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Structure Probability Blocks [JOAT]Structure Probability Blocks Introduction Structure Probability Blocks is an open-source market structure and quality-zone overlay. It detects confirmed structure breaks, searches for the most relevant opposing candle, scores the resulting block, and highlights the strongest active block without filling the chart with redundant zones. The problem it solves is order block clutter. Many zone tools draw every candidate equally. Structure Probability Blocks filters for impulse, candle quality, relative volume, recency, and overlap so the displayed blocks have cleaner context. The enhanced chart layer also projects BOS/CHoCH break rails, impulse guide lines, and compact score labels directly beside the structure event. Core Concepts 1. Confirmed Pivot Tracking Swing highs and lows are confirmed using symmetric pivots. Because pivots require bars on both sides, this is intentionally delayed and non-repainting. 2. Break Qualification A structure break requires price to close through the tracked pivot and meet a minimum ATR-based impulse requirement. 3. Seed Candle Search After a break, the script searches backward for the best opposing candle candidate. The score considers body quality, wick behavior, volume rank, and recency. 4. Strongest Active Block Highlight Among active blocks, the highest-scored block receives stronger border and midline treatment. Weaker overlapping blocks can be removed when the overlap guard is enabled. 5. Break Rails and Impulse Guides When a qualified BOS or CHoCH forms, the indicator can draw a dashed horizontal break rail from the pivot level to the right edge and a dotted impulse guide from the selected seed candle to the break close. The on-chart tag includes score, zone range, drive, RVOL, and break price. 6. Strongest Block Ribbon The highest-scored active block is also projected as a subtle ribbon using plot/fill logic. This gives a clean strongest-zone read even when several historical boxes remain visible. Features Confirmed structure breaks: Breaks require closed-bar confirmation Quality-scored blocks: Scores combine impulse, candle structure, relative volume, and recency BOS/CHoCH context: Block labels identify continuation or character-shift context BOS/CHoCH break rails: Dashed projected levels mark the exact pivot level that price broke Impulse guide lines: Dotted guides connect the seed candle to the break close Expanded score tags: Labels show score, zone range, drive, RVOL, and break level Prime block highlight: Highest active score receives stronger visual emphasis Strongest block ribbon: Highest active zone is projected as a lightweight filled band Overlap guard: Keeps the stronger of overlapping active blocks Prime candle tint: Candles can be softly colored by the strongest active structure bias Broken block handling: Keep, fade, extend, or remove resolved blocks Top-right dashboard: Active count, bull/bear count, best score, break state, last pulse, volume rank, and break mode Alerts: New bullish and bearish quality block events Input Parameters Structure: Pivot Length: Swing confirmation sensitivity Search Span: Bars searched for a seed candle Break Impulse: Minimum ATR expansion required for a break Volume Span: Lookback used for volume rank Min Score: Minimum block quality score required How to Use This Indicator Step 1: Use the dashboard to identify current bull/bear structural bias. Step 2: Focus on the strongest highlighted active block first. Step 3: Use the dashed BOS/CHoCH rail as the exact structural break reference. Step 4: Treat broken/faded blocks as resolved context rather than fresh opportunities. Step 5: Combine with a regime or pressure tool before making directional decisions. Indicator Limitations Pivot confirmation is delayed by the pivot length, which is intentional non-repainting behavior A high block score does not imply a guaranteed reaction Volume rank can be less useful on instruments with unreliable volume The script identifies structural context, not complete risk-defined trades Originality Statement Structure Probability Blocks is original in its quality-scored seed selection, impulse qualification, overlap prioritization, prime block highlighting, and compact structural dashboard. It does not copy third-party source code. Disclaimer This open-source indicator is provided for educational and informational purposes only. It is not financial advice. Structural zones can fail, and traders should always use independent analysis and proper risk management. -Made with passion by jackofalltrades
مؤشر Pine Script®
من ‎officialjackofalltrades‎
[3Commas] UNI Vault Grid - UNI - Indicator UNI Vault Grid — UNI — Indicator 🔷 What it does: This indicator is the visual + signal-only companion to the static geometric grid strategy for Uniswap (UNI/USDT). It draws all 57 grid levels on the chart, fires Buy and Sell signals on each close-cross event, tracks a virtual P&L card (simulating what the matching strategy would have done), and ships webhook alerts for routing signals to a connected grid bot. Use it when you want the grid logic running on your chart without strategy.* engine — for visual confirmation, manual entries, or external bot routing. - 57 geometrically-spaced levels between Low (2.979) and High (4.171) drawn as horizontal lines - Buy / Sell labels printed at each level on cross events - Virtual P&L tracker mirrors the strategy version's bookkeeping - Static range — grid does NOT shift up when price exits the band (trailing-up disabled) - Webhook-ready alert payload for connected grid bot 🔷 Who is it for: Traders who want to visualize the grid and signal layer on their chart without running the strategy engine. Bot operators routing signals from TradingView alerts to a connected grid bot via webhook. Discretionary swing traders who want grid levels as decision support while executing manually. Users comparing live signal flow against backtested behavior of the matching strategy publication. 🔷 How does it work: Grid Construction: On the first bar, the indicator pre-computes 57 price levels between Low (2.979) and High (4.171) using geometric spacing (≈ 0.61% step). Each level is drawn as a horizontal line — green for the lowest, red for the highest, aqua for the middle levels. Signal Generation: On every confirmed bar, the indicator checks each level for a close-cross-down (Buy signal) or close-cross-up (Sell signal) against the next level above. A label is printed at the level on each cross. Buy labels are aqua, Sell labels are fuchsia and include the realized virtual P&L. Virtual P&L Tracker: The indicator maintains its own bookkeeping that mirrors the strategy version — when a Buy level fills, qty is recorded; when the next-up Sell level crosses, the per-level P&L is added to the virtual net. Stats card displays Net P&L, Max Drawdown, Total Fills, Win Rate, and Profit Factor. Webhook Alerts: A grid_start JSON payload (Bot ID, Email Token, Pair) is fired once when the first bar enters the configured backtest window. This is informational — grid bots are typically configured on the bot interface directly. 🔷 Why it's unique: Identical grid math to the strategy publication — same 57 levels, same step, same cross-detection logic. The virtual P&L card lets you see live what the strategy version is doing in backtest, but on an indicator pane (no strategy.* engine, no order fills). Static range fidelity — no trailing-up. The grid stays locked exactly where you configured it, which makes risk envelope easy to reason about before deploying capital. Brand watermark + stats overlay — consistent visual layer with all other 3Commas Vault Grid publications. 🔷 Considerations Before Using the Indicator: Market & Timeframe: Calibrated for a 15-minute chart on UNI/USDT spot pairs. The runtime warning label flags any TF other than 15m. Higher TFs produce far fewer fills; lower TFs (1m, 5m) generate more signals but slow chart rendering. Limitations: The indicator does NOT place orders — it only signals. If you wire the alerts to a grid bot, the bot is responsible for executing entries and exits. The virtual P&L card is an in-indicator simulation only, not a real account P&L. It does not include funding, slippage, or partial fills. Backtesting & Demo Testing: The strategy version is the canonical reference for realized backtest performance (with commission, slippage, and the strategy engine's order book). This indicator's virtual P&L is a useful estimate but cannot replace the strategy tester report. Demo-trade your bot for at least one month before any live deployment. Parameter Adjustments: The grid range, level count, and per-level amount should be re-evaluated for each deployment period. UNI's "fair range" shifts over time — a grid calibrated for one regime may not work for the next. The default 2.979 — 4.171 envelope reflects UNI's recent volatility band as of publication. 🔷 INDICATOR SETTINGS Grid High Price — Upper boundary of the grid range (default 4.171). Grid Low Price — Lower boundary of the grid range (default 2.979). Grid Levels — Total number of price levels (default 57). Grid Mode — Geometric (constant % spacing) or Arithmetic (constant absolute spacing). Amount per Level (USDT, ref) — Notional per fill (default 175.44) — used for virtual P&L only. Trailing Up — Disabled by default. Enables adaptive grid behavior on breakout (off keeps grid static). Trail Up Threshold % — % above High at which trailing fires (only used if Trailing Up enabled). Shift Up Magnitude % — How much of the current range to shift when trailing-up fires. Limit by Date Range — Constrain virtual backtest to a specific date window (default Jan 19 — May 19 2026). Initial Capital (USDT, ref for % calc) — Used to convert virtual P&L into a % figure on the stats card. Show grid lines on chart — Toggle horizontal level lines (red top, green bottom, aqua middle). Show fill labels on chart — Toggle Buy / Sell labels printed on each cross. Show stats card — Toggle the on-chart virtual backtest summary. Stats card position — Where to anchor the stats card. Show watermark — Toggle the brand watermark. Watermark text / position / size / transparency — Controls for the watermark overlay. Recommended TF (for warning) — Timeframe baseline for runtime warning (default 15m). Webhook (Grid Bot) — Bot ID, Email Token, Pair label for signal routing. 🔷 ALERTS grid_start — Fires once when the first bar enters the configured backtest window. Webhook-ready JSON payload with Bot ID, Email Token, and Pair label. 🔷 RELATED PUBLICATIONS Strategy version (with full Strategy Tester backtest report): [https://www.tradingview.com/script/Dc5iUh2F-3Commas-UNI-Vault-Grid-UNI-USDT/ 👨🏻‍💻💭 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.
مؤشر Pine Script®
من ‎3Commas‎
2
[3Commas] UNI Vault Grid - UNI/USDT UNI Vault Grid — UNI/USDT 🔷 What it does: This strategy implements a static geometric grid trading system for Uniswap (UNI), designed to capture range-bound oscillations between a configurable High and Low price boundary. It pre-computes 57 price levels using geometric spacing (≈ 0.61% step), buys at each level on close-cross-down, and sells at the next level up on close-cross-up. Unlike adaptive grid variants with trailing logic, this version stays locked to the original range — no auto-shift up. Profit comes from capturing the spread between adjacent grid lines on every oscillation; the structure is designed for periods where UNI consolidates within a defined band rather than trending strongly in one direction. - 57 geometrically-spaced levels between Low (2.979) and High (4.171) - Buy on close-cross-down through an unfilled level; sell on close-cross-up through the next level - Fixed notional per level (175.44 USDT default), all fills equally sized - No trailing up — grid stays locked to the configured range - No stop loss — positions held until matching sell level is hit 🔷 Who is it for: Swing traders who identify ranging conditions on UNI and want to monetize the oscillations. Bot operators who automate grid execution through webhook integration with a connected bot. Spot accumulators with a directional view that UNI will remain inside the configured boundaries during the deployment period. Risk-conscious participants who prefer predictable accumulation envelopes (capped at full-grid-filled at the Low boundary). 🔷 How does it work: Long Entry: When close crosses down through an unfilled grid level, the strategy opens a long position sized to the per-level notional amount (default 175.44 USDT). Each level operates independently — multiple buys can stack across the ladder simultaneously during a downward swing, creating a structured accumulation pattern. Short Entry: Not used — this is a long-only spot grid. Exit Management: For each filled level, the strategy places a limit exit at the next level up. When close crosses up through that target, the position closes and the level becomes available to buy again. No stop loss is used; the grid's Low boundary defines the structural worst-case accumulation point. Static range — the grid does NOT shift when price exits the boundary. If price breaks above High, the strategy stops opening new buys until price returns inside the band. If price breaks below Low, all 57 levels are filled and the position holds unrealized loss until either the average is recovered or the user manually closes. 🔷 Why it's unique: Pure static range design — most grid implementations include trailing-up logic that compromises the original risk envelope when price trends. This variant stays locked to the configured range, which gives a fully predictable worst-case scenario: maximum unrealized loss is bounded by (Current Price − Grid Low) × Total Position at Low. Traders know exactly what they are signing up for before deploying capital. Calibrated for UNI's DEX-token volatility — the 0.61% step and 57-level ladder are dense enough to capture UNI's higher-frequency intraday oscillations (typical of mid-cap altcoins with active DEX flow) while keeping the configured envelope tight. This contrasts with sparser grids used for majors like ETH/BTC where each step needs to be wider to match the larger absolute moves. Bot Integration — entry alerts ship with webhook-ready JSON payloads. The grid_start alert fires once on first activation. Bot ID, Email Token, and pair label are exposed as inputs. 🔷 Considerations Before Using the Indicator: Market & Timeframe: This strategy is calibrated for a 15-minute chart on UNI/USDT spot pairs with active intraday range. Fill density depends directly on how often close crosses grid levels. Higher timeframes (1h+) produce far fewer fills; lower timeframes (1m, 5m) generate more fills but slow backtests on TradingView's plan limits. The runtime warning label flags any TF other than 15m. Limitations: No stop loss and no trailing range adjustment. The strategy is structurally exposed to two failure modes: (1) Price breaks above High — strategy idles, no new fills until reversal back into range (2) Price breaks below Low — all 57 levels fill, unrealized loss accumulates until average is recovered or position is manually closed This is the trade-off of a pure static grid: predictable risk envelope, but no adaptive protection against trend breakouts. Pair this strategy with manual range validation and an exit plan before deploying capital. Backtesting & Demo Testing: Always validate the grid range and step size on historical data for the specific instrument. UNI's volatility profile shifts across DeFi cycles — what was a ranging instrument can become a strong-trend instrument and vice versa, especially around governance events, fee-switch proposals, or DEX-flow rotations. Re-test on your own venue using venue-specific commission and slippage. Demo-trade for at least one month before any live deployment. Past performance is not indicative of future results. Parameter Adjustments: Commission defaults to 0.10% (Bybit spot taker). Adjust for your venue — Binance Spot ~0.10%, Coinbase Advanced ~0.50%, OKX Spot ~0.08%. The grid range and level count should be re-evaluated for each new deployment period — UNI's "fair range" shifts over time, and a grid calibrated for one regime may not work for the next. 🔷 STRATEGY PROPERTIES Symbol: BYBIT:UNIUSDT (Uniswap / Tether Spot). Strategy is generic — works on any spot pair with sufficient depth and structural range. Timeframe: 15m chart (mandatory — strategy is calibrated for this TF). Test Period: Jan 19, 2026 — May 19, 2026 (≈ 4 months / last 120 days). Initial Capital: 11,000 USDT (10,000 investment + 1,000 buffer for commission and grid fluctuations). Order Size per Trade: 175.44 USDT per grid level. Total investment envelope = 10,000 USDT (57 levels × 175.44). Maximum simultaneous position count: 57 levels. Commission: 0.10% taker — Bybit spot reference; adjust for your venue. Slippage: 2 ticks — typical taker execution on liquid UNI/USDT pairs. Margin for Long and Short Positions: 100% (1× leverage assumed; no margin amplification). Indicator Settings: Default Configuration. Grid Mode: Geometric High Price: 4.171 Low Price: 2.979 Levels: 57 Amount per Level: 175.44 USDT Trailing Up: disabled Step (computed): ≈ 0.61% Strategy: Long Only. 🔷 STRATEGY RESULTS ⚠️ Remember, past results do not guarantee future performance. Net Profit: Max Drawdown: Total Closed Trades: Percent Profitable: Profit Factor: Average Trade: Average # Bars in Trades: Reference TradingView Pine backtest on BYBIT:UNIUSDT (15m chart), Jan 19 2026 — May 19 2026 (≈4 months / last 120 days at time of publication). The reference period captures UNI's choppy post-recovery phase, which is structurally favorable for static range grids — the strategy fills repeatedly as price oscillates through the band. Built-in GRID Bot backtest reference (last 120 days): +23.15% net profit / 1,290 trades. The Pine simulation differs slightly from the bot backtester due to fee structure, slippage model, and close-based level-crossing detection vs. exchange-side limit orders. Re-test on your own venue with venue-specific commission before live deployment. 🔷 How to Use It: 🔸 Adjust Settings: Set the grid High and Low boundaries based on UNI's observed range over the past 1–3 months. The default 2.979 — 4.171 envelope reflects UNI's recent volatility band. Amount per level should be sized so that filling the entire ladder (all 57 levels = 10,000 USDT exposure) does not exceed your risk budget. Scale linearly to your equity. Always confirm you are on a 15-minute chart — the runtime warning label flags mismatches. 🔸 Results Review: Verify Maximum Drawdown stays within your personal risk budget. The strategy operates with no stop loss, so the worst-case is the full grid being filled at the Low boundary while price continues lower. Calculate this scenario before going live: if every level fills and price drops 10% below the grid Low, what is your unrealized loss? That is your hard floor. Re-test on your own venue with realistic commission and slippage. 🔸 Create alerts to trigger the connected bot: The strategy exposes a "grid_start" alert that fires once when the first bar enters the configured backtest window. Configure the alert in TradingView with the webhook URL pointing to your bot's signal endpoint. The Bot ID, Email Token, and Pair label can be set in the script's inputs. Note that grid bots are typically configured directly within the bot interface, so this alert is primarily informational for monitoring purposes. 🔷 INDICATOR SETTINGS Grid High Price — Upper boundary of the grid range. Grid Low Price — Lower boundary of the grid range. Grid Levels — Total number of price levels between Low and High (default 57). Grid Mode — Distribution of levels: Geometric (constant % spacing) or Arithmetic (constant absolute spacing). Amount per Level (USDT) — Notional value of each buy fill. Total Investment (USDT, ref) — Reference total capital deployed across all levels (informational). Trailing Up — Disabled by default; enable to make grid shift up on breakout (turns this into adaptive grid behavior). Trail Up Threshold % — Percentage above High at which trailing-up triggers (only used if Trailing Up enabled). Shift Up Magnitude % — How much of the current range to shift when trailing-up fires (only used if Trailing Up enabled). Limit by Date Range — Constrain backtest to a specific date window. Show grid lines on chart — Toggle visual display of all level lines. Recommended TF (for warning) — Timeframe baseline for the runtime mismatch warning (default 15m). Stats card / Watermark — Display layer controls for on-chart backtest summary and branding. Webhook — Bot ID, Email Token, and Pair label for connected bot signal routing. 👨🏻‍💻💭 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.
استراتيجية Pine Script®
من ‎3Commas‎
1
Market Stucture shifts Strength Ranker [Quantum Edge]📌 Overview Market Structure Shifts Strength Ranker is an institutional market structure detection tool built by Quantum Edge Capital LLC that goes beyond simply labeling BOS and CHoCH — it scores every structural break using a weighted multi-factor ranking model inspired by Support Vector Machine (SVM) classification. Every time a Break of Structure or Change of Character fires, it receives a 0–100 confidence score based on the volume, momentum, and displacement quality of the break. The result: you instantly know not just that structure broke, but how convincingly it broke. ⚙️ How It Works Market Structure Detection Uses standard pivot high/low detection (configurable lookback) to track the last confirmed swing high and swing low. Structure logic: BOS (Break of Structure) — Price closes beyond the last swing extreme in the direction of the existing trend. Confirms trend continuation. CHoCH (Change of Character) — Price closes beyond the last swing extreme against the existing trend direction. Signals a potential trend reversal — the first sign that smart money may be shifting sides. BOS labels render with a solid line; CHoCH labels render with a dashed line to visually distinguish continuation from reversal signals at a glance. SVM-Inspired Strength Scoring Each confirmed break is scored using a three-factor weighted model: Raw Score = ( R V O L × W v ) + ( R S I n o r m × W r ) + ( D i s t n o r m × W d ) Raw Score=(RVOL×W v ​ )+(RSI norm ​ ×W r ​ )+(Dist norm ​ ×W d ​ ) The raw score is then passed through a sigmoid function scaled to 0–100: Score = 100 1 + e − ( r a w S c o r e × 2 − 1 ) Score= 1+e −(rawScore×2−1) 100 ​ The three scoring components are: Factor Formula What It Measures Relative Volume (RVOL) volume / SMA(volume, 20) Whether the break occurred on elevated institutional activity RSI Momentum abs(RSI - 50) / 50 Distance of momentum from equilibrium — stronger trending momentum = higher score Break Distance (close - pivot) / ATR How far price closed beyond the structure level normalized by volatility Each factor has an independent user-configurable weight (default: 0.4 / 0.3 / 0.3). Weights must be tuned to your instrument and strategy — volume-heavy instruments like ES and NQ may benefit from higher RVOL weight; momentum-driven assets may favor RSI weight. Score Interpretation Score > 70 — High-conviction structural break. Elevated volume, strong momentum, and significant displacement. Treat as a valid structural signal worth acting on. Score 30–70 — Moderate conviction. Structure confirmed but one or more factors are weak. Use additional confluence before entering. Score < 30 — Low-conviction break. Likely a weak or manipulative break. Flag as a potential false breakout or Judas swing — no trade. 🎨 Visuals BOS label — Solid horizontal line at the broken pivot level, score printed below (bullish) or above (bearish) the midpoint of the break CHoCH label — Dashed horizontal line at the broken pivot level, same score label Both labels display the break type (BOS or CHoCH) on the first line and the SVM score on the second line, color-coded green (bullish) or red (bearish) 📋 Dashboard The on-chart Structural SVM Ranking table displays the last 5 structural breaks in reverse chronological order, each row showing: Column Content Break Type BOS or CHoCH Direction Bullish (green) or Bearish (red) SVM Score 0–100 score, color-coded: green if >70, red if <30, neutral if 30–70 This gives you a running institutional-grade audit of recent structural quality — at a glance you can see whether the current trend is being built on high-conviction or weak breaks. 🛠️ Settings Group Setting Default Description Market Structure Pivot Lookback 5 Bars left and right required to confirm a swing high/low Market Structure Show BOS On Toggle Break of Structure labels Market Structure Show CHoCH On Toggle Change of Character labels SVM Ranking Relative Volume Weight 0.4 Weight of RVOL in the scoring formula (0–1) SVM Ranking RSI Momentum Weight 0.3 Weight of RSI deviation in the scoring formula (0–1) SVM Ranking Break Distance Weight 0.3 Weight of ATR-normalized break distance (0–1) SVM Ranking ATR Length for Normalization 14 ATR period used to normalize the break distance factor Dashboard Show Dashboard On Toggle the SVM ranking table Dashboard Position Top Right Top Right / Bottom Right / Bottom Left Dashboard Size Small Tiny / Small / Normal / Large / Huge 📋 How to Use Use CHoCH as your bias trigger — A CHoCH is the first signal that the prior trend is failing. Do not enter immediately on a CHoCH — wait for the subsequent BOS in the new direction to confirm the trend has actually shifted. CHoCH = awareness. BOS = confirmation. Require score > 60 minimum for entries — Structural breaks with scores below 60 reflect weak displacement, low volume, or poor momentum. These are potential manipulation traps. Filter them out by only acting on breaks that score above your threshold. Use high-scoring BOS as continuation entries — A BOS scoring 75+ means strong volume, strong momentum, and meaningful displacement from the prior structure level. These are the breaks where institutional participation is clear. Trail stops above/below the broken pivot. Combine with liquidity context — A high-scoring BOS that also swept external liquidity (BSL or SSL) before breaking structure is the highest-probability setup. The sweep clears the stops; the BOS confirms the new delivery direction. Watch score decay across sequential BOS — If BOS scores are declining on each successive break (e.g., 75 → 62 → 48), momentum is weakening inside the trend. A CHoCH at the end of a declining score sequence is a high-conviction reversal signal. Tune weights to your instrument — On ES and NQ, volume is highly meaningful — increase Relative Volume Weight to 0.5–0.6. On forex or instruments with less reliable volume data, reduce it and increase Break Distance Weight or RSI Momentum Weight. ⚠️ Notes Built in Pine Script v6. The SVM scoring model is a linear weighted classifier normalized through a sigmoid function — it is not a trained machine learning model but approximates SVM decision boundary logic through calibrated feature weighting. Pivot detection requires Pivot Lookback bars to the right of a swing to confirm it, meaning labels appear N bars after the actual swing high/low. This is by design for non-repainting accuracy. Each pivot level resets after triggering a break — the same level cannot fire twice. This prevents duplicate labels on prolonged consolidation near a pivot. The dashboard retains the last 5 breaks only. On very active sessions, earlier breaks scroll off the table. Weights do not need to sum to 1.0, but keeping the total near 1.0 maintains the sigmoid scaling behavior as intended. © Quantum Edge Capital LLC. Licensed under CC BY-NC-SA 4.0. Non-commercial use only.
مؤشر Pine Script®
من ‎Prolific-Prophets‎
Regime Execution Strategy [JOAT]Regime Execution Strategy Introduction Regime Execution Strategy is an open-source TradingView strategy that integrates adaptive forecast context, extreme-channel state, trend pressure, relative volume, and EMA structure into a single rule-based execution model. The strategy is designed to be realistic, non-repainting, and readable rather than curve-fit to one symbol. The problem it solves is trade filtering. A single signal source can trigger too often in poor conditions. Regime Execution Strategy requires multiple independent votes before entries are allowed, then uses ATR-based stop and target logic for consistent risk framing. Core Concepts 1. Adaptive Forecast Bias The strategy estimates a dynamic mean and band structure. Price above or below the adaptive mean contributes to directional bias. 2. Extreme Channel Bias Persistent upper and lower channel levels define a midpoint and directional state. The channel contributes a second independent vote. 3. Pressure and Structure Gate Momentum, pullback location, and fast/slow EMA structure contribute to the regime score. A minimum vote count and relative-volume filter are required before entry. longSignal = barstate.isconfirmed and bullVotes >= voteThreshold and bullRegime and (longBreakout or longReclaim) 4. ATR-Based Risk Management Stops and targets are derived from ATR and position average price. The strategy also includes max drawdown and max intraday filled order risk controls. Features Integrated regime detection: Forecast, channel, pressure, and EMA structure combine into a regime score Multi-vote entry logic: Entries require several independent components to align More active defaults: Default RVOL and regime thresholds are permissive enough to participate across many timeframes ATR stop and target: Risk is framed with volatility-adjusted exits Bias-flip exits: Positions can close when the opposing regime gains enough votes Risk controls: Max drawdown and max intraday filled orders are included Overlay visuals: Forecast bands and adaptive channel context can be displayed on chart Top-right dashboard: Regime, score, pressure, RVOL, votes, position, band width, and setup Alerts: Long and short setup events Input Parameters Forecast: Source, Forgetting Factor, Regression Horizon, Band Multiplier, ATR Blend, and Rebase Interval Regime: Fast EMA and Slow EMA: Trend structure references Pressure Length: Momentum and pullback window Pressure Threshold: Minimum pressure vote threshold Min RVOL: Participation filter Min Votes: Minimum number of aligned components for entries Risk: Stop ATR: Stop distance multiplier Target ATR: Target distance multiplier Max Drawdown %: Strategy risk halt setting Max Intraday Filled Orders: Limits daily trade frequency How to Use This Strategy Step 1: Read the dashboard regime before judging entries. Step 2: Use votes and pressure to understand why a setup qualified. Step 3: Review stop and target settings for the symbol and timeframe being tested. Step 4: Evaluate results across multiple markets and date ranges, not one optimized window. Strategy Limitations This strategy is not optimized for a specific symbol or timeframe More active defaults can increase trade count and also increase exposure to choppy periods Backtest fills are simulated by TradingView and may not match live execution All entry signals use confirmed-bar logic, so entries can occur after the intrabar move has begun Strategy performance should be evaluated with realistic commission, slippage, and position sizing Originality Statement Regime Execution Strategy is original in its integration of adaptive forecast bias, extreme-channel state, pressure voting, relative volume gating, EMA structure, ATR exits, and dashboard reporting into one open-source strategy. It does not copy third-party source code. Disclaimer This open-source strategy is for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Backtested results do not predict future performance. Trading involves substantial risk, and users are responsible for their own risk management. -Made with passion by jackofalltrades
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Concordance Allocation Strategy [JOAT]Concordance Allocation Strategy Introduction Concordance Allocation Strategy is an open-source TradingView strategy that integrates regime detection, directional bias, momentum alignment, value-location filtering, and ATR-based risk management into one non-repainting framework. It is designed to trade only when multiple independent layers agree on bar close. The problem this strategy solves is isolated signal bias. A single good-looking signal can fail quickly if it appears in the wrong market regime, against the wrong directional structure, or in the wrong part of value. Concordance requires those layers to align before it enters a trade, then manages risk with fixed ATR targets and adaptive exits. Core Concepts 1. Regime filter The strategy uses a probability-based trend-versus-range classifier. Trades are only considered when the directional regime is confirmed on a closed bar. 2. Directional bias engine An ATR-based bias band adapts to noisy conditions and recovery stress so long and short bias are not driven by a simple moving average cross. 3. Momentum confirmation A centered adaptive stochastic spread must align with the directional side. This prevents entries based on trend context alone. 4. Value-location filter The strategy requires price to be properly aligned with percentile-derived value rails before entries are allowed. This helps avoid chasing direction in poor location. 5. Structured risk management Every position uses: ATR stop loss ATR take profit Adaptive trailing behavior once price extends far enough Context exits when regime or momentum deteriorates Features Multi-layer entry filter: Regime, bias, momentum, and value must agree Bar-close confirmation: Entries are evaluated using confirmed-bar logic ATR stop loss and take profit: Risk is defined from volatility, not fixed ticks Adaptive exit behavior: Bias band can tighten once the move extends No higher-timeframe dependency: Uses current-timeframe calculations only Institutional dashboard: Shows exposure state, regime, momentum, bias band, and value rails Non-repainting framework: No future references and no lookahead logic Input Parameters Regime Layer: Return Lookback Volatility Lookback Efficiency Length Regime Learning Trend Gate Directional Bias: ATR Length ATR Base Multiplier Avoidance Expansion Recovery Pull Noise Threshold ATR Momentum Layer: Stochastic Length Stochastic Smoothing Price Presmoothing Adaptive Attenuation Momentum Spread Gate Value Layer: Value Lookback Lower Rail Percentile Upper Rail Percentile Rail Smoothing Risk Layer: Stop ATR Take Profit ATR Trail Activation ATR Trail Buffer ATR How to Use This Strategy Step 1: Read the regime The strategy only acts when the directional regime is confirmed. If the regime is rotational, it stands down. Step 2: Confirm directional bias The ATR bias band must agree with the side of the trade. This avoids taking long momentum setups under bearish structure or the reverse. Step 3: Check momentum and value together Momentum must align with the side and price must be operating in the correct value location. Both filters are required. Step 4: Review risk settings before use Stop and target multiples should be adjusted to the market and timeframe being tested. The defaults are intended to be realistic rather than aggressively optimized. Strategy Limitations No strategy can eliminate false regime transitions or rapid reversals Percentile value rails adapt to the sample window and may lag sudden structural changes The strategy is designed for realism and context alignment, not maximum trade frequency Originality Statement Concordance Allocation Strategy is original in how it requires regime confirmation, directional bias, momentum agreement, and value-location agreement before allowing entries. It is published because: The strategy avoids isolated indicator triggers and instead uses a layered confirmation model Its risk logic combines fixed ATR objectives with adaptive context exits The design is intentionally current-timeframe, bar-close confirmed, and non-repainting Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice, and backtest results do not guarantee future performance. Trading involves risk of loss, and any strategy can underperform or fail in changing market conditions. Always evaluate settings carefully and use proper risk management.
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Tension Flow Trend [BigBeluga] - Historical RRTension Flow Trend is a high-performance trend-following framework that treats price action like a reactive elastic system. By moving beyond static averages, this indicator introduces "Price Tension"—a sophisticated measurement of how overstretched a trend is relative to its baseline—now enhanced with a live Historical RR (Risk:Reward) backtesting engine. By combining the ultra-low-lag properties of the Hull Moving Average (HMA) with real-time Z-Score volatility analysis, this indicator visualizes not just the direction of the market, but the mathematical "exhaustion" of every move. 🔵 THE ELASTICITY FRAMEWORK The Ultra-Responsive HMA Baseline: At the heart of the system is a 50-period Hull Moving Average. Specifically engineered to eliminate the lag found in traditional SMAs, the HMA provides a "true north" that reacts instantly to structural shifts without the usual delay. Price Tension (Z-Score Engine): The indicator measures the vertical distance between price and the HMA, normalizing it using standard deviation. This Z-Score represents the "Tension" of the trend—showing you exactly when the market has deviated too far from its mean. Dynamic Transparency Feedback: As price enters an extreme Z-Score range, the trend ribbon’s transparency increases. A bright, solid ribbon indicates compressed, high-probability energy, while a fading ribbon warns that the "elastic band" is stretched to its limit. 🔵 PERFORMANCE & RISK INTELLIGENCE Automated RR Projection: Upon every "START" signal, the script automatically plots dynamic Risk:Reward boxes. It calculates an ATR-based stop loss and projects a take-profit target based on your custom RR ratio, visualizing the trade's path in real-time. Rolling Performance Tracker: The indicator features a built-in backtester that tracks the win/loss history of the most recent trades. It calculates your Win Rate based on a rolling sample size, allowing you to see how the strategy is performing under current market conditions. Signal Cooldown Logic: To eliminate "whipsaw" noise, a configurable cooldown engine ensures that signals only trigger during significant structural shifts. This prevents signal clustering in sideways or choppy markets. 🔵 DUAL-DASHBOARD SYSTEM Energy Monitor (Bottom-Right): Tracks the numerical Z-Score and categorizes the market status. "Strong" indicates healthy momentum, while "Overextended" warns of an imminent mean-reversion risk. RR Performance Table (Top-Right): Provides an institutional-grade breakdown of your strategy performance, including total Wins, Losses, and the current Win Rate percentage for the specified trade window. 🔵 STRATEGIC APPLICATION The Momentum Breakout: Look for "START" labels that appear when the HMA slope aligns with a price crossover. These represent the birth of a new trend cycle where tension is low and expansion is likely. Managing Trend Exhaustion: When the ribbon begins to fade and the Energy Dashboard hits "Overextended," it is time to tighten stops or take partial profits. High tension usually precedes a sharp snap-back to the baseline. Confirming with Win Rate: Use the Performance Dashboard to gauge market regime. If the rolling Win Rate is high, the market is respecting the trend envelopes; if it drops, the market may be entering a consolidation phase where you should wait for better alignment. Mean Reversion Targets: For contrarian traders, the HMA baseline serves as a natural "magnet." When price is significantly overextended, look for price to be pulled back into the HMA "Neutral Zone." Tension Flow Trend transforms your chart into a map of market stress and opportunity. By visualizing the tension behind every candle and providing real-time performance feedback, it ensures you stay on the right side of the trend while trading with professional-grade risk management.
مؤشر Pine Script®
من ‎BigBeluga‎
7
Z-Score Probability Pro KAMA Z-Score Probability Pro KAMA, v1.0 by Erika Barker Hey guys, this is the successor to my original Z-Score Probability HMA Indicator, which you can still use if you prefer that one. This is version 1.0 of the new rebuild, and it is a pretty big upgrade. The goal was to keep the statistical foundation that made the original useful, but make it more adaptive, cleaner, and better at understanding different market conditions. What is new 1. Timeframe auto-adaptation No more constantly re-tuning the indicator when you switch charts. The lookback now automatically adjusts based on the chart timeframe, using a calendar-style window, defaulting to about 5 trading days. The dashboard also shows the effective lookback being used, so you always know what the script is calculating from. It works from 1 minute charts all the way up to weekly charts. 2. Better smoothing logic The original HMA was doing a lot of work at once. In this version, the baseline and the Z-score smoothing are separated so each one can do its own job better. By default: * Baseline: KAMA, great for adapting to noisy markets * Z-score smoothing: ALMA, smoother and cleaner on the oscillator HMA is still available if you prefer the original feel. 3. Modified Z-Score option There is now an optional Modified Z-Score mode using MAD, median absolute deviation. This is useful for markets with big outliers, fat tails, sudden spikes, crypto moves, small caps, and anything that tends to behave a little wild. When this mode is turned on, the threshold bands automatically adjust. 4. Regime filter using Hurst logic (been needing out on this a lot lately on personal stuff) This version attempts to classify the market as: * Trending * Mean-reverting * Random That matters because an extreme Z-score does not always mean the same thing. In a mean-reverting market, an extreme Z-score can suggest exhaustion. In a trending market, that same extreme can sometimes mean continuation or breakout strength. This was one of the biggest things I wanted to improve from the original. 5. Divergence engine The indicator now includes both regular and hidden divergence. It can detect: * Regular bullish divergence * Regular bearish divergence * Hidden bullish divergence * Hidden bearish divergence Divergences are confirmed using pivots, so they are non-repainting, but they will appear a few bars after the actual pivot. That is the tradeoff for confirmation. 6. Higher-timeframe confirmation The script can pull Z-score confirmation from a higher timeframe. You can use the automatic HTF mode or set it manually. HTF values only update after the higher-timeframe candle closes, so this is designed to avoid repainting. 7. Strong Buy and Strong Sell signals Signals are based on a confluence score instead of just one condition. The score looks at things like: * Z-score reversal * Divergence * Baseline slope * Market regime * Higher-timeframe agreement * Volume confirmation, when volume is available You can choose the conviction level: * Low * Medium * High Medium is the default and should give fewer, cleaner signals. 8. Live dashboard The dashboard shows: * Detected timeframe * Effective lookback * Current Z-score * Market regime * Hurst value * Higher-timeframe status * Bull and bear scores * Conviction threshold * Last signal You can move it to any corner of the chart. 9. More stable defaults The defaults were chosen to be centered in stable performance zones, not over-optimized for one market. Basically, I did not want this to be something that only looks good on one ticker, one timeframe, during one perfect backtest window. 10. Built in Pine v6 This version uses Pine v6 features, including dynamic higher-timeframe requests and confirmed-bar alert logic. Repaint disclosure This indicator is designed to avoid repainting, but there are a few things to know: * Divergence and Strong Buy/Sell labels appear after pivot confirmation, default is 3 bars later * Higher-timeframe confirmation only updates after the higher-timeframe candle closes * Alerts fire on confirmed bars, not intrabar ticks So, signals are delayed slightly by design, but that is what makes them confirmed. How to use it Beginner Leave everything on default. Watch the dashboard and look for: * Strong Buy * Strong Sell Medium conviction is probably the best starting point. Intermediate Try the Modified Z-Score mode on crypto, small caps, or anything with sharp moves and big outliers. Turn on Hidden Divergence if you like trading trend continuation setups. Advanced You can tune the component weights to match your own strategy. The indicator is flexible, so you can make it more reversal-focused, more trend-following, or more confirmation-heavy depending on your trading style.
مؤشر Pine Script®
من ‎erikabarker‎
Aureate Market Architecture Strategy [JOAT]Aureate Market Architecture Strategy Introduction Aureate Market Architecture Strategy is an open-source TradingView strategy that integrates regime classification, structure bias, breakout pressure, liquidity confirmation, and risk management into one confirmed-bar execution model. The strategy is built for users who want a rules-based implementation of the broader JOAT architecture rather than a single-indicator signal stream. Its design goal is not to maximize trade count. Its design goal is to trade only when multiple independent conditions agree: the market is in an expansion-permitted regime structure bias supports direction pressure is strong enough to justify participation liquidity context confirms the move risk and daily drawdown constraints allow a new position This produces a strategy that is intentionally selective and explicitly non-repainting. Core Concepts 1. Regime Detection The strategy classifies the market into accumulation, expansion, or exhaustion using ATR behavior, balance width, and normalized breakout pressure. A persistence requirement prevents the regime state from flipping too quickly. 2. Structure Bias Filter Directional participation is gated by confirmed medium-term structural breaks, EMA orientation, and price location relative to the fast EMA. An optional higher-timeframe bias filter can be added using completed higher-timeframe candles only. 3. Pressure Confirmation Breakout pressure is derived from a composite of multiple ROC windows and smoothed into an adaptive signal. The strategy does not permit entries unless that signal exceeds its volatility-adjusted threshold. 4. Liquidity Context The strategy estimates upper and lower liquidity anchors, counts relative touch density, and looks for sweep failure behavior to confirm whether the current move has supportive liquidity context. 5. Risk and Exit Stack Every position uses an initial stop, a take-profit target based on risk multiple, an adaptive trailing component, a daily loss lockout, and a cooldown after exit. Features Three-state regime engine: accumulation, expansion, and exhaustion Persistence logic: regime changes require confirmation across multiple bars Structure bias filter: confirmed BOS logic combined with EMA alignment Optional HTF bias filter: completed higher-timeframe candles only Adaptive breakout pressure: multi-window ROC model normalized by its own volatility Liquidity confirmation: anchor touches, sweep failures, and relative-volume support Long and short entry logic: both directions use the same confirmed-bar architecture Risk management: ATR-based initial stop, target, trailing logic, and daily loss control Cooldown control: prevents immediate re-entry after an exit Dashboard and chart overlays: display current state, active bias, and risk context Default Strategy Properties Initial Capital: 100000 Order Size: 10% of equity Commission Model: Percent Commission Value: 0.01 Pyramiding: 0 Calc On Order Fills: enabled Calc On Every Tick: disabled Input Parameters Regime Engine Regime ATR Length Regime Baseline Length Balance Window Accumulation Volatility Threshold Expansion Volatility Threshold Regime Persistence Bars Structure Bias Short Pivot Medium Pivot Fast EMA Slow EMA Use Confirmed HTF Bias Filter HTF Bias Timeframe Breakout Pressure Fast ROC Medium ROC Slow ROC Macro ROC Pressure Smoothing Pressure Threshold Multiplier Liquidity Context Liquidity Window Sweep Depth ATR Relative Volume Floor Risk Management Initial Stop ATR Take Profit R Multiple Trail ATR Multiple Daily Lockout % Cooldown Bars After Exit How to Use This Strategy Step 1: Treat the Regime as the First Gate The strategy only wants to be active in the expansion state. If the dashboard shows accumulation or exhaustion, the system is designed to be more selective or inactive. Step 2: Check Directional Alignment The cleanest trades occur when structure bias, EMA alignment, pressure, and liquidity all support the same side. Step 3: Respect the Risk Model The stop, target, trail, and daily lockout are part of the strategy logic. They should not be ignored when evaluating results. Step 4: Expect Selectivity This strategy is built to filter aggressively. Users looking for frequent trades may need different settings or a different methodology. Step 5: Evaluate Over Enough Trades No strategy should be judged from a very small sample. Assess it across enough market conditions to understand where the architecture performs well and where it degrades. Strategy Limitations This strategy uses chart-derived liquidity and regime approximations rather than exchange microstructure data Selective filters can reduce trade frequency substantially on some instruments and timeframes Backtest results depend on instrument, timeframe, commission, slippage assumptions, and session behavior Non-repainting logic reduces false signals but can also introduce later entries than predictive systems Originality Statement Aureate Market Architecture Strategy is original in the way it integrates regime state, structural confirmation, normalized pressure, liquidity context, and layered risk controls into one coherent execution model. The purpose of the integration is practical: each component addresses a different failure mode that appears when breakout systems rely on only one dimension of evidence. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice and does not guarantee profitability. Backtest outcomes are hypothetical and derived from historical data. Live trading includes slippage, execution variance, and market conditions that can differ materially from historical results.
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Concord Execution Mandate [JOAT]Concord Execution Mandate Introduction Concord Execution Mandate is an open-source strategy that combines regime classification, higher-timeframe bias, structure breaks, daily pivot context, reversion-basis reclaim logic, and divergence safety into one execution framework. It is designed to test whether directional entries improve when multiple context layers are aligned rather than relying on a single trigger. The problem this strategy solves is unstructured execution. Many strategies either enter too often without context or wait for perfect alignment so long that they never engage. Concord Execution Mandate uses a softer confluence model that can still trade frequently while preserving directional context, confirmed-bar logic, realistic costs, and explicit risk controls. Core Concepts 1. Regime And Context Layer The strategy starts with an adaptive range-state engine supported by ADX, choppiness, and higher-timeframe EMA bias. These inputs do not all act as hard blockers; instead, they contribute to whether the environment is favorable enough for execution. 2. Structural And Rotation Triggers Entries can come from confirmed bullish or bearish BOS behavior, continuation crosses back through the regime filter, or more aggressive rotation entries through the daily pivot, reversion basis, or short EMA. 3. Soft Alignment Model Daily pivot bias, EMA weave bias, geometry bias, and regime location are combined into a directional alignment score. The strategy requires enough agreement to avoid fully random entries, but it does not require every filter to align perfectly before acting. 4. Risk Management Stops are based on the closer of pivot structure or ATR distance. Targets are expressed as a reward multiple of live risk, and a trailing stop can activate only after price reaches a configurable multiple of initial risk. Context-flip exits can close trades early when directional state changes materially. Features Adaptive regime filter: Core state engine for directional context Higher-timeframe bias: Optional EMA-based external direction filter Structure triggers: Confirmed BOS logic using stored pivots Continuation and rotation entries: Additional execution paths beyond BOS Daily pivot and EMA weave context: Location-versus-bias inputs for alignment scoring Reversion reclaim logic: Optional re-entry through a mean basis before entry Divergence safety filter: Optional block on fresh opposing divergence ATR and structure-based stops: Dynamic risk anchoring Reward targets and ATR trailing: Structured exit management Context-flip exits: Early closure when regime or bias reverses Realistic defaults: Percent-of-equity sizing, commission, and slippage are defined in the strategy properties Default Strategy Properties Initial capital: 100000 Default order size: 5 percent of equity Commission: 0.02 percent Slippage: 2 ticks Order processing: on bar close Pyramiding: 0 How to Use This Strategy Step 1: Read the dashboard to confirm the current regime, structural state, and whether the entry stack is armed. Step 2: Use the strategy on instruments and timeframes where directional movement and retracement behavior are both visible enough to generate a meaningful sample. Step 3: Review whether aggressive rotation entries or stricter reclaim filters better match the market being tested. Step 4: Keep the published chart clean and use the same Properties values shown in the strategy description when presenting results. Step 5: Evaluate the strategy using a broad sample of trades rather than isolated trades or one short backtest segment. Strategy Limitations This strategy still relies on lagging structure confirmation and can miss the first portion of fast reversals More aggressive settings can increase trade count at the cost of lower selectivity Higher-timeframe bias can conflict with local execution context during turning points Backtest results depend on symbol, timeframe, session behavior, and execution assumptions This strategy is designed to be realistic, not optimized for one narrow market condition Originality Statement Concord Execution Mandate is original in how it integrates adaptive regime logic, structural breaks, rotation entries, soft alignment scoring, reclaim filtering, divergence safety, and layered exit management into one execution framework. The combination is intentional because the strategy is designed to test whether context-aware execution can remain active without devolving into random signal generation. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice and does not guarantee future performance. Backtests are based on historical data, configured assumptions, and simulated order handling. Always validate behavior independently and use appropriate risk management. -Made with passion by jackofalltrades
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
NY Session Trend Retest StrategyA Session-based trend continuation and breakout system built around the relationship between: * Higher timeframe trend * Anchored VWAP * Premarket structure * EMA positioning * Session liquidity behavior It’s essentially a **hybrid momentum + mean reversion framework** designed for intraday futures trading, especially instruments like: * NQ / MNQ * ES / MES * Gold / MGC where intraday institutional flow around VWAP and session highs/lows matters heavily. --- # Core Strategy Concept The strategy attempts to align trades with: 1. Higher timeframe directional bias 2. Intraday institutional positioning via Anchored VWAP 3. Session expansion away from equilibrium 4. Liquidity reactions at key levels Instead of blindly buying/selling crossovers, it tries to enter only when price interacts with important session reference points while the broader trend is already established. --- # Higher Timeframe Trend Filter The backbone of the system is a higher timeframe EMA trend filter. ```text Price above HTF EMA = bullish environment Price below HTF EMA = bearish environment ``` This prevents counter-trend trades during strong directional sessions and keeps the strategy aligned with broader market structure. The idea is: * buy pullbacks in bullish regimes * short rallies in bearish regimes rather than constantly fading momentum. --- # Anchored VWAP Logic The anchored VWAP resets every trading session and acts as the strategy’s institutional equilibrium level. This is one of the most important parts of the system because it determines: * directional bias * entry location * trade quality * exit behavior * market regime conditions The strategy treats VWAP as: * support in bullish sessions * resistance in bearish sessions and uses it to detect whether the market is: * trending * balanced * compressed * expanding --- # Entry Systems Your strategy has three independent entry models. --- ## 1. VWAP Retest Entries These are trend continuation entries. ### Long setup: * price retests VWAP * closes back above VWAP * HTF trend is bullish ### Short setup: * price retests VWAP * closes back below VWAP * HTF trend is bearish This attempts to capture: > institutional continuation after equilibrium retests These are generally your highest-quality trend entries. --- ## 2. Premarket Breakout Entries This is your expansion model. The strategy tracks: * premarket high * premarket low Then enters when price either: * closes beyond those levels OR * retests them successfully depending on the selected breakout mode. This captures: * opening drive momentum * liquidity sweeps * range expansion after overnight consolidation --- ## 3. EMA Retest Entries These are secondary trend continuation entries using a faster EMA. They allow entries during: * shallow pullbacks * momentum continuation * trending intraday conditions without requiring full VWAP interaction. --- # VWAP Regime Filter One of the more advanced components is your VWAP regime filter. This prevents trades during: * flat VWAP conditions * compressed price action * low expansion environments The filter measures: 1. VWAP slope 2. Compression range and blocks entries when the market lacks directional intent. This is important because most intraday losses come from: * sideways VWAP chop * low volatility rotations * fake breakouts during equilibrium The filter attempts to avoid those environments entirely. --- # Exit Logic Your exit system is adaptive rather than fixed. --- ## Standard EMA Exit Normally trades exit when candle bodies close aggressively across the exit EMA. This acts as: * trend failure detection * momentum loss confirmation rather than a static take-profit. --- ## VWAP Exit Override This is one of the more unique parts of the strategy. If a trade enters: * below the exit EMA on longs OR * above the exit EMA on shorts the strategy temporarily ignores EMA exits. Instead, it switches to VWAP-based exits until: * price recovers back into profit * reclaims trend structure This prevents: * premature exits * weak-entry shakeouts * breakout trades getting cut immediately It is especially useful for: * PM breakout entries * volatility expansion trades * reclaim setups --- # Partial Profit Taking The strategy scales out at: * premarket highs/lows * intraday highs/lows This allows: * partial realization into liquidity * reduced emotional volatility * better trade management during expansion --- # Breakeven Logic After partial profit is taken: * stops move to breakeven This creates: * asymmetric risk * free-trade conditions * better protection during reversals while still allowing runners to continue. --- # Trade Cooldown System After a trade closes, the strategy waits a configurable amount of time before allowing another entry. This helps avoid: * revenge trading behavior * chop reentries * overtrading during consolidations especially during: * midday conditions * failed breakout clusters * post-news volatility compression --- # Session-Based Design The strategy is heavily session-aware. It distinguishes between: * premarket activity * NY regular trading hours * session transitions and resets important calculations daily. This makes it much more tailored for futures markets than generic indicator systems. --- # Overall Trading Philosophy The strategy is fundamentally trying to trade: > directional expansion away from institutional equilibrium while avoiding: * flat VWAP environments * low volatility compression * weak counter-trend conditions It combines: * trend following * liquidity trading * session structure * VWAP mean reversion concepts * breakout continuation behavior into a single adaptive framework.
استراتيجية Pine Script®
من ‎itzkarmakyo‎
Concordance Execution Mandate [JOAT]Concordance Execution Mandate Introduction Concordance Execution Mandate is an open-source TradingView strategy that integrates the indicator concepts used throughout the JOAT Suite into one execution framework. It combines crossframe bias, auction location, stepped structure, momentum timing, absorption participation, and volatility gating before any trade is allowed. It also renders on-chart trade rails, stop placement, profit targets, and a dashboard summarizing the active execution state. The purpose of the strategy is not to optimize one narrow market condition. The purpose is to require multiple independent conditions to agree before a trade is taken. This reduces single-factor noise and creates a more realistic execution process than a strategy that relies on only one oscillator or one moving-average crossover. Core Concepts 1. Crossframe Regime Filter Higher-timeframe trend alignment establishes the directional permission layer. If the dominant bias is not aligned, the strategy remains filtered. 2. Auction Location Filter Price must also be in a constructive value location for longs or a defensive value location for shorts. This reduces cases where a trend is positive but price is poorly located relative to accepted value. 3. Structure and Momentum Gate The local stepped structure and momentum score must agree with the higher-level direction before a trade is permitted. 4. Absorption and Volatility Filter If an active absorption range exists, the strategy uses it as a participation filter. Volatility percentile and directional volatility behavior are also used to avoid unsuitable states. 5. ATR-Based Risk Management Stops are sized from ATR and, when enabled, can anchor to structural references. Targets are placed using configurable R multiples. Features Multi-layer trade permission: Crossframe, auction, structure, momentum, absorption, and volatility must align Confirmed-bar logic: Entry conditions are evaluated on confirmed bars ATR-based stop logic: Risk is normalized to current market conditions Two staged exits: TP1 and TP2 are placed automatically, with a third informational rail on-chart On-chart trade rails: Entry, stop, TP1, TP2, and TP3 are drawn directly on the chart Risk/reward fills: Visual fill between entry and stop or target levels Execution dashboard: Displays regime, permission, auction state, structure state, momentum, absorption, ATR percentile, position state, and active risk rail Realistic default properties: Uses commission, slippage, and percent-of-equity sizing Strategy Properties Used By Default Initial Capital: 100000 Commission Type: Percent Commission Value: 0.05 Slippage: 2 Pyramiding: 0 Position Size: 10% of equity Orders Processed On Close: Enabled How to Use This Strategy Step 1: Read the dashboard before evaluating the backtest. The strategy is built around permission states, not constant market participation. Step 2: Check whether the system is in Long Bias, Short Bias, or Mixed mode. Step 3: Observe whether the strategy is filtering trades because one of the major layers is missing, such as auction location or volatility suitability. Step 4: Use the on-chart rails to understand how the strategy is defining risk and reward at each entry. Strategy Limitations Like all strategies, results depend on market, timeframe, and input choices Higher-timeframe filters are intentionally delayed for non-repainting safety Multiple filters can reduce trade frequency substantially The strategy is designed as a robust execution framework, not as a guarantee of profitability Backtest results should be interpreted with realistic skepticism and proper context Originality Statement Concordance Execution Mandate is original in the way it integrates top-down bias, auction location, local structure, momentum timing, participation filtering, and volatility gating into one execution process with visible trade management rails. The script is published to show how multiple institutional-style context layers can be fused into a realistic open-source framework. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to trade any market. Backtest results are based on historical data and do not guarantee future performance. All trading involves risk, including the risk of loss. Use independent judgment and proper risk management. -Made with passion by jackofalltrades
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
RSI Volume LadderA long-only pyramiding strategy that scales into corrections using RSI oversold conditions confirmed by above-average volume. Each subsequent entry requires a meaningful price drop from the previous fill, with an asymmetric exit structure: Take Profit anchored to the average entry, Stop Loss anchored to the lowest fill. Built for traders who want to systematically dollar-cost into pullbacks within an uptrend, with clearly defined risk per pyramid stack. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ORIGINALITY — WHAT MAKES THIS DIFFERENT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Five specific mechanics that, in this combination, distinguish this script from other averaging-down systems published on TradingView: - ASYMMETRIC EXIT ANCHORING Take Profit is calculated from the average entry price of the pyramid — so winners run from the averaged-down cost basis. Stop Loss is calculated from the LOWEST entry price among all open positions — so the absolute worst-case loss is bounded by your deepest fill, not your average. This asymmetry is the key to making pyramiding viable: averaging works for you on the upside without inflating downside risk. - PRICE-DROP GATE FOR EACH PYRAMID LEG Every subsequent entry requires both a fresh RSI + volume signal AND a configurable minimum price drop from the previous fill (default 1.5%). This prevents stacking three positions within a tight range during a slow grind down — pyramiding only triggers on meaningful pullbacks, forcing real averaging instead of cosmetic averaging. - ASYMMETRIC COOLDOWN ON EXIT After a Stop Loss, the strategy waits N bars (default 3) before allowing new entries — blocks the "catch the falling knife" pattern where RSI stays oversold for many bars during a cascade. After a Take Profit, cooldown is configurable separately and defaults to 0, because a successful exit signals continued mean-reversion behavior worth participating in. - ENTRY-TIMING SAFETY Exit detection runs at the top of the bar evaluation, BEFORE the entry check. This means a Stop Loss hit on a bar cannot trigger a new entry on the same bar — even if RSI is still deeply oversold and volume is elevated. The cooldown counter is set before the entry logic ever sees the bar, eliminating a subtle but realistic execution problem in pyramiding systems. - VISUAL EXIT CLASSIFICATION When the position closes, the script automatically classifies the exit as TP or SL by measuring distance from actual fill price to each pre-set level, and renders a fuchsia or red cross at the exit price. No look-ahead, no estimation — the classification uses the closed trade's recorded exit price. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ CREDITS & FOUNDATIONS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This script builds on established methodologies with original Pine v5 implementation of every layer: - RSI — Wilder, 1978 (standard implementation via ta.rsi) - Volume confirmation — classical technical analysis - Pyramiding / scaling-in — standard portfolio management technique (Tharp, Elder) - Dollar-cost averaging principles — long-standing investment methodology ALL CODE in this script was written from scratch. No code has been copied from other public or private scripts. The five mechanics listed under ORIGINALITY above are original combinations and implementations. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW THE STRATEGY WORKS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ENTRY CONDITIONS (all must be true): - RSI below the configurable oversold threshold (default 30) - Volume above SMA × configurable multiplier (default 1.5× of SMA20) - For pyramiding: price must be at least X% below the last fill (default 1.5%) - Cooldown not active from the previous exit - Open positions count below the pyramiding cap (default 3) PYRAMID BUILDING: Up to 3 long positions can be opened. Each new entry independently re-checks all conditions — the RSI + volume signal must reappear, AND the price drop gate must be satisfied. Position size per entry is fixed (default 5% of equity), so a full three-position stack uses approximately 15% of equity. EXIT LOGIC: Both legs run as an OCO (one-cancels-other) bracket: Take Profit = average entry × (1 + tpPercent / 100), default +4% Stop Loss = lowest entry × (1 − slPercent / 100), default −3% All positions close together when either level is hit. The TP/SL levels update on every bar as the pyramid grows — average shifts on each new fill, lowest fill anchors deeper if a new low is hit. COOLDOWN MECHANISM: On exit, the strategy records the bar index and exit type. While bar_index − lastExitBar ≤ requiredCooldown , new entries are blocked. The required cooldown differs by exit type (default 3 bars after SL, 0 bars after TP), reflecting that an SL exit often happens during continuing weakness, while a TP exit signals healthy mean reversion. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ VISUALIZATION ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ENTRY ARROWS — blue triangles below each fill, labeled Long_1 / Long_2 / Long_3 with the order price AVERAGE ENTRY LINE — blue, updates as the pyramid grows (staircase pattern) TAKE PROFIT LINE — fuchsia, updates with the average STOP LOSS LINE — red, anchored to the lowest fill (steps down only if a deeper entry occurs) EXIT CROSS — fuchsia at TP hit, red at SL hit, placed at the actual exit price The line style is plot.style_linebr , which connects within an open position and breaks cleanly between positions — making each pyramid cycle visually self-contained on the chart. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW TO USE IT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ This is a complete entry + exit strategy, but it is NOT a turn-it-on-and-walk-away system. Use it as a framework to test and adapt to your specific instrument: - Load on a liquid asset with mean-reverting behavior in an uptrend. The strategy was developed on crypto majors (BTC, ETH) and major equity indices. Start with the default parameters and run the Strategy Tester on at least 6 months of history. - Pay attention to: • Net Profit and Max Drawdown ratio • Average loss vs. average win • Whether losing streaks cluster during specific market regimes Tune to your instrument's volatility: • Higher-volatility assets (alt-coins, small caps) → increase dropPercent (2-3%), increase slPercent (4-6%) • Lower-volatility assets (BTC, indices) → decrease dropPercent (1-1.5%), tighter slPercent (2-3%) • Higher timeframes (1h, 4h) → wider TP/SL to match bar range - Consider adding an external trend filter for your live use. The strategy will pyramid into any oversold reading regardless of higher-timeframe context. Adding an EMA200 filter (only enter if price > EMA200) materially changes the risk profile on instruments prone to extended downtrends. - Treat the strategy output as a structured framework for your dip-buying process, not as a guaranteed system. Combine with your own market analysis, position sizing, and broader risk management. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ INPUTS WORTH KNOWING ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ RSI Length (default 14) and Oversold threshold (default 30) — standard RSI configuration. Lower threshold = fewer, deeper-oversold entries. Volume SMA length (default 20) and Multiplier (default 1.5×) — volume confirmation strength. Higher multiplier = only enter on standout volume spikes, fewer entries. Min drop between pyramid entries (default 1.5%) — prevents tight clustering. Higher = waits for deeper pullbacks before adding. Max pyramid positions (default 3) — caps the stack. Note: pyramiding=3 is also set in the strategy() header. Take Profit % from average (default 4%) — anchored to running average entry price. Stop Loss % from lowest fill (default 3%) — anchored to the deepest entry, shared across all open positions. Cooldown after SL (default 3 bars) — blocks the falling-knife pattern after a stop-out. Cooldown after TP (default 0 bars) — re-enter immediately after a successful exit. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ REALISTIC EXPECTATIONS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Pyramiding into corrections is a well-known approach with well-known limitations. The strategy works best when: The underlying asset has a structural uptrend Volatility produces regular pullbacks of meaningful depth The market is not in a sustained bear regime What this strategy provides: A disciplined framework for scaling into pullbacks instead of single-shot entries Asymmetric exit anchoring that lets winners run from the averaged cost basis Built-in protection against catching the falling knife via cooldown Transparent visualization of each pyramid leg, exit, and risk level What it does NOT provide: Protection from prolonged bear trends (averaging down into a structural decline is the dominant failure mode of this entire strategy family) A guaranteed profitable system A signal generator for assets that don't mean-revert A replacement for your own market analysis, position sizing, or higher-timeframe context Treat the output as ONE structured input in your trading process. The biggest risk to your account using a pyramiding strategy is mis-applying it to a downtrending asset — always confirm regime alignment before going live. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TECHNICAL NOTES & DISCLOSURES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ NO REPAINT . Uses process_orders_on_close=true — all orders execute on confirmed bar close. No request.security() calls, no lookahead_on, no barmerge.lookahead_on. REALISTIC EXECUTION . Default commission 0.05% per trade (typical crypto exchange taker fee). Position sizing in % of equity, not fixed contracts. Initial capital 10,000. DATA USED : only standard Pine inputs — open, high, low, close, volume. Indicators: RSI, SMA of volume. No external feeds, no security() calls, no synthetic data. PERFORMANCE : max_labels_count=500. Pyramiding capped at 3. No unbounded growth of internal objects. ASSETS : developed on crypto majors and tested across 5m, 15m timeframes. Works on equities and forex but parameters were tuned on crypto and may need adjustment for assets with different intraday behavior. EDUCATIONAL AND ANALYTICAL TOOL . Intended for traders who understand pyramiding mechanics and the inherent risk of averaging-down strategies, and who want a structured framework to test on their own instruments. OPEN SOURCE . Read the code, learn from it, fork it. Feedback and bug reports welcome in the comments. Check my profile for other published scripts.
استراتيجية Pine Script®
من ‎wielkieef‎
ATR Fibonacci Trend Envelopes [BigBeluga]ATR Fibonacci Trend Envelopes is a professional-grade trend-following and mean-reversion framework. It combines the volatility-filtering power of Average True Range (ATR) with the mathematical precision of the Fibonacci Golden Ratio to define high-probability "buy/sell pockets" within an established trend. Equipped with a live Multi-Timeframe (MTF) dashboard, this indicator allows traders to monitor trend alignment across four different time horizons simultaneously, ensuring that local entries are always supported by the broader market structure. 🔵 THE DUAL-ENGINE FRAMEWORK Volatility-Adjusted Trend Engine: The indicator uses a customizable Moving Average (SMA, EMA, HMA, etc.) combined with an ATR multiplier to create dynamic envelopes. This filters out market noise and only signals a trend change when price decisively breaks the volatility boundary. Dynamic Golden Pocket (0.618 - 0.786): Unlike static retracements, these Fibonacci levels are calculated relative to the current ATR envelope. The "Pocket" acts as a high-interest zone where price is expected to find support (in uptrends) or resistance (in downtrends). Predictive Slope Projections: Using the current rate of change, the script projects the trend and Fibonacci levels into the future. This allows traders to visualize where "Value" will be in the coming bars, facilitating better trade planning and order placement. 🔵 CORE ARCHITECTURE MTF Alignment Dashboard: A real-time table tracks the trend status and "Pocket" proximity across four timeframes. A "BULL" status combined with an "INSIDE" pocket signal across multiple timeframes indicates a high-confluence institutional setup. Dynamic Transparency Feedback: The visual intensity of the Golden Pocket adapts based on price proximity. As price approaches the mid-point of the pocket, the colors become more saturated, providing an intuitive visual cue that the market is entering a high-probability reversal zone. Momentum-Driven Basis: The trend baseline (1.0 level) acts as the ultimate anchor. As long as price remains above this volatility-adjusted line in a bullish regime, the trend is considered structurally sound. 🔵 FEATURES Multi-MA Versatility: Choose from 5 different moving average types to calculate your trend basis, allowing the indicator to be tuned for slow-moving macro trends or fast-moving scalping setups. Real-Time Level Labels: Clear, real-time labels (0.5, 0.618, 0.786, 1.0) on the right axis provide exact price targets and stop-loss anchors at a glance. Customizable Projection Length: Adjust how far the indicator looks into the "future," allowing you to anticipate structural shifts before they occur on the chart. Adaptive UI Positioning: The dashboard can be moved to any corner of the chart and scaled to match your screen resolution, ensuring it never interferes with your technical analysis. 🔵 STRATEGIC APPLICATION The "Golden" Pullback: In a confirmed Bull trend (Cyan baseline), wait for price to enter the Dynamic Golden Pocket. Use the saturation of the baseFill color to identify the core of the value zone for a long entry. MTF Confluence Trading: Only take trades when at least three timeframes on the dashboard show the same trend direction. If the 1H and 4H are "BULL" while the 15m enters the "INSIDE" pocket, you have a high-probability trend-continuation setup. Volatility Breakouts: Monitor the distance between the baseline and the 0.5 Fib. When the ATR-based envelopes contract, a volatility breakout is imminent. A "⦿" label signal combined with a price cross of the 1.0 level marks the start of a new momentum cycle. Dynamic Exit Planning: Use the projected 0.5 or 0.618 levels as trailing profit targets. Because these levels adjust for both price and volatility, they represent a mathematically "fair" area to take chips off the table. ATR Fibonacci Trend Envelopes bridges the gap between classic technical analysis and modern volatility modeling. By combining MTF awareness with the natural pull of the Fibonacci ratios, it provides a clear, actionable map for navigating any market condition.
مؤشر Pine Script®
من ‎BigBeluga‎
10
Concordance Strategy [JOAT]JOAT Concordance Strategy Introduction JOAT Concordance Strategy is an open-source multi-factor TradingView strategy designed to integrate the JOAT indicator stack into one execution framework. It combines regime context, liquidity interaction, retracement logic, pressure confirmation, channel behavior, and participation filters to decide when enough independent evidence exists to justify a trade. The problem it solves is single-factor dependency. Trend-only systems often chase poor location. Liquidity-only systems can trigger too early. Oscillator-only systems can fade strong directional auctions. Retracement-only systems can buy weak pullbacks without sponsorship. This strategy attempts to solve that by requiring overlap. It does not assume one tool family is sufficient on its own. Instead, it asks whether multiple analytical dimensions agree. That agreement is what the strategy calls concordance. Core Concepts 1. Regime Gate The strategy first evaluates local and higher-timeframe baseline structure, slope, volatility state, and directional control. 2. Hard and Soft Directional States The system uses stronger and softer directional states instead of an all-or-nothing gate. 3. Liquidity and Structure Stack Entries consider sweep behavior, break state, and displacement. 4. Retracement and Confluence Layer Local and HTF retracement context help determine whether price is pulling back into a structurally meaningful area. 5. Pressure Confirmation Pressure logic attempts to confirm that price action has sponsorship behind it rather than only visual momentum. 6. Sigma Channel State Channel logic helps determine whether price is re-entering a directional path or fading from extension. 7. Participation Filter Relative volume and delta-style participation help avoid weak sponsorship environments. 8. Risk and Exit Model The strategy uses structure-aware ATR stops, partial exits, break-even logic, trailing behavior, and optional time exits. Features Integrated multi-factor entry model: regime, liquidity, retracement, pressure, channel, and participation More active soft-entry path: allows more trades while keeping directional structure Confirmed-bar logic: entries use confirmed state conditions Equity-risk sizing: position size is derived from risk per trade ATR and structure-aware stops: volatility and market structure both matter Two-stage profit taking: TP1 and TP2 split the exit logic Break-even and trailing logic: protects trades after expansion Time-based exit: removes stale positions when needed Dashboard: regime, confluence, pressure, ledger, and position state are displayed Strategy Properties Used by Default Initial capital: 100000 Commission type: percent Commission value: 0.02 Pyramiding: 0 Position sizing: equity-risk based Trade management: partial exits, break-even logic, ATR trail, optional time exit How to Use This Strategy Step 1: Treat it as a research framework rather than a promise of future performance. Step 2: Evaluate it across multiple markets and timeframes because the more permissive logic should produce broader participation than the earlier strict version. Step 3: Judge the quality of the trade distribution rather than focusing on one isolated metric. Step 4: Respect the compromises between selectivity and trade frequency. Step 5: Use realistic expectations and avoid reading a single backtest as proof of repeatable future outcomes. Strategy Limitations The strategy still depends on confirmed conditions and can therefore enter later than a discretionary trader Trade frequency and quality vary significantly by symbol and timeframe Default settings are general-purpose and may not be ideal for every market Optimizing too aggressively can become curve fitting Backtest results are hypothetical and do not guarantee future performance Originality Statement This strategy is original in how it requires agreement across regime, liquidity, retracement, pressure, channel, and participation modules before or during entry qualification. The components are not merged simply to produce a busier system. Each one addresses a different failure mode in execution. Their overlap is the basis for participation. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice. Backtest results are hypothetical and depend on assumptions, settings, and market selection. They do not guarantee future returns. Trading involves substantial risk of loss. Always validate assumptions independently and use responsible risk management. Best Use Cases Researching whether cross-confirmation improves selectivity over single-factor systems Studying how regime, liquidity, retracement, and participation interact inside one strategy Comparing trade frequency across markets and timeframes after the softer entry expansion Testing realistic risk-management assumptions inside a multi-layer strategy Interpretation Notes This strategy should be evaluated as a process, not as a single summary metric. Trade count matters. Distribution of trades matters. How the system behaves across different instruments matters. The softer entry path was added to prevent the strategy from becoming too inactive, especially on higher timeframes. That makes the strategy more usable for broad testing while still preserving directional structure. Publication Notes This strategy should be published with a clean chart and realistic default Properties. If showing results, the description should stay grounded and avoid implying that one test run guarantees future outcomes. The chart image should make the strategy entries and exits easy to understand. -Made with passion by jackofalltrades Evaluation Framework 1. Start by checking whether the strategy is active on the instrument and timeframe you care about. 2. Compare trade count before and after threshold changes. 3. Review whether trade quality remains acceptable as activity increases. 4. Study the interaction between regime, liquidity, pressure, and participation at entry. 5. Judge the strategy by distribution and robustness rather than one isolated metric. Why This Matters The strategy exists to test whether agreement across multiple independent analytical layers can improve execution quality. That research question is more important than any one headline metric. Open-Source Notes This strategy is published open source so users can inspect how the modules overlap and how the risk model is applied. Who This Is For This strategy is for users who want to study how multiple context layers can be combined inside one execution model. It is not intended for anyone looking for a one-click guarantee. Summary JOAT Concordance Strategy is best understood as a structured research tool. It exists to test whether regime, liquidity, retracement, pressure, channel, and participation agreement can improve decision quality. Additional Notes This strategy should be judged with realistic commission and execution assumptions. It should also be evaluated on enough trades to produce a meaningful sample. The defaults are intended to stay grounded rather than theatrical.
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Charter Execution Model [JOAT]Charter Execution Model Introduction Charter Execution Model is an open-source Pine Script v6 strategy that integrates the broader JOAT framework into a single non-repainting execution model. It does not rely on one trigger alone. Instead, it uses a hierarchy of filters: regime eligibility first, liquidity bias second, structure confirmation third, and imbalance or displacement triggers fourth. Only when those layers align does the strategy consider taking a trade. The goal of this strategy is not to present a magical black box. It is to model a disciplined decision stack. Many strategies fail because they treat every trigger the same way regardless of context. Charter Execution Model is built around the idea that context should do most of the work. If the market is not in a mature directional regime, if the liquidity ledger is not skewed appropriately, or if local structure does not agree, then a trigger by itself is not enough. The script uses realistic execution controls directly in the declaration: fixed initial capital, percent-of-equity sizing, non-zero commission, non-zero slippage, no pyramiding, confirmed-bar evaluation, and orders processed on close. Those defaults are intended to make the backtest more responsible and easier to interpret than an overly aggressive model with idealized execution assumptions. This strategy is best understood as a research framework. It can help traders study how context filters, imbalance triggers, continuation pressure, and ATR-based exits behave when combined inside one model. It is not a guarantee of future profitability, and it should be evaluated thoughtfully across symbols, regimes, and timeframes. Core Concepts 1. Regime Eligibility Layer The first gate determines whether the market is mature enough to even consider longs or shorts. It uses a directional midpoint and structural midpoint built from EMA and HMA references, then normalizes their spread by ATR and combines that with heat positioning inside the recent price range. bool bullRegime = directionalMid > structuralMid float regimeStrength = clamp(spreadNorm * 0.60 + math.abs(heatNorm - 50.0) * 0.80, 0, 100) bool matureBullRegime = bullRegime and regimeStrength >= regimeFloor and regimePersistence >= 12 That means the strategy does not allow triggers to fire in weak or undeveloped directional states. Context comes first. 2. Liquidity Bias Layer Next, the strategy builds a rolling bin-based liquidity distribution and compares buy-side volume versus sell-side volume. A long context requires positive liquidity bias and price above the reference EMA. A short context requires negative liquidity bias and price below the reference EMA. This adds an inventory-style filter so the strategy is not trading purely off price shape. 3. Structure Filter Local structure is confirmed using pivot-derived reference points and a rolling swing lookback. Longs require price to hold above recent swing support and above the slow EMA. Shorts require the inverse. This helps reduce cases where a regime and liquidity reading are still positive or negative, but local price structure has already started to degrade. 4. Trigger Stack Once context aligns, the strategy allows three possible triggers: a confirmed imbalance gap, a displacement shift, or an optional continuation retest into the directional midpoint. This means the model can participate through both fresh displacement and controlled continuation. Importantly, the trigger layer does not override the context layer. It only becomes active when the earlier filters already agree. 5. ATR-Based Exit Framework Risk management is handled through ATR-sensitive invalidation and two fixed-R profit targets. When the regime is especially strong, an optional trailing rule tightens the stop using recent local price action. This creates a trade structure with a defined stop, two staged exits, and optional adaptation in stronger conditions without relying on unrealistic all-in-all-out assumptions. Features Four-layer decision hierarchy: Regime, liquidity, structure, and trigger conditions must align before entry Confirmed-bar logic: Entries are evaluated only on confirmed bars to avoid repaint-style execution logic Non-zero execution costs: Includes realistic commission and slippage in the strategy declaration No pyramiding: Prevents stacking multiple positions in the same direction Partial profit framework: Uses two independent `strategy.exit()` orders to scale out at separate R multiples Optional continuation triggers: Allows pullback-style participation inside already qualified context Optional strong-regime trailing stop: Tightens exits when regime strength is elevated Dashboard summary: Displays regime, liquidity bias, pressure, trigger state, position state, stop settings, and current risk fields Clean visual overlay: Shows directional and structural mids with contextual fill directly on the chart Open-source research design: Lets users inspect and adapt the full context-to-execution hierarchy Default Strategy Properties Initial capital: `100000` is used as the default starting capital in the script declaration Position sizing: Orders use `strategy.percent_of_equity` with a default quantity of `10`, meaning the strategy allocates 10% of equity per position by default Commission: Commission is modeled as `0.02%` per trade Slippage: Slippage is modeled as `2` ticks Pyramiding: Pyramiding is set to `0`, so the model does not stack entries in the same direction Order timing: `process_orders_on_close = true` and `calc_on_every_tick = false`, so the model evaluates and processes with confirmed-bar logic Input Parameters Regime: Fast Length: Controls the fast directional reference Slow Length: Controls the slow structural reference ATR Length: Sets the ATR normalization length Heat Window: Defines the range window for heat normalization Regime Strength Floor: Sets the minimum maturity threshold for context eligibility Liquidity Filter: Liquidity Lookback: Sets the rolling history used for the liquidity model Liquidity Bins: Controls the liquidity distribution granularity Liquidity Bias Floor: Sets the minimum skew required before liquidity counts as directional Structure Filter: Pivot Length: Sets pivot confirmation sensitivity Swing Lookback: Defines the rolling structural context window Trigger Stack: Gap Sigma Filter: Sets the minimum imbalance displacement required for gap-style triggers Shift Momentum Length: Controls the raw momentum lookback Shift RSI Length: Controls the pressure RSI smoothing Displacement Floor: Sets the threshold for shift-style triggers Allow Continuation Triggers: Enables or disables pullback continuation entries Continuation Pressure Floor: Sets the minimum pressure level for continuation logic Risk Management: Stop ATR Multiplier: Scales the ATR contribution to stop placement Target 1 R: Sets the first partial profit target Target 2 R: Sets the second partial profit target Trail In Strong Regime: Enables optional trailing behavior when regime strength is elevated How to Use This Strategy Step 1: Evaluate Context Before Results Begin by understanding what the strategy is trying to do rather than focusing immediately on performance output. It only wants to trade when a mature regime, directional liquidity bias, and confirming structure are all aligned. If that idea does not match your own process, the results will be hard to interpret. Step 2: Study Trigger Type Distribution Not all entries come from the same source. Some come from imbalance gaps, some from displacement shifts, and some from continuation pressure. Understanding which trigger type dominates on a given market can be more useful than simply checking net profit. Step 3: Understand The Exit Framework The model uses a staged exit approach. Half the position is managed toward the first target and half toward the second. A stop is always active, and strong-regime trailing can tighten the exit path further. Review this logic carefully before drawing conclusions from the backtest. Step 4: Keep Expectations Realistic The strategy includes commission, slippage, confirmed-bar logic, and no pyramiding, but that still does not make the backtest “real.” Results depend on the instrument, the timeframe, the data sample, and how well the context assumptions fit the market studied. Step 5: Use It As A Research Framework Charter Execution Model is best used as a framework for studying context-first execution logic. Adapt the filters, test the thresholds, and evaluate how the hierarchy behaves across different environments rather than assuming the defaults are universally optimal. Strategy Limitations The strategy relies on historical context filters that may adapt poorly to sudden regime shifts or atypical event-driven conditions Liquidity bias is based on bar-level directional volume attribution rather than true exchange order-flow data Processing orders on close simplifies execution and can differ materially from real fills on fast markets Backtest results are sensitive to parameter choices, timeframe selection, instrument behavior, and dataset length Originality Statement Charter Execution Model is original in the way it organizes multiple analytical layers into a disciplined execution hierarchy. It is not published as a simple indicator mashup strategy: It requires mature regime, directional liquidity bias, and local structure to align before any trigger is allowed to matter It supports multiple trigger archetypes inside the same context framework rather than treating one trigger as universally sufficient It combines staged exits, ATR-sensitive invalidation, and optional strong-regime trailing inside a consistent risk model It exposes its internal context state on-chart so users can study why the strategy is active or inactive at any point Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Backtest results depend on assumptions, data quality, slippage, commission, bar resolution, and market conditions. Past performance does not guarantee future results. Always use independent judgment and proper risk management before using any strategy logic in live markets. -Made with passion by jackofalltrades
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Concordance Regime Synthesis [JOAT]Concordance Regime Synthesis Introduction Concordance Regime Synthesis is an open-source strategy framework that combines regime state, pressure, participation, structure, and higher-timeframe bias into one non-repainting confluence model. The strategy is designed to avoid single-factor entries by requiring multiple independent conditions to align before risk is deployed. Core Concepts 1. Multi-factor confluence scoring Long and short setups are scored independently using regime direction, normalized price pressure, participation-axis deviation, delta behavior, recent structure, and optional higher-timeframe bias. 2. Regime-aware execution Entries only occur when directional confluence exceeds a threshold and the score spread clearly favors one side. 3. ATR-based risk handling Stops, targets, and optional trailing logic are all derived from ATR so the strategy adapts to volatility instead of using fixed-tick assumptions. Strategy Properties Initial capital: 10,000 Order size: 10% of equity per trade Commission: 0.06% Slippage: 1 tick Pyramiding: 0 Orders processed on close Originality Statement This strategy is original in its use of a confluence gate that requires independent agreement from regime, pressure, delta, participation, structure, and optional HTF alignment before entries are allowed. It is published as an educational framework for multi-factor strategy construction rather than as a promise of future performance. Disclaimer This strategy is for educational and informational purposes only. Backtest results depend on symbol, timeframe, market regime, and execution assumptions. Historical results do not guarantee future returns. Always validate assumptions and use realistic risk controls.
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Custom Buy/Sell IndicatorCreate you own custom strategies using this 'Custom Buy/Sell Indicator'. It allows other indicators to be combined together into a BUY/SELL strategy, using up to seven separate rules. It is essentially the same as my 'Simple Buy/Sell Indicator', but combines up to seven rules rather than just four, plus the rules can be combined using various different logical expressions. There are ten different logical expressions which should cover many common usages, however the list is by no means exhaustive. Should you require a different expression, drop me a comment and I'll try to provide an update. The output is: 1 = BUY 0 = None -1 = SELL This can then be used as an input to my 'Simple Pyramid Strategy' or my 'Complex Single Trade Strategy'. Each rule compares two values with can be zero centred with an offset of -50 to make it So instead of testing for overbought and oversold with > 70 and < 30, you would offset by -50. Then you would test for > 20 (overbought), which becomes < -20 (oversold) when inverted.
مؤشر Pine Script®
من ‎JustinTimeTunes‎
Complex Single Trade StrategyThis 'Complex Single Trade Strategy' is a generic trading strategy that features three different types of stops, and four take profits. It takes a Buy/Sell source input of: The first signal will trigger a position to open immediately in that direction, but subsequent signals in the same direction will be ignored whilst the position remains open, as this strategy allows only one position at once. A signal in the opposite direction to the current position can either be ignored, or it can close the position, or it can close it then immediately open another one in the opposite direction. It also takes an optional 'Cancel' indicator just to close positions. Other signals will be ignored. The three different types of stops, that can be applied individually, or together: * Regular Stop * Initial Trailing Stop * Trailing Stop The initial trailing stop works like a regular trailing stop until it reaches the cut off level, a percentage of the current asset price above or below the entry level, then it will no longer trail the price, remaining statically at this level. From here the regular trailing stop can take over trailing the price. This is useful to move the stop to the entry level (or there abouts) fairly quickly. From there you might want to trail the price with a larger trailing stop for the rest of the trade. 0 cut off means it stops trailing the price at your entry level, positive above, negative below, for a long trade. For a short it would be the opposite. Typically you would want: Trailing Stop > Initial Trailing Stop >= Stop The four take profits each specify an amount to reduce the position size by, and at what specified percentage gain in price this is triggered. My 'Simple Buy/Sell Indicator' and 'Custom Buy/Sell Indicator' (coming soon - watch this space) can be used to combine other indicators together into BUY/SELL strategies, using multiple custom rules. These can then be used as inputs to this strategy.
استراتيجية Pine Script®
من ‎JustinTimeTunes‎
SMC CHOCH BOS Dual Structure + Candle Color v6📊 SMC CHOCH & BOS Dual Structure Indicator — User Guide This indicator is designed to map market structure using Smart Money Concepts (SMC), combining: CHOCH (Change of Character) BOS (Break of Structure) Swing Structure (macro) Internal Structure (micro) Dynamic candle coloring based on structural shifts It provides a complete framework to understand trend shifts, confirmations, and execution timing. 🧠 CORE CONCEPTS 🔹 CHOCH (Change of Character) Represents a potential reversal in market direction. Bullish CHOCH → Market shifts from bearish to bullish Bearish CHOCH → Market shifts from bullish to bearish 👉 This is the early signal, but not always confirmed. 🔹 BOS (Break of Structure) Represents trend continuation or confirmation. Occurs when price breaks previous structure in the direction of the trend The first BOS after a CHOCH is especially important 👉 This is the confirmation phase. ⚙️ SETTINGS EXPLAINED 🔸 Show Structure Swing → Displays macro structure (clean, less noise) Internal → Displays micro structure (faster, more signals) Both → Combines both for full context 👉 Recommended: Both 🔸 Swing Structure Length Controls the sensitivity of macro structure. Higher value → smoother, fewer signals Lower value → more reactive 👉 Recommended: 8–15 🔸 Internal Structure Length Controls micro structure detection. Lower value → faster signals Higher value → more filtering 👉 Recommended: 2–5 🔸 Confirm Break By Candle Close ON → Break only confirmed after candle closes (more reliable) OFF → Break detected instantly (faster, more aggressive) 👉 Recommended: ON 🔸 Candle Color Based On Defines which structure controls candle coloring: Swing → slower, trend-based coloring Internal → faster, execution-based coloring 👉 Recommended: Swing → for bias Internal → for entries 🔸 Change Candle Color On Defines when the trend/color shifts: CHOCH Faster reaction More signals Higher risk First BOS After CHOCH More confirmation Fewer signals Higher probability 👉 Recommended: First BOS After CHOCH 🔸 Color Candles ON → candles follow structural direction OFF → structure only (lines + labels) 🔸 Colors Customize: Swing bullish/bearish Internal bullish/bearish Candle colors 🔸 Show BOS/CHOCH Text Displays text labels directly on structure lines: No background Centered on the line Clean visual style 📈 HOW TO USE (PROFESSIONAL APPROACH) 🔹 1. Define Direction (Swing Structure) Use Swing CHOCH + BOS to identify overall bias Only trade in the direction of Swing trend 🔹 2. Execute with Internal Structure Wait for Internal CHOCH Then confirm with Internal BOS 👉 This is your entry trigger 🔹 3. Best Setup (High Probability) ✔ Swing trend bullish ✔ Internal CHOCH (pullback ends) ✔ First BOS confirms continuation 👉 That’s your trade ⚠️ COMMON MISTAKES ❌ Trading CHOCH alone ❌ Ignoring higher timeframe structure ❌ Entering after extended moves ❌ Using Internal signals against Swing trend 🔥 SIMPLE RULE SET CHOCH = potential shift BOS = confirmation Swing = direction Internal = execution 🎯 FINAL THOUGHT This indicator is not just for signals — it’s a market structure framework. If used correctly, it helps you: Avoid late entries Trade with structure, not emotion Align with institutional flow
مؤشر Pine Script®
من ‎rodrigodearantes2022‎
Failed Pullback Reversal Planner [AGPro Series]Failed Pullback Reversal Planner 🧠 Core Idea Did the pullback fail to recover, and is it now creating a reversal-warning context? 📌 Overview / What it does Failed Pullback Reversal Planner is a chart-first reversal risk planner built for one specific situation: a pullback inside an existing trend stops behaving like a healthy retracement and begins losing control. The script maps a failed pullback pocket, control-loss rail, invalidation reference, target-room guide, compact state labels, alerts, and a clean AG Pro panel. It converts pullback depth, failed recovery, close behavior, volume response, and follow-through into a 0-100 Failure Score. It does not predict future price movement, automate entries, or issue guaranteed buy/sell signals. Its role is to organize failed-pullback context into a clearer decision framework. 🎯 Purpose & Design Philosophy This script was built because many pullback tools only focus on continuation quality. They often ask whether the pullback is healthy enough to resume the original trend. Failed Pullback Reversal Planner focuses on the opposite decision layer. It asks whether the pullback failed to recover, lost the control reference, and now deserves reversal-risk review. The design supports traders who want cleaner structure, risk location, target-room context, and next-action guidance without turning every candle into a signal. ⚡ Why This Script Is Different Most tools focus on pullback continuation, moving-average bounces, or generic reversal markers. This script does NOT clone Pullback Acceptance Planner, Low Volume Pullback Zones, Trend Continuation Quality, or a generic reversal signal indicator. Instead, it treats failed pullbacks as a planning problem. Price must first enter a pullback context, then fail recovery around a control rail, then show enough close quality, volume response, and follow-through to raise reversal-risk state. ⚙️ Methodology 1. Context Detection The script identifies former bullish or bearish trend context using fast, base, and slow EMA alignment. 2. Reference Mapping It builds a failed pullback pocket, control-loss rail, invalidation reference, and target-room guide using ATR-normalized logic. 3. Reaction Evaluation It scores pullback depth, failed recovery, close against the former trend, volume response, and nearby follow-through. 4. Visual Output It displays concept-native zones, centered zone labels, compact event labels, guide rails, alerts, and a premium AG Pro planning panel. 🗺️ How to Read the Chart Zones = the failed pullback pocket and reversal-risk zone. Labels = pullback test, control-loss, reversal-risk, or reset markers. Colors = teal shows bullish reversal-risk context, pink shows bearish reversal-risk context, amber shows watch context, red shows control-loss or risk context, and indigo shows reset/recovery context. Panel = a compact decision dashboard showing Pullback State, Failure Score, Reversal Risk, Invalidation, and Action. 🚦 Signals & States • PB TEST → a recent pullback is being monitored for failed-recovery behavior. • CTRL LOST → price has lost the control reference but has not fully qualified the warning state. • REV RISK → failed pullback context has enough score to deserve reversal-risk review. • RESET → optional marker showing that price reclaimed the invalidation reference and the failed-pullback plan should be reset. • NO SETUP → no active failed-pullback context is present. 🔔 Alerts Logic Alerts trigger when the planner detects a monitored failed-pullback setup, a reversal-risk warning, invalidation/reset behavior, or meaningful follow-through after control loss. Alerts are attention markers only. They are not trade instructions. 🧩 Confluence Logic The strongest failed-pullback context appears when pullback depth is meaningful, price loses the control rail, the candle closes against the former trend, volume supports the shift, and follow-through begins beyond nearby structure. When these components align, the Failure Score rises and the panel moves from watch context toward reversal-risk review. 📊 When to Use • Trend pullbacks that start losing recovery quality • Potential reversal transitions after a failed retracement • Markets where a prior trend is weakening around a control reference • Situations where invalidation and target-room context matter ⚠️ When NOT to Use • Very low liquidity markets • Extremely noisy sideways conditions • News-driven volatility spikes • Markets with no clean prior trend context • Symbols where volume behavior is unreliable 🎛️ Key Inputs • Sensitivity → controls how strict the failed-pullback model is. • Former Trend Side → restricts evaluation to bullish-trend or bearish-trend failures when needed. • Failure Window Bars → defines how long after a pullback touch control-loss behavior can qualify. • Control-Loss Buffer ATR → adjusts the rail used to mark failed recovery. • Invalidation Buffer ATR → controls the reset reference beyond the fast trend anchor. • Label and Panel Settings → control panel location, theme, font size, label size, label spacing, and visible label count. 🖥️ Interface & Visual Design The interface is built around a clean AG Pro decision panel and chart-first planning visuals. The first panel row uses the AG Pro merged blue header standard with only the script name. The remaining rows focus on the active decision: pullback state, failure score, reversal risk, invalidation, and action. The chart uses a focused failed pullback pocket, a reversal-risk zone, guide rails, and compact labels. The goal is a premium planning view without crowded generic signals. 🧪 Practical Usage Workflow 1. Read the panel state. 2. Check whether a pullback test is active. 3. Watch whether price loses the control rail. 4. Review the Failure Score and reversal-risk label. 5. Compare the invalidation reference and target-room guide before interpreting the context. 🔍 Interpretation Guidelines Think in terms of failed recovery quality, not prediction. A higher Failure Score means the current pullback has stronger failed-recovery characteristics across depth, control loss, close behavior, volume, and follow-through. A control-loss state means the setup is weakening but may still need more confirmation. A reset state means the failed-pullback idea has been reclaimed and should be reassessed. 🚫 What This Script Is NOT • Not a prediction engine • Not financial advice • Not auto trading • Not guaranteed signals • Not a generic pullback continuation indicator ⚠️ Limitations & Transparency • Timeframe differences can change how pullback depth and failure windows appear. • High volatility can distort ATR-normalized rails. • Low-volume instruments may reduce the reliability of the volume component. • Sideways markets can create repeated failed-pullback noise. • Outputs should be interpreted with broader market structure. 🧠 Market Context Notes Failed pullbacks often matter when a market was expected to recover in the direction of the prior trend but instead loses the control reference. The script does not assume that every failed recovery becomes a full reversal. It simply marks when the context is strong enough to deserve review. 🧾 Use Case Examples When a bullish trend pulls back toward the fast/base EMA area, fails to recover, and closes below the control rail with stronger participation, the planner may raise bearish reversal-risk context. When a bearish trend pulls back upward, fails to reject lower, and closes above the control rail with follow-through, the planner may raise bullish reversal-risk context. 🧱 System Philosophy The script is built around decision quality. It does not try to add another signal layer. It asks whether a specific market behavior is valid, how strong it is, where it is invalidated, and what should be reviewed next. 🔐 Non-Promise Statement No guarantees. No certainty. The script organizes observable market behavior into a structured analytical view. 📉 Risk Disclosure Trading involves risk. Users are responsible for their own analysis, risk management, and decisions. This script does not provide financial advice or guaranteed trading outcomes. 📚 Educational Note Use the planner as an educational framework for studying failed pullbacks, recovery quality, control loss, and reversal-risk context.
مؤشر Pine Script®
من ‎AGProLabs‎
Concordia Regime Execution [JOAT]Concordia Regime Execution Introduction Concordia Regime Execution is an open-source TradingView strategy that integrates regime detection, trend bias, structure, momentum breadth, pressure confirmation, and ATR-based risk management into one non-repainting execution model. The strategy is built as a realistic framework rather than a curve-fit showcase. The problem Concordia solves is signal fragmentation. Regime, trend, structure, and momentum are often evaluated separately, which leads to entries taken in the wrong environment. Concordia requires multiple engines to align before a position is opened, then manages risk through predefined stop, target, trailing, and bias-failure exits. Core Concepts 1. Regime Detection ADX, choppiness, and compression work together to classify whether the market is suitable for directional participation. 2. Trend Bias Filter Fast, intermediate, and structural EMAs plus anchored VWAP context define directional bias before any entry can pass. 3. Structure Confirmation Confirmed bullish or bearish breaks of recent swing structure add structural alignment to the trade decision. 4. Momentum Breadth A compact ribbon engine classifies whether fast momentum is actually expanding in the same direction as trend and structure. 5. Pressure and Risk Layer Chart-derived pressure and crowding inputs help confirm continuation and suppress entries during elevated stress. 6. Risk Management Each trade uses ATR-based initial stop placement, ATR-based profit target, optional trailing activation, and bias-failure closure if internal conditions deteriorate. Features Regime gate: Expansion, compression, and transitional filtering Trend alignment: EMA stack plus anchored VWAP bias logic Structure filter: Recent swing break confirmation Momentum breadth: Ribbon spread confirmation instead of a single oscillator line Pressure confirmation: Chart-derived directional pressure and crowding logic Risk model: ATR stop, ATR target, trailing trigger, and bias-failure exit Top-right dashboard: Regime, bias, structure, momentum, pressure, risk, setup scores, active position, and stop/target levels Confirmed-bar entries: All setup logic is gated on confirmed bars How to Use This Strategy Step 1: Start with liquid markets Concordia is better suited to instruments where anchored VWAP, ATR, and structure transitions behave consistently. Step 2: Use realistic assumptions Commission, slippage, and position sizing inputs should match your actual market and trading conditions before evaluating performance. Step 3: Evaluate regime quality first The strategy is intentionally selective. If the market is compressing or structurally unstable, fewer trades should occur. Step 4: Review bias-failure exits These exits are included to avoid overstaying trades when internal alignment breaks down before the stop or target is reached. Strategy Limitations Like any rules-based strategy, it can underperform in abrupt gap conditions or news-driven spikes ATR-based exits adapt to volatility, but they are not guaranteed to be optimal for every instrument The strategy is intentionally conservative and may miss some fast reversals Historical performance does not guarantee future results Originality Statement Concordia Regime Execution is original in the way it integrates regime, trend, structure, momentum breadth, pressure confirmation, and ATR-based trade management into a single open-source strategy designed for realistic chart use rather than decorative backtest output. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice and should not be treated as a recommendation to buy or sell any instrument. Strategy results are based on historical chart data and platform assumptions. Live trading results can differ materially. Always validate settings and use independent risk management.
استراتيجية Pine Script®
من ‎officialjackofalltrades‎
Crownmark Allocation Engine [JOAT]Crownmark Allocation Engine Introduction Crownmark Allocation Engine is an open-source TradingView strategy that integrates regime classification, adaptive trend corridors, auction-value context, pressure confirmation, divergence suppression, and ATR-based trade management into one non-repainting framework. Its purpose is not to maximize signal count. Its purpose is to require multiple independent layers to agree before risk is deployed. The problem this strategy solves is overcommitting to one analytical dimension. Trend alone can be late. Pressure alone can be noisy. Divergence alone can fire too early. Auction context alone does not create an entry. Crownmark combines those ideas so that entries occur only when broader regime, local structure, value position, and internal participation are aligned. Core Concepts 1. Regime Filter First The strategy begins with a composite regime score built from fast/slow EMA displacement, ADX strength via `ta.dmi()`, efficiency, volatility expansion, and trend slope. If the regime is not sufficiently directional, the strategy does not permit an entry. 2. Adaptive Corridor Pullback Entry Once regime bias is directional, price must also align with an adaptive KAMA-based corridor. Longs require bullish corridor structure and a pullback that remains constructive relative to the baseline and inner band. Shorts require the mirror condition on the downside. 3. Auction and VWAP Context Price must be positioned acceptably relative to a rolling value area and rolling VWAP. This is intended to keep entries from triggering in structurally poor locations when the rest of the model is favorable. 4. Pressure Confirmation and Divergence Guard The strategy uses an effort-versus-result style pressure model to require directional initiative at the moment of entry. It also suppresses entries when recent confirmed divergence argues against the trade direction. 5. Managed Exits Open positions use ATR-based stop loss and take profit levels, plus a trailing logic anchored to the adaptive baseline. Positions can also be closed by context failure, by opposite signal, or by maximum bar duration in trade. Features Composite regime filter: Trend, ADX, volatility, slope, and efficiency must support the direction Adaptive corridor entries: Uses a KAMA baseline with hybrid ATR/stdev width Auction location filter: Requires acceptable relation to rolling value area and VWAP Pressure confirmation: Requires directional effort-versus-result support Divergence suppression: Recent opposing divergence can block new entries ATR-based risk management: Stop, target, and trailing logic Context exits: Positions can flatten when regime or pressure collapses Dashboard summary: Regime, corridor, auction, pressure, divergence, exposure, and regime score Default Strategy Properties Initial Capital: 100000 Order Size: 10% of equity Pyramiding: 0 Commission: 0.01% Order Processing: on close calc_on_every_tick: false Input Parameters Regime Engine: Fast/Slow regime lengths ADX length Volatility length Efficiency length Bull and bear regime thresholds Trend Corridor: Baseline length KAMA fast and slow parameters Width length Width multiplier Pullback tolerance Auction Context: Auction lookback Value area width Auction acceptance toggle VWAP alignment toggle Risk Management: ATR length Stop ATR multiple Target ATR multiple Trail ATR multiple Maximum bars in trade Flatten on opposite signal toggle How to Use This Strategy Step 1: Verify the Market Type If the regime score is near balance, the strategy is intentionally selective. Crownmark is designed for directional conditions more than rotational ones. Step 2: Let the Entry Layers Stack An entry requires regime, corridor, auction, pressure, and divergence conditions to agree. If one layer is missing, the strategy waits. Step 3: Respect the Exit Logic The strategy uses both price-based and context-based exits. A position can close because the stop or target was reached, but it can also close because the original trade thesis has weakened. Step 4: Review Results in Context Do not evaluate the strategy by win rate alone. Regime selectivity, trade duration, average excursion, commission sensitivity, and the instrument being tested all matter. Strategy Limitations This strategy uses bar-close logic and does not replicate intrabar execution behavior The rolling auction model is a simplified proxy and not a full market profile engine Divergence suppression can skip trades that later work, by design Different assets and timeframes may require threshold tuning to remain realistic Originality Statement Crownmark Allocation Engine is original in how it combines regime scoring, corridor structure, auction-value location, pressure confirmation, and divergence suppression into one coordinated execution model. The strategy is not a basic trend-following template with cosmetic additions. Each layer has a distinct analytical role, and entries are only allowed when those layers support one another. Disclaimer This strategy is provided for educational and informational purposes only. It is not financial advice and does not imply future performance. Backtest results depend heavily on instrument, timeframe, execution assumptions, and historical conditions. Use realistic expectations, confirm settings carefully, and apply sound risk management.
استراتيجية Pine Script®
من ‎officialjackofalltrades‎