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PXX Levels by AlgoKingsPXX Levels by AlgoKings RISK DISCLAIMER: This indicator is an analytical tool for educational purposes only, not financial advice. Trading carries substantial risk of loss. This tool does not guarantee profitable trades. Always use proper risk management and never risk more than you can afford to lose. WHAT ARE PXX LEVELS? PXX (Previous X High/Low) displays key support and resistance levels from completed market cycles. Unlike standard pivot indicators that use fixed bars, this tool calculates levels using natural market rhythms (sessions, 90-minute institutional windows, true daily periods) that align with institutional trading behavior. Example: Previous Day High at 15,200 acts as resistance. Previous London session Low at 15,150 acts as support. UNDERLYING METHODOLOGY This indicator combines four analytical layers: 1. CYCLE-BASED PERIOD DETECTION Tracks 10 cycle types across swing and intraday timeframes: SWING CYCLES: - Yearly: 12-month institutional rebalancing highs/lows - Quarterly: 3-month earnings cycle extremes - Monthly: Calendar month highs/lows - Weekly: 7-day swing extremes - Daily: Standard 18:00-18:00 EST bars - TrueDay: 00:00-00:00 EST for 24-hour markets (futures, forex, crypto) INTRADAY CYCLES: - Session: Asia (18:00-02:00), London (02:00-08:30), NY AM (08:30-12:00), NY PM (12:00-17:00) EST - 90m: Three 90-minute institutional windows (LN 1/2/3, AM 1/2/3, PM 1/2/3) - 30m: 30-minute cycle extremes - 10m: 10-minute cycle extremes Technical implementation: - TrueDay calculation: Detects candle closes at exactly 00:00 EST using time modulo arithmetic on 24-hour markets - Session detection: Pattern matching on hour:minute timestamps (e.g., hr==2 and mn==30 triggers London session end at 02:30) - 90m subdivision: Three 90-minute windows per session identified by specific time boundaries - Cycle completion: Uses request.security with lookahead_on to detect when previous period (high , low ) closes 2. LEVEL TRACKING AND STATE MANAGEMENT Proprietary state machine for each level: LEVEL STATES: - Live: Current cycle forming, level updates bar-by-bar as new highs/lows form - Final: Cycle completed, level locked at cycle's high/low - Taken: Price has touched/exceeded the level (mitigation) - Extended: Level continues displaying after cycle completion or mitigation State transitions: - New cycle detected → Create Live level at current high/low - Cycle completes → Transition Live to Final, lock coordinates - Price touches level → Mark as Taken, optional removal from chart - History limit reached → Purge oldest levels Technical components: - Level Object: Tracks y-price, x-start time, x2-current extension, isFinal/isTaken/isLive/isExtend flags - Dynamic extension: Levels extend to current bar (x2 = time) until finalized or taken - Mitigation detection: Compares current high >= level for resistance, low <= level for support 3. OFF-CHART LEVEL BACKFILL Handles higher timeframe levels that formed before chart data: When chart timeframe is lower than cycle period (e.g., 5m chart showing Daily levels), the indicator backfills up to 4 historical cycles using nested request.security calls (high , low , high , low , etc.). These off-chart levels are marked with tag in tooltips. Anchor detection: If price matches an off-chart level's value, the indicator anchors it to the current bar time, removing the off-chart designation and making it actionable. 4. OVERLAP CONSOLIDATION AND PURGE HIERARCHY Advanced filtering to prevent chart clutter: OVERLAP DETECTION: When multiple cycles produce identical levels (same y-price and x2-extension), the indicator combines them into a single visual with merged labels. Example: "P D, P W H" shows Previous Day and Previous Week High coincide. Algorithm compares all levels at barstate.islast, identifies duplicates by y-coordinate and x2-endpoint, undraws lower precedence levels, and appends their names to higher precedence level's tooltip. PURGE HIERARCHY: - "Purge 10m/30m on new 90m Cycle": When 90m cycle completes, removes all 10m and 30m sub-cycle levels from chart - "Purge 90m on new Session Cycle": When Session cycle completes, removes all 90m levels from chart - This prevents clutter by automatically cleaning sub-levels when parent cycle resets Implementation uses array-based tracking where higher cycle types (Session, 90m) hold references to lower cycle Pxx objects, allowing cascading purge operations on cycle completion. WHY CLOSED-SOURCE? This script protects proprietary algorithms: - Cycle boundary detection: Custom logic for TrueDay (00:00 EST detection), Session identification (time-based pattern matching for 5 sessions), 90m subdivision (9 windows per day with specific time triggers), requiring complex hour/minute arithmetic - Off-chart backfill system: Nested request.security calls to retrieve 4 historical cycles with isOffChart flagging and dynamic anchor detection when price revisits historical levels - Level state machine: Multi-state tracking (Live/Final/Taken/Extended) with transition logic, including dynamic y-coordinate updates during Live state and precise finalization timing - Overlap consolidation algorithm: Compares all active levels at each bar using y-coordinate and x2-endpoint matching, merges duplicate levels, preserves highest precedence visual while concatenating names - Purge hierarchy system: Parent-child relationships between cycle types (Session→90m→30m/10m) with cascading cleanup operations triggered on cycle completion events Standard support/resistance indicators show fixed pivot points. This script provides institutional-level cycle tracking with intelligent state management and visual optimization. TECHNICAL COMPONENTS Core structures: - Cycle Object: Tracks cycle type, period string, current bar data, and array of historical CycleBar objects (up to 5 cycles deep) - CycleBar Object: Stores high/low values, timestamps (open, close, high-time, low-time), cycle name, and off-chart status - Level Object: Contains y-price, start/end coordinates, state flags (isFinal, isTaken, isLive, isExtend, isOffChart, isCurrent), and drawing objects (line, labels) - Pxx Object: Manages array of high levels and array of low levels for one cycle type, handles updates/extensions/purging Cycle detection: - TrueDay: Tests hour==0 and minute==0 at time_close OR dayofweek change (excluding Monday for non-crypto) - Session: Matches hour:minute pairs (17:00=ASIA, 02:30=LN, 07:00=AM, 11:30=PM, 16:00=VOID) - 90m: Nine specific time boundaries from 02:30 to 16:00 EST - Default cycles: Uses previous period close time (time ) from request.security HOW TO USE Setup: 1. Apply to any chart (works on all symbols and timeframes) 2. Enable/disable cycle types in settings (Swing Cycles, Intraday Cycles) 3. Configure History count for each cycle (how many previous levels to show) 4. Enable "Live" to see current cycle levels forming in real-time 5. Enable "Extend" to keep levels visible after mitigation Chart Timeframe Requirements: - Swing cycles: Chart TF must be <= cycle period and divide evenly (e.g., Daily requires 1H or lower) - Intraday cycles: Chart TF must divide evenly into cycle (e.g., Session/90m/30m require 30m or lower, 10m requires 10m or lower) - TrueDay: Automatically used instead of Daily on 1H and below for 24-hour markets Interpretation: - Horizontal lines show Previous High (resistance) and Previous Low (support) from completed cycles - "P" prefix = Previous cycle (e.g., "P D H" = Previous Day High) - No prefix = Current cycle forming (e.g., "LN 2 L" = Current London 2nd 90m Low) - Dotted line = Level has been taken (mitigated) - Solid line = Level still active - Dot at left = Level formation point - Label at right = Cycle name and high/low designation - in tooltip = Level formed before chart data, not yet anchored SETTINGS EXPLAINED Time Cycles (Each cycle has 5 settings): - Checkbox: Enable/disable cycle - Color: Line color for this cycle's levels - History: Number of previous cycles to display (1-4, or higher for intraday) - Extend: Keep level visible after mitigation - Live: Show current cycle's level as it forms bar-by-bar Swing Cycles Available: Year, Quarter, Month, Week, Day (uses TrueDay automatically on 1H and below for 24h markets) Intraday Cycles Available: Session (5 sessions per day), 90m (9 windows per day), 30m, 10m Options: - Line Width: Thickness of level lines (default: 1) - Label: Show/hide text labels with size and color options - Show Mitigated: Keep levels on chart after taken (shows as dotted) or remove them - Purge 10m/30m on new 90m Cycle: Auto-remove sub-levels when 90m completes - Purge 90m on new Session Cycle: Auto-remove 90m levels when Session completes Common Configurations: - Scalping: Enable 10m, 30m, 90m with History=1-3, Live=true, Extend=false - Day Trading: Enable Session, 90m, Day with History=1-4, Live=true - Swing Trading: Enable Day, Week, Month with History=1-2, Extend=true - Position Trading: Enable Week, Month, Quarter, Year with Extend=true UPDATES This script is actively maintained. Updates released through TradingView's native update system. For technical questions, use the comment section below.
Penunjuk Pine Script®
oleh AlgoKings_Official
cephxs / Opening Prices + True Opens [Pro +]TRUE OPENS One concept. Five cycles. Zero complexity. THE CONCEPT True Opens are simple: the opening price of Q2 in any cycle . Based on Quarterly Theory. That's it. Every cycle divides into quarters. Q1 sets the range. Q2 establishes the True Open—the price institutions reference for the remainder of the cycle. Q3 and Q4 play out relative to that anchor. This indicator plots True Opens across five nested cycles, from micro to monthly. No signals, no oscillators, no noise—just clean price levels that matter. Credit: The True Open concept was developed and shared publicly by Daye . This indicator is an implementation of that framework. THE FIVE CYCLES Micro TO: ~22.5-minute quarters (64 sessions/day). Ultra-short-term reference for scalpers. 90m TO: Four macro sessions—Asia, London, NY, PM. Each session's Q2 (the second 90 minutes) gives you Asia TO, London TO, NY TO, and PM TO. Daily TO: 6-hour quarters (18:00-00:00, 00:00-06:00, 06:00-12:00, 12:00-18:00 ET). The "True Day" is midnight—the opening price of the 00:00-06:00 session. Weekly TO: Monday = Q1, Tuesday = Q2 (True Week), Wednesday = Q3, Thursday = Q4. The "True Week" is Tuesday's daily open. Monthly TO: Week 1 = Q1, Week 2 = Q2 (True Month), Week 3 = Q3, Week 4 = Q4 (+ distortion days 29-31). The "True Month" is the Monday open of the second trading week. HOW TO USE Add to chart: Enable the cycles relevant to your timeframe. Auto mode handles visibility—lower timeframes see more granular TOs, higher timeframes see only the larger cycles. Watch price relative to TO: Price above TO = bullish bias for that cycle. Price below = bearish bias. Simple. Layer multiple cycles: When micro, 90m, and daily TOs align on the same side, you have confluence across timeframes. Use as magnets: Price often returns to True Opens before continuing. They act as equilibrium points within cycles. Frame your trades: Know which cycle you're trading. Scalping? Reference the micro TO. Swing trading? The weekly TO is your anchor. WHAT MAKES THIS SIMPLE Auto Mode: The indicator automatically shows only the TOs relevant to your chart timeframe—no manual configuration needed Clean Labels: Each TO is labeled by session (Asia TO, London TO, True Day, True Week, True Month) Visual Clarity: Dashed lines while Q2 is active, solid lines once confirmed. You always know which TOs are still forming. No Clutter: Historical TOs auto-cleanup by default. Only the current cycle's TO is shown unless you want history. INPUTS Master Toggles Show Micro/90m/Daily/Weekly/Monthly TO: Enable or disable each cycle independently Show 8:30 Open: Plots the 8:30 ET open (economic news reference) Show 9:30 Open: Plots the equity market open (RTH reference) Display Mode Auto: Uses sensible TF ranges per cycle (recommended) Custom: Define your own TF visibility ranges for each cycle Label Preset Auto: Session-specific labels (Asia TO, London TO, True Day, etc.) Custom Names: Use your own text for each level Time: Shows the bar time (HH:mm) when the TO was captured Line Style Auto: Dashed while Q2 is active, solid after Q2 closes Custom: Choose solid, dashed, or dotted for all lines Colors Customizable colors for each cycle level Separate colors for 8:30 and 9:30 opens Settings Active Line Bar Offset: How far the line extends past current bar Show Historical True Opens: Keep all TOs visible instead of auto-cleanup KEY FEATURES Five Nested Cycles: Micro, 90m, Daily, Weekly, Monthly—all using the same Q2 principle Auto TF Visibility: Each cycle appears only on appropriate timeframes Trading Day Detection: Works correctly for futures, forex, and crypto with different session opens DST-Aware: Uses America/Toronto timezone for automatic daylight saving adjustments Crypto Support: Monthly TO correctly uses Monday's open for 24/7 markets 8:30 & 9:30 Opens: Bonus levels for news and equity open references BEST PRACTICES Start with Auto mode—it's tuned for the most common use cases On 1-5m charts, focus on 90m TOs (Asia, London, NY, PM) On 15m-1H charts, the Daily TO (True Day) becomes your primary reference On 4H+ charts, Weekly and Monthly TOs provide swing trade anchors True Opens work best when combined with other ICT concepts (liquidity, FVGs, order blocks) DISCLAIMER This indicator is for educational purposes only and does not constitute financial advice. True Opens provide context, not signals—always use proper risk management and confirm with your own analysis. Past performance does not guarantee future results. CREDITS True Open concept by Daye (TraderDaye), publicly shared on social media. Implementation by cephxs. Made with ❤️ by cephxs
Penunjuk Pine Script®
oleh fstarcapital
Ichimoku Theories [LuxAlgo]The Ichimoku Theories indicator is the most complete Ichimoku tool you will ever need. Four tools combined into one to harness all the power of Ichimoku Kinkō Hyō. This tool features the following concepts based on the work of Goichi Hosoda: Ichimoku Kinkō Hyō: Original Ichimoku indicator with its five main lines and kumo. Time Theory: automatic time cycle identification and forecasting to understand market timing. Wave Theory: automatic wave identification to understand market structure. Price Theory: automatic identification of developing N waves and possible price targets to understand future price behavior. 🔶 ICHIMOKU KINKŌ HYŌ Ichimoku with lines only, Kumo only and both together Let us start with the basics: the Ichimoku original indicator is a tool to understand the market, not to predict it, it is a trend-following tool, so it is best used in trending markets. Ichimoku tells us what is happening in the market and what may happen next, the aim of the tool is to provide market understanding, not trading signals. The tool is based on calculating the mid-point between the high and low of three pre-defined ranges as the equilibrium price for short (9 periods), medium (26 periods), and long (52 periods) time horizons: Tenkan sen: middle point of the range of the last 9 candles Kinjun sen: middle point of the range of the last 26 candles Senkou span A: middle point between Tankan Sen and Kijun Sen, plotted 26 candles into the future Senkou span B: midpoint of the range of the last 52 candles, plotted 26 candles into the future Chikou span: closing price plotted 26 candles into the past Kumo: area between Senkou pans A and B (kumo means cloud in Japanese) The most basic use of the tool is to use the Kumo as an area of possible support or resistance. 🔶 TIME THEORY Current cycles and forecast Time theory is a critical concept used to identify historical and current market cycles, and use these to forecast the next ones. This concept is based on the Kihon Suchi (translating to "Basic Numbers" in Japanese), these are 9 and 26, and from their combinations we obtain the following sequence: 9, 17, 26, 33, 42, 51, 65, 76, 129, 172, 200, 257 The main idea is that the market moves in cycles with periods set by the Kihon Suchi sequence. When the cycle has the same exact periods, we obtain the Taito Suchi (translating to "Same Number" in Japanese). This tool allows traders to identify historical and current market cycles and forecast the next one. 🔹 Time Cycle Identification Presentation of 4 different modes: SWINGS, HIGHS, KINJUN, and WAVES . The tool draws a horizontal line at the bottom of the chart showing the cycles detected and their size. The following settings are used: Time Cycle Mode: up to 7 different modes Wave Cycle: Which wave to use when WAVE mode is selected, only active waves in the Wave Theory settings will be used. Show Time Cycles: keep a cleaner chart by disabling cycles visualisation Show last X time cycles: how many cycles to display 🔹 Time Cycle Forecast Showcasing the two forecasting patterns: Kihon Suchi and Taito Suchi The tool plots horizontal lines, a solid anchor line, and several dotted forecast lines. The following settings are used: Show time cycle forecast: to keep things clean Forecast Pattern: comes in two flavors Kihon Suchi plots a line from the anchor at each number in the Kihon Suchi sequence. Taito Suchi plot lines from the anchor with the same size detected in the anchored cycle Anchor forecast on last X time cycle: traders can place the anchor in any detected cycle 🔶 WAVE THEORY All waves activated with overlapping The main idea behind this theory is that markets move like waves in the sea, back and forth (making swing lows and highs). Understanding the current market structure is key to having realistic expectations of what the market may do next. The waves are divided into Simple and Complex. The following settings are used: Basic Waves: allows traders to activate waves I, V and N Complex Waves: allows traders to activate waves P, Y and W Overlapping waves: to avoid missing out on any of the waves activated Show last X waves: how many waves will be displayed 🔹 Basic Waves The three basic waves The basic waves from which all waves are made are I, V, and N I wave: one leg moves V wave: two legs move, one against the other N wave: Three legs move, push, pull back, and another push 🔹 Complex Waves Three complex waves There are other waves like P wave: contracting market Y wave: expanding market W wave: double top or double bottom 🔶 PRICE THEORY All targets for the current N wave with their calculations This theory is based on identifying developing N waves and predicting potential price targets based on that developing wave. The tool displays 4 basic targets (V, E, N, and NT) and 3 extended targets (2E and 3E) according to the calculations shown in the chart above. Traders can enable or disable each target in the settings panel. 🔶 USING EVERYTHING TOGETHER Please DON'T do this. This is not how you use it Now the real example: Daily chart of Nasdaq 100 futures (NQ1!) with our Ichimoku analysis Time, waves, and price theories go together as one: First, we identify the current time cycles and wave structure. Then we forecast the next cycle and possible key price levels. We identify a Taito Suchi with both legs of exactly 41 candles on each I wave, both together forming a V wave, the last two I waves are part of a developing N wave, and the time cycle of the first one is 191 candles. We forecast this cycle into the future and get 22nd April as a key date, so in 6 trading days (as of this writing) the market would have completed another Taito Suchi pattern if a new wave and time cycle starts. As we have a developing N wave we can see the potential price targets, the price is actually between the NT and V targets. We have a bullish Kumo and the price is touching it, if this Kumo provides enough support for the price to go further, the market could reach N or E targets. So we have identified the cycle and wave, our expectations are that the current cycle is another Taito Suchi and the current wave is an N wave, the first I wave went for 191 candles, and we expect the second and third I waves together to amount to 191 candles, so in theory the N wave would complete in the next 6 trading days making a swing high. If this is indeed the case, the price could reach the V target (it is almost there) or even the N target if the bulls have the necessary strength. We do not predict the future, we can only aim to understand the current market conditions and have future expectations of when (time), how (wave), and where (price) the market will make the next turning point where one side of the market overcomes the other (bulls vs bears). To generate this chart, we change the following settings from the default ones: Swing length: 64 Show lines: disabled Forecast pattern: TAITO SUCHI Anchor forecast: 2 Show last time cycles: 5 I WAVE: enabled N WAVE: disabled Show last waves: 5 🔶 SETTINGS Show Swing Highs & Lows: Enable/Disable points on swing highs and swing lows. Swing Length: Number of candles to confirm a swing high or swing low. A higher number detects larger swings. 🔹 Ichimoku Kinkō Hyō Show Lines: Enable/Disable the 5 Ichimoku lines: Kijun sen, Tenkan sen, Senkou span A & B and Chikou Span. Show Kumo: Enable/Disable the Kumo (cloud). The Kumo is formed by 2 lines: Senkou Span A and Senkou Span B. Tenkan Sen Length: Number of candles for Tenkan Sen calculation. Kinjun Sen Length: Number of candles for the Kijun Sen calculation. Senkou Span B Length: Number of candles for Senkou Span B calculation. Chikou & Senkou Offset: Number of candles for Chikou and Senkou Span calculation. Chikou Span is plotted in the past, and Senkou Span A & B in the future. 🔹 Time Theory Show Time Cycle Forecast: Enable/Disable time cycle forecast vertical lines. Disable for better performance. Forecast Pattern: Choose between two patterns: Kihon Suchi (basic numbers) or Taito Suchi (equal numbers). Anchor forecast on last X time cycle: Number of time cycles in the past to anchor the time cycle forecast. The larger the number, the deeper in the past the anchor will be. Time Cycle Mode: Choose from 7 time cycle detection modes: Tenkan Sen cross, Kijun Sen cross, Kumo change between bullish & bearish, swing highs only, swing lows only, both swing highs & lows and wave detection. Wave Cycle: Choose which type of wave to detect from 6 different wave types when the time cycle mode is set to WAVES. Show Time Cycles: Enable/Disable time cycle horizontal lines. Disable for better performance. how last X time cycles: Maximum number of time cycles to display. 🔹 Wave Theory Basic Waves: Enable/Disable the display of basic waves, all at once or one at a time. Disable for better performance. Complex Waves: Enable/Disable complex wave display, all at once or one by one. Disable for better performance. Overlapping Waves: Enable/Disable the display of waves ending on the same swing point. Show last X waves: 'Maximum number of waves to display. 🔹 Price Theory Basic Targets: Enable/Disable horizontal price target lines. Disable for better performance. Extended Targets: Enable/Disable extended price target horizontal lines. Disable for better performance.
Penunjuk Pine Script®
oleh LuxAlgo
45
Cycle Phase & ETA Tracker [Robust v4] Cycle Phase & ETA Tracker Description The Cycle Phase & ETA Tracker is a powerful tool for analyzing market cycles and predicting the completion of the current cycle (Estimated Time of Arrival, or ETA). It visualizes the cycle phase (0–100%) using a smoothed signal and displays the forecasted completion date with an optional confidence band based on cycle length variability. Ideal for traders looking to time their trades based on cyclical patterns, this indicator offers flexible settings for robust cycle analysis. Key Features Cycle Phase Visualization: Tracks the current cycle phase (0–100%) with color-coded zones: green (0–33%), blue (33–66%), orange (66–100%). ETA Forecast: Shows a vertical line and label indicating the estimated date of cycle completion. Confidence Band (±σ): Displays a band around the ETA to reflect uncertainty, calculated using the standard deviation of cycle lengths. Multiple Averaging Methods: Choose from three methods to calculate average cycle length: Median (Robust): Uses the median for resilience against outliers. Weighted Mean: Prioritizes recent cycles with linear or quadratic weights. Simple Mean: Applies equal weights to all cycles. Adaptive Cycle Length: Automatically adjusts cycle length based on the timeframe or allows a fixed length. Debug Histogram: Optionally displays the smoothed signal for diagnostic purposes. Setup and Usage Add the Indicator: Search for "Cycle Phase & ETA Tracker " in TradingView’s indicator library and apply it to your chart. Configure Parameters: Core Settings: Track Last N Cycles: Sets the number of recent cycles used to calculate the average cycle length (default: 20). Higher values provide stability but may lag market shifts. Source: Selects the data source for analysis (e.g., close, open, high; default: close price). Use Adaptive Cycle Length?: Enables automatic cycle length adjustment based on timeframe (e.g., shorter for intraday, longer for daily) or uses a fixed length if disabled. Fixed Cycle Length: Defines the cycle length in bars when adaptive mode is off (default: 14). Smaller values increase sensitivity to short-term cycles. Show Debug Histogram: Enables a histogram of the smoothed signal for debugging signal behavior. Cycle Length Estimation: Average Mode: Selects the method for calculating average cycle length: "Median (Robust)", "Weighted Mean", or "Simple Mean". Weights (for Weighted Mean): For "Weighted Mean", chooses "linear" (moderate emphasis on recent cycles) or "quadratic" (strong emphasis on recent cycles). ETA Visualization: Show ETA Line & Label: Toggles the display of the ETA line and date label. Show ETA Confidence Band (±σ): Toggles the confidence band around the ETA, showing the uncertainty range. Band Transparency: Adjusts the transparency of the confidence band (0 = fully transparent, 100 = fully opaque; default: 85). ETA Color: Sets the color for the ETA line, label, and confidence band (default: orange). Interpretation: The cycle phase (0–100%) indicates progress: green for the start, blue for the middle, and orange for the end of the cycle. The ETA line and label show the predicted cycle completion date. The confidence band reflects the uncertainty range (±1 standard deviation) of the ETA. If a warning "Insufficient cycles for ETA" appears, wait for the indicator to collect at least 3 cycles. Limitations Requires at least 3 cycles for reliable ETA and confidence band calculations. On low timeframes or low-volatility markets, zero-crossings may be infrequent, delaying ETA updates. Accuracy depends on proper cycle length settings (adaptive or fixed). Notes Test the indicator across different assets and timeframes to optimize settings. Use the debug histogram to troubleshoot if the ETA appears inaccurate. For feedback or suggestions, contact the author via TradingView. Cycle Phase & ETA Tracker Описание Индикатор Cycle Phase & ETA Tracker предназначен для анализа рыночных циклов и прогнозирования времени завершения текущего цикла (ETA — Estimated Time of Arrival). Он отслеживает фазы цикла (0–100%) на основе сглаженного сигнала и отображает предполагаемую дату завершения цикла с опциональной доверительной полосой, основанной на стандартном отклонении длин циклов. Индикатор идеально подходит для трейдеров, которые хотят выявлять циклические закономерности и планировать свои действия на основе прогнозируемого времени. Ключевые особенности Фазы цикла: Визуализирует текущую фазу цикла (0–100%) с цветовой кодировкой: зеленый (0–33%), синий (33–66%), оранжевый (66–100%). Прогноз ETA: Показывает вертикальную линию и метку с предполагаемой датой завершения цикла. Доверительная полоса (±σ): Отображает зону неопределенности вокруг ETA, основанную на стандартном отклонении длин циклов. Гибкие методы усреднения: Поддерживает три метода расчета средней длины цикла: Median (Robust): Медиана, устойчивая к выбросам. Weighted Mean: Взвешенное среднее, где недавние циклы имеют больший вес (линейный или квадратичный). Simple Mean: Простое среднее с равными весами. Адаптивная длина цикла: Автоматически подстраивает длину цикла под таймфрейм или позволяет задать фиксированную длину. Отладочная гистограмма: Опционально отображает сглаженный сигнал для анализа. Настройка и использование Добавьте индикатор: Найдите "Cycle Phase & ETA Tracker " в библиотеке индикаторов TradingView и добавьте его на график. Настройте параметры: Core Settings: Track Last N Cycles: Количество последних циклов для расчета средней длины (по умолчанию 20). Большие значения дают более стабильные результаты, но могут запаздывать. Source: Источник данных (по умолчанию цена закрытия). Use Adaptive Cycle Length?: Включите для автоматической настройки длины цикла по таймфрейму или отключите для использования фиксированной длины. Fixed Cycle Length: Длина цикла в барах, если адаптивная длина отключена (по умолчанию 14). Show Debug Histogram: Включите для отображения сглаженного сигнала (полезно для отладки). Cycle Length Estimation: Average Mode: Выберите метод усреднения: "Median (Robust)", "Weighted Mean" или "Simple Mean". Weights (for Weighted Mean): Для режима "Weighted Mean" выберите "linear" (умеренный вес для новых циклов) или "quadratic" (сильный вес для новых циклов). ETA Visualization: Show ETA Line & Label: Включите для отображения линии и метки ETA. Show ETA Confidence Band (±σ): Включите для отображения доверительной полосы. Band Transparency: Прозрачность полосы (0 — полностью прозрачная, 100 — полностью непрозрачная, по умолчанию 85). ETA Color: Цвет для линии, метки и полосы (по умолчанию оранжевый). Интерпретация: Фаза цикла (0–100%) показывает прогресс текущего цикла: зеленый — начало, синий — середина, оранжевый — конец. Линия и метка ETA указывают предполагаемую дату завершения цикла. Доверительная полоса показывает диапазон неопределенности (±1 стандартное отклонение). Если отображается предупреждение "Insufficient cycles for ETA", дождитесь, пока индикатор соберет минимум 3 цикла. Ограничения Требуется минимум 3 цикла для надежного расчета ETA и доверительной полосы. На низких таймфреймах или рынках с низкой волатильностью пересечения нуля могут быть редкими, что замедляет обновление ETA. Эффективность зависит от правильной настройки длины цикла (fixedL или адаптивной). Примечания Протестируйте индикатор на разных таймфреймах и активах, чтобы подобрать оптимальные параметры. Используйте отладочную гистограмму для анализа сигнала, если ETA кажется неточным. Для вопросов или предложений по улучшению свяжитесь через TradingView.
Penunjuk Pine Script®
oleh Goldman_Gleb
Kemet Capital [PRO+]█████████████████████████████████████████████████████████████ █─▄▄▄▄█▄─█─▄█▄─▄▄─█─▄▄▄▄█▄─▄▄─█▄─▄█▄─▄─▀█▄─▄█─▄▄▄▄█▄─▀█▀─▄█─▄▄▄█ █─██▄─██▄─▄███▄▄▄─█▄▄▄▄─██▄▄▄─██─███─▄─▀██─██─██▄─██─█▄█─██▄▄▄──█ ▀▄▄▄▄▄▀▀▄▄▄▀▀▄▄▄▄▀▀▄▄▄▄▄▀▄▄▄▄▄▀▄▄▄▀▄▄▄▄▀▀▄▄▄▀▄▄▄▄▄▀▄▄▄▀▄▄▄▀▄▄▄▄▄▀ 🔺 KEMET CAPITAL 🔺 Advanced ICT Quarterly Theory & Sequential SMT Suite ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📖 OVERVIEW Kemet Capital is a comprehensive trading toolkit built on ICT (Inner Circle Trader) concepts, specifically designed around Quarterly Theory and Sequential SMT (Smart Money Technique) divergences. This indicator provides institutional-grade analysis by tracking correlations between related assets and identifying high-probability reversal zones. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚡ KEY FEATURES 🔷 QUARTERLY THEORY CYCLES ━━━━━━━━━━━━━━━━━━━━━━━━━ The market operates in fractal time cycles. This indicator divides each session into four quarters (Q1-Q4), allowing you to identify: • Accumulation (Q1) - Smart money builds positions • Manipulation (Q2) - False moves to trap retail • Distribution (Q3) - The main directional move • Reversion/Continuation (Q4) - Profit-taking or trend continuation Cycles available: ◉ Micro Cycles (22.5 min quarters) ◉ 90-Minute Cycles (Session quarters) ◉ Daily Cycles (6-hour quarters) ◉ Weekly Cycles (Daily quarters) ◉ Monthly Cycles (Weekly quarters) 🔷 SEQUENTIAL SMT (SMART MONEY TECHNIQUE) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SMT divergences occur when correlated assets fail to make the same highs or lows, signaling institutional activity. This indicator tracks TWO types of SMT: ◉ Normal SMT - Divergence on wicks (highs/lows) ◉ Hidden SMT - Divergence on candle bodies (opens/closes) Auto-correlation pairs include: • Indices: NQ/ES/YM, US100/US500/US30 • Metals: XAU/XAG/XPT (Gold/Silver/Platinum) • Crypto: BTC/ETH/ADA • Forex: EUR/GBP/AUD vs USD 📐 Lines automatically anchor to candle wicks and update in real-time! 🔷 TRUE OPENS ━━━━━━━━━━━━━ Key reference levels based on Quarterly Theory: ◉ TMO - True Month Open (Week 2 open) ◉ TWO - True Week Open (Tuesday 00:00 NY) ◉ TDO - True Day Open (00:00 NY / Midnight) ◉ TSO - True Session Open (Q2 of each session) ◉ TMSO - True Micro Session Open These levels act as magnets for price and key support/resistance zones. 🔷 CISD (CHANGE IN STATE OF DELIVERY) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ CISD marks the exact level where the market confirms a change in direction after an SMT divergence. Features: ◉ Normal CISD - Standard confirmation level ◉ HP (High Probability) CISD - Aligned with higher timeframe bias ◉ Auto-invalidation after 2-3 candle body breaks ◉ Pending color (orange) when level is being tested 🔷 STANDARD DEVIATIONS / DEFINING RANGE (DFR) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Projects expansion targets from the Defining Range: • ±1 Standard Deviation • ±2 Standard Deviations • ±2.5 Standard Deviations • ±4 Standard Deviations Available for 90m, Daily, and Weekly cycles. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 HOW TO USE 1️⃣ IDENTIFY THE CYCLE Look at the Q1-Q4 labels to understand where you are in the current cycle. • Q1/Q2 = Wait for manipulation to complete • Q3 = Look for entries in the direction of the move • Q4 = Consider taking profits or trailing stops 2️⃣ WAIT FOR SMT DIVERGENCE When you see an SMT line appear, it signals that correlated assets are diverging - a sign of institutional activity. 3️⃣ CONFIRM WITH CISD Once price breaks the reference candle (creating a CISD level), you have confirmation of the reversal. 4️⃣ TRADE WITH CONFLUENCE Best setups occur when: • SMT appears in Q2 (manipulation phase) • CISD confirms in Q3 direction • Price respects True Open levels • HP CISD aligns with HTF bias ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ SETTINGS 🎨 Theme: Dark / Light mode support 📊 Cycles: Toggle each timeframe independently 🔀 SSMT: Enable/disable Normal and Hidden SMT per cycle 🎯 True Opens: Show/hide each level 📐 DFR: Configure standard deviation projections ⚡ CISD: Control max lines and HP filtering 🤝 Correlation: Auto or Manual pair selection ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📌 RECOMMENDED TIMEFRAMES ◉ Micro Cycles: 1m - 2m ◉ 90m Cycles: 3m - 10m ◉ Daily Cycles: 15m - 30m ◉ Weekly Cycles: 1H - 12H ◉ Monthly Cycles: 4H - 1W ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER This indicator is a technical analysis tool and should not be considered financial advice. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose. Trading involves substantial risk of loss. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏛️ CREDITS Concepts based on ICT (Inner Circle Trader) methodology. Quarterly Theory framework by Daye. Developed by Kemet Capital. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📬 SUPPORT For questions, suggestions, or custom modifications, please reach out through TradingView private messages. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ #ICT #QuarterlyTheory #SMT #SmartMoney #Divergence #CISD #TrueOpen #InstitutionalTrading #PriceAction
Penunjuk Pine Script®
oleh KemetCapital
Daye Quarterly Theory by toodegrees> Introduction and Acknowledgements The Daye Quarterly Theory° tool encompasses the cyclical Time aspect of the markets as studied and developed by Daye (traderdaye on Twitter). I am not the creator of this Theory, and I do not hold the answers to all the questions you may have; I suggest you to study it from Daye's tweets and material. I collaborated directly with Daye to bring a comprehensive Time tool to Tradingview. S/O to @a1tmaniac and @joshuuu for their previous works on this Theory. > Tool Description This is purely a graphical aid for traders to be able to quickly determine Daye's Quarterly Cycles, and save Time while on the charts. The disruptive value of this tool is that it reliably plots forwards in Time, allowing you to strategize and tape read efficiently; as well as calculating all the Cycles, from Micro Sessions, to the Year. 
> Quarterly Theory by Daye The underlying idea is that Time is to be divided in Quarters for correct interpretation of Market Cycles. The specific starting point of a Cycle will depend on the Timeframe at hand.
 Daye being one of the most prominent Inner Circle Trader students, these ideas stem from ICT's concepts themselves, and are to be used hand in hand (PD Array Matrix, PO3, Institutional Price Levels, ...). These Quarters represent: 
A - Accumulation (required for a cycle to occur) 
M - Manipulation 
D - Distribution 
X - Reversal/Continuation The latter are going to always be in this specific sequence; however the cycle can be transposed to have its beginning in X, trivially followed by A, M, and finally D. This feature is not automatic and at the subjective discretion of the Analyst. Note: this theory has been developed on Futures, hence its validity and reliability may change depending on the market Time. This tool does provide a dynamic and auto-adapting aspect to different market types and Times, however they must be seen as experimental. > Quarterly Cycles The Quarterly Cycles currently supported are: Yearly, Monthly, Weekly, Daily, 90 Minute, Micro Sessions. – Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each Q1 - January, February, March Q2 - April, May, June (True Open, April Open) Q3 - July, August, September Q4 - October, November, December Note: this Cycle is the most difficult to optimize as Timeframes become more granular due to the sheer length of its duration. With Time and advancements it will become more accurate. This is the only Cycle for which accuracy is not 100%. – Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day). Q1 - Week 1, first Monday of the month Q2 - Week 2, second Monday of the month (True Open, Daily Candle Open Price) Q3 - Week 3, third Monday of the month Q4 - Week 4, fourth Monday of the month – Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action. Q1 - Monday Q2 - Tuesday (True Open, Daily Candle Open Price) Q3 - Wednesday Q4 - Thursday – Daily Cycle: The Day can be broken down into 6H quarters. These Times roughly define the sessions of the Trading Day, reinforcing the Theory’s validity. Q1 - 18:00 - 00:00, Asian Session Q2 - 00:00 - 06:00, London Session (True Open, Midnight New York Time) Q3 - 06:00 - 12:00, NY Session Q4 - 12:00 - 18:00, PM Session Note: these Times are based on Futures Trading in New York Time, these will vary depending on the market type (experimental). – 90 Minute Cycle: Merely dividing one of the Daily Cycle’s Quarters we obtain 90 minute quarters. The first one in a Trading Day – 90min Cycles of the Asian Session – follows as an example, in New York Time. Q1 - 18:00 - 19:30 Q2 - 19:30 - 21:00 (True Open) Q3 - 21:00 - 22:30 Q4 - 22:30 - 00:00 – Micro Cycle: Lastly, dividing a 90 Minute Cycle yields 22.5 Minute Quarters, known as Micro Sessions. An example breaking down the 90 Minute Cycle from 18:00 to 19:30 follows. Q1 - 18:00 - 18:22:30 Q2 - 18:22:30 - 18:45 (True Open) Q3 - 18:45 - 19:07:30 Q4 - 19:07:30 - 19:30
 Note: trivially, these may not be exact unless the Timeframe is in the seconds, to correctly account for the half minute in each quarter – this said the tool is able to plot these anyways, although slight inaccuracy needs to be taken account depending on the Timeframe. 
It is important to remember and be aware that the current chart’s Timeframe will heavily impact the plotted Time Cycles. This tool is in its initial form and it will be improved and adapted as traders start using it on a daily basis. > Tool Settings Plot Settings: "Plot Type" will allow you to decide how the Cycles will be displayed. Out of the box the tool will be plotted on a separate pane, at the bottom of the chart; you can decide the orientation of the cycles from longest cycle at the bottom (Bottom Pane), or top (Top Pane). Alternatively you can move the tool to the chart and have the cycles plot on price (Move To -> Existing Pane Above), specifically above price (Top), or below (Bottom). The cycles will auto adjust their position based on the visible price action. "Historical Cycles" will show previous Historical Cycles, up to where available in terms of script memory. "Plot Size" will allow you to vary the height of the Cycle’s boxes "Show Labels" will give you an auto-adapting legend which will help you determine which Cycle is which if you get lost. 

The remaining Settings are self explanatory, allowing you to change colors, and choose which Cycles to see. The source of the code is hidden due to the use of private libraries of mine. Happy to answer any questions in terms of code, where I will not be able to divulge any detail that concerns said libraries. Thank you for understanding! Major thanks to Daye for his Time and Knowledge, it was a pleasure to collaborate and work together on this tool. GLGT!
Penunjuk Pine Script®
oleh toodegrees
108
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE) A Three-Pillar Framework for Decoding Institutional Activity 🎓 THEORETICAL FOUNDATION The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture. This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum. ⚡ THE THREE-PILLAR ARCHITECTURE 1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT') Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? " Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market. Formulaic Concept: Coherence = f(Dominance, Synchronization) Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers. Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action. The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions. 2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION') Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? " Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes." Algorithmic Process: Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events. Node Creation: A raw node is created at the mean price of the identified candle. Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level. Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics. 3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING') Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? " Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles. Algorithmic Process: Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle). Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle." Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak). Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum. 🔧 COMPREHENSIVE INPUT SYSTEM Pillar I: Market Coherence Engine Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine. Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise. Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions. Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns. Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation. Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals. Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves. Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals. Pillar II: Harmonic Liquidity Matrix Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints. Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels. Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent. Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike. High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes. Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest. Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes. High (0.6-0.8): Creates wider, more consolidated zones of liquidity. Low (0.2-0.3): Creates more numerous, precise, and distinct levels. Pillar III: Cyclical Resonance Matrix Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance. Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping. Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading. Institutional Signal Architecture Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence. Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency. Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default. Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals. Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts. 🎨 ADVANCED VISUAL SYSTEM The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed. Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes. Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels. Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance. 🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment. Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context. Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent. 💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average. Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry. 🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process." Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim. ⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm. Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy. 📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD) The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status. Header: Displays the script title and version. Coherence Engine Section: State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition. Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing. Liquidity Matrix Section: Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked. Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest. Cycle Matrix Section: Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy. Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation. Signal Status Section: A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color. 🎯 SIGNAL GENERATION LOGIC Aetherium's signal logic is built on the principle of strict, non-negotiable confluence. Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market. Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node. For a Buy Signal: Price must be rejecting the Node from below (testing it as support). For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance). Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction. Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike. Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move. 🚀 ADVANCED TRADING STRATEGIES The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal. The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion. Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target. ⚖️ RESPONSIBLE USAGE AND LIMITATIONS Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future. Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties. Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change. Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal. Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics. 🔮 CONCLUSION The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations. It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm. "In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung — Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
Penunjuk Pine Script®
oleh DskyzInvestments
18
AlgoCados x Gann Toolkit AnalysisAlgoCados x Gann Toolkit Analysis The "AlgoCados x Gann Toolkit Analysis" is an advanced TradingView indicator combining the principles of W.D. Gann’s methodologies with the power of custom anchor points and time cycles. Tailored for traders seeking precision in market timing and price-level analysis, this toolkit integrates the Anchored Square of 9, customizable Gann Fans, and Time cycles. It offers unparalleled flexibility, allowing users to apply Gann’s techniques across different market assets and timeframes by squaring the chart, providing insights into support, resistance, and potential trend reversals. CME_MINI:NQH2025 # Core Functionalities # Gann’s Square of 9 Price Projections This indicator applies Gann’s Square of 9 principles, allowing traders to anchor price projections at significant highs, lows, opens, or closes. By following the Gann Wheel methodology, it calculates critical support and resistance levels through angular shifts, providing accurate projections based on the chosen anchor point. Traders can adjust the anchor to align with various market conditions, refining their analysis according to their preferred starting price. # Gann’s Cycles Time Projection Incorporating Gann’s natural cycles of 144 and 360, this indicator utilizes bar index logic to project time cycles, best suited for unit-based timeframes (e.g., 1 minute, 1 hour, 1 day). These time projections are plotted dynamically, adapting in real time to new data and offering a structured view of Gann’s cyclical approach to market timing. # Customizable Gann Fans The toolkit includes a flexible Gann Fan module that lets traders scale ratios around a user-defined “1x1” ratio, making it adaptable across different assets and timeframes. With seven standard fan lines (1x1, 2x1, 4x1, 8x1, 1x2, 1x4, 1x8), each line is drawn dynamically based on the selected anchor point, providing insights into price action direction and potential support/resistance zones. These fans can be positioned for both bullish and bearish setups. # Square of 4 Projections By dividing Gann’s 360° cycles into four 90° segments, the indicator generates additional projections for more granular analysis. These divisions highlight key support/resistance levels, allowing traders to observe market responses at each 90° increment and identify potential reversal points. By default users will view larger cycles, up to 5760°, to capture significant long-term trends. # Dynamic Labeling and Visualization The indicator features customizable line styles (solid, dotted, dashed) and labeling options (Levels, Prices, Levels + Prices). This flexibility allows traders to create clear, structured chart visuals that reflect their analytical needs. Dynamic labels display degrees and prices for each projection, helping traders understand price movements at a glance. CME_MINI:NQH2025 # Mathematical Foundation and Indicator Logic # Anchor Point Calculation The selected anchor (High, Low, Open, or Close) serves as the baseline for Gann calculations, determining all subsequent projections. Users can control the anchor time and adjust for offsets to optimize alignment with key market events. # Angular Shifts and Square Root Scaling Projections are calculated by applying angular shifts to the square root of the anchor price, with the toolkit generating both positive and negative deviations. This method reveals potential price levels by mapping out a series of support and resistance points based on Gann’s cyclic philosophy. # Time Cycle Analysis_ 144 & 360 Cycles Utilizing the bar index logic, the indicator plots time projections aligned with Gann’s 144 and 360 cycles, which apply best to unit-based timeframes like 1 minute, 1 hour, 1 day, etc. Time cycles are labeled and extended dynamically, ensuring the chart reflects real-time market shifts as new bars are added. # Key Features and Customization Options # Adjustable Angular Shifts and Cycles Angular shifts from 360° to 5760° are available, offering detail from intraday to long-term trends. The Square of 4 cycles enhance analysis by dividing the 360° Gann Wheel into four equal parts, revealing critical resistance/support points within each cycle. # Fully Customizable Projection Lines Projection lines are customizable by style (solid, dotted, dashed) and color, ensuring a clear distinction between equilibrium, support, and resistance levels. The toolkit also includes separate settings for upper and lower deviations, allowing traders to focus on specific market directions. # Flexible Input Settings for Time and Price Users can set anchor points, time cycles, line styles, and labels with precision, tailoring the indicator to any asset, timeframe, or market condition. # Dynamic Labeling and Offsets Each projection line displays dynamic labels that show angular shifts and associated prices, enhancing readability and ease of analysis. Labels can be offset to avoid chart clutter, creating a clean and user-friendly chart. CME_MINI:NQH2025 # Recommended Usage # Time Cycles for Key Market Events Anchor points should align with major highs or lows to reflect accurate time cycles. The toolkit’s flexibility in time cycle selection (1x1, 144, or 360 cycles) ensures precision in market timing analysis. Ideal for unit-based timeframes such as 1 minute, 1 hour, 1 day, 1 week, or 1 month. # Price Levels with Gann Fans Set anchor points on significant highs or lows to apply the Gann Fan tool effectively, projecting key price levels across multiple timeframes; the default fan is set on 1x1 (one price unit for one time unit), the ratio can be manually changed based on the chart specifics. # Square of 4 Analysis Dividing Gann Wheels into 90° segments allows traders to identify critical support and resistance levels within each 360° cycle. This feature is ideal for pinpointing intraday reversals or aligning with long-term trend cycles. # Technical Overview Indicator Name : AlgoCados x Gann Toolkit Analysis Platform Compatibility : TradingView Version : Pine Script v6 License: Mozilla Public License 2.0 Author : AlgoCados, © 2025 Overlay : True (overlays directly on price chart) Core Functions : Anchored Square of 9, Customizable Gann Fans, and Time-Cycles projections Customizable Settings : Anchor time/point, Angular shifts, Time cycles, Fan ratios, Label styles Maximize Gann Analysis Precision with AlgoCados; Healthy with Your Trading!
Penunjuk Pine Script®
oleh AlgoCados
SFC Smart Money Manipulation - Time, Advanced Market StructureThis indicator shows the market structure in more advanced way and different time cycles. Markets moves in cycles and swings. The indicator will help to determine these cycles and swings by time and price. These are the two columns of the market understanding. The third one is volume/ momentum, but it will not be discussed here. Advanced Market Structure According to ICT and Larry Williams Market Structure is not only Highs and Lows. They present more advanced understanding of the MS: -Short Term Highs/ Lows -Intermediate Term Highs/ Lows -Long Term Highs/ Lows Rules of how to determine the Swing Points according to Larry Williams: "A market has made a short-term low when we have a day (or bar if you are using different time periods) that has a higher low on both sides. By the same token a short-term high will be a day (or bar) that has lower bars on both sides of it." "A short-term high with lower short-term highs on both sides is an intermediate- term high. By the same token, a short-term low with higher short-term lows on both sides is an intermediate-term low." "An intermediate-term high with lower intermediate-term highs on both sides of it is just naturally a long-term high by our definition, thanks to understanding market structure. An intermediate-term low with higher intermediate-term lows on both sides of it is just naturally a long-term low by our definition, thanks to understanding market structure." If the Highs and Lows are labeled properly there is high probability to predict the next High or Low. In this way the trader will know how the current trend is changing and what kind of retracement is coming - deep or shallow. Timing Market moves in time cycles. There is a theory that the swings are equal by time and length. This is not always the case, but very very often. Indicator time features: - Swing Trading days - how many time market needed to form a swing. Only Long term(main) Swings are measured. This will help trader to label T-formations. " T Formations is cyclically related for formations that can be drawn to project the time frame of likely turning points. Basically T-formations are based on the concept that the time distance between the starting low/high of the cyclical wave and its peak is likely to be subsequently repeated between that peak and the final low/high of that cycle." - Seasonality - theoretically an asset should go up or down in particular yearly quarter. Practically the direction not always match to quarters. Thats why the indicator shows the theoretical seasonal direction and historical real direction. Seasonal direction is automatically displayed or XAUUSD, XAGUSD, EURUSD, AUDUSD, GBPUSD. There is a ways to set the seasonality manually. - Earnings Season - This time is very important for Stocks and Indices. Most of the time the assets are in bullish trend during the Earnings Seasons. - Monthly separator - Shows the monthly time cycle - Gold bullish months - There are studies on Gold market. They shows that Gold is very bullish in particular months. These are displayed. The indicator works only on Daily Time Frame.
Penunjuk Pine Script®
oleh SerpentForexClub
1
Harmonic Frequency Visualizer [BackQuant]Harmonic Frequency Visualizer Overview Harmonic Frequency Visualizer is a cycle-analysis and cross-asset resonance tool that uses a simplified Discrete Fourier Transform (DFT) to measure how strongly specific cycle periods are present in price. It is not a “trend indicator” and it is not trying to predict direction by itself. Its job is to quantify rhythm: which repeating periods (in bars) are currently dominant, whether those cycles are expanding or contracting (phase direction), and whether multiple instruments are sharing the same dominant periods at the same time (resonance). This indicator has two main output modes: Spectrum : a frequency “snapshot” showing amplitude at each tested period for up to five instruments. Spectrogram : a history heatmap showing how the spectrum evolves through time (for the chart instrument). Spectrum Spectrogram On top of that, it produces a Dominant Cycle Oscillator derived from the dominant cycle’s phase, which gives a continuous cycle position metric (peak/trough style zones) without repainting. This is designed for traders who want cycle context the same way they want volatility context: not as a magic signal, but as structure. What “frequency” and “cycles” mean in trading terms A cycle period (say 21 bars) means: “a repeating pattern that tends to complete one full oscillation every 21 bars.” If price contains such a pattern, the DFT will detect a strong correlation between price and a 21-bar sine/cosine wave. Markets do not have perfectly stable periodic motion, but they often show: Mean-reverting swings around value. Trend pulses with pullback cadence. Volatility clustering that creates rhythmic expansions and contractions. Cycle tools are trying to measure those repeating components, and DFT is the standard mathematical way to do it. Where DFT comes from (the core idea) The Discrete Fourier Transform comes from Fourier analysis, a foundational signal processing concept: Fourier’s idea : any sufficiently well-behaved signal can be expressed as a sum of sine and cosine waves at different frequencies, each with: An amplitude (how strong that wave is). A phase (where you are within the wave cycle). In continuous math you get the Fourier Transform. In sampled data (like candles) you use the Discrete Fourier Transform. It converts a time series (price over time) into a frequency description (strength of different cycles). In markets: Time domain: candles and price series. Frequency domain: cycle periods and their strengths. Why sine and cosine, not just sine A sine wave alone cannot represent every phase alignment cleanly. DFT uses both cosine and sine components because together they form an orthogonal basis that can represent any phase shift. You can think of it like this: Cosine component captures “in-phase” alignment with the cycle. Sine component captures “quadrature” (90-degree shifted) alignment. Combining them gives full information: amplitude + phase. Mathematically, a single frequency component can be written as: A * cos(ωt + φ) But DFT estimates A and φ by separately accumulating cosine and sine projections. How this script implements the DFT (and what it is actually measuring) This is not a full-spectrum FFT across every frequency. It is a targeted DFT across a fixed set of cycle periods: Tested periods The script tests 8 predefined periods: 5, 8, 13, 21, 34, 55, 89, 120 These are Fibonacci-like cycle candidates commonly used in cycle/market structure work. The point is not that Fibonacci is magic. The point is that these represent a reasonable spread from short to long rhythms without needing hundreds of frequencies (which would be heavy in Pine). Normalization step (important) Before computing the DFT, the script normalizes the series: mn = SMA(src, lookback) sd = stdev(src, lookback) norm = (src - mn) / sd (if sd != 0) Why normalize: DFT amplitude depends on the scale of the input series. If you compare BTC and TLT raw prices, the magnitude is meaningless. Z-score normalization makes amplitude more comparable across instruments and regimes. So the spectrum is measuring “cyclical structure in standardized deviations,” not raw dollars. Projection onto cosine and sine For each tested period P: ω = 2π / P (angular frequency for that period) Compute: - sCos = Σ(norm * cos(ωk)) - sSin = Σ(norm * sin(ωk)) Interpretation: You are correlating the last window of normalized price with a cosine wave of period P. And also correlating it with a sine wave of period P. If the price has a strong P-bar rhythm, these sums grow in magnitude. Window length detail The script uses: window = min(lookback - 1, 99) So even if lookback is 200, the internal DFT accumulation caps at 100 bars for performance stability. This is a deliberate trade: stable computation in Pine, while still letting you define normalization lookback and overall context. Amplitude computation Once sCos and sSin are computed: raw magnitude = sqrt(sCos² + sSin²) This is the length of the vector (sCos, sSin). That vector length is the standard way to combine the orthogonal components into one strength metric. Then it scales it into a 0–100 “display amplitude”: amp = sqrt(sCos² + sSin²) / lookback * 100 * sensitivity amp is capped to 100 So: Higher amplitude means stronger alignment with that cycle period. Sensitivity is a user control to amplify or damp the display scaling. Important: amplitude here is not a probability, and it is not guaranteed “signal quality.” It is a standardized “how much of that cycle exists in the recent window” metric. Phase computation Phase is computed using atan2(sSin, sCos). That matters because: A simple atan(sin/cos) fails in different quadrants. atan2 correctly resolves the angle from -π to +π. Phase tells you where you are within the cycle: Two cycles can have same amplitude but opposite phase. Phase is what lets you infer “approaching peak vs trough” behavior. Dominant cycle selection The script chooses the dominant cycle as the period with the highest amplitude among the tested periods: domIdx = argmax(amp ) domAmp = max amplitude domPhase = phase at domIdx This dominant cycle is used for: Spectrogram history matrix (chart symbol). Dominant cycle oscillator. Data window outputs (dominant period, oscillator value). Spectrum View: what you see and how to read it In Spectrum mode, the indicator draws a frequency snapshot for up to five instruments. Each instrument gets a spectrum line (or bars/area depending on style) plotted across the 8 periods on the x-axis, with amplitude (0–100) on the y-axis. X-axis meaning Each x position corresponds to a period (5 → 120 bars). You are not looking at “frequency in Hz.” You are looking at “period in bars,” which is more intuitive in trading. Y-axis meaning Amplitude is a scaled measure of how strongly that period is present in the recent normalized data. Higher means stronger. Plot styles Waveform: connects amplitude points into a continuous shape, best for seeing spectrum shape. Bars: draws vertical bars per period, best for quick comparison. Area: similar to waveform but filled toward baseline for emphasis. Dominant peaks and phase direction labels The script highlights dominant cycles per symbol (if enabled): If max amplitude > 20, it labels that peak with the symbol name. If Show Phase Direction is enabled, it appends ▲ or ▼. Phase direction logic: rising = sin(phase) < 0 ▲ means cycle is in a “rising” phase segment ▼ means cycle is in a “falling” phase segment This is not “price will rise now.” It is “the dominant cycle’s instantaneous phase suggests you are on the upward vs downward half of that oscillation.” In real markets, you use this as context, not as a standalone trade trigger. It also draws small ▲/▼ markers on secondary peaks (amp > 15) to show phase direction of other meaningful cycles, giving you a richer picture than “one dominant period.” Resonance Zones: cross-asset harmonic alignment Resonance is where this tool becomes more than a single-chart curiosity. What resonance means here A resonance zone is flagged when at least 3 out of 5 instruments have strong amplitude at the same tested period. Mechanically: For each period i: - Count instruments with amp > 30 - If count >= 3, mark resonance at that period When resonance is detected: A vertical highlight box is drawn behind that period. A ⚡ marker is printed at the top. Interpretation: Multiple assets are expressing a similar cycle length at the same time. This can indicate macro rhythm, shared liquidity timing, or cross-market synchronization. This is especially useful when your instrument set includes: Rates proxy (TLT), commodities (oil, gold), and crypto indices. You can visually spot when markets are “vibrating” together at a shared period. Resonance is not automatically bullish or bearish. It is telling you “cycle length agreement,” which can help with timing models and contextual trade planning. Spectrogram View: frequency over time Spectrum mode is a snapshot. Spectrogram mode adds time evolution. What a spectrogram is A spectrogram is a 2D heatmap where: Rows = different periods (frequency bands). Columns = time history (bars ago → now). Color = amplitude strength. This allows you to see: Which cycles are persistent vs fleeting. When dominant cycle shifts occur (energy moves from one period to another). Cycle regime transitions (short cycles dominating in chop vs longer cycles dominating in trend). How the script builds the spectrogram matrix It maintains a matrix with: NUM_PERIODS rows (8 periods) histBars columns (history length) Each bar: Remove the oldest column. Append the newest amplitude array from chartSpec. So the spectrogram is always a rolling history of the chart symbol’s cycle amplitudes. It does not attempt to store five symbols (too heavy), it focuses on the active chart for time evolution. Heat coloring Amplitude values map to a custom gradient: Low = dark blue Mid = blue/cyan to orange High = yellow This makes dominant energy bands visually obvious. A stable bright band means persistent cycle dominance. Dominant Cycle Oscillator: phase mapped to a 0–100 oscillator The oscillator is derived from the dominant cycle phase (chart symbol): oscRaw = cos(domPhase) oscValue = 50 + 50 * oscRaw (maps -1..1 into 0..100) Interpretation: When cos(phase) ≈ +1, oscillator near 100 (cycle peak zone). When cos(phase) ≈ -1, oscillator near 0 (cycle trough zone). Midline 50 corresponds to the quarter-cycle transition points. It also colors the oscillator by phase direction: oscRising = sin(domPhase) < 0 Rising phase = green-ish Falling phase = red-ish This gives you a clean timing reference: The dominant period tells you the cycle length. The oscillator tells you where you are within that cycle. It is not forecasting price. It is telling you the current phase position of the strongest detected cycle component. Alerts and practical timing usage Alerts are based on the oscillator: Cross above 80: dominant cycle entering peak zone. Cross below 20: dominant cycle entering trough zone. Cross 50: midline cross (phase transition). In practice, you use these as “timing context” alerts, for example: If your trend model is bullish and cycle oscillator enters trough zone, it can hint at a favorable pullback timing window. If you are mean-reversion trading and cycle peak zone aligns with resistance, that confluence matters. Again: cycle timing needs structure confirmation. The oscillator alone is not a trade system. Multi-instrument design and non-repaint behavior The indicator requests five external instruments via request.security. It uses: close with lookahead_on This forces the data to be “previous confirmed close” so the spectral calculations do not repaint intra-bar. That matters because cycle measures can change drastically within a bar if you let them use live values. So: Spectra for external symbols are based on confirmed historical closes. Chart symbol spectrogram and oscillator are also stable in the sense they depend on confirmed series values (dominant phase updates bar-to-bar). Key parameters and how they change behavior Analysis Lookback Affects normalization and the DFT window cap: Higher lookback stabilizes mean/stdev normalization and reduces random shifts. Lower lookback makes the tool more reactive but more prone to regime noise. Because the inner DFT accumulation caps at 100 bars, very high lookback mostly affects normalization rather than the raw projection length. Sensitivity Scales displayed amplitude: Higher sensitivity makes peaks stand out more. Lower sensitivity compresses amplitude. It is a display control, not a physics constant. View Mode Spectrum: cross-asset snapshot comparison, resonance detection. Spectrogram: time evolution of cycle energy for chart symbol. Show Phase Direction Adds ▲/▼ markers derived from sin(phase). Useful for quick cycle position intuition, but do not treat ▲ as “buy.” Show Resonance Zones Marks periods where many instruments share strong energy. Useful for macro rhythm alignment. Highlight Dominant Cycles Labels peaks. If you disable it, the chart becomes cleaner but less informative. Spectrogram History Controls how many columns are stored. Higher makes a longer heatmap but costs more drawing. Limitations and what not to assume This tool is honest DSP applied to market data, but market data is not a stationary sine wave generator. Key limitations: Cycles drift. Dominant period can shift as regime changes. The tool only tests 8 candidate periods. If the true dominant period is 30, it will express as energy near 34 or distributed across neighbors. Normalization helps comparability, but does not make amplitude “absolute truth.” DFT assumes a stable frequency over the window. Markets often violate that. Phase-based oscillators are timing aids, not predictors. This is why the indicator is best used as: Context for entries/exits, not a standalone system. A way to see when cycle energy concentrates or disperses. A way to detect when multiple markets share a timing rhythm. How to use it properly (workflows) 1) Cycle regime identification If short periods (5–13) dominate, market is often choppy, reactive, and mean-reverting. If mid periods (21–55) dominate, market often shows swing structure. If long periods (89–120) dominate, market can be in slower macro drift, trend legs, or compressed volatility regimes. 2) Timing layer for an existing strategy Use your trend model to decide direction. Use dominant cycle oscillator to decide timing within that direction. Use spectrogram to avoid trading when dominant period is unstable or flipping rapidly. 3) Cross-asset confirmation If you see resonance at a period, watch whether your main instrument is also showing strength there. Resonance can justify holding a cycle-based timing thesis with more confidence because it is not isolated. 4) Expectation management If the spectrum is flat (no peaks above threshold), that is information: No clean dominant cycle, randomness dominates. Cycle-based timing will be unreliable. Summary Harmonic Frequency Visualizer uses a targeted Discrete Fourier Transform across predefined cycle periods to measure amplitude and phase of cyclical components in price. It supports multi-instrument spectrum comparison, resonance detection when several markets share strong energy at the same periods, and a spectrogram heatmap for the chart instrument showing how cycle dominance evolves over time. A dominant cycle oscillator maps phase into a 0–100 timing readout with alerts for peak/trough/midline transitions. It is a cycle context engine designed to complement trend, structure, and risk models, not replace them.
Penunjuk Pine Script®
oleh BackQuant
Quinn-Fernandes Fourier Transform of Filtered Price [Loxx]Down the Rabbit Hole We Go: A Deep Dive into the Mysteries of Quinn-Fernandes Fast Fourier Transform and Hodrick-Prescott Filtering In the ever-evolving landscape of financial markets, the ability to accurately identify and exploit underlying market patterns is of paramount importance. As market participants continuously search for innovative tools to gain an edge in their trading and investment strategies, advanced mathematical techniques, such as the Quinn-Fernandes Fourier Transform and the Hodrick-Prescott Filter, have emerged as powerful analytical tools. This comprehensive analysis aims to delve into the rich history and theoretical foundations of these techniques, exploring their applications in financial time series analysis, particularly in the context of a sophisticated trading indicator. Furthermore, we will critically assess the limitations and challenges associated with these transformative tools, while offering practical insights and recommendations for overcoming these hurdles to maximize their potential in the financial domain. Our investigation will begin with a comprehensive examination of the origins and development of both the Quinn-Fernandes Fourier Transform and the Hodrick-Prescott Filter. We will trace their roots from classical Fourier analysis and time series smoothing to their modern-day adaptive iterations. We will elucidate the key concepts and mathematical underpinnings of these techniques and demonstrate how they are synergistically used in the context of the trading indicator under study. As we progress, we will carefully consider the potential drawbacks and challenges associated with using the Quinn-Fernandes Fourier Transform and the Hodrick-Prescott Filter as integral components of a trading indicator. By providing a critical evaluation of their computational complexity, sensitivity to input parameters, assumptions about data stationarity, performance in noisy environments, and their nature as lagging indicators, we aim to offer a balanced and comprehensive understanding of these powerful analytical tools. In conclusion, this in-depth analysis of the Quinn-Fernandes Fourier Transform and the Hodrick-Prescott Filter aims to provide a solid foundation for financial market participants seeking to harness the potential of these advanced techniques in their trading and investment strategies. By shedding light on their history, applications, and limitations, we hope to equip traders and investors with the knowledge and insights necessary to make informed decisions and, ultimately, achieve greater success in the highly competitive world of finance. █ Fourier Transform and Hodrick-Prescott Filter in Financial Time Series Analysis Financial time series analysis plays a crucial role in making informed decisions about investments and trading strategies. Among the various methods used in this domain, the Fourier Transform and the Hodrick-Prescott (HP) Filter have emerged as powerful techniques for processing and analyzing financial data. This section aims to provide a comprehensive understanding of these two methodologies, their significance in financial time series analysis, and their combined application to enhance trading strategies. █ The Quinn-Fernandes Fourier Transform: History, Applications, and Use in Financial Time Series Analysis The Quinn-Fernandes Fourier Transform is an advanced spectral estimation technique developed by John J. Quinn and Mauricio A. Fernandes in the early 1990s. It builds upon the classical Fourier Transform by introducing an adaptive approach that improves the identification of dominant frequencies in noisy signals. This section will explore the history of the Quinn-Fernandes Fourier Transform, its applications in various domains, and its specific use in financial time series analysis. History of the Quinn-Fernandes Fourier Transform The Quinn-Fernandes Fourier Transform was introduced in a 1993 paper titled "The Application of Adaptive Estimation to the Interpolation of Missing Values in Noisy Signals." In this paper, Quinn and Fernandes developed an adaptive spectral estimation algorithm to address the limitations of the classical Fourier Transform when analyzing noisy signals. The classical Fourier Transform is a powerful mathematical tool that decomposes a function or a time series into a sum of sinusoids, making it easier to identify underlying patterns and trends. However, its performance can be negatively impacted by noise and missing data points, leading to inaccurate frequency identification. Quinn and Fernandes sought to address these issues by developing an adaptive algorithm that could more accurately identify the dominant frequencies in a noisy signal, even when data points were missing. This adaptive algorithm, now known as the Quinn-Fernandes Fourier Transform, employs an iterative approach to refine the frequency estimates, ultimately resulting in improved spectral estimation. Applications of the Quinn-Fernandes Fourier Transform The Quinn-Fernandes Fourier Transform has found applications in various fields, including signal processing, telecommunications, geophysics, and biomedical engineering. Its ability to accurately identify dominant frequencies in noisy signals makes it a valuable tool for analyzing and interpreting data in these domains. For example, in telecommunications, the Quinn-Fernandes Fourier Transform can be used to analyze the performance of communication systems and identify interference patterns. In geophysics, it can help detect and analyze seismic signals and vibrations, leading to improved understanding of geological processes. In biomedical engineering, the technique can be employed to analyze physiological signals, such as electrocardiograms, leading to more accurate diagnoses and better patient care. Use of the Quinn-Fernandes Fourier Transform in Financial Time Series Analysis In financial time series analysis, the Quinn-Fernandes Fourier Transform can be a powerful tool for isolating the dominant cycles and frequencies in asset price data. By more accurately identifying these critical cycles, traders can better understand the underlying dynamics of financial markets and develop more effective trading strategies. The Quinn-Fernandes Fourier Transform is used in conjunction with the Hodrick-Prescott Filter, a technique that separates the underlying trend from the cyclical component in a time series. By first applying the Hodrick-Prescott Filter to the financial data, short-term fluctuations and noise are removed, resulting in a smoothed representation of the underlying trend. This smoothed data is then subjected to the Quinn-Fernandes Fourier Transform, allowing for more accurate identification of the dominant cycles and frequencies in the asset price data. By employing the Quinn-Fernandes Fourier Transform in this manner, traders can gain a deeper understanding of the underlying dynamics of financial time series and develop more effective trading strategies. The enhanced knowledge of market cycles and frequencies can lead to improved risk management and ultimately, better investment performance. The Quinn-Fernandes Fourier Transform is an advanced spectral estimation technique that has proven valuable in various domains, including financial time series analysis. Its adaptive approach to frequency identification addresses the limitations of the classical Fourier Transform when analyzing noisy signals, leading to more accurate and reliable analysis. By employing the Quinn-Fernandes Fourier Transform in financial time series analysis, traders can gain a deeper understanding of the underlying financial instrument. Drawbacks to the Quinn-Fernandes algorithm While the Quinn-Fernandes Fourier Transform is an effective tool for identifying dominant cycles and frequencies in financial time series, it is not without its drawbacks. Some of the limitations and challenges associated with this indicator include: 1. Computational complexity: The adaptive nature of the Quinn-Fernandes Fourier Transform requires iterative calculations, which can lead to increased computational complexity. This can be particularly challenging when analyzing large datasets or when the indicator is used in real-time trading environments. 2. Sensitivity to input parameters: The performance of the Quinn-Fernandes Fourier Transform is dependent on the choice of input parameters, such as the number of harmonic periods, frequency tolerance, and Hodrick-Prescott filter settings. Choosing inappropriate parameter values can lead to inaccurate frequency identification or reduced performance. Finding the optimal parameter settings can be challenging, and may require trial and error or a more sophisticated optimization process. 3. Assumption of stationary data: The Quinn-Fernandes Fourier Transform assumes that the underlying data is stationary, meaning that its statistical properties do not change over time. However, financial time series data is often non-stationary, with changing trends and volatility. This can limit the effectiveness of the indicator and may require additional preprocessing steps, such as detrending or differencing, to ensure the data meets the assumptions of the algorithm. 4. Limitations in noisy environments: Although the Quinn-Fernandes Fourier Transform is designed to handle noisy signals, its performance may still be negatively impacted by significant noise levels. In such cases, the identification of dominant frequencies may become less reliable, leading to suboptimal trading signals or strategies. 5. Lagging indicator: As with many technical analysis tools, the Quinn-Fernandes Fourier Transform is a lagging indicator, meaning that it is based on past data. While it can provide valuable insights into historical market dynamics, its ability to predict future price movements may be limited. This can result in false signals or late entries and exits, potentially reducing the effectiveness of trading strategies based on this indicator. Despite these drawbacks, the Quinn-Fernandes Fourier Transform remains a valuable tool for financial time series analysis when used appropriately. By being aware of its limitations and adjusting input parameters or preprocessing steps as needed, traders can still benefit from its ability to identify dominant cycles and frequencies in financial data, and use this information to inform their trading strategies. █ Deep-dive into the Hodrick-Prescott Fitler The Hodrick-Prescott (HP) filter is a statistical tool used in economics and finance to separate a time series into two components: a trend component and a cyclical component. It is a powerful tool for identifying long-term trends in economic and financial data and is widely used by economists, central banks, and financial institutions around the world. The HP filter was first introduced in the 1990s by economists Robert Hodrick and Edward Prescott. It is a simple, two-parameter filter that separates a time series into a trend component and a cyclical component. The trend component represents the long-term behavior of the data, while the cyclical component captures the shorter-term fluctuations around the trend. The HP filter works by minimizing the following objective function: Minimize: (Sum of Squared Deviations) + λ (Sum of Squared Second Differences) Where: 1. The first term represents the deviation of the data from the trend. 2. The second term represents the smoothness of the trend. 3. λ is a smoothing parameter that determines the degree of smoothness of the trend. The smoothing parameter λ is typically set to a value between 100 and 1600, depending on the frequency of the data. Higher values of λ lead to a smoother trend, while lower values lead to a more volatile trend. The HP filter has several advantages over other smoothing techniques. It is a non-parametric method, meaning that it does not make any assumptions about the underlying distribution of the data. It also allows for easy comparison of trends across different time series and can be used with data of any frequency. Another significant advantage of the HP Filter is its ability to adapt to changes in the underlying trend. This feature makes it particularly well-suited for analyzing financial time series, which often exhibit non-stationary behavior. By employing the HP Filter to smooth financial data, traders can more accurately identify and analyze the long-term trends that drive asset prices, ultimately leading to better-informed investment decisions. However, the HP filter also has some limitations. It assumes that the trend is a smooth function, which may not be the case in some situations. It can also be sensitive to changes in the smoothing parameter λ, which may result in different trends for the same data. Additionally, the filter may produce unrealistic trends for very short time series. Despite these limitations, the HP filter remains a valuable tool for analyzing economic and financial data. It is widely used by central banks and financial institutions to monitor long-term trends in the economy, and it can be used to identify turning points in the business cycle. The filter can also be used to analyze asset prices, exchange rates, and other financial variables. The Hodrick-Prescott filter is a powerful tool for analyzing economic and financial data. It separates a time series into a trend component and a cyclical component, allowing for easy identification of long-term trends and turning points in the business cycle. While it has some limitations, it remains a valuable tool for economists, central banks, and financial institutions around the world. █ Combined Application of Fourier Transform and Hodrick-Prescott Filter The integration of the Fourier Transform and the Hodrick-Prescott Filter in financial time series analysis can offer several benefits. By first applying the HP Filter to the financial data, traders can remove short-term fluctuations and noise, effectively isolating the underlying trend. This smoothed data can then be subjected to the Fourier Transform, allowing for the identification of dominant cycles and frequencies with greater precision. By combining these two powerful techniques, traders can gain a more comprehensive understanding of the underlying dynamics of financial time series. This enhanced knowledge can lead to the development of more effective trading strategies, better risk management, and ultimately, improved investment performance. The Fourier Transform and the Hodrick-Prescott Filter are powerful tools for financial time series analysis. Each technique offers unique benefits, with the Fourier Transform being adept at identifying dominant cycles and frequencies, and the HP Filter excelling at isolating long-term trends from short-term noise. By combining these methodologies, traders can develop a deeper understanding of the underlying dynamics of financial time series, leading to more informed investment decisions and improved trading strategies. As the financial markets continue to evolve, the combined application of these techniques will undoubtedly remain an essential aspect of modern financial analysis. █ Features Endpointed and Non-repainting This is an endpointed and non-repainting indicator. These are crucial factors that contribute to its usefulness and reliability in trading and investment strategies. Let us break down these concepts and discuss why they matter in the context of a financial indicator. 1. Endpoint nature: An endpoint indicator uses the most recent data points to calculate its values, ensuring that the output is timely and reflective of the current market conditions. This is in contrast to non-endpoint indicators, which may use earlier data points in their calculations, potentially leading to less timely or less relevant results. By utilizing the most recent data available, the endpoint nature of this indicator ensures that it remains up-to-date and relevant, providing traders and investors with valuable and actionable insights into the market dynamics. 2. Non-repainting characteristic: A non-repainting indicator is one that does not change its values or signals after they have been generated. This means that once a signal or a value has been plotted on the chart, it will remain there, and future data will not affect it. This is crucial for traders and investors, as it offers a sense of consistency and certainty when making decisions based on the indicator's output. Repainting indicators, on the other hand, can change their values or signals as new data comes in, effectively "repainting" the past. This can be problematic for several reasons: a. Misleading results: Repainting indicators can create the illusion of a highly accurate or successful trading system when backtesting, as the indicator may adapt its past signals to fit the historical price data. This can lead to overly optimistic performance results that may not hold up in real-time trading. b. Decision-making uncertainty: When an indicator repaints, it becomes challenging for traders and investors to trust its signals, as the signal that prompted a trade may change or disappear after the fact. This can create confusion and indecision, making it difficult to execute a consistent trading strategy. The endpoint and non-repainting characteristics of this indicator contribute to its overall reliability and effectiveness as a tool for trading and investment decision-making. By providing timely and consistent information, this indicator helps traders and investors make well-informed decisions that are less likely to be influenced by misleading or shifting data. Inputs Source: This input determines the source of the price data to be used for the calculations. Users can select from options like closing price, opening price, high, low, etc., based on their preferences. Changing the source of the price data (e.g., from closing price to opening price) will alter the base data used for calculations, which may lead to different patterns and cycles being identified. Calculation Bars: This input represents the number of past bars used for the calculation. A higher value will use more historical data for the analysis, while a lower value will focus on more recent price data. Increasing the number of past bars used for calculation will incorporate more historical data into the analysis. This may lead to a more comprehensive understanding of long-term trends but could also result in a slower response to recent price changes. Decreasing this value will focus more on recent data, potentially making the indicator more responsive to short-term fluctuations. Harmonic Period: This input represents the harmonic period, which is the number of harmonics used in the Fourier Transform. A higher value will result in more harmonics being used, potentially capturing more complex cycles in the price data. Increasing the harmonic period will include more harmonics in the Fourier Transform, potentially capturing more complex cycles in the price data. However, this may also introduce more noise and make it harder to identify clear patterns. Decreasing this value will focus on simpler cycles and may make the analysis clearer, but it might miss out on more complex patterns. Frequency Tolerance: This input represents the frequency tolerance, which determines how close the frequencies of the harmonics must be to be considered part of the same cycle. A higher value will allow for more variation between harmonics, while a lower value will require the frequencies to be more similar. Increasing the frequency tolerance will allow for more variation between harmonics, potentially capturing a broader range of cycles. However, this may also introduce noise and make it more difficult to identify clear patterns. Decreasing this value will require the frequencies to be more similar, potentially making the analysis clearer, but it might miss out on some cycles. Number of Bars to Render: This input determines the number of bars to render on the chart. A higher value will result in more historical data being displayed, but it may also slow down the computation due to the increased amount of data being processed. Increasing the number of bars to render on the chart will display more historical data, providing a broader context for the analysis. However, this may also slow down the computation due to the increased amount of data being processed. Decreasing this value will speed up the computation, but it will provide less historical context for the analysis. Smoothing Mode: This input allows the user to choose between two smoothing modes for the source price data: no smoothing or Hodrick-Prescott (HP) smoothing. The choice depends on the user's preference for how the price data should be processed before the Fourier Transform is applied. Choosing between no smoothing and Hodrick-Prescott (HP) smoothing will affect the preprocessing of the price data. Using HP smoothing will remove some of the short-term fluctuations from the data, potentially making the analysis clearer and more focused on longer-term trends. Not using smoothing will retain the original price fluctuations, which may provide more detail but also introduce noise into the analysis. Hodrick-Prescott Filter Period: This input represents the Hodrick-Prescott filter period, which is used if the user chooses to apply HP smoothing to the price data. A higher value will result in a smoother curve, while a lower value will retain more of the original price fluctuations. Increasing the Hodrick-Prescott filter period will result in a smoother curve for the price data, emphasizing longer-term trends and minimizing short-term fluctuations. Decreasing this value will retain more of the original price fluctuations, potentially providing more detail but also introducing noise into the analysis. Alets and signals This indicator featues alerts, signals and bar coloring. You have to option to turn these on/off in the settings menu. Maximum Bars Restriction This indicator requires a large amount of processing power to render on the chart. To reduce overhead, the setting "Number of Bars to Render" is set to 500 bars. You can adjust this to you liking. █ Related Indicators and Libraries Goertzel Cycle Composite Wave Goertzel Browser Fourier Spectrometer of Price w/ Extrapolation Forecast Fourier Extrapolator of 'Caterpillar' SSA of Price Normalized, Variety, Fast Fourier Transform Explorer Real-Fast Fourier Transform of Price Oscillator Real-Fast Fourier Transform of Price w/ Linear Regression Fourier Extrapolation of Variety Moving Averages Fourier Extrapolator of Variety RSI w/ Bollinger Bands Fourier Extrapolator of Price w/ Projection Forecast Fourier Extrapolator of Price STD-Stepped Fast Cosine Transform Moving Average Variety RSI of Fast Discrete Cosine Transform loxfft
Penunjuk Pine Script®
oleh loxx
6
BTI - Bitcoin (BTC) Top Indicator [Logue]Bitcoin top indicator. This indicator is a combination of multiple on-chain and seasonality BTC macro cycle top indicators, plus the Pi-Cycle top moving average. Because there is no magic single indicator to detect macro cycle tops in bitcoin, the BTI detects confluence of multiple indicators to select tops of each BTC macro cycle. The individual indicators used for the BTI are: 1) Cumulative Value Days Destroyed (CVDD) - The CVDD was created by Willy Woo and is the ratio of the cumulative value of Coin Days Destroyed in USD and the market age (in days). While this indicator is used to detect bottoms normally, an extension is used to allow detection of BTC tops. When the BTC price goes above the CVDD extension, BTC is generally considered to be overvalued. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. This indicator is triggered when the BTC price is above the CVDD extension. 2) Net Unrealized Profit Loss (NUPL) - The NUPL measures the profit state of the bitcoin network to determine if past transfers of BTC are currently in an unrealized profit or loss state. Values above zero indicate that the network is in overall profit, while values below zero indicate the network is in overall loss. Highly positive NUPL values indicate overvaluation of the BTC network. Based on decreasing "strength" of BTC tops, a decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops. Therefore, future trigger values can be calculated over time. This indicator is triggered when the NUPL is above the trigger value. 3) Market Value-Realized Value Z-score (MVRV-Z) - The MVRV-Z measures the value of the bitcoin network by comparing the market cap to the realized value and dividing by the standard deviation of the market cap (market cap – realized cap) / std(market cap)). When the market value is significantly higher than the realized value, the bitcoin network is "overvalued". Very high values have signaled cycle tops in the past. This indicator is triggered when the MVRVZ value is above 55. 4) Puell multiple (PUELL) - PUELL is the ratio between the daily coin issuance in USD and its 365-day moving average. This multiple helps to measure miner profitability. When the PUELL goes to extremely high values relative to historical values, it indicates the profitability of the miners is very high and a top may be near. This indicator triggers when the PUELL is above 3.33. 5) Calendar Seasonality Index (CSI) - The CSI takes advantage of the consistency of BTC cycles. Past cycles have formed macro tops every four years between October 21st and December 12th. Therefore, this indicator triggers at set times that are marked every four years between these two dates. 6) Halving Seasonality Index (HSI) - The HSI, as with the CSI, takes advantage of the consistency of BTC cycles following the major event that is the halving. Aside from the first halving cycle, cycles have formed macro tops approximately 538 days after each halving. Therefore, this indicator triggers at set times that are marked 528 to 548 days (i.e., 538 +- 10 days) after each halving. 7) Polylog Regression (PLR) - The BTC cycle tops and bottoms were separately fit using a polynomial regression for the PLR. The bottom band was fit on much more data than the top band, so is likely to be more reliable. The shape of the regression into the future was estimated, so may not be accurate into the future, but is the best fit of tops and bottoms to date. This indicator is used to estimate when tops and bottoms are near when the price goes into the top or bottom bands. This triggers when the BTC price is inside or above the upper polylog regression channel. 8) Realized Price (RP) - The RP is summation of the value of each BTC when it last moved divided by the total number of BTC in circulation. This gives an estimation of the average "purchase" price of BTC on the bitcoin network based on when it was last transacted. This indicator tells us if the average network participant is in a state of profit or loss. This indicator is normally used to detect BTC bottoms, but an extension can be used to detect when the bitcoin network is "highly" overvalued. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. This indicator triggers when the BTC price is above the realized price extension. 9) Pi-cycle Top (PCT) - The PCT indicator is simply the cross of the 111-day moving average above a 2x multiple of the 350-day moving average of the BTC price. While there is no fundamental reasoning behind why this works, it has worked to indicate previous bitcoin tops by taking advantage of the cyclicality of the BTC price and measurement overextension of BTC price. This indicator triggers when the fast moving average (111-day) crosses above the 2x multiple of the slow moving average (350-day). 10) Transaction Fee Spike (TFS) - Transaction fees on the bitcoin network can signal a mania phase when they increase well above historical values. This mania phase may indicate we are near a top in the BTC price. The daily transaction fee total in USD is divided by the number of daily transactions to calculate the average transaction fee paid on the bitcoin network. The transaction fees increasing above $40 trigger this indicator. The on-chain indicators (CVDD, NUPL, MVRV-Z, PUELL, RP, and TFS) work together to give a health check of the BTC price as compared to its network health. The seasonality indicators (CSI, HSI, and PLR) work together to map the macro cycles of BTC. The PCT gives a view of the overvaluation of the BTC price. Each of these indicators is weighted evenly when selected and if over 45% of the indicators are triggering on a candle (i.e., at least 5 of 10), the overall BTI indicator prints a clear signal -- a red dot with a white middle portion between the white horizontal lines at the top of the indicator. This signal is meant to indicate when the macro cycle top is likely already hit or is near. Each of the individual indicators used for the BTI are proven macro top indicators over multiple cycles. Each of the individual indicators are shown in their own rows to visualize which indicators are triggering. You are able to deselect any indicator you do not wish to have considered and select it back again. To prepare you for indicators triggering, the BTI shows dark blue or dark green when the indicator is close to triggering (i.e., generally around 20% from the trigger value, a less intense background will appear, and 10% from the trigger value, a more intense background will appear). The color of the individual indicators turns pink when they are triggered. The background color of the BTI becomes blue when at least 30% of the indicators considered are triggering and it becomes purple/pink when the BTI fully triggers. See the BTC chart above the indicator showing the performance of the indicator in picking out macro top regions (red dots with white middle portion). Because not all daily data for BTC can be shown on one chart, ensure you also play with the indictor yourself. The BLX is most appropriate, but the indicator works on all BTC/USD charts. Because of the limits imposed by TradingView, the indicator doesn't work on time frames lower than 4 h or higher than the weekly. You can use this indicator to help you understand when the BTC price is more likely topping based on past performance of these indicators. This indicator pairs with the BBI (Bitcoin (BTC) Bottom Indictor) and the BTB (Bitcoin Top and Bottom indicator). Use this indicator at your own risk. I make no assertions that this indicator will work to detect any future top since we all know that past performance is no guarantee of future results.
Penunjuk Pine Script®
oleh Da_Prof
48
dmn's ICT AMD-Goldbach█ OVERVIEW This script is built on ICT time & price theory and the theory of algorithmic market maker models, and visualizes the intraday divided using powers of three into accumulation, manipulation and distribution cycles. It also includes an automatically calculated and plotted Goldbach level (a.k.a. IPDA level or Huddleston level) overlay, to help visualize where in the current market maker profile price is in relation to the AMD cycles, and where it might trade to. █ CONCEPTS Accumulation, Manipulation, Distribution Cycles A 24 hour day, with the default set to start at 20:00 CET (the start of the Forex CLS Settlement operational timeline) is split in three parts - 9, 6 and 9 hours for the three cycles (roughly corresponding with Asia, London Open and New York + London Close sessions). Since charts are fractals, there's also intra-cycle time fibs available in the script, to highlight the smaller fractal equivalents in each cycle. These cycles are used to visualize the three phases (AMD) for easier identification of the current daily profile by analyzing during what cycle highs and lows of the day are made. An example of a bullish day could be price rallying before making a low during the accumulation cycle, being manipulated higher and retracing to form an optimal trade entry during the manipulation cycle, expanding and creating the high of the day before selling off during the distribution cycle, with a potential reversal before it ends. Goldbach levels The Goldbach levels are based on the size of a price range (or price swing, if you will) expressed as a factor of power of three (3^n). To decide what number to tell the script to use for the calculation, we look at what 3^n number best fits an average swing on the preferred timeframe we're trading. For example; PO3 27 (3^3)might be fit for scalping, while PO3 243 (3^5) may correspond to the daily or weekly range, depending on the asset. The script then calculates a range high and a range low using a power of three formula based on the current price and divides it into levels using Goldbach numbers. At these levels one might expect to see price form various "blocks" as defined in concept by Michael J. Huddleston. The blocks that correspond to the Goldbach levels are labeled with abbreviations as follows: Ext = External range Low = Range low High = Range high FVG = Fair value gap RB = Rejection block OB = Order block LV = Liquidity void BR = Breaker MB = Mitigation block Using these levels and said blocks we identify where in the current running market maker profile price is offered, and trade the preferred timeframe in line with the AMD cycles accordingly. █ FEATURES Custom AMD time cycles session times. Custom time fib for fractal cycles. Color and style customization. Show only current or also historical cycles. Equilibrium mode for Goldbach levels (show only high/low and midpoint) Autodetection of asset type, with manual override. █ NOTE The default timings for the AMD cycles are set up for Forex pairs. For other asset types, such as indices, other timings are nessecary for optimal results. Goldbach levels requires the correct symbol type setting for the calculation to work properly. Disable the script's autodetection and enable/disable the Forex option according to the type of chart if it fails.
Penunjuk Pine Script®
oleh fxdmn
128
StatX's TT | AMD | Goldbach | Fractal [Beta v2] - For FreeStatX's TT | AMD | Goldbach | Fractal |TT|AMD|GB|Fractal| By StatX is a comprehensive institutional trading toolkit that combines advanced price grid mathematics with time-based delivery cycles. This indicator merges the statistical power of the MXGB Engine (Automatic Power of 3 calculations) with a fully customizable AMD (Accumulation, Manipulation, Distribution) session overlay. This tool is designed to frame the market in both Price (using algorithmic grids) and Time (using session-based cycles), providing a complete roadmap for price delivery. 1. The MXGB Statistical Engine (Auto PO3) At the heart of the indicator is the MXGB Engine, which automatically detects the volatility of the asset and assigns the correct "Power of 3" (PO3) grid size. Hybrid Calculation: Intelligently combines Timeframe analysis with Statistical Volatility (ATR/Volume) to find the perfect grid size (e.g., 27, 81, 243). Adaptability: Works seamlessly on Forex, Crypto (BTC/ETH), and Indices (NAS100/US30) without manual tweaking. Manual Override: You can force specific PO3 presets (1/3, 9, 27, 81, 243, etc.) if you have a specific thesis. 2. GB & TT Grid Systems The indicator projects horizontal levels based on mathematical ratios used in algorithmic pricing. GB (Goldbach/Standard): The classic grid dividing ranges into quadrants and octants. Perfect for standard range trading. TT (Twin Towers): A specialized grid variation with unique node ratios (0.14, 0.26, 0.60, etc.) designed for specific algo-delivery signatures. IPDA Labels: Levels are labeled with institutional terminology (Premium/Discount, Old High/Low, EQ, Rejection Blocks, etc.) rather than just numbers. 3. AMD (Accumulation, Manipulation, Distribution) A brand new, fully customizable Time-Price section. Projected Sessions: As soon as a session starts (e.g., London Open), the indicator draws a box projected to the end of that session. This frames the "Playing Field" for the current session instantly. Time Cycles: Vertical lines are drawn within the session box at specific harmonic time intervals (0.375, 0.625, 0.81, etc.). These act as "Time Kill Zones" where price reversals or accelerations often occur. Settlement Time Zone: Defines the day start based on a specific exchange time (default: Europe/Stockholm), ensuring session alignments are correct regardless of your local chart time. Wicks vs. Bodies: Choose whether the session High/Low is defined by candle wicks (standard) or bodies (closing price). 4. Enigma Zones (OFG) A secondary overlay layer that highlights "Order Flow Grids." These are specific zones calculated from higher timeframe volatility, often acting as "magentic" zones where price consolidates before expanding. How to Use (Workflow) Step 1: Grid Setup (Price) Add the indicator to your chart. In GB Settings, set Calc Mode to "Hybrid". The indicator will automatically draw the correct grid size (e.g., 243 points). Observe price respect at the 0.0 (Low), 0.5 (EQ), and 1.0 (High) levels. Toggle TT if you are trading assets that respect the Twin Tower nodes (0.14/0.86) more strictly. Step 2: AMD Timing (Time) Go to AMD Settings and configure your session times (e.g., Accumulation: 20:00-04:59, Manipulation: 05:00-10:59, Distribution: 11:00-19:59). Live Trading: When a session starts, look at the Time Cycle (Vertical Lines). # Scenario: If price is Accumulating, look for a "Judas Swing" (Manipulation) to trigger near the 0.375 or 0.625 time vertical. # Use the Projected Box to see where the current High/Low stands relative to the session duration. Step 3: Confluence Combine the GB Horizontal Levels with the AMD Vertical Times. Example: If price hits a GB +1 Level (Price Resistance) exactly at the AMD 0.625 Time Cycle (Time Resistance) during the Manipulation phase, this is a high-probability reversal setup. Settings Overview GB Settings: Controls the main horizontal grid, PO3 numbers, and Line styles. PD Customization: Toggles specific colored backgrounds for Premium/Discount arrays (OB, FVG, etc.) within the grid. AMD Settings: # Settlement Time Zone: Crucial for aligning the day correctly. # A / M / D Groups: Enable/Disable boxes, set colors, and toggle History. # Time Cycles: Customize the vertical time harmonic ratios. Enigma Lv: Toggles the secondary OFG zone layer.
Penunjuk Pine Script®
oleh NetNine
Thiru 369 LabelsThiru 369 Labels **Thiru 369 Labels** is a sophisticated time-based indicator that calculates the numerical sum of time digits and displays visual labels when the sum matches harmonic values (3, 6, or 9). Based on the mathematical principles popularized by Nikola Tesla, this indicator helps traders identify potential market timing opportunities during major trading sessions. 📊 What It Does This indicator monitors the current time (hour and minute) and calculates the sum of all digits, reducing it to a single digit. When this final sum equals 3, 6, or 9, a label is displayed on the chart. The indicator specifically focuses on three major trading sessions: - **London Session**: 02:30 - 07:00 (GMT-5) - **NY AM Session**: 07:00 - 11:30 (GMT-5) - **NY PM Session**: 11:30 - 16:00 (GMT-5) 🔢 How It Works ### Time Sum Calculation The indicator uses a standard mathematical reduction method: 1. **Extract Digits**: Takes the hour and minute (e.g., 09:51) 2. **Sum All Digits**: Adds all digits together (0 + 9 + 5 + 1 = 15) 3. **Reduce to Single Digit**: Continues reducing until single digit (15 → 1 + 5 = 6) 4. **Check Match**: If result equals 3, 6, or 9, displays label Examples: - **03:30** → 0 + 3 + 3 + 0 = **6** ✅ (Perfect 6) - **12:06** → 1 + 2 + 0 + 6 = **9** ✅ (Perfect 9) - **09:51** → 0 + 9 + 5 + 1 = 15 → 1 + 5 = **6** ✅ - **14:22** → 1 + 4 + 2 + 2 = 9 ✅ (Perfect 9) Session Detection The indicator automatically detects when the current time falls within active trading sessions and only displays labels during these periods. This ensures you're only seeing relevant timing signals during market hours. Cycle Detection The indicator can also detect different time cycles within sessions: - **90-minute cycles**: Major session periods - **30-minute cycles**: Sub-cycles within sessions - **10-minute cycles**: Detailed intervals 🎯 Key Features ✅ Time Sum Detection - Calculates time sum using standard 369 method - Displays labels when sum matches 3, 6, or 9 - Customizable target sums (default: 3, 6, 9) ✅ Session Monitoring - London Session (02:30 - 07:00) - NY AM Session (07:00 - 11:30) - NY PM Session (11:30 - 16:00) - Enable/disable individual sessions ✅ Cycle Detection - 90-minute cycles - 30-minute cycles - 10-minute cycles - Optional cycle information display ✅ Visual Customization - Label size options (Auto, Tiny, Small, Normal, Large, Huge) - Custom colors for each sum (3, 6, 9) - Session-based colors (Purple=London, Green=NY AM, Blue=NY PM) - Label transparency control - Text-only labels (no background box) ✅ Display Options - Show/hide time text - Show/hide cycle information - Drawing limit options (Current Day, Last 2/3/5 Days, All Days) - Debug table for real-time monitoring ✅ Advanced Settings - Timezone selection (27 timezone options) - Swing sensitivity for label positioning - Label offset control - Confirmed bars only option 📖 How to Use Step 1: Add Indicator to Chart 1. Open TradingView 2. Click "Indicators" button 3. Search for "Thiru 369 Labels" 4. Click to add to chart Step 2: Configure Basic Settings **Time Sum Settings:** - Enable Time Sum Detection: ✅ (default: ON) - Target Sums: "3,6,9" (default) - Label Size: Choose your preferred size - Drawing Limit: "All Days" (default) or limit to specific periods **Session Settings:** - Monitor London Session: ✅ (default: ON) - Monitor NY AM Session: ✅ (default: ON) - Monitor NY PM Session: ✅ (default: ON) **Cycle Settings:** - 90 Minute Cycles: ✅ (default: ON) - 30 Minute Cycles: ✅ (default: ON) - 10 Minute Cycles: ✅ (default: ON) Step 3: Customize Appearance **Label Colors:** - Use Custom Sum Colors: OFF (default) - Uses session colors - OR Enable to use: Blue (3), Red (6), Maroon (9) **Display Settings:** - Label Transparency: Adjust as needed - Show Time Text: Optional - Show Cycle Information: Optional - Show Debug Table: ✅ (recommended for monitoring) Step 4: Set Timezone **General Settings:** - Session Timezone: Select your timezone (default: GMT-5) - Choose from 27 timezone options Step 5: Monitor Labels - Labels will automatically appear when: - Time sum equals 3, 6, or 9 - Current time is within an active session - Drawing limit allows it 💡 Use Cases 1. Market Timing Entries Use 3, 6, 9 labels as potential entry signals when combined with other technical analysis: - Wait for label to appear - Confirm with price action - Enter trade with proper risk management 2. Session Analysis Identify optimal trading times within sessions: - Monitor which sessions show most labels - Track label frequency per session - Plan trading around high-frequency periods 3. Cycle Recognition Understand market rhythm patterns: - 90-minute cycles for major moves - 30-minute cycles for intermediate moves - 10-minute cycles for precise timing 4. Time-Based Confirmation Use labels to confirm other indicators: - Combine with price action - Use with support/resistance levels - Confirm with volume analysis ⚙️ Settings Overview Time Sum Settings - **Enable Time Sum Detection**: Master switch for the indicator - **Target Sums**: Comma-separated list of target values (default: "3,6,9") - **Label Size**: Size of displayed labels - **Show Time Text**: Display time along with sum - **Show Cycle Information**: Display cycle type (90m, 30m, 10m) - **Drawing Limit**: Limit labels to specific time periods - **Show Debug Table**: Real-time monitoring table - **Only Show on Confirmed Bars**: Wait for bar confirmation Session Settings - **Monitor London Session**: Enable/disable London session (02:30-07:00) - **Monitor NY AM Session**: Enable/disable NY AM session (07:00-11:30) - **Monitor NY PM Session**: Enable/disable NY PM session (11:30-16:00) Cycle Settings - **90 Minute Cycles**: Enable 90-minute cycle detection - **30 Minute Cycles**: Enable 30-minute cycle detection - **10 Minute Cycles**: Enable 10-minute cycle detection Display Settings - **Label Transparency**: Control label background transparency Label Colors - **Color for Sum 3**: Custom color for sum = 3 - **Color for Sum 6**: Custom color for sum = 6 - **Color for Sum 9**: Custom color for sum = 9 - **Use Custom Sum Colors**: Toggle between custom and session colors General Settings - **Session Timezone**: Select timezone for calculations (27 options) - **Swing Sensitivity**: Bars for swing detection - **Label Offset**: Vertical spacing for labels 🔍 Debug Table The debug table provides real-time information: - **Time**: Current time with seconds - **Sum**: Calculated time sum - **Session**: Active session (London, NY AM, NY PM, or None) - **Cycle**: Active cycle (90min, 30min, 10min, or None) - **Status**: Match status (MATCH! or No Match) - **Targets**: Configured target sums - **Next**: Next potential sum value Enable the debug table to monitor the indicator's calculations in real-time. 📊 Examples Example 1: Perfect 6 **Time**: 03:30 **Calculation**: 0 + 3 + 3 + 0 = 6 **Result**: Label "6" appears (if in active session) Example 2: Perfect 9 **Time**: 12:06 **Calculation**: 1 + 2 + 0 + 6 = 9 **Result**: Label "9" appears (if in active session) Example 3: Reduced to 6 **Time**: 09:51 **Calculation**: 0 + 9 + 5 + 1 = 15 → 1 + 5 = 6 **Result**: Label "6" appears (if in active session) Example 4: Reduced to 3 **Time**: 11:10 **Calculation**: 1 + 1 + 1 + 0 = 3 **Result**: Label "3" appears (if in active session) 🎨 Visual Features Label Display - **Text Only**: Clean text labels without background boxes - **Color Coded**: Different colors for different sums or sessions - **Smart Positioning**: Labels positioned above/below candles based on swing detection - **Adaptive Offset**: Automatic spacing to avoid overlap Session Colors (Default) - **London Session**: Purple labels - **NY AM Session**: Green labels - **NY PM Session**: Blue labels Custom Colors (Optional) - **Sum 3**: Blue - **Sum 6**: Red - **Sum 9**: Maroon 📜 License & Attribution **Copyright**: © 2025 ThiruDinesh **License**: Mozilla Public License 2.0 **Contact**: TradingView @ThiruDinesh This indicator is based on mathematical principles of numerical reduction and harmonic numbers, concepts popularized by Nikola Tesla and used in various trading methodologies.
Penunjuk Pine Script®
oleh thirudinesh
1
Multi-Asset Trend Background [SwissAlgo]Multi-Asset Trend Background --------------------------------------------------------- Purpose This indicator colors the chart background green (uptrend) or red (downtrend) to show the broad phases of a selected asset or ratio (for example SP500, or Gold), regardless of the current ticker on the chart (for example BTC). The aim is not to generate signals, but to show when the selected asset (such as SP500 or Gold) was in a sustained uptrend or downtrend, so you can compare another chart (for example BTC) against that backdrop. It helps frame price action in context, highlighting how macro drivers often align with or diverge from other markets. From mid-2016 to late-2017, the SP500 was in a clear uptrend — Bitcoin rallied strongly in the same period, showing alignment between equities and crypto risk-taking. When Gold trended higher, the SP500 often weakened, reflecting their tendency to move inversely in longer cycles. As HYG/TLT turned down in early 2020, QQQ also struggled — illustrating how credit risk appetite is linked to equity performance. During periods of DXY strength, Gold frequently showed the opposite trend, consistent with the historical dollar–gold relationship. When RSP/SPY trended down, rallies in the S&P 500 were driven by a narrow group of large-cap stocks, while a rising ratio indicated broad market participation. --------------------------------------------------------- Why it May Help You Provides context for asset correlations. Helps identify whether a chart is moving with or against its macro environment. Useful for cycle mapping and historical study of market phases. Filters noise and emphasizes established trends rather than short swings. --------------------------------------------------------- How it Works You select an asset or ratio from a dropdown. The script calculates a mid-term moving average, then measures its slope, slope change, and slope acceleration to quantify the trend’s direction and consistency. A longer-term moving average filter defines whether the long-term backdrop is bullish or bearish. Background Coloring rules: Green = slope strongly positive in line with long-term uptrend, or downtrend showing constructive reversal signs. Red = slope strongly negative in line with long-term downtrend, or uptrend showing weakening slope. No shading = neutral or mixed conditions. This slope-based approach avoids the limitations of simple MA crosses, aiming to capture broad, consistent trend phases across different assets, with a mid/long-term view. --------------------------------------------------------- Assets You Can Select EQUITIES – good reference to gauge risk appetite in financial markets SP500 = broad benchmark. Uptrend = strength in US equities signalling risk-on conditions; downtrend = weakness, risk-off market phase. NASDAQ = tech and growth stocks. Uptrend = technology/growth leadership, risk appetite; downtrend = tech underperformance and fading risk appetite. DOW = industrial and value stocks. Uptrend = industrial/value strength/economic strength; downtrend = weakness in traditional sectors and potential economic downturn. RUSSELL2000 = small caps. Uptrend = typical in risk-on environments and FOMO; downtrend = small-cap underperformance, "flight to safety". COMMODITIES – proxies for inflation, industry, and safe-haven demand. GOLD = safe-haven. Uptrend = defensive demand rising/risk-off/inflation fears; downtrend = weaker demand for safety. SILVER = partly industrial, partly safe-haven. Uptrend = stronger industrial cycle, or precious metals demand and risk appetite. COPPER = industrial barometer. Uptrend = stronger industrial activity; downtrend = economic slowdown concerns. CRUDE OIL = energy prices. Uptrend = rising energy/inflation pressures; downtrend = weaker demand or supply relief. NATURAL GAS = volatile energy prices. Uptrend = higher energy costs and inflation pressure; downtrend = easing energy conditions. BONDS / FX – monetary policy, credit, and risk appetite signals. TLT = long-term US bonds. Uptrend = falling yields (bond demand)/flight to safety; downtrend = rising yields (risk on) HYG = high-yield credit. Uptrend = strong credit appetite; downtrend = risk aversion in credit markets. DXY = US dollar index. Uptrend = dollar strength (weaker EUR, GBP, SEK, etc); downtrend = dollar weakness. USDJPY = carry trade proxy. Uptrend = stronger USD vs JPY (risk appetite); downtrend = JPY strength (risk-off). CHFUSD = Swiss franc. Uptrend = franc strength (defensive flow); downtrend = franc weakness. YIELD INVERSION = US10Y–US02Y. Uptrend = curve steepening; downtrend = inversion deepening (higher recession risk). HOME BUILDERS = US housing sector. Uptrend = housing sector strength (risk on); downtrend = weakness (risk off). EURUSD = euro vs dollar. Uptrend = euro strength (risk appetite); downtrend = euro weakness (risk aversion). CRYPTO – digital asset benchmarks. BITCOIN = digital gold. Uptrend = BTC strength; downtrend = BTC weakness. CRYPTO_TOTAL = entire crypto market cap. Uptrend = broad crypto growth; downtrend = contraction. CRYPTO_ALTS = altcoin market cap. Uptrend = altcoin expansion (often “alt season”); downtrend = contraction. RATIOS – relative measures to extract macro signals. COPPER/BTC = compares industrial cycle vs Bitcoin cycle. Uptrend = copper outperforming BTC; downtrend = BTC outperforming copper. Seems aligned with BTC macro tops and bottoms in the mid/long run. RSP/SPY = market breadth (equal-weight vs cap-weighted). Uptrend = strong broad participation in market growth; downtrend = narrow leadership (fewer stocks leading the growth). PCE/CPI = Fed’s inflation measure (PCE) vs consumer perceived inflation (CPI). Uptrend = PCE rising faster than CPI; downtrend = CPI running hotter than PCE. Fluctuates around 1; values above 1 may indicate hawkish Fed stands, values < 1 may indicate more dovish Fed stands. HYG/TLT = credit vs bonds. Uptrend = risk appetite (high-yield outperforming long-term treasury bonds); downtrend = risk aversion. GOLD/SILVER = defensive vs cyclical metals. Uptrend = gold outperforming (risk-off tilt); downtrend = silver outperforming (risk-on tilt). EURUSD/BTC = fiat vs crypto. Uptrend = EUR strengthening vs BTC; downtrend = BTC strengthening vs EUR. In general, the BTC trend is aligned EUR/USD trend. --------------------------------------------------------- Limitations Trend detection may lag by design to reduce noise. Ratios rely on the availability and session rules of their components. Background colors update on bar close; intra-bar values may differ. Parameters are fixed and may not suit all assets equally. --------------------------------------------------------- Disclaimer This script is for educational and research purposes only. It does not provide financial advice or trade recommendations. Historical trend alignment does not guarantee future outcomes. Use with additional independent analysis.
Penunjuk Pine Script®
oleh SwissAlgo
BBI - Bitcoin (BTC) Bottom Indicator [Logue]This indicator is a combination of multiple on-chain and seasonality BTC macro cycle bottom indicators. Because there is no magic single indicator to detect macro cycle bottoms in bitcoin, the BBI detects confluence of multiple indicators to select bottoms of each BTC macro cycle. The individual indicators used for the BBI are: 1) Cumulative Value Days Destroyed (CVDD) - The CVDD was created by Willy Woo and is the ratio of the cumulative value of Coin Days Destroyed in USD and the market age (in days). When the BTC price goes below this value, BTC is generally considered to be undervalued. This indicator is triggered when the BTC price is below the CVDD. 2) Net Unrealized Profit Loss (NUPL) - The NUPL measures the profit state of the bitcoin network to determine if past transfers of BTC are currently in an unrealized profit or loss state. Values above zero indicate that the network is in overall profit, while values below zero indicate the network is in overall loss. Highly negative NUPL values indicate an undervaluation of the BTC network. This indicator is triggered when the NUPL is below -15. 3) Market Value-Realized Value Z-score (MVRV-Z) - The MVRV-Z measures the value of the bitcoin network by comparing the market cap to the realized value and dividing by the standard deviation of the market cap (market cap – realized cap) / std(market cap)). When the market value is significantly lower than the realized value, the bitcoin network is "undervalued". Very low values have signaled cycle bottoms in the past. This indicator is triggered when the MVRVZ value is below 4. 4) Puell multiple (PUELL) - PUELL is the ratio between the daily coin issuance in USD and its 365-day moving average. This multiple helps to measure miner profitability. When the PUELL goes to extremely low values relative to historical values, it indicates the profitability of the miners is low and a bottom may be near. This indicator triggers when the PUELL is below 0.4. 5) Calendar Seasonality Index (CSI) - The CSI takes advantage of the consistency of BTC cycles. Past cycles have formed macro bottoms every four years between December and February. Therefore, this indicator triggers at set times that are marked every four years in December, January, or February. 6) Halving Seasonality Index (HSI) - The HSI, as with the CSI, takes advantage of the consistency of BTC cycles following the major event that is the halving. Past cycles have formed macro bottoms approximately 948 days after each halving. Therefore, this indicator triggers at set times that are marked 903-993 days (i.e., 948 +- 45 days) after each halving. 7) Polylog Regression (PLR) - The BTC cycle tops and bottoms were separately fit using a polynomial regression for the PLR. The bottom band was fit on much more data than the top band, so is likely to be more reliable. The shape of the regression into the future was estimated, so may not be accurate into the future, but is the best fit of tops and bottoms to date. This indicator is used to estimate when tops and bottoms are near when the price goes into the top or bottom bands. This triggers when the BTC price is inside or below the lower polylog regression channel. 8) Realized Price (RP) - The RP is summation of the value of each BTC when it last moved divided by the total number of BTC in circulation. This gives an estimation of the average "purchase" price of BTC on the bitcoin network based on when it was last transacted. This indicator tells us if the average network participant is in a state of profit or loss. This indicator triggers when the BTC price is below the realized price. 9) Hash Rate Capitulation (HRC) - The HRC indicator measures the rate of change of the hash rate. Steadily increasing hash rate is a sign of health of the bitcoin network. This indicator uses moving averages (20- and 100-day) of the hash rate to indicate when a decrease in the rate of change is has occurred (i.e., the 20-day MA goes below the 100-day MA). This indicator triggers when the 20-day moving average of the hash rate going below the 100-day moving average. The on-chain indicators (CVDD, NUPL, MVRV-Z, PUELL, RP, and HRC) work together to give a health check of the BTC price as compared to its network health. The seasonality indicators (CSI, HSI, and PLR) work together to map the macro cycles of BTC. Each of these indicators is weighted evenly when selected and if over 40% of the indicators are triggering on a candle (i.e., at least 4 of 9), the overall BBI indicator prints a clear signal -- a green dot with a white middle portion between the white horizontal lines at the top of the indicator. This signal is meant to indicate when the macro cycle bottom is likely already hit or is near. Each of the individual indicators used for the BBI are proven macro bottom indicators over multiple cycles. Each of the individual indicators are shown in their own rows to visualize which indicators are triggering. You are able to deselect any indicator you do not wish to have considered and select it back again. To prepare you for indicators triggering, the BBI shows dark blue or dark green when the indicator is close to triggering (i.e., generally around 20% from the trigger value, a less intense background will appear, and 10% from the trigger value, a more intense background will appear). The color of the individual indicators turns pink when they are triggered. The background color of the BBI becomes blue when at least 30% of the indicators considered are triggering and it becomes green when the BBI fully triggers. See the BTC chart above the indicator showing the performance of the indicator in picking out macro bottom regions (green dots with white middle portion). Because not all daily data for BTC can be shown on one chart, ensure you also play with the indictor yourself. The BLX is most appropriate, but the indicator works on all BTC/USD charts. Because of the limitations of moving averages in TradingView, the indicator doesn't work on time frames lower than 4 h. You can use this indicator to help you understand when the BTC price is more likely bottoming based on past performance of these indicators. This indicator pairs with the BTI (Bitcoin (BTC) top indictor) and the BTB (Bitcoin top and bottom) indicators. Use this indicator at your own risk. I make no assertions that this indicator will work to detect any future bottom since we all know that past performance is no guarantee of future results.
Penunjuk Pine Script®
oleh Da_Prof
7
Optimist Pulse Wave [RC] Optimist Pulse Wave Optimist Pulse Wave is a closed-source oscillator that analyzes market momentum and internal price energy using a structured multi-wave and multi-filter framework. The indicator is intended to help traders assess momentum strength, phase transitions, and potential exhaustion areas across different market conditions. Data Sources and Technical Components The script is derived from price OHLC data and internally incorporates commonly known technical elements, including: Simple Moving Averages (SMA) Exponential Moving Averages (EMA) Relative Strength Index (RSI) Moving Average Convergence Divergence (MACD) and used proprietary algorithm to make price and volume data to waves These elements are not used or displayed in their standard standalone form. They are combined, transformed, and normalized to construct a layered momentum model. Conceptual Framework Market momentum develops in layers and degrees of strength. Rather than producing a single oscillator output, this indicator decomposes momentum into multiple wave types, and then evaluates each wave through progressive strength filters. Wave Types The script models momentum using five wave types, each representing a different time-response of price: 1. Pulse Wave | Short-term momentum and rapid price acceleration 2. Swing Wave | Intermediate momentum capturing swing-level movements 3. Trend Wave | Broader directional momentum reflecting trend persistence 4. Cycle Wave | Dominant rhythm of price over extended periods 5. Epoch Wave | Long-duration structural momentum used to contextualize regime changes or prolonged conditions Strength Filters Each wave type is further evaluated using five internal strength filters, representing increasing levels of momentum confirmation: Base | Minimal momentum conditions for the wave Enhanced | Improved momentum quality with reduced noise Strong | Sustained momentum with higher consistency Dominant | Momentum aligned across multiple internal measures Absolute | Extreme or fully developed momentum state These filters help distinguish weak signals from structurally strong conditions. Normalization and Zones All wave and filter outputs are normalized to a fixed 0–100 scale, allowing comparison across symbols and timeframes. The oscillator is visually divided into: Green / Lower Zone : (Low Energy / Accumulation) Weak or rebuilding momentum Middle Zone : Transitional or balanced conditions Red / Upper Zone : (High Energy / Distribution / Exhaustion)Strong momentum or potential exhaustion Zone interpretation is context-dependent. Visual Trade Signals ✔ Green markers → Pulse-based BUY zones (energy expansion from lows) ✔ Red markers → Pulse-based SELL zones (energy exhaustion from highs) Visual Markers Visual markers appear when specific wave-and-filter combinations indicate: Momentum expansion from low-strength conditions Momentum deterioration after extended strength Markers are intended as analytical references, not automated trade instructions. 🌍 Works Across All Markets & Timeframes ✔ Index (NIFTY, BANKNIFTY) ✔ Stocks ✔ Forex ✔ Crypto ✔ Scalping, Intraday to Positional Usage Guidelines This indicator may assist traders in: Evaluating trend quality and momentum health Timing entries during pullbacks Identifying momentum exhaustion Avoiding low-energy or sideways conditions It should be used in conjunction with price action and contextual analysis. Important Notes The script uses commonly known technical components in a non-standard, composite structure No predictive certainty or profitability claims are made All outputs require user interpretation and confirmation Settings and Training Videos available in followed folder drive.google.com
Penunjuk Pine Script®
oleh raikarcapital
BTC Runner V1Bitcoin Runner V1 — advanced proprietary visual tool created specifically for long-term Bitcoin cycle research on 1D, 1W and 1M timeframes. The indicator operates in two fundamentally different visual modes: Buffett Mode (4-Year Halving Cycle Logic) Fully built on Bitcoin’s historical ~4-year halving cycle. Using an original mathematical formula and real-time price data, the indicator continuously tracks whether the current cycle has reached the structural point that historically marked the final phase of previous bull markets. As soon as ALL formula conditions are met for the first time: - Chart background instantly changes color (green → red at cycle top, red → green at cycle bottom reversal) - A large permanent non-repainting banner appears showing the exact date and price of the All-Time High (ATH) of the current cycle - Fixed label “ATH” with price and timestamp is plotted and remains on the chart forever Examples on charts: - Chart #1 (20 Jan 2018) — green background still active, bull phase ongoing - Chart #2 (22 Jan 2018) — exact moment all conditions triggered: background turns red + permanent ATH banner with unchangeable data appears The same logic works in reverse when a bear cycle ends and a new bull cycle begins. Cramer Mode (Historical Correction & Drawdown Zones Logic) Based on over 10 years of personal observation of recurring percentage zones across multiple Bitcoin cycles: • Major corrections historically reaching up to ~84% from local highs • Intermediate drawdowns typically 20–55% When ALL conditions of the multi-stage proprietary formula are satisfied for the first time after a prolonged decline or consolidation, the indicator automatically draws in real time: 1. Large green background banner with bold white text “AP” (Analyzed Point) — marking the price level where, according to many years of observation across several cycles, such deep corrections have historically completed. 2. Dynamic floating label “TP” (Tracked Progress) — a temporary price marker that moves with the current price in real time. As soon as price touches or exceeds this level, the entire banner instantly and permanently turns blue and the text changes to “AP Completed”. All banners, colors, and labels appear strictly automatically in live mode and never repaint. Important: - The script contains over 500 lines of completely original closed-source code. - No standard indicators are used (moving averages, Fibonacci, waves, volume, volume profile, etc.). Only pure original mathematical modeling. - The indicator is intended exclusively for research, educational, and informational purposes. - It contains no trading recommendations, investment advice, or calls to action of any kind. Respectful note to TradingView moderators and users: If any visual elements or logic seem similar to previously published open-source scripts — feel free to use those open-source versions instead. Bitcoin Runner V1 is a 100% original closed-source tool based on the author’s personal multi-year research and observations.
Penunjuk Pine Script®
oleh ByteMEME
1
BTB - Bitcoin (BTC) Top and Bottom Indicator [Logue]This indicator is a combination of multiple on-chain, seasonality, and momentum BTC macro cycle bottom and top indicators. The BTB detects confluence of multiple indicators to select bottoms and tops of each BTC macro cycle. More detail can be seen on the BTI and BBI indicators. The BTB indicators are: 1) Cumulative Value Days Destroyed (CVDD) - The CVDD is the ratio of the cumulative value of coin days destroyed in USD and the market age (in days). When the BTC price goes below this value, BTC is generally considered to be undervalued. The bottom indicator is triggered when the BTC price is below the CVDD or above the CVDD extension. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. 2) Net Unrealized Profit Loss (NUPL) - The NUPL measures if past transfers of BTC are currently in an unrealized profit or loss state. Historically positive or negative NUPL values indicate an over/undervaluation of the BTC network. The bottom indicator is triggered when the NUPL is below -15 and the top is triggered above an adjusted value based on decreasing "strength" of BTC tops. A decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops and used to determine overvaluation. 3) Market Value-Realized Value Z-score (MVRV-Z) - The MVRV-Z measures the value of the bitcoin network by comparing the market cap to the realized value and dividing by the standard deviation of the market cap (market cap – realized cap) / std(market cap)). The bottom indicator is triggered when the MVRVZ value is below 4 and tops are above 55. 4) Puell multiple (PUELL) - PUELL is the ratio between the daily coin issuance in USD and its 365-day moving average. This multiple helps to measure miner profitability. Extremes in PUELL may indicate tops or bottoms. The bottom indicator triggers when the PUELL is below 0.4 and top is triggered above 3.33. 5) Calendar Seasonality Index (CSI) - The CSI takes advantage of the consistency of BTC cycles. Past cycles have formed macro bottoms every four years between December and February which triggers the bottom indicator. Past cycles have formed macro tops every four years between October 21st and December 12th, triggering the top indicator. 6) Halving Seasonality Index (HSI) - Past cycles have formed macro bottoms approximately 948 days after each halving, triggering this indicator at set times, 948 +- 45 days, after each halving. Aside from the first halving, cycles have formed macro tops approximately 538 days after each halving. Therefore, this indicator triggers at 538 +- 10 days after each halving. 7) Polylog Regression (PLR) - The BTC cycle tops and bottoms were separately fit using a polynomial regression. The shape of the regression into the future was estimated and a fit was used to estimate when tops and bottoms are near. This triggers when the BTC price is inside or below the lower polylog regression channel and when the BTC price is inside or above the upper polylog regression channel. 8) Realized Price (RP) - The RP is summation of the value of each BTC when it last moved divided by the total number of BTC in circulation. This gives an estimation of the average "purchase" price of BTC. This indicator triggers when the BTC price is below the realized price or above an RP extension. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. 9) Plus Directional Movement (PDM) weekly index - The PDM is a momentum indicator that measures the strength of a trend in the positive direction. The weekly PDM is calculated by determining the difference between the week's high price and the previous week's high price smoothed by a 14-period moving average. Higher PDM values indicate higher momentum in the positive (higher price) direction. Based on decreasing "strength" of BTC tops, a decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops for this indicator. This indicator is triggered when the PDM is above the trigger value or below 14. 10) Logarithmic Moving Average Convergence Divergence (LMACD) weekly indicator - The LMACD is a momentum indicator that measures the strength of a trend using the difference of the log values of the 12-period and 26-week exponential moving averages. Larger positive numbers indicate a larger positive momentum. Based on decreasing "strength" of BTC tops, a decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops for this indicator. This indicator is triggered when the PDM is above the trigger value or below -0.06. 11) Hash Rate Capitulation (HRC) - The HRC indicator measures the rate of change of the hash rate. Steadily increasing hash rate is a sign of health of the bitcoin network. This indicator uses moving averages (20- and 100-day) of the hash rate to indicate when a decrease in the rate of change is has occurred (i.e., the 20-day MA goes below the 100-day MA). This indicator triggers when the 20-day moving average of the hash rate going below the 100-day moving average. 12) Pi-cycle Top (PCT) - The PCT indicator is simply the cross of the 111-day moving average above a 2x multiple of the 350-day moving average of the BTC price. While there is no fundamental reasoning behind why this works, it has worked to indicate previous bitcoin tops by taking advantage of the cyclicality of the BTC price and measurement overextension of BTC price. This indicator triggers when the fast moving average (111-day) crosses above the 2x multiple of the slow moving average (350-day). 13) Transaction Fee Spike (TFS) - Transaction fees on the bitcoin network can signal a mania phase when they increase well above historical values. This mania phase may indicate we are near a top in the BTC price. The daily transaction fee total in USD is divided by the number of daily transactions to calculate the average transaction fee paid on the bitcoin network. The transaction fees increasing above $40 trigger this indicator. The on-chain indicators (CVDD, NUPL, MVRV-Z, PUELL, RP, and HRC) work together to give a health check of the BTC price as compared to its network health. The seasonality indicators (CSI, HSI, and PLR) work together to map the macro cycles of BTC. The momentum indicators (PDM and LMACD) give the strength of the BTC trend. Each of these indicators is weighted evenly when selected and if over 45% of the indicators are triggering on a candle, the overall BTB indicator prints a clear signal. This signal is meant to indicate when the macro cycle bottom or top is likely hit or is near. You are able to deselect any indicator you do not wish to have considered and select it back again. To prepare you for indicators triggering, the BTB shows dark blue or dark green when the indicator is close to triggering. The background color of the BBI becomes blue when at least 30% of the indicators considered are triggering and it becomes green when the BBI fully triggers. The BLX is most appropriate chart, but the indicator works on all BTC/USD charts. Because of the limitations of TradingView, the indicator doesn't work on time frames lower than 4 h or over one week. Use this indicator at your own risk. I make no assertions that this indicator will work to detect any future bottom or top since we all know that past performance is no guarantee of future results.
Penunjuk Pine Script®
oleh Da_Prof
22
Intraday Toolkit1. Visual Components of the Indicator Understanding the visual cues is essential for quick decision-making during fast-moving intraday sessions: Trend Background: The background color represents the Primary Cycle (80-period) bias. Green indicates a bullish trend (price is above the primary cycle), and red indicates a bearish trend (price is below the primary cycle). The Three Cycles: Yellow Line: Short Cycle (20) – Used for momentum triggers. Orange Line: Mid Cycle (40) – Represents the baseline for volatility envelopes. Red Line: Primary Cycle (80) – Defines the overall trend direction. Volatility Envelopes: Two green lines plotted at a distance (1.5x ATR) from the Mid Cycle. These act as exhaustion zones where price is likely to revert or consolidate. Rule 3 Signals (Purple Circles): These appear when a specific 3-candle momentum breakout occurs. 2. Trading Strategy for 5m & 15m This toolkit is most effective when you use the 15m chart for trend confirmation and the 5m chart for precise entries. Long (Buy) Setup Enter a long position when the following alignment occurs: Bullish Bias: The background must be Green (Price > Primary Cycle). Cycle Low: A pivot low must have been detected (the indicator identifies a local bottom). Momentum Trigger: Price must close above the Yellow Short Cycle line while the previous candle was below it. Rule 3 Confirmation: If a purple circle appears simultaneously, it confirms strong buying momentum. Short (Sell) Setup Enter a short position when the following alignment occurs: Bearish Bias: The background must be Red (Price < Primary Cycle). Cycle High: A pivot high must have been detected (the indicator identifies a local top). Momentum Trigger: Price must close below the Yellow Short Cycle line while the previous candle was above it. Rule 3 Confirmation: A purple circle above the price confirms a bearish momentum shift. 3. Exit and Take-Profit Logic The script includes "State Control" to manage your exits effectively: Targeting the Envelopes: The primary profit target is the Outer Green Envelope. If price touches the upper envelope (for longs) or lower envelope (for shorts), the trend may be exhausted. Momentum Exit: If price crosses back over the Yellow Short Cycle line in the opposite direction of your trade, the toolkit considers the move over and signals an exit. 4. Specific Tips for Day Trading Avoid "Counter-Trend" Signals: Do not take Buy signals if the background is Red, or Sell signals if the background is Green. The logic is built to filter these out for better win rates. The "Rule 3" Advantage: Use the purple circles as a "second chance" entry. If you missed the initial Buy/Sell signal, a Rule 3 circle indicates momentum is still strong in that direction. Timeframe Synergy: * 15m: Best for seeing the "Big Picture" and avoiding noise. 5m: Best for finding entries with smaller stop-losses near the Yellow Short Cycle line.
Penunjuk Pine Script®
oleh sunya
Sentient FLDOverview of the FLD The Future Line of Demarcation (FLD) was first proposed by JM Hurst in the 1970s as a cycle analysis tool. It is a smoothed median price plotted on a time-based chart, and displaced into the future (to the right on the chart). The amount of displacement is determined by performing a cycle analysis, the line then plotted to extend beyond the right hand edge of the chart by half a cycle wavelength. Interactions between price and the FLD As price action unfolds, price interacts with the FLD line, either by crossing over the line, or by finding support or resistance at the line. Targets When price crosses an FLD a target for the price move is generated. The target consists of a price level and also expected time. When price reaches that target it is an indication that the cycle influencing price to move up or down has completed that action and is about to turn around. If price fails to reach a target by the expected time, it indicates bullish or bearish pressure from longer cycles, and a change in mood of the market. Sequence of interactions Price interacts with the FLD in a regular sequence of 8 interactions which are labelled using the letters A - H, in alphabetical order. This sequence of interactions occurs between price and a cycle called the Signal cycle. The full sequence plays out over a single wave of a longer cycle, called the Sequence cycle. The interactions are: A category interaction is where price crosses above the FLD as it rises out of a trough of the Sequence cycle. B & C category interactions often occur together as a pair, where price comes back to the FLD line and finds support at the level of the FLD as the first trough of the Signal cycle forms. D category interaction is where price crosses below the FLD as it falls towards the second trough of the Signal cycle. E category interaction is where price crosses above the FLD again as it rises out of the second trough of the Signal cycle. F category interaction is where price crosses below the FLD as it falls towards the next trough of the Sequence cycle. G & H category interactions often occur together as a pair, where price comes back to the FLD line and finds resistance at the level of the FLD before a final move down into the next Sequence cycle trough. Trading Opportunities This sequence of interactions provides the trader with trading opportunities: A and E category interactions involve price crossing over the FLD line, for a long trading opportunity. D and F category interactions involve price crossing below the FLD line, for a short trading opportunity. B and C category interactions occur where price finds support at the FLD, another long trading opportunity. G and H category interactions occur where price finds resistance at the FLD, another short trading opportunity. 3 FLD Lines Plotted The Sentient FLD indicator plots three FLD lines, for three primary cycles on your time-based charts: The Signal cycle (pink color, can be changed in the settings), which is used to generate trading signals on the basis of the sequence of interactions between price and the FLD The Mid cycle (orange color, can be changed in the settings), which is used for confirmation of the signals from the signal cycle FLD. The Sequence cycle (green color, can be changed in the settings) which is the cycle over which the entire A - H sequence of interactions plays out. Cycle Analysis In addition to plotting the three FLD lines, the Sentient FLD indicator performs a cycle phasing analysis and identifies the positions of the troughs of five cycles on your chart (The Signal, Mid & Sequence cycles and two longer cycles for determining the underlying trend). The results of this analysis are plotted by using diamond symbols to mark the timing of past troughs of the cycles, and circles to mark the timing of the next expected troughs, with lines extending to each side to represent the range of time in which the trough is expected to form. These are called circles-and-whiskers. The diamonds are stacked vertically because the troughs are synchronized in time. The circles-and-whiskers therefore are also stacked, creating a nest-of-lows which is a high probability period for a trough to form. Identifying the Interactions The Sentient FLD also identifies the interactions between price and each one of the three FLDs plotted on your chart, and those interactions are labelled so that you can keep track of the unfolding A - H sequence. Next Expected Interaction Because the Sentient FLD is able to identify the sequence of interactions, it is also able to identify the next expected interaction between price and the FLD. This enables you to anticipate levels of support or resistance, or acceleration levels where price is expected to cross through the FLD. Cycle Table A cycle table is displayed on the chart (position can be changed in settings). The cycle table comprises 6 columns: The Cycle Name (CYCLE): the name of the cycle which is its nominal wavelength in words. The Nominal Wavelength (NM): The nominal wavelength of the cycle measured in bars. The Current Wavelength (CR): The current recent wavelength of the cycle measured in bars. The Variation (VAR): The variation between the nominal wavelength and current wavelength as a percentage (%). The relevant Sequence Cycle (SEQ): The cycle over which the sequence of interactions with this FLD plays out. The Mode (MODE): Whether the cycle is currently Bearish, Neutral or Bullish. Benefits of using the Sentient FLD The cycle analysis shown with diamonds and circles marking the troughs, and next expected troughs of the cycles enable you to anticipate the timing of market turns (troughs and peaks in the price), because of the fact that cycles, by definition, repeat with some regularity. The results of the cycle analysis are also displayed on your chart in a table, and enable you to understand at a glance what the current mode of each cycle is, whether bullish, bearish or neutral. The identification of the sequence of interactions between price and the FLD enables you to anticipate the next interaction, and thereby expect either a price cross of the FLD or dynamic levels of support and resistance at the levels of the FLD lines, only visible to the FLD trader. When the next expected interaction between price and the FLD is an acceleration point (price is expected to cross over the FLD), that level can be used as a signal for entry into a trade. Similarly when the next expected interaction between price and the FLD is either support or resistance, that level can be used as a signal for entry into a trade when price reacts as expected, finding support or resistance. The targets that are generated as a result of price crossing the FLD represent cycle exhaustion levels and times, and can be used as take profit exits, or as levels after which stops should be tightened. The indicator optionally also calculates targets for longer timeframes, and displays them on your chart providing useful context for the influence of longer cycles without needing to change timeframe. Example In this image you can see an example of the different aspects of the indicator working on a 5 minute chart (details below): This is what the indicator shows: The 3 FLD lines are for the 100 minute (pink), 3 hour (orange) and 6 hour (green) cycles (refer to the cycle table for the cycle names). Previous targets can be seen, shown as pointed labels, with the same colors. The cycle table at the bottom left of the chart is colour coded, and indicates that the cycles are all currently running a bit long, by about 14%. Note also the grey-colored 6 hour target generated by the 15 x minute timeframe at 12:20. When targets are close together their accuracy is enhanced. At the foot of the chart we can see a collection of circles-and-whiskers in a nest-of-lows, indicating that a 12 hour cycle trough has been due to form in the past hour. The past interactions between price and the signal cycle are labelled and we can see the sequence of E (with some +E post-interaction taps), F and then G-H. The next interaction between price and the signal is the A category interaction - a long trading opportunity as price bounces out of the 12 hour cycle trough. Notice the green upward pointing triangles on the FLD lines, indicating that they are expected to provide acceleration points, where price will cross over the FLD and move towards a target above the FLD. The cycle table shows that the cycles of 6 hours and longer are all expected to be bullish (with the 12 hour cycle neutral to bullish). On the basis that we are expecting a 12 hour trough to form, and the 6 hour cycle targets have been reached, and the next interaction with the signal cycle is an A category acceleration point, we can plan to enter into a long trade. Two hours later This screenshot shows the situation almost 2 hours later: Notes: The expected 12 hour cycle trough has been confirmed in the cycle analysis, and now displayed as a stack of diamonds at 12:25 Price did cross over the signal cycle FLD (the 100 minute cycle, pink FLD line) as expected. That price cross is labelled as an A category interaction at 13:00. A 100 minute target was generated. That target was almost, but not quite reached in terms of price, indicating that the move out of the 12 hour cycle trough is not quite as bullish as would be expected (remember the 12 hour cycle is expected to be neutral-bullish). The time element of the target proved accurate however with a peak forming at the expected time. Stops could have been tightened at that time. Notice that price then came back to the signal FLD (100 minute) line at the time that the next 100 minute cycle trough was expected (see the pink circle-and-whiskers between 13:40 and 14:25, with the circle at 14:05. Price found support (as was expected) when it touched the signal FLD at 13:55 and 14:00, and that interaction has been labelled as a B-C category interaction pair. We also have a 3 hour target above us at about 6,005. That could be a good target for the move. Another 2 hours later This screenshot shows the situation another 2 hours later: Notes: We can see that the 100 minute cycle trough has been confirmed at 13:45 The nest-of-lows marking the time the 3 hour cycle trough was expected is between 15:00 and 15:45, with a probable trough in price at 15:00 The sequence of interactions is labelled: A at 13:00; B-C at 14:00; another B-C (double B-C interactions are common) at 14:30; E at 15:10; +E (a post E tap) at 16:20 Price has just reached a cluster of targets at 6005 - 6006. The 3 hour target we noted before, as well as a 6 hour target and a 12 hour target from the 15 x minute timeframe. Notice how after those targets were achieved, price has exhausted its upward move, and has turned down. The next expected interaction with the signal cycle FLD is an F category interaction. The downward pointing red triangles on the line indicate that the interaction is expected to be a price cross down, as price moves down into the next 6 hour cycle trough. Other Details The Sentient FLD indicator works on all time-based charts from 10 seconds up to monthly. The indicator works on all actively traded instruments, including forex, stocks, indices, commodities, metals and crypto.
Penunjuk Pine Script®
oleh sentient-trader
25
TASC 2025.01 Linear Predictive Filters█ OVERVIEW This script implements a suite of tools for identifying and utilizing dominant cycles in time series data, as introduced by John Ehlers in the "Linear Predictive Filters And Instantaneous Frequency" article featured in the January 2025 edition of TASC's Traders' Tips . Dominant cycle information can help traders adapt their indicators and strategies to changing market conditions. █ CONCEPTS Conventional technical indicators and strategies often rely on static, unchanging parameters, which may fail to account for the dynamic nature of market data. In his article, John Ehlers applies digital signal processing principles to address this issue, introducing linear predictive filters to identify cyclic information for adapting indicators and strategies to evolving market conditions. This approach treats market data as a complex series in the time domain. Analyzing the series in the frequency domain reveals information about its cyclic components. To reduce the impact of frequencies outside a range of interest and focus on a specific range of cycles, Ehlers applies second-order highpass and lowpass filters to the price data, which attenuate or remove wavelengths outside the desired range. This band-limited analysis isolates specific parts of the frequency spectrum for various trading styles, e.g., longer wavelengths for position trading or shorter wavelengths for swing trading. After filtering the series to produce band-limited data, Ehlers applies a linear predictive filter to predict future values a few bars ahead. The filter, calculated based on the techniques proposed by Lloyd Griffiths, adaptively minimizes the error between the latest data point and prediction, successively adjusting its coefficients to align with the band-limited series. The filter's coefficients can then be applied to generate an adaptive estimate of the band-limited data's structure in the frequency domain and identify the dominant cycle. █ USAGE This script implements the following tools presented in the article: Griffiths Predictor This tool calculates a linear predictive filter to forecast future data points in band-limited price data. The crosses between the prediction and signal lines can provide potential trade signals. Griffiths Spectrum This tool calculates a partial frequency spectrum of the band-limited price data derived from the linear predictive filter's coefficients, displaying a color-coded representation of the frequency information in the pane. This mode's display represents the data as a periodogram . The bottom of each plotted bar corresponds to a specific analyzed period (inverse of frequency), and the bar's color represents the presence of that periodic cycle in the time series relative to the one with the highest presence (i.e., the dominant cycle). Warmer, brighter colors indicate a higher presence of the cycle in the series, whereas darker colors indicate a lower presence. Griffiths Dominant Cycle This tool compares the cyclic components within the partial spectrum and identifies the frequency with the highest power, i.e., the dominant cycle . Traders can use this dominant cycle information to tune other indicators and strategies, which may help promote better alignment with dynamic market conditions. Notes on parameters Bandpass boundaries: In the article, Ehlers recommends an upper bound of 125 bars or higher to capture longer-term cycles for position trading. He recommends an upper bound of 40 bars and a lower bound of 18 bars for swing trading. If traders use smaller lower bounds, Ehlers advises a minimum of eight bars to minimize the potential effects of aliasing. Data length: The Griffiths predictor can use a relatively small data length, as autocorrelation diminishes rapidly with lag. However, for optimal spectrum and dominant cycle calculations, the length must match or exceed the upper bound of the bandpass filter. Ehlers recommends avoiding excessively long lengths to maintain responsiveness to shorter-term cycles.
Penunjuk Pine Script®
oleh PineCodersTASC
12