Inizia

Statistics

[Pandora][Swarm] Rapid Exponential Moving AverageENVISIONING POSSIBILITY What is the theoretical pinnacle of possibility? The current state of algorithmic affairs falls far short of my aspirations for achievable feasibility. I'm lifting the lid off of Pandora's box once again, very publicly this time, as a brute force challenge to conventional 'wisdom'. The unfolding series of time mandates a transcendental systemic alteration... THE MOVING AVERAGE ZOO: The realm of digital signal processing for trading is filled with familiar antiquated filtering tools. Two families of filtration, being 'infinite impulse response' (EMA, RMA, etc.) and 'finite impulse response' (WMA, SMA, etc.), are prevalently employed without question. These filter types are the mules and donkeys of data analysis, broadly accepted for use in finance. At first glance, they appear sufficient for most tasks, offering a basic straightforward way to reduce noise and highlight trends. Yet, beneath their simplistic facade lies a constellation of limitations and impediments, each having its own finicky quirks. Upon closer inspection, identifiable drawbacks render them far from ideal for many real-world applications in today's volatile markets. KNOWN FUNDAMENTAL FLAWS: Despite commonplace moving average (MA) popularity, these conventional filters suffer from an assortment of fundamental flaws. Most of them don't genuinely address core challenges of how to preserve the true dynamics of a signal while suppressing noise and retaining cutoff frequency compliance. Their simple cookie cutter structures make them ill-suited in actuality for dynamic market environments. In reality, they often trade one problem for another dilemma, forsaking analytics to choose between distortion and delay. A deeper seeded issue remains within frequency compliance, how adequately a filter respects (or disrespects) the underlying signal’s spectral properties according to it's assigned periodic parameter. Traditional MAs habitually distort phase relationships, causing delayed reactions with surplus lag or exaggerations with excessive undershoot/overshoot. For applications requiring timely resilience, such as algorithmic trading, these shortcomings are often functionally unacceptable. What’s needed is vigorous filters that can more accurately retain signal behaviors while minimizing lag without sacrificing smoothness and uniformity. Until then, the public MA zoo remains as a collection of corny compromises, rather than a favorable toolbelt of solutions. P.S.: In PSv7+, in my opinion, many of these geriatric MAs deserve no future with ease of access for the naive, simply not knowing these filters are most likely creating bigger problems than solving any. R.E.M.A. What is this? I prefer to think of it as the "radical EMA", definitely along my lines of a retire everything morte algorithm. This isn't your run of the mill average from the petting zoo. I would categorize it as a paradigm shifting rampant economic masochistic annihilator, sufficiently good enough to begin ruthlessly executing moving averages left and right. Um, yeah... that kind of moving average destructor as you may soon recognize with a few 'Filters+' settings adjustments, realizing ordinary EMA has been doing us an injustice all this time. Does it possess the capability to relentlessly exterminate most averaging filters in existence? Well, it's about time we find out, by uncaging it on the loose into the greater economic wilderness. Only then can we truly find out if it is indeed a radical exponential market accelerant whose time has come. If it is, then it may eventually become a reality erasing monolithic anomaly destined for greatness, ultimately changing the entire landscape of trading in perpetuity. UNLEASHING NEXT-GEN: This lone next generation exoweapon algorithm is intended to initiate the transformative beginning stages of mass filtration deprecation. However, it won't be the only one, just the first arrival of it's alien kind from me. Welcome to notion #1 of my future filtration frontier, on this episode of the algorithmic twilight zone. Where reality takes a twisting turn one dimension beyond practical logic, after persistent models of mindset disintegrate into insignificance, followed by illusory perception confronted into cognitive dissonance. An evolutionary path to genuine advancement resides outside the prison of preconceptions, manifesting only after divergence from persistent binding restrictions of dogmatic doctrines. Such a genesis in transformative thinking will catalyze unbounded cognitive potential, plowing the way for the cultivation of total redesigns of thought. Futuristic innovative breakthroughs demand the surrender of legacy and outmoded understandings. Now that the world's largest assembly of investors has been ensembled, there are additional tasks left to perform. I'm compelled to deploy this mathematical-weapon of mass financial creation into it's rightful destined hands, to "WE THE PEOPLE" of TV. SCRIPT INTENTION: Deprecate anything and everything as any non-commercial member sees desirably fit. This includes your existing code formulations already in working functional modes of operation AND/OR future projects in the works. Swapping is nearly as simple as copying and pasting with meager modifications, after you have identified comparable likeness in this indicators settings with a visual assessment. Results may become eye opening, but only if you dare to look and test. Where you may suspect a ta.filter() is lacking sufficient luster or may be flat out majorly deficient, employing rema, drema, trema, or qrema configurations may be a more suitable replacement. That's up to you to discern. My code satire already identifies likely bottom of the barrel suspects that either belong in the extinction record or have already been marked for deprecation. They are ordered more towards the bottom by rank where they belong. SuperSmoother is a masterpiece here to stay, being my original go-to reference filter. Everything you see here is already deprecated, including REMA... REMA CHARACTERISTICS - VERY low lag - No overshoot - Frequency compliant - Proper initialization at bar_index==0 - Period parameter accepts poitive floating point numerics (AND integers!) - Infinite impulse response (IIR) filter - Compact code footprint - Minimized computational overhead
Indicatore Pine Script®
di ImmortalFreedom
4
BTC Correlation PercentagePurpose This indicator displays the correlation percentage between the current trading instrument and Bitcoin (BTC/USDT) as a text label on the chart. It helps traders quickly assess how closely an asset's price movements align with Bitcoin's fluctuations. Key Features Precise Calculation: Shows correlation as a percentage with one decimal place (e.g., 25.6%). Customizable Appearance: Allows adjustment of colors, position, and calculation period. Clean & Simple: Displays only essential information without cluttering the chart. Universal Compatibility: Works on any timeframe and with any trading pair. Input Settings Core Parameters: BTC Symbol – Ticker for Bitcoin (default: BINANCE:BTCUSDT). Correlation Period – Number of bars used for calculation (default: 50 candles). Show Correlation Label – Toggle visibility of the correlation label. Visual Customization: Text Color – Label text color (default: white). Background Color – Label background color (default: semi-transparent blue). Border Color – Border color around the label (default: gray). Label Position – Where the label appears on the chart (default: top-right). Interpreting Correlation Values 70% to 100% → Strong positive correlation (asset moves in sync with BTC). 30% to 70% → Moderate positive correlation. -30% to 30% → Weak or no correlation. -70% to -30% → Moderate negative correlation (asset moves opposite to BTC). -100% to -70% → Strong negative correlation. Practical Use Cases For Altcoins: A correlation above 50% suggests high dependence on Bitcoin’s price action. For Futures Trading: Helps assess systemic risks tied to BTC movements. During High Volatility: Determines whether an asset’s price change is driven by its own factors or broader market trends. How It Works The indicator recalculates automatically with each new candle. For the most reliable results, it is recommended for use on daily or higher timeframes. This tool provides traders with a quick, visual way to gauge Bitcoin’s influence on other assets, improving decision-making in crypto markets. 🚀 This response is AI-generated, for reference only. New chat
Indicatore Pine Script®
di KUBIK73
TRI - Smart Zones============================================================================ # TRI - SMART ZONES v2.0 ## Professional Smart Money Concepts Indicator for Pine Script v6 ============================================================================ ## 📊 OVERVIEW **TRI - Smart Zones** is a comprehensive Smart Money Concepts indicator that combines multiple institutional trading concepts into a single, powerful tool. Built with Pine Script v6 for optimal performance and reliability. ## 🎯 CORE FEATURES ### **Fair Value Gaps (FVG)** - **Detection**: Automatic identification of price imbalances - **Types**: Bullish and Bearish Fair Value Gaps - **Threshold**: Customizable gap size requirements (0.1% default) - **Extension**: Configurable zone projection length - **Mitigation**: Real-time tracking of gap fills ### **Order Blocks (OB)** - **Detection**: Volume-based institutional footprint identification - **Types**: Bullish and Bearish Order Blocks - **Method**: Pivot-based volume analysis with configurable lookback - **Validation**: Market structure confirmation required - **Extension**: Adjustable zone projection ### **BSL/SSL Liquidity Levels** - **Multi-Timeframe**: Automatic higher timeframe reference - **Dynamic**: Real-time level updates and extensions - **Visual**: Clear line markings with timeframe labels - **Smart**: Adaptive timeframe selection based on current chart ### **Fibonacci Extensions** - **ZigZag Integration**: Advanced pivot point detection - **Levels**: Customizable Fibonacci ratios (38.2%, 61.8%, 100%, 161.8%) - **Projection**: Dynamic extension from swing points - **Visual**: Subtle dashed lines with level/price labels ### **Smart Dashboard** - **Zone Statistics**: Real-time FVG and OB counts - **Success Rates**: Mitigation percentages for each zone type - **Market Bias**: Intelligent bullish/bearish/neutral assessment - **Positioning**: Customizable location and size ### **Zone Analysis Engine** - **Technical Confluence**: RSI, ADX, ATR, Volume analysis - **VWAP Integration**: Institutional price reference - **Confidence Scoring**: High/Mid/Low signal classification - **Signal Arrows**: Visual trade direction indicators ## 🔔 ALERT SYSTEM ### **Market Structure Alerts** - `Market Bias Changed` - Shift in overall market sentiment - `BSL Touched` - Buy Side Liquidity level reached - `SSL Touched` - Sell Side Liquidity level reached ### **Zone Touch Alerts** - `OB Touched` - Any Order Block interaction - `Bullish OB Touched` - Bullish Order Block touch - `Bearish OB Touched` - Bearish Order Block touch - `FVG Touched` - Any Fair Value Gap interaction - `Bullish FVG Touched` - Bullish FVG touch - `Bearish FVG Touched` - Bearish FVG touch - `Zone Touched` - Any Smart Zone interaction - `Bullish Zone Touched` - Any bullish zone touch - `Bearish Zone Touched` - Any bearish zone touch ## ⚙️ CONFIGURATION ### **Zone Detection** - Enable/disable FVG and OB detection independently - Maximum zones per type (3-15, default: 8) - Zone-specific threshold and extension settings ### **Visual Customization** - Individual color schemes for each zone type - Adjustable transparency levels - Configurable line styles and widths - Dashboard positioning and sizing options ### **Technical Analysis** - RSI, ADX, ATR period customization - Volume threshold multipliers - Confidence level color coding - Signal display toggle ## 🚀 PINE SCRIPT v6 OPTIMIZATIONS - **User-Defined Types**: Structured data for zones and statistics - **Methods**: Type-specific operations for better code organization - **Enhanced Arrays**: Optimized memory management - **Switch Statements**: Improved performance for zone classification - **Error Handling**: Robust input validation and edge case management - **Performance**: Efficient algorithms for real-time analysis ## 📈 TRADING APPLICATIONS ### **Entry Strategies** - Zone confluence for high-probability setups - Multi-timeframe confirmation via BSL/SSL - Fibonacci extension targets - Signal arrows for directional bias ### **Risk Management** - Zone mitigation for stop-loss placement - Market bias for position sizing - Dashboard statistics for strategy validation ### **Market Analysis** - Institutional footprint identification - Liquidity level mapping - Market structure assessment - Trend continuation vs reversal analysis ## 🔧 TECHNICAL SPECIFICATIONS - **Version**: Pine Script v6 - **Overlay**: True (draws on price chart) - **Max Objects**: 100 boxes, 100 lines, 50 labels - **Performance**: Optimized for real-time analysis - **Compatibility**: All TradingView chart types and timeframes
Indicatore Pine Script®
di riccardo_tempesta
1
Simple Leveraged PnLThis script shows your live trade PnL, ROE, R:R ratio, margin, leverage, entry, TP, and SL directly on the chart. It draws: Green/red zones for your Take Profit and Stop Loss ranges. A pinned info card (movable to any corner of the chart) showing all key trade details in one place. You can fully customize: Card position (top/middle/bottom × left/middle/right) Text size, colors, and background Zone transparency It works for both Long and Short positions and updates in real time.
Indicatore Pine Script®
di WinnersBeatTheMarket
☑️VMA Win % Dashboard for Different LengthsVMA Win % Dashboard for Different Lengths Overview This Pine Script indicator evaluates the performance of a Variable Moving Average (VMA) for lengths 13 to 17. It tracks the success rate of price hitting target levels during bullish or bearish trends and displays results in a table. It is part of a combination that includes two other indicators: ✅ VMA Avg ATR + Days to Targets Total Improved 🎯 and 📊 Visual MTF VMA Dashboard🔄️. How It Works 1. Inputs: - ATR Length: 14 periods (for volatility). - VMA Lengths: 13, 14, 15, 16, 17. 2. VMA Calculation: - Uses closing price. - Measures price increases (pdm) and decreases (mdm). - Smooths data to calculate a Directional Movement Index (DMI). - Adjusts VMA based on momentum and volatility. 3. Trend Detection: - Bullish: VMA rises (green). - Bearish: VMA falls (red). - Neutral: No direction (white). - Confirms trends align with daily and 195-minute timeframes. 4. Performance Tracking: - Trend Start: Records price, ATR, and time when a trend begins. - Price Movement: Tracks highest (bullish) or lowest (bearish) price. - Targets: ---- T1: Starting price ± historical average movement (ATR-based). ---- T2: Starting price ± 6x ATR. - Statistics: ---- Counts hits (reached T1/T2) and misses (didn’t reach T1). ---- Calculates win percentages: % of trends hitting T1. 5. Dashboard: - Table with columns: VMA Length, Win % Up, Win % Down. - Shows win percentages for each length (e.g., 75.23%). Use Cases - Trend Trading: Confirms trend direction and success rate. - Optimization: Finds the best VMA length. - Risk Management: Sets ATR-based trade targets. - Combination: Complements ✅ VMA Avg ATR + Days to Targets Total Improved 🎯 and 📊 Visual MTF VMA Dashboard🔄️ for a complete strategy. Example - VMA 15: 80% Win Up, 55% Win Down → Best for bullish trades. - VMA 13: 75% Win Up, 60% Win Down → More balanced. Limitations - Based on historical data, not future predictions. - Only analyzes trends aligned with higher timeframes. - No VMA lines or signals plotted on the chart.
Indicatore Pine Script®
di adonilopez
Combined Futures Open Interest [Sam SDF-Solutions]The Combined Futures Open Interest indicator is designed to provide comprehensive analysis of market positioning by aggregating open interest data from the two nearest futures contracts. This dual-contract approach captures the complete picture of market participation, including rollover dynamics between front and back month contracts, offering traders crucial insights into institutional positioning and market sentiment. Key Features: Dual-Contract Aggregation: Automatically identifies and combines open interest from the first and second nearest futures contracts (e.g., ES1! + ES2!), providing a complete view of market positioning that single-contract analysis might miss. Multi-Period Analysis: Tracks open interest changes across multiple timeframes: 1 Day: Immediate market sentiment shifts 1 Week: Short-term positioning trends 1 Month: Medium-term institutional flows 3 Months: Quarterly positioning aligned with contract expiration cycles Smart Data Handling: Utilizes last known values when data is temporarily unavailable, preventing false signals from data gaps while clearly indicating when stale data is being used. EMA Smoothing: Incorporates a customizable Exponential Moving Average (default 65 periods) to identify the underlying trend in open interest, filtering out daily noise and highlighting significant deviations. Dynamic Visualization: Color-coded main line showing directional changes (green for increases, red for decreases) Optional fill areas between OI and EMA to visualize momentum Separate contract lines for detailed rollover analysis Customizable labels for significant percentage changes Comprehensive Information Table: Displays real-time statistics including: Current total open interest across both contracts Period-over-period changes in absolute and percentage terms EMA deviation metrics Visual status indicators for quick assessment Contract symbols and data quality warnings Alert System: Configurable alerts for: Significant daily changes (customizable threshold) EMA crossovers indicating trend changes Large percentage movements suggesting institutional activity How It Works: Contract Detection: The indicator automatically identifies the base futures symbol and constructs the appropriate contract codes for the two nearest expirations, or accepts manual symbol input for non-standard contracts. Data Aggregation: Open interest data from both contracts is retrieved and summed, providing a complete picture that accounts for positions rolling between contracts. Historical Comparison: The indicator calculates changes from multiple lookback periods (1/5/22/66 days) to show how positioning has evolved across different time horizons. Trend Analysis: The EMA overlay helps identify whether current open interest is above or below its smoothed average, indicating momentum in position building or reduction. Visual Feedback: The main line changes color based on daily changes, while the optional table provides detailed numerical analysis for traders requiring precise data. ___________________ This indicator is essential for futures traders, particularly those focused on index futures, commodities, or currency futures where understanding the aggregate positioning across nearby contracts is crucial. It's especially valuable during rollover periods when positions shift between contracts, and for identifying institutional accumulation or distribution patterns that single-contract analysis might miss. By combining multiple timeframe analysis with intelligent data handling and clear visualization, it simplifies the complex task of monitoring open interest dynamics across the futures curve.
Indicatore Pine Script®
di SDF-Solutions
Quant Signals: Market Sentiment Monitor HUDWavelets & Scale Spectrum This indicator is ideal for traders who adapt their strategy to market conditions — such as swing traders, intraday traders, and system developers. Trend-followers can use it to confirm trending conditions before entering. Mean-reversion traders can spot choppy markets where reversals are more likely. Risk managers can monitor volatility shifts and regime changes to adjust position size or pause trading. It works best as a market context filter — telling you the “weather” before you decide on the trade. Wavelets are like tiny “measuring rulers” for price changes. Instead of looking at the whole chart at once, a wavelet looks at differences in price over a specific time scale — for example, 2 bars, 4 bars, 8 bars, and so on. The scale spectrum is what you get when you measure volatility at several of these scales and then plot them against scale size. If the spectrum forms a straight line on a log–log chart, it means price changes follow a consistent pattern across time scales (a power-law relationship). The slope of that line gives the Hurst exponent (H) — telling you whether moves tend to persist (trend) or reverse (mean-revert). The height of the line gives you the volatility (σ) — the average size of moves. This approach works like a microscope, revealing whether the market’s behaviour is consistent across short-term and long-term horizons, and when that behaviour changes. This tool applies a wavelet-based scale-spectrum analysis to price data to estimate three key market state measures inside a rolling window: Hurst exponent (H) — measures persistence in price moves: H > ~0.55 → market is trending (moves tend to continue). H < ~0.45 → market is choppy/mean-reverting (moves tend to reverse). Values near 0.5 indicate a neutral, random-walk-like regime. Volatility (σ) — the average size of price swings at your chart’s timeframe, optionally annualized. Rising volatility means larger price moves, falling volatility means smaller moves. Fit residual — how well the observed multi-scale volatility fits a clean power-law line. Low residual = stable behaviour; high residual = structural change (possible regime shift).
Indicatore Pine Script®
di Faduzzle
Quant Signals: Entropy w/ ForecastThis is the first of many quantitative signals I plan to create for TV users. Most technical analysis (TA) tools—like moving averages, oscillators, or chart patterns—are heuristic: they’re based on visually identifiable shapes, threshold crossovers, or empirically chosen rules. These methods rarely quantify the information content or structural complexity of market data. By quantifying market predictability before making a forecast, this method filters out noise and focuses your trading only during statistically favorable conditions—something traditional TA cannot objectively measure. This MEPP-based approach is quantitative and model-free: It comes from information theory and measures Shannon entropy rate to assess how predictable the market is at any moment. Instead of interpreting price formations, it uses a data-compression algorithm (Lempel–Ziv) to capture hidden structure in the sequence of returns. Forecasts are generated using a principle from statistical physics (Maximum Entropy Production), not historical chart patterns. In short, this method measures the market's predictability BEFORE deciding a directional forecast is worth trusting. This tool is to inform TA traders on the market's current regime, whether it is smooth and predictable or it is volatile and turbulent. Technical Introduction: In information theory, Shannon entropy measures the uncertainty (or information content) in a sequence of data. For markets, the entropy rate captures how much new information price returns generate over time: Low entropy rate → price changes are more structured and predictable. High entropy rate → price changes are more random and unpredictable. By discretizing recent returns into quartile-based states, this indicator: Calculates the normalized entropy rate as a regime filter. Uses MEPP to forecast the next state that maximizes entropy production. Displays both the regime status (predictable vs chaotic) and the forecast bias (bullish/bearish) in a dashboard. Measurements & How to Use Them TLDR: HIGH ENTROPY -> information generation/market shift -> Don't trust forecast/strategy 1. H (bits/sym) Shannon entropy rate of the last μ discrete returns, in bits per symbol (0–2). Lower → more predictable; higher → more random. Use as a raw measure of market structure. 2. H_max (log₂Ω) Theoretical maximum entropy for Ω states. Here Ω = 4 → H_max = 2.0 bits. Reference value for normalization. 3. Entropy (norm) H / H_max, scaled between 0 and 1. < 0.5–0.6 → predictable regime; > 0.6 → chaotic regime. Main regime filter — forecasts are more reliable when below your threshold. 4. Regime Label based on Entropy (norm) vs your entThresh. LOW (predictable) = higher odds forecast will be correct. HIGH (chaotic) = forecasts less reliable. 5. Next State (MEPP Forecast) Discrete return state (1–4) predicted to occur next, chosen to maximize entropy production: Large Down (strong bearish) Small Down (mild bearish) Small Up (mild bullish) Large Up (strong bullish) Use as your bias direction. 6. Bias Simplified label from the Next State: States 1–2 = Bearish bias (red) States 3–4 = Bullish bias (green) Align strategy direction with bias only in LOW regime.
Indicatore Pine Script®
di Faduzzle
Relative Volume + Z-score + Normal Volume + Avg. VolumeA statistical way to visualize volume analytically compared to traditional volume. All Lookback Periods and Colors can be changed so user can make it feel personalized - Relative Volume (RVOL) visualizer with the color of the histogram bar changing to represent exceeding a threshold specified by the user For example --> (1.5 = Orange Bar) & (2 = Red Bar) - Toggle View between RVOL visualization of volume vs. normal view of volume plot - Z score lookback for volume across specified lookback per what user wants (dot/symbol above the bar) - Average Volume Plot
Indicatore Pine Script®
di ranger089
ADR/ATR Session by LK## **Features** 1. **Custom ADR & ATR Calculation** * Calculates **Average Daily Range (ADR)** and **Average True Range (ATR)** separately for: * **Session timeframe** (default H4 / 06:00–13:00) * **Daily timeframe** * Independent smoothing method selection (**SMA, EMA, RMA, WMA**) for H4 ADR, H4 ATR, Daily ADR, and Daily ATR. 2. **Percentage Metrics** * % of ADR / ATR covered by the **current H4 bar**. * ADR / ATR expressed as a percentage of the **current price**. * % of ADR already reached for the **current day**. * % of Daily ATR vs current day’s True Range. 3. **Dynamic Chart Lines** * Draws **3 lines for H4**: Session Open, ADR High, ADR Low. * Draws **3 lines for Daily**: Daily Open, ADR High, ADR Low. * Lines **extend to the right** so they stay visible across the chart. * Colors and widths are fully customizable. 4. **Real-Time Data Table** * Compact table displaying all ADR/ATR values and percentages. * Adjustable table font size (**tiny, small, normal, large, huge**). * Transparent background option for minimal chart obstruction. 5. **Flexible Session Settings** * Select session start and end time in hours/minutes. * Choose session timezone (chart timezone or major financial centers). * Toggle H4 lines, Daily lines separately. 6. **Lookahead Control** * Option to wait for higher-timeframe candle close before updating values (more accurate, less repainting). --- ## **How to Use** ### **1. Adding the Indicator** * Copy and paste the Pine Script into TradingView’s Pine Editor. * Click **“Add to chart”**. * Make sure your chart supports the higher timeframes you choose (e.g., H4 and Daily). ### **2. Setting Your Session** * **Session Start Hour** & **End Hour** → Defines the intraday session to measure ADR/ATR (default: 06:00–13:00). * **Session Timezone** → Pick “Chart” or a major financial center (e.g., New York, London, Tokyo). ### **3. Choosing Smoothing Methods** * For each ADR/ATR (H4 and Daily), choose: * SMA (Simple) * EMA (Exponential) * RMA (Wilder’s smoothing) * WMA (Weighted) ### **4. Adjusting Chart Display** * **Show H4 Lines** → Displays session open and ADR High/Low for the current H4 session. * **Show Daily Lines** → Displays daily open and ADR High/Low. * Customize line colors and widths. ### **5. Reading the Table** * **H4 Section** * ADR / ATR values for the selected session. * % of ADR/ATR covered by the **current H4 bar**. * ADR/ATR as % of the current price. * **Daily Section** * ADR / ATR for the daily timeframe. * % of ADR already covered by today’s range. * ADR/ATR as % of price. ### **6. Pro Tips** * Use **H4 ADR %** to gauge intraday exhaustion — if current range is near 100%, market may slow or reverse. * Use **Daily ADR %** for swing trade context — if a day has moved beyond its ADR, expect lower continuation probability. * Combine with support/resistance to identify high-probability reversal zones.
Indicatore Pine Script®
di kimngan894923
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.
Indicatore Pine Script®
di Goldman_Gleb
Entropy (Fiedor/Kontoyiannis) - Part 2 of Fiedor's TheoryThis indicator estimates the Shannon entropy of a price series using a Markov chain model of binary returns, following the approach of Fiedor (2014) and Kontoyiannis (1997). % of Max shows current entropy as a percentage of its theoretical maximum (1 bit for binary up/down moves). Percentile ranks the current entropy against historical values in the chosen lookback window. High entropy suggests price movement is less predictable by frequentist models; low entropy implies more structure and predictability. Use this as an informational oscillator, not a trading signal. This is a visualization of Part 1 of Fiedor's Theory. The same entropy logic is already embedded in Part 1 however the second pane is a nice reminder of why it works.
Indicatore Pine Script®
di Faduzzle
Binance Funding Rates [vichtoreb]Source: www.binance.com The funding rate has two components: the interest rate and the average Premium Index. Binance furnishes the Premium Index data for crypto assets on the TradingView platform. This script uses that data to calculate the funding rate. Binance updates the Premium Index every 5 seconds. The average Premium Index (denoted **P\_avg**) is the time-weighted average of all Premium Index data points: P_avg = wma(Premium Index, n) where **n** is the averaging length. At each change time—8:00 PM, 4:00 AM, and 12:00 PM (UTC-4)—Binance sets P_avg = wma(Premium Index, 5 760) This is the weighted moving average of the last 8 hours because 5 760 × 5 s = 8 h. Binance then calculates the new funding rate: Funding Rate = P_avg + clamp(interest rate − P_avg, −0.05 %, 0.05 %) This value updates only at those change times (8:00 PM, 4:00 AM, and 12:00 PM, UTC-4). **Indicator precision** TradingView limits historical requests to 5 000 candles. To match Binance exactly, 5 760 candles are required. As a workaround, the script samples the Premium Index every *resolution* seconds (or minutes), where *resolution* is the indicator’s timeframe input. If it weren't for this limitation, setting resolution = 5 sec, we would get EXACTLY the same result as the official one **Interest rate** On Binance Futures, the interest rate is 0.03 % per day by default (0.01 % per funding interval, as funding occurs every 8 hours). This does not apply to certain contracts, such as ETH/BTC, for which the interest rate is 0 %. **Estimate line** If the “show estimate” input is enabled, the indicator plots wma(Premium Index, n) + clamp(interest rate − P_avg, −0.05 %, 0.05 %) with **n** equal to the number of bars that have elapsed since the last funding-rate change.
Indicatore Pine Script®
di victhoreb
Latent Regime Informed Monte Carlo ForecastThis script uses a Monte Carlo simulation to forecast where price might be a set number of bars into the future (default 6 bars ahead). It generates hundreds of possible future price paths based on an average move (drift) and random shocks (volatility). The result is a distribution of outcomes, displayed as probability zones: the median (most likely), inner bands (50% confidence), and wider bands (80% and 95% confidence). Due to the randomness assumption in Monte Carlo simulations, the paths are not very important so to minimize cluttering on the graphs we only plot bands. These zones help you visualize uncertainty, set stops and targets based on probabilities, and spot when market behavior changes. The accuracy of any Monte Carlo forecast depends heavily on how well you estimate trend and volatility. By default and no prior information the Monte Carlo simulation gives you a parabolic forecast that assumes absolute randomness. This is where the Kalman filter comes in. The filter (derived from control theory) aims to detect latent (unobservable) traits about the system by continuously updating its transition probabilities to better understand how the latent traits affect the observable measurement (price). With each new observable state we get better and better transition probabilities and enhances our understanding about the latent and unobservable market characteristics like trend and volatility. Both crucial measurements for short term market sentiment. Extracting these measurements for market sentiment informs us how to better parametrize the Monte Carlo simulation for a better forecast. Each bar, the KF updates its estimates based on how close its last prediction was to reality. In calm periods, it holds estimates steady; in volatile periods, it adapts quickly. This gives you real-time, low-lag measurements of both trend and volatility. By feeding these adaptive estimates into the Monte Carlo simulation, the forecast becomes much more responsive to current market conditions. In trends, the predicted paths tilt toward the direction of movement; in choppy markets, they spread wider but stay centered; when volatility spikes, the probability zones expand immediately. The result is a dynamic forecast tool that adjusts on every bar, giving you a clearer, probability-based picture of where the market could go next. This is my very first script and I would love feedback/ideas for different topics. My background is in economics/mathematics and interests lie in time series analysis/exploring financial features for DS
Indicatore Pine Script®
di Faduzzle
Adaptive Correlation Engine (ACE)🧠 Adaptive Correlation Engine (ACE) Quantify inter-asset relationships with adaptive lag detection and actionable insights. 📌 What is ACE? The Adaptive Correlation Engine (ACE) is a precision tool for seeking to uncover meaningful relationships between two assets — not just raw correlation, but also lag dynamics, leader detection, and alignment vs. divergence classification. Unlike static correlation tools, ACE intelligently scans multiple lag windows to find: ✅ The maximum correlation between the base asset and a comparison symbol ⏱️ The optimal lag (if any) at which the correlation is strongest 🧭 Whether the assets are Aligned (positive correlation) or Divergent (inverse) 🔁 Which symbol is leading, and by how many bars 📈 Actionable signal strength based on a user-defined correlation threshold ⚙️ How It Works Correlation Scan: For each bar, ACE checks the correlation between the charted asset (close) and a lagged version of the comparison asset across a sliding window of lookback periods. Lag Optimization: The engine searches from lag 0 up to your specified Max Lag to find where the correlation (positive or negative) is most significant. Relationship Classification: The indicator classifies the relationship as: Aligned: Positive correlation above the threshold Divergent: Negative correlation above the threshold Synchronous: No lag detected Low Signal: Correlation is weak or noisy Visual & Tabular Insights: ACE plots the highest detected correlation on the chart and shows an insight table displaying: - Correlation value - Detected lag - Direction type (aligned/divergent) - Leading asset - Suggested action (e.g., “Likely continuation” or “Possible mean reversion”) 💡 How to Use It Use ACE to identify leadership patterns between assets (e.g., ETH leads altcoins, SPX leads crypto, etc.) Spot potential lagging trade setups where one asset’s move may soon echo in another Confirm or challenge correlation-based trading assumptions with data Combine with technical indicators or price action to time entries and exits more confidently 🔔 Alerts Built-in alerts notify you when correlation strength crosses your actionable threshold, classified by alignment or divergence. 🛠️ Inputs Compare Symbol: The asset to compare against (e.g., INDEX:ETHUSD) Correlation Lookback: Rolling window for calculating correlation Max Lag Bars: Maximum lag shift to test Minimum Actionable Correlation: Signal threshold for trade-worthy insights ⚠️ Disclaimer This tool is for research and informational purposes only. It does not constitute financial advice or a trading signal. Always perform your own due diligence and consult a financial advisor before making investment decisions.
Indicatore Pine Script®
di RWCS_LTD
Information Theory Market AnalysisINFORMATION THEORY MARKET ANALYSIS OVERVIEW This indicator applies mathematical concepts from information theory to analyze market behavior, measuring the randomness and predictability of price and volume movements through entropy calculations. Unlike traditional technical indicators, it provides insight into market structure and regime changes. KEY COMPONENTS Four Main Signals: • Price Entropy (Deep Blue): Measures randomness in price movements • Volume Entropy (Bright Blue): Analyzes volume pattern predictability • Entropy MACD (Purple): Shows relationship between price and volume entropy • SEMM (Royal Blue): Stochastic Entropy Market Monitor - overall market randomness gauge Market State Detection: The indicator identifies seven distinct market states: • Strong Trending (SEMM < 0.1) • Weak Trending (0.1-0.2) • Neutral (0.2-0.3) • Moderate Random (0.3-0.5) • High Randomness (0.5-0.8) • Very Random (0.8-1.0) • Chaotic (>1.0) KEY FEATURES Advanced Analytics: • Signal Strength Confluence: 0-5 scale measuring alignment of multiple factors • Entropy Crossovers: Detects shifts between accumulation and distribution phases • Extreme Readings: Identifies statistical outliers for potential reversals • Trend Bias Analysis: Directional momentum assessment Information Dashboard: • Real-time entropy values and market state • Signal strength indicator with visual highlighting • Trend bias with directional arrows • Color-coded alerts for extreme conditions Customizable Display: • Adjustable SEMM scaling (5x to 100x) for optimal visibility • Multiple line styles: Smooth, Stepped, Dotted • 9 table positions with 3 size options • Professional blue color scheme with transparency controls Comprehensive Alert System - 15 Alert Types Including: • Extreme entropy readings (price/volume) • Crossover signals (dominance shifts) • Market state changes (trending ↔ random) • High confluence signals (3+ factors aligned) HOW TO USE Reading the Signals: • Entropy Values > ±25: Strong structural signals • Entropy Values > ±40: Extreme readings, potential reversals • SEMM < 0.2: Trending market favors directional strategies • SEMM > 0.5: Random market favors range/scalping strategies Signal Confluence: Look for multiple factors aligning: • Signal Strength ≥ 3.0 for higher probability setups • Background highlighting indicates confluence • Table shows real-time strength assessment Timeframe Optimization: • Short-term (1m-15m): Entropy Length 14-22, Sensitivity 3-5 • Swing Trading (1H-4H): Default settings optimal • Position Trading (Daily+): Entropy Length 34-55, Sensitivity 8-12 EDUCATIONAL APPLICATIONS Market Structure Analysis: • Understand when markets are trending vs. ranging • Identify accumulation and distribution phases • Recognize extreme market conditions • Measure information content in price movements Information Theory Concepts: • Binary entropy calculations applied to financial data • Probability distribution analysis of returns • Statistical ranking and percentile analysis • Momentum-adjusted randomness measurement TECHNICAL DETAILS Calculations: • Uses binary entropy formula: - • Percentile ranking across multiple timeframes • Volume-weighted probability distributions • RSI-adjusted momentum entropy (SEMM) Customization Options: • Entropy Length: 5-100 bars (default: 22) • Average Length: 10-200 bars (default: 88) • Sensitivity: 1.0-20.0 (default: 5.0, lower = more sensitive) • SEMM Scaling: 5.0-100.0x (default: 30.0) IMPORTANT NOTES Risk Considerations: • Indicator measures probabilities, not certainties • High SEMM values (>0.5) suggest increased market randomness • Extreme readings may persist longer than expected • Always combine with proper risk management Educational Purpose: This indicator is designed for: • Market structure analysis and education • Understanding information theory applications in finance • Developing probabilistic thinking about markets • Research and analytical purposes Performance Tips: • Allow 200+ bars for proper initialization • Adjust scaling and transparency for optimal visibility • Use confluence signals for higher probability analysis • Consider multiple timeframes for comprehensive analysis DISCLAIMER This indicator is for educational and analytical purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own research and consider your risk tolerance before making trading decisions. Version: 5.0 Category: Oscillators, Volume, Market Structure Best For: All timeframes, trending and ranging markets Complexity: Intermediate to Advanced
Indicatore Pine Script®
di bearbearbull23
Position Size 📐 DT/ST (Today's Open)💡 Purpose: This indicator automatically calculates intraday (DT) and swing trading (ST) position sizes based on your account capital, risk per trade, and stop-loss percentage, using today’s daily open price as the entry price reference. ⚙️ Main Functionalities: Dynamic Position Sizing Calculates Full size position based on the maximum risk you allow per trade. Breaks it down into ¼ Size, ⅓ Size, and ½ Size positions for flexible scaling. Two Distinct Trading Styles: DT (Day Trading) – Uses your specified intraday stop-loss % (default: 2%). ST (Swing Trading) – Uses your specified swing stop-loss % (default: 10%). Lot Size Rounding Automatically rounds quantities to a chosen lot size (e.g., 1 for cash equity or futures lot size for derivatives). Customizable Table Position Display the table anywhere on your chart: Top Right, Top Left, Bottom Right, or Bottom Left. Optimized for Dark or Light Themes Yellow header with black text for visibility. Blue row labels for strategy type. Grey background with white text for calculated values. Live Market Adaptation All values update in real-time as today’s daily open price changes (on new daily candles). Works for any symbol, asset class, or time frame. 🧮 Formula: Position Size (Full) = Max Risk ₹ / (Price × StopLoss%) ¼, ⅓, and ½ Sizes = Scaled from Full size 📌 Ideal For: Traders who want quick, ready-to-use position sizes right on their chart. Those who follow fixed risk-per-trade and need fast decision-making without manual calculations.
Indicatore Pine Script®
di varshashoots