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EMA CCI SSL BUY SELL Signal [THANHCONG]📌 Introduction This is a technical indicator that combines three powerful elements to detect potential Buy/Sell signals based on: 📈 EMA (8, 21, 89) – Identifies short, medium, and long-term trends 🔄 CCI Turbo & CCI 14 – Measures short-term momentum 🔍 SSL Channel from a higher timeframe (HTF) – Detects key support and resistance zones The indicator can automatically or manually select an appropriate HTF to generate clear entry signals. ⚙️ Key Features ✅ Buy/Sell signals based on confluence of EMA, CCI, and SSL HTF cross ⏱ Multi-timeframe support for flexible analysis 📊 Real-time signal info table showing: Latest signal type Price at signal Percentage change since signal 📍 Visual labels for Buy/Sell signals directly on the chart 🧭 How to Use Add the indicator to a chart (preferably 5-minute or higher) Select HTF mode: Auto: Automatically chooses an appropriate HTF Manual: Select your own HTF (e.g. H4, D1) Watch for signal labels: Green label (Buy) = potential long opportunity Red label (Sell) = potential short opportunity Use the signal info table on the top-right to monitor live change Combine with risk management and personal trading strategy 🟪 🔥 Recommended Combo: MDCX + RSI + EMA To confirm signals and enhance reliability, pair this indicator with "MACD + RSI + EMA ", which is also available on the chart: ✅ MCDX > 0 or rising MCDX histogram → confirms bullish money flow ✅ MCDX < 0 or falling MCDX histogram → confirms bearish money flow ✅ RSI > 50 supports Buy, RSI < 50 supports Sell ❗ Avoid Buy when RSI > 70 (overbought) or Sell when RSI < 30 (oversold) This combination gives a clearer picture of trend + momentum + money flow + overbought/oversold conditions before making decisions. 🙏 Gratitude Huge thanks to the TradingView community for providing an open space to share, learn, and grow. This tool was built with the purpose of supporting traders — not for profit — and I hope it helps improve your analysis. ⚠️ Disclaimer This is a technical support tool, not financial advice. Use at your own discretion. Please test on a demo account and ensure you have a proper risk management plan in place. #EMA #CCI #SSL #MACD #RSI #Trend #Momentum #Buy #Sell #Confirmation #TradingStrategy
Pine Script® indicator
by ThanhCong_
3
multi-tf standard devs [keypoems]Multi-Timeframe Standard Deviations Levels A visual map of “how far is too far” across any three higher time-frames. 1. What it does This script plots dynamic price “rails” built from standard deviation (StDev)—the same math that underpins the bell curve—on up to three higher-time-frames (HTFs) at once. • It measures the volatility of intraday open-to-close increments, reaching back as far as 5000 bars (≈ 20 years on daily data). • Each HTF can be extended to the next session or truncated at session close for tidy dashboards. • Lines can be mirrored so you see symmetric positive/negative bands, and optional background fills shade the “probability cone.” Because ≈ 68 % of moves live inside ±1 StDev, ≈ 95 % inside ±2, and ≈ 99.7 % inside ±3, the plot instantly shows when price is statistically stretched or compressed. 3. Key settings Higher Time-Frame #1-3 Turn each HTF on/off, pick the interval (anything from 1 min to 1 year), and decide whether lines should extend into the next period. Show levels for last X days Keep your chart clean by limiting how many historical sessions are displayed (1-50). Based on last X periods Length of the StDev sample. Long look-backs (e.g. 5 000) iron-out day-to-day noise; short look-backs make the bands flex with recent volatility. Fib Settings Toggle each multiple, line thickness/style/colour, label size, whether to print the numeric level, the live price, the HTF label, and whether to tint the background (choose your own opacity). 4. Under-the-hood notes StDev is calculated on (close – open) / open rather than absolute prices, making the band width scale-agnostic. Watch for tests of ±1: Momentum traders ride the breakout with a target at the next band. Mean-reversion traders wait for the first stall candle and trade back to zero line or VWAP. Bottom line: Multi-Timeframe Standard-Deviations turns raw volatility math into an intuitive “price terrain map,” helping you instantly judge whether a move is ordinary, stretched, or extreme—across the time-frames that matter to you. Original code by fadizeidan and stats by NQStats's ProbableChris.
Pine Script® indicator
by keypoems
Swing High/Low by %REnglish Description Swing High/Low by %R This indicator identifies potential swing high and swing low points by combining William %R overbought/oversold turning points with classic swing price structures. Swing High: Detected when William %R turns down from overbought territory and the price forms a local high (higher than both neighboring bars). Swing Low: Detected when William %R turns up from oversold territory and the price forms a local low (lower than both neighboring bars). This tool is designed to help traders spot possible market reversals and better time their entries and exits. Customizable parameters: Williams %R period Overbought & Oversold thresholds The indicator plots clear signals above/below price bars for easy visualization. For educational purposes. Please use with proper risk management! คำอธิบายภาษาไทย Swing High/Low by %R อินดิเคเตอร์นี้ใช้ระบุจุด Swing High และ Swing Low ที่มีโอกาสเป็นจุดกลับตัวของตลาด โดยอาศัยสัญญาณจาก William %R ที่พลิกกลับตัวบริเวณ overbought/oversold ร่วมกับโครงสร้างราคาแบบ swing Swing High: เกิดเมื่อ William %R พลิกกลับลงจากเขต Overbought และราคาแท่งกลางสูงกว่าทั้งสองแท่งข้างเคียง Swing Low: เกิดเมื่อ William %R พลิกกลับขึ้นจากเขต Oversold และราคาแท่งกลางต่ำกว่าทั้งสองแท่งข้างเคียง ช่วยให้เทรดเดอร์สามารถมองเห็นโอกาสในการกลับตัวของราคา และใช้ประกอบการวางแผนจังหวะเข้าหรือออกจากตลาดได้อย่างแม่นยำมากขึ้น ตั้งค่าได้: ระยะเวลา Williams %R ค่าขอบเขต Overbought & Oversold อินดิเคเตอร์จะแสดงสัญลักษณ์อย่างชัดเจนบนกราฟเพื่อความสะดวกในการใช้งาน ควรใช้ร่วมกับการบริหารความเสี่ยง
Pine Script® indicator
by August_Supertrader
2
Inside 4+ Candles Box (Entry + Target + SMA Stop Logic)🔍 What This Script Does This indicator detects price compression areas using 4 or more consecutive inside candles, then draws a breakout box to visually highlight the range. Once price closes above the box, a long entry marker is plotted, along with: 🎯 Target line at 1x box size above the breakout. ❌ Stop-loss at the box low or at a dynamic SMA-based level if the box is too large. 🧠 Why It’s Unique This script combines inside bar compression, breakout logic, risk control, and visual clarity — all in one tool. It also cancels the setup entirely if price closes below the box low before breakout, avoiding late or false entries. ⚙️ Customizable Settings Minimum inside candles (default = 4) SMA length (used as stop if box is large) Box size % threshold to activate smart stop Entry, Target, and Stop marker colors 📌 Notes For long setups only (no short signals). Use on any asset or timeframe (ideal on 4H/1D). This is not financial advice. Use with proper risk management. Backtest thoroughly before live use. Built with ❤️ by using Pine Script v6. 🇸🇦 وصف مختصر باللغة العربية: هذا المؤشر يكتشف مناطق تماسك السعر من خلال 4 شموع داخلية أو أكثر، ثم يرسم مربعًا يحدد منطقة الاختراق المحتملة. عند الإغلاق أعلى المربع، يتم عرض إشارة دخول وسطر هدف بنسبة 100% من حجم المربع. كما يتم احتساب وقف الخسارة تلقائيًا إما عند قاع المربع أو عند متوسط متحرك ذكي (SMA) إذا كان حجم المربع كبيرًا. الميزة الإضافية: إذا تم كسر قاع المربع قبل الاختراق، يتم إلغاء الصفقة تلقائيًا لتجنب الدخول المتأخر. 🧪 للاستفادة التعليمية والتحليل فقط. لا يُعتبر توصية مالية.
Pine Script® indicator
by abusuhil
Spectral Order Flow Resonance (SOFR) Spectral Order Flow Resonance (SOFR) See the Market’s Hidden Rhythms—Trade the Resonance, Not the Noise! The Spectral Order Flow Resonance (SOFR) is a next-generation tool for traders who want to go beyond price and volume, tapping into the underlying “frequency signature” of order flow itself. Instead of chasing lagging signals or reacting to surface-level volatility, SOFR lets you visualize and quantify the real-time resonance of market activity—helping you spot when the crowd is in sync, and when the regime is about to shift. What Makes SOFR Unique? Not Just Another Oscillator: SOFR doesn’t just measure momentum or volume. It applies spectral analysis (using Fast Fourier Transform) to normalized order flow, extracting the dominant cycles and their resonance strength. This reveals when the market is harmonizing around key frequencies—often the precursor to major moves. Regime Detection, Not Guesswork: By tracking harmonic alignment and phase coherence across multiple Fibonacci-based frequencies, SOFR identifies when the market is entering a bullish, bearish, or neutral resonance regime. This is visualized with a dynamic dashboard and info line, so you always know the current state at a glance. Dynamic Dashboard: The on-chart dashboard color-codes each key metric—regime, dominant frequency, harmonic alignment, phase coherence, and energy concentration—so you can instantly gauge the strength and direction of the current resonance. No more guesswork or clutter. Universal Application: Works on any asset, any timeframe, and in any market—futures, stocks, crypto, forex. If there’s order flow, SOFR can reveal its hidden structure. How Does It Work? Order Flow Normalization: SOFR calculates the net buying/selling pressure and normalizes it using a rolling mean and standard deviation, making the signal robust across assets and timeframes. Spectral Analysis: The script applies FFT to the normalized order flow, extracting the magnitude and phase of several key frequencies (typically Fibonacci numbers). This allows you to see which cycles are currently dominating the market. Resonance & Regime Logic: When multiple frequencies align and exceed a dynamic resonance threshold, and phase coherence is high, SOFR detects a “resonance regime”—bullish, bearish, or neutral. This is when the market is most likely to experience a strong, sustained move. Visual Clarity: The indicator plots each frequency’s magnitude, highlights the dominant one, and provides a real-time dashboard with color-coded metrics for instant decision-making. SOFR Dashboard Metrics Explained Regime: What it means: The current “state” of the market as detected by SOFR—Bullish, Bearish, or Neutral. Why it matters: The regime tells you whether the market’s order flow is resonating in a way that favors upward moves (Bullish), downward moves (Bearish), or is out of sync (Neutral). This helps you align your trades with the prevailing market force, or stand aside when there’s no clear edge. Dominant Freq: What it means: The most powerful frequency (cycle length, in bars) currently detected in the order flow. Why it matters: Markets often move in cycles. The dominant frequency shows which cycle is currently driving price action, helping you time entries and exits with the market’s “heartbeat.” Harmonic Align: What it means: The number of key frequencies (out of 3) that are currently in resonance (above threshold). Why it matters: When multiple frequencies align, it signals that different groups of traders (with different time horizons) are acting in concert. This increases the probability of a strong, sustained move. Phase Coh.: What it means: A measure (0–100%) of how “in sync” the phases of the key frequencies are. Why it matters: High phase coherence means the market’s cycles are reinforcing each other, not cancelling out. This is a classic signature of trending or explosive moves. Energy Conc.: What it means: The concentration of spectral energy in the dominant frequency, relative to the average. Why it matters: High energy concentration means the market’s activity is focused in one cycle, increasing the odds of a decisive move. Low concentration means the market is scattered and less predictable. How to Use Bullish Regime: When the dashboard shows a green regime and high harmonic alignment, the market is in a bullish resonance—look for long opportunities or trend continuations. Bearish Regime: When the regime is red and alignment is high, the market is in a bearish resonance—look for short opportunities or trend continuations. Neutral Regime: When the regime is gray or alignment is low, the market is out of sync—consider waiting for clearer signals or using other tools. Combine with Your Strategy: Use SOFR as a confirmation tool, a filter for trend/range conditions, or as a standalone regime detector. The dashboard’s color-coded metrics help you instantly spot when the market is entering or exiting resonance. Inputs Explained FFT Window Length : Controls the number of bars used for spectral analysis. Higher values smooth the signal, lower values make it more sensitive. Order Flow Period: Sets the lookback for normalizing order flow. Shorter periods react faster, longer periods are smoother. Fibonacci Frequencies: Choose which cycles to analyze. Default values (5, 8, 13) capture common market rhythms. Resonance Threshold: Sets how strong a frequency’s signal must be to count as “in resonance.” Lower for more signals, higher for stricter filtering. Signal Smoothing & Amplify: Fine-tune the display for your chart and asset. Dashboard & Info Line Toggles: Show or hide the on-chart dashboard and info line as needed. Why This Matters Most indicators show you what just happened. SOFR shows you when the market is entering a state of resonance—when crowd behavior is most likely to produce powerful, sustained moves. By visualizing the hidden structure of order flow, you gain a tactical edge over traders who only see the surface. For educational purposes only. Not financial advice. Always use proper risk management. Use with discipline. Trade your edge. — Dskyz, for DAFE Trading Systems
Pine Script® indicator
by DskyzInvestments
2
Market Structure with VD-+[RanaAlgo]The "Market Structure with VD-+ " indicator identifies key market structure levels (Higher Highs, Higher Lows, Lower Highs, Lower Lows) while analyzing volume delta (buying vs. selling pressure). It plots horizontal lines at pivot points and extends them forward for visibility. The script tracks cumulative positive and negative volume delta, resetting at a user-defined session start time. Traders can customize line styles, colors, and thickness for better visualization. The tool helps confirm trends and reversals by combining price action with volume analysis, making it useful for intraday and swing trading strategies. A dynamic label displays real-time volume delta percentages for quick reference.
Pine Script® indicator
by RanaAlgo
4
Math by Thomas Swing RangeMath by Thomas Swing Range is a simple yet powerful tool designed to visually highlight key swing levels in the market based on a user-defined lookback period. It identifies the highest high, lowest low, and calculates the midpoint between them — creating a clear range for swing trading strategies. These levels can help traders: Spot potential support and resistance zones Analyze price rejection near range boundaries Frame mean-reversion or breakout setups The indicator continuously updates and extends these lines into the future, making it easier to plan and manage trades with visual clarity. 🛠️ How to Use Add to Chart: Apply the indicator on any timeframe and asset (works best on higher timeframes like 1H, 4H, or Daily). Configure Parameters: Lookback Period: Number of candles used to detect the highest high and lowest low. Default is 20. Extend Lines by N Bars: Number of future bars the levels should be projected to the right. Interpret Lines: 🔴 Red Line: Swing High (Resistance) 🟢 Green Line: Swing Low (Support) 🔵 Blue Line: Midpoint (Mean level — useful for equilibrium-based strategies) Trade Ideas: Bounce trades from swing high/low zones. Breakout confirmation if price closes strongly outside the range. Reversion trades if price moves toward the midpoint after extreme moves.
Pine Script® indicator
by MathThomas
Consolidation Range [BigBeluga]A hybrid volatility-volume indicator that isolates periods of price equilibrium and reveals the directional force behind each range buildup. Consolidation Range is a powerful tool designed to detect compression phases in the market using volatility thresholds while visualizing volume imbalance within those phases. By combining low-volatility detection with directional volume delta, it highlights where accumulation or distribution is occurring—giving traders the confidence to act when breakouts follow. This indicator is particularly valuable in choppy or sideways markets where range identification and sentiment context are key. 🔵 CONCEPTS Volatility Compression: Uses ADX (Average Directional Index) to detect periods of low trend strength—specifically when ADX drops below a configurable threshold. Range Structure: Upon a low-volatility trigger, the script dynamically anchors horizontal upper and lower bounds based on local highs and lows. Directional Volume Delta: Inside each active range, it calculates the net difference between buy and sell volume, showing who controlled the range. Sentiment Bias: A label appears in the center of the zone on breakout, showing the accumulated delta and bias direction (▲ for positive, ▼ for negative). Range Validity Filter: Only ranges with more than 15 bars are considered valid—short-lived consolidations are auto-filtered. 🔵 KEY FEATURES Detects low volatility market phases using ADX logic (crosses under "Volatility Threshold Input"). Automatically plots adaptive consolidation zones with upper and lower boundary lines. Includes dynamic midline to visualize the price average inside the range. Visual range is filled with a progressive gradient to reflect distance between highs and lows. When the range is active, the indicator accumulates volume delta (Buy - Sell volume) . Upon breakout, the total volume delta is displayed at the midpoint , providing insight into market sentiment during the consolidation phase. Filters out weak or short-lived consolidations under 15 bars. 🔵 HOW TO USE Spot ranging or compression zones with minimal effort. Use breakouts with volume delta bias to assess the strength or weakness of moves. Combine with trend-following tools or volume-based confirmation for stronger setups. Apply to higher timeframes for macro consolidation tracking . 🔵 CONCLUSION Consolidation Range now brings together volatility filtering and directional volume delta into one smart module. This hybrid logic allows traders to not only identify balance zones but also understand who was in control during the buildup—offering a sharper edge for breakout and trend continuation strategies.
Pine Script® indicator
by BigBeluga
11
Divinearrow-tttypical Video Content Summary (Taylor Trading Technique) Introduction: George D. Taylor’s Approach Developed in the 1950s. Based on the idea that market movements are cyclical. 3-Day Cycle Breakdown Buy Day: Formation of a low → Look for long positions. Sell Day: Close long positions → Usually a sideways move. Sell Short Day: Reversal from highs → Opportunity for short positions. Examples with Candlestick Charts The characteristics of each day are illustrated using candlestick patterns. RSI, MACD, and other auxiliary indicators are often included. Integrating the Strategy with Current Market Data TTT signals + trend confirmation tools. Support-resistance levels and volume analysis are integrated. Risk Management Target and stop loss levels. Position sizing and risk control.
Pine Script® indicator
by divinebullet
FVG DetectorFAIR VALUE GAP (IMBALANCE) A convenient tool for automatically displaying imbalances on the current timeframe, and if necessary, you can display imbalances of a higher timeframe on the current chart. It has a wide and flexible system of settings. It displays not only the imbalance zone, but also the center of the imbalance, which is quite convenient Basic settings: Minimum FVG size in % - Minimum imbalance size to display Percentage of filling FVG - For how many percent the imbalance must be covered for it to be considered invalid. Show FVG - The number of imbalances that will be displayed on the chart Show FVG middle line - Shows the middle of the imbalance Filling 50% FVG - When the imbalance is filled by 50%, the midpoint of the imbalance changes When Candle Close - The indicator performs calculations only when a candle closes and a new one begins. Prevents additional load on the system FVG Length - Number of candles for how long the imbalance will be extended (used for older TFs). If set to 0, the zone will be stretched to the end of the chart History - Displays all imbalances in history PineScreener mode Candle number - When PineScreener mode is activated, the data of the specified candle will be displayed. If you need to analyze yesterday, then set to 1 and the data will be shown for yesterday. The PineScreener table displays the following data: LSize - LongSize, the size of the imbalance in percentage LBegin - LongBegin, displays the distance to the begin imbalance in percentage LMiddle - LongMiddle, displays the distance to the middle imbalance in percentage LEnd - LongEnd, displays the distance to the end imbalance in percentage SSize - ShortSize, the size of the imbalance in percentage SBegin - ShortBegin, displays the distance to the begin imbalance in percentage SMiddle - ShortMiddle, displays the distance to the middle imbalance in percentage SEnd - ShortEnd, displays the distance to the end imbalance in percentage LHB - Long Hit Begin of imbalance LHM - Long Hit Middle of imbalance LHE - Long Hit End of imbalance SHB - Short Hit Begin of imbalance SHM - Short Hit Middle of imbalance SHE - Short Hit End of imbalance If you have any suggestions on how to improve the indicator, please write
Pine Script® indicator
by Cibor842
SMA Strategy with Re-Entry Signal (v6 Style)tradingview 指標 //@version=5 indicator("SMA Strategy with Re-Entry Signal (v6 Style)", overlay=true) // === 可調參數 === // smaPeriod10 = 10 smaPeriod20 = 20 smaPeriod30 = 30 smaPeriod60 = 60 smaPeriod250 = 250 // === 計算 SMA === // sma10 = ta.sma(close, smaPeriod10) sma20 = ta.sma(close, smaPeriod20) sma30 = ta.sma(close, smaPeriod30) sma60 = ta.sma(close, smaPeriod60) sma250 = ta.sma(close, smaPeriod250) // === 趨勢判斷 === // isUptrend = close > sma30 // === 加倉訊號邏輯 === // reentrySignal = isUptrend and ta.crossover(close, sma20) // === 背景顏色提示 === // bgColor = isUptrend ? color.new(color.green, 90) : close < sma30 ? color.new(color.red, 90) : na bgcolor(bgColor) // === 畫出加倉符號（↑） === // plotshape(reentrySignal, title="Re-entry Signal", location=location.belowbar, color=color.lime, style=shape.labelup, text="↑", textcolor=color.black) // === 繪製 SMA 線 === // plot(sma10, color=color.blue, title="SMA 10") plot(sma20, color=color.orange, title="SMA 20") plot(sma30, color=color.purple, title="SMA 30") plot(sma60, color=color.teal, title="SMA 60") plot(sma250, color=color.gray, title="SMA 250")
Pine Script® indicator
by bonniestock2020
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike. ## Theoretical Foundation ### Historical Context of Bear Market Prediction Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models. Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data. ### Methodological Framework The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment. The mathematical foundation follows the general form: Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100 Where: - Wi = Category weight (i = 1,2,3,4) - Ci = Normalized category score - Categories: Macroeconomic, Technical, Sentiment, Breadth ## Component Analysis ### 1. Macroeconomic Risk Factors #### Yield Curve Analysis The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations. Implementation: - 2Y-10Y Spread: Captures market expectations of monetary policy trajectory - 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure. #### Credit Risk Premium Assessment High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress. Threshold Calibration: - Normal conditions: < 350 basis points - Elevated risk: 350-500 basis points - Severe stress: > 500 basis points #### Currency and Commodity Stress Indicators The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress. ### 2. Technical Analysis Factors #### Multi-Timeframe Moving Average Analysis The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules. Implementation: - Price relative to 50-day and 200-day simple moving averages - Moving average convergence/divergence analysis - Multi-timeframe MACD assessment (daily and weekly) #### Momentum and Volatility Analysis The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement. ### 3. Market Sentiment Factors #### Volatility Index Analysis The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average. Calibration: - Low volatility: VIX < 20 - Elevated concern: VIX 20-25 - High fear: VIX > 25 - Panic conditions: VIX > 30 #### Put-Call Ratio Analysis Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets. ### 4. Market Breadth Factors #### Advance-Decline Analysis Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns. Components: - Daily advance-decline ratio - Advance-decline line momentum - McClellan Oscillator (Ema19 - Ema39 of A-D difference) #### New Highs-New Lows Analysis The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990). ## Dynamic Threshold Methodology The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions. Dynamic Threshold Calculation: - Warning Level: Base threshold ± (Volatility × 1.0) - Danger Level: Base threshold ± (Volatility × 1.5) - Bounds: ±10-20 points from base threshold ## Professional Implementation ### Institutional Usage Patterns Professional risk managers typically employ multi-factor bear market models in several contexts: #### 1. Portfolio Risk Management - Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70% - Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached - Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods #### 2. Risk Budgeting - Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations - Stress Testing: Using probability levels to calibrate stress test scenarios - Capital Requirements: Adjusting regulatory capital based on systemic risk assessment #### 3. Client Communication - Risk Reporting: Quantifying market risk for client presentations - Investment Committee Decisions: Providing objective risk metrics for strategic decisions - Performance Attribution: Explaining defensive positioning during market stress ### Implementation Framework Professional traders typically implement such models through: #### Signal Hierarchy: 1. Probability < 30%: Normal risk positioning 2. Probability 30-50%: Increased hedging, reduced leverage 3. Probability 50-70%: Defensive positioning, cash building 4. Probability > 70%: Maximum defensive posture, short exposure consideration #### Risk Management Integration: - Position Sizing: Inverse relationship between probability and position size - Stop-Loss Adjustment: Tighter stops during elevated risk periods - Correlation Monitoring: Increased attention to cross-asset correlations ## Strengths and Advantages ### 1. Comprehensive Coverage The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes. ### 2. Dynamic Adaptability The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes. ### 3. Real-Time Processing Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management. ### 4. Transparency and Interpretability The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals. ### 5. Historical Validation Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power. ## Limitations and Weaknesses ### 1. Data Dependencies The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions. ### 2. Regime Change Sensitivity Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007). ### 3. False Signal Risk Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods. ### 4. Currency and Geographic Bias The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets. ### 5. Correlation Breakdown During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002). ## References Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851. Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680. Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292. Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24. Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764. Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27. Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26. Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street. Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61. Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49. Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261. Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research. Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720. Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102. Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220. Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46. Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908. Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House. Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105. Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research. Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125. Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
Pine Script® indicator
by EdgeTools
2
Swing Setup FINALSwing Signal Tracker Description: The Swing Signal Tracker is a powerful swing trading indicator designed to help traders identify optimal entry points based on key technical indicators — RSI, EMA, and volume analysis. This tool simplifies the decision-making process by providing clear buy and sell signals directly on the price chart. Key Metrics Used: RSI (Relative Strength Index): Measures momentum to identify overbought and oversold conditions. The default settings use a 14-period RSI with oversold and overbought levels at 30 and 70, respectively. EMA (Exponential Moving Average): The 200-period EMA is used to define the overall trend direction, helping to filter signals for higher probability trades. Volume: Volume is compared against its 20-period simple moving average (SMA) multiplied by a customizable factor (default 1.2) to confirm the strength behind a move. How It Works: Long Signals: Trigger when RSI indicates oversold conditions (≤ 30), the price is above the 200 EMA (bullish trend), and volume exceeds the defined threshold, signaling a potential upward swing. Short Signals: Trigger when RSI indicates overbought conditions (≥ 70), the price is below the 200 EMA (bearish trend), and volume is elevated, signaling a potential downward swing. Visual Features: Clear green and red triangle markers show long and short entry points on the chart. Labels mark oversold long and overbought short signals for easy identification. The 200 EMA is plotted as a purple line to provide visual context of the trend. Dotted horizontal lines at RSI 30 and 70 levels help monitor momentum thresholds. Ideal Use Case: The Swing Signal Tracker is perfect for traders looking for a straightforward, rule-based approach to swing trading, combining momentum, trend, and volume for robust entry signals.
Pine Script® indicator
by jewgeni-s
Enhanced False Breakout Pro## Enhanced False Breakout Pro - Trading Indicator **A sophisticated technical analysis tool that identifies high-probability false breakout reversals with advanced confluence scoring and multi-factor validation.** ### 📊 **What This Indicator Does** This indicator detects "false breakouts" - situations where price appears to break through key support or resistance levels but quickly reverses, creating excellent trading opportunities. Unlike basic false breakout indicators, this enhanced version uses multiple confirmation filters to significantly improve signal quality and reduce false positives. ### 🎯 **Key Features** **Advanced Signal Filtering:** - **Volume Confirmation**: Filters signals based on above-average volume activity - **RSI Divergence Detection**: Identifies momentum divergences that strengthen reversal signals - **Volatility Filter**: Uses ATR to ensure signals occur during meaningful market movements - **Multi-Timeframe Analysis**: Optional higher timeframe trend confirmation - **Confluence Scoring**: Rates each signal 1-10 based on multiple technical factors **Smart Detection Logic:** - Tracks new highs/lows over configurable periods - Monitors multiple breakout attempts in the same direction - Validates reversals within specified time windows - Filters minimum breakout size to avoid noise **Enhanced Visuals:** - Dynamic labels showing signal type and confluence scores - Color-coded chart bars for signal confirmation - Dashed lines connecting breakout points to reversal confirmations - Information table displaying active filter status ### ⚙️ **Customizable Settings** **Main Settings:** - False Breakout Period (default: 20) - Minimum bars between signals (default: 5) - Signal validity period (default: 5) **Advanced Filters:** - Volume multiplier threshold (default: 1.5x average) - RSI divergence parameters (14-period, 70/30 levels) - ATR volatility filter (14-period, 1.0x multiplier) - Multi-timeframe trend confirmation **Signal Quality:** - Minimum confluence score threshold (1-10) - Aggressive mode for more sensitive detection - Multiple smoothing options (WMA, HMA, EMA) ### 📈 **How to Use** 1. **Signal Identification**: Look for triangle markers with accompanying labels 2. **Quality Assessment**: Higher confluence scores indicate stronger signals 3. **Entry Timing**: Enter when price confirms the false breakout reversal 4. **Risk Management**: Use the identified support/resistance levels for stops **Signal Types:** - 🔻 **False Breakout Up**: Price failed to break below support - potential long setup - 🔺 **False Breakout Down**: Price failed to break above resistance - potential short setup ### 💡 **Trading Strategy** False breakouts often represent some of the highest-probability trading setups because they: - Trap retail traders on the wrong side - Create liquidity for institutional entries - Often lead to strong moves in the opposite direction - Provide clear risk/reward levels ### 🔧 **Best Practices** - Use on higher timeframes (1H+) for more reliable signals - Combine with overall market trend analysis - Set minimum confluence score to 4+ for higher quality signals - Enable volume and volatility filters for cleaner signals - Consider multi-timeframe confirmation for swing trades ### ⚠️ **Risk Disclaimer** This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose. --- *This enhanced version builds upon the original False Breakout indicator with significant improvements in signal quality, filtering, and user experience.*
Pine Script® indicator
by hsnnml
GCM Centre Line Candle MarkerGCM Centre Line Candle Marker (GCM-CLCM) - Descriptive Notes Indicator Overview: The "GCM Centre Line Candle Marker" is a versatile TradingView overlay indicator designed to enhance chart analysis by drawing short horizontal lines at user-defined "centre" points of candles. These lines provide a quick visual reference to key price levels within each candle, such as midpoints, open, close, or typical prices. The indicator offers extensive customization for line appearance, positioning, and conditional display, including an option to highlight only bullish engulfing patterns. Key Features: 1. Customizable Line Position: o Users can choose from various methods to calculate the "centre" price for the line:  (High + Low) / 2 (Default)  (Open + Close) / 2  Close  Open  (Open + High + Low + Close) / 4 (HLCO/4)  (Open + High + Close) / 3 (Typical Price HLC/3 variation)  (Open + Close + Low) / 3 (Typical Price OCL/3 variation) 2. Line Appearance Customization: o Visibility: Toggle lines on/off. o Style: Solid, dotted, or dashed lines. o Width: Adjustable line thickness (1 to 5). o Length: Defines how many candles forward the line extends (1 to 10). o Color: Lines are colored based on candle type (bullish/bearish), with user-selectable base colors. o Dynamic Opacity: Line opacity is dynamically adjusted based on the candle's size relative to recent candles. Larger candles produce more opaque lines (up to the user-defined maximum opacity), while smaller candles result in more transparent lines. This helps significant candles stand out. 3. Price Labels: o Show Labels: Option to display price labels at the end of each center line. o Label Background Color: Customizable. o Dynamic Text Color: Label text color can change based on the movement of the center price:  Green: Current center price is higher than the previous.  Red: Current center price is lower than the previous.  Gray: No change or first label. o Static Text Color: Alternatively, a fixed color can be used for all labels. 4. Conditional Drawing - Bullish Engulfing Filter: o Users can enable an option to Only Show Bullish Engulfing Candles. When active, center lines will only be drawn for candles that meet bullish engulfing criteria (current bull candle's body engulfs the previous bear candle's body). 5. Performance Management: o Max Lines to Show: Limits the number of historical lines displayed on the chart to maintain clarity and performance. Older lines are automatically removed as new ones are drawn. 6. Alert Condition: o Includes a built-in alert: Big Bullish Candle. This alert triggers when a bullish candle's range (high - low) is greater than the 20-period simple moving average (SMA) of candle ranges. How It Works: • For each new candle, the script calculates the "center" price based on the user's Line Position selection. • If showLines is enabled and (if applicable) the bullish engulfing condition is met, a new line is drawn from the current candle's bar_index at the calculated _center price, extending lineLength candles forward. • The line's color is determined by whether the candle is bullish (close > open) or bearish (close < open). • Opacity is calculated dynamically: scaledOpacity = int((100 - maxUserOpacity) * (1 - dynamicFactor) + maxUserOpacity), where dynamicFactor is candleSize / maxSize (current candle size relative to the max size in the last 20 candles). This means maxUserOpacity is the least transparent the line will be (for the largest candles), and smaller candles will have lines approaching full transparency. • Optional price labels are added at the end of these lines. • The script manages an array of drawn lines, removing the oldest ones if the maxLines limit is exceeded. Potential Use Cases: • Visualizing Intra-Candle Levels: Quickly see midpoints or other key price points without manual drawing. • Short-Term Reference Points: The extended lines can act as very short-term dynamic support/resistance or points of interest. • Pattern Recognition: Highlight bullish engulfing patterns or simply emphasize candles based on their calculated center. • Volatility Indication: The dynamic opacity can subtly indicate periods of larger or smaller candle ranges. • Confirmation Tool: Use in conjunction with other indicators or trading strategies. User Input Groups: • Line Settings: Controls all aspects of the line's appearance and calculation. • Label Settings: Manages the display and appearance of price labels. • Other Settings: Contains options for line management and conditional filtering (like Bullish Engulfing). This indicator provides a clean and customizable way to mark significant price levels within candles, aiding traders in their technical analysis.
Pine Script® indicator
by uniGram
Swing-Based Volatility IndexSwing-Based Volatility Index This indicator helps traders quickly determine whether the market has moved enough over the past few hours to justify scalping. It measures the percentage price swing (high to low) over a configurable time window (e.g., last 4–8 hours) and compares it to a minimum threshold (e.g., 1%). ✅ If the percent move exceeds the threshold → Market is volatile enough to scalp (green background). 🚫 If it's below the threshold → Market is too quiet (red background). Features: Adjustable lookback period in hours Custom threshold for volatility sensitivity Automatically adapts to the current chart timeframe This tool is ideal for scalpers and short-term traders who want to avoid entering trades in low-volatility environments.
Pine Script® indicator
by crodl