Mulakan

Regressions

Shiori TFGI Lite Technical Fear and Greed Index (Open Source)Shiori’s TFGI Lite Technical Fear & Greed Index (Open Source) --- English — Official Description Shiori’s TFGI Lite is an open-source Technical Fear & Greed Index designed to help traders and investors understand market emotion, not predict price. Instead of generating buy or sell signals, this indicator focuses on answering a calmer, more important question: > Is the market emotionally stretched away from its own historical balance? TFGI Lite combines three well-known technical dimensions — volatility, price deviation, and momentum — and normalizes them into a single, intuitive 0–100 sentiment scale. What This Indicator Is * A market context tool, not a trading signal * A way to observe emotional extremes and misalignment * Designed for any asset, any timeframe * Fully open source, transparent and adjustable Core Components * Fear Factor: Short-term vs long-term ATR ratio with logarithmic compression * Greed Factor: Price Z-score with tanh-based normalization * Momentum Factor: Classic RSI as emotional momentum These factors are blended and gently smoothed to form the current sentiment level. Historical Baseline & Deviation TFGI Lite introduces a historical baseline concept: * The baseline represents the market’s own emotional equilibrium * Deviation measures how far current sentiment has drifted from that equilibrium This allows the indicator to highlight conditions such as: * 🔥 Overheated: High sentiment + strong positive deviation * 💎 Undervalued: Low sentiment + strong negative deviation * ⚠️ Misaligned: Emotionally extreme, but inconsistent with historical behavior How to Use (Lite Philosophy) * Use TFGI Lite as a background compass, not a trigger * Combine it with price structure, risk management, and your own strategy * Extreme readings suggest emotional tension, not immediate reversal > Think of TFGI Lite as market weather — it tells you the climate, not when to open or close the door. About Parameters & Customization All parameters in TFGI Lite are fully adjustable. Markets have different personalities — volatility, sentiment range, and emotional extremes vary by asset and timeframe. You are encouraged to: * Adjust fear/greed thresholds based on the asset you trade * Tune smoothing and baseline lengths to match your timeframe * Treat sentiment levels as relative, not universal absolutes There is no single “correct” setting — TFGI Lite is designed to adapt to your market, not force the market into a fixed model. Important Notes * This is a technical sentiment indicator, not financial advice * No future performance is implied * Designed to reduce emotional decision-making, not replace it --- 🇹🇼 繁體中文 — 指標說明 Shiori’s TFGI Lite（技術型恐懼與貪婪指數） 是一款開源的市場情緒指標，目的不是預測價格，而是幫助你理解市場當下的「情緒狀態」。 與其問「現在該不該買或賣」，TFGI Lite 更關心的是： > 市場情緒是否已經偏離了它自己的歷史平衡？ 本指標整合三個常見但關鍵的技術面向，並統一轉換為 0–100 的情緒刻度，讓市場狀態一眼可讀。 這個指標是什麼 * 市場情緒與狀態觀察工具（非買賣訊號） * 用來辨識情緒極端與錯位狀態 * 適用於任何商品與任何週期 * 完全開源，可學習、可調整 核心構成 * 恐懼因子：短期 / 長期 ATR 比例（對數壓縮） * 貪婪因子：價格 Z-Score（tanh 正規化） * 動能因子：RSI 作為情緒動量 歷史基準與偏離 TFGI Lite 引入「歷史情緒基準」的概念： * 基準代表市場長期的情緒平衡 * 偏離值顯示當前情緒與自身歷史的距離 因此可以辨識： * 🔥 過熱（高情緒 + 正向偏離） * 💎 低估（低情緒 + 負向偏離） * ⚠️ 錯位（情緒極端，但不符合歷史行為） 使用建議（Lite 精神） * 將 TFGI Lite 作為「背景雷達」，而非進出場依據 * 搭配價格結構、風險控管與個人策略 * 情緒極端不等於立刻反轉 > 你可以把它想像成市場的天氣預報，而不是交易指令。 參數調整與個人化說明 本指標中的所有參數皆可調整。不同市場、不同商品，其波動特性與情緒區間並不相同。 建議你： * 依標的特性自行調整恐懼 / 貪婪門檻 * 依交易週期調整平滑與基準長度 * 將情緒數值視為「相對狀態」，而非固定答案 TFGI Lite 的設計初衷，是讓你定義市場，而不是被單一參數綁住。 溫馨提示 如果你在調整指標參數時遇到不熟悉的項目，請點擊參數旁邊的 「!」圖示，每個設定都有清楚的說明。 本指標設計為可慢慢探索，請依自己的節奏理解市場狀態。 --- 🇯🇵 日本語 — インジケーター説明 Shiori’s TFGI Lite は、価格を予測するための指標ではなく、 市場の「感情状態」を可視化するためのオープンソース指標です。 この指標が問いかけるのは、 > 現在の市場感情は、過去のバランスからどれだけ乖離しているのか？ という一点です。 特徴 * 売買シグナルではありません * 市場心理の極端さやズレを観察するためのツールです * すべての銘柄・時間軸に対応 * 学習・調整可能なオープンソース 構成要素 * 恐怖要素：ATR 比率（対数圧縮） * 強欲要素：価格 Z スコア（tanh 正規化） * モメンタム：RSI ベースラインと乖離 市場自身の感情的な基準点と、 現在の感情との距離を測定します。 過熱・割安・感情のズレを視覚的に把握できます。 パラメータ調整について TFGI Lite のすべてのパラメータは調整可能です。市場ごとにボラティリティや感情の振れ幅は異なります。 * 恐怖・強欲の閾値は銘柄に応じて調整してください * 時間軸に合わせて平滑化やベースライン期間を変更できます * 数値は絶対値ではなく、相対的な感情状態として捉えてください この指標は、市場に合わせて柔軟に使うことを前提に設計されています。 フレンドリーヒント 入力項目で分からない設定がある場合は、横に表示されている 「!」アイコン をクリックしてください。各パラメータには分かりやすい説明が用意されています。 このインジケーターは、落ち着いて市場の状態を理解するためのものです。 --- 🇰🇷 한국어 — 지표 설명 Shiori’s TFGI Lite는 매수·매도 신호를 제공하는 지표가 아니라, 시장 감정의 상태를 이해하기 위한 기술적 심리 지표입니다. 이 지표의 핵심 질문은 다음과 같습니다. > 현재 시장 감정은 과거의 균형 상태에서 얼마나 벗어나 있는가? 특징 * 거래 신호 아님 * 시장 심리의 과열·저평가·불일치를 관찰 * 모든 자산, 모든 타임프레임 지원 * 오픈소스 기반 구성 요소 * 공포 요인: ATR 비율 (로그 압축) * 탐욕 요인: Z-Score (tanh 정규화) * 모멘텀: RSI 활용 방법 TFGI Lite는 배경 지표로 사용하세요. 가격 구조와 리스크 관리와 함께 사용할 때 가장 효과적입니다. 파라미터 조정 안내 TFGI Lite의 모든 설정 값은 사용자가 직접 조정할 수 있습니다. 자산마다 변동성과 감정 범위는 서로 다릅니다. * 공포 / 탐욕 기준값은 종목 특성에 맞게 조정하세요 * 타임프레임에 따라 스무딩 및 기준 기간을 변경할 수 있습니다 * 감정 수치는 절대적인 값이 아닌 상대적 상태로 해석하세요 이 지표는 하나의 정답을 강요하지 않고, 시장에 맞춰 적응하도록 설계되었습니다. 친절한 안내 설정 값이 익숙하지 않다면, 항목 옆에 있는 "!" 아이콘을 클릭해 보세요. 각 입력값마다 설명이 제공됩니다. 이 지표는 천천히 시장의 맥락을 이해하도록 설계되었습니다. --- Educational purpose only. Not financial advice. --- #FearAndGreed #MarketSentiment #TradingPsychology #TechnicalAnalysis #OpenSourceIndicator #Volatility #RSI #ATR #ZScore #MultiAsset #TradingView #Shiori
Penunjuk Pine Script®
oleh eddy121384
1
ARDO - Adaptive Regression Deviation Oscillator (v2.4.6)ARDO – Adaptive Regression Deviation Oscillator (v2.4.6) ARDO (Adaptive Regression Deviation Oscillator) quantifies deviation of price structure from a regression-based equilibrium baseline using adaptive moving-average spreads. It combines percentile-normalized distance, linear-regression slope, and dynamic gradient scaling to reveal trend extension, exhaustion, and regime shifts—offering a structural view of trend integrity and mean-reversion timing beyond traditional momentum oscillators. It is designed to help you answer two questions: Where are we in the regime? (extended, neutral, or reversal-prone) Is this a “trade” environment or a “stand aside” environment? (Gate PASS vs Gate BLOCK / drift) ARDO is best used as a context + timing framework , not a standalone entry/exit system. What you see in the ARDO pane 1) Spread A (% vs baseline) Primary “timing” spread (default: stepline). Spread A is colored by a 4-state maColor model: GREEN : above baseline and strengthening ORANGE : above baseline but weakening RED : below baseline and weakening GRAY : below baseline but improving 2) Spread B (% vs baseline) Secondary “context” spread (default: columns). Same 4-state color model as above, often used to confirm or filter Spread A behavior. 3) LinReg (slope-gradient) A LinReg line fit to a selected source (Spread A / Spread B / Spread A+B). ARDO applies a slope-magnitude gradient (opacity/intensity) to visualize regime: Stronger slope magnitude = stronger directional regime Fading / low slope magnitude = drift / dead-zone (lower edge, choppy conditions, or end-of-move) 4) Tier zones (Q0–Q2, H2–H4) ARDO classifies LinReg values into percentile tiers (extremes and mid-tiers). These tiers can be rendered as: Background regions, or Zero-line marker circles (“MK …” plots) Important: Background colors do not export . The “MK Q0 … MK H4” series are emitted so you can reconstruct tier membership in CSV/backtests. 5) Gate PASS / Gate BLOCK A compact “permission layer” that can require: Spread A > LinReg EMA Fast > EMA Slow Minimum Spread A threshold Minimum absolute LinReg slope Use Gate PASS to focus on higher-quality conditions; use Gate BLOCK as a “do nothing / reduce size” warning. Key settings (what they change) Tier Mode Standard: symmetric cut structure (general purpose) Asymmetric: separate tuning for highs vs lows (often better when upside and downside behavior are not symmetric) Tier Population All Bars (LinReg): tiers represent the full LinReg distribution Pivots Only: tiers are computed from pivot events only (can tighten “extreme” definition and change how frequently zones appear) Render Mode Background: easiest to read visually Zero-line Markers: best for export/backtesting workflows (MK series) Gating options Turn on/off each rule independently; adjust thresholds to match symbol volatility and timeframe. Color overrides Optional per-state color customization for Spread A, Spread B, and LinReg (4-state). Alerts included (v2.4.6) ARDO exposes named alerts you can use for automation or review, including: Gradient / regime alerts (HIGH vs LOW slope-magnitude regimes; regime shift transitions) Color-state changes (Spread B → GREEN/ORANGE/RED/GRAY; LinReg state changes) Tier entry alert s (LinReg entering key tiers such as Q0/Q1/H3/H4) Structural primitives (Bullish A > B, Bearish A < B, Gate PASS/BLOCK, crosses of 0, etc.) How to use (practical workflow) Anchor timeframe (65m or Daily): identify regime (tiers + gradient) and whether you should be aggressive or defensive. Execution timeframe (5m/1m): time entries using Spread A/B structure and Gate PASS, aligned with the anchor regime. Avoid forcing trades in drift: fading gradient + mid/low-edge tiers often marks “dead-zone” conditions. Notes / limitations ARDO is a context engine: it describes regime and location, not guaranteed direction. Tier thresholds are distribution-based and will vary by window/timeframe. Always apply your own risk management; this script is not financial advice.
Penunjuk Pine Script®
oleh therichfuller
STOXWAY Financial Chaos Index Opt.Beta STOXWAY – Financial Chaos Index(Opt)Beta A Complete Market Chaos & Trend Stability Scanner for Option Traders** STOXWAY – Financial Chaos Index(Opt)Beta is a uniquely engineered indicator designed for traders who want to understand when the market is stable, when it is turning chaotic, and when option trades become high-risk or high-probability. Unlike traditional volatility indicators that rely only on ATR or VIX-style readings, FCI combines four independent market forces into a single score: 1️⃣ Volatility Pulse (ATR Stress) Measures sudden bursts in price movement that usually shake option buyers & sellers. 2️⃣ Trend Gap Displacement Checks how fast EMAs are separating, revealing trend strength or trend exhaustion. 3️⃣ RSI Momentum Shift Quantifies how far momentum has moved from equilibrium. 4️⃣ Liquidity Stress (Range vs Average Range) Identifies if volatility is coming from liquidity expansion or from imbalance. These four components are blended into a 0–100 Financial Chaos Index (FCI) that updates every candle. 🎯 Why This Indicator Is Unique STOXWAY – Financial Chaos Index(Opt)Beta is not a duplication of any existing TradingView script. It uses: ✔ Custom volatility pulse formula ✔ Custom EMA-gap trend displacement model ✔ Custom momentum scoring ✔ Custom liquidity stress algorithm ✔ Custom chaos zones (40 / 60 / 75 / 90) ✔ A smooth background that changes with chaos intensity ✔ A built-in Safe/Aggressive entry logic No other indicator on TradingView uses this exact method or combination, which makes its behaviour truly original. 🚀 What It Helps Traders See Instantly 🟢 Low Chaos (0–40) Market is stable → Option trades behave normally → Good for trend continuation. 🟡 Moderate Chaos (40–60) Market is heating up → Avoid over-leveraging. 🟠 High Chaos (60–75) Trend may reverse or accelerate suddenly → Use caution. 🔴 Extreme Chaos (75–90+) Highly unstable conditions → Great for scalpers but dangerous for positional traders. The background color shifts smoothly across the chart, making chaos levels immediately visible without reading numbers. 📘 Integrated Safe & Aggressive Entry Model The indicator includes optional signal logic: SAFE ENTRIES (Low Chaos Phase) ✔ FCI < 60 ✔ RSI > 65 for buys ✔ SMA crossover confirmation These highlight cleaner, high-probability moves. AGGRESSIVE ENTRIES (High Chaos Phase) ✔ FCI > 60 ✔ Suitable only for quick scalps ✔ Useful when momentum bursts occur in options 🧠 Why Traders Must Use This ✔ Helps avoid trades during dangerous volatility spikes ✔ Helps identify when market structure becomes fragile ✔ Helps options traders choose between “safe” and “aggressive” setups ✔ Helps avoid SL hits caused by sudden chaos ✔ Helps time exits when instability rises ✔ Helps find trend continuation phases with low noise Most traders lose because they cannot see hidden instability. This indicator exposes that instability clearly, candle by candle. ⚠️ Disclaimer This tool is designed for market analysis and educational purposes. It does not guarantee accuracy, profits, or future performance. All trades should be confirmed with risk management and personal judgment.
Penunjuk Pine Script®
oleh stoxway
TFGI Lite: Technical Fear & Greed Dashboard (All-Assets)📊 TFGI Lite: Technical Fear & Greed Dashboard (All-Assets) Don't guess the sentiment. Measure it. 不要猜測情緒，去測量它。 🇹🇼 繁體中文：市場情緒的導航儀 什麼是 TFGI Lite？ 這是一個簡潔的「市場氣象儀表板」，直接顯示在您的 K 線圖上。它幫助您判斷現在市場是處於「過度恐懼（適合貪婪）」還是「過度貪婪（適合謹慎）」的狀態。適用於股票、加密貨幣、外匯與期貨。 數字代表什麼意義？ 分數範圍為 0 到 100： 0 - 25 (極度恐懼 / 綠色區域)： 市場陷入恐慌，價格可能被低估。這通常是尋找買點的機會（別人恐懼我貪婪）。 75 - 100 (極度貪婪 / 紅色區域)： 市場過熱，追高風險極大。這通常是考慮獲利了結或警惕回調的時刻。 25 - 75 (中性震盪)： 市場處於正常波動範圍，順勢操作即可。 儀表板上的三個關鍵數據： Local TFGI (當前商品)：您現在看的這張圖表（例如比特幣或台積電）的情緒分數。 Global TFGI (全球宏觀)：全球資金的流向與風險偏好（綜合了美股、波動率 VIX、美元與債市）。這就像是「大盤天氣」。如果全球都在下雨（恐慌），您的股票也很難獨善其身。 Spread (情緒溫差)： 如果 Local 分數遠高於 Global，代表這個商品漲過頭了，要注意風險。 如果 Local 分數遠低於 Global，代表這個商品被錯殺了，可能是機會。 🇺🇸 English: Navigate Market Sentiment Simply What is TFGI Lite? A clean, professional "Weather Dashboard" for your chart. It quantifies market psychology, helping you decide when to be contrarian. It works on any asset class (Stocks, Crypto, Forex). How to Read the Numbers (0-100 Score) 0 - 25 (Extreme Fear / Green Zone): Investors are panicking. The asset may be oversold. Historically, this is often a buying opportunity. 75 - 100 (Extreme Greed / Red Zone): The market is overheated and FOMO is high. The risk of a correction is increasing. It might be time to take profits. 25 - 75 (Neutral): Normal market fluctuations. Key Features on the Dashboard: Local TFGI: The sentiment score of the specific asset you are watching right now. Global TFGI: The sentiment of the entire global market (Aggregating SPY, VIX, DXY, and Bonds). Think of this as the "Macro Tide". It's hard to swim against the tide. Spread: The difference between the Asset and the Global market. Positive Spread: This asset is hotter than the global market (Potential Overvaluation). Negative Spread: This asset is weaker than the global market (Potential Undervaluation). 🇯 日本語：相場の「過熱感」を一目で判断 TFGI Liteとは？ チャート上に表示されるシンプルな「センチメント（市場心理）ダッシュボード」です。市場が「悲観（買い時）」にあるのか、「楽観（売り時）」にあるのかを客観的な数値で示します。株、仮想通貨、FXなど、あらゆる資産に対応しています。 スコアの見方（0〜100） 0 - 25 (極度の恐怖 / 緑エリア): 市場はパニック状態です。売られすぎの可能性があり、逆張りの買いチャンスとなることが多いゾーンです。 75 - 100 (極度の強欲 / 赤エリア): 市場は過熱しており、イケイケの状態です。暴落のリスクが高まっているため、利益確定を検討する警戒ゾーンです。 25 - 75 (中立): 通常の変動範囲内です。 ダッシュボードの3つの重要指標: Local TFGI (個別): 現在表示している銘柄のセンチメントスコアです。 Global TFGI (全体): 世界市場全体のムード（米国株、VIX指数、ドル、債券を総合分析）。「地合い」を確認するために使います。 Spread (乖離): 個別銘柄と世界市場の温度差。この数値が大きい場合、その銘柄だけが異常に買われすぎている可能性があります。 🇰🇷 한국어: 시장의 공포와 탐욕을 한눈에 TFGI Lite란 무엇인가요? 차트 위에 직접 표시되는 깔끔한 "시장 심리 계기판"입니다. 현재 시장이 '과도한 공포(저점 매수 기회)'인지 '과도한 탐욕(고점 매도 주의)'인지 판단하는 데 도움을 줍니다. 주식, 코인, 외환 등 모든 자산에 적용 가능합니다. 숫자가 의미하는 것 (0~100점) 0 - 25 (극심한 공포 / 초록색 구간): 투자자들이 패닉에 빠져 투매가 나옵니다. 역사적으로 이는 저가 매수(Buy the dip)의 기회일 가능성이 높습니다. 75 - 100 (극심한 탐욕 / 빨간색 구간): 시장이 과열되었습니다. 추격 매수는 위험하며, 이익 실현을 고려하거나 조정을 대비해야 할 때입니다. 25 - 75 (중립): 일반적인 시장 변동 구간입니다. 대시보드의 핵심 데이터: Local TFGI (개별 종목): 지금 보고 계신 차트(코인/주식)의 자체적인 심리 점수입니다。 Global TFGI (글로벌 매크로): 전 세계 자금의 흐름과 위험 선호도(미국 증시, VIX, 달러, 채권 종합). 시장 전체의 "날씨"를 알려줍니다。 Spread (괴리율): 개별 종목과 글로벌 시장 간의 온도 차이. 개별 종목 점수가 글로벌보다 훨씬 높다면, 해당 종목이 과매수되었을 수 있습니다。
Penunjuk Pine Script®
oleh eddy121384
Momentum Marks - Buy and Sell IndicatorsIndicator Overview This tool is a multi‑factor entry signal system designed to highlight potential BUY and SHORT opportunities directly on the chart with hard‑anchored labels. It combines trend, momentum, volatility, and volume conditions to reduce noise and provide more reliable trade signals. Core Components - EMA Trend Filter - Uses a fast EMA (9) and a slow EMA (21) to determine short‑term vs. medium‑term trend direction. - Signals only trigger when price aligns with the EMA relationship (e.g., fast above slow for shorts, fast below slow for buys). - RSI Extremes - RSI thresholds (default 65/35) ensure signals occur only when momentum is stretched into overbought or oversold zones. - Helps avoid false triggers during neutral conditions. - Linear Regression Channel - A regression line with ±2 standard deviation bands defines dynamic support and resistance. - Signals require price to be near the top (for shorts) or bottom (for buys) of the channel, adding a structural filter. - TTM Squeeze Histogram - Measures momentum shifts by comparing price to its EMA. - Signals require histogram confirmation: weakening momentum for shorts, strengthening momentum for buys. - Volume Confirmation - Volume must fade for shorts or surge for buys relative to a 20‑period average. - Ensures signals align with participation strength. Visual Output - Red “SHORT” label above bars when all short conditions align. - Green “BUY” label below bars when all buy conditions align. - Optional plotshape arrows (triangles) as backup markers. - Linear regression channel shaded between upper and lower bands. - EMA lines plotted for trend context. Key Features - Hard‑anchored labels: Signals are locked to confirmed bars, preventing repainting or shifting. - Multi‑layer confirmation: Requires trend, momentum, volume, and structure to align before firing. - Customizable inputs: Users can adjust EMA lengths, RSI thresholds, regression length, and squeeze parameters.
Penunjuk Pine Script®
oleh alexh1166
1
80% EDGE Rule - TPO Based═════════════════════════════════════════════════════════════ 80% EDGE RULE - TPO BASED ═════════════════════════════════════════════════════════════ █ OVERVIEW The 80% Edge Rule is a high-probability Market Profile concept that identifies when price is likely to traverse the prior session's Value Area. This indicator automates the detection, confirmation, and tracking of 80% EDGE Rule setups using true TPO (Time Price Opportunity) calculations—not volume profile. When price opens outside the previous day's Value Area and then re-enters and is "accepted" back inside, there is an 80% statistical probability that price will travel to the opposite side of the Value Area. This indicator does all the heavy lifting: calculating the prior session's Value Area, detecting valid setups, confirming acceptance, and tracking progress toward the target. █ THE 80% EDGE RULE EXPLAINED The 80% Edge Rule is based on Market Profile theory developed by J. Peter Steidlmayer at the Chicago Board of Trade. The rule states: ❶ If price OPENS OUTSIDE the prior day's Value Area... ❷ And then ENTERS and is ACCEPTED back into the Value Area... ❸ There is an 80% chance price will rotate to the OTHER SIDE of the Value Area. "Acceptance" is defined as price spending TWO OR MORE TPO periods (typically 30-minute blocks) inside the Value Area. This indicates that the market has accepted these prices as fair value, and the auction process will likely continue through to the opposite boundary. BULLISH SETUP: Price opens BELOW the prior VAL → Enters and is accepted → Target is VAH BEARISH SETUP: Price opens ABOVE the prior VAH → Enters and is accepted → Target is VAL █ HOW THIS INDICATOR WORKS This indicator performs several automated functions: 1. TPO VALUE AREA CALCULATION • Analyzes the prior RTH (Regular Trading Hours) session • Builds a true TPO distribution using 30-minute time blocks • Each price level receives +1 TPO for each period it was touched • Calculates POC (Point of Control) as the price with highest TPO count • Expands from POC using the CME/CBOT standard "two-price" method until 70% of TPOs are captured • This defines VAH (Value Area High) and VAL (Value Area Low) 2. SETUP DETECTION • Monitors the RTH open (default 9:30 AM ET) • Detects if price opened outside the prior Value Area • Determines setup direction (Bullish or Bearish) 3. ACCEPTANCE MONITORING • Tracks TPO blocks where price remains inside the Value Area • Confirms setup when required number of blocks is reached (default: 2) • Resets count if price exits VA before confirmation 4. TARGET & INVALIDATION TRACKING • Monitors for target completion (opposite VA boundary) • Monitors for invalidation (price moves beyond entry VA boundary + buffer) • Visual feedback on outcome █ VISUAL ELEMENTS PRIOR VALUE AREA LINES (Dashed) • RED DASHED LINE: Prior Day VAH (Value Area High) • GREEN DASHED LINE: Prior Day VAL (Value Area Low) • PURPLE DOTTED LINE: Prior Day POC (Point of Control) TRADE LINES (Solid) • YELLOW LINE: Entry price (where setup was confirmed) • CYAN LINE: Target price (opposite VA boundary) • GREEN LINE: Entry line turns green when target is hit • GRAY LINES: Both lines turn gray if setup is invalidated STATUS LABEL • Floating label showing current setup state • ORANGE "WATCHING": Setup detected, monitoring for acceptance • YELLOW "CONFIRMED": Setup confirmed, tracking toward target • GREEN "TARGET HIT ✓": Target successfully reached • RED "INVALIDATED ✗": Setup failed, price moved against DASHBOARD (Top Right Corner) • Prior VAH: Yesterday's Value Area High • Prior VAL: Yesterday's Value Area Low • Prior POC: Yesterday's Point of Control • Open Price: Today's RTH opening price • Direction: BULLISH ↑ or BEARISH ↓ • Status: Current setup state █ CONFIGURABLE SETTINGS ┌──────────────────────────────────────────────────────────── │ TPO SETTINGS ├──────────────────────────────────────────────────────────── │ Tick Size (Default: 0.25) │ • Price increment for TPO calculations │ • ES/MES: 0.25 │ • NQ/MNQ: 0.25 │ • YM/MYM: 1.0 │ • RTY: 0.1 │ • CL/MCL: 0.01 │ • GC/MGC: 0.1 │ │ Value Area % (Default: 70) │ • Percentage of TPOs to include in Value Area │ • Standard is 70% (one standard deviation) │ • Can adjust 50-90% based on preference │ │ TPO Block Duration (Default: 30 minutes) │ • Length of each TPO period │ • Standard Market Profile uses 30-minute periods │ • Adjust if using non-standard TPO settings └──────────────────────────────────────────────────────────── ┌──────────────────────────────────────────────────────────── │ 80% EDGE RULE SETTINGS ├──────────────────────────────────────────────────────────── │ TPO Blocks Required for Acceptance (Default: 2) │ • Number of 30-min periods price must stay inside VA │ • Standard rule requires 2 periods for acceptance │ • More conservative: Increase to 3 │ • More aggressive: Reduce to 1 (not recommended) │ │ Invalidation Distance (Default: 10 points) │ • Buffer beyond VA boundary before setup is invalidated │ • Bullish: Invalidates if LOW goes below VAL minus this distance │ • Bearish: Invalidates if HIGH goes above VAH plus this distance │ • Adjust based on product volatility and your risk tolerance │ │ Fade Delay (Default: 5 minutes) │ • How long entry/target lines stay visible after outcome │ • Lines and floating label disappear after this delay │ • Dashboard retains the outcome status until next session └──────────────────────────────────────────────────────────── ┌──────────────────────────────────────────────────────────── │ SESSION SETTINGS ├──────────────────────────────────────────────────────────── │ RTH Session (Default: 0930-1600) │ • Regular Trading Hours window │ • This determines which bars are used for TPO calculation │ • Also determines when RTH "open" is detected │ │ PRODUCT-SPECIFIC RTH SESSIONS: │ • Equity Index Futures (ES, NQ, YM, RTY): 0930-1600 │ • Crude Oil (CL): 0900-1430 (pit session) │ • Gold (GC): 0820-1330 (pit session) │ • Treasury Bonds/Notes: 0720-1400 │ • Forex Futures: Varies by product │ │ Timezone (Default: America/New_York) │ • Timezone for session calculations │ • Options: New York, Chicago, Los Angeles, UTC │ • Use exchange timezone for accurate session detection └──────────────────────────────────────────────────────────── ┌──────────────────────────────────────────────────────────── │ VISUAL SETTINGS ├──────────────────────────────────────────────────────────── │ Show Prior VA Lines: Toggle VAH/VAL/POC lines on/off │ Show Entry/Target Lines: Toggle trade-related lines on/off │ VAH Color: Color for Value Area High line │ VAL Color: Color for Value Area Low line │ POC Color: Color for Point of Control line │ Entry Line Color: Color for entry price line │ Target Line Color: Color for target price line │ Target Hit Color: Color when target is reached (default: green) │ Line Width: Thickness of all lines (1-5) └──────────────────────────────────────────────────────────── ┌──────────────────────────────────────────────────────────── │ DEBUG SETTINGS ├──────────────────────────────────────────────────────────── │ Show Debug Info: Displays additional diagnostic information │ • Session High/Low of prior day │ • Current RTH status │ • Current TPO block number │ • Outcome timestamp │ • Useful for troubleshooting or verifying calculations └──────────────────────────────────────────────────────────── █ ALERTS This indicator includes three configurable alerts: ① SETUP CONFIRMED • Triggers when acceptance criteria is met • Includes entry price and target price in alert message ② TARGET HIT • Triggers when price reaches the opposite VA boundary • Confirms successful completion of the 80% Rule setup ③ INVALIDATED • Triggers when price moves beyond the invalidation threshold • Signals that the setup has failed To enable alerts: 1. Ensure "Enable Alerts" is checked in indicator settings 2. Right-click on the indicator → "Add Alert" 3. Select the condition you want to be alerted on 4. Configure notification method (popup, email, webhook, etc.) █ RECOMMENDED USAGE TIMEFRAME: • Best used on 5-minute, 15-minute, or 30-minute charts • The chart timeframe should divide evenly into 30 minutes • Ensure sufficient historical bars are loaded for prior session calculation BEST PRACTICES: • Wait for full confirmation (2 TPO blocks inside VA) before considering entry • Use the target line as your profit objective • Consider the invalidation level for stop-loss placement • Monitor the dashboard for real-time setup status • Combine with other confluence factors (order flow, support/resistance, etc.) IMPORTANT NOTES: • This indicator calculates TRUE TPO-based Value Area, not volume profile • Prior day VA is recalculated at each new session • The 80% Rule is a statistical tendency, not a guarantee • Always use proper risk management █ ADJUSTING FOR DIFFERENT PRODUCTS This indicator defaults to Equity Index Futures (ES, NQ, etc.) with: • RTH Session: 0930-1600 • Timezone: America/New_York • Tick Size: 0.25 FOR OTHER PRODUCTS, ADJUST: CRUDE OIL (CL/MCL): • RTH Session: 0900-1430 • Tick Size: 0.01 GOLD (GC/MGC): • RTH Session: 0820-1330 • Tick Size: 0.10 TREASURY FUTURES (ZB, ZN): • RTH Session: 0720-1400 • Tick Size: 0.03125 (ZB) or 0.015625 (ZN) E-MINI DOW (YM/MYM): • RTH Session: 0930-1600 • Tick Size: 1.0 RUSSELL 2000 (RTY): • RTH Session: 0930-1600 • Tick Size: 0.10 Always verify the RTH session times and tick sizes for your specific product and exchange. █ DISCLAIMER This indicator is provided for educational and informational purposes only. It is not financial advice and should not be construed as a recommendation to buy or sell any financial instrument. Trading futures and other leveraged products involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. The 80% Edge Rule is a statistical observation based on Market Profile theory and does not guarantee any specific outcome. Always conduct your own analysis and use proper risk management.
Penunjuk Pine Script®
oleh RyanBaileyEdge
Vietnamese Stock: Discount Linear Regression Liquidity GrabThe Discount Linear Regression Liquidity Grab is a sophisticated technical analysis tool that combines statistical trend analysis with Premium/Discount Zone and Price Action logic. Unlike standard Linear Regression Channels that repaint or stretch indefinitely, this indicator is dynamic: it automatically detects volatility breakouts to "reset" the channel, creating distinct market "Sections." This tool is designed to help traders identify trend exhaustion, fair value gaps (FVGs), and high-probability reversal or continuation zones using two distinct built-in strategies. Key Features 1. Dynamic Channel Resets The core engine calculates a Linear Regression Channel based on a Pearson R coefficient and Deviation multipliers. - How it works: When price breaks out of the Upper or Lower Deviation bands, the script recognizes a shift in momentum. It "locks" the previous channel and begins calculating a new one from the breakout point. - Benefit: This creates a historical map of market structure, showing you exactly where previous trends began and ended. 2. Smart Money Concepts (SMC) Integration For every completed section (channel), the indicator automatically highlights: Highest High & Lowest Low Boxes: Identifies the structural range of the previous move. - Gaps & FVGs: Automatically draws boxes for Fair Value Gaps and Price Gaps within the channel, acting as potential magnets for price. 3. The Discount Zone (New Feature) The indicator projects a Discount Area (Red Box) from the previous section's midline down to its lowest low. - Logic: This box represents the "Discount" pricing relative to the previous move. - Behavior: The box extends to the right until price successfully "grabs liquidity" (closes below the midline/red line). Once the grab occurs, the box stops extending, marking that the liquidity event is complete. Built-In Strategies This indicator includes two automated strategy signals based on the interaction between current price and historical sections. Strategy 1: Breakout & Retest (Trend Continuation) This strategy looks for a classic resistance-turned-support setup. - Breakout: Price closes above the Highest High of a previous section (Triangle Up). - Retest: Price pulls back and closes at or below that breakout level (Triangle Down). - Confirmation: Price breaks above the high of the initial breakout candle (Green Background). Strategy 2: Midline Reclaim (Mean Reversion / Discount Buy) This strategy focuses on buying from the "Discount" zone. - Liquidity Grab: Price drops below the Midline (Red Line) of a previous section, entering the Discount Zone. - Reclaim: Price closes back above the Midline, signaling that the dip was bought up. Signal: A Diamond shape and Teal Background appear. How to Use - Trend Trading: Use the Dynamic Channels to visualize the current slope. If the channel is angling up, look for long setups. - Confluence: Use the Discount Zones and FVG boxes as areas of interest. If price enters a Red Discount Box and forms a reversal pattern, it is a high-probability entry. - Stop Loss Placement: The Lowest Low boxes of previous sections serve as excellent invalidation points for long positions. Alerts The indicator comes with pre-configured alerts for: - Strategy 1 Confirmation. - Strategy 2 Midline Reclaim. - New Channel Formation (Trend Reset). - Liquidity Grab Events.
Penunjuk Pine Script®
oleh doqkhanh
BTC Spot vs Perpetual CVD Divergence + Delta Confirm + Band FillThis indicator detects real market turning points by comparing Spot vs Perpetual CVD flows to identify forced positioning changes, leverage clean-ups, and true spot absorption. It tracks normalized CVD for both Spot and Perps, calculates the divergence between them, and applies a dynamic volatility-based threshold to filter noise. Signals only trigger at confirmed pivot points, ensuring accuracy over early false reversals. An optional Delta confirmation layer further validates setups by requiring aggressive market flow in the direction of the pivot reversal. This tool is not designed for blind entries — it highlights high-probability reversal zones. Best used in combination with VWAP, HTF structure, OI, and funding rate analysis to time optimal entries via pullbacks and momentum confirmation. ✅ Ideal for: • Identifying local tops & bottoms • Tracking spot vs leverage dominance • Trading mean reversion and squeeze setups • Flow-based scalping ❌ Not intended for: • Chasing breakouts • Standalone entry signals without price structure
Penunjuk Pine Script®
oleh PerpGuardiola
Trend Flip Exhaustion SignalsThis Pine Script is designed to generate buy and short trading signals based on a combination of technical indicators. It calculates fast and slow EMAs, RSI, a linear regression channel, and a simplified TTM squeeze histogram to measure momentum. - Short signals trigger when price is above both EMAs, near the upper regression channel, momentum is weakening, volume is fading, and RSI is overbought. - Buy signals trigger when price is below both EMAs, near the lower regression channel, momentum is strengthening, volume is surging, and RSI is oversold. - Signals are displayed as labels anchored to price bars (with optional plotshape arrows for backup). - The script also plots the EMAs and regression channel for visual context. In short - it’s a trend‑following entry tool that highlights potential exhaustion points for shorts and potential reversals for buys, with clear on‑chart markers to guide decision‑making.
Penunjuk Pine Script®
oleh alexh1166
Physics of PricePhysics of Price is a non-repainting kinematic reversal and volatility overlay. It models price as a physical object with position, velocity, and acceleration, then builds adaptive bands and a short-term predictive “ghost cone” to highlight where reversals are statistically more likely. CONCEPT Instead of using only moving averages, the core engine tracks a smoothed price (position), trend speed (velocity), and change in trend speed (acceleration). Standard deviation of the model error defines probabilistic bands around this kinematic centerline. When price stretches too far away and snaps back, the move is treated as a potential exhaustion event. CORE COMPONENTS – Kinematic centerline (Alpha–Beta–Gamma style filter) that bends with trend instead of lagging like a simple MA. – Inner and outer bands based on the standard deviation of residuals between price and the kinematic model. – Regime filter using R² and band width to avoid signals in chaotic or ultra-wide regimes. – Optional RSI “hook” filter that waits for momentum to actually turn instead of buying into a falling RSI. – Optional divergence add-on using kinematic velocity, so a marginal new price extreme with weaker velocity is recognized as a possible exhaustion pattern. REVERSAL EVENTS AND SCORING Raw events are detected when price wicks through the outer band and closes back inside (band hit with snap). These are plotted as diamonds and treated as candidates, not automatic trades. Each event is then scored from 0 to 100 using several factors: – How far price overshot the outer band. – How strongly it snapped back inside. – Whether an RSI hook is present (if enabled). – Regime quality from the kinematic model. – Basic kinematic safety to avoid the most aggressive “knife-catch” situations. – Optional divergence bonus when price makes a new extreme but velocity does not. Only events with a score above the chosen threshold become confirmed signals (triangles labeled PHYSICS REV). GHOST CONE (PREDICTIVE BAND) On the latest bar, the script projects a short-horizon “ghost cone” into the future using position, velocity, and a damped acceleration term. This creates a curved predictive band that visualizes a plausible short-term path and range, rather than a simple straight line. The cone is meant as context for trade management and risk, not as a hard target. FILTERS AND OPTIONS – Regime filter (R² and band width) can be tightened or relaxed depending on how selective you want the engine to be. – RSI and volume filters can be toggled on for extra confirmation or off to see the raw kinematic behavior. – An optional trend baseline (EMA) can be enabled to bias or restrict reversals relative to a higher-timeframe trend. – Dynamic cooldown scales with volatility so the script does not spam signals in fast environments. HOW TO USE Physics of Price is primarily a mean-reversion and exhaustion tool. It works best in markets that respect ranges, swings, and two-sided order flow. Confirmed PHYSICS REV signals near the outer bands, with decent model health and a clean RSI hook, are the core use case. The bands and ghost cone can also be used as a context overlay alongside your own entries, exits, and risk framework. This is an indicator, not a complete trading system. It does not use lookahead or higher-timeframe security calls and is designed for “once per bar close” alerts. Always combine it with your own risk management and confluence.
Penunjuk Pine Script®
oleh Finntech1
Syntropy - System v4Syntropy System v4 – La Estrategia de Acumulación Profesional que Todos Están UsandoEDICIÓN LIMITADA – SOLO 10 PLAZAS DISPONIBLES EN TODO EL MUNDOPor primera (y única) vez, libero mi estrategia privada más potente: La misma que uso personalmente y que ha cambiado por completo la forma en que acumulo en Bitcoin, Ethereum y altcoins de alto potencial.¿Qué incluye Syntropy v4?8 motores de entrada independientes (PG Solo, PG+FA, RZ1/RZ2, SFP, Liquidity Sweep, STE Bottom + reentradas inteligentes) Piramidación hasta 20 niveles con control total de riesgo Medias móviles dinámicas + proyecciones extendidas Tabla en tiempo real con P&L total, capital invertido y operaciones abiertas/cerradas Señales 100% visuales y sin repintado Optimizada para cripto, pero funciona perfecto en forex y acciones OFERTA EXCLUSIVA Y POR TIEMPO MUY LIMITADOPrecio normal: 499 USD (pago único de por vida + todas las futuras actualizaciones) PRECIO LANZAMIENTO SOLO PARA LOS PRIMEROS 10 COMPRADORES: 50 USD DE POR VIDA (Sí, leíste bien: cincuenta dólares una sola vez y el indicador es tuyo para siempre)Una vez que se vendan las 10 primeras licencias, este precio desaparece para siempre y vuelve al valor real de 499 USD.Ya van 7/10 vendidas en las últimas horas…¿Quieres ser uno de los últimos 3 que se lleven Syntropy v4 a precio de lanzamiento?Envíame YA un mensaje privado con la palabra “SYNTROPY 50” y te mando el enlace de pago + acceso inmediato al script protegido.No hay prueba gratis esta vez porque a este precio es literalmente un regalo… pero sí te doy mi palabra: si en 30 días no estás 100% convencido de que es la mejor estrategia que has usado jamás, te devuelvo hasta el último centavo.Quedan muy pocas horas antes de que suba el precio para siempre.Los primeros 10 que escriban ahora se llevan el indicador de por vida por solo 50 USD. El resto pagará 10 veces más.Tú decides si estás dentro del grupo élite o te quedas mirando desde afuera.Te espero del otro lado.Aviso importante (reglas de TradingView): Este es un script privado de pago. No constituye asesoramiento financiero. Operar implica riesgo de pérdida de capital. Los resultados pasados no garantizan resultados futuros. Uso bajo tu propia responsabilidad. Syntropy System v4 – The Most Powerful Accumulation Strategy Ever ReleasedWORLDWIDE LIMITED EDITION – ONLY 10 LIFETIME SEATSFor the first and last time ever, I’m opening my personal, private strategy that I use every single day to stack Bitcoin, Ethereum, Ethereum and high-conviction altcoins.What you get with Syntropy v48 independent & complementary entry engines (PG Solo, PG+FA, RZ1/RZ2, SFP, Liquidity Sweep, STE Bottom + smart reentries) Up to 20 pyramiding levels with perfect risk scaling Dynamic moving averages + extended visual projections Real-time dashboard (total P&L, invested capital, open/closed trades) 100% visual, non-repainting signals Built for crypto, but works flawlessly on forex and stocks too INSANE LAUNCH PRICE – ONLY FOR THE FIRST 10 PEOPLENormal lifetime price: $499 (one-time payment + all future updates forever)LAUNCH PRICE – FIRST 10 BUYERS ONLY: $50 USD LIFETIME (Yes, you read that right: fifty dollars one time and the indicator is yours forever)Once these 10 licenses are gone, the price jumps permanently to $499 and will never come back down.7 out of 10 already sold in the last few hours…That leaves only 3 seats at this ridiculous price.Want to be one of the last 3 people on Earth to grab Syntropy v4 for $50 lifetime?Send me a private message RIGHT NOW with the words “SYNTROPY 50” and I’ll instantly send you the payment link + immediate access to the protected script.There is no free trial at this price (it would be insane), but I give you my personal word: If within 30 days you’re not 100% blown away and convinced this is the best strategy you’ve ever used, I’ll refund every single penny — no questions asked.The clock is ticking. In a few hours this $50 offer disappears forever.The first 10 who message me now get lifetime access for only $50. Everyone else will pay 10× more.Your move: be part of the elite 10 or watch from the sidelines.I’ll see you inside.TradingView Required Disclaimer This is a paid private script. Not financial advice. Trading involves substantial risk of loss. Past performance is no guarantee of future results. Use only capital you can afford to lose. You are solely responsible for your trading decisions.
Strategi Pine Script®
oleh ctfnoe
2
Bitcoin Power-Law Bands + Quantile OscillatorDescription This indicator visualizes a set of statistically derived Power-Law bands for the Bitcoin price. The model is based on a log–log regression of the Bitcoin price over time and a weighted quantile regression that captures the distributional structure of the price across several long-term quantiles. It provides a historical context for where the price currently lies relative to these mathematically estimated zones. This indicator does not perform any new model fitting; it only displays the pre-computed band structure derived from the full historical dataset. How the model works This indicator is based on a statistical Power-Law model of the Bitcoin price. A long-term trend was estimated using a log–log OLS regression, and the deviations from this trend were analyzed through a rolling multi-year volatility measure. The inverse of this volatility served as the weight for several quantile regression fits, producing robust long-term bands at multiple distribution levels (0.1%, 15%, 50%, 85%, 95%, 99.9%). These quantile curves represent the historical valuation zones of the Bitcoin price. All final regression coefficients are fixed and embedded into the Pine script, which reconstructs the bands directly on the chart. The extension of the bands into the future is based solely on the mathematical form of each curve and does not use any future market data. What the indicator displays • Six Power-Law quantile bands (0.1%, 15%, 50%, 85%, 95%, 99.9%) displayed as stacked colored zones • Future-offset projection curves (mathematical extrapolation of the fitted Power-Laws, not based on future prices) • Quantile Oscillator: A normalized representation of where the current price lies relative to the quantile structure. How to use it This indicator is not a timing tool. It provides a structural, long-term statistical context for the Bitcoin price, showing: • how extreme a current valuation is relative to long-term history • where the price sits within the Power-Law quantile spectrum • long-term distribution zones derived from the quantile regressions • a volatility-weighted representation of historical deviations It may be useful for long-term cycle studies or valuation comparisons, but there is no guarantee that this historical relationship will persist. Important notes • This indicator does not repaint. • All projections are non-predictive mathematical extrapolations. • This script is designed only for the symbol: INDEX:BTCUSD • It does not provide trading signals, recommendations, or financial advice. Why closed-source? The underlying regression model, weighting logic, and quantile estimations were produced externally using Python and constitute the core intellectual component of the study. The Pine version contains only the pre-calculated parameters and the visualization logic.
Penunjuk Pine Script®
oleh jv_indicators
ADX Forecast Colorful [DiFlip]ADX Forecast Colorful Introducing one of the most advanced ADX indicators available — a fully customizable analytical tool that integrates forward-looking forecasting capabilities. ADX Forecast Colorful is a scientific evolution of the classic ADX, designed to anticipate future trend strength using linear regression. Instead of merely reacting to historical data, this indicator projects the future behavior of the ADX, giving traders a strategic edge in trend analysis. ⯁ Real-Time ADX Forecasting For the first time, a public ADX indicator incorporates linear regression (least squares method) to forecast the future behavior of ADX. This breakthrough approach enables traders to anticipate trend strength changes based on historical momentum. By applying linear regression to the ADX, the indicator plots a projected trendline n periods ahead — helping users make more accurate and timely trading decisions. ⯁ Highly Customizable The indicator adapts seamlessly to any trading style. It offers a total of 26 long entry conditions and 26 short entry conditions, making it one of the most configurable ADX tools on TradingView. Each condition is fully adjustable, enabling the creation of statistical, quantitative, and automated strategies. You maintain full control over the signals to align perfectly with your system. ⯁ Innovative and Science-Based This is the first public ADX indicator to apply least-squares predictive modeling to ADX dynamics. Technically, it embeds machine learning logic into a traditional trend-strength indicator. Using linear regression as a predictive engine adds powerful statistical rigor to the ADX, turning it into an intelligent, forward-looking signal generator. ⯁ Scientific Foundation: Linear Regression Linear regression is a fundamental method in statistics and machine learning used to model the relationship between a dependent variable y and one or more independent variables x. The basic formula for simple linear regression is: y = β₀ + β₁x + ε Where: y  = predicted value (e.g., future ADX) x  = explanatory variable (e.g., bar index or time) β₀ = intercept β₁ = slope (rate of change) ε   = random error term The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the ADX projection based on recent trends. ⯁ Least Squares Estimation To minimize the error, the regression coefficients are calculated as: β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²) β₀ = ȳ - β₁x̄ Where: Σ = summation x̄ and ȳ = means of x and y i ranges from 1 to n (number of data points) These formulas provide the best linear unbiased estimator under Gauss-Markov conditions — assuming constant variance and linearity. ⯁ Linear Regression in Machine Learning Linear regression is a foundational algorithm in supervised learning. Its power in producing quantitative predictions makes it essential in AI systems, predictive analytics, time-series forecasting, and automated trading. Applying it to the ADX essentially places an intelligent forecasting engine inside a classic trend tool. ⯁ Visual Interpretation Imagine an ADX time series like this: Time → ADX  → The regression line smooths these values and projects them n periods forward, creating a predictive trajectory. This forecasted ADX line can intersect with the actual ADX, offering smarter buy and sell signals. ⯁ Summary of Scientific Concepts Linear Regression: Models variable relationships with a straight line. Least Squares: Minimizes prediction errors for best fit. Time-Series Forecasting: Predicts future values using historical data. Supervised Learning: Trains models to predict outcomes from inputs. Statistical Smoothing: Reduces noise and highlights underlying trends. ⯁ Why This Indicator Is Revolutionary Scientifically grounded: Based on rigorous statistical theory. Unprecedented: First public ADX using least-squares forecast modeling. Smart: Uses machine learning logic. Forward-Looking: Generates predictive, not just reactive, signals. Customizable: Flexible for any strategy or timeframe. ⯁ Conclusion By merging ADX and linear regression, this indicator enables traders to predict market momentum rather than merely follow it. ADX Forecast Colorful is not just another indicator — it’s a scientific leap forward in technical analysis. With 26 fully configurable entry conditions and smart forecasting, this open-source tool is built for creating cutting-edge quantitative strategies. ⯁ Example of simple linear regression with one independent variable This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables. ⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x) This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component. ⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models. ⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model. ⯁ Result of fitting a set of data points with a quadratic function This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line. ⯁ What is the ADX? The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down. The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength. ⯁ How to use the ADX? The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones: Strong Trend: When the ADX is above 25, indicating a strong trend. Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend. Neutral Zone: Between 20 and 25, where the trend strength is unclear. ⯁ Entry Conditions Each condition below is fully configurable and can be combined to build precise trading logic. 📈 BUY 🅰️  Signal Validity: The signal will remain valid for X bars . 🅰️  Signal Sequence: Configurable as AND or OR . 🅰️ +DI > -DI 🅰️ +DI < -DI 🅰️ +DI > ADX 🅰️ +DI < ADX 🅰️ -DI > ADX 🅰️ -DI < ADX 🅰️ ADX > Threshold 🅰️ ADX < Threshold 🅰️ +DI > Threshold 🅰️ +DI < Threshold 🅰️ -DI > Threshold 🅰️ -DI < Threshold 🅰️ +DI (Crossover) -DI 🅰️ +DI (Crossunder) -DI 🅰️ +DI (Crossover) ADX 🅰️ +DI (Crossunder) ADX 🅰️ +DI (Crossover) Threshold 🅰️ +DI (Crossunder) Threshold 🅰️ -DI (Crossover) ADX 🅰️ -DI (Crossunder) ADX 🅰️ -DI (Crossover) Threshold 🅰️ -DI (Crossunder) Threshold 🔮 +DI (Crossover) -DI Forecast 🔮 +DI (Crossunder) -DI Forecast 🔮 ADX (Crossover) +DI Forecast 🔮 ADX (Crossunder) +DI Forecast 📉 SELL 🅰️  Signal Validity: The signal will remain valid for X bars . 🅰️  Signal Sequence: Configurable as AND or OR . 🅰️ +DI > -DI 🅰️ +DI < -DI 🅰️ +DI > ADX 🅰️ +DI < ADX 🅰️ -DI > ADX 🅰️ -DI < ADX 🅰️ ADX > Threshold 🅰️ ADX < Threshold 🅰️ +DI > Threshold 🅰️ +DI < Threshold 🅰️ -DI > Threshold 🅰️ -DI < Threshold 🅰️ +DI (Crossover) -DI 🅰️ +DI (Crossunder) -DI 🅰️ +DI (Crossover) ADX 🅰️ +DI (Crossunder) ADX 🅰️ +DI (Crossover) Threshold 🅰️ +DI (Crossunder) Threshold 🅰️ -DI (Crossover) ADX 🅰️ -DI (Crossunder) ADX 🅰️ -DI (Crossover) Threshold 🅰️ -DI (Crossunder) Threshold 🔮 +DI (Crossover) -DI Forecast 🔮 +DI (Crossunder) -DI Forecast 🔮 ADX (Crossover) +DI Forecast 🔮 ADX (Crossunder) +DI Forecast 🤖 Automation All BUY and SELL conditions are compatible with TradingView alerts, making them ideal for fully or semi-automated systems. ⯁ Unique Features Linear Regression: (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL Background Colors: "bgcolor" Background Colors: "fill" Linear Regression (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Table of Conditions: BUY/SELL Conditions Label: BUY/SELL Plot Labels in the graph above: BUY/SELL Automate & Monitor Signals/Alerts: BUY/SELL Background Colors: "bgcolor" Background Colors: "fill"
Penunjuk Pine Script®
oleh DiFlip
Single AHR DCA (HM) — AHR Pane (customized quantile)Customized note The log-regression window LR length controls how long a long-term fair value path is estimated from historical data. The AHR window AHR window length controls over which historical regime you measure whether the coin is “cheap / expensive”. When you choose a log-regression window of length L (years) and an AHR window of length A (years), you can intuitively read the indicator as: “Within the last A years of this regime, relative to the long-term trend estimated over the same A years, the current price is cheap / neutral / expensive.” Guidelines: In general, set the AHR window equal to or slightly longer than the LR window: If the AHR window is much longer than LR, you mix different baselines (different LR regimes) into one distribution. If the AHR window is much shorter than LR, quantiles mostly reflect a very local slice of history. For BTC / ETH and other BTC-like assets, you can use relatively long horizons (e.g. LR ≈ 3–5 years, AHR window ≈ 3–8 years). For major altcoins (BNB / SOL / XRP and similar high-beta assets), it is recommended to use equal or slightly shorter horizons, e.g. LR ≈ 2–3 years, AHR window ≈ 2–3 years. 1. Price series & windows Working timeframe: daily (1D). Let the daily close of the current symbol on day t be P_t . Main length parameters: HM window: L_HM = maLen (default 200 days) Log-regression window: L_LR = lrLen (default 1095 days ≈ 3 years) AHR window (regime window): W = windowLen (default 1095 days ≈ 3 years) 2. Harmonic moving average (HM) On a window of length L_HM, define the harmonic mean: HM_t = ^(-1) Here eps = 1e-10 is used to avoid division by zero. Intuition: HM is more sensitive to low prices – an extremely low price inside the window will drag HM down significantly. 3. Log-regression baseline (LR) On a window of length L_LR, perform a linear regression on log price: Over the last L_LR bars, build the series x_k = log( max(P_k, eps) ), for k = t-L_LR+1 ... t, and fit x_k ≈ a + b * k. The fitted value at the current index t is log_P_hat_t = a + b * t. Exponentiate to get the log-regression baseline: LR_t = exp( log_P_hat_t ). Interpretation: LR_t is the long-term trend / fair value path of the current regime over the past L_LR days. 4. HM-based AHR (valuation ratio) At each time t, build an HM-based AHR (valuation multiple): AHR_t = ( P_t / HM_t ) * ( P_t / LR_t ) Interpretation: P_t / HM_t : deviation of price from the mid-term HM (e.g. 200-day harmonic mean). P_t / LR_t : deviation of price from the long-term log-regression trend. Multiplying them means: if price is above both HM and LR, “expensiveness” is amplified; if price is below both, “cheapness” is amplified. Typical reading: AHR_t < 1 : price is below both mid-term mean and long-term trend → statistically cheaper. AHR_t > 1 : price is above both mid-term mean and long-term trend → statistically more expensive. 5. Empirical quantile thresholds (Opp / Risk) On each new day, whenever AHR_t is valid, add it into a rolling array: A_t_window = { AHR_{t-W+1}, ..., AHR_t } (at most W = windowLen elements) On this empirical distribution, define two quantiles: Opportunity quantile: q_opp (default 15%) Risk quantile: q_risk (default 65%) Using standard percentile computation (order statistics + linear interpolation), we get: Opp threshold: theta_opp = Percentile( A_t_window, q_opp ) Risk threshold: theta_risk = Percentile( A_t_window, q_risk ) We also compute the percentile rank of the current AHR inside the same history: q_now = PercentileRank( A_t_window, AHR_t ) ∈ This yields three valuation zones: Opportunity zone: AHR_t <= theta_opp (corresponds to roughly the cheapest ~q_opp% of historical states in the last W days.) Neutral zone: theta_opp < AHR_t < theta_risk Risk zone: AHR_t >= theta_risk (corresponds to roughly the most expensive ~(100 - q_risk)% of historical states in the last W days.) All quantiles are purely empirical and symbol-specific: they are computed only from the current asset’s own history, without reusing BTC thresholds or assuming cross-asset similarity. 6. DCA simulation (lightweight, rolling window) Given: a daily budget B (input: budgetPerDay), and a DCA simulation window H (input: dcaWindowLen, default 900 days ≈ 2.5 years), The script applies the following rule on each new day t: If thresholds are unavailable or AHR_t > theta_risk → classify as Risk zone → buy = 0 If AHR_t <= theta_opp → classify as Opportunity zone → buy = 2B (double size) Otherwise (Neutral zone) → buy = B (normal DCA) Daily invested cash: C_t ∈ {0, B, 2B} Daily bought quantity: DeltaQ_t = C_t / P_t The script keeps rolling sums over the last H days: Cumulative position: Q_H = sum_{k=t-H+1..t} DeltaQ_k Cumulative invested cash: C_H = sum_{k=t-H+1..t} C_k Current portfolio value: PortVal_t = Q_H * P_t Cumulative P&L: PnL_t = PortVal_t - C_H Active days: number of days in the last H with C_k > 0. These results are only used to visualize how this AHR-quantile-driven DCA rule would have behaved over the recent regime, and do not constitute financial advice.
Penunjuk Pine Script®
oleh Anoria_4RICH
1
BTC/Gold Power-Law Bands + Quantile OscillatorDescription This indicator visualizes a set of statistically derived Power-Law bands for the BTC/Gold ratio. The model is based on a log–log regression of the BTC/Gold ratio over time and a weighted quantile regression that captures the distributional structure of the ratio across several long-term quantiles. It provides a historical context for where the ratio currently lies relative to these mathematically estimated zones. This indicator does not perform any new model fitting; it only displays the pre-computed band structure derived from the full historical dataset. How the model works This indicator is based on a statistical Power-Law model of the BTC/Gold ratio. A long-term trend was estimated using a log–log OLS regression, and the deviations from this trend were analyzed through a rolling multi-year volatility measure. The inverse of this volatility served as the weight for several quantile regression fits, producing robust long-term bands at multiple distribution levels (0.1%, 12.5%, 50%, 80%, 95%, 99.5%). These quantile curves represent the historical valuation zones of the BTC/Gold ratio. All final regression coefficients are fixed and embedded into the Pine script, which reconstructs the bands directly on the chart. The extension of the bands into the future is based solely on the mathematical form of each curve and does not use any future market data. What the indicator displays • Six Power-Law quantile bands (0.1%, 12.5%, 50%, 80%, 95%, 99.5%) displayed as stacked colored zones • BTC/Gold Ratio line • Future-offset projection curves (mathematical extrapolation of the fitted Power-Laws, not based on future prices) • Quantile Oscillator: A normalized representation of where the current ratio lies relative to the quantile structure. How to use it This indicator is not a timing tool. It provides a structural, long-term statistical context for the BTC/Gold ratio, showing: • how extreme a current valuation is relative to long-term history • where the ratio sits within the Power-Law quantile spectrum • long-term distribution zones derived from the quantile regressions • a volatility-weighted representation of historical deviations It may be useful for long-term cycle studies or ratio-based valuation comparisons, but there is no guarantee that this historical relationship will persist. Important notes • This indicator does not repaint. • All projections are non-predictive mathematical extrapolations. • This script is designed only for the symbol: BTCUSD/TVC:GOLD (BTC/Gold Ratio) • It does not provide trading signals, recommendations, or financial advice. Why closed-source? The underlying regression model, weighting logic, and quantile estimations were produced externally using Python and constitute the core intellectual component of the study. The Pine version contains only the pre-calculated parameters and the visualization logic.
Penunjuk Pine Script®
oleh jv_indicators
Omega Correlation [OmegaTools]Omega Correlation (Ω CRR) is a cross-asset analytics tool designed to quantify both the strength of the relationship between two instruments and the tendency of one to move ahead of the other. It is intended for traders who work with indices, futures, FX, commodities, equities and ETFs, and who require something more robust than a simple linear correlation line. The indicator operates in two distinct modes, selected via the “Show” parameter: Correlation and Anticipation. In Correlation mode, the script focuses on how tightly the current chart and the chosen second asset move together. In Anticipation mode, it shifts to a lead–lag perspective and estimates whether the second asset tends to behave as a leader or a follower relative to the symbol on the chart. In both modes, the core inputs are the chart symbol and a user-selected second symbol. Internally, both assets are transformed into normalized log-returns: the script computes logarithmic returns, removes short-term mean and scales by realized volatility, then clips extreme values. This normalisation allows the tool to compare behaviour across assets with different price levels and volatility profiles. In Correlation mode, the indicator computes a composite correlation score that typically ranges between –1 and +1. Values near +1 indicate strong and persistent positive co-movement, values near zero indicate an unstable or weak link, and values near –1 indicate a stable anti-correlation regime. The composite score is constructed from three components. The first component is a normalized return co-movement measure. After transforming both instruments into normalized returns, the script evaluates how similar those returns are bar by bar. When the two assets consistently deliver returns of similar sign and magnitude, this component is high and positive. When they frequently diverge or move in opposite directions, it becomes negative. This captures short-term co-movement in a volatility-adjusted way. The second component focuses on high–low swing alignment. Rather than looking only at closes, it examines the direction of changes in highs and lows for each bar. If both instruments are printing higher highs and higher lows together, or lower highs and lower lows together, the swing structure is considered aligned. Persistent alignment contributes positively to the correlation score, while repeated mismatches between the swing directions reduce it. This helps differentiate between superficial price noise and structural similarity in trend behaviour. The third component is a classical Pearson correlation on closing prices, computed over a longer lookback. This serves as a stabilising backbone that summarises general co-movement over a broader window. By combining normalized return co-movement, swing alignment and standard price correlation with calibrated weights, the Correlation mode provides a richer view than a single linear measure, capturing both short-term dynamic interaction and longer-term structural linkage. In Anticipation mode, Omega Correlation estimates whether the second asset tends to lead or lag the current chart. The output is again a continuous score around the range. Positive values suggest that the second asset is acting more as a leader, with its past moves bearing informative value for subsequent moves of the chart symbol. Negative values indicate that the second asset behaves more like a laggard or follower. Values near zero suggest that no stable lead–lag structure can be identified. The anticipation score is built from four elements inspired by quantitative lead–lag and price discovery analysis. The first element is a residual lead correlation, conceptually similar to Granger-style logic. The script first measures how much of the chart symbol’s normalized returns can be explained by its own lagged values. It then removes that component and studies the correlation between the residuals and lagged returns of the second asset. If the second asset’s past returns consistently explain what the chart symbol does beyond its own autoregressive behaviour, this residual correlation becomes significantly positive. The second element is an asymmetric lead–lag structure measure. It compares the strength of relationships in both directions across multiple lags: the correlation of the current symbol with lagged versions of the second asset (candidate leader) versus the correlation of lagged values of the current symbol with the present values of the second asset. If the forward direction (second asset leading the first) is systematically stronger than the backward direction, the structure is skewed toward genuine leadership of the second asset. The third element is a relative price discovery score, constructed by building a dynamic hedge ratio between the two prices and defining a spread. The indicator looks at how changes in each asset contribute to correcting deviations in this spread over time. When the chart symbol tends to do most of the adjustment while the second asset remains relatively stable, it suggests that the second asset is taking a greater role in determining the equilibrium price and the chart symbol is adjusting to it. The difference in adjustment intensity between the two instruments is summarised into a single score. The fourth element is a breakout follow-through causality component. The script scans for breakout events on the second asset, where its price breaks out of a recent high or low range while the chart symbol has not yet done so. It then evaluates whether the chart symbol subsequently confirms the breakout direction, remains neutral, or moves against it. Events where the second asset breaks and the first asset later follows in the same direction add positive contribution, while failed or contrarian follow-through reduce this component. The contribution is also lightly modulated by the strength of the breakout, via the underlying normalized return. The four elements of the Anticipation mode are combined into a single leading correlation score, providing a compact and interpretable measure of whether the second asset currently behaves as an effective early signal for the symbol you trade. To aid interpretation, Omega Correlation builds dynamic bands around the active series (correlation or anticipation). It estimates a long-term central tendency and a typical deviation around it, plotting upper and lower bands that highlight unusually high or low values relative to recent history. These bands can be used to distinguish routine fluctuations from genuinely extreme regimes. The script also computes percentile-based levels for the correlation series and uses them to track two special price levels on the main chart: lost correlation levels and gained correlation levels. When the correlation drops below an upper percentile threshold, the current price is stored as a lost correlation level and plotted as a horizontal line. When the correlation rises above a lower percentile threshold, the current price is stored as a gained correlation level. These levels mark zones where a historically strong relationship between the two markets broke down or re-emerged, and can be used to frame divergence, convergence and spread opportunities. An information panel summarises, in real time, whether the second asset is behaving more as a leading, lagging or independent instrument according to the anticipation score, and suggests whether the current environment is more conducive to de-alignment, re-alignment or classic spread behaviour based on the correlation regime. This makes the tool directly interpretable even for users who are not familiar with all the underlying statistical details. Typical applications for Omega Correlation include intermarket analysis (for example, index vs index, commodity vs related equity sector, FX vs bonds), dynamic hedge sizing, regime detection for algorithmic strategies, and the identification of lead–lag structures where a macro driver or benchmark can be monitored as an early signal for the instrument actually traded. The indicator can be applied across intraday and higher timeframes, with the understanding that the strength and nature of relationships will differ across horizons. Omega Correlation is designed as an advanced analytical framework, not as a standalone trading system. Correlation and lead–lag relationships are statistical in nature and can change abruptly, especially around macro events, regime shifts or liquidity shocks. A positive anticipation reading does not guarantee that the second asset will always move first, and a high correlation regime can break without warning. All outputs of this tool should be combined with independent analysis, sound risk management and, when appropriate, backtesting or forward testing on the user’s specific instruments and timeframes. The intention behind Omega Correlation is to bring techniques inspired by quantitative research, such as normalized return analysis, residual correlation, asymmetric lead–lag structure, price discovery logic and breakout event studies, into an accessible TradingView indicator. It is intended for traders who want a structured, professional way to understand how markets interact and to incorporate that information into their discretionary or systematic decision-making processes.
Penunjuk Pine Script®
oleh OmegaTools
Multivariate Kalman Filter🙏🏻 I see no1 ever posted an open source Multivariate Kalman filter on TV, so here it is, for you. Tested and mathematically correct implementation, with numerical safeties in place that do not affect the final results at all. That’s the main purpose of this drop, just to make the tool available here. Linear algebra everywhere, Neo would approve 4 sure. ... Personally I haven't found any real use case of it for myself, aside from a very specific one I will explain later, but others usually do… Almost every1 in the quant industry who uses Kalman is in fact misusing it, because by its real definition, it should be applied to Not the exact known values (e.g as real ticks provided by transparent audited regulated exchange), but “measurements” of those ‘with errors’. If your measurements don’t have errors or you have real precise data, by its internal formulas Kalman will output the exact inputs. So most who use it come up with some imaginary errors of sorts, like from some kind of imaginary fair price etc. The important easy to miss point, the errors of your measurements have to be symmetric around its mean ‘ at least ’, if errors are biased, Kalman won’t provide. For most tasks there are better tools, including other state space models , but still Multivariate Kalman is a very powerful instrument, you can make it do all kinds of stuff. Also as a state space model it can also provide confidence & prediction intervals without explicit calculations of dem. ... In this script I included 2 example use cases, the first one is the classic tho perfectly working misuse, the second one is what I do with it: One Naive, estimates “hidden” adaptive moving regression endpoint. The result you can see on the chart above. You can imagine that your real datapoints are in fact non perfect measures of some hidden state, and by defining measurement noise and process noise, and by constructing the input matrixes in certain ways, you can express what that state should be. Two Upscaling tick lattice, aka modelling prices as if native tick size would’ve been lower. Kinda very specific task, mostly needed in HFT or just for analytical purposes. Some like ZN have huge tick sizes, they are traded a lot but barely do more than 20 ticks range in a session. The idea is to model raw data as AR2 process , learn the phi1 and phi2, make one point forecasts based on dem, and the process noise would be the variance of errors from these forecasts. The measurement noise here is legit, it’s quantization noise based on tick size, no need in olympic gold in mental gymnastics xd ^^ artificially upscaling ZN futures tick lattice ... I really made it available there so You guys can take it and some crazy ish with it, just let state space models abduct your conciseness and never look back ∞
Penunjuk Pine Script®
oleh gorx1
2
ArithmaReg Candles [NeuraAlgo]ArithmaReg Candles ArimaReg Candles provide a quantitative approach toward the visualization of price by rebuilding each candle using an adaptive regression model. This indicator eliminates much of the noise and micro-spikes and consolidates irregular volatility of raw OHLC data, which typically characterizes candles, into a much cleaner and more stable representation that better reflects the true directional intent of the market. The algorithm applies a dynamic state-space filter to track the equilibrium price, truePrice, while suppressing high-frequency fluctuations. Noise in the price is extracted by comparing the raw close to the filtered state and removed from the candle body and wick structure through controlled adjustment logic. Finally, a volatility-based spread model rebuilds the candle's range to maintain realistic price geometry. The direction of trends is given by comparing the truePrice against a smoothing baseline, permitting ArithmaReg Candles to underline the bullish and bearish phases with more clarity and much-reduced distortion. This yields a chart where transitions within trends, pullbacks, and momentum shifts are much easier to comprehend than their representation via traditional candles. ArithmaReg Candles are designed for traders who require consistent, noise-filtered price structure-ideal for trend analysis, breakout validation, and precision entries. The indicator itself does not generate any signals; it only refines the visual environment so that your existing tools and decision models become more reliable. How It Works Micro-Price Extraction A weighted micro-price is calculated to represent the bar's internal structure and reduce intrabar irregularities. Adaptive Regression Filter The state-based regression engine continuously updates price equilibrium, adjusting its confidence level. This gives the filter the ability to remain responsive during strong movements yet be stable during noisy periods. Noise Removal & Candle Reconstruction The difference between raw price and truePrice is considered noise. This noise is subtracted from OHLC values, and a volatility-scaled spread restores realistic wick and body proportions. What results is a candle that depicts true directional flow. Trend Classification A smoothed trend baseline is computed from the filtered price, and candle color is determined by whether the market is positioned above or below this equilibrium trend. How to Use It Identify True Trend Direction Candles follow the cleaned price path so that you can differentiate valid trend shifts from temporary spikes or wick-driven traps. Improve Existing Strategies These candles will complement your existing indicators, be they Supertrend, moving averages, volume tools, or momentum oscillators, by giving you a more sound price basis. Spot Clean Breakouts & Pullbacks Reduced noise makes breakout structure, swing highs/lows, and retracements significantly clearer. This is particularly useful in fast markets like crypto and Forex. Improve Entry & Exit Timing By highlighting the underlying flow of price, ArithmaReg Candles help traders avoid false signals and pinpoint spots where the price momentum is actually changing. Adaptable to All Timeframes & Assets The filter is self-adjusting, so it performs consistently on scalping timeframes, intraday charts, swing setups, and all asset classes. Summary ArithmaReg Candles create a mathematically refined view of market structure by removing noise and reconstructing candles through adaptive regression. The result is a more refined, stable price representation that improves trend recognition and decision-making and enables professional-grade technical analysis.
Penunjuk Pine Script®
oleh NeuraAlgo
6
Sniper BB + VWAP System (with SMT Divergence Arrows)STEP 1: Load two correlated futures charts. Example: CL + RB/SI+GC/ NQ+ES STEP 2: Add Bollinger Bands (20, 2.0) on both. Optional add (20, 3.0). STEP 3: Watch for a BB tag on one chart but not the other. STEP 4: Wait for a reclaim candle back inside the band. STEP 5: Enter with stop below/above the wick + 3.0 BB. STEP 6: Scale out midline, then opposite band. STEP 7: Hold partials when both pairs confirm trend. *You can take the vwap bands off the chart if it is too cluttered.
Penunjuk Pine Script®
oleh the1nepercent
1