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ETF Leverage VerificationDo leveraged ETFs really return what they promise? Do they return the exact 2x or 3x? Or a slightly different multiple? How much do they deviate from the promised leverage multiples? Do these deviations impact investors in a positive or negative manner? These are the questions that I want to answer with this indicator. The ETF Leverage Verification indicator challenges the conventional understanding of leveraged ETFs by measuring how they actually perform versus their theoretical targets. Instead of assuming leveraged ETFs perfectly track their target multiple, this indicator quantifies the real-world behavior by comparing the expected returns versus the actual results on every trading day. Key Features Measures actual versus expected performance of leveraged ETFs Tracks deviation patterns across thousands of trading days Identifies asymmetric behavior in up versus down markets Quantifies beneficial "cushioning effect" during market declines Provides statistical summary of performance patterns Works with any leverage factor (2x, 3x, -1x, etc.) Compatible with all leveraged ETFs (equity, bond, commodity, volatility) How to Use the Indicator Enter the Expected Leverage Factor (default: 2.0) Select the Base Asset (underlying index, e.g., SPX) Select the Leveraged Asset (leveraged ETF, e.g., SSO) Understanding the Results Green markers: Days when the ETF outperformed its expected multiple Red markers: Days when the ETF underperformed its expected multiple Data Table: Positive Deviations: Count of days with better-than-expected performance Negative Deviations: Count of days with worse-than-expected performance Avg Deviation: Average magnitude of deviation from expected returns Frequency Skew: Difference between beneficial deviations in down vs. up markets Impact: Overall assessment of pattern benefit to investors Summary Label: Percentage of positive deviations in up and down markets Total sample size for statistical significance Key Patterns to Look For Positive Deviation in Negative Days: This occurs when a leveraged ETF falls less than expected during market declines. For example, if SPX falls 1% and a 2x ETF falls only 1.8% (instead of the expected 2%), this creates a +0.2% deviation. This pattern is beneficial as it provides downside protection. Negative Deviation in Positive Days: This happens when a leveraged ETF rises less than expected during market advances. For example, if SPX rises 1% and a 2x ETF rises only 1.9% (instead of the expected 2%), this creates a -0.1% deviation. This pattern reduces upside performance. Frequency Skew: The most critical metric that measures how much more frequently beneficial deviations occur in down markets compared to up markets. A higher positive skew indicates a stronger asymmetric pattern that helps long-term performance. Mathematical Background The indicator computes the deviation between expected and actual performance: Deviation = Actual Return - Expected Return Where: Expected Return = Base Asset Return × Leverage Factor The deviation is then categorized into four possible outcomes: Positive deviation on positive market days Negative deviation on positive market days Positive deviation on negative market days Negative deviation on negative market days In short, more positive deviations are good for investors. Please feel free to criticize. I'm happy to improve the indicator.
Pine Script® göstergesi
HenriqueCentieiro tarafından
Polynomial Regression + RSI Explosive Zones// Sonic R EMA_len = input.int(89, title="EMA Signal Length") HiLoLen = input.int(34, title="PAC EMA Length") // Polynomial Regression regression_length = input.int(10, title="Regression Length") fractal_size = input.int(2, title="Fractal Size") // Color inputs for regression colorMid = input.color(color.red, title="Mid Line Color") colorMax = input.color(color.orange, title="Max Line Color") colorMin = input.color(color.green, title="Min Line Color") colorUpper = input.color(color.blue, title="Upper Line Color") colorLower = input.color(color.purple, title="Lower Line Color") // === SONIC R === // PAC lines pacC = ta.ema(close, HiLoLen) pacL = ta.ema(low, HiLoLen) pacH = ta.ema(high, HiLoLen) plot(pacL, title="PAC Low EMA", color=color.new(color.blue, 50)) plot(pacH, title="PAC High EMA", color=color.new(color.blue, 50)) plot(pacC, title="PAC Close EMA", color=color.new(color.blue, 0), linewidth=2) fill(plot(pacL), plot(pacH), color=color.aqua, transp=90, title="Fill PAC") // EMA lines ema610 = ta.ema(close, 610) ema200 = ta.ema(close, 200) emaSignal = ta.ema(close, EMA_len) plot(ema610, title="EMA 610", color=color.white) plot(ema200, title="EMA 200", color=color.fuchsia) plot(emaSignal, title="EMA Signal", color=color.orange, linewidth=2)
Pine Script® göstergesi
phuocminhpham85 tarafından
FVG IndicatorYet another indicator allowing you to plot FVGs with the following specific features: FVG Detection: It automatically identifies bullish (BISI) and bearish (SIBI) FVGs based on the relationship between candle highs and lows. Clear Visualization: It draws boxes to represent the FVGs and adds a median line for each FVG, making them easier to identify. Dynamic Styles: The indicator adapts the appearance of FVGs (color and border style) based on their current state: Untested: When the price has not yet interacted with the FVG. Tested (Partially Traversed): When the price has entered the FVG. Fully Traversed (Unmitigated): When the price has completely crossed the FVG but has not yet "invalidated" it (closed beyond the FVG). Mitigated: When the FVG is invalidated by price action, it disappears from the chart to avoid clutter. This disappearance only occurs after the closing of the mitigating candle. Full Customization: You can adjust all colors and border styles for each FVG state via the indicator's settings, as well as the maximum number of FVGs displayed. ----------------------------------------------------------------------------------------------------------------------
Pine Script® göstergesi
Jean-Biffleur tarafından
Multi-Timeframe PivotDescription: This script provides an advanced tool for multi-timeframe pivot point analysis. It identifies swing points based on a candle's relationship to its neighbors. The default strength settings of 1 align with the Inner Circle Trader (ICT) concept of market structure. The ICT concept defines a swing point based on a simple 3-candle pattern: - A swing high is a candle where the candles to the immediate left and right both have lower highs. - A swing low is a candle where the candles to the immediate left and right both have higher lows. A key feature is its ability to accurately calculate and translate pivot points from up to five higher timeframes (HTFs) and display them precisely on a lower timeframe (LTF) chart. NOTE: This indicator is designed to show HTF data on an LTF chart. If you select a timeframe in the settings that is lower than your current chart's timeframe, it will show pivots for the chart's timeframe instead. Core Features: - Up to five independent higher timeframes. - Per-timeframe customization for pivot strength (left/right bars) and color. - Optional "Watchlines" that project the price of each pivot forward, complete with a text label identifying the timeframe. - An optional "Alignment Model" that colors the background when price is aligned across all active timeframes (requires at least 2 TFs to be enabled). Default State: For a clean initial application, the Watchlines and Alignment Model features are disabled by default but can be enabled in the settings.
Pine Script® göstergesi
nickbonenkamp tarafından
VEP - Volume Explosion Predictor💥 VEP - Volume Explosion Predictor General Overview The Volume Explosion Predictor (VEP) is an advanced indicator that analyzes volume peaks to predict when the next volume explosion might occur. Using statistical analysis on historical patterns, it provides accurate probabilities on moments of greater trading activity. MAIN FEATURES 🎯 Intelligent volume peak detection Automatically identifies significant volume peaks Anti-consecutive filter to avoid redundant signals Customizable threshold for detection sensitivity 📊 Advanced statistical analysis Calculates the average distance between volume peaks Monitors the number of sessions without peaks Tracks the maximum historical range without activity 🔮 Predictive system Dynamic probability: Calculates the probability of an imminent peak Visual indicators: Background colors that change based on probability Time forecasts: Estimates remaining sessions to the next peak 📈 Visual signals Colored arrows: Green for bullish peaks, red for bearish peaks Statistics table: Complete real-time overview ALERT SYSTEM 🚨 Three Alert Levels New Valid Volume Peak: New peak detected Approaching Prediction: Increasing probability High Peak Probability: High probability of explosion HOW TO USE IT 📋 Recommended setup Timeframe : Works on all timeframes but daily, weekly or monthly timeframe usage is recommended. In any case, it should always be used consistently with your time horizon Markets : Stocks, crypto, forex, commodities Threshold for volume peak realization : It's recommended to start with 2.0x (i.e., twice the volume average) for normal markets, 1.5x for more volatile markets. This parameter can be set in the settings as desired 🎨 Visual interpretation Green Arrows : Peak during bullish candle Red Arrows : Peak during bearish candle Red Background : High probability (>90%) of new peak Yellow Background : Medium probability (50-70%) 📊 STATISTICS TABLE The table shows: Total peaks analyzed Average distance between peaks Current sessions without peaks Forecast remaining sessions Percentage probability Volume threshold needed for peak realization STRATEGIC ADVANTAGES 🎯 For Day Traders Anticipates moments of greater volatility for analysis, supporting the evaluation of trading setups and providing context on low volume periods 📈 For Swing Traders Identifies high-probability volume patterns, supporting breakout analysis with volume and improving understanding of market timing 🔍 For Technical Analysts Understands the stock's volume patterns. Helps evaluate the historical market interest and supports quantitative research and analysis OTHER THINGS TO KNOW... A) Anti-Consecutive Algorithm : allows to avoid multiple and consecutive volume signals and peaks at close range B) Statistical Validation : Uses standard deviation for accuracy C) Memory Management : Limits historical data for optimal performance D) Compatibility : Works with all TradingView chart types ⚠️ IMPORTANT DISCLAIMER This indicator is exclusively a technical analysis tool for studying volume patterns. It does not provide investment advice, trading signals or entry/exit points. All trading decisions are at the complete discretion and responsibility of the user. Always use in combination with other technical and fundamental analysis and proper risk management. DESCRIZIONE IN ITALIANO 💥 VEP - Volume Explosion Predictor Panoramica Generale Il Volume Explosion Predictor (VEP) è un indicatore avanzato che analizza i picchi di volume per prevedere quando potrebbe verificarsi la prossima esplosione di volume. Utilizzando analisi statistiche sui pattern storici, fornisce probabilità accurate sui momenti di maggiore attività di trading. CARATTERISTICHE PRINCIPALI 🎯 Rilevamento intelligente dei picchi di volume - Identifica automaticamente i picchi di volume significativi - Filtro anti-consecutivo per evitare segnali ridondanti - Soglia personalizzabile per la sensibilità del rilevamento 📊 Analisi statistica avanzata Calcola la distanza media tra i picchi di volume Monitora il numero di sessioni senza picchi Traccia il range massimo storico senza attività 🔮 Sistema predittivo Probabilità dinamica: Calcola la probabilità di un imminente picco Indicatori visivi: Colori di sfondo che cambiano in base alla probabilità Previsioni temporali: Stima delle sessioni rimanenti al prossimo picco 📈 Segnali visivi 1) Frecce colorate: Verdi per picchi rialzisti, rosse per ribassisti 2) Tabella statistiche: Panoramica completa in tempo reale SISTEMA DI ALERT 🚨 Tre Livelli di Alert 1) New Valid Volume Peak: Nuovo picco rilevato 2) Approaching Prediction: Probabilità in aumento 3) High Peak Probability: Alta probabilità di esplosione COME UTILIZZARLO 📋 Setup consigliato - Timeframe : Funziona su tutti i timeframe ma è consigliabile un utilizzo su timeframe giornaliero, settimanale o mensile. In ogni caso va sempre utilizzato coerentemente con il proprio orizzonte temporale - Mercati : Azioni, crypto, forex, commodities - Limite affinché si realizzi il picco di volumi : Si consiglia di iniziare con 2.0x (ovvero due volte la media dei volumi) per mercati normali, 1.5x per mercati più volatili. Questo parametro può essere settato nelle impostazioni a proprio piacimento 🎨 Interpretazione visuale Frecce Verdi : Picco durante candela rialzista Frecce Rosse : Picco durante candela ribassista Sfondo Rosso : Alta probabilità (>90%) di nuovo picco Sfondo Giallo : Probabilità media (50-70%) 📊 TABELLA STATISTICHE La tabella mostra: 1. Totale picchi analizzati 2. Distanza media tra picchi 3. Sessioni attuali senza picchi 4. Previsione sessioni rimanenti 5. Probabilità percentuale 6. Soglia volume necessaria affinché si realizzi il picco di volumi VANTAGGI STRATEGICI 🎯 Per Day Traders Anticipa i momenti di maggiore volatilità per analisi, supportando la valutazione dei setup di trading e fornendo al contempo un contesto sui periodi di basso volume 📈 Per Swing Traders 1. Identifica pattern di volume ad alta probabilità, supportando l'analisi dei breakout con volume e migliorando la comprensione dei tempi di mercato 🔍 Per Analisti Tecnici Comprende i pattern di volume del titolo. Aiuta a fare una valutazione dell'interesse storico del mercato ed è di supporto alla ricerca e analisi quantitativa ALTRE COSE DA SAPERE... A) Algoritmo Anti-Consecutivo : permette di evitare segnali e picchi di volume multipli e consecutivi multipli a distanza ravvicinata B) Validazione Statistica : Utilizza deviazione standard per l'accuratezza C) Gestione Memoria : Limita i dati storici per performance ottimali D) Compatibilità : Funziona con tutti i tipi di grafico TradingView ⚠️ DISCLAIMER IMPORTANTE Questo indicatore è esclusivamente uno strumento di analisi tecnica per lo studio dei pattern di volume. Non fornisce consigli di investimento, segnali di trading o punti di ingresso/uscita. Tutte le decisioni di trading sono a completa discrezione e responsabilità dell'utente. Utilizzare sempre in combinazione con altre analisi tecniche, fondamentali e una adeguata gestione del rischio.
Pine Script® göstergesi
FrancescoMerlettini tarafından
市场参与度宽度 (S&P/Nasdaq)指标功能和解读： 下拉菜单切换： 在指标的设置（点击指标名称旁边的小齿轮图标）中，您可以轻松地从 "S&P 500" 切换到 "Nasdaq 100"，指标会自动更新显示对应的数据。 同框显示： 蓝色的粗线代表50天市场参与度（中期健康度），橙色的细线代表20天市场参与度（短期情绪），两者在同一个副图中，方便您进行对比和观察。 关键水平线： 50%线 (灰色实线): 这是最重要的多空分界线。当指标线持续在50%以上时，表明市场处于强势；反之则处于弱势。 80%线 (红色虚线): 当短期指标（橙色线）进入80%以上时，可能意味着市场情绪过热，进入超买区。 20%线 (绿色虚线): 当短期指标进入20%以下时，可能意味着市场情绪过度悲观，进入超卖区，有时是机会的信号。 背离分析： 您可以观察当主图指数（如SPY）创出新高时，这个指标是否也创出新高。如果指数新高而指标没有，就形成了顶背离，是市场内部力量减弱的警示信号。 Indicator function and interpretation: Drop-down menu switch: In the indicator settings (click the small gear icon next to the indicator name), you can easily switch from "S&P 500" to "Nasdaq 100", and the indicator will automatically update to display the corresponding data. Same frame display: The thick blue line represents the 50-day market participation (medium-term health), and the thin orange line represents the 20-day market participation (short-term sentiment). Both are in the same sub-chart for your comparison and observation. Key horizontal lines: 50% line (solid gray line): This is the most important dividing line between long and short. When the indicator line is continuously above 50%, it indicates that the market is strong; otherwise, it is weak. 80% line (dashed red line): When the short-term indicator (orange line) enters above 80%, it may mean that the market sentiment is overheated and enters the overbought zone. 20% line (dashed green line): When the short-term indicator enters below 20%, it may mean that the market sentiment is overly pessimistic and enters the oversold zone, which is sometimes a signal of opportunity. Divergence analysis: You can observe whether this indicator also hits a new high when the main chart index (such as SPY) hits a new high. If the index hits a new high but the indicator does not, it forms a top divergence, which is a warning signal of weakening internal market forces.
Pine Script® göstergesi
kmdczf tarafından
Simple v6 Moving‑Average TrendTo provide a visual guide for trend direction using EMA crossovers, supported by a dynamic trailing stop for potential exit zones. It shows whether the price is above or below a moving average and highlights shifts in trend with labeled signals and a stop-line. ⚙️ How It Works 1. EMA Calculation It computes a single EMA (default: 20-period) from the current chart’s close price. The EMA represents the short-term trend.
Pine Script® göstergesi
MrAlex_17 tarafından
GER40 Opening Range Breakout (Simple)✅ GER40 Opening Range Breakout Strategy — Trading Plan 🎯 Objective: Capture early momentum after the Frankfurt open by trading breakouts of the initial 15-minute range. 📌 Rules Summary: Instrument: GER40 (DAX40) Timeframe: 5-minute or 15-minute chart Session Focus: 08:00–10:00 CET Opening Range: 08:00–08:15 CET 🛠 Entry Conditions: Long entry: Price breaks above the 08:00–08:15 high with volume confirmation. Short entry: Price breaks below the 08:00–08:15 low with volume confirmation. Optional confirmation: RSI > 50 for long, RSI < 50 for short.
Pine Script® göstergesi
Abanobi tarafından
Omori Law Recovery PhasesWhat is the Omori Law? Originally a seismological model, the Omori Law describes how earthquake aftershocks decay over time. It follows a power law relationship: the frequency of aftershocks decreases roughly proportionally to 1/(t+c)^p, where: t = time since the main shock c = time offset constant p = power law exponent (typically around 1.0) Application to the markets Financial markets experience "aftershocks" similar to earthquakes: Market Crashes as Main Shocks: Major market declines (crashes) represent the initial shock event. Volatility Decay: After a crash, market volatility typically declines following a power law pattern rather than a linear or exponential one. Behavioral Components: The decay pattern reflects collective market psychology - initial panic gives way to uncertainty, then stabilization, and finally normalization. The Four Recovery Phases The Omori decay pattern in markets can be divided into distinct phases: Acute Phase: Immediately after the crash, characterized by extreme volatility, panic selling, and sharp reversals. Trading is hazardous. Reaction Phase: Volatility begins decreasing, but markets test previous levels. False rallies and retests of lows are common. Repair Phase: Structure returns to the market. Volatility approaches normal levels, and traditional technical analysis becomes more reliable. Recovery Phase: The final stage where market behavior normalizes completely. The impact of the original shock has fully decayed. Why It Matters for Traders Understanding where the market stands in this recovery cycle provides valuable context: Risk Management: Adjust position sizing based on the current phase Strategy Selection: Different strategies work in different phases Psychological Preparation: Know what to expect based on the phase Time Horizon Guidance: Each phase suggests appropriate time frames for trading
Pine Script® göstergesi
HenriqueCentieiro tarafından
EMA + RSI Trend Strength v6✅ Indicator Name: EMA + RSI Trend Strength v6 📌 Purpose: This indicator combines trend detection (via EMA) with momentum confirmation (via RSI) to help traders identify high-probability bullish or bearish conditions. It also provides optional visual buy/sell signals and trend shading directly on the chart. ⚙️ Core Components: 1. Inputs: emaLen: Length of the Exponential Moving Average (default: 50). rsiLen: RSI period for momentum analysis (default: 14). rsiOB, rsiOS: RSI levels for context (default: 70/30, but mainly 50 is used for trend strength). showSignals: Toggle for showing entry signals. 2. Logic: Bullish Condition: Price is above the EMA RSI is above 50 (indicating positive momentum) Bearish Condition: Price is below the EMA RSI is below 50 3. Visuals & Outputs: EMA Line: Orange line on the price chart showing the trend direction. Buy Signal: Green triangle appears below the candle when bullish condition is met. Sell Signal: Red triangle appears above the candle when bearish condition is met. Background Color: Light green when bullish Light red when bearish
Pine Script® göstergesi
Gold_Hunters_Club tarafından
Tsallis Entropy Market RiskTsallis Entropy Market Risk Indicator What Is It? The Tsallis Entropy Market Risk Indicator is a market analysis tool that measures the degree of randomness or disorder in price movements. Unlike traditional technical indicators that focus on price patterns or momentum, this indicator takes a statistical physics approach to market analysis. Scientific Foundation The indicator is based on Tsallis entropy, a generalization of traditional Shannon entropy developed by physicist Constantino Tsallis. The Tsallis entropy is particularly effective at analyzing complex systems with long-range correlations and memory effects—precisely the characteristics found in crypto and stock markets. The indicator also borrows from Log-Periodic Power Law (LPPL). Core Concepts 1. Entropy Deficit The primary measurement is the "entropy deficit," which represents how far the market is from a state of maximum randomness: Low Entropy Deficit (0-0.3): The market exhibits random, uncorrelated price movements typical of efficient markets Medium Entropy Deficit (0.3-0.5): Some patterns emerging, moderate deviation from randomness High Entropy Deficit (0.5-0.7): Strong correlation patterns, potentially indicating herding behavior Extreme Entropy Deficit (0.7-1.0): Highly ordered price movements, often seen before significant market events 2. Multi-Scale Analysis The indicator calculates entropy across different timeframes: Short-term Entropy (blue line): Captures recent market behavior (20-day window) Long-term Entropy (green line): Captures structural market behavior (120-day window) Main Entropy (purple line): Primary measurement (60-day window) 3. Scale Ratio This measures the relationship between long-term and short-term entropy. A healthy market typically has a scale ratio above 0.85. When this ratio drops below 0.85, it suggests abnormal relationships between timeframes that often precede market dislocations. How It Works Data Collection: The indicator samples price returns over specific lookback periods Probability Distribution Estimation: It creates a histogram of these returns to estimate their probability distribution Entropy Calculation: Using the Tsallis q-parameter (typically 1.5), it calculates how far this distribution is from maximum entropy Normalization: Results are normalized against theoretical maximum entropy to create the entropy deficit measure Risk Assessment: Multiple factors are combined to generate a composite risk score and classification Market Interpretation Low Risk Environments (Risk Score < 25) Market is functioning efficiently with reasonable randomness Price discovery is likely effective Normal trading and investment approaches appropriate Medium Risk Environments (Risk Score 25-50) Increasing correlation in price movements Beginning of trend formation or momentum Time to monitor positions more closely High Risk Environments (Risk Score 50-75) Strong herding behavior present Market potentially becoming one-sided Consider reducing position sizes or implementing hedges Extreme Risk Environments (Risk Score > 75) Highly ordered market behavior Significant imbalance between buyers and sellers Heightened probability of sharp reversals or corrections Practical Application Examples Market Tops: Often characterized by gradually increasing entropy deficit as momentum builds, followed by extreme readings near the actual top Market Bottoms: Can show high entropy deficit during capitulation, followed by normalization Range-Bound Markets: Typically display low and stable entropy deficit measurements Trending Markets: Often show moderate entropy deficit that remains relatively consistent Advantages Over Traditional Indicators Forward-Looking: Identifies changing market structure before price action confirms it Statistical Foundation: Based on robust mathematical principles rather than empirical patterns Adaptability: Functions across different market regimes and asset classes Noise Filtering: Focuses on meaningful structural changes rather than price fluctuations Limitations Not a Timing Tool: Signals market risk conditions, not precise entry/exit points Parameter Sensitivity: Results can vary based on the chosen parameters Historical Context: Requires some historical perspective to interpret effectively Complementary Tool: Works best alongside other analysis methods Enjoy :)
Pine Script® göstergesi
HenriqueCentieiro tarafından
Avg High/Low Lines with TP & SL아래 코드는 TradingView Pine Script v6으로 작성된 스크립트로, 주어진 캔들 수 동안의 평균 고가와 저가를 계산해서 그 위에 수평선을 그리며, 해당 수평선 돌파 시 진입 가격을 기록하고, 손절가(SL)와 목표가(TP)를 자동으로 계산하여 표시하는 전략입니다. 알림(alert) 기능도 포함되어 있습니다. 코드 주요 기능 요약 length 기간 동안 평균 고가, 저가를 단순 이동평균(SMA)으로 계산 평균 고가선, 저가선 수평선을 일정 바 개수만큼 좌우 연장하여 차트에 표시 평균 고가 돌파 시 매수 진입, 평균 저가 돌파 시 매도 진입 처리 진입 가격 저장 및 상태 관리 (inLong, inShort 플래그) 손절가(SL): 롱이면 평균 저가, 숏이면 평균 고가 목표가(TP): 진입가에서 손절 거리의 1.5배만큼 설정 진입가 기준으로 TP, SL 라인과 라벨 표시 상단 돌파 후 종가 마감 시 매수 알림, 하단 돌파 후 종가 마감 시 매도 알림 Sure! Here’s the English explanation of your TradingView Pine Script v6 code: Summary of Key Features Calculates the simple moving average (SMA) of the high and low prices over a user-defined number of candles (length). Draws horizontal lines for the average high and average low, extending them a specified number of bars to the left and right on the chart. Detects breakouts above the average high to trigger a long entry, and breakouts below the average low to trigger a short entry. Records the entry price and manages trade states using flags (inLong, inShort). Sets the stop loss (SL) at the average low for long positions, and at the average high for short positions. Calculates the take profit (TP) level based on the entry price plus 1.5 times the stop loss distance. Draws lines and labels for the TP and SL levels starting from the entry bar, extended to the right. Sends alerts when the price closes above the average high after a breakout (long signal), or closes below the average low after a breakout (short signal). -onestar-
Pine Script® göstergesi
puma901123 tarafından
ATR Stop-Loss with Fibonacci Take-Profit [jpkxyz]ATR Stop-Loss with Fibonacci Take-Profit Indicator This comprehensive indicator combines Average True Range (ATR) volatility analysis with Fibonacci extensions to create dynamic stop-loss and take-profit levels. It's designed to help traders set precise risk management levels and profit targets based on market volatility and mathematical ratios. Two Operating Modes Default Mode (Rolling Levels) In default mode, the indicator continuously plots evolving stop-loss and take-profit levels based on real-time price action. These levels update dynamically as new bars form, creating rolling horizontal lines across the chart. I use this mode primarily to plot the rolling ATR-Level which I use to trail my Stop-Loss into profit. Characteristics: Levels recalculate with each new bar All selected Fibonacci levels display simultaneously Uses plot() functions with trackprice=true for price tracking Custom Anchor Mode (Fixed Levels) This is the primary mode for precision trading. You select a specific timestamp (typically your entry bar), and the indicator locks all calculations to that exact moment, creating fixed horizontal lines that represent your actual trade levels. Characteristics: Entry line (blue) marks your anchor point Stop-loss calculated using ATR from the anchor bar Fibonacci levels projected from entry-to-stop distance Lines terminate when price breaks through them Includes comprehensive alert system Core Calculation Logic ATR Stop-Loss Calculation: Stop Loss = Entry Price ± (ATR × Multiplier) Long positions: SL = Entry - (ATR × Multiplier) Short positions: SL = Entry + (ATR × Multiplier) ATR uses your chosen smoothing method (RMA, SMA, EMA, or WMA) Default multiplier is 1.5, adjustable to your risk tolerance Fibonacci Take-Profit Projection: The distance from entry to stop-loss becomes the base unit (1.0) for Fibonacci extensions: TP Level = Entry + (Entry-to-SL Distance × Fibonacci Ratio) Available Fibonacci Levels: Conservative: 0.618, 1.0, 1.618 Extended: 2.618, 3.618, 4.618 Complete range: 0.0 to 4.764 (23 levels total) Multi-Timeframe Functionality One of the indicator's most powerful features is timeframe flexibility. You can analyze on one timeframe while using stop-loss and take-profit calculations from another. Best Practices: Identify your entry point on execution timeframe Enable "Custom Anchor" mode Set anchor timestamp to your entry bar Select appropriate analysis timeframe Choose relevant Fibonacci levels Enable alerts for automated notifications Example Scenario: Analyse trend on 4-hour chart Execute entry on 5-minute chart for precision Set custom anchor to your 5-minute entry bar Configure timeframe setting to "4h" for swing-level targets Select appropriate Fibonacci Extension levels Result: Precise entry with larger timeframe risk management Visual Intelligence System Line Behaviour in Custom Anchor Mode: Active levels: Lines extend to the right edge Hit levels: Lines terminate at the breaking bar Entry line: Always visible in blue Stop-loss: Red line, terminates when hit Take-profits: Green lines (1.618 level in gold for emphasis) Customisation Options: Line width (1-4 pixels) Show/hide individual Fibonacci levels ATR length and smoothing method ATR multiplier for stop-loss distance
Pine Script® göstergesi
jpkxyz tarafından
RSP / VOO 比值指標The RSP/VOO ratio compares the performance of the S&P 500 Equal Weight ETF (RSP) to the S&P 500 Market Cap Weighted ETF (VOO). When the ratio is falling, it indicates that large-cap stocks—especially mega-cap tech names—are outperforming the broader market. In contrast, a rising ratio suggests that smaller and mid-sized companies are catching up or leading, which may signal a healthy broadening of market participation. Investors often use this ratio to identify shifts in market leadership and assess the strength or fragility of a rally.
Pine Script® göstergesi
littlesun1992 tarafından