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Happy Trigger EliteHAPPY TRIGGER ELITE is a high-performance, structural scalping strategy engineered for precision and explosive growth across high-volatility assets. Developed for the QuantCrawler Discord Community, this strategy bridges the gap between sophisticated pivot analysis and aggressive, high-probability execution. ​At its core, the strategy utilizes a modified LuxAlgo Ghost Engine to detect "Missed Reversals"—critical zones where the market fails to confirm a new high or low, signaling an imminent structural shift. ​🛠️ Key Strategic Pillars ​Structural Ghost Detection: Identifies high-probability reversal points by tracking structural failures rather than just price wicks. ​Dynamic Trailing Logic: Employs a precise "Trail Activation" system designed to lock in profits while giving trades the necessary "breathing room" to reach extended targets. ​Momentum Guard (ATR): Uses an ATR-based volatility filter to ensure the strategy only engages when there is sufficient market participation and "gas in the tank". ​RSI Exhaustion Filter: Prevents "chasing" moves by requiring price to be in an overextended state before a reversal entry is considered. ​🛡️ Institutional-Grade Risk Management ​Built with funded account safety in mind, the strategy includes hard-coded protection features to safeguard your equity: ​Daily Circuit Breaker: An automated shutdown occurs if the user-defined Max Daily Loss is reached, preventing significant drawdowns during choppy market conditions. ​Visual Session Tracking: Automatically identifies peak volume windows, providing a clear visual guide for optimal trading environments. ​Account Buffer Logic: Calibrated to maintain a stable equity curve by balancing aggressive targets with tight risk-to-reward parameters. Credit: LuxAlgo Optimized by: MeliMillionaire247
Pine Script®策略
由MeliMillionaire247提供
SMC Pro BTC - ICT Order Blocks & FVG [DOE]# SMC Pro BTC - ICT Order Blocks & FVG A multi-timeframe smart money concepts engine built exclusively for Bitcoin. This indicator combines order blocks, fair value gaps, liquidity sweeps, break of structure, and premium discount zone analysis into one backtest-verified, non-repainting strategy — every signal you see in history is exactly what you would have seen live. Built by a former quantitative analyst from a US-based systematic fund. The structural logic behind this indicator is the same order flow mechanics that institutional algorithms use to identify and exploit liquidity imbalances — adapted for retail traders on TradingView. At the fund, we did not use RSI or MACD. We tracked where unfilled orders sat, where liquidity clustered, and where price needed to travel to resolve imbalances. That is what Smart Money Concepts formalizes, and that is what this indicator automates. This is a free, open-source tool. All backtest results below are fully reproducible on your chart with the default settings. No hidden parameters. No curve-fitting. No repainting. ## TWO STRATEGY MODES — CHOOSE YOUR RISK PROFILE The indicator offers two distinct execution modes built on the same structural foundation. The difference is filter strictness — one prioritizes opportunity, the other prioritizes quality. Both include commissions and slippage in their backtested results, because a backtest without commissions is fiction. ### AGGRESSIVE MODE Entries fire on any valid Break of Structure (BOS) or Change of Character (CHoCH) confirmed by an order block and fair value gap on the confirmation timeframe. This mode captures more setups, including momentum re-entries and early reversal signals. It accepts a lower win rate in exchange for catching a larger portion of trending moves. | Metric | Value | |---|---| | Total Trades | 55 | | Win Rate | 49.09% | | Net P&L | +49.12% | | Profit Factor | 1.41 | | Max Drawdown | 14.70% | A 49% win rate may not sound impressive on the surface. But this is not a coin flip. The 1.41 profit factor means that winning trades meaningfully outweigh losers — the strategy is designed to let winners run through a configurable risk-to-reward ratio. Over 55 trades with real commissions (0.075% per trade) and slippage (3 ticks per order), the system returned nearly 50% on initial capital. That is what positive expectancy looks like in practice. Mark Douglas wrote that there is a random distribution between wins and losses for any set of variables that define an edge. You do not need to win every trade. You need an edge and the discipline to follow it over a series. This mode is built for that exact mindset. ### SELECTIVE MODE Adds a premium/discount zone filter on top of all Aggressive conditions. Longs are only permitted in the discount zone of the higher-timeframe dealing range. Shorts are only permitted in the premium zone. This single structural filter cuts the trade count by more than half while dramatically improving signal quality. | Metric | Value | |---|---| | Total Trades | 21 | | Win Rate | 61.90% | | Net P&L | +26.92% | | Profit Factor | 2.347 | | Max Drawdown | 8.66% | A profit factor above 2.0 combined with single-digit drawdown is rare for any fully disclosed, non-repainting BTC strategy. The Selective mode achieves both over three full years of data. The tradeoff is fewer trades — 21 versus 55 — which means this mode requires patience. It is designed for traders who prefer waiting for optimal positioning over catching every move. Both modes are provided so you can evaluate the tradeoff between frequency and precision on your own terms. There is no objectively "better" mode. There is only the mode that matches your risk tolerance and psychological profile. ## ENTRY LOGIC — STEP BY STEP Every signal is generated through a strict multi-timeframe confluence model. No single condition is sufficient. The indicator requires alignment across structure, zone, imbalance, and liquidity before producing a signal. Here is the full logic for long entries — short entries mirror the process with inverted conditions. ### LONG ENTRY SEQUENCE **Step 1 — HTF Directional Bias (Break of Structure)** The Direction Timeframe (default: 4H) detects a bullish break of structure or change of character using swing highs and lows. This establishes the higher-timeframe directional bias. Without bullish structure on the HTF, no long signal can fire. This is the first gate. **Step 2 — MTF Confirmation (Structural Alignment)** The Confirmation Timeframe (default: 1H) must confirm with its own bullish BOS or CHoCH, aligning both timeframes in the same direction. This dual-timeframe structural alignment filters out a significant amount of noise and counter-trend traps. **Step 3 — Order Block Identification** The script looks back up to the configured OB Lookback Bars to find the last bearish candle before the impulsive bullish move — the order block where smart money accumulated positions. This zone represents an area of institutional demand that is likely to attract price on a revisit. **Step 4 — Fair Value Gap Validation** The indicator checks for a bullish fair value gap (the gap between candle 1's high and candle 3's low in a three-candle sequence) that overlaps the identified order block zone. An OB alone is a level. An OB combined with an FVG is confluence — two independent structural signals agreeing on the same price zone. This overlap is where the highest-probability entries concentrate. **Step 5 — Liquidity Sweep Confirmation** Before the signal can fire, the indicator verifies that a recent liquidity sweep occurred within the configured Sweep Memory window. A liquidity sweep means price dipped below a prior swing low, triggering stop-loss orders and pending sell orders, before reversing. This is the classic ICT stop hunt — institutional participants accumulating liquidity from retail stop-outs. Without this sweep, the setup lacks the liquidity fuel that drives the reversal. **Step 6 — Premium/Discount Zone Filter (Selective Mode Only)** In Selective mode, the entry must occur in the discount zone of the HTF dealing range, defined by the P/D Zone Threshold parameter. This ensures longs are taken only when price is trading at a structural discount — the lowest-risk portion of the range. **Step 7 — Execution** All conditions are met. The long signal fires on the next confirmed bar. Stop-loss is placed below the order block low minus the SL Buffer percentage. Take-profit is calculated at the configured Risk:Reward Ratio distance from entry. Both levels are plotted visually on the chart. ### SHORT ENTRY SEQUENCE The short entry mirrors the long with inverted conditions across all seven steps: 1. HTF bearish BOS or CHoCH establishes bearish bias 2. MTF bearish BOS or CHoCH confirms the direction 3. Bearish order block identified (last bullish candle before the sell-off) 4. Bearish fair value gap overlaps the order block zone 5. Liquidity sweep above a prior swing high (stop hunt to the upside) 6. Price in the premium zone of the HTF dealing range (Selective mode only) 7. SL placed above OB high plus buffer; TP calculated at R:R distance below entry Every step is objective. There is no discretionary component. The indicator either detects the confluence or it does not. This is not chart art — it is structure, codified. ## FEATURES - Non-repainting, non-lookahead signals — barstate.isconfirmed enforced on all calculations; what you see in history is what you would have seen live - Multi-timeframe structure analysis — HTF for direction, MTF for confirmation, entry timeframe for execution - Order block detection with configurable lookback depth and automatic invalidation when price trades through the zone - Fair value gap multi-zone display — shows up to N unfilled FVGs per direction simultaneously, configurable by maximum count and maximum distance from current price, so you only see the gaps that are structurally relevant to your current timeframe and price action - Liquidity sweep recognition with adjustable memory window for detecting stop hunts before entries - Break of Structure (BOS) and Change of Character (CHoCH) detection via swing-point analysis on multiple timeframes - Premium/discount zone mapping from the HTF dealing range, with configurable threshold for zone extremes - Automatic trade management — stop-loss and take-profit levels plotted with visual trade boxes on every signal - Two strategy modes — Aggressive for opportunity-seeking traders, Selective for precision-focused traders - Fully configurable parameters — every setting is exposed with sensible defaults optimized for BTC 4H - Built-in strategy engine — run backtests directly in TradingView's Strategy Tester with your own commission and slippage settings - Clean chart presentation — signals, zones, and labels are designed for readability on both desktop and mobile ## SETTINGS DOCUMENTATION **Strategy Mode** — Aggressive / Selective Aggressive uses the full confluence model: BOS/CHoCH + Order Block + FVG + Liquidity Sweep. Selective adds the premium/discount zone filter on top of everything. If you are new to smart money concepts, start with Selective — fewer signals, but each one carries stronger structural backing. **Direction TF (HTF)** — Default: 240 (4H) The higher timeframe that establishes directional bias through structural breaks. Increase to Daily (1440) for fewer, higher-conviction signals on larger moves. Decrease to 60 (1H) for more responsive structure detection on shorter swings. **Confirmation TF (MTF)** — Default: 60 (1H) The mid timeframe that confirms HTF bias before any entry can trigger. Must be lower than or equal to the Direction TF. The default 240/60 pair provides a 4:1 ratio that balances responsiveness with structural reliability. **Swing Length** — Default: 10 | Range: 3-50 The number of bars used to identify swing highs and swing lows for structural analysis. Lower values increase sensitivity (more BOS/CHoCH signals, more noise). Higher values detect only major structural shifts. The default of 10 is balanced for BTC on the 4H timeframe. **OB Lookback Bars** — Default: 15 | Range: 3-30 How far back the script searches for a valid order block after a structural break is detected. Smaller values yield higher precision but may miss valid blocks that formed earlier. Larger values capture more blocks but increase the risk of the OB being partially mitigated. **Sweep Memory** — Default: 20 bars | Range: 5-50 The lookback window for detecting a liquidity sweep before confirming an entry. If valid sweeps are being missed on your asset or timeframe, increase this value. If you want tighter sweep-to-entry timing, decrease it. **Risk:Reward Ratio** — Default: 2.0 | Range: 1.0-5.0 Determines take-profit placement relative to stop-loss distance. At 2.0, the TP is placed twice the SL distance from entry. Higher values produce larger winning trades but lower win rates. Always re-run the backtest after changing this setting to understand the impact on overall expectancy. **SL Buffer %** — Default: 0.3 | Range: 0.0-2.0 A buffer added beyond the order block boundary for stop-loss placement, designed to prevent wick stop-outs on volatile assets like BTC. At 0.3%, a $100,000 OB low places the stop-loss at $99,700. **P/D Zone Threshold** — Default: 0.80 | Range: 0.50-0.85 | Selective Mode Only Controls how deep into the premium or discount zone price must be for an entry to qualify. At 0.80, longs require price to be in the bottom 20% of the HTF range and shorts require the top 20%. At 0.50, the indicator uses standard equilibrium (above/below 50%). This parameter is ignored in Aggressive mode. **Max FVGs per Side** — Default: 5 | Range: 1-10 Controls how many unfilled fair value gaps are displayed per direction (bullish and bearish independently). At 5, the chart shows up to 5 active bullish FVGs and 5 active bearish FVGs simultaneously. Lower values reduce visual clutter on smaller timeframes. Higher values provide more structural context on higher timeframes where gaps may persist longer. When the limit is reached, the oldest FVG is removed to make room for the newest one. **FVG Max Distance %** — Default: 8.0 | Range: 1.0-25.0 FVGs whose midpoint is further than this percentage from the current price are automatically hidden. This keeps the chart focused on structurally relevant gaps — a gap at 85K is not actionable when price is at 97K. On higher timeframes or during high-volatility periods, increase this value to retain wider context. On lower timeframes or in tight ranges, decrease it to keep only the nearest gaps visible. **Show Trade Boxes** — On / Off Toggles the visual boxes that display entry, stop-loss, and take-profit levels for each signal. Green boxes indicate long positions. Red boxes indicate short positions. ## CONCEPTS EXPLAINED For traders learning smart money concepts, here is a plain-language breakdown of every structural element this indicator uses. **Order Blocks (OB)** An order block is the last opposing candle before a significant impulsive move. In a bullish scenario, it is the last bearish candle before a strong rally. Institutional traders place large orders at these levels during accumulation or distribution phases, creating zones where price is statistically likely to react when it returns. Order blocks are the foundation of SMC entry models — they represent where smart money positioned itself. **Fair Value Gap (FVG)** A fair value gap is a three-candle price imbalance where a gap exists between candle 1's high (or low) and candle 3's low (or high). In a bullish FVG, candle 2 moved so aggressively that it left a gap between candle 1's high and candle 3's low. These gaps represent areas where price moved too fast for orders to fill completely. Markets tend to return to these inefficiencies to rebalance. When an FVG overlaps an order block, you have two independent structural signals pointing to the same zone — that is high-probability confluence. **Break of Structure (BOS)** A break of structure occurs when price moves beyond a prior swing high (bullish BOS) or swing low (bearish BOS) in the direction of the prevailing trend. It signals continuation — the trend is intact and expanding. This indicator uses BOS detection on both the higher timeframe and the confirmation timeframe to ensure structural alignment before entries. **Change of Character (CHoCH)** A change of character is a structural break against the prevailing trend, signaling a potential reversal. In a downtrend, a CHoCH occurs when price breaks above the most recent lower high. This is significant because it is the first objective signal that sellers may be losing control. The indicator treats CHoCH as a valid trigger alongside BOS, allowing entries on both trend continuations and early reversals. **Liquidity Sweep** A liquidity sweep occurs when price briefly pushes beyond a key structural level — a swing high or swing low — to trigger clustered stop-loss orders and pending orders, then reverses. This is a core ICT concept. Institutional participants need liquidity to fill large positions, and retail stop-losses provide that liquidity. The sweep-and-reverse pattern is one of the most reliable structural signals in price action analysis. This indicator requires a confirmed sweep before any entry signal fires. **Premium and Discount Zones** The premium/discount zone model divides the higher-timeframe dealing range into two halves using the 50% equilibrium level. The upper half is the premium zone — where price is expensive relative to the range, favoring short positions. The lower half is the discount zone — where price is cheap relative to the range, favoring long positions. The Selective mode narrows this further using the P/D Zone Threshold, requiring entries at the extremes of these zones for maximum positional advantage. ## HOW TO USE THIS INDICATOR **Step 1 — Add to Chart** Add the indicator to any BTCUSDT chart. The default settings are optimized for the 4H timeframe on Binance data, but the logic works on any Bitcoin pair and can be adapted to other timeframes by adjusting the Direction TF, Confirmation TF, and Swing Length parameters. **Step 2 — Choose Your Mode** Open Settings and select either Aggressive or Selective mode. Aggressive generates more signals and captures more of the trend. Selective generates fewer, higher-quality signals with tighter risk control. If you are still learning smart money concepts, Selective mode provides a cleaner read because every signal has maximum structural confluence. **Step 3 — Read the Signals** Entry arrows appear directly on the chart when all confluence conditions are met. Green arrows indicate long entries. Red arrows indicate short entries. Stop-loss and take-profit levels are plotted as horizontal lines extending from each signal. **Step 4 — Enable Trade Boxes** Turn on Show Trade Boxes in Settings for a clear visual representation of each trade's risk and reward. The box spans from entry to TP, with the SL level marked. This makes it easy to evaluate the risk-reward ratio of each signal at a glance. **Step 5 — Run the Strategy Tester** Open TradingView's Strategy Tester panel to verify the backtest results on your chart and data. Set commission and slippage to match your exchange's actual fees. The default commission of 0.075% per trade represents Binance taker fees. Adjust if you trade on a different exchange. **Step 6 — Adjust Settings Carefully** If you modify parameters, change one at a time and re-run the backtest after each change to understand the isolated impact. The default settings are the product of extensive testing — they are not arbitrary. Move away from them deliberately, not casually. **Step 7 — Combine with Your Own Context** This indicator provides structural signals based on smart money concepts. It does not account for fundamental catalysts, macroeconomic events, or on-chain data. Use these signals as one input within your broader analytical framework. The strongest results come from traders who combine structural signals with their own understanding of market context. **Step 8 — Manage Risk** No indicator guarantees profits. Size your positions according to your account size and risk tolerance. Never risk more than you can afford to lose on a single trade. The backtest results represent historical performance under specific conditions — live trading introduces variables that backtests cannot fully capture. ## BACKTEST CONDITIONS — FULL TRANSPARENCY Every number published here is reproducible. Load the indicator with default settings on BTCUSDT 4H and open the Strategy Tester. Here are the exact conditions: - Symbol: BTCUSDT (Binance) - Timeframe: 4H - Period: January 2023 through February 2026 (3+ years of data) - Initial Capital: $10,000 - Order Size: 100% of equity per trade - Commission: 0.075% per trade (Binance taker fee) - Slippage: 3 ticks per order - Non-repainting: barstate.isconfirmed enforced on all signal calculations - No lookahead bias: lookahead = barmerge.lookahead_off on all request.security() calls - No future leakage: entries execute on the bar after all conditions are confirmed Sample sizes are moderate — 55 trades for Aggressive, 21 for Selective. The Selective mode's 21 trades in particular should be supplemented with forward-testing on live data to build stronger statistical confidence. Both modes are provided so you can evaluate the frequency-versus-quality tradeoff with full transparency. Past performance under specific historical conditions does not guarantee future results. Markets evolve. Volatility regimes shift. The only honest way to evaluate any strategy is continuous forward-testing alongside historical backtesting. ## DISCLAIMER This indicator is published for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any asset. Trading Bitcoin and other financial instruments involves substantial risk of loss. Leverage, volatility, exchange downtime, liquidity gaps, and other real-world factors can significantly impact live performance versus backtested results. You should carefully consider your financial objectives, level of experience, and risk appetite before trading. Never trade capital you cannot afford to lose. You are solely responsible for your own trading decisions and their outcomes. The author makes no guarantees about the accuracy, completeness, or reliability of this indicator or its signals. Use it at your own risk. --- **Suggested Tags:** `smartmoneyconcepts` `orderblocks` `fairvaluegap` `bitcoin` `ICT` `BOS` `liquidez` `bloques` `accionprecio` --- ## VERSION EN ESPANOL (Resumen) Para la documentacion completa, consulta la seccion en ingles arriba. A continuacion, un resumen de los puntos clave. --- ### Que es SMC Pro BTC Motor de smart money concepts multi-temporal construido exclusivamente para Bitcoin. Combina bloques de ordenes, fair value gaps, barridos de liquidez, rupturas de estructura y zonas premium/descuento en una sola estrategia verificada por backtest, sin repintado y de codigo abierto. Desarrollado por un ex-analista cuantitativo de un fondo sistematico en Estados Unidos — la misma mecanica de flujo de ordenes que usan los algoritmos institucionales, adaptada para traders retail en TradingView. Todos los resultados son reproducibles con los ajustes por defecto. Sin parametros ocultos. Sin sobreajuste. ### Dos Modos de Estrategia **Modo Agresivo** — Entradas en cualquier BOS/CHoCH valido confirmado por bloque de ordenes + FVG + barrido de liquidez. Mas operaciones, mayor exposicion a movimientos tendenciales. | Metrica | Valor | |---|---| | Total de Trades | 55 | | Win Rate | 49.09% | | P&L Neto | +49.12% | | Factor de Beneficio | 1.41 | | Drawdown Maximo | 14.70% | **Modo Selectivo** — Agrega filtro de zona premium/descuento. Longs solo en zona de descuento, shorts solo en zona premium. Menos operaciones, mayor calidad por senal. | Metrica | Valor | |---|---| | Total de Trades | 21 | | Win Rate | 61.90% | | P&L Neto | +26.92% | | Factor de Beneficio | 2.347 | | Drawdown Maximo | 8.66% | Ambos modos incluyen comisiones (0.075%) y slippage (3 ticks) en los resultados. No hay un modo objetivamente mejor — solo el que se ajusta a tu perfil de riesgo. ### Como Usar - **Agrega el indicador** a cualquier chart BTCUSDT (optimizado para 4H, Binance). Selecciona modo Agresivo o Selectivo en Configuracion. - **Lee las senales:** flechas verdes = largo, flechas rojas = corto. Activa Show Trade Boxes para ver entrada, SL y TP visualmente. Los FVGs activos se muestran como zonas en el chart — configura cuantos quieres ver y a que distancia maxima del precio con Max FVGs per Side y FVG Max Distance %. - **Verifica con el Strategy Tester:** abre el panel de Strategy Tester de TradingView, ajusta comisiones y slippage a las tarifas de tu exchange, y confirma los resultados en tu propio chart. - **Gestiona tu riesgo:** ningun indicador garantiza ganancias. Dimensiona posiciones segun tu cuenta y tolerancia al riesgo. Combina estas senales con tu propio analisis fundamental y de contexto de mercado. ### Condiciones del Backtest BTCUSDT (Binance) | 4H | Enero 2023 - Febrero 2026 | Capital: $10,000 | 100% equity por trade | Comision: 0.075% | Slippage: 3 ticks | Sin repintado (barstate.isconfirmed) | Sin lookahead bias | Sin filtracion futura. ### Aviso Legal Este indicador se publica con fines educativos e informativos unicamente. No constituye asesoria financiera ni recomendacion de compra o venta. Operar Bitcoin implica riesgo sustancial de perdida. Nunca operes con capital que no puedas permitirte perder. El rendimiento pasado no garantiza resultados futuros. Usalo bajo tu propio riesgo.
Pine Script®策略
由DOE_Trade提供
test 2 EMA RSI VOL ATR Strategy VC2.51.14//@version=5 // EMA RSI VOL ATR Strategy VC2.51.14 - alertfix + optional emergency SL (strategy.close) strategy("EMA RSI VOL ATR Strategy VC2.51.14", overlay=true, initial_capital=1000, default_qty_type=strategy.percent_of_equity, default_qty_value=100, pyramiding=0, commission_type=strategy.commission.percent, commission_value=0.08, slippage=20, calc_on_order_fills=true, calc_on_every_tick=false, margin_long=0, margin_short=0) // ── State ───────────────────────────────────────────────────────────────────── var bool in_long = false var bool in_short = false var int last_alert_time = 0 var float long_entry_price = na var float short_entry_price = na // One-action-per-candle guard (ENTRIES ONLY) var int last_action_bar = na can_act() => na(last_action_bar) or bar_index > last_action_bar // ── Inputs ──────────────────────────────────────────────────────────────────── entry_ema_length = input.int(7, "Entry EMA Length") exit_ema_length = input.int(21, "Exit EMA Length") // this is the normal SL used only when trailing is OFF (same as original) stop_loss_pct = input.float(2.2, "Stop Loss % (no trailing)", minval=0.1, maxval=20.0) // trailing config (unchanged) trail_mode = input.string("Legacy (close-ATR)", "Trailing Stop Mode", options= ) use_trailing_stop = input.bool(true, "Use Trailing Stop") atrLookback = input.int(14, "ATR Lookback") atrMultiplier = input.float(2, "ATR Multiplier", minval=0.5, step=0.1) fixed_usd = input.float(40.0, "Fixed USD Distance", minval=0.01) trail_pct_of_price = input.float(2.6, "% of Price (for Percent mode)", minval=0.05, maxval=10.0) init_offset_usd = input.float(2.0, "Initial Offset USD", minval=0.00) show_trail_usd = input.bool(false, "Show Trail Distance (USD)") breakeven_pct = input.float(3, "Breakeven Trigger %", minval=0.5, step=0.1) // NEW: emergency hard SL that always works on top of everything use_emergency_sl = input.bool(true, "Use Emergency Hard SL") emergency_sl_pct = input.float(14.0, "Emergency Hard SL %", minval=0.5, maxval=50.0) rsi_length = input.int(14, "RSI Length") rsi_long_threshold = input.int(55, "RSI Long Threshold") rsi_short_threshold = input.int(51, "RSI Short Threshold") use_volume_filter = input.bool(true, "Use Volume Filter") volume_sma_length = input.int(14, "Volume SMA Length") min_bars_between_trades = input.int(1, "Min Bars Between Trades") min_minutes_between_signals = input.int(10, "Min Minutes Between Signals") min_amount = 0.05 show_rsi = input.bool(false, title="Show RSI on Chart") show_rsi_levels = input.bool(true, title="Show RSI Levels") rsi_level_dash_interval = input.int(3, "RSI Level Dash Interval", minval=1) rsi_lookback = input.int(200, "RSI Overlay Lookback", minval=50) rsi_bottom_buffer = input.float(5.0, "RSI Bottom Buffer %", minval=0.0, maxval=20.0) / 100 rsi_height_pct = input.float(20.0, "RSI Height %", minval=10.0, maxval=50.0) / 100 start_time = input.time(1735689600000, "Start Date") // 2025-01-01 allow_shorts = input.bool(true, title="Allow Shorts") show_labels = input.bool(false, title="Show Signal Labels") show_quantity = input.bool(false, title="Show Quantity") use_ema200_short = input.bool(true, "Use EMA200 for Shorts") adx_length = input.int(14, "ADX Length for Trend Confirm (Shorts)") adx_threshold = input.int(20, "ADX Threshold for Shorts") secret_code = input.string("secret.code.xxx", title="Secret Code") bot_uuid = input.string("bot.uuid.xxx", title="Bot UUID") // ── Filters & calcs ────────────────────────────────────────────────────────── ema200 = ta.ema(close, 200) ema_entry = ta.ema(close, entry_ema_length) ema_exit = ta.ema(close, exit_ema_length) ascending_entry = ema_entry > ema_entry descending_entry = ema_entry < ema_entry and ema_entry < ema_entry rsi = ta.rsi(close, rsi_length) atr = ta.atr(atrLookback) volume_sma = ta.sma(volume, volume_sma_length) adx = ta.ema(ta.tr(true), adx_length) // preserved behavior // Bar spacing & time spacing var int bars_since_last_exit = 0 if strategy.position_size != 0 and strategy.position_size == 0 bars_since_last_exit := 0 else bars_since_last_exit := nz(bars_since_last_exit ) + 1 var int last_signal_time = 0 time_cond_time = time - last_signal_time >= min_minutes_between_signals * 60000 // RSI overlay visuals price_high = ta.highest(high, rsi_lookback) price_low = ta.lowest(low, rsi_lookback) price_range = price_high - price_low rsi_height = price_range * rsi_height_pct rsi_bottom = price_low - price_range * rsi_bottom_buffer rsi_scaled = rsi_bottom + (rsi / 100) * rsi_height rsi_30_scaled = rsi_bottom + 0.3 * rsi_height rsi_50_scaled = rsi_bottom + 0.5 * rsi_height rsi_70_scaled = rsi_bottom + 0.7 * rsi_height // Conditions volume_cond = not use_volume_filter or volume > volume_sma time_cond = bars_since_last_exit >= min_bars_between_trades long_cond_base = ascending_entry and close > ema_entry and rsi > rsi_long_threshold and close > ema200 and time >= start_time and volume_cond and time_cond and time_cond_time short_cond_base = allow_shorts and descending_entry and close < ema_entry and rsi < rsi_short_threshold and (not use_ema200_short or close < ema200) and adx > adx_threshold and time >= start_time and volume_cond and time_cond and time_cond_time // ── Alert helpers ──────────────────────────────────────────────────────────── iso_ts() => t = time_close str.tostring(year(t)) + "-" + str.tostring(month(t), "00") + "-" + str.tostring(dayofmonth(t), "00") + "T" + str.tostring(hour(t), "00") + ":" + str.tostring(minute(t), "00") + ":" + str.tostring(second(t), "00") + "Z" build_payload(_action) => act = _action if _action == "exit_long" act := "exit_long" else if _action == "exit_short" act := "exit_short" s1 = "{" + "\"secret\":\"" + secret_code + "\"," + "\"max_lag\":\"300\"," + "\"timestamp\":\"" + iso_ts() + "\"," s2 = "\"trigger_price\":\"" + str.tostring(close, format.mintick) + "\"," + "\"tv_exchange\":\"" + syminfo.prefix + "\"," + "\"tv_instrument\":\"" + syminfo.ticker + "\"," s3 = "\"action\":\"" + act + "\"," + "\"bot_uuid\":\"" + bot_uuid + "\"" + "}" s1 + s2 + s3 send_alert(_action) => alert(build_payload(_action), alert.freq_once_per_bar) // ── Entries (BAR CLOSE ONLY, ONE ACTION PER BAR) ───────────────────────────── if barstate.isconfirmed and can_act() // LONG branch if long_cond_base if strategy.position_size < 0 send_alert("exit_short") strategy.close("Short") strategy.entry("Long", strategy.long) long_entry_price := close last_signal_time := time if strategy.position_size <= 0 and not in_long send_alert("enter_long") last_alert_time := timenow in_long := true in_short := false last_action_bar := bar_index // SHORT branch else if short_cond_base if strategy.position_size > 0 send_alert("exit_long") strategy.close("Long") strategy.entry("Short", strategy.short) short_entry_price := close last_signal_time := time if strategy.position_size >= 0 and not in_short send_alert("enter_short") last_alert_time := timenow in_short := true in_long := false last_action_bar := bar_index // ── Breakeven (same logic as before, no can_act guard) ─────────────────────── if barstate.isconfirmed if strategy.position_size > 0 and not na(long_entry_price) and close > long_entry_price * (1 + breakeven_pct / 100) strategy.exit("BE Long", "Long", stop = long_entry_price) if strategy.position_size < 0 and not na(short_entry_price) and close < short_entry_price * (1 - breakeven_pct / 100) strategy.exit("BE Short", "Short", stop = short_entry_price) // ── Trailing exits (original logic) ────────────────────────────────────────── mintick = syminfo.mintick to_ticks(usd) => int(math.max(1, math.round(usd / mintick))) legacy_points = int(close - atr * atrMultiplier) legacy_offset = int(atr * atrMultiplier) true_atr_ticks = to_ticks(atr * atrMultiplier) fixed_usd_ticks = to_ticks(fixed_usd) percent_ticks = to_ticks(close * (trail_pct_of_price / 100.0)) init_offset_ticks = to_ticks(init_offset_usd) trail_ticks = 0 offset_ticks = 0 if trail_mode == "True ATR" trail_ticks := true_atr_ticks offset_ticks := true_atr_ticks else if trail_mode == "Fixed USD" trail_ticks := fixed_usd_ticks offset_ticks := init_offset_ticks else if trail_mode == "Percent of Price" trail_ticks := percent_ticks offset_ticks := init_offset_ticks else trail_ticks := legacy_points offset_ticks := legacy_offset current_trail_usd = trail_ticks * mintick legacy_trail_usd = legacy_points * mintick plot(show_trail_usd ? current_trail_usd : na, title="Trail Distance (USD)", color=color.new(color.teal, 0)) plot(show_trail_usd and trail_mode == "Legacy (close-ATR)" ? legacy_trail_usd : na, title="Legacy Trail (USD)", color=color.new(color.orange, 0)) if use_trailing_stop and barstate.isconfirmed if strategy.position_size > 0 strategy.exit("Trail Long", "Long", trail_points = trail_ticks, trail_offset = offset_ticks) else if strategy.position_size < 0 strategy.exit("Trail Short", "Short", trail_points = trail_ticks, trail_offset = offset_ticks) // ── Fixed SL if trailing OFF (same as original) ────────────────────────────── if not use_trailing_stop and barstate.isconfirmed and can_act() if strategy.position_size > 0 and not na(long_entry_price) strategy.exit("SL Long", "Long", stop = long_entry_price * (1 - stop_loss_pct / 100)) last_action_bar := bar_index else if strategy.position_size < 0 and not na(short_entry_price) strategy.exit("SL Short", "Short", stop = short_entry_price * (1 + stop_loss_pct / 100)) last_action_bar := bar_index // ── EMERGENCY HARD SL (independent, optional) ──────────────────────────────── if barstate.isconfirmed and strategy.position_size != 0 and use_emergency_sl float emergency_long_entry = na(long_entry_price) ? strategy.position_avg_price : long_entry_price float emergency_short_entry = na(short_entry_price) ? strategy.position_avg_price : short_entry_price // Long: if low pierces emergency SL if strategy.position_size > 0 and not na(emergency_long_entry) float long_em_sl = emergency_long_entry * (1 - emergency_sl_pct / 100) if low <= long_em_sl strategy.close("Long") // Short: if high pierces emergency SL if strategy.position_size < 0 and not na(emergency_short_entry) float short_em_sl = emergency_short_entry * (1 + emergency_sl_pct / 100) if high >= short_em_sl strategy.close("Short") // ── Exit alerts when flat ──────────────────────────────────────────────────── if strategy.position_size != 0 and strategy.position_size == 0 and barstate.isconfirmed send_alert(strategy.position_size > 0 ? "exit_long" : "exit_short") last_alert_time := timenow if strategy.position_size > 0 in_long := false long_entry_price := na else in_short := false short_entry_price := na // ── Plots ──────────────────────────────────────────────────────────────────── plot(ema_entry, "EMA Entry", color=color.blue, linewidth=1) plot(ema_exit, "EMA Exit", color=color.yellow, linewidth=1) plot(ema200, "EMA 200 (Trend Filter)", color=color.gray, linewidth=2) plot(show_rsi ? rsi_scaled : na, "RSI Overlay", color=color.purple, linewidth=1) plot(show_rsi and show_rsi_levels and bar_index % rsi_level_dash_interval == 0 ? rsi_30_scaled : na, "RSI 30", color=color.gray, style=plot.style_circles, linewidth=1) plot(show_rsi and show_rsi_levels and bar_index % rsi_level_dash_interval == 0 ? rsi_50_scaled : na, "RSI 50", color=color.gray, style=plot.style_circles, linewidth=1) plot(show_rsi and show_rsi_levels and bar_index % rsi_level_dash_interval == 0 ? rsi_70_scaled : na, "RSI 70", color=color.gray, style=plot.style_circles, linewidth=1) buy_signal = long_cond_base and strategy.position_size == 0 exit_long_signal = not long_cond_base and strategy.position_size > 0 short_signal = short_cond_base and strategy.position_size == 0 exit_short_signal = not short_cond_base and strategy.position_size < 0 reverse_to_long = long_cond_base and strategy.position_size < 0 reverse_to_short = short_cond_base and strategy.position_size > 0 plotshape(show_labels and buy_signal and not reverse_to_long ? true : na, title="Buy", style=shape.circle, location=location.belowbar, color=color.green, size=size.tiny) plotshape(show_labels and short_signal and not reverse_to_short ? true : na, title="Short", style=shape.circle, location=location.abovebar, color=color.red, size=size.tiny) plotshape(show_labels and exit_long_signal and not reverse_to_short ? true : na, title="Exit Long", style=shape.circle, location=location.abovebar, color=color.orange, size=size.tiny) plotshape(show_labels and exit_short_signal and not reverse_to_long ? true : na, title="Exit Short", style=shape.circle, location=location.belowbar, color=color.orange, size=size.tiny) plotshape(show_labels and reverse_to_long ? true : na, title="Exit -> Buy", style=shape.circle, location=location.belowbar, color=color.green, size=size.tiny, offset=-1) plotshape(show_labels and reverse_to_short ? true : na, title="Exit -> Short", style=shape.circle, location=location.abovebar, color=color.red, size=size.tiny, offset=-1)
Pine Script®策略
由Fre_Fre提供
1
Fractal Sweep Strategy# Fractal Sweep Strategy A trend-following strategy that trades **sweeps** of fractal highs and lows, using two complementary entry models that can run in parallel. --- ## Concept The strategy identifies **fractal points** (local highs/low over N bars) and enters when price **sweeps** them—breaking above a fractal high or below a fractal low—then closes back in the opposite direction. This often signals a rejection and potential reversal. **Sweep High** → Short bias **Sweep Low** → Long bias --- ## Entry Models ### 1. Attempted Candle - **Immediate trade:** The sweep candle itself is bearish (for short) or bullish (for long). - **Delayed trade:** If the sweep candle is not in the right direction, the strategy waits for the first **Attempted candle**: - **Short:** Bearish candle with `high > high ` (takes out the prior candle’s high). - **Long:** Bullish candle with `low < low ` (takes out the prior candle’s low). - **Entry:** At the close of the Attempted candle (repainting-safe). - **SL:** Low of the Attempted candle (short) / High of the Attempted candle (long). - **TP:** CRV × risk (default CRV = 2). ### 2. Trigger Level - **Setup:** Fractal high is swept by a **bullish** candle, and the **next candle is not** an Attempted candle. - **Trigger level:** Body low of the sweep candle (`min(open, close)`), ignoring the wick. - **Activation:** Any later candle closes **below** the trigger level. - **Entry:** At the close of the breaking candle, or at the open of the next candle if the break is detected one bar late. - **SL:** High of the sweep candle (Trigger Level candle). - **TP:** CRV × risk (default CRV = 2). ### Parallel Mode With **"Both"** selected, both models run at the same time. Pyramiding allows up to 2 short positions (one from each model) when both trigger. --- ## Risk Management - **Stop Loss:** High/Low of the reference candle (Attempted or Trigger Level candle). - **Take Profit:** Entry ± (CRV × risk), with separate CRV for each model. - **Max Trades per Day:** Limits total entries across both models (default: 5). --- ## Optional Filters ### Supertrend H1 (Directional Bias) - **Off:** No filter. - **With Trend:** Long only in H1 uptrend, short only in H1 downtrend. - **Counter Trend:** Long only in H1 downtrend, short only in H1 uptrend. ### Session Filter - Restricts trades to a time window (e.g. 08:00–17:00) in the selected timezone. --- ## Fractal Settings - **Bars in Fractal:** 3, 5, 7, or 9 (default: 5). - **Fractals Timeframe:** Chart TF or higher (e.g. M15 for MTF fractals). - **Max Age:** Fractals older than N bars are ignored. --- ## Visuals - Fractal lines and markers (▲/▼). - SL/TP lines for open trades. - Optional debug labels (trade explanation, sweep labels, no-trade reasons). - Optional H1 Supertrend overlay when bias is active. --- ## Repainting Safety Entries are placed only on **confirmed bars** (`barstate.isconfirmed`), so signals are fixed once the candle closes. --- ## Credits - **Fractal logic:** Based on MTF Fractals - **Strategy:** Lean Strategy Blueprint - **License:** CC BY-NC-SA 4.0
Pine Script®策略
由Lean_Trading提供
15-Min ORB Strategy for NQ Here I created a very simple 15M ORB strategy for NQ / MNQ. This strategy marks the high and low of the 15-Min opening candle for the New York session ( 0930 - 0945 ) and enters Long / Short based on where the 5 Minute candle closes if it closes above / below the 15 Minute range. It has a customisable RR for TP1 and TP2 and the amount of contracts you can use. Please bear in mind that this is a very basic strategy as it is my first time making a script for TradingView. I an open to any constructive criticism to help me improve my script. Thank you for taking the time to read this and I hope you guys enjoy my script!
Pine Script®策略
由Dryeye2006提供
Regression Slope Oscillator Strategy (Modified from BigBeluga)Regression Slope Oscillator Strategy (Modified from BigBeluga) This strategy is based on the Regression Slope Oscillator – BigBeluga oscillator, enhanced with multi-timeframe confirmation, dual signal labeling, ATR/fixed-risk management, and visual reversal markers. Core Concept The oscillator calculates the averaged logarithmic regression slope across a configurable range of lookback lengths. It identifies momentum shifts when the oscillator crosses the zero line, producing trade signals with optional multi-timeframe confirmation. Multi-Timeframe Confirmation Adaptive MTF filtering ensures trades are executed only when the trend aligns across neighboring timeframes: Current TF Lower TF Higher TF 1 min 5 min 15 min 5 min 1 min 15 min 15 min 5 min 1 hour 1 hour 15 min 4 hour A trade executes only if: Current TF crosses the zero line. Both lower and higher TF oscillators are on the same side of zero. The bar is confirmed (no repainting). Dual Signal System MTF-Filtered Signals “Long MTF” / “Short MTF” Trigger only when the dynamic MTF filter is satisfied. Used for actual strategy entries and exits. Simple Zero-Cross Signals “LONG” / “SHORT” Trigger on the current timeframe only. Useful for visual comparison of raw oscillator behavior versus filtered signals. Reversal Dots Added oscillator-pane dots and price-chart dots to highlight reversals against the signal line: Red dot = bearish reversal Lime dot = bullish reversal Positioned either on the oscillator pane or directly above/below candles for clarity. This visually emphasizes momentum reversals, independent of trade execution. Risk Management Fixed Tick Mode: User-defined take profit and stop loss in ticks. ATR-Based Mode: Take profit and stop loss scaled by volatility with separate multipliers. This flexibility supports scalping, day trading, or systematic momentum approaches. Live Trend Table Displays direction relative to zero for all major timeframes: 1 min → Daily. Customizable text size and table visibility. Provides a quick visual check of trend alignment across TFs. Performance Table Tracks total trades, wins, losses, win rate %, and average win/loss in ticks. Helps quickly evaluate adjustments or parameter changes. Visual Enhancements Gradient-colored candles based on oscillator strength. Oscillator and signal line overlay with filled background. Reversal dots on oscillator and price chart. Entry labels and real-time alerts for MTF trades. Recommended Use Traders looking for trend-aligned momentum trades. Scenarios requiring multi-timeframe confirmation. Lower timeframe scalping where false zero-crosses are filtered. Visual monitoring of oscillator reversals and trade outcomes.
Pine Script®策略
由aaronrileycheer提供
MES 15m High Win Rate Mean ReversionCore Idea It assumes: Most 15-minute moves in normal conditions revert back toward fair value. Fair value = VWAP + 20-period mean It is not a trend strategy. It bets against short-term overextension. Market Environment It Wants This system performs best when: Market is rotational Volatility is moderate No major macro catalyst Institutions are rebalancing inventory It avoids: Strong breakout days Expansion after news Persistent trend sessions Step-By-Step Logic 1️⃣ Volatility Compression Filter It checks: ATR (14) Compared to its 30-bar average If ATR is too high → no trade. This attempts to skip news days and expansion regimes. 2️⃣ Extreme Detection On the 15-minute chart: It calculates: 20-period mean 2 standard deviation Bollinger Bands VWAP A trade triggers only when: For Long: Price touches lower 2σ band Price is below VWAP For Short: Price touches upper 2σ band Price is above VWAP This defines “statistical stretch.” 3️⃣ Position Structure 6 MES contracts 5 point stop (~$150 risk) 6–6.5 point target (~$180–$195 reward) Max 2 trades per day One trade per direction Why It Has Higher Win Rate Because: It trades exhaustion, not continuation. It enters after price is statistically stretched. Target is smaller than stop multiple systems. It avoids high volatility regimes. Mean reversion strategies win often because markets rotate more than they trend. What It Is Not It is not: A breakout system A momentum system A trend following model A high daily payout generator It is a: Low-frequency, moderate-edge, capital-preservation framework. Risk Characteristics From your backtest: Win rate ≈ 60% Profit factor ≈ 1.7 Max drawdown ≈ $435 Low trade count That is healthy. But understand: When trend days hit, it will lose. If volatility regime changes structurally, edge degrades. Strengths Smooth equity curve Compatible with prop trailing drawdown Emotionally manageable Predictable trade frequency Weaknesses Underperforms in trending months Can have clusters of 3–4 losses Needs volatility filter to stay safe Won’t consistently produce $350 every day Psychological Fit This system fits traders who: Prefer frequent small wins Can accept occasional flat weeks Care more about survival than speed Avoid revenge trading
Pine Script®策略
由spagnolomatteo21提供
Trend Strategy Flip📌 Trend Strategy Flip — Adaptive Trend‑Following System with Smart Flip Logic (Built on the L1 Proximal Filter concept by LuxAlgo) Trend Strategy Flip is an adaptive trend‑following system built on top of the L1 Proximal Filter, a concept originally introduced by LuxAlgo. This strategy expands the idea with multi‑mode entries, smart flip logic, breakeven automation, and a clean visual HUD for real‑time decision support. The result is a lightweight, responsive trend engine suitable for both discretionary and automated trading. 🔍 Core Concept The system uses the L1 Proximal Filter to extract a smooth, noise‑resistant trend line (z) and its velocity (v). This allows the strategy to detect: Confirmed trend reversals (Mode A) Early entries via price cross or velocity shift (Mode B1/B2) Next‑bar confirmation entries (Mode C) When the trend flips, the strategy can automatically reverse the position. ✨ Key Features ✔ Built on the L1 Proximal Filter (LuxAlgo concept) A robust, adaptive trend extraction method. ✔ Multiple Entry Modes Choose between confirmed, early, or next‑bar entries. ✔ Smart Flip Logic Automatically reverses positions on trend change. ✔ Breakeven Protection Dynamic breakeven activation with a semi‑transparent BE line. ✔ Compact HUD (Top‑Right Corner) Displays: Current position Entry price Live PnL (%) Last flip direction Breakeven status Bars since entry ✔ Optional Trend Background Soft diagonal gradient (lightweight imitation) for visual trend context. ✔ Clean Visual Markers Entry arrows, flip markers, trend line, and BE line. ✔ Alerts Included Ready for automation or webhook‑based execution. 🎯 Use Cases Trend‑following systems Reversal/flip strategies Automated execution via alerts Swing and intraday trading Strategy research and optimization ⚠️ Notes This strategy is based on the L1 Proximal Filter concept by LuxAlgo, extended with additional logic and visualization. For educational and research purposes only. Always test before using in live trading.
Pine Script®策略
由olegask68提供
META Scalp 5m (RSI+ADX/DMI+TSI+Vol+Squeeze+SMC-lite) [v1.1]Script Description META Scalp 5m (RSI+ADX/DMI+TSI+Vol+Squeeze+SMC-lite) is a futures scalping strategy designed primarily for the 5-minute timeframe. Its goal is to filter higher-probability entries through a multi-indicator confluence engine that calculates a Score (from -100 to +100) and converts it into an estimated short-term probability of bullish or bearish continuation. This script is not a magic predictor. It is a consensus-based decision engine: when multiple conditions align (direction + strength + volatility + context), it triggers entries with automatic risk management (SL/TP) based on ATR. What it shows on the chart Plots Fast EMA and Slow EMA for trend direction. Entry markers: Triangle “L” = Long signal Triangle “S” = Short signal SMC-lite events: SW↑ = High sweep (possible stop hunt above) SW↓ = Low sweep (possible stop hunt below) Information panel showing: Current Score P(Long) / P(Short) in % ADX Volume confirmation (VolOk) Squeeze status (ON/OFF) Indicators and Modules Included 1) Trend Filter (EMA) Fast EMA (default 21) and Slow EMA (default 55). Bullish bias when: Fast EMA > Slow EMA and rising. Bearish bias when: Fast EMA < Slow EMA and falling. Purpose: avoid trading against strong trend momentum. 2) RSI RSI (default 14) with configurable midpoint (default 50). Bias: RSI > 50 → bullish bias RSI < 50 → bearish bias RSI weight increases as it moves further away from 50. 3) ADX/DMI (Strength + Direction) Uses +DI, -DI and ADX via ta.dmi(). Works as: Strength filter: market considered tradable only if ADX ≥ threshold (default 18). Direction: +DI > -DI → bullish; -DI > +DI → bearish. When ADX is low, the script treats the market as choppy and avoids trades. 4) TSI (True Strength Index) Momentum confirmation: TSI above signal → bullish TSI below signal → bearish 5) Volume Filter Compares current volume vs Volume SMA (default 20). VolOk when: Volume > SMA(volume) × multiplier (default 1.10) Filters low-participation signals. 6) Squeeze (BB vs KC approximation) + Momentum Detects volatility compression: Bollinger Bands inside Keltner Channels = Squeeze ON Expansion signal when: Squeeze OFF and momentum aligns: Momentum rising → bullish bias Momentum falling → bearish bias Goal: capture post-compression expansions. 7) SMC-lite (Basic Smart Money Concepts) This module implements simplified SMC logic: A) Equal Highs / Equal Lows + Sweep Detects equal highs/lows using pivots and ATR tolerance. Sweep logic: Wick above EQH and close back below → SW↑ (bearish/contrarian) Wick below EQL and close back above → SW↓ (bullish/contrarian) B) BOS-lite (Break of Structure) Continuation signal when price closes beyond the last swing high/low. Higher Timeframe Confirmation (15m) Optional but recommended. Calculates EMAs on a higher timeframe (default 15m). If Score goes against HTF trend → score is penalized. This avoids many bad 5m trades. Score Engine & Probability Core engine produces a Score between -100 and +100. Positive score → Long bias Negative score → Short bias Converted into estimated probabilities: P(Long) increases with Score P(Short) = 100% − P(Long) Important: probability is a mathematical transformation of the score, not a guaranteed statistical prediction. Entry Rules Long Entry Triggered when: Score ≥ Entry threshold (default 60) Market not in chop (ADX filter) Short Entry Triggered when: Score ≤ −Entry threshold Market not in chop Trade Management (SL/TP) Risk management uses ATR-based dynamic levels: Stop Loss = ATR × SL multiplier (default 1.2) Take Profit = ATR × TP multiplier (default 1.5) Optional: ATR trailing stop Early Exit (Score deterioration) Positions can close early when confluence weakens: Long closes if score falls below exit threshold. Short closes if score rises above negative exit threshold. Recommended Trading Approach Best used as a quality filter, not blind signals. Recommended Settings (5m scalping) Timeframe: 5m HTF confirmation: 15m ON ADX minimum: 18–22 Entry score: 60–75 SL: 1.0–1.3 ATR TP: 1.2–1.8 ATR Trailing stop: useful in trending markets. Workflow Wait for Score to exceed threshold. Avoid trades when ADX is low. Prefer trades aligned with HTF trend. Let SL/TP manage the trade. Alerts Built-in alerts: META LONG META SHORT SMC Sweep High SMC Sweep Low Limitations Pine Script cannot access private indicators (LuxAlgo, SmartBuzz, etc.). TradingView VPVR/VRVP cannot be accessed directly via Pine. Designed for backtesting and screening. Adjust settings per asset and exchange. Best Practices Test separately on BTC, ETH, and altcoins. Include realistic fees and slippage. Avoid high-impact news periods.
Pine Script®策略
由salvadorvelasco2009提供
Options test Daily Long 08:30 Exit next day 08:00 UTCThis strategy allows to "backtest" 0DTE option straddles. It "buys" right after the expiration time and sells next day on expiration. Once you run the script, you can download the excel file with the results of each trade that will give you the followng information: - potential move at expiry - largest drawups and drawdowns With this information you can manually backtest your options strategy on diffrent assets.
Pine Script®策略
由surf48提供
3Commas DCA Strategy Backtesting [The Quant Science]This strategy is an advanced Dollar Cost Averaging (DCA) simulator designed to replicate the logic of 3Commas algorithmic trading bots directly within TradingView. This streamlined version showcases the power of Pine Script in developing high-efficiency backtests. By deep-diving into the data before going live, users can stress-test their setups and avoid costly mistakes. The following 3Commas configuration is assumed for this template: Direction: Long | Order Type: Limit | Exchange: Binance (BTC/USDT Initial Order Size: Set to 1000 USDT. Entry Logic: Our custom TradingView signal triggers on an RSI bearish cross of the 35 level, initiating a Long DCA sequence on oversold conditions. The Averaging orders logic for this template is configured as follows: Deviation to open first averaging order: 1% Averaging order size: 100 USDT Deviation step multiplier: 1.5 Order size multiplier: 1.5 Averaging orders per trade: 11 Limit averaging orders placed on exchange: 11 Critical Note: Max amount for bot usage & Backtesting Accuracy When configuring 3Commas, always prioritize the Max amount for bot usage parameter. This is essential to ensure your backtesting data remains realistic and avoids "illusory" results. As shown in this setup, the Max amount for bot usage is approximately 8,500 USDT. This represents the maximum amount of funds the bot can trade. To maintain high-fidelity backtesting on TradingView, we have set the Initial Capital to 10,000 USDT. By utilizing ~85% of the available equity (8,500 out of 10,000 USDT), the simulation closely mirrors real-world trading conditions. If your Max amount for bot usage exceeds your account balance, you must adjust your configuration. Always align your bot settings with your specific trading goals and financial capacity to avoid liquidation or failed order execution. 🧠 Workflow Description This strategy automates 3Commas-style Dollar Cost Averaging (DCA), operating exclusively on the Long side. The first order is triggered when the 7-period RSI crosses down the oversold threshold (default: 35), signaling a potential local bottom. Upon entry, the system simultaneously calculates and places 10 averaging orders via limit orders at progressively lower price levels to manage the position. The spacing between these orders is dynamic; it increases exponentially through a deviation multiplier, allowing the strategy to cover deep drawdowns effectively. Simultaneously, the volume of each subsequent purchase grows according to an amount multiplier, aggressively pulling the average entry price downward. The trade is closed either at a take profit target triggered once the total position equity reaches the set value or via a stop loss calculated from the initial entry price. Backtesting Considerations & Performance Analysis Despite the positive net profit shown in the strategy report, this specific configuration underperforms when compared to a simple Buy & Hold approach. In this scenario, a Buy & Hold investor who simply hold 10,000 USDT worth of the asset would have achieved a significantly higher return than the trader executing this DCA strategy. This indicates that while the bot is "profitable" in absolute terms, it is not capital-efficient under these specific market conditions. ❌ To keep this simulator streamlined and focused on core DCA logic, the current version does not include the following features: Base Template Only: This is a foundational framework designed for educational and initial testing purposes. No Leverage Backtesting: All calculations assume a 1x spot-trading margin (no liquidation or margin cost simulation). No Short Selling: This version is strictly long-only. Simplified DCA Settings: Advanced 3Commas parameters (such as Minimum Deviation Step or Non-linear Volume Scaling) are not included. Fixed Order Count: The strategy is hardcoded to 11 total orders (1 Base Order + 10 Averaging Orders). Standard Profit Logic: Take Profit % is calculated based on the Average Price, while Stop Loss % is anchored to the Initial Base Order price. No Reinvestment (Compounding): The strategy uses a fixed position size and does not automatically reinvest profits into subsequent deals. Feel free to swap the trigger logic or optimize the averaging settings to discover a configuration that outperforms a simple Buy & Hold strategy.
Pine Script®策略
由thequantscience提供
Ultimate Div - High Vis + Weekend Close Ultimate Intraday Divergence Terminal This is a comprehensive, institutional-grade trading system built specifically for Forex major pairs (EURUSD, USDJPY, GBPUSD) on the 15m and 1H timeframes. It combines momentum divergence confluence with trend filtering and professional risk management. 🔹 Core Strategy Logic The system identifies Regular and Hidden Divergences across three major oscillators simultaneously. To filter out low-probability signals, it requires a "Confluence" of at least two oscillators before triggering an entry. RSI (Relative Strength Index): Captures overextended momentum. MACD (Moving Average Convergence Divergence): Captures trend shifts. Stochastic: Captures rapid cyclic exhaustion. 🔹 Trend & Protection Filters Ichimoku Cloud Filter: Signals are only valid if they align with the higher-order trend defined by the Kumo Cloud (Bullish signals above, Bearish signals below). Volatility (News) Filter: Automatically detects abnormal ATR spikes (common during NFP or CPI) and pauses trading for 5 bars to prevent "whipsaw" losses. Weekend Protection: Automatically closes all positions on Friday evening to avoid Sunday gap risks. 🔹 Visual Experience (Optimized for Dark Mode) Dynamic Backgrounds: The chart background shifts to Dark Green (Bullish) or Dark Maroon (Bearish) based on the Ichimoku trend. Neon High-Vis Markers: Neon Cyan (Bullish) and Neon Red (Bearish) shapes ensure signals pop against black backgrounds. Real-Time Dashboard: Monitor your current Win Rate, Confluence levels, and Daily PnL at a glance. Floating PnL Label: A live-tracking label follows price during active trades, showing real-time profit/loss in pips and percentage. 🔹 Risk Management SOP Risk-per-Trade: Automatically calculates position sizes based on 1% of equity. Daily Drawdown Limit: Halts trading for the day if a 3% loss limit is hit. Take Profit / Stop Loss: Dynamic calculation based on user-defined Risk:Reward ratios. 🛠 How to Use Add to Chart: Set your timeframe to 15m. Verify Trend: Ensure the background color matches the direction you intend to trade. Wait for Confluence: Watch the dashboard for a 2/3 or 3/3 signal. Manage: Let the automated SL and TP handle the exit, or use the floating PnL label to manually scale out.
Pine Script®策略
由chgotom提供
Linda Bradford Raschke 3-10-16 Anti StrategyLinda Bradford Raschke's famous "310" MACD variation (fast=3, slow=10, signal=16) adapted into a mechanical "Anti" pullback strategy. The "Anti" targets the first meaningful pullback after a sharp counter-trend move / potential trend exhaustion. Implemented logic: • LONG: Signal sloping up + MACD > 0 + recent MACD dip then hook up above signal • SHORT: Inverted logic Includes: • Optional ATR-based or fixed % SL/TP • Visual entry labels + background trend bias • Alerts for long/short setups Best used with discretion + proper risk management - backtest thoroughly before trade. Inspired by Linda Bradford Raschke's teachings. v6 • Open to improvements/suggestions.
Pine Script®策略
由uzair2join提供
Institutional Risk Engine v3//@version=6 strategy( "Institutional Risk Engine v3", overlay=true, initial_capital=100000, pyramiding=0, default_qty_type=strategy.percent_of_equity, default_qty_value=10, calc_on_order_fills=true) // ========================================================== // 1️⃣ MULTI-ASSET DATA // ========================================================== btc = request.security("BINANCE:BTCUSDT", timeframe.period, close) eth = request.security("BINANCE:ETHUSDT", timeframe.period, close) es = request.security("CME_MINI:ES1!", timeframe.period, close) // Returns btc_ret = math.log(btc/btc ) eth_ret = math.log(eth/eth ) es_ret = math.log(es/es ) // Volatility btc_vol = ta.stdev(btc_ret, 50) eth_vol = ta.stdev(eth_ret, 50) es_vol = ta.stdev(es_ret, 50) // Correlations corr_be = ta.correlation(btc_ret, eth_ret, 50) corr_bs = ta.correlation(btc_ret, es_ret, 50) corr_es = ta.correlation(eth_ret, es_ret, 50) // ========================================================== // 2️⃣ VOL PARITY WITH CORRELATION ADJUSTMENT // ========================================================== inv_btc = btc_vol != 0 ? 1/btc_vol : 0 inv_eth = eth_vol != 0 ? 1/eth_vol : 0 inv_es = es_vol != 0 ? 1/es_vol : 0 sum_inv = inv_btc + inv_eth + inv_es w_btc = inv_btc / sum_inv w_eth = inv_eth / sum_inv w_es = inv_es / sum_inv // Approx portfolio variance portfolio_var = ( w_btc*w_btc*btc_vol*btc_vol + w_eth*w_eth*eth_vol*eth_vol + w_es*w_es*es_vol*es_vol + 2*w_btc*w_eth*corr_be*btc_vol*eth_vol + 2*w_btc*w_es*corr_bs*btc_vol*es_vol + 2*w_eth*w_es*corr_es*eth_vol*es_vol ) // ========================================================== // 3️⃣ 12-MONTH SHARPE TARGETING (252 trading days proxy) // ========================================================== ret = math.log(close/close ) mean_ret = ta.sma(ret, 252) vol_ret = ta.stdev(ret, 252) sharpe = vol_ret != 0 ? (mean_ret / vol_ret) * math.sqrt(252) : 0 target_sharpe = 1.5 sharpe_scale = sharpe > target_sharpe ? 1 : sharpe > 1 ? 0.7 : 0.4 // ========================================================== // 4️⃣ RISK OF RUIN // ========================================================== wins = strategy.wintrades loss = strategy.losstrades total = strategy.closedtrades p = total > 0 ? wins / total : 0.5 q = 1 - p risk_per_trade = 0.01 capital_units = strategy.equity * risk_per_trade risk_of_ruin = p > q ? math.pow(q/p, capital_units) : 1 // ========================================================== // 5️⃣ PROP FIRM SURVIVAL MODEL // ========================================================== var float peak_equity = na peak_equity := na(peak_equity) ? strategy.equity : math.max(peak_equity, strategy.equity) trailing_dd = (strategy.equity - peak_equity) / peak_equity // Daily var float day_start = na new_day = ta.change(time("D")) != 0 if new_day day_start := strategy.equity daily_pnl = strategy.equity - day_start daily_loss_limit = day_start * 0.03 trailing_limit = -0.10 prop_ok = daily_pnl > -daily_loss_limit and trailing_dd > trailing_limit // Near violation compression prop_scale = trailing_dd > -0.05 ? 1 : trailing_dd > -0.08 ? 0.6 : 0.3 // ========================================================== // FINAL CAPITAL SCALING // ========================================================== base_alloc = 0.6 final_scale = base_alloc * sharpe_scale * prop_scale position_pct = final_scale * 100 // ========================== // ENTRY // ========================== long_signal = close > ta.ema(close, 20) and ta.crossover(ta.rsi(close, 6), 50) // Prop condition default (avoid empty block issues) if strategy.position_size == 0 and prop_ok if long_signal strategy.entry("LONG", strategy.long) // ========================================================== // EXIT // ========================================================== if strategy.position_size != 0 avg = strategy.position_avg_price strategy.exit("EXIT", limit = avg * 1.01, stop = avg * 0.995) // ========================================================== // DASHBOARD // ========================================================== var table dash = table.new(position.top_right, 2, 8) if barstate.islast table.cell(dash, 0, 0, "Portfolio Vol") table.cell(dash, 0, 1, "Sharpe") table.cell(dash, 1, 1, str.tostring(sharpe,"#.##")) table.cell(dash, 0, 2, "Risk of Ruin") table.cell(dash, 1, 2, str.tostring(risk_of_ruin,"#.#####")) table.cell(dash, 0, 3, "Trailing DD") table.cell(dash, 1, 3, str.tostring(trailing_dd*100,"#.##")+"%") table.cell(dash, 0, 4, "Prop OK") table.cell(dash, 1, 4, str.tostring(prop_ok)) table.cell(dash, 0, 5, "Sharpe Scale") table.cell(dash, 1, 5, str.tostring(sharpe_scale,"#.##")) table.cell(dash, 0, 6, "Prop Scale") table.cell(dash, 1, 6, str.tostring(prop_scale,"#.##")) table.cell(dash, 0, 7, "Position %") table.cell(dash, 1, 7, str.tostring(position_pct,"#.##"))
Pine Script®策略
由bettencourt37提供
Bank Nifty Futures Five RoundsNSE:BANKNIFTY1! STRATEGY OVERVIEW — BIG PICTURE This is a mean-reversion, intraday, round-number rejection strategy designed for Bank Nifty Futures on the 1-minute chart. It fades failed moves around major round numbers instead of chasing momentum. WHAT THIS STRATEGY IS NOT • Not a breakout strategy • Not a trend-following strategy • Not a scalping strategy CORE ASSUMPTION Around 500-point round numbers, Bank Nifty often overshoots by ~50 points and then reverts. This strategy fades that failed extension. KEY LEVELS Every bar identifies the current 500-point block. Example: Price 59,732 → Block 59,500–60,000 Levels used: • Exact 500 round (59,500) • Round +50 (59,550) rejection zone • Round −50 (59,450) rejection zone TIME FILTER Trades allowed only between 09:30 IST and 15:10 IST. MARKET CONDITION FILTER Distance from 50 EMA must be reasonable (~300 points max). Trending markets are avoided. ENTRY LOGIC SHORT: Price touches +50 and closes below it (rejection). LONG: Price touches −50 and closes above it (reclaim). RISK MANAGEMENT Hard stop loss from entry: • Long: −80 points • Short: +80 points PROFIT MANAGEMENT • 50% booked at +60 points • Remaining 50% targets +160 points • Break-even activates only after +90 points in favor SESSION EXIT All positions closed at 15:10 IST. EXPECTANCY Avg loss ≈ −80 Avg win ≈ +110 to +130 Win rate ≈ 45–52% WHEN THIS STRATEGY FAILS • Strong trend days • News-driven sessions • Very low volatility days This is a survival-first intraday system designed for consistency, not prediction.
Pine Script®策略
由shomPips提供
Linda Bradford Raschke's 80-20 Momentum Candlestick StrategyLinda Bradford Raschke's "80-20" strategy from "Street Smarts: High Probability Short-Term Trading Strategies" (co-authored with Laurence Connors). Core idea: Identify a strong "momentum candlestick" on daily (body ≥80% of range, shadows ≤20%) signaling potential reversal. Then on intraday TF, trade false breakouts: price breaks close ± threshold (e.g. 20 points), reverses back to close → enter counter-direction. - LONG: False downside break → revert up → buy at momentum close. - SHORT: False upside break → revert down → sell at momentum close. - Target: ~50% of momentum body (center). - SL: ATR-based or beyond momentum extremes. - Valid for 1-3 days post-momentum candle. Best for indices (S&P, Nasdaq), forex majors, volatile stocks. Use daily for detection, H1/M15 for entries. Not financial advice — Backtest thoroughly, use with discretion and proper risk management. Original concept: Street Smarts book + discussions (e.g., RoboForex blog, MQL5 articles). Open-source v6 — suggestions welcome!
Pine Script®策略
由uzair2join提供
Structural Volatility Expansion StrategyStructural Volatility Expansion Strategy Purpose This strategy studies the relationship between confirmed market structure breaks and volatility regime shifts. Its objective is to participate in directional expansions that occur after structural confirmation, while filtering out low-volatility consolidations and false breakouts. The script is intended for research and systematic evaluation, not predictive claims. Methodology The model combines three interacting components: 1. Confirmed Structural Break Logic Market structure is derived using confirmed pivot highs and pivot lows. A bullish structural break is defined as a close above the most recent confirmed pivot high. A bearish structural break is defined as a close below the most recent confirmed pivot low. Pivots require full bar confirmation, which prevents forward-looking bias and repainting. This approach differs from simple rolling highest/lowest calculations by using structurally validated turning points. 2. Volatility Regime Classification Volatility is measured using ATR relative to its moving average baseline. Two regimes are defined: Compression: ATR below its historical baseline. Expansion: ATR above its historical baseline. Trades are only allowed during expansion phases. This attempts to reduce participation during statistically lower-momentum environments. 3. Liquidity Sweep Filter Breakouts that wick beyond structural levels but fail to close beyond them are treated as liquidity sweeps and are excluded. This reduces exposure to stop-run reversals where structure appears broken intrabar but fails on close. 4. Higher Timeframe Alignment Directional bias is determined using a higher timeframe moving average. Long entries require higher timeframe close above its MA. Short entries require higher timeframe close below its MA. Lookahead is disabled to avoid repainting. This introduces multi-timeframe confirmation without using future data. Risk Management Default strategy properties: Initial capital: 10,000 Position sizing: 2% of equity per trade Commission: 0.04% Slippage: 2 ticks Pyramiding: Disabled Stops are ATR-based and targets use a fixed risk-reward multiple (default 2:1). The position sizing is intentionally conservative and does not exceed commonly accepted sustainable risk thresholds. Backtesting Transparency When evaluating results: Use markets with sufficient liquidity. Ensure a dataset that generates a meaningful number of trades (ideally 100+). Keep default commission and slippage settings unchanged. Avoid optimizing inputs solely to maximize historical performance. Performance results are dependent on instrument, timeframe, and historical period tested. This script does not guarantee profitability and should be forward-tested before any live use. Intended Use This strategy is designed for: Studying structural continuation patterns Researching volatility regime transitions Comparing breakout performance during expansion vs compression Systematic strategy development It is not intended as financial advice. Originality Notes The script: Uses confirmed pivot-based structure rather than raw lookback highs/lows Filters entries by volatility regime classification Excludes wick-only structural violations Applies non-repainting higher timeframe bias Uses realistic transaction cost modeling The logic emphasizes interaction between structure and volatility rather than indicator stacking. Limitations & Responsible Use This strategy has several important limitations: Lag From Pivot Confirmation Structural pivots require confirmation, which introduces delay. Signals may occur after a portion of the move has already developed. ATR Sensitivity Volatility classification depends on ATR relative to its baseline. During regime transitions, expansion signals may appear slightly late or briefly revert to compression. Trend Dependency The strategy performs best during directional market phases. Extended sideways environments may reduce performance even with volatility filtering. Higher Timeframe Influence The higher timeframe moving average is a smoothing mechanism and may not capture sudden macro shifts immediately. Market Specific Behavior Different asset classes (crypto, forex, equities, indices) exhibit different volatility cycles. Parameters may require testing across multiple datasets rather than optimization for a single instrument. Backtest Limitations Historical testing does not account for: Liquidity variations Execution delays Psychological decision-making factors Structural market changes over time Forward testing and risk control are recommended before any real capital deployment. Suggested Evaluation Approach For objective evaluation: Test across multiple years of data. Use instruments with consistent liquidity. Maintain realistic commission and slippage settings. Avoid curve-fitting inputs to a specific historical window. Compare results across trending and ranging environments. Risk Disclaimer This script is provided for research and educational purposes only. It does not constitute investment advice. All trading involves risk, and past performance does not guarantee future results.
Pine Script®策略
由JaxonJackFX提供
Tribute To Peter LynchTribute To Peter Lynch - Fund Manager Simulator "Know what you own, and know why you own it." - Peter Lynch WHO WAS PETER LYNCH? Peter Lynch is one of the greatest investors who ever lived. From 1977 to 1990, he managed the Fidelity Magellan Fund and turned it from $18 million into $14 billion in assets. He averaged a 29.2% annual return for 13 straight years, making Magellan the best-performing mutual fund in the world. What made Lynch different? He believed regular people could beat Wall Street. He bought stocks in companies he understood - he'd ask minivan owners at movie theaters what they thought of their Chrysler, he'd notice the local factory hiring more people, he'd pay attention to which donut shop had the longest line. He called this your "investor's edge" - the things you already know from your daily life that Wall Street analysts sitting in their offices can't see. Lynch famously said: "If you can tell your stock story to a fifth grader and they understand it, you've got a good one. The more complicated the story, the more likely it is to fall apart." He also had the stomach for downturns. During his 13 years at Magellan, the market dropped 10% or more NINE times, and Magellan fell right along with it every single time. But he never panicked. He knew that behind every stock is a company, and if the company is doing well, the stock will eventually follow. WHAT THIS SCRIPT DOES This is a fund manager simulator built entirely around Peter Lynch's investing philosophy. It's not a technical indicator. There are no moving averages, no RSI, no MACD. Lynch was a fundamental investor - he cared about what a company earns, how fast it's growing, how much debt it has, and whether the story makes sense. The script classifies any stock into one of Lynch's 6 categories, scores it on a 0-100 Lynch Score, evaluates the fundamental story, and generates buy/sell signals based purely on the same criteria Lynch used at Magellan. THE 6 STOCK CATEGORIES Lynch believed you can't treat all stocks the same. A 50% gain on a Slow Grower is fantastic and probably time to sell. The same 50% on a Fast Grower could be just the beginning of a 10-bagger. He broke every stock into 6 categories: 1. FAST GROWERS (20%+ earnings growth) Companies growing earnings fast, typically small to mid-sized. These are the potential 10-baggers. Lynch looked for PEG ratios below 1.0 and used his "baseball inning" concept - you want to buy these in innings 2-5, when the formula is proven but there's still a long runway ahead. Think of Walmart when it only had a few hundred stores, or Microsoft 3 years after its IPO. 2. SLOW GROWERS (3-8% earnings growth) Large, mature companies that grow about as fast as the overall economy. You buy these for the dividend. Lynch looked for steady, rising dividends with a low payout ratio (so the dividend is safe). If the dividend yield drops or the payout ratio gets too high, it's time to move on. 3. STALWARTS (10-14% earnings growth) Big, solid companies that aren't going to disappear but aren't going to triple overnight either. Lynch's rule: take your 30-50% gain and rotate the money into another Stalwart. These are your portfolio's defense - they hold up in recessions and won't go bankrupt. 4. CYCLICALS (tied to the economic cycle) Companies in industries like autos, airlines, steel, and chemicals that boom and bust with the economy. Here's Lynch's counterintuitive trick: buy cyclicals when the PE is HIGH (that means earnings are at the trough and about to recover) and sell when the PE is LOW (earnings have peaked and are about to fall). This is the opposite of how PE works for every other category. 5. TURNAROUNDS (beaten down, potential recovery) Companies in deep trouble that might recover. Lynch always checked: does this company have enough cash to survive? Is there a real plan (new management, cost cutting, selling bad divisions)? He said don't buy on hope - wait for actual evidence the turnaround is working. But when they work, the upside can be enormous. 6. ASSET PLAYS (hidden value) Companies sitting on assets the market doesn't see or doesn't value - real estate, patents, brand names, cash on the balance sheet. Lynch's example: Disney after it opened Epcot. Growth slowed, but the company was sitting on the Disney name, all that Florida land, and a library of characters worth billions that were carried on the books for nothing. BAR REPLAY - WHERE THIS SCRIPT REALLY SHINES This script was built with TradingView's Bar Replay feature in mind. Bar Replay is what transforms this from a backtest into a fund manager simulator. HOW TO USE BAR REPLAY: 1. Add the script to your chart 2. Pick any stock and classify it (Fast Grower, Stalwart, etc.) 3. Set your fundamental inputs if using Manual mode, or let Auto mode pull TradingView financial data 4. Click the Bar Replay button on your toolbar (the clock icon with a rewind arrow) 5. Pick a starting date - maybe go back 5 years, or 10, or start right before a crash 6. Press Play and watch the simulation unfold bar by bar WHAT YOU'LL SEE IN BAR REPLAY: - The Lynch Score updates in real time as fundamentals change each quarter - The Story Status shifts: "Growth Accelerating" might become "Growth Slowing" as the company matures - Buy and sell signals fire when Lynch's criteria are met - The P&L tracker shows your position gain in real time - The Peter Lynch portrait in the corner changes color based on how your portfolio is doing: -- Equity rising: Lynch appears in bright GREEN against a deep BLUE background, getting more vivid as gains grow -- Heavy drawdown: Lynch turns CRIMSON RED against a BLACK background -- Stop loss hit: The portrait FLASHES RED as a warning -- Neutral: Lynch appears in CYAN/TEAL against dark navy - The daily Lynch wisdom quote rotates, keeping you in his mindset BAR REPLAY SCENARIOS TO TRY: - Start replay on Apple (AAPL) in 2003 as a Turnaround - watch it reclassify into a Fast Grower - Replay Ford (F) through 2008-2012 as a Cyclical - see Lynch's high-PE-buy rule in action - Run Coca-Cola (KO) from 1990 as a Stalwart - practice the 30-50% rotate rule - Try any stock through the 2020 COVID crash - Lynch survived 9 crashes at Magellan, now you can experience one SETTINGS GUIDE - EXPLAINED SIMPLY Think of the settings like customizing a video game character before you play. Here's what each group does: GROUP 1: STOCK TYPE "What kind of company is this?" Pick one of the 6 categories. This changes ALL the rules the script uses. Baseball Inning: Where is this company in its life? - Innings 1-3 = Young, lots of room to grow (like a kid) - Innings 4-6 = Middle age, proving itself - Innings 7-9 = Old, running out of gas Early innings get a score bonus. Late innings get a penalty. GROUP 2: FUNDAMENTAL DATA "Where do the numbers come from?" - Auto mode: TradingView pulls real financial data (EPS, revenue, debt) automatically. Best for stocks. - Manual mode: You type in the numbers yourself. Use this for crypto, forex, or if Auto data looks wrong. GROUP 3: PEG & VALUATION "How do I know if a stock is cheap or expensive?" PEG = Price-to-Earnings divided by Growth rate. - PEG of 1.0 = fairly priced (PE matches growth rate) - PEG below 1.0 = cheap (you're paying less than what the growth is worth) - PEG above 2.0 = expensive The Buy Threshold (default 1.0) means: "only buy if PEG is at or below this number." The Sell Threshold (default 2.0) means: "sell if PEG goes above this number." GROUP 4: BALANCE SHEET HEALTH "Is this company in good financial shape?" - Max Debt/Equity: How much debt is too much? Default 0.50 means total debt shouldn't be more than half of the company's net worth. Lynch always checked the balance sheet. - Min Cash Ratio: Does the company have enough cash? Important for Turnarounds. - Max Payout Ratio: Is the company paying out too much of its earnings as dividends? Above 80% means the dividend might get cut. GROUP 5: CATEGORY RULES "Special rules for each stock type." These are the specific thresholds for each of the 6 categories. The defaults are based on Lynch's actual criteria from his books. Examples: - Fast Grower Min Growth 20%: Lynch said a Fast Grower needs at least 20% earnings growth - Stalwart Rotate Target 40%: Lynch rotated Stalwarts after 30-50% gains - Cyclical Trough PE 25: Buy cyclicals when PE is HIGH (counterintuitive!) GROUP 6: STRATEGY SETTINGS "Should the Lynch Score control the trades?" - Score Gate OFF (default): The Lynch Score is just a meter showing conviction. Trades fire based on category rules alone. - Score Gate ON: The Lynch Score must be above the entry threshold to buy and below the exit threshold to sell. This adds an extra filter. GROUP 7: RISK MANAGEMENT "How much can I lose on one trade?" - Stop Loss: If the stock drops this % from your entry price, sell automatically. Default 15%. - Take Profit: If the stock rises this % from your entry price, sell automatically. Default 100% (a double). GROUP 8: DISPLAY "What do I see on the chart?" - Show/hide the Lynch portrait, the dashboard panel, and buy/sell signals - Customize your bull/bear/neutral colors THE DASHBOARD The top-right panel shows everything Lynch would want to see at a glance: - LYNCH SCORE: A 0-100 conviction meter with a visual bar. Built from 5 sub-scores: -- PEG Score (0-25): Is the stock cheap relative to its growth? -- Earnings Score (0-25): Is earnings growth meeting the target for this category? -- Balance Sheet Score (0-20): How healthy is the financial structure? -- Margin Score (0-15): Are profit margins good and expanding? -- Dividend Score (0-15): Is the dividend policy appropriate for this category? - STORY STATUS: The current fundamental narrative in plain English -- "Growth Accelerating", "Trough - Buy Zone", "Turnaround Succeeding", etc. - SIGNAL: The specific reason behind the current buy or sell signal - P&L: When in a trade, shows your unrealized gain/loss and warns Stalwart holders when approaching the rotate target - VALUATION: PEG ratio, PE ratio, and fair value comparison - EARNINGS: EPS, EPS growth rate, and revenue growth vs. category targets - BALANCE SHEET: Debt/equity ratio and net cash per share - MARGINS: Profit margin trend (expanding or contracting) - DIVIDENDS: Yield, payout ratio, and sustainability assessment - DAILY WISDOM: A rotating quote from Peter Lynch to keep you grounded RESEARCH & SOURCES This script was built using the following primary sources, all studied extensively: 1. "One Up On Wall Street" by Peter Lynch with John Rothchild (1989) share.google Lynch's first book laying out his complete investment philosophy - the 6 categories, PEG ratio, the "story" framework, and the idea that everyday investors have edges over professionals. 2. "Beating the Street" by Peter Lynch with John Rothchild (1993) share.google Lynch's second book where he walks through his actual portfolio decisions at Magellan, explains his mutual fund strategy, and shows step-by-step how he picks stocks. 328 pages of real-world application. 3. "The Peter Lynch Playbook" compiled by Mayur Jain (@mjbaldbard) share.google A comprehensive set of notes summarizing both Lynch books plus interview snippets. Covers portfolio allocation percentages, category-specific checklists, the 2-minute drill for each stock type, risk/reward profiles, and sell criteria. This document was instrumental in translating Lynch's qualitative approach into quantifiable rules. 4. Peter Lynch's "Stock Shop" Video Consultation (Fidelity Archives) youtu.be A full-length video presentation where Lynch personally explains his approach to categorizing stocks, building stories, understanding PE ratios, evaluating balance sheets, and managing risk. Key quotes transcribed and used to calibrate the scoring engine and story status logic. IMPORTANT NOTES - This is a STRATEGY script, not an indicator. It generates actual backtestable trades. - The script is purely fundamental. No technical analysis. Lynch didn't use charts to make decisions. - Auto mode requires stocks with TradingView financial data. For other instruments, use Manual mode. - The Lynch Score is a CONVICTION METER by default, not a trade gate. Enable Score Gate in settings if you want it to filter trades. - All portrait coloring is non-repainting. Colors only update on confirmed (closed) bars. - Start with Bar Replay. That's where the magic happens. Watch the story unfold bar by bar, just like Lynch did at his desk at Fidelity every morning. "The key organ is the stomach, not the brain." - Peter Lynch
Pine Script®策略
由Beck_Mullen提供
LBR with HM Gartley 1935 on Log Returns Momentum Vol TargetOverview Linda Bradford Raschke's Momentum-based strategy, made by conclusions from the book Profits in the Stock Market by H.M. Gartley in 1935, and uses log returns for directional bias as well as dynamic volatility targeting to maintain consistent risk exposure. Sizes positions inversely to realized volatility (from log returns std dev) for better compounding in trending markets like gold (XAUUSD). Key Features Log returns calculation: ln(close / close ) for time-additive momentum. Directional signals: Enter long when momentum > 0, short when < 0 (configurable strict crossover mode). Volatility scaling: Targets user-defined annual vol (default 20%) → reduces size in high-vol periods. Exits: Percentage TP/SL + explicit close on opposite signals for reliable backtests. Debug visuals: Momentum plot, signal shapes, real-time table (vol, size factor, qty, signal state). How to Use Best on Daily or higher timeframes for meaningful log momentum (e.g., XAUUSD, BTCUSD, stocks). Adjust Momentum Lookback (default 50 bars), Target Vol %, TP/SL %. Backtest with commissions/slippage enabled for realism. Use on log-scale chart for % perspective. Limitations & Notes No guarantees of profitability; markets involve risk. Designed for educational/quant purposes; test thoroughly. Not financial advice. Open-source for community learning. Credits Built on standard quant finance principles (log returns for normality/additivity, vol targeting for risk control). Inspired by discussions on compounding and GARCH-like vol estimation from Linda Bradford Raschke's conclusions from the book Profits in the Stock Market by H.M. Gartley in 1935.
Pine Script®策略
由uzair2join提供
Legendary LBR Powered Channel Gold Momentum Scalper with HTF FLTLegendary Linda Bradford Raschke's - A heavily adapted and evolved version of a classic moving-average channel scalping concept, re-designed specifically for the noisy 1-minute timeframe on XAUUSD (Gold Spot). The original idea (using EMA 16/30 as a channel, WMA 5/12 crossovers for breakout confirmation, and RSI 19 for trend strength) performed poorly on ultra-low timeframes due to excessive noise and frequent false signals. This version diverges significantly from the strict original rules to achieve better realism and positive expectancy in backtests. Core changes from the original concept: No requirement for the EMAs to be horizontal/flat on the 1-minute chart (too rare and unreliable) No simultaneous double WMA crossover trigger (replaced with strong directional momentum candle + ATR expansion) Higher-timeframe trend filter added (15-minute EMA 50 > EMA 200 for longs, reverse for shorts) to align with bigger moves RSI role shifted from trend confirmation (>50/<50) to avoiding extreme overbought/oversold entries Exits changed from WMA reversal cross to volatility-based: fixed ATR take-profit + trailing stop Indicators used: Higher timeframe (15m): EMA 50 (fast) & EMA 200 (slow) → overall trend direction Current timeframe (1m): ATR(14) → volatility measurement, SL/TP sizing RSI(14) → filter extreme conditions Price action: strong directional candle (close breaks previous close by ≥0.8×ATR) Entry rules: Long: Strong bullish candle + HTF trend bullish (15m EMA50 > EMA200) + RSI < 70 Short: Strong bearish candle + HTF trend bearish (15m EMA50 < EMA200) + RSI > 30 Risk management: Stop Loss: 1.0 × ATR below/above entry Take Profit: 2.5 × ATR (initial target) Trailing stop: activates after price moves 1.5 × ATR in favor, trails at 0.5 × ATR distance Fixed position size (0.1 lot recommended for micro accounts) Best usage: Timeframe: 1 minute XAUUSD only Sessions: London + New York overlap (highest liquidity/volatility) Backtest period: focus on recent data (2024–2026 preferred) Risk: 0.5–1% equity per trade maximum — high frequency requires tight discipline Important notes: This is a significantly modified adaptation built to function on 1-minute charts where the original logic fails. Forward test thoroughly, combine with discretion and broader market context. Trade responsibly.
Pine Script®策略
由uzair2join提供