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The Ultimate Crypto Market Breadth: Advance/Decline [Top 120]The Ultimate Crypto Market Breadth: Advance/Decline 📖 What is this Indicator? The crypto market is notorious for printing fakeouts. Often, Bitcoin or a handful of massive layer-one coins will pump the entire market cap higher, creating the illusion of a massive bull run. Meanwhile, beneath the surface, 80% of altcoins are bleeding out. The Advance/Decline (A/D) Breadth Line is the ultimate "look under the hood." This indicator acts as a modified "Blowup Indicator" for crypto. Instead of just looking at the price of BTC or the Total Market Cap, it tracks the daily performance of the Top 120 Cryptocurrencies by volume. It asks one simple question: Did more coins close green today, or did more coins close red? By aggregating the daily Advance/Decline data of 120 highly liquid assets, this tool gives you a pure, manipulation-free view of true market sentiment and underlying strength. ⚙️ How to Install (Read Carefully!) Due to TradingView’s strict limit of 40 request.security() data calls per script, a 120-coin breadth indicator cannot be coded into a single file. This tool requires 3 data feeds to run. Follow these steps exactly to get the unified dashboard: Step 1: Add the Data Feeds Add these three dependency scripts to your chart. Once they are on your chart, hide them (click the eye icon) so they don't clutter your screen. Step 2: Add the Master Aggregator Add this script (The Master Aggregator) to your chart. Step 3: Route the Data Double-click the Master Aggregator on your chart to open its settings. Go to the Inputs tab. Map Part 1 Data to the Net A/D plot of your hidden Part 1 script. Map Part 2 Data to the Net A/D plot of your hidden Part 2 script. Map Part 3 Data to the Net A/D plot of your hidden Part 3 script. Click OK! You will now see a single, unified histogram showing the absolute breadth of the crypto market. ⏱️ The Best Timeframe: Daily (1D) This indicator is strictly designed to be mastered on the Daily (1D) timeframe. Here is why: Why not 4H? The crypto market is open 24/7 and is highly volatile intraday. Measuring 4-hour intervals creates massive amounts of "noise" as algorithmic bots wash prices back and forth. It provides false signals. Why not Weekly? While a Weekly A/D line is great for macro-investors, it is too slow for active swing traders. By the time a weekly breadth candle closes red, the dump has already happened. The Daily Sweet Spot: The Daily close is the only universally respected metric for a trend shift. It captures the true net result of global participation over a 24-hour cycle. 📈 How to Use & Master the A/D Line 1. Trend Confirmation (The "All Clear") If Bitcoin is breaking out to new highs, and this indicator is printing massive green bars (+60, +80, +100), it means the rally is healthy. The vast majority of the market is participating. Buy the dips with confidence. 2. Bearish Divergence (The Warning Sign) This is the most powerful signal this indicator provides. If the chart (e.g., TOTAL2 or BTC) is grinding up to make a new high, but the A/D histogram is shrinking or printing red bars, danger is imminent. This means heavyweights are propping up the index while smart money is quietly distributing (selling) the broader altcoin market. Tighten stops and prepare for a reversal. 3. Bullish Divergence (The Bottom is In) If the market is crashing and making lower lows, but the A/D line stops printing deep red bars and starts printing higher lows (or flipping green), the selling pressure has exhausted. The market is secretly gaining strength despite the ugly price action. Get ready to long. 4. The Capitulation Washout Look for extreme red spikes (e.g., -110 out of 120 coins down). This signifies absolute panic. When an extreme red bar is immediately followed by a solid green bar the next day, it is a classic "V-Bottom" washout signal. The weak hands have been flushed. Note: This indicator uses the ignore_invalid_symbol=true failsafe. If an exchange delists a coin or changes a ticker, the script will automatically bypass it instead of crashing your chart, ensuring lifetime stability!
Pine Script® indicator
by R2D2_4Life
1
Advanced UT-Trail System Pro [identityKa]Advanced UT-Trail System Pro 🏆 Aiming for the highest standard of chart analysis, this is not just an indicator; it is a complete, institutional-grade risk management and trading system. 🚀 Why This System? Standard signal bots fail because they lack context. They tell you to buy in a bear market and sell in a bull market, leading to massive drawdowns. The identityKa UT-Trail System solves this by fusing the legendary Heikin-Ashi smoothed UT Trailing Stop with a strict Macro Trend Shield and automated Take-Profit geometry. ⚙️ Key Features (The Editor's Choice Engine): 🛡️ The Macro Shield (200 EMA): The system completely blocks counter-trend signals. It will only print a BUY when price is above the 200 EMA, and a SELL when below. Protect your capital from ranging chop. 🎯 Auto Take-Profit Projection: The moment a valid signal is fired, the algorithm dynamically calculates and draws TP1 (Safe) and TP2 (Max) target lines based on real-time ATR volatility. You always know your exit before you enter. 📊 Live HUD Dashboard: A minimalist, transparent command center in the bottom right corner updates you on the Macro Trend, Current UT State, and Market Volatility at a glance. 📈 Dynamic Stepline Trailing: Plots a continuous, step-like trailing stop-loss line behind the price. Stay in the winning trades longer and cut losers short. 🧠 Auto-Adaptive Timeframe AI: Are you tired of indicators lagging on 15m charts? This system features a dynamic self-adjusting engine. If you switch to lower timeframes, the algorithm automatically shifts into "Scalp Mode," speeding up the ATR sensitivity and Macro EMA to completely eliminate lag. Switch back to 4H, and it reverts to "Swing Mode." 💡 How to Use: Wait for a valid BUY/SELL label. Set your stop-loss at the stepline trailing indicator. Take partial profits at TP1, and let the rest run to TP2 or until the trailing stop is hit. 💎 Note: This indicator is the crowning jewel of our free toolkit from the identityKa Pro Ecosystem. Follow my profile for advanced all-in-one trading algorithms and premium tools.
Pine Script® indicator
by IdentityKa
Mean Reversion V-F V.1I received lot of request to publish better version of Mean Reversion V-F so here you go In V.1 WE going in Long trade after MA falling # of bars The # of bars can be adjust from the settings New calculation for deviations - after the first trade calculation start from close of the bar and so on The first trade is market trade the rest are limit trades so can get to it in any time if the price drop to that deviations level Can be use for crypto and stocks For stocks just enable Use for Stocks and input # of stocks The strategy gave my lot better results and less drown down If any question let my know Happy trading
Pine Script® strategy
by fullmax
NY Pre-Session Sweep# NY Pre-Session Sweep ## Overview Session-based strategy for the New York Pre-Session (14:30–16:30 Berlin). Uses "Attempted Candles" after a sweep of the Pre-Session box. Optimized for XAUUSD on the 5-minute chart. Integrated with Telegram and Pine Connector for alerts and external bots. --- ## Strategy Concept The strategy uses the Pre-Session box (14:30–16:30 Berlin) as a reference range. Trades are only taken when the market sweeps a session extreme and the candle closes in the direction of the sweep (Attempted Candle). --- ## Time Structure (Berlin, DST-safe) | Phase | Time (Berlin) | Description | |-------|---------------|-------------| | **Pre-Session Box** | 14:30 – 16:30 | High/Low of the box are collected as reference | | **Trading 1** | 16:30 – 19:00 | First trading phase | | **Pause** | 19:00 – 19:00 | Brief pause | | **Trading 2** | 19:00 – 22:00 | Second trading phase | **Note:** Signal on the last candle of Trading 1 (18:55) → Entry only at the open of the first candle of Trading 2 (19:00). --- ## Entry Logic (Attempted Candle) **Long Signal:** - Current candle low < Session Lowest Low (lowest low since session start) - Candle closes bullish (Close > Open) - Candle low < Previous candle low (new low) **Short Signal:** - Current candle high > Session Highest High (highest high since session start) - Candle closes bearish (Close < Open) - Candle high > Previous candle high (new high) **Entry:** At the open of the candle **after** the Attempted Candle (no entry on the ATP candle itself). --- ## Risk Management - **Stop Loss:** Low of the Attempted Candle (Long) or High (Short) - **Take Profit:** Entry ± (Risk × R), default R = 3.0 - **Half-Wick SL:** With very long wicks, SL is set to half the candle body so TP remains reachable (threshold configurable) - **Position Size:** 1% of equity (adjustable) --- ## Trade Management - **Max Trades per Day:** 3 (default) - **After TP:** No further trades that day (unless "Allow opposite after TP" is enabled) - **After SL:** Opposite trade allowed if a counter-direction Attempted signal occurred while in position - **Reference Update:** After each trade, reference levels (Session High/Low) are updated --- ## Optional Filters **Williams %R Filter (default: off):** - Long only when Williams %R is in the Long zone (e.g. -75 to -25) - Short only when Williams %R is in the Short zone (e.g. -100 to 0) - Reduces trades in sideways conditions --- ## Integration **Pine Connector / Webhook:** - JSON alert with symbol, direction, entry, SL, TP, R and session label - For bots, trade copiers or webhooks **Telegram:** - Optional: Alert includes chat_id and HTML text for Telegram webhook - Signal format: Symbol, direction, SL, TP **Signal Tester:** - Periodic test alerts (e.g. every 15 min.) to verify connection --- ## Chart Settings - **Timeframe:** 5 minutes (required) - **Symbol:** XAUUSD recommended, works with any symbol - **Timezone:** Strategy uses Europe/Berlin (DST-safe) --- ## Visual Elements - **Pre-Session Box** (blue): High/Low of the Pre-Session - **Pause Box** (orange): High/Low during the pause - **Attempted Candles:** Green/red triangles below/above the candle - **Entry Markers:** Larger triangles at entry - **SL/TP Lines:** Red (SL) and green (TP) lines --- ## Notes - No hedging: Only one direction per day (except opposite trade after SL) - Trading days: Monday–Friday configurable (default: Mon–Fri) - Strategy designed for systematic trading and backtesting --- *Not financial advice. Past performance is not indicative of future results. Trading involves risk.*
Pine Script® strategy
by Lean_Trading
Honeymoonist - Panic Buy / SellPanic Buy / Sell Detector v1 — Spot extreme price moves the moment they happen. This overlay indicator detects sudden, abnormal price surges (Panic Buy) and sharp drops (Panic Sell) based on percentage thresholds you define. It's built for traders who want to catch moments of extreme buying or selling pressure — whether you're scalping on 1-minute charts or swing trading on daily. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔑 KEY FEATURES • Three lookback modes to fit your trading style • One signal per event — no duplicate or stacking labels • Independent buy/sell cooldowns to reduce noise • Configurable alert messages with full context (ticker, price, % change, mode) • Clean visual output: shape markers, info labels, and background highlights ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📐 HOW IT WORKS The indicator calculates the percentage change between the current close and a reference price. When this change exceeds your configured threshold, a signal fires. % Change = (Current Close − Reference Price) / Reference Price × 100 The reference price depends on which lookback mode you choose: 1 — Bar Count Compares close to close , where N is a number of bars you set (default: 10). Simple and predictable. 2 — Time Interval Same logic as Bar Count, but N is automatically calculated from a timeframe you select. For example, if your chart is 1-minute and you choose a 5-minute lookback, N = 5 bars. This keeps the lookback consistent even if you switch chart timeframes. N = ceil(Lookback Timeframe ÷ Chart Timeframe) 3 — Cumulative Streak Tracks consecutive bars closing in the same direction and accumulates the total percentage change. A signal fires when the cumulative move crosses the threshold. This mode catches gradual momentum buildups that the other modes might miss. • Neutral bars (close = previous close) keep the streak alive. • Once a signal fires, it won't fire again until the streak ends and a new one begins. • The first streak on chart load is suppressed to avoid false signals. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ SETTINGS Signal • Panic Buy Threshold (%) — Minimum rise to trigger a buy signal (default: 1.0%) • Panic Sell Threshold (%) — Minimum drop to trigger a sell signal (default: 1.0%) • Lookback Mode — Bar Count, Time Interval, or Cumulative Streak • Lookback (bars) — Number of bars for Bar Count mode (default: 10) • Lookback Timeframe — Timeframe for Time Interval mode (default: 1 min) • Cooldown (bars) — Minimum bars between same-type signals (default: 3) Alert • Alert Only on Bar Close — When on, alerts wait for bar confirmation. When off (default), alerts fire on the first tick that crosses the threshold. Faster, but may produce false signals if the bar reverses. Visuals • Show Info Labels — Toggle the detail labels on/off • Show Background — Toggle background highlighting on/off • Label Size — tiny / small / normal / large • Panic Buy Color / Panic Sell Color — Customise signal colours • Background Opacity — 0 (fully opaque) to 100 (fully transparent) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔔 ALERT SETUP 1. Add the indicator to your chart 2. Create a new alert → Condition: "Panic Buy / Sell Detector" 3. Trigger: "Any alert() function call" 4. In the Message box, type: {{message}} 5. The alert will include: signal type, ticker, reference price → close price, % change, timeframe, and mode Example alert message: 🟢 PANIC BUY — BTCUSDT.P | 98000.00 → 99200.00 | 1.22% | TF: 5 | Mode: Time Interval 🔴 PANIC SELL — BTCUSDT.P | 99200.00 → 97800.00 | -1.41% | TF: 5 | Mode: Time Interval For webhook/bot integration (LINE, Telegram, Discord), you can use: {"text": "{{message}}", "price": "{{close}}", "time": "{{timenow}}"} ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 TIPS • Start with Time Interval mode — it adapts automatically when you switch chart timeframes. • Use Cumulative Streak mode for catching slow, grinding moves that build up over many bars. • Set cooldown to 3–5 bars to avoid alert fatigue during volatile sessions. • Enable "Alert Only on Bar Close" for more reliable signals in backtesting or if you're away from the screen. • Lower the threshold for stable assets (stocks, forex); raise it for volatile assets (crypto, small caps). ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER This indicator is an informational tool only. It does not generate trade orders, calculate P&L, or provide financial advice. Use it as one input among many in your trading decisions. Past signals do not guarantee future results. Always manage your risk. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📜 LICENSE This source code is released under the Mozilla Public License 2.0.
Pine Script® indicator
by honeymoonist
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® strategy
by Fre_Fre
1
BTC Cycle Composite IndicatorBTC Cycle Composite Indicator: A Multi-Factor Approach to Identifying Market Tops and Bottoms Introduction The Bitcoin market is characterized by distinct four-year cycles driven by halving events, yet accurately pinpointing cycle tops and bottoms remains a challenge even for experienced traders. Single indicators often generate false signals or lag significantly. The BTC Cycle Composite Indicator addresses this by integrating multiple proven on-chain metrics, technical analysis tools, and cycle-based models into a single coherent framework. Its goal is to provide traders with a probabilistic risk score that highlights periods of extreme overvaluation (potential tops) and undervaluation (potential bottoms), while filtering out noise through advanced confirmation mechanisms. Core Design Philosophy The indicator is built on a multi-factor voting system. Instead of relying on any single metric, it aggregates signals from a diverse set of independent indicators that capture different aspects of market behavior: On-chain valuation (MVRV Z-Score, Puell Multiple, CVDD, NUPL) reflects the positioning of long-term holders and miners. Technical momentum (Pi Cycle Oscillator, RSI, price deviation from moving averages) identifies price extremes. Cycle timing (halving progress, post-halving windows) anchors the analysis within the historical rhythm of Bitcoin. Market structure (Power Law channel, V/T Ratio, 15% rule) adds context about the broader macro trend. Each indicator contributes to a risk score (0–100), and only when a sufficient number of them align—and additional filters (trend, volatility, signal spacing) are satisfied—does the indicator generate a clear visual signal. Detailed Component Breakdown 1. On-Chain Metrics (Simulated for Demonstration) MVRV Z-Score: Compares market value to realized value, normalized by standard deviation. Historically, values above 7 have marked major tops, while values near 0.1 have indicated bottoms. The indicator can also use a dynamic 6‑month rolling Z‑score to adapt to changing market structure. Puell Multiple: Measures miner revenue relative to its 365‑day moving average. Extremely high values (>3.33) suggest miner over‑profitability and potential selling pressure; very low values (<0.5) signal miner capitulation and bottoms. CVDD (Cumulative Value Coin Days Destroyed): A bottom‑capture metric that tracks the dollar value of coin‑days destroyed. When price falls below the CVDD extension line, it historically marked strong accumulation zones. NUPL (Net Unrealized Profit/Loss): Gauges the aggregate profit/loss status of the market. NUPL > 0.75 corresponds to extreme greed (euphoria), while negative values indicate fear. 2. Technical Indicators Pi Cycle Oscillator: Unlike the classic Pi Cycle Top indicator that waits for a 111 SMA / 350 SMA×2 cross, this oscillator measures the percentage distance between the two moving averages. When this value exceeds a user‑defined threshold (e.g., 80%), it serves as an early warning of an overheated market. Price Deviation from 200‑day SMA: A simple yet powerful mean‑reversion tool. Deviations above +50% have historically coincided with tops, while deviations below -20% align with bottoms. RSI (14): Standard overbought/oversold levels (70/30) are used, but they are only considered in conjunction with other factors. V/T Ratio: Compares on‑chain transaction value to token velocity; extreme deviations from its moving average can signal turning points. 3. Cycle and Structural Factors Halving Progress: The indicator calculates the exact position between two consecutive halvings. Four color‑coded phases (green, lime, yellow, red) visually represent the typical market sentiment progression. Top/Bottom Windows: Historical data shows that cycle tops often occur 528–548 days after a halving, while bottoms tend to form within the first 200 days. These windows are used as soft filters. Power Law Channel Position: Based on the long‑term power law regression, prices near the upper band (>80th percentile) are considered overextended, while those near the lower band (<20th percentile) are undervalued. 15% Rule (optional): When price drops more than 15% from its 500‑day high after a series of strong bullish candles, it may indicate distribution by smart money—a supplementary top confirmation. 4. Altcoin Season Signals Bitcoin dominance (BTC.D) is monitored for sharp moves. A decline of more than 2% over 14 days suggests capital rotation into altcoins, while a rise of more than 2% indicates Bitcoin strength. These raw signals are further validated by: Price position relative to 200‑day SMA. RSI entering oversold (for alt‑season) or overbought (for BTC‑season) territory. Volume spikes (above 1.5× the 20‑day average). Candlestick patterns (hammer/bullish engulfing for buys; shooting star/bearish engulfing for sells). How the Components Work Together The indicator does not simply flash a signal when any one metric triggers. Instead, it employs a multi‑stage aggregation and filtering process: Risk Score Calculation Each of the ten top‑oriented and eight bottom‑oriented indicators votes independently. The percentage of active indicators forms the raw risk score (e.g., 7 out of 10 = 70% top risk). Weighted Adjustment (Optional) Because some indicators are more predictive during specific cycle phases, the indicator can apply dynamic weights. For example, Pi Cycle and MVRV receive higher weights in the late halving phase (red zone), while Puell and CVDD are emphasized in the early phase (green zone). Multi‑Stage Filtering Trend Filter: Signals are only considered if they align with the primary trend (price above/below 200‑day SMA). Volatility Filter: Using ATR, signals are discarded during low‑volatility consolidation unless volatility exceeds 1.2× its 20‑day average. Momentum Filter: Requires the short‑term moving average to be sloping in the direction of the signal (e.g., for a top signal, price should be above its 20‑day MA and the MA should be rising). Signal Suppression: After a signal is generated, no further signals of the same type are allowed for a user‑defined number of bars (default 20) to prevent clustering. Confirmation Bars: A signal must persist for a minimum number of consecutive bars (default 2) before being displayed. Visual Output Colored Background: The chart background gradually shifts from green (early accumulation) to red (late distribution) based on halving progress, providing an intuitive sense of cycle phase. Halving Markers: Blue vertical lines and labels mark each halving date. Cycle Top/Bottom Labels: When all filters are satisfied, a red “Cycle Top” label appears above the bar (with the current risk score), and a blue “Cycle Bottom” label appears below. Arrow Signals: Small red downward arrows (⬇️TOP) and green upward arrows (⬆️BOT) are plotted on every qualifying bar for easy spotting. Buy/Sell Signals: For altcoin‑season entries, tiny green “🪙 BUY” triangles at the bottom and orange “₿ SELL” triangles at the top are displayed. Risk Score Panel: A table in the bottom‑right corner shows the current top/bottom risk percentages and the number of triggered indicators, updated in real time. Practical Usage Recommended Settings Timeframe: Daily or weekly charts work best, as the underlying metrics are designed for medium‑ to long‑term cycles. Parameters: Most thresholds (e.g., MVRV levels, Pi Cycle oscillator threshold, minimum risk score) are adjustable. Beginners can keep the defaults; advanced users may fine‑tune based on backtesting. On‑Chain Data Source: The indicator currently uses simulated MVRV, Puell, etc., for demonstration. For live trading, replace these with real data sources such as CRYPTOCAP:BTC.MVRV or subscribe to a reliable on‑chain data provider. Interpretation A top risk score above 60 accompanied by a red background and a “Cycle Top” label suggests that multiple independent metrics are flashing warning signs. This is a signal to consider taking profits or tightening stops. A bottom risk score above 60 in the green zone with a “Cycle Bottom” label indicates a historically favorable accumulation area. The BUY/SELL signals are more tactical and may appear more frequently; they should be used in conjunction with the broader cycle context. Limitations and Disclaimer No indicator is infallible. The BTC Cycle Composite Indicator is a tool for probability assessment, not a crystal ball. Past performance does not guarantee future results. Users should always combine it with fundamental analysis, order book data, and proper risk management. The indicator’s parameters may need periodic adjustment as market dynamics evolve (e.g., the Pi Cycle oscillator threshold may drift over time). Originality and Innovation While the individual indicators are well‑known, their combination and the filtering logic are original: Dynamic weighting based on halving progress adapts the model to different cycle phases. Multi‑timeframe confirmation (optional weekly RSI check) adds an extra layer of robustness. 15% rule provides a unique structural filter for top detection. Signal suppression and momentum filters drastically reduce false positives compared to a simple “majority vote” approach. The risk score panel gives users immediate insight into the internal state of the model, fostering transparency. Conclusion The BTC Cycle Composite Indicator is designed for traders who want a comprehensive, data‑driven view of Bitcoin’s cyclical extremes. By aggregating diverse metrics and applying rigorous filtering, it aims to highlight high‑probability turning points while minimizing noise. Whether you are a long‑term investor seeking accumulation zones or a swing trader looking for trend shifts, this indicator offers a structured way to interpret the complex interplay of on‑chain, technical, and cyclical forces that drive Bitcoin’s market cycles.
Pine Script® indicator
by neeson1987
SPX Sector AD + Iceberg TICKThis indicator is a "Market Internals" engine designed to reveal the true strength of S&P 500 moves. By looking under the hood of the index, it helps traders distinguish between broad market participation and rallies driven solely by heavyweights (the "Magnificent 7"). It combines three powerful concepts into a single pane: Sector Breadth, Buying Aggression (TICK), and Trend Following. 1. The Core: Weighted vs. Unweighted Divergence Weighted Histogram (The Generals): Represents the S&P 500 performance based on sector market cap (e.g., Tech/XLK has a ~33% impact, while Utilities/XLU has ~2%). When these bars are strong, the mega-caps are moving. Unweighted Line (The Soldiers): Represents the average performance of all 11 sectors equally. When this line rises, there is broad market participation. The Edge: Spot divergences. If the Weighted Bars are rising but the Unweighted Line is falling, the rally is narrow and potentially fragile (a "General's Rally"). 2. The Iceberg: Cumulative TICK A scaled cumulative TICK line is plotted in the background (the "Iceberg"). This visualizes the raw buying vs. selling aggression on the NYSE throughout the session. Green Iceberg: Persistent buying pressure / accumulation. Red Iceberg: Persistent selling pressure / distribution. 3. The Signal: Breadth Trend Instead of generating signals on price, this script applies ATR Trailing Stop logic directly to the Weighted AD Line. Buy Signal (B): Triggers when the internal sector strength breaks above its own volatility band. Sell Signal (S): Triggers when sector momentum breaks down. This often provides an earlier warning of trend changes than price action alone. How to Use Bullish Confirmation: Price is rising + Green Histogram + Green Iceberg + Unweighted Line rising. Bearish Divergence: Price makes a new High, but the Breadth Bot prints a lower High or a Sell signal. Rotation: If the Histogram is flat but the Unweighted Line is ripping higher, capital is rotating from Mega Caps into the broader market. Settings: Includes customizable weights for all 11 SPDR Sectors. Adjustable "Visual Divisor" for the TICK to fit it perfectly behind your sector data. Customizable ATR settings for the Breadth signals.
Pine Script® indicator
by nellutla
Smart MACD + KNN (Dynamic SL Fix)This script is a comprehensive trading system designed for TradingView that combines traditional momentum indicators with machine learning concepts and advanced trade management logic. Here is a detailed description of its features: 1. Signal Generation (The "Brain") Smart MACD: Uses a standard MACD (Moving Average Convergence Divergence) to identify buy and sell opportunities. KNN Machine Learning: Filters every MACD signal using a K-Nearest Neighbors algorithm. It analyzes historical market data (RSI, CCI, Volatility, Volume) to determine if the current signal is statistically likely to be profitable. If the ML prediction is negative, the signal is ignored. Trend Filter: An optional 200 EMA filter ensures you only trade with the long-term trend (Buy above EMA 200, Sell below). Volatility Guard: Automatically blocks signals during extreme volatility spikes (like news events) to prevent bad entries. 2. Trade Management (The Logic) Single Trade Mode: The script enforces a "one trade at a time" rule. It will not generate a new "Buy" signal if a "Buy" trade is already active. It waits for the trade to hit Take Profit (TP) or Stop Loss (SL) before resetting. Flip Capability: While it blocks same-direction signals, it allows opposite signals. If you are in a Long trade and a valid Short signal appears, it effectively "flips" the trade—closing the Long and opening the Short immediately. Dynamic Stop Loss (Stepped ROI): This is a profit-locking feature. Trigger 1: When price moves X% in profit, the SL moves to a specified ROI % (e.g., Break Even). Trigger 2: When price moves further to Y% profit, the SL moves again to lock in a larger profit. 3. Automation & Alerts Customizable Messages: You can input your own text or JSON commands for Entry, TP, and SL alerts directly in the settings menu. 3x Trigger Safety: Every alert fires 3 times continuously to ensure that external bots or webhooks receive the signal, minimizing the risk of missed trades due to network lag. 4. Visuals TP/SL Lines: Draws active Stop Loss and Take Profit lines on the chart that update in real-time. Dashboard Table: A panel in the top-right corner displays the precise price levels for the current TP and SL. Fog & Colors: The background and candles change color based on the trend direction, giving you an immediate visual cue of market sentiment.
Pine Script® indicator
by knowledgejoe
LuxAlgo - L1 Proximal Filter [MTF & Alerts] Maxxed EditionLuxAlgo - L1 Proximal Filter Maxxed Edition. What's New & Improved. This is the Maxxed Version of the original LuxAlgo L1 Proximal Filter — cleaner, smarter, and built for real trading/automation. Core Improvements Multi-Timeframe (MTF) Confirmation: Entries only trigger when the lower timeframe (chart TF) and higher timeframe are fully aligned. Two ways to get an entry: LTF leads the flip and HTF is already in that direction (immediate high-probability entry). HTF finally flips to match an existing LTF trend (strong confirmation/catch-up entry). This filters out weak/counter-trend signals — only trades with the higher-timeframe bias. Smart Close Signals:When HTF confirmation is enabled and the LTF flips against the current HTF trend (divergence), a close signal is issued immediately. Example: You're long because both TFs were bullish → LTF flips bearish while HTF still bullish → "Close Long" fires. This protects profits and avoids riding against the higher trend — early exit on weakness. Visual Clarity:Clean arrow labels (↑/↓) for entries. Solid circles for closes. Thin lines on both LTF and HTF filters. Subtle shaded fill between price and filter. Fully customizable background trend color (with transparency slider). Automation-Ready Alerts: Four clean, selectable alert conditions: "Entry Long", "Entry Short", "Close Long", "Close Short". Perfect for webhooks, bots, or notifications — set separate alerts or combine as needed. Messages are clear and include context. This edition turns the original smooth filter into a complete trend-following system: enter only on alignment, exit on divergence. All credit to @LuxAlgo and original description below: The Proximal Range Filter indicator provides a robust range/noise-filtering solution that utilizes an L1 soft-thresholding approach to determine market trends while minimizing lag and erratic price movements. 🔶 USAGE The indicator is primarily used to identify the current trend direction and significant price shifts while ignoring minor market noise. It appears as a colored line on the price chart, transitioning between bullish and bearish states. 🔹 Trend Identification Users can determine the current market sentiment by looking at the color of the filter line and the associated gradient fill: A green line and fill indicate a bullish trend, suggesting that price is consistently overcoming the upper noise threshold. A red line and fill indicate a bearish trend, suggesting that price is consistently breaking below the lower noise threshold. 🔹 Trend Switches The indicator plots "Trend Switch Dots" at the specific point where a trend reversal is confirmed. These dots appear at the previous filter level to highlight the origin of the new trend direction. This visual cue helps traders identify the exact moment the filter "stepped" in a new direction. 🔹 Responsiveness and Volatility By adjusting the inputs, traders can tailor the filter to different trading styles: For high-volatility assets (like Crypto), increasing the ATR Multiplier can help filter out "fakeouts" that occur during consolidation. In trending markets, a higher Adaptation Rate (μ) allows the filter to track price changes more aggressively once the noise threshold is exceeded, reducing lag. A lower ATR Multiplier combined with a lower Adaptation Rate creates a more "stepped" filter, useful for identifying major support/resistance levels created by the filter's flat periods. 🔶 DETAILS The core of this indicator is the L1 Proximal Filter logic. Unlike standard moving averages that react to every price tick, this filter uses a "Soft-Thresholding" mechanism to isolate meaningful price action from random volatility. 🔹 Calculation Logic The filter operates through a specific prediction-adaptation cycle: Noise Threshold: The script calculates a dynamic threshold using a 200-period ATR multiplied by the user-defined setting. This ensures the filter's sensitivity scales automatically with the asset's current volatility. State Prediction: The algorithm predicts the next state based on the previous filtered value and the current velocity (the rate of change). Adaptive Blending: The prediction is blended with the new incoming source data using the Adaptation Rate (μ). This creates a temporary "candidate" value for the filter. Soft-Thresholding: The difference between the candidate value and the previous filter state is evaluated. If the absolute difference is less than the threshold, the velocity is set to zero (the filter remains flat). If it exceeds the threshold, the threshold value is subtracted from the absolute difference to calculate the "meaningful" signal. This mathematical approach ensures that only price movements strong enough to overcome the statistical noise (the ATR threshold) result in a change to the filter's value. 🔹 Trend Switch Dots The Trend Switch Dots are plotted with a -1 offset. This is because a trend change is only confirmed once the current bar's filter value moves relative to the previous bar. The dot marks the price level where the "breakout" from the previous noise range occurred. 🔶 SETTINGS Source: The price data used for calculation (typically the Close price). ATR Multiplier: Defines the noise threshold. Higher values require larger price movements to change the filter's value, resulting in a smoother output that ignores more "whipsaws." Adaptation Rate (μ): Controls how fast the internal prediction adapts to price changes. A value of 1.0 reacts most aggressively to new data, while lower values provide more smoothing during the adaptation phase.
Pine Script® indicator
by Maximilianned
SJ Stoch MFT 3 📊 Stoch MTF 3 TF Direction Only This indicator is a Multi-Timeframe Stochastic (MTF) designed to identify trade direction by analyzing the Stochastic direction across 3 different timeframes simultaneously. It focuses only on direction, not overbought/oversold levels, making it ideal as a trend filter to reduce false signals and improve trade accuracy. ⸻ 🔧 How It Works For each selected timeframe, the indicator calculates the Stochastic oscillator and determines its direction: • 🔼 Bullish → %K is above %D • 🔽 Bearish → %K is below %D A signal is generated only when all 3 timeframes agree on the same direction. ⸻ ⏱ Configurable Timeframes • TF1: Default M1 • TF2: Default M5 • TF3: Default M15 All timeframes are fully customizable to fit any trading style. ⸻ 🎯 Signals on Chart • 🟢 BUY Signal Triggered when Stochastic direction is bullish on all 3 timeframes. • 🔴 SELL Signal Triggered when Stochastic direction is bearish on all 3 timeframes. Signals are displayed as small circles below the candles, keeping the chart clean and readable. ⸻ 🔔 Alerts Built-in TradingView alerts are included: • BUY signal alert • SELL signal alert Suitable for: • Manual trading • Automation / Webhook alerts • EA or trading bot integration ⸻ 📌 Best Use Cases • Scalping and Intraday trading • Traders who rely on Stochastic • Multi-timeframe trend confirmation • Directional filter for any trading strategy ⸻ ⚠️ Disclaimer This indicator is not a standalone trading system. For best results, combine it with proper risk management, price action, or support/resistance analysis.
Pine Script® indicator
by samranj
WaveTrend & RSI Combined (v-final)# RSI Divergence + WaveTrend Combined ## Overview This indicator combines RSI Divergence detection with WaveTrend crosses to generate high-probability trading signals. It filters out noise by only showing divergences when confirmed by WaveTrend momentum crosses in the same direction. ## Key Features ### 1. Smart Divergence Detection - Detects both bullish and bearish RSI divergences - Uses **price pivot validation** to ensure divergences start from significant chart highs/lows, not just RSI extremes - Divergence endpoints must be in the **neutral zone (20-80)** to avoid overbought/oversold traps ### 2. WaveTrend Cross Confirmation - **Golden Cross**: WaveTrend crossover in oversold territory (below -60) - **Dead Cross**: WaveTrend crossover in overbought territory (above +60) - Crosses are displayed at RSI 20 (golden) and RSI 80 (dead) levels for easy visualization ### 3. Combined Signal Logic - **LONG Signal**: Bullish RSI Divergence + Golden Cross within the divergence period - **SHORT Signal**: Bearish RSI Divergence + Dead Cross within the divergence period - Divergences are **only displayed** when a matching cross exists in the same period ### 4. Visual Elements - **Yellow lines**: Divergence connections between master point and current point - **Small diamonds**: Divergence markers (green for bullish, red for bearish) - **Triangles**: Confirmed entry signals (▲ for LONG, ▼ for SHORT) - **Circles**: WaveTrend crosses (green at bottom for golden, red at top for dead) - **Background color**: Highlights signal bars (green for LONG, red for SHORT) - **Debug table**: Shows real-time RSI, divergence count, WaveTrend values, and cross status ## Settings ### RSI Divergence - RSI Length (default: 14) - Overbuy/Oversell levels - Divergence detection parameters (loopback, confirmation, limits) ### WaveTrend - Channel Length (default: 10) - Average Length (default: 21) - Overbought/Oversold levels - Cross Detection Level (default: 60) ### Pivot Detection - Pivot Left/Right Bars (default: 5) - Controls sensitivity for price pivot validation ## How to Use 1. **Wait for signal**: Look for the triangle markers (▲/▼) with background color 2. **Confirm with crosses**: Ensure the corresponding WaveTrend cross (circle) is visible 3. **Check divergence line**: The yellow line should connect meaningful price pivots ## Alerts - Built-in alert conditions for both LONG and SHORT signals - Webhook-ready format for automation (Telegram, Discord, auto-trading bots) ## Best Practices - Works well on higher timeframes (1H, 4H, Daily) - Combine with support/resistance levels for better entries - Use proper risk management - not every signal is a winner ## Credits - RSI Divergence logic inspired by K-zax - WaveTrend calculation based on LazyBear's implementation - Combined and enhanced by sondengs --- *This indicator is for educational purposes only. Always do your own research and manage your risk appropriately.*
Pine Script® indicator
by sondengs
Mine Shaft + Drift + Ore Pocket Detector (Gap+Touch)Mine Shaft + Drift + Ore Pocket Detector (Gap+Touch) — Full Description (v1.6.1, Pine v6) *Experimental - *Test Phase* 1) What this indicator is intended to do This indicator attempts to algorithmically discover “mine shaft” price structure on a chart by: Collecting structural anchor points (gaps and optionally pivots), Generating candidate trend “rails” (centerline + parallel upper/lower borders) from pairs of anchors, Fitting an optimal channel width around each candidate centerline, Scoring candidates based on how well price action conforms to the channel (touches + containment), Selecting and rendering: the main shaft channel (primary), additional drifts (secondary shafts per direction), And then detecting Ore Pockets: time locations where multiple selected lines intersect (time confluence / intersection clustering). The conceptual model is: A shaft = a best-fit channel that price respects over time (the “main tunnel”). Drifts = alternate channels close in quality to the main shaft (secondary tunnels). Ore pockets = future/past time coordinates where multiple channels’ centerlines intersect densely (confluence in time, not necessarily in price). 2) What it is doing right now (current behavior) In its current form, the script does a bounded, performance-limited scan: It stores a limited number of anchor points in arrays. It only considers a bounded number of recent anchors per direction. It constructs candidate lines from anchor pairs and evaluates channel fitness using sampled bars. On the last bar, it selects top candidates per direction and draws: a “main” channel per mode (single best overall, or separate up/down), plus optional drift channels, plus ore pocket markers. It is producing meaningful channels and drifts, but it is currently more likely to lock onto a strong “local” shaft than the one macro shaft spanning the entire market structure. 3) Core mechanics (how the script finds shafts) 3.1 Anchor generation (what points it uses) Anchors are the “support points” used to build candidate shaft centerlines. Two anchor families are supported: A) Gap anchors (from your selected gap mode) These attempt to capture “displacement events” and their boundaries/mids. B) Pivot anchors (optional structural anchors) These use pivots to inject macro structure points that are not strictly gap-based. All anchors are stored as: anchorX: bar_index of anchor anchorY: price of anchor anchorD: direction flag (+1 for up, -1 for down) Anchors are capped by maxAnchors with FIFO trimming. 3.2 Candidate generation (how it produces centerlines) For each direction (+1 and -1): Collect “recent” anchors of that direction within lookbackBars (bounded to maxDirAnchors). For each pair of anchors (x1,y1) and (x2,y2) that satisfy: spacing within , slope sign consistent with direction, Construct the line equation: slope m and intercept b Fit a channel width w around that line (via width mode). Score it (touches + inside count minus width penalty). Keep the top K rails (K = driftCount+1 typically). 3.3 Scoring model (what “best” means right now) For a candidate centerline: At sampled bars (stride sampling), compute: channel top = y(x) + w channel bot = y(x) - w Evaluate: Inside: candle range fits within the channel ± tolerance Touches: high near top border, low near bottom border (within tolerance) Score formula: score = insideCount * insideWeight + touchCount * touchWeight - (w / ATR) * widthPenalty So: Higher inside and touch counts increase score Wider channels are penalized (in ATR units) to avoid “cheating” via enormous width 3.4 Width fitting (how the channel thickness is chosen) Width is either: Fit (scan widths): scans widths between a min width and a max deviation cap and selects the best scoring width. Fixed ATR Envelope: uses a fixed width derived from ATR (currently hard-coded to a 2.0 ATR envelope in your present draft). Fixed Max Deviation: width is max observed deviation from line in sampled window. This matters because “macro shaft” detection is strongly influenced by whether the width-fitting is allowed to expand enough to contain large historical moves, without being penalized into losing to a smaller local shaft. 3.5 Rendering (what gets drawn) For any selected rail, it draws: Upper border line (top rail) Lower border line (bottom rail) Optional centerline (main only) Optional fill between borders (main only) Label at current bar with touches and inside count Drifts render similarly but without main-only features (depending on flags). 3.6 Ore Pocket detection (time confluence) Ore pockets are not “price zones” directly. They are computed as follows: Collect selected centerlines (m,b) for: the main selected shaft(s), and all drift centerlines (both directions if present) For each pair of selected lines, compute intersection x-coordinate: x* = (b2 - b1) / (m1 - m2) Only keep intersections within: Cluster intersections by time proximity (clusterBars) Mark the strongest clusters (highest counts) as “Ore Pocket” vertical dotted lines with labels. Interpretation: A dense cluster indicates many selected rails converge around a similar time coordinate. It is a “time confluence” hypothesis point. 4) Full settings reference (what each setting is for) 01) Gap Anchors Gap Mode FVG (3-candle) Uses a classic 3-candle fair value gap pattern: Up gap if low > high Down gap if high < low Anchors are derived from the gap boundaries. Candle Gap (open-close) Gap based on open vs close of the same bar with a tick threshold. Candle Gap (open-prev close) Gap based on open vs close with a tick threshold. Gap Threshold (ticks) Only used for the candle gap modes. Controls the minimum gap size required to register an anchor. Anchor Price Boundary: anchors at one gap boundary (more “structural edge”) Mid: anchors at midpoint of the gap (more “center of displacement”) Include Pivot Anchors (structure) When enabled, adds pivots as additional anchors to stabilize macro detection. Pivot Length Pivot sensitivity (how many bars left/right define a pivot). Larger values = fewer, more structural pivots. 02) Channel Fit + Touch Scoring Lookback Bars The historical window used to: filter which anchors are considered “recent enough” evaluate channel fitness (sampled evaluation) Larger lookback tends to favor macro shafts, but also increases computational risk (mitigated by evalBars and stride). ATR Length ATR period used for tolerance and width penalty scaling. Tolerance (ATR mult) Defines how close price must be to a rail to count as “touch” and how strict the “inside channel” containment is. Higher tolerance = easier to score high on touch/inside. Min Border Touches (keep rail) Minimum number of border touches required before a candidate is even eligible. Score: Inside Weight Weight of inside count in score. Score: Border Touch Weight Weight of border touches in score. This is a strong driver of “shaft-like” behavior. Score: Width Penalty (in ATRs) Penalizes wide channels relative to ATR. Higher penalty biases toward narrow/local shafts. 03) Performance Controls Max Stored Anchors (global) Maximum anchor points kept in memory arrays. Too low can cause loss of macro structure; too high increases candidate noise. Max Anchors / Direction (scan) Hard cap on how many anchors are used in candidate generation per direction. Critical: this strongly influences whether macro shaft can be found, because if you only keep the most recent anchors, you lose the early-structure anchor points. Eval Bars (max) Maximum historical bars actually evaluated for scoring. Even if lookbackBars is large, evaluation is capped here. Eval Stride (sample every N bars) Sampling step for evaluation. Larger stride = faster but less accurate scoring. 04) Candidate Generation Min Anchor Spacing (bars) Minimum distance between the two anchors used to define a candidate line. Prevents micro-noise lines from being evaluated. Max Anchor Spacing (bars) Maximum distance between the two anchors used to define a candidate line. If this is too low, you cannot generate truly macro candidate lines. 05) Shaft + Drift Display Main Shaft Mode Best Overall (Single Shaft): chooses one best rail among Up/Down and draws it as main. Up Only: show only the best upward rail. Down Only: show only the best downward rail. Up + Down: show both main up rail and main down rail simultaneously. Show Ascending Shaft Toggles rendering for the “up” main shaft (when mode allows it). Show Descending Shaft Toggles rendering for the “down” main shaft (when mode allows it). Drifts per Direction Number of additional top-ranked rails to draw per direction (after the best one). Extend Lines Right: extend lines to the right only. Both: extend both left and right. Fill Main Shaft Channel Fill between upper and lower borders for main shaft. Main Shaft Fill Transparency Transparency level for main fill. Show Main Shaft Centerline Draw the dashed centerline for the main shaft. 06) Ore Pocket (Intersection-Time Confluence) Show Ore Pockets (Time Confluence) Enables ore pocket discovery and rendering. Intersection Window Forward (bars) How far into the future intersections are considered. Intersection Window Backward (bars) How far into the past intersections are considered. Cluster Radius (bars) How close in time intersections must be to merge into a cluster. Min Intersections per Cluster Minimum cluster count required before a pocket is shown. Max Pocket Markers Limit how many pocket clusters are drawn. 07) Visual Controls Show Gap Anchors Displays the gap anchor dots for debugging. Show Pivot Anchors Displays pivot anchor dots for debugging. 5) How to use it (practical workflow) Step A — Confirm anchor behavior Turn on Show Gap Anchors. Choose your Gap Mode. Verify you are seeing anchors where you expect (displacement boundaries). If anchors are sparse: Reduce gap threshold (ticks) for candle-gap modes Enable pivots to inject structure Increase lookbackBars and maxAnchors so early anchors are not dropped Step B — Get stable main shaft candidate discovery Enable Include Pivot Anchors with a medium pivotLen. Use Fit (scan widths) initially. Increase Max Anchors / Direction (scan) so you’re not only using recent anchors. Increase Max Anchor Spacing so macro pairs are eligible. If you keep getting only local shafts: That is usually because the candidate pool does not include enough old anchors, or the maxSpacing prevents long-span lines. Step C — Tune scoring so the “whole-structure” shaft wins If the script picks a small local channel instead of the macro channel: Increase insideWeight relative to touchWeight (macro channels tend to contain longer structure even with fewer perfect “touches”) Reduce widthPenalty, because macro channels may need to be wider to accommodate historical volatility Increase lookbackBars and evalBars to make “whole-structure fit” matter Step D — Drifts as secondary shafts Once main shaft is good: Increase Drifts per Direction Validate that drifts represent meaningful alternate sub-shafts rather than noisy duplicates. If drifts look too similar: This is expected if many candidates differ only slightly; future refinements should diversify drift selection (see “what still needs done”). Step E — Ore pockets interpretation Ore pockets indicate time confluence of multiple rails. Use them as: “Time windows to watch” Not as deterministic price levels Tune: clusterBars (cluster tightness) minClusterSize (signal strength) 6) What still needs done (explicit backlog) The macro “main mining shaft channel” spanning the entire market structure, and Smaller shafts/drifts nested inside the macro structure. To accomplish that, the current algorithm needs additional architecture. Concretely: A) True multi-scale / hierarchical discovery (primary missing feature) Right now: one pass, one lookback, one score objective. Still Needed: Macro pass: discover a primary shaft using a very long evaluation window and anchor set. Micro pass(es): discover drifts/secondary shafts using: residuals (distance from macro centerline), or segmented time windows (regime partitions), or anchor subsets constrained to local regions. This is the single biggest reason we are not consistently getting the full-structure shaft. B) Anchor retention strategy for macro detection Right now: anchors are FIFO capped and direction scanning uses “recent anchors only.” To reliably find 10-year shafts we need: an option to store/retain representative anchors across the entire history, not only the most recent ones. Examples of necessary improvements: “Stratified anchor sampling” across time (keep some old anchors even when maxAnchors is hit) “Macro anchor bank” (separate storage for pivots or major gaps) C) Candidate generation constraints must support macro lines If we want a shaft spanning the whole structure: maxSpacing must allow it the candidate pool must contain anchors far apart in time So the algorithm needs: better selection of anchor pairs for long-span candidates (e.g., include earliest/oldest anchors + newest anchors deliberately, not accidentally) D) Drift diversification Right now drifts are “next best by score,” which often yields near-duplicates. We want: “diverse” secondary shafts: enforce minimum angular difference, enforce minimum offset difference, or penalize candidates too similar to the already-selected shaft. E) Width fitting logic for macro channels Macro channels often require: either a higher width cap, or a different penalty profile. Current width penalty is simple and can bias against macro channels. Needed: width penalty that scales by timescale or by total evaluated bars, or separate macro/micro scoring. F) Ore pocket semantics enhancement (optional but aligned) Currently pockets are time intersections only. If you want “pocket zones,” improvements could include: projecting intersection price and drawing a zone box, clustering in (time, price) space instead of only time, adding “importance” weighting based on which lines intersect (macro line intersections weighted higher). 7) Known limitations (current version) Heavy compute only runs on last bar (good for performance), but means: changes in anchors/parameters can reselect rails abruptly Candidate set is bounded; macro shaft can be missed if not in pool Drift selection can be redundant Ore pockets are time clusters, not price clusters
Pine Script® indicator
by Eyemaginative
1
SPY Quant ML + Session Filter Strategy [CocoChoco]S&P 500 Quant: Machine Learning & Mean Reversion (Session-Filtered) Overview This is a professional-grade quantitative strategy designed specifically for the S&P 500. It combines classical statistical mean reversion (Z-Score) with a modern Machine Learning filter and rigorous institutional-grade risk management. The strategy is optimized for traders who prioritize high win rates and capital preservation, specifically avoiding the "gap risk" associated with holding positions overnight. Core Methodology 1. Statistical Entry (The Z-Score Engine) The strategy identifies "oversold" conditions in a bullish context. It calculates the Z-Score of the price relative to its 20-period Mean (SMA). By default, it looks for a -1.2 Standard Deviation extension, signaling a high-probability "dip" ripe for a snap-back to the mean. 2. Trend & ML Filters To avoid "catching a falling knife," the strategy uses two layers of confirmation: Trend Filter: Only takes Long positions when the price is above the 200-period SMA, ensuring we only buy dips in a confirmed uptrend. ML Correlation Filter: A Machine Learning-inspired module that analyzes the correlation between RSI and Volatility (ATR). It only permits entries when market internal dynamics suggest a reversal is technically "healthy." 3. Institutional Risk Management This script is built for "safety-first" automation: Hard Stop Loss: Fixed at 1.5% to protect against sudden market shocks. Active Trailing: A dual-trigger trailing stop. It activates once the price touches the 20 SMA (The Mean) OR once a trade reaches a 0.50% profit threshold. This ensures near-winners are protected and large runners are captured. Intraday Circuit Breaker: Includes a Max Daily Drawdown (2%) limit. If hit, the script automatically closes losing positions and halts trading for the day, while allowing winning positions to continue. Key Features Session-Specific: Tailored for the US Trading Session (UTC/NY times). Zero Overnight Risk: Automatically flattens all positions before the market close (16:00 NY Time). Holiday Intelligence: Hard-coded logic for US Market Holidays and Early Closes (2026–2028), ensuring the bot doesn't get stuck in illiquid holiday markets. Hourly Entry Cap: Limits entries to one per hour to prevent over-concentration during a single price leg. How to Use Timeframe: I suggest you use it on the 5-minute or 1-hour timeframe for optimal results. Instrument: Designed for the S&P 500, but highly effective on SPY, IVV, and ES (Futures). Pyramiding: Designed to handle up to 3 concurrent positions, allowing the strategy to scale into a move as the Z-Score deepens. Automation Ready This script is fully compatible with webhook-based automation tools. All signals (Entry, SL, Trail, Market Close, and Daily Limit) are clearly labeled in the Alert comments for seamless execution. I haven't tasted it though. This is not financial advice. Please perform your own tests and manage your risk. Disclaimer Past performance does not guarantee future results. This script is a tool for quantitative analysis and should be used as part of a broader diversified trading plan.
Pine Script® strategy
by CocoChoco1
BTC - Sentiment (Posts weighted) LSMABTC - Sentiment (Posts Weighted) LSMA | RM Concept In the current 2026 market regime, Bitcoin has transitioned into a mature institutional asset. However, retail "Social Liquidity" remains the primary driver of local volatility and blow-off tops. This script serves as a deterministic proxy for crowd conviction, utilizing the LUNARCRUSH:BTC_SENTIMENT feed to identify when social hype has decoupled from fundamental value. Data Source: LunarCrush Integration This model utilizes the native LunarCrush data prefix. Unlike simple "mention counts," the BTC_SENTIMENT metric is a percentage-based value (0-100%) representing the "Sentiment of positive posts weighted by interactions." • Interactions vs. Volume: By weighting sentiment by interactions (likes, shares, comments), the data filters out bot-driven "spam" and focuses on what real participants are actually engaging with. • Meaning of the Value: 100% indicates that every single interaction-weighted post is positive; 0% indicates total negativity. Historically, BTC sentiment rarely drops below 60% or stays above 90% for long, creating a predictable mean-reverting corridor. Technical Architecture • The LSMA Denoising Engine Raw social data is inherently "jittery." To extract a tradable signal, we apply a Least Squares Moving Average (LSMA) with a 28-day lookback. • Mathematical Advantage: Unlike a Simple Moving Average (SMA), the LSMA calculates a linear regression line for each period to find the "best fit." This allows the indicator to track the velocity of sentiment shifts with significantly less lag, which is critical for identifying "Social Exhaustion" before a price reversal occurs. • The Social Heat Index (SHI) Calculation: To align this data with the broader Rob Maths ecosystem, we normalize the LSMA output into a standardized 0–10 score using a Linear Feature Scaling (Min-Max) formula: SHI = ((Current LSMA - 65) / 25) * 10 ; This formula treats 65% as the "Floor" (Apathy) and 90% as the "Ceiling" (Hysteria). This 0–10 scale allows for immediate comparison against other institutional risk metrics. Regime Audits & Usage • Accumulation (Blue Zone / <72.5%): Social Despair. Retail interest is at a mathematical minimum. Historically, these periods of "Social Apathy" coincide with major local bottoms as institutional "Smart Money" absorbs the lack of retail demand. • Neutral Zone (Grey): Sustainable growth. Sentiment is within the normal distribution. • Distribution (Red Zone / >82.5%): Overheated. The crowd is in a state of maximum FOMO. When the SHI exceeds 8.5/10, the risk of a "Liquidity Flush" increases significantly. Visual Scaling To ensure the curve is readable, the indicator pane is hard-locked to a 65–90 scale. This prevents the "flat line" effect often seen in 0-100 oscillators and highlights the subtle divergences that occur at cycle peaks. Disclaimer Past performance does not guarantee future results. Social metrics are alternative data points and should be used in conjunction with price action and risk management. This is a mathematical model, not financial advice. Tags Rob Maths, Rob_Maths, robmaths, Bitcoin, Sentiment, LunarCrush, Quant, LSMA, OnChain, Social Liquidity
Pine Script® indicator
by Rob_Maths
EstongA* Bot Alerts ProV1*Here’s a consolidated list of warnings and advice for traders, whether you're just starting or are experienced: ⚠️ Critical Warnings 1. You can lose all your capital – Trading is not a get-rich-quick scheme. Never trade with money you can’t afford to lose. 2. Avoid leverage until you fully understand it – Leverage amplifies both gains and losses. Many traders get wiped out by over-leveraging. 3. Beware of "guaranteed profit" systems – If it sounds too good to be true, it is. No strategy works all the time. 4. Emotional trading is a career killer – Fear, greed, and revenge trading destroy accounts. 5. Don’t follow tips or "hot leads" blindly – Do your own analysis. Many influencers are secretly unloading positions onto followers. 📚 Essential Advice Mindset & Psychology • Treat trading like a business, not gambling. Have a plan for every trade. • Develop patience – Wait for high-probability setups; don’t force trades. • Accept losses as part of the game – Even the best traders have losing streaks. The key is risk management. • Keep a trading journal – Record every trade: entry/exit reasoning, emotional state, outcome. Review weekly. Risk Management (Non-Negotiable) • Risk only 1-2% of your capital per trade – This protects you from ruin during a losing streak. • Always use stop-losses – Decide your stop-loss BEFORE entering a trade. • Never add to a losing position ("averaging down") – This is how small losses become catastrophes. • Have a risk/reward ratio of at least 1:2 – Aim for potential profit to be at least double your potential loss. Strategy & Education • Master one market/strategy at a time – Don’t jump between forex, stocks, crypto, and options simultaneously. • Backtest and forward-test any strategy before using real money. • Understand market context – Are you in a trending or ranging market? Adjust your strategy accordingly. • Continuously educate yourself – Markets evolve. Stay updated, but avoid constantly switching strategies. Practical Habits • Start with a demo account – Prove you can be consistently profitable before using real money. • When moving to real money, start small – The psychology changes with real money on the line. • Set trading hours and stick to them – Avoid overtrading and burnout. • Regularly withdraw profits – Secure gains and reinforce the reality of your earnings. 🚨 Red Flags in Yourself • Chasing losses – Trying to immediately recoup a loss leads to bigger losses. • Overconfidence after wins – Leads to taking oversized, reckless trades. • Ignoring your trading plan – If you’re making exceptions, you don’t have a plan. • Blaming the market or others – You are responsible for every trade. Take ownership. 🔍 Choosing a Broker/Platform • Regulation is crucial – Ensure they are licensed by a reputable authority (FCA, SEC, ASIC, etc.). • Understand all fees – Spreads, commissions, overnight financing, withdrawal fees. • Test customer support – You need them in a crisis. • Start with a well-known, established broker – Avoid obscure platforms with offers that seem too good. 💡 Final Wisdom • Preservation of capital is more important than making profits. Survive to trade another day. • The market will always be there – Missing an opportunity is better than taking a bad trade. • Trading is a marathon of consistency, not a sprint for mega-returns. • If you're consistently losing, stop, step back, and re-evaluate. Sometimes the best trade is no trade. Remember, approximately 90% of retail traders lose money. To be in the successful 10%, you need discipline, continuous learning, and emotional control more than a "perfect" strategy. Good luck.
Pine Script® indicator
by Palpiptaste
OrangePulse v3.0 Lite - Educational DCA StrategyThis open-source script is a simplified version of the OrangePulse algorithm, designed for educational purposes to demonstrate the power of Dollar Cost Averaging (DCA) and Mean Reversion. 📈 Strategy Logic: The script uses a combination of Bollinger Bands and RSI (Relative Strength Index) to identify potential mean reversion opportunities. - Entry: Triggered when price pushes below the lower Bollinger Band while RSI is in oversold territory. - Management: Utilizes up to 3 Safety Orders (DCA) to improve the average entry price during pullbacks. 🎯 Features: • Customizable Volume Scale and Step Scale for Safety Orders. • Visual AVG price line and TP/SL levels. • Time-window filter for backtesting. • Real-time Status Table for position monitoring. This script is shared in the spirit of open-source development on TradingView. It is intended to help traders understand how automated position building and risk management work in volatile markets. Check my profile status/bio for more information on our project. ⚠️ Disclaimer: For educational purposes only. Past performance does not guarantee future results.
Pine Script® strategy
by OrangePulse