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Sigmoid Risk AllocatorThe Sigmoid Risk Allocator is a dynamic position sizing indicator that tells you how much of your capital to allocate based on current market conditions. Unlike simple "risk-on/risk-off" signals, this indicator gives you smooth, gradual transitions based on a sigmoid function. Why a Sigmoid Curve? Most position sizing approaches use fixed thresholds: "If drawdown > 20%, buy. Otherwise, don't." This creates all-or-nothing decisions. Using the sigmoid (S-curve) makes this decision different. It creates a smooth transition where: Small drawdowns → Stay near your baseline allocation Moderate drawdowns → Gradually increase exposure Large drawdowns → Approach maximum allocation The sigmoid curve naturally "saturates" at the extremes, preventing you from going all-in too early or panicking out too fast. This is very useful to meek traders psychology and risk management in check. What's a Sigmoid Function? The sigmoid function is a mathematical S-curve defined as: σ(x) = 1 / (1 + e^(-x)) This formula takes any input value and smoothly maps it to a number between 0 and 1. The curve has three key properties that make it ideal for position sizing in investing: Smooth transitions: No sudden jumps. Allocation changes gradually. Saturation at extremes: The curve flattens near 0 and 1, preventing overreaction and overexposure. Sensitive in the middle: Most of the action happens around the midpoint. To convert this into an allocation percentage, the indicator uses: Allocation = α_min + (α_max - α_min) × σ(k × (Risk - Midpoint)) Where: - `α_min` = Your minimum allocation (default 50%) - `α_max` = Your maximum allocation (default 100%) - `Risk` = Current risk metric (drawdown %, volatility, or Kelly %) - `Midpoint` = The risk level where allocation sits halfway between min and max (default 15%) - `k` = Steepness—how quickly allocation changes around the midpoint Example : With defaults, if drawdown hits 15% (the midpoint), your allocation will be 75% (halfway between 50% and 100%). As the drawdown increases beyond 15%, the allocation curves toward 100%. As it decreases toward 0%, allocation curves toward 50%. Cool, isn't it? Asymmetric Response: Fast In, Slow Out The indicator uses different steepness values for scaling in vs. scaling out. This is great to increase trend following. This is something I'm proud of too in this indicator. k_increase = 30 (steep curve): When drawdowns appear, allocation ramps up quickly to catch the opportunity k_decrease = 5 (slower curve): When conditions normalize, allocation decreases slowly to avoid selling the rebound This asymmetry reflects how markets behave—drawdowns often overshoot fundamentals (rewarding quick entries), while recoveries tend to be more orderly (rewarding patience on exits). Three Risk Metrics You can choose what drives your allocation: Drawdown (Default) Volatility - Scales your position inversely to current market volatility. Kelly Criterion - Automatically calculates optimal position size. The indicator applies a conservative "half Kelly" by default. Use Cases Position sizing for swing trading or trend following Risk management overlay for any existing strategy Drawdown-based DCA (dollar cost averaging) decisions Volatility-adjusted exposure management Feel free to provide feedback and share your thoughts! - Henrique Centieiro
Индикатор Pine Script®
от HenriqueCentieiro
Position Size Gev_Risk ($) The amount of money you are willing to lose if the stop-loss is hit. Base Stop Price The stop-loss price you set. The stop is recalculated in real time as price moves. Fee (%) round-trip Estimated total trading fees for opening and closing the position. Stop Mode With Buffer: adds extra distance to the stop, resulting in a smaller position size No Buffer: uses the Base Stop Price exactly as entered Stop Buffer (%) The percentage added to the stop distance when Stop Mode is set to With Buffer. Live adjustment behavior The stop price updates continuously as price moves, and the position size is recalculated live to stay aligned with the selected Risk ($).
Индикатор Pine Script®
от gevanv
Entropy-Gated Expansion StateThis indicator identifies sustained directional expansion regimes by separating regime qualification from regime persistence. Directional entropy is used to detect when price transitions from a disordered environment into a structured one, acting as a gate that enables participation only during favorable market conditions. Once qualified, trend structure maintains the active state through consolidations and minor pullbacks, ensuring the indicator remains engaged throughout the expansion phase rather than firing as a short-lived signal. The result is a persistent, state-based output that avoids sideways markets, reduces noise, and remains active during sustained trends across a wide range of assets, including high-volatility instruments.
Индикатор Pine Script®
от Mr_Thomas_Shelby
Return Skew (Directional Asymmetry)This indicator measures the asymmetry of returns over a rolling window, specifically evaluating whether positive returns dominate negative returns in magnitude rather than frequency. The purpose of this indicator is to identify assets whose upside moves are structurally stronger than their downside moves, indicating convex return behaviour. Unlike trend or momentum indicators, return skew captures the quality of price movement, distinguishing between assets that grind upward versus those that experience explosive upside relative to drawdowns. By requiring positive return skew, this indicator helps avoid assets that are rising through frequent small gains but are vulnerable to sharp downside moves, thereby favouring assets exhibiting genuine asymmetric upside potential.
Индикатор Pine Script®
от Mr_Thomas_Shelby
Today's Price Position On Intraday-From Low /High OVERVIEW A clean, professional indicator that displays your stock's current position relative to today's high, today's low, and yesterday's close - all in one convenient table. 🎯 WHAT IT SHOWS Three key metrics in real-time: - From Low: How far price has moved from today's lowest point - From High: How far price is from today's highest point - % Today: Today's percentage change vs yesterday's 4 PM close ✨ KEY FEATURES ✓ Real-time percentage tracking throughout the trading day ✓ Works on ALL intraday timeframes (1min, 5min, 15min, etc.) ✓ Includes Pre-Market (4:00-9:30 AM) and Regular Trading Hours (9:30-4:00 PM) ✓ Color-coded indicators: Green (up), Red (down), Yellow (at reference point) ✓ Clean, non-intrusive table display in bottom-right corner ✓ Accurate reference to previous day's actual closing price 🔧 TESTING MODE Built-in testing mode allows you to: - Manually input test values for High, Low, Close, and Previous Close - Verify calculations and behavior before live trading 📈 IDEAL FOR - Day traders monitoring intraday price action - Swing traders tracking daily momentum - Anyone wanting quick visual reference of price position - Traders who need to know "where we are" at a glance 💡 HOW TO USE Simply add to your chart - no configuration needed! The indicator automatically: 1. Tracks today's high and low (including pre-market) 2. References yesterday's 4 PM closing price 3. Calculates your current position as percentages 4. Updates in real-time with color-coded signals 🎨 COLOR LEGEND - Green: Price is up/above reference - Red: Price is down/below reference - Yellow: Price is exactly at reference point (unchanged) - Orange: Previous day's close reference price ⚙️ TECHNICAL NOTES - Automatically resets at start of each trading day - Handles both pre-market and regular hours seamlessly - Uses confirmed previous day close (no repainting) - Lightweight and efficient - won't slow down your charts Perfect for traders who want professional-grade information without chart clutter!
Индикатор Pine Script®
от jhor_10
FOMC Policy Events[nakano]### FOMC Policy Events #### Summary / 概要 This indicator plots the historical policy decisions of the U.S. Federal Open Market Committee (FOMC) directly onto your chart. It is an essential tool for traders and analysts who want to visualize how the market reacts to changes in monetary policy. All historical event data from 2000 onwards is hard-coded into the script for fast and reliable performance. このインジケーターは、米国連邦公開市場委員会（FOMC）の過去の政策決定をチャート上に直接プロットします。金融政策の変更に対する市場の反応を視覚的に分析したいトレーダーやアナリストにとって不可欠なツールです。2000年以降の全ての過去イベントデータが含まれます。 --- #### Features / 主な機能 * **Comprehensive Historical Data / 包括的な過去データ** Includes all historical scheduled and emergency FOMC rate decisions from January 2000. 2000年1月以降の、全ての定例および緊急のFOMC金利決定の履歴を含みます。 * **Detailed Event Labels / 詳細なイベントラベル** Each event is marked with a clear label showing: 各イベントには、以下の情報を示す明確なラベルが表示されます： * The exact date of the announcement. 発表の正確な日付 * The type of decision (Rate Hike, Rate Cut, Hold, or Emergency Cut). 決定内容（利上げ、利下げ、据え置き、緊急利下げ） * The resulting Federal Funds Target Rate. 決定後の政策金利（FF金利ターゲット） * **Fully Customizable Display / 柔軟な表示設定** From the indicator's settings menu, you can: インジケーターの設定画面から、以下の操作が可能です： * Individually toggle the visibility of Rate Hikes, Rate Cuts, and Holds. 「利上げ」「利下げ」「据え置き」の表示・非表示を個別に切り替える * Choose your preferred language for the labels (English or Japanese). ラベルの表示言語を「英語」または「日本語」から選択する * **Clear Visual Cues / 明確なビジュアル** * **Rate Hikes:** Green labels positioned below the price bars. **利上げ：** バーの下に緑色のラベル * **Rate Cuts:** Red labels positioned above the price bars. **利下げ：** バーの上に赤色のラベル * **Holds:** Gray labels positioned above the price bars. **据え置き：** バーの上に灰色のラベル * **Emergency Events:** Specially highlighted in maroon for easy identification. **緊急イベント：** 識別しやすいように特別な色（ワインレッド）で強調表示 --- #### How to Use / 使用方法 1. Add the indicator to your chart. インジケーターをチャートに追加します。 2. Click the **Settings (gear icon)** next to the indicator name on your chart. チャート上のインジケーター名の横にある**設定（歯車アイコン）**をクリックします。 3. In the "Display Settings" section, check or uncheck the boxes to show or hide different event types. 「Display Settings」セクションで、各イベントタイプの表示・非表示をチェックボックスで切り替えます。 4. In the "Language Settings" section, select your preferred language from the dropdown menu. 「Language Settings」セクションで、ドロップダウンメニューからお好みの言語を選択します。 --- #### A Note on Data / データについて The event data included in this script is static and contains historical decisions up to September 2025. The script does not plot future scheduled meetings and will need to be manually updated as new policy decisions are made. このスクリプトに含まれるイベントデータは静的なものであり、2026年1月までの過去の決定を含んでいます。未来のスケジュールをプロットする機能はなく、新しい金融政策が決定された場合は、スクリプトの手動更新が必要です。
Индикатор Pine Script®
от nakanock
Laguerre Filter [BackQuant]Laguerre Filter Overview The Laguerre Filter is a powerful trend-following tool designed to smooth price action while maintaining responsiveness to market changes. It is based on the Laguerre recursive filter, which is a type of signal processing filter that adapts to both the current price dynamics and the underlying trend. The Laguerre Filter can be seen as a method to reduce market noise, enabling traders to more easily identify the strength and direction of trends while minimizing lag. The Laguerre Filter is well-suited for markets with varying volatility levels, offering a smoother representation of price action without the delay associated with traditional moving averages. By dynamically adjusting to price movements, the Laguerre Filter provides a more adaptive and reliable signal compared to simpler smoothing techniques. What is the Laguerre Filter? The Laguerre Filter is derived from the Laguerre polynomial, which is used in signal processing for smooth filtering of data. The Laguerre filter is a recursive filter, meaning that each new value is calculated based on both the current price data and previous values, with a weighting system that allows it to adapt to market conditions. This recursive nature helps reduce the impact of short-term fluctuations, enabling the filter to focus on the underlying trend. The Laguerre filter uses a feedback mechanism, where the input signal (price data) is smoothed iteratively. This iterative process helps avoid the lag that is typically associated with traditional moving averages while still capturing the overall trend direction. The filter is designed to have: Adaptive behavior: It reacts quickly to significant price changes while ignoring minor fluctuations. Reduced noise: By filtering out random short-term price movements, it provides a clearer view of the underlying trend. Customizability: Traders can adjust the filter’s sensitivity through user inputs, making it adaptable to different market conditions. Core Calculation Methodology The core of the Laguerre Filter lies in its recursive calculation: Each new value is calculated using the previous value along with the current price input. The recursive formula is governed by two key parameters: the damping factor (gamma) and the order of the filter (number of Laguerre elements). The damping factor controls how responsive the filter is to changes in price. A higher gamma value makes the filter smoother but introduces more lag, while a lower gamma value makes it more reactive to price changes but can introduce more noise. The order defines how many Laguerre elements are used in the calculation. A higher order results in a smoother output but with more delay, while a lower order provides a faster response but less smoothing. The filter works by weighting previous values with a binomial weighting system, which assigns more weight to recent values and less weight to older values. This creates a dynamic smoothing effect that adapts to price volatility, ensuring that the filter is neither too slow nor too noisy. Signal Logic and Trend Detection The Laguerre Filter continuously evaluates the strength and direction of the trend by comparing the current smoothed value to the previous value: If the current value is greater than the previous value, the trend is considered bullish, and the filter will signal a long condition. If the current value is less than the previous value, the trend is considered bearish, and the filter will signal a short condition. The trend detection logic is based on the recursive nature of the filter, which smooths price movements over time. This allows the filter to capture the broader trend while minimizing the influence of short-term price fluctuations. The trend state is also visually represented by color-coding: Green color represents an uptrend (bullish condition). Red color represents a downtrend (bearish condition). Neutral (white) indicates no clear trend direction. This color-coding helps traders easily identify the prevailing trend and decide whether to enter or exit trades based on the trend's strength. Laguerre Filter Behavior and Performance The performance of the Laguerre Filter can be influenced by several factors: Gamma (Damping Factor): A higher gamma value results in a smoother filter but increases lag. A lower gamma value allows for a faster response but may introduce more noise, making it more reactive to smaller price changes. Filter Order: The order determines how many Laguerre elements are used in the filter calculation. A higher order provides more smoothing but increases lag, while a lower order results in a quicker response but less smoothing. The sweet spot for gamma is typically between 0.7 and 0.85, where the filter offers a good balance between smoothness and responsiveness. The filter order is usually set to 4 for classic Laguerre filtering, but higher orders can be used for more smoothing if needed. The Laguerre Filter’s performance shines in markets with sustained trends, where the filter can effectively capture and represent the underlying direction without excessive lag. It is particularly useful in volatile markets, as it helps smooth out noise while providing a clear picture of the trend. Visual Presentation The Laguerre Filter provides a dynamic, color-coded line that follows the trend direction. This line can be displayed alongside price data to visually highlight the market trend. In addition to the main Laguerre line, several visual enhancements can be applied: Gradient fill between the price and the Laguerre Filter line, providing a visual cue for bullish or bearish market conditions. Candle coloring to reflect the current trend, making it easier to spot trend reversals or confirmations directly on the chart. Background shading to visually highlight areas of strong trend or consolidation. Edge glow effect that highlights trend boundaries, making it easy to spot key levels of support or resistance. These visual elements enhance the usability of the Laguerre Filter, allowing traders to quickly assess the market trend and make informed decisions. Practical Use Cases 1) Trend Following The Laguerre Filter is ideal for trend-following strategies. By using the filter to identify the prevailing trend, traders can: Enter long positions when the Laguerre Filter turns bullish (green). Enter short positions when the Laguerre Filter turns bearish (red). By aligning trades with the dominant trend, traders can improve their chances of success. 2) Trend Strength Assessment The Laguerre Filter can also be used to assess the strength of the trend: A rising Laguerre value indicates a strengthening uptrend. A falling Laguerre value indicates a strengthening downtrend. A flattening Laguerre value signals weakening momentum or consolidation. This information can be used to adjust position sizing or to decide when to enter or exit a trade. 3) Trade Management The Laguerre Filter can also assist in trade management: Use the Laguerre line as a trailing stop for long positions in an uptrend. Scale out of positions as the Laguerre value begins to flatten or reverse. Use the Laguerre Filter to avoid trades when the market is in consolidation or lacks a clear trend. Tuning Guidelines The Laguerre Filter can be adjusted for different market conditions using the following parameters: Gamma (Damping Factor): Adjust for the desired level of responsiveness versus smoothness. Typical values range from 0.7 to 0.85. Filter Order: Adjust to control the level of smoothing. The default value of 4 is a good starting point, but higher orders can be used for smoother filters. Summary The Laguerre Filter is a versatile and adaptive trend-following indicator that smooths price data and reduces noise, making it easier to identify and follow trends. By using recursive smoothing techniques and adjustable parameters, the Laguerre Filter provides an accurate representation of market conditions with minimal lag. It is especially useful in volatile markets where traditional moving averages may fail to capture the underlying trend. With its color-coded trend detection, gradient fills, and customizable settings, the Laguerre Filter is a powerful tool for traders looking to stay aligned with the prevailing market direction.
Индикатор Pine Script®
от BackQuant
1
PPAO - Propagator Price Action Oscillator How PPAO works in one cycle (what it does every candle) PPAO has 3 moving parts that run every bar: 1) It measures new candle pressure (the “push”) This is the forcing term. Return (ret): did price go up or down from last close? Body: did the candle close above or below its open? CLV: did the candle close near the high or near the low of its range? With Option B, the “price action push” is directional: Body is positive on bullish candles, negative on bearish candles. CLV is: near +1 if the candle closes near the high (buying strength), near -1 if it closes near the low (selling strength). So a candle that closes weak (near the low) pushes PPAO downward even if the candle range is large. 2) It decides how much to remember vs forget (the “friction”) This is damping / decay. High volatility (noisy market) → forget faster Low volatility (cleaner market) → remember longer So PPAO adapts: in chop it won’t hold bias for long; in smooth trends it will. 3) It updates a hidden “momentum engine” (state) Internally it keeps two numbers (p and q) that store the market’s impulse with memory. Every candle: it shrinks the old state (decay), rotates it a bit (momentum/volatility creates oscillation), then adds the candle push (forcing). Finally, it converts that hidden state into a 0–100 line: > 50 means the state is aligned bullish, < 50 means it’s aligned bearish. The image below will give you an example of a deep analysis using the Propagator Price Action Oscillator (PPAO). PPAO below 30 What that means mechanically Below 30 = bearish impulse extreme. It happens when the recent candles are consistently “bearish pressure” according to the forcing inputs: returns are negative and/or candles close weak inside their range (CLV negative) and/or bodies are bearish (close < open) Also, if volatility is elevated, damping can make this flip faster and stay extreme during a strong impulse. What it means behaviorally PPAO < 30 is not “prediction.” It is diagnosis: “Recent candle pressure has been strongly bearish.” This can show up in two common market contexts: Continuation context Price is breaking structure down, and candles keep closing weak → PPAO stays < 30. Distribution / hidden weakness context (important) Price may look stable or near a high, but candles are repeatedly closing poorly inside their ranges (negative CLV). That makes PPAO drop under 30 even if price hasn’t collapsed yet. That second case is exactly why Option B (Body + CLV) is useful: it can flag weak closes / selling absorption earlier than “price-only” oscillators. PPAO above 70 What that means mechanically Above 70 = bullish impulse extreme. It occurs when the forcing inputs are strongly positive: returns are positive and/or candles close strong inside their range (CLV positive) and/or bodies are bullish (close > open) If volatility is not exploding, damping won’t erase the accumulated bullish state quickly, so PPAO can stay above 70 during sustained buying pressure. What it means behaviorally Again: not a prophecy, but an impulse read: “Recent candle pressure has been strongly bullish.” Two common contexts: Trend continuation Price is pushing higher and closes are strong → PPAO remains > 70. Exhaustion risk If price is hitting major resistance/liquidity and you start seeing weaker closes (CLV drops) while PPAO stops making new highs → that’s where reversals begin to appear. The key takeaway using both images PPAO extremes are best understood as: Below 30: “Sellers are currently dominating candle pressure.” Above 70: “Buyers are currently dominating candle pressure.” Whether that dominance leads to continuation or reversal depends on what price does next (structure + where you are on the chart). PPAO is measuring pressure, not guaranteeing outcome.
Индикатор Pine Script®
от TheWannaBeQuant
1
AI Academy: Volume k-NN [PhenLabs]📊 AI Academy: Volume k-NN Version: PineScript™ v6 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📌 Description AI Academy: Volume k-NN (Theory Edition) is an educational indicator designed to demystify how artificial intelligence pattern recognition works directly on your TradingView charts. Rather than being a black-box signal generator, this tool visualizes the entire k-Nearest Neighbors algorithm process in real-time, showing you exactly how AI identifies similar historical patterns and generates predictions. The indicator scans up to 2,000 historical bars to find patterns that match your current price action, then uses an ensemble of the closest matches to project potential future movement. What sets this apart is the integrated “AI Grimoire”—an interactive educational book overlay that teaches core machine learning concepts through four illuminating chapters. Whether you’re a trader curious about AI methodology or a developer learning algorithmic concepts, this indicator transforms abstract machine learning theory into tangible, visual understanding. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 Points of Innovation • First TradingView indicator to visualize k-NN algorithm execution in real-time with full transparency • Interactive “AI Grimoire” educational overlay teaches machine learning concepts while you trade • Dual-mode pattern matching combines price action with optional volume confirmation • Confidence-based opacity system visually communicates prediction reliability • Historical match visualization shows exactly which past patterns informed the prediction • Ghost bar projections display averaged ensemble predictions with adjustable forecast horizons ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔧 Core Components • Pattern Capture Engine: Converts recent price action into logarithmic returns for normalized comparison across different price levels • k-NN Search Algorithm: Calculates Euclidean distance between current pattern and historical patterns to find closest matches • Volume Weighting System: Optional feature that incorporates volume patterns into distance calculations with adjustable influence • Ensemble Predictor: Averages future returns from k-nearest historical matches to generate consensus forecast • Confidence Calculator: Measures average distance of top matches to determine prediction reliability on 0-100% scale • AI Grimoire Display: Table-based educational overlay rendering book-style content with chapter navigation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔥 Key Features • Adjustable Pattern Length: Define how many bars constitute the current pattern for matching (5-100 bars) • Configurable Search Depth: Control how far back the algorithm searches for historical matches (500-4,900 bars) • Flexible k-Neighbors: Select how many closest matches inform the prediction (1-20 neighbors) • Volume Toggle: Enable or disable volume pattern matching for different market conditions • Volume Influence Slider: Fine-tune the weight given to volume vs. price patterns (0-100%) • Ghost Bar Count: Adjust how many future bars the indicator projects (3-15 bars) • Minimum Confidence Filter: Set threshold to hide low-confidence predictions • Historical Match Display: Toggle visibility of colored boxes marking source patterns ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎨 Visualization • Blue Scanner Box: Highlights current pattern being analyzed labeled “AI INPUT (The Prompt)” • Green Historical Boxes: Mark past patterns where price subsequently moved bullish • Red Historical Boxes: Mark past patterns where price subsequently moved bearish • Ghost Bars: Semi-transparent candles projecting into the future showing predicted price path • Confidence Label: Displays prediction confidence percentage and number of matches used • AI Grimoire Book: Leather-bound book overlay in top-right corner with navigable chapters ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📖 Usage Guidelines Algorithm Settings • Pattern Length — Default: 20 | Range: 5-100 | Controls how many recent bars define the pattern. Shorter values find more matches but less specific. Longer values find fewer but more precise matches. • Search Depth — Default: 2000 | Range: 500-4900 | Determines how many historical bars to scan. Higher values find more potential matches but increase computation time. • k-Neighbors — Default: 5 | Range: 1-20 | Number of closest matches to use for prediction. Higher values smooth predictions but may dilute strong signals. • Ghost Bar Count — Default: 5 | Range: 3-15 | How many future bars to project. Shorter horizons are typically more reliable. • Use Volume Matching — Default: Off | When enabled, patterns must match on both price AND volume characteristics. • Volume Influence — Default: 30% | Range: 0-100% | Weight given to volume pattern when volume matching is enabled. Visualization Settings • Bullish/Bearish Match Colors — Customize colors for historical match boxes based on outcome direction. • Min Confidence % — Default: 60 | Predictions below this threshold will not display. • Show Historical Matches — Default: On | Toggle visibility of source pattern boxes on chart. Education Settings • Select Chapter — Navigate through AI Grimoire chapters or keep book closed for clean chart view. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Best Use Cases • Learning how k-Nearest Neighbors algorithm functions in a trading context • Understanding the relationship between historical patterns and forward predictions • Identifying when current market conditions resemble past scenarios • Supplementing discretionary analysis with pattern-based confluence • Teaching others machine learning concepts through visual demonstration • Validating whether volume confirms price pattern formations • Building intuition for what AI “sees” when analyzing charts ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ Limitations • Past pattern similarity does not guarantee future outcome similarity • Requires sufficient historical data (minimum 500+ bars) to function properly • Computation-intensive on lower timeframes with maximum search depth • Cannot predict truly novel “black swan” events not represented in historical data • Volume matching less effective on assets with inconsistent volume reporting • Predictions become less reliable as forecast horizon extends further out • Educational overlay may obstruct chart view on smaller screens ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 What Makes This Unique • Full Transparency: Unlike black-box AI tools, every step of the algorithm is visualized on your chart • Integrated Education: The AI Grimoire teaches machine learning concepts without leaving TradingView • Theory Meets Practice: See exactly which historical patterns inform each prediction • Honest Uncertainty: Confidence scoring and opacity fading acknowledge when the AI “doesn’t know” • Dual-Mode Analysis: Optional volume weighting adds institutional-quality analysis dimension ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 How It Works 1. Pattern Capture: On each bar, the indicator captures the most recent price changes as logarithmic returns, creating a normalized “fingerprint” of current market behavior. If volume matching is enabled, volume changes are captured similarly. 2. Historical Search: The algorithm iterates through up to 2,000 historical bars, calculating the Euclidean distance between the current pattern fingerprint and each historical pattern. Distance combines price similarity and optional volume similarity based on weight settings. 3. Neighbor Selection: All historical patterns are ranked by similarity (lowest distance = most similar). The k-closest matches are selected as the “ensemble council” that will inform the prediction. 4. Confidence Calculation: Average distance of top-k matches determines confidence. Tighter clustering of similar patterns yields higher confidence scores, while scattered or distant matches produce lower confidence. 5. Prediction Generation: Future returns from each historical match (what happened AFTER those patterns) are averaged together. This ensemble average is applied to current price to generate ghost bar projections. 6. Visualization: Historical match locations are marked with colored boxes (green for bullish outcomes, red for bearish). Ghost bars render with opacity tied to confidence level—higher confidence means more solid bars. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 Note: This indicator is designed primarily for educational purposes —to help traders understand how AI pattern recognition algorithms function. While the predictions can supplement your analysis, they should never be used as the sole basis for trading decisions. The AI Grimoire chapters explain key concepts including why AI “hallucinates” during unprecedented market events. Always combine with proper risk management and additional confirmation. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Индикатор Pine Script®
от PhenLabs
Apex Wallet - Real-Time Market Volume Delta & Order FlowOverview The Apex Wallet Market Volume Delta is a professional liquidity analysis tool designed to decode the internal structure of market volume. Unlike standard volume bars, this script calculates the "Delta"—the net difference between buying and selling pressure—to reveal the true conviction of market participants in real-time. Dynamic Multi-Mode Intelligence This indicator features an adaptive calculation engine that recalibrates its internal logic based on your trading style: Scalping: Fast-response settings (9-period MA) for immediate execution on low timeframes. Day-Trading: Balanced settings (26-period MA) optimized for intraday sessions. Swing-Trading: High-filter settings (52-period MA) for major trend confirmation. Advanced Order Flow Detection Real-Time Delta Calculation: Tracks the precise interaction between price and volume to identify aggressive buyers vs. passive sellers. Dual Calculation Modes: Choose between "Buy/Sell" (aggressive) or "Buy/Sell/Neutral" for a more granular view of flat market periods. Visual Delta Labels: Displays the net volume values directly above each bar, with color-coded alerts (Green for Bullish Delta, Red for Bearish Delta). Scalable UI: Features a "Scale Down Factor" to simplify large volume numbers into readable units (10/100/1k/10k). Key Features: Visual Split: Clearly differentiates historical volume from real-time buying and selling flows. Trend Confirmation: Integrated optional EMA to compare current volume surges against the average market liquidity. Clean Interface: Professional-grade histogram styling with clear demarcation of session activity.
Индикатор Pine Script®
от Apex-Wallet
Apex Wallet - Bitcoin Halving Cycle & Profit ProjectionOverview The Apex Wallet Bitcoin Halving Cycle Profit is a strategic macro-analysis tool designed for Bitcoin investors and long-term holders. It provides a visual framework of Bitcoin's 4-year cycles by identifying past halving dates and projecting future ones automatically. The script highlights key accumulation and profit-taking windows based on historical cycle performance. Dynamic Cycle Intelligence Halving Milestones: Automatically detects and marks all major halving events (2012, 2016, 2020, 2024) with precise timestamps. Predictive Projections: Using an estimated 1,460-day cycle, the script projects up to 30 future halving events to help plan long-term investment horizons. Timeframe Optimization: Built specifically for Weekly (W) and Monthly (M) charts to provide a clean, high-level perspective of market structure. Key Strategy Visuals Profit Windows: Visualizes "Start" and "End" profit zones with automated vertical lines and color-coded labels based on user-defined offsets from the halving. DCA Chain Signals: Identifies strategic Dollar Cost Averaging (DCA) points throughout the cycle to assist in disciplined accumulation. Heatmap Shading: Features dynamic background shading that intensifies as the cycle progresses toward historical peak performance periods. How to Use: Switch to a Weekly or Monthly Bitcoin chart. Use the Green Labels (Profit START) to identify early cycle strength. Monitor the Red Labels (Profit END) for historical cycle exhaustion zones.
Индикатор Pine Script®
от Apex-Wallet