Dimitrios Kataliakos. All rights reserved. This document and the associated indicator code are proprietary work based on the original theory of markets as expanding systems.
Pine Script® 인디케이터
tokyogate의
Machine Learning RSI | AI Classification & Ranking (Zeiierman)█ Overview The Machine Learning RSI | AI Classification & Ranking (Zeiierman) is an adaptive RSI intelligence system that combines momentum analysis, historical analog recognition, machine learning classification, confidence scoring, and dynamic trend management into a single framework. Rather than interpreting RSI solely through traditional overbought and oversold thresholds, the indicator examines how similar RSI environments have behaved historically and uses those observations to classify current market conditions. The script transforms RSI into a multi-dimensional feature space, stores historical market behavior, identifies the closest historical analogs, and allows those analogs to vote on future directional bias. An adaptive feature-optimization engine then continuously learns which RSI characteristics provide the greatest predictive value under current market conditions. The result is a hybrid system that blends: • Multi-dimensional RSI analysis • Historical analog matching • Machine learning classification • Adaptive feature weighting • Rank & confidence scoring • AI-driven trend management █ Why is this one unique This is not a normal RSI. It is a full analog classification engine built in Pine Script v6. It turns RSI behavior into an 8-feature market fingerprint, stores historical examples, labels them by future outcome, finds the closest past situations, lets those analogs vote, then converts the result into an adaptive ML RSI, rank/confidence scores, signals, and an ML-modulated Supertrend. ⚪ What it does At a high level: 1. Builds 8 RSI-derived features It does not only use the RSI value. It models: RSI level, slope, acceleration, distance from 50, percentile rank, RSI volatility, fast/slow RSI spread, and smoothed RSI regime. That means each bar becomes a multi-dimensional “state” of momentum, not just “RSI is 63.” 2. Creates a memory bank Each confirmed bar is stored with its feature snapshot and a future outcome label. The label is based on whether price moved up or down after a fixed horizon, scaled by ATR. That is the learning dataset. 3. Uses K-nearest-neighbor analog matching For the current bar, the script scans the historical bank and finds the closest past examples. It uses a Lorentzian-style compressed distance: log(1 + abs(feature difference)) That is good because it reduces the impact of outliers. Huge feature mismatches do not completely dominate the model. 4. Lets analogs vote Nearest neighbors vote bull or bear, weighted by distance. Closer matches matter more. The output becomes: analogScore, bias direction, agreement fraction, and gap tightness. 5. Auto-optimizes feature weights This is one of the most sophisticated parts. The script uses a Fisher-discriminant-style calculation to determine which RSI features currently best separate bullish vs. bearish outcomes. Then it rescales those weights and smooths them over time. So the model can learn that, for example, RSI slope matters more on one instrument, while RSI percentile or regime matters more on another. 6. Builds rank and confidence Signals are not triggered just because the model flips bullish or bearish. They must pass a quality system: Rank blends agreement, distance tightness, trend alignment, volatility health, regime fit, slope fit, smoothness, persistence, and penalties for chop or early flips. Confidence focuses more on analog agreement, tightness, persistence, and slope fit. This is much better than a simple buy/sell oscillator because it asks: “Is this setup actually supported?” 7. Adds adaptive Supertrend The Supertrend is not static. Its band width changes based on ML conviction. High conviction tightens the trailing stop. Low conviction or chop widens it. That makes the trend system responsive without being blindly reactive. ⚪ Why it is good The strongest part is that it combines machine learning logic, technical architecture, and trade-quality filtering into a single system. Most TradingView indicators are fixed formulas: RSI crosses 30, MACD crosses, Supertrend flips, moving average slope changes. This code differs because it creates a small local learning model directly in Pine. The unique edge is the combination of: • Feature engineering: RSI is transformed into 8 separate behavioral dimensions. • Historical analog learning: Current market conditions are compared to past similar conditions. • Distance-weighted voting: Closer historical examples have more influence. • Auto feature weighting: The system adapts which features matter most. • ATR-based outcome labeling: Learning is normalized by volatility, not just raw price movement. • Quality scoring: Signals require both rank and confidence. • Adaptive trend logic: The ML engine not only generates oscillator signals but also modifies Supertrend behavior. That combination is rare in Pine Script. TradingView supports advanced data structures such as arrays, matrices, and user-defined types, but many public scripts still use simpler procedural indicator logic. This script uses those advanced structures as a true modeling framework. ⚪ What makes it sophisticated The code actually implements an AI-style classification workflow: Input features → labeled memory → nearest-neighbor search → weighted classification → confidence scoring → adaptive output. That is a real machine-learning pattern. But this script goes further than a basic KNN signal tool because it adds: • Auto-optimized feature weights using class separation. • Rank/confidence gates instead of raw prediction signals. • Chop, volatility, and trend filters to reduce bad market conditions. • ML-driven Supertrend adaptivity rather than using ML only for arrows. • Non-repainting signal discipline by firing on confirmed bars only. ⚪ Why It’s Marketable Most RSI indicators treat every reading the same. This tool takes a different approach by analyzing how similar RSI conditions performed in the past and evaluating the current setup against those historical patterns. It only generates signals when multiple factors align, including confidence, trend direction, volatility, and market structure. What makes it valuable is that it transforms RSI from a simple momentum oscillator into a context-aware decision framework. Rather than reacting to fixed overbought and oversold levels, it identifies recurring market behaviors, measures the similarity of current conditions to historical examples, and assigns a quality score to each opportunity. It then filters out low-probability environments and dynamically adjusts its trend management based on the strength of the model's conviction. The result is a more selective, adaptive, and intelligent signal engine that helps traders focus on higher-quality setups instead of every RSI fluctuation. This moves well beyond the capabilities of a conventional TradingView RSI indicator. ⚪ Main weakness It is not deep learning, and it does not train a neural network. It is an online analog classifier. That is still legitimate AI-style logic. Also, because it learns from historical analogs inside the chart, performance depends heavily on market regime, symbol, timeframe, memory depth, and filters. █ How It Works ⚪ Machine Learning Feature Engine Most RSI indicators analyze a single value. The Machine Learning RSI transforms RSI into a complete momentum fingerprint, consisting of eight independent characteristics that describe how momentum behaves beneath the surface. The model analyzes: • RSI Value • RSI Slope • RSI Acceleration • Distance From Neutral (50) • RSI Percentile Rank • RSI Volatility • Fast vs Slow RSI Spread • RSI Regime Structure Features cur = Features.new( rOsc / 100.0, scale01(rOsc - rOsc , winLen), scale01(rOsc - rOsc - (rOsc - rOsc ), winLen), math.abs(rOsc - 50.0) / 50.0, ta.percentrank(rOsc, winLen) / 100.0, scale01(ta.stdev(rOsc, 14), winLen), scale01(rOscF - rOscS, winLen), scale01(ta.ema(rOsc, 20) - 50.0, winLen) ) Together these features create a much richer representation of market behavior than traditional RSI calculations. Instead of asking: “Where is RSI?” The model asks: “What type of momentum behavior is currently occurring?” ⚪ Historical Analog Memory The indicator continuously builds a memory bank of historical market behavior. Every confirmed bar is stored together with its RSI fingerprint and the future outcome that followed. row = array.from( fVal, fSlp, fAcc, fMid, fPct, fChn, fSpr, fReg, float(outcome) ) bank.add_row(0, row) Over time the model accumulates hundreds or even thousands of historical observations. Each observation becomes a real market example the system can reference later. Rather than relying entirely on fixed formulas, the indicator learns from historical market behavior. ⚪ AI Classification Engine Once the memory bank has been built, the Machine Learning RSI begins searching for historical situations that closely resemble the current market. The comparison is performed across all eight RSI features simultaneously. g = cur.gapTo(row, wts) Similarity is measured using a weighted Lorentzian distance function. compress(float d) => math.log(1.0 + math.abs(d)) Unlike traditional distance calculations, logarithmic compression reduces the influence of extreme outliers and prevents a single feature from dominating the comparison process. This creates a more stable and robust analog matching system. The objective is not to find identical charts. The objective is to find historical momentum environments that behaved similarly. ⚪ Historical Analog Voting After locating the closest historical matches, the system allows them to vote on the current market direction. Closer analogs receive greater influence while weaker matches contribute less. float w = 1.0 / (1.0 + n.gap) v.score := v.score + n.cls * w The weighted votes are combined into a final classification score. eng.analogScore := vote.total > 0 ? vote.score / vote.total : 0.0 This process produces: • Directional Bias • Analog Agreement • Classification Strength • Similarity Quality • Market Conviction Rather than attempting to predict the future directly, the model asks: “How did the most similar momentum environments behave when they occurred previously?” ⚪ Adaptive Feature Optimizer Markets are constantly changing. Features that are highly predictive in one environment may become less useful in another. To solve this problem, the Machine Learning RSI includes an adaptive feature optimization engine. The model continuously evaluates which RSI characteristics are doing the best job separating bullish outcomes from bearish outcomes. float f = math.pow(mB - mBe, 2) / (vB + vBe + 1e-6) This process is based on Fisher Discriminant Analysis. Features that consistently separate winning conditions from losing conditions receive larger weights. Features that lose predictive power gradually receive less influence. wts.value := wAuto.get(0) wts.slope := wAuto.get(1) wts.accel := wAuto.get(2) wts.mid := wAuto.get(3) This allows the model to adapt automatically to changing market conditions without requiring constant manual optimization. ⚪ Rank & Confidence Engine Most indicators generate signals immediately after a condition is met. The Machine Learning RSI goes several steps further. Every setup receives two independent evaluations. • Rank → Measures setup quality. • Confidence → Measures model conviction. Rank evaluates: • Historical agreement • Analog quality • Trend alignment • Volatility conditions • Regime structure • Momentum consistency • Market stability Confidence evaluates: • Historical consensus • Analog clustering • Directional consistency • Signal persistence • Structural confirmation setup.rank := rankScore(…) setup.conf := confScore(…) Signals are only generated once both quality and confidence requirements have been satisfied. This helps filter weaker market conditions while prioritizing stronger opportunities. ⚪ AI-Driven Learning System The Machine Learning RSI does not simply memorize historical outcomes. It learns what constitutes a meaningful outcome. Each historical observation is classified based on future movement relative to current volatility. outcome = moveFwd > 2 * bandFwd ? 3 : moveFwd > bandFwd ? 2 : moveFwd > 0 ? 1 : moveFwd < -2 * bandFwd ? -3 : moveFwd < -bandFwd ? -2 : moveFwd < 0 ? -1 : 0 • Large bullish moves receive stronger bullish labels. • Large bearish moves receive stronger bearish labels. • Small movements receive weaker classifications. This allows the model to distinguish meaningful market behavior from ordinary noise. ⚪ ML Supertrend System The indicator includes an adaptive Machine Learning Supertrend that responds to model conviction. Unlike traditional Supertrends that rely on a fixed ATR multiplier, the ML Supertrend dynamically adjusts its sensitivity based on classification strength. mlDrive = math.abs(convSmoothed) * 0.5 + eng.gapTight * 0.3 + eng.agreeFrac * 0.2 As conviction increases: • Bands tighten • Trend changes become faster • Stops become more responsive As conviction decreases: • Bands widen • Noise tolerance increases • Whipsaws are reduced adaptMult = stMultBase * (1.0 + stMlResp * (1.0 - mlDrive)) This creates a trend-following system that adapts to the strength of the model’s conviction rather than relying solely on volatility. █ How To Use ⚪ Reading The ML RSI The Machine Learning RSI ranges from 0 to 100. • Values above 50 suggest bullish momentum conditions dominate the market. • Values below 50 suggest bearish momentum conditions dominate the market. • Readings above 70 typically indicate strong bullish conditions, while readings below 30 suggest strong bearish pressure. ⚪ Reading The Signals The Machine Learning RSI generates signals when the model detects a meaningful shift in market conditions and that shift passes both its quality and confidence requirements. • Long signals indicate that the classification engine has identified a bullish market environment supported by historical analog agreement, trend structure, and market conditions. • Short signals indicate that the classification engine has identified a bearish market environment supported by historical analog agreement, trend structure, and market conditions. ⚪ Using The ML Supertrend The ML Supertrend acts as both a trend filter and a dynamic trailing stop. • When the Supertrend flips bullish, the model considers the market to be operating in an uptrend regime. • When the Supertrend flips bearish, the model considers the market to be operating in a downtrend regime. █ Settings Price Source: controls the price data used to build every RSI feature inside the learning engine. Base RSI Length: controls the main RSI period used to create the ML RSI and its feature set. Memory Depth: controls how many historical bars the model stores and searches when looking for similar market conditions. Analog Count (k): controls how many closest historical matches are allowed to vote on the current market direction. Show Signal Markers: toggles the Long and Short signal markers on the chart. Candle Coloring: colors candles based on the current ML Supertrend regime. Min Rank to Signal: controls the minimum setup-quality score required before a signal can appear. Min Confidence to Signal: controls the minimum model conviction required before a signal can appear. Trend Gate: requires signals to align with the ML Supertrend direction. Volatility Band: filters signals so they only appear in healthier volatility conditions. Min Vol Rank: controls the lower volatility threshold required for signals. Chop Filter: blocks signals during choppy, range-bound market conditions. Learning Sensitivity: controls how large a future move must be before the model treats it as a meaningful historical outcome. Auto-Optimize Weights: allows the model to automatically learn which RSI features are most important. Adaptation Speed: controls how quickly the learned feature weights adjust to changing market behavior. Feature Weights: manually control the importance of each RSI feature when Auto-Optimize Weights is disabled. Show ML Supertrend: toggles the adaptive ML Supertrend line, cloud, and trend visuals. Supertrend Source: controls the price source used to build the ML Supertrend bands. ATR Multiplier: controls the base distance of the ML Supertrend from price. ML Band Adaptivity: controls how strongly model conviction adjusts the Supertrend band width. RSI Signal Line Type: selects the moving average style displayed on the ML RSI. RSI Signal Line Length: controls the smoothing length of the RSI signal line. BB StdDev: controls the Bollinger Band width when using SMA + Bollinger Bands. Colors: customize signal markers, candle coloring, ML RSI colors, Supertrend colors, cloud colors, and signal line visuals. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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