DAILY WYCKOFF ATMWyckoff Confidence Dashboard
A clean, mobile-optimized Wyckoff phase and alignment dashboard built for serious traders.
This tool dynamically detects Accumulation, Distribution, Markup, and Markdown across multiple timeframes (1H/15M) and scores confidence based on:
• HTF trend direction
• Liquidity sweeps
• Fair Value Gap (FVG) presence
• Volume/OBV confirmation
• Multi-timeframe phase/action alignment
Includes smart alerts and a lightweight dashboard interface — no clutter, just actionable structure-based insight.
Great for SMC, Wyckoff, or price-action traders seeking high-confluence entries.
在脚本中搜索"price action"
rsi jokerعندنا رسم بياني (شارت) على منصة TradingView.
واضح أنه شارت زمني قصير (ممكن M5 أو M15).
مرسوم عليه مستويات HH (Higher High), LL (Lower Low), HL (Higher Low), LH (Lower High).
الاتجاه الحالي:
من الرسم نلاحظ أن السعر عمل HH (قمة جديدة أعلى) ثم بعدها هبط بقوة وسجل LL (قاع جديد أقل).
بعد الـ LL، بدأ السعر يصعد لكن سجل LH (قمة أقل من السابقة)، مما يعني أن الاتجاه على المدى القريب يميل للهبوط (ترند هابط).
الخطوط المرسومة:
الخط الأحمر العلوي يمثل ترند هابط يربط القمم (مقاومة مائلة).
الخطوط الخضراء في الأسفل تمثل قناة سعرية هابطة أو دعم مائل.
الخط الأصفر يمثل خط اتجاه ثانوي/ضعيف داخل الترند.
المناطق المهمة:
المنطقة الحمراء بالأعلى: منطقة مقاومة قوية (إمداد/Supply Zone).
المنطقة الخضراء بالأسفل: منطقة دعم (طلب/Demand Zone).
الوضع الحالي للسعر:
السعر ارتد من الدعم (LL) وطلع لمستوى الترند الأحمر.
الآن يختبر المقاومة المائلة، ولو كسرها مع ثبات أعلى ممكن نشوف صعود للتجربة على المنطقة الحمراء.
لكن لو فشل بالكسر (رفض عند الترند)، ممكن يرجع للهبوط ويعيد اختبار المنطقة الخضراء.
📌 السيناريوهات المتوقعة:
صعود مشروط: إذا كسر الترند الأحمر + ثبات بشمعة واضحة → أهدافه المنطقة الحمراء (منطقة العرض).
هبوط مرجح: إذا فشل بالكسر → يرجع يعيد اختبار القاع السابق (LL) أو يكمل ضمن القناة الهابطة.
تحليل مختصر:
الاتجاه العام قصير المدى هابط، وأي صعود حالياً يعتبر تصحيح ما لم يكسر الترند العلوي والمنطقة الحمراء بثبات. Alright ✅ Let’s break this chart down in English:
General Structure:
This is a chart from TradingView on a short timeframe (likely M5 or M15).
It shows marked levels: HH (Higher High), LL (Lower Low), HL (Higher Low), LH (Lower High).
Trend Analysis:
Price created a Higher High (HH) but then dropped sharply to form a Lower Low (LL).
After the LL, price bounced but only managed to form a Lower High (LH) → this indicates a downtrend (bearish structure).
Drawn Lines:
Red descending line: main downtrend resistance (connecting lower highs).
Green lines below: channel support (downward sloping support zone).
Yellow line: minor/secondary trendline inside the main structure.
Key Zones:
Red zone (top): strong supply/resistance area.
Green zone (bottom): demand/support area.
Current Price Action:
Price bounced from the LL (support) and is now testing the red trendline (resistance).
If price breaks above and holds, it could push toward the red supply zone.
If price fails to break, it will likely drop back down, retesting the LL or sliding further inside the bearish channel.
📌 Scenarios:
Bullish case: Break + hold above the red trendline → target = red supply zone.
Bearish case (more likely): Rejection at the trendline → continuation downward to test LL or lower channel support.
🔎 Summary:
The short-term structure is bearish. Any upside move is just a correction unless price breaks above the trendline and supply zone.
Liquidity Pulse Revealer (LPR) — by Qabas_algoLiquidity Pulse Revealer (LPR) — by Qabas_algo
The Liquidity Pulse Revealer (LPR) is a technical framework designed to uncover hidden phases of institutional activity by combining volatility (ATR Z-Score) and liquidity (Volume Z-Score) into a dual-condition detection model. Instead of relying on price action alone, LPR measures how volatility and traded volume behave relative to their historical distributions, revealing when the market is either “compressed” or “expanding with force.”
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🔹 Core Mechanics
1. ATR Z-Score (Volatility Normalization)
• LPR calculates the Average True Range (ATR) on a higher timeframe (HTF).
• It applies a Z-Score transformation across a configurable lookback period to determine if volatility is statistically compressed (below mean) or expanded (above mean).
2. Volume Z-Score (Liquidity Normalization)
• Simultaneously, traded volume is normalized using the same Z-Score method.
• Elevated Volume Z-Scores signal the presence of institutional activity (accumulation/distribution or aggressive breakout participation).
3. Dual Conditions → Regimes
• 🧊 Iceberg Volume = Low ATR Z-Score + High Volume Z-Score.
→ Indicates a “hidden liquidity build-up” phase where price compresses but big players are positioning.
• ⚡ Revealed Momentum = High ATR Z-Score + High Volume Z-Score.
→ Marks explosive volatility phases where institutional activity is fully expressed in directional moves.
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🔹 Visualization
• Iceberg Zones (blue shaded boxes):
Drawn automatically around periods of statistical compression + elevated volume. These zones act as launchpads; once broken, they often precede strong directional expansions.
• Revealed Zones (green shaded boxes):
Highlight expansionary phases with both volatility and volume spiking. They often align with trend acceleration or terminal exhaustion zones.
• Midline Tracking:
Each zone maintains a dynamic average (mid-price), updated as the session evolves, providing reference for breakout confirmation and invalidation levels.
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🔹 Practical Use Cases
• Accumulation/Distribution Detection:
Spot where “smart money” is quietly building or unloading positions before large moves.
• Breakout Confirmation:
A breakout occurring after an Iceberg zone carries higher conviction than random volatility.
• Profit Management:
If a Revealed Momentum zone appears after a strong uptrend, it often signals distribution or exhaustion — useful for partial profit taking.
• Multi-Timeframe Adaptability:
With Auto, Multiplier, and Manual higher-timeframe modes, LPR adapts seamlessly to intraday scalping or swing trading contexts.
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🔹 Alerts
• Instant alerts for the start of new Iceberg or Revealed zones.
• Optional alerts for breakouts above/below the last Iceberg zone boundaries.
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🔹 Example Trading Scenario
1. Detection: An 🧊 Iceberg Volume zone forms around support (low volatility + high volume).
2. Trigger: Price closes above the upper boundary of this Iceberg zone.
3. Entry: Go long on the breakout.
4. Stop Loss: Place stop just below the Iceberg zone’s low (where the liquidity build-up started).
5. Target: Hold until a ⚡ Revealed Momentum zone forms — then start scaling out as the expansion matures.
This simple framework transforms hidden institutional behavior into actionable trade setups with clear risk management.
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⚠️ Disclaimer: The LPR is a research and educational tool. It does not provide financial advice. Always apply proper risk management and use in combination with your own trading framework.
Confluence StackPlease read the instructions below. The code was mostly written using AI so may contain errors. Happy trading all and good luck. ATB Richard
INTENDED USE
This indicator is designed for technical traders who want to move beyond simple buy/sell signals and gain a deeper understanding of the underlying market dynamics. It is ideal for trend followers, swing traders, and anyone looking to confirm the quality of a trend.
WHO IS THIS FOR?
Traders who want to differentiate between strong, sustainable trends and weak, unreliable moves.
Analysts looking to identify high-conviction setups backed by multiple factors (e.g., momentum confirmed by volume).
Discretionary traders who need a quick, visual tool to gauge market sentiment and avoid choppy conditions.
WHY USE IT?
Traditional indicators often give conflicting signals. The Confluence Stack solves this by aggregating multiple perspectives into one clear visual. It helps you answer not just "Is the market going up?" but "WHY is it going up, and how strong is the conviction?". This allows for more informed decision-making and helps filter out low-probability trades.
DISCLAIMER AND LICENSE
This script is for educational purposes only and is not a recommendation to buy or sell any financial instrument. All trading and investment decisions are the sole responsibility of the user. Trading involves significant risk.
This source code is subject to the terms of the Mozilla Public License 2.0 at www.mozilla.org
HOW TO USE THIS INDICATOR
This indicator is designed to show the 'character' of a market move by grouping signals into distinct categories. Instead of seeing many individual signals, you see the strength of the underlying forces driving the price.
1. READ THE HEIGHT (Strength of Confluence)
The total height of the stack shows the strength of agreement. A tall stack means many signals are aligned, indicating a high-conviction move. A short stack means weak agreement and a choppy, indecisive market.
2. READ THE COLOR (Character of the Move)
The colors tell you WHY the market is moving.
BLUE (Momentum): A stack of mostly blue shades indicates a trend driven by pure momentum. This is the 'speed' of the market.
RSI (Relative Strength Index): Measures the magnitude of recent price gains versus losses. A smooth measure of trend strength.
Stochastic Oscillator: Measures the current closing price's position within the recent high-low range. More sensitive to immediate price action.
CCI (Commodity Channel Index): Measures the price's deviation from its moving average. Excels at identifying cyclical turns.
MACD (Moving Average Convergence Divergence): A trend-following momentum indicator showing the relationship between two moving averages. Excellent for identifying the start and end of trends.
YELLOW (Volume): The appearance of yellow shades confirms the move is supported by high market participation. This is the 'fuel' for the trend.
Volume Ratio: A custom signal that triggers when buy or sell volume is unusually high compared to its recent average.
CRV (Candle Range Volume): A custom signal that looks for candles with significant price range and volume.
OBV (On-Balance Volume): A cumulative indicator that adds volume on up days and subtracts it on down days. It shows the long-term flow of money.
FUCHSIA (Volatility): A fuchsia block signals a volatility breakout. This adds a sense of urgency and confirms the price is moving with exceptional force.
Bollinger Bands: A signal triggers when the price closes outside of the upper or lower standard deviation bands.
ORANGE (Price Action): An orange block is a pure price structure signal. It's a raw statement of intent from the market.
Price Gap: A signal that triggers when there's a gap up or gap down between candles.
3. READ THE TRANSITION (Shift in Sentiment)
The most important signal from the stacks is the flip from one side of the zero line to the other.
Flipping from Negative to Positive: A bearish stack disappears and is replaced by a bullish stack. This indicates market sentiment is shifting from bearish to bullish.
Flipping from Positive to Negative: A bullish stack disappears and is replaced by a bearish stack. This warns of a potential top or the start of a new downtrend.
4. FILTER FOR NOISE (Plot Threshold)
In choppy markets, the stack can flicker with low signal counts (e.g., +1 or -1). To focus only on high-conviction moves, go to the indicator settings and increase the "Plot Threshold". A setting of 2 or 3 will hide all stacks that don't have at least 2 or 3 agreeing signals, effectively filtering out market noise and keeping your chart clean.
5. CUSTOMIZE YOUR SIGNALS (Enable/Disable)
This indicator is fully customizable. In the settings, you can enable or disable each of the 9 indicators individually. For example, if you are a pure momentum trader, you could disable all Volume, Volatility, and Price Action signals to focus only on the blue stacks. Tailor it to fit your specific trading style.
EXAMPLE INTERPRETATIONS
Strong, Confirmed Trend: A tall stack of mostly blue (Momentum) and yellow (Volume) indicates a high-quality trend backed by both speed and market participation.
Momentum-Only Trend: A tall stack of only blue is a strong momentum move, but the lack of yellow (Volume) is a warning that the move may lack the "fuel" to be sustained.
Choppy/Indecisive Market: A short, mixed-color stack flickering around the zero line means the market is choppy with no clear conviction. It's often best to stay out.
Volatility Breakout: A new stack that appears suddenly with a fuchsia (Bollinger Bands) block on its first bar suggests a volatility-driven breakout is initiating.
Exhaustion Move: An orange (Price Gap) block appearing at the peak of a tall, long-standing stack can signal an exhaustion gap, potentially marking the end of the trend.
Weakening Conviction (Divergence): If price makes a new high but the positive stack is visibly shorter than the stack at the previous price high, it suggests underlying conviction is weakening.
Crypto Strength MatrixOverview
The "Crypto Strength Matrix" is a custom Pine Script v5 indicator designed for cryptocurrency traders to assess the relative strength of major crypto market segments against traditional markets (e.g., the U.S. Dollar Index) and Bitcoin dominance. This indicator plots the strength of Altcoins (excluding ETH and SOL), Ethereum (ETH), Solana (SOL), the Dollar Index (DXY) versus Altcoins, and Bitcoin Dominance (DOM) on a 0-100 scale, using the Relative Strength Index (RSI) methodology. It provides a visual and intuitive way to identify overbought (>70) or oversold (<30) conditions across these assets, helping traders spot potential entry or exit points in the crypto market.
How It Works
The indicator fetches real-time data from various crypto and forex symbols available on TradingView, including:
CRYPTOCAP:TOTAL2 (total altcoin market cap),
CRYPTOCAP:ETH and CRYPTOCAP:SOL (market caps of ETH and SOL),
CRYPTO:ETHUSD and CRYPTO:SOLUSD (ETH and SOL prices),
CRYPTOCAP:BTC.D (Bitcoin dominance),
TVC:DXY (U.S. Dollar Index).
Calculations:
Altcoin Strength (OTH): Measures the RSI of the normalized market cap of all altcoins excluding ETH and SOL (calculated as TOTAL2 - ETH - SOL), relative to the total altcoin market cap. This reflects the strength of smaller altcoins.
ETH Strength: Computes the RSI of ETH/USD price adjusted by the DXY, isolating ETH's performance against the dollar.
SOL Strength: Similar to ETH, calculates the RSI of SOL/USD price adjusted by the DXY, focusing on Solana's strength.
DXY vs Altcoins: Uses the RSI of the DXY divided by the normalized total altcoin market cap, indicating the dollar's strength relative to altcoins.
Bitcoin Dominance (DOM): Directly applies RSI to Bitcoin dominance data, showing BTC's market control.
Each metric is plotted as a line with a unique color (OTH in aqua, ETH in teal, SOL in purple, DXY in green, DOM in orange) and labeled at the end of the chart for easy identification. Horizontal lines at 70 (overbought), 50 (neutral), and 30 (oversold) provide reference levels.
How to Use
Add the Indicator: Apply the "Crypto Strength Matrix" to a cryptocurrency chart (e.g., BTC/USD or ETH/USD) on a daily or 4-hour timeframe for optimal results.
Interpret the Lines:
OTH (Altcoins excluding ETH and SOL): A value above 70 suggests strong momentum in smaller altcoins, while below 30 indicates weakness. Monitor for divergence with ETH and SOL.
ETH and SOL: High values (>70) signal potential overbought conditions for these assets, while low values (<30) may indicate oversold opportunities.
DXY: Rising above 70 may suggest a stronger dollar, potentially pressuring crypto prices, while below 30 could indicate a weakening dollar, favoring crypto.
DOM: A value above 70 reflects strong Bitcoin dominance, often leading to altcoin underperformance, while below 30 may signal altcoin season.
Combine with Price Action: Use the indicator alongside candlestick patterns or volume analysis to confirm trade signals.
Adjust RSI Length: The default RSI length is 14, but you can tweak this input in the indicator settings to suit your trading style (e.g., 7 for shorter-term, 21 for longer-term trends).
Monitor Trends: Look for crossovers between lines (e.g., OTH rising above DXY) or alignment with the 50 neutral line to gauge market shifts.
Tips
Timeframe Selection: Daily charts provide a broad market view, while 4-hour charts offer more frequent signals. Avoid very short timeframes (e.g., 5m) due to noise.
Contextual Awareness: Combine with macroeconomic news (e.g., U.S. dollar strength) and Bitcoin price movements for better decision-making.
Risk Management: Use the indicator as a supplementary tool, not a standalone signal, and always set stop-losses based on your risk tolerance.
This indicator is ideal for crypto traders seeking a comprehensive view of market dynamics without the complexity of multiple charts. Enjoy trading with the "Crypto Strength Matrix"!
SMT Divergence PSP&PCP - Milana TradesThis indicator is designed for traders who want to combine SMT Divergence (SMT) analysis with Precision Swing Points and Candles (PSP/PCP) to identify potential market reversals, trend changes, and optimal entry points. It works on one, two, or three symbols simultaneously, and provides alerts for all key signals.
1. SMT Divergence
Purpose:
SMT Divergence identifies discrepancies between the price movements of a reference market (controlling asset) and the current chart. This helps traders detect when “smart money” might be acting differently than the public trend.
How it works:
The indicator tracks pivot highs and lows in both the current chart and the reference symbol.
If the current chart forms a high but the reference asset fails to confirm it (or vice versa), this creates a bearish or bullish divergence.
These divergences are drawn as lines on the chart with customizable color, style, and label size.
Broken or invalid divergences are automatically removed to avoid clutter.
Visual Features:
+SMT / -SMT labels indicate bullish or bearish divergences.
Lines connect the divergence points for easy visualization.
Alerts:
Bullish SMT
Bearish SMT
2. Precision Swing Points (PSP) and Precision Candle Points (PCP)
Purpose:
Precision Swing Points are extremely accurate pivot points in the price movement, showing potential short-term reversals.
Precision Candle Points extend this by confirming reversal candlestick patterns at these pivots.
How it works:
The indicator checks pivot highs/lows for patterns across multiple symbols.
Bullish PSP indicates a potential upward reversal.
Bearish PSP indicates a potential downward reversal.
PCP signals are more conservative and require a pattern confirmation, often used for safer entries.
Key Features:
Works with 1, 2, or 3 symbols simultaneously to detect correlated reversals.
Automatically removes broken or invalid PSP/PCP points.
Supports display customization: text size, colors, and which patterns to show.
Provides correlation between symbols to gauge market synchronicity.
Alerts:
Bullish PSP
Bullish PCP
Bearish PSP
Bearish PCP
This SMT & Precision Swing Point Indicator combines smart money divergence with highly accurate swing points and candlestick pattern confirmations to provide a powerful tool for market analysis. It helps traders:
Detect divergences between key markets.
Identify high-probability reversal points.
Filter signals according to trend and precision.
Receive alerts for actionable trading opportunities without constant chart monitoring.
It is ideal for traders using Price Action, Smart Money concepts, and multi-symbol analysis.
SMC - Institutional Confidence Oscillator [PhenLabs]📊 Institutional Confidence Oscillator
Version: PineScript™v6
📌 Description
The Institutional Confidence Oscillator (ICO) revolutionizes market analysis by automatically detecting and evaluating institutional activity at key support and resistance levels using our own in-house detection system. This sophisticated indicator combines volume analysis, volatility measurements, and mathematical confidence algorithms to provide real-time readings of institutional sentiment and zone strength.
Using our advanced thin liquidity detection, the ICO identifies high-volume, narrow-range bars that signal institutional zone formation, then tracks how these zones perform under market pressure. The result is a dual-wave confidence oscillator that shows traders when institutions are actively defending price levels versus when they’re abandoning positions.
The indicator transforms complex institutional behavior patterns into clear, actionable confidence percentiles, helping traders align with smart money movements and avoid common retail trading pitfalls.
🚀 Points of Innovation
Automated thin liquidity zone detection using volume threshold multipliers and zone size filtering
Dual-sided confidence tracking for both support and resistance levels simultaneously
Sigmoid function processing for enhanced mathematical accuracy in confidence calculations
Real-time institutional defense pattern analysis through complete test cycles
Advanced visual smoothing options with multiple algorithmic methods (EMA, SMA, WMA, ALMA)
Integrated momentum indicators and gradient visualization for enhanced signal clarity
🔧 Core Components
Volume Threshold System: Analyzes volume ratios against baseline averages to identify institutional activity spikes
Zone Detection Algorithm: Automatically identifies thin liquidity zones based on customizable volume and size parameters
Confidence Lifecycle Engine: Tracks institutional defense patterns through complete observation windows
Mathematical Processing Core: Uses sigmoid functions to convert raw market data into normalized confidence percentiles
Visual Enhancement Suite: Provides multiple smoothing methods and customizable display options for optimal chart interpretation
🔥 Key Features
Auto-Detection Technology: Automatically scans for institutional zones without manual intervention, saving analysis time
Dual Confidence Tracking: Simultaneously monitors both support and resistance institutional activity for comprehensive market view
Smart Zone Validation: Evaluates zone strength through volume analysis, adverse excursion measurement, and defense success rates
Customizable Parameters: Extensive input options for volume thresholds, observation windows, and visual preferences
Real-Time Updates: Continuously processes market data to provide current institutional confidence readings
Enhanced Visualization: Features gradient fills, momentum indicators, and information panels for clear signal interpretation
🎨 Visualization
Dual Oscillator Lines: Support confidence (cyan) and resistance confidence (red) plotted as percentage values 0-100%
Gradient Fill Areas: Color-coded regions showing confidence dominance and strength levels
Reference Grid Lines: Horizontal markers at 25%, 50%, and 75% levels for easy interpretation
Information Panel: Real-time display of current confidence percentiles with color-coded dominance indicators
Momentum Indicators: Rate of change visualization for confidence trends
Background Highlights: Extreme confidence level alerts when readings exceed 80%
📖 Usage Guidelines
Auto-Detection Settings
Use Auto-Detection
Default: true
Description: Enables automatic thin liquidity zone identification based on volume and size criteria
Volume Threshold Multiplier
Default: 6.0, Range: 1.0+
Description: Controls sensitivity of volume spike detection for zone identification, higher values require more significant volume increases
Volume MA Length
Default: 15, Range: 1+
Description: Period for volume moving average baseline calculation, affects volume spike sensitivity
Max Zone Height %
Default: 0.5%, Range: 0.05%+
Description: Filters out wide price bars, keeping only thin liquidity zones as percentage of current price
Confidence Logic Settings
Test Observation Window
Default: 20 bars, Range: 2+
Description: Number of bars to monitor zone tests for confidence calculation, longer windows provide more stable readings
Clean Break Threshold
Default: 1.5 ATR, Range: 0.1+
Description: ATR multiple required for zone invalidation, higher values make zones more persistent
Visual Settings
Smoothing Method
Default: EMA, Options: SMA/EMA/WMA/ALMA
Description: Algorithm for signal smoothing, EMA responds faster while SMA provides more stability
Smoothing Length
Default: 5, Range: 1-50
Description: Period for smoothing calculation, higher values create smoother lines with more lag
✅ Best Use Cases
Trending market analysis where institutional zones provide reliable support/resistance levels
Breakout confirmation by validating zone strength before position entry
Divergence analysis when confidence shifts between support and resistance levels
Risk management through identification of high-confidence institutional backing
Market structure analysis for understanding institutional sentiment changes
⚠️ Limitations
Performs best in liquid markets with clear institutional participation
May produce false signals during low-volume or holiday trading periods
Requires sufficient price history for accurate confidence calculations
Confidence readings can fluctuate rapidly during high-impact news events
Manual fallback zones may not reflect actual institutional activity
💡 What Makes This Unique
Automated Detection: First Pine Script indicator to automatically identify thin liquidity zones using sophisticated volume analysis
Dual-Sided Analysis: Simultaneously tracks institutional confidence for both support and resistance levels
Mathematical Precision: Uses sigmoid functions for enhanced accuracy in confidence percentage calculations
Real-Time Processing: Continuously evaluates institutional defense patterns as market conditions change
Visual Innovation: Advanced smoothing options and gradient visualization for superior chart clarity
🔬 How It Works
1. Zone Identification Process:
Scans for high-volume bars that exceed the volume threshold multiplier
Filters bars by maximum zone height percentage to identify thin liquidity conditions
Stores qualified zones with proximity threshold filtering for relevance
2. Confidence Calculation Process:
Monitors price interaction with identified zones during observation windows
Measures volume ratios and adverse excursions during zone tests
Applies sigmoid function processing to normalize raw data into confidence percentiles
3. Real-Time Analysis Process:
Continuously updates confidence readings as new market data becomes available
Tracks institutional defense success rates and zone validation patterns
Provides visual and numerical feedback through the oscillator display
💡 Note:
The ICO works best when combined with traditional technical analysis and proper risk management. Higher confidence readings indicate stronger institutional backing but should be confirmed with price action and volume analysis. Consider using multiple timeframes for comprehensive market structure understanding.
Fibonacci Sequence Circles [BigBeluga]🔵 Overview
The Fibonacci Sequence Circles is a unique and visually intuitive indicator designed for the TradingView platform. It combines the principles of the Fibonacci sequence with geometric circles to help traders identify potential support and resistance levels, as well as price expansion zones. The indicator dynamically anchors to key price points, such as pivot highs, pivot lows, or timeframe changes (daily, weekly, monthly), and generates Fibonacci-based circles around these anchor points.
⚠️For proper indicators visualization use simple not logarithmic chart
🔵 Key Features
Customizable Anchor Points : The indicator can be anchored to Pivot Highs , Pivot Lows , or timeframe changes ( Daily, Weekly, Monthly ), making it adaptable to various trading strategies.
Fibonacci Sequence Logic : The circles are generated using the Fibonacci sequence, where the diameter of each circle is the sum of the diameters of the two preceding circles.
first = start_val
secon = start_val + int(start_val/2)
three = first + secon
four = secon + three
five = three + four
six = four + five
seven = five + six
eight = six + seven
nine = seven + eight
ten = eight + nine
Adjustable Start Value : Traders can modify the starting value of the sequence to scale the circles larger or smaller, ensuring they fit the current price action.
Color Customization : Each circle can be individually enabled or disabled, and its color can be customized for better visual clarity.
Visual Labels : The diameter of each circle (in bars) is displayed next to the circle, providing additional context for analysis.
🔵 Usage
Step 1: Set the Anchor Point - Choose the anchor type ( Pivot High, Pivot Low, Daily, Weekly, Monthly ) to define the center of the Fibonacci circles.
Step 2: Adjust the Start Value - Modify the starting value of the Fibonacci sequence to scale the circles according to the price action.
Step 3: Customize Circle Colors - Enable or disable specific circles and adjust their colors for better visualization.
Step 4: Analyze Price Action - Use the circles to identify potential support/resistance levels, price expansion zones, or trend continuation areas.
Step 5: Combine with Other Tools - Enhance your analysis by combining the indicator with other technical tools like trendlines, moving averages, or volume indicators.
The Fibonacci Sequence Circles is a powerful and flexible tool for traders who rely on Fibonacci principles and geometric patterns. Its ability to anchor to key price points and dynamically scale based on market conditions makes it suitable for various trading styles and timeframes. Whether you're a day trader or a long-term investor, this indicator can help you visualize and anticipate price movements with greater precision.
Simple Liquidity Zones [Supertrade]🔎 What this indicator does
This indicator is designed to highlight liquidity sweep zones on the chart.
• A liquidity sweep occurs when price briefly breaks above a recent swing high or below a recent swing low, but fails to close beyond it.
• Such behavior often indicates that price has taken liquidity (stop orders resting above highs or below lows) and may reverse.
The indicator marks these events as bullish or bearish liquidity zones:
• Bullish Zone (green) → Price swept a swing low and closed back above it (possible bullish reversal area).
• Bearish Zone (red) → Price swept a swing high and closed back below it (possible bearish reversal area).
These zones are drawn as shaded horizontal bands that extend forward in time, providing visual areas where liquidity grabs occurred.
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⚙️ How calculations are made
The indicator does not use moving averages or smoothing.
Instead, it works with raw price action:
1. Swing Detection → It checks the highest high and lowest low of the past N bars (swing length).
2. Sweep Logic →
o A bearish sweep happens if the high breaks above the previous swing high, but the close returns below that level.
o A bullish sweep happens if the low breaks below the previous swing low, but the close returns above that level.
3. Zone Creation → When a sweep is detected, a shaded zone is drawn just above/below the swing level.
4. Persistence → Zones extend into the future until replaced by new ones (or optionally until price fully trades through them).
This makes the calculations simple, transparent, and responsive to actual market structure without lag.
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📈 How it helps traders
This tool helps traders by:
• Visualizing liquidity areas → Shows where price previously swept liquidity and may act as support/resistance.
• Identifying reversals → Helps spot potential turning points after liquidity grabs.
• Risk management → Zones highlight areas where stops may be targeted, useful for positioning stop-loss orders.
• Confluence tool → Works best when combined with other strategies such as order blocks, trendlines, or volume analysis.
⚠️ Note: Like all indicators, this should not be used in isolation. It provides context, not guaranteed trade signals.
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🏦 Markets & Timeframes
• Works across all markets (crypto, forex, stocks, indices, commodities).
• Particularly effective in high-liquidity environments where stop-hunting is common (e.g., forex majors, BTC/ETH, S&P500).
• Timeframes:
o Lower timeframes (1m–15m) → Scalpers can spot intraday liquidity sweeps.
o Higher timeframes (1H–1D) → Swing traders can identify major liquidity pools.
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NPM Rsi DivergenceNPM RSI Divergence Indicator
The NPM RSI Divergence Indicator is a closed-source tool designed to help traders identify potential reversals and high-probability trade setups using divergence between price action and the Relative Strength Index (RSI). It highlights areas where momentum is weakening or strengthening, giving traders early signals of potential trend changes.
What it does
Detects divergences between RSI and price movement, indicating potential trend reversals or continuation.
Shows the strength or reliability of each divergence signal to help traders gauge probability.
Plots visual markers directly on the chart for easier recognition of potential setups.
Helps traders spot early exhaustion points in trends before price reverses or continues strongly.
How it works (concept-level)
Compares price highs/lows with RSI highs/lows to detect hidden or regular divergences.
Applies adaptive filtering to reduce false signals in choppy or low-volatility markets.
Aggregates divergence signals into clear visual markers and strength indicators.
Incorporates momentum context to highlight divergences that are more likely to produce actionable moves.
How to use it
1. Apply the indicator to your chosen symbol and timeframe.
2. Observe divergence markers and their strength indicators on the chart.
3. Confirm potential trade opportunities by considering trend direction and market context.
4. Use divergence signals to assist with trade entry, exit, or risk management decisions.
Alerts
Optionally set alerts when divergence signals appear or when the strength indicator exceeds a user-defined threshold.
Notes
Suitable for multiple markets, including forex, indices, crypto, and equities.
Can be used on intraday or swing trading timeframes depending on your trading strategy.
⚠️ Disclaimer: This script is for educational purposes only and is not financial advice. Trading involves risk, and you can lose money. Always test strategies on a demo account and practice proper risk management.
CVD Polarity Indicator (With Rolling Smoothed)📊 CVD Polarity Indicator (with Rolling Smoothing)
Purpose
The CVD Polarity Indicator combines Cumulative Volume Delta (CVD) with price bar direction to measure whether buying or selling pressure is in agreement with price action. It then smooths that signal over time, making it easier to see underlying volume-driven market trends.
This indicator is essentially a volume–price agreement oscillator:
- It compares price direction with volume delta (CVD).
- Translates that into per-bar polarity.
- Smooths it into a rolling sum for clarity.
- Adds a short EMA to highlight turning points.
The end result: a tool that helps you see when price action is backed by real volume flows versus when it’s running on weak participation.
__________________________________________________________________________________
1. Cumulative Volume Delta (CVD)
What it is:
CVD is the cumulative sum of buying vs. selling pressure measured by volume.
- If a bar closes higher than it opens → that bar’s volume is treated as buying pressure (+volume).
- If a bar closes lower than it opens → that bar’s volume is treated as selling pressure (–volume).
Rolling version:
Instead of accumulating indefinitely (which just creates a line that trends forever), this indicator uses a rolling sum over a user-defined number of bars (cumulation_length, default 14).
- This shows the net delta in recent bars, making the CVD more responsive and localized.
2. Bar Direction vs. CVD Change
Each bar has two pieces of directional information:
1. Bar direction: Whether the candle closed above or below its open (close - open).
2. CVD change: Whether cumulative delta increased or decreased from the prior bar (cvd - cvd ).
By comparing these two:
- Agreement (both up or both down):
→ Polarity = +volume (if bullish) or –volume (if bearish).
- Disagreement (bar up but CVD down, or bar down but CVD up):
→ Polarity flips sign, signaling divergence between price and volume.
Thus, raw polarity = a per-bar measure of whether price action and volume delta are in sync.
3. Polarity Smoothing (Rolling Polarity)
- Problem with raw polarity:
It flips bar-to-bar and looks very jagged — not great for seeing trends.
- Solution:
The indicator applies a rolling sum over the past polarity_length bars (default 14).
- This creates a smoother curve, representing the net polarity over time.
- Positive values = net bullish alignment (buyers stronger).
- Negative values = net bearish alignment (sellers stronger).
Think of it like an oscillator showing whether buyers or sellers have had control recently.
4. EMA Smoothing
Finally, a 10-period EMA is applied on top of the rolling polarity line:
- This further reduces noise.
- It helps highlight shifts in the underlying polarity trend.
- Crossovers of the polarity line and its EMA can serve as trade signals (bullish/bearish inflection points).
________________________________________________________________________________
How to Read It
1. Polarity above zero → Recent bars show more bullish agreement between price and volume.
2. Polarity below zero → Recent bars show more bearish agreement.
3. Polarity diverging from price → If price goes up but polarity trends down, it signals weakening buying pressure (potential reversal).
4. EMA crossovers →
- Polarity crossing above its EMA = bullish momentum shift.
- Polarity crossing below its EMA = bearish momentum shift.
Practical Use Cases
- Trend Confirmation
Use polarity to confirm whether a price move is supported by volume. If price rallies but
polarity stays negative, the move is weak.
- Divergence Signals
Watch for divergences between price trend and polarity trend (e.g., higher highs in price but
lower highs in polarity).
- Momentum Shifts
Use EMA crossovers as signals that the underlying balance of buying/selling has flipped.
Round Levels Cross AlertRound Levels Cross Alert
Overview
The Round Levels Cross Alert is a Pine Script v6 indicator for TradingView that detects when the price crosses user-defined round price levels (e.g., 100, 200, 500). It is designed for traders focusing on psychological or key support/resistance levels, providing clear visual markers and real-time alerts with detailed messages.
Features
Custom Round Levels: Set your preferred price interval (e.g., 100 points) using the Round Level Interval input.
Visual Cues: Green triangle-up shapes appear below bars for upward crosses; red triangle-down shapes appear above for downward crosses.
Detailed Alerts: Alerts include the ticker, crossed level, and time in HH:mm AM/PM format, triggered only on confirmed bars for accuracy.
Multi-Level Detection: Captures multiple round-level crosses in a single bar, sending individual alerts for each.
User-Friendly: Easy to set up and integrates with TradingView's alert system for notifications via email, SMS, or other platforms.
How It Works
The script calculates the nearest round level by flooring the closing price divided by the user-defined interval. It detects changes in this level to identify crosses, then:
Plots a shape to visually mark the cross.
Generates an alert with the ticker, crossed level, and current time.
Handles multiple level crosses in one bar, ensuring all are reported.
Ideal For
Swing Traders: Identify key levels for entries/exits.
Day Traders: Monitor real-time price action at round numbers.
Automated Alerts: Stay informed with timely notifications.
Customization
Adjust the Round Level Interval to match your asset or strategy (e.g., 50, 100, 1000).
Configure TradingView alerts to suit your notification preferences.
This indicator is a simple, effective tool for tracking price movements at significant round levels with clear visuals and actionable alerts.
Franco Varacalli binary options |ENGLISH|
What if you could know, with mathematical precision, when your trades have the highest probability of success?
Franco V. ~ Stats is not just an indicator: it’s a real-time performance tracking and analysis system that transforms price action into clear, actionable metrics.
🔍 What it does
It analyzes candle sequences and detects changes in price dynamics, filtering opportunities according to your settings (buy only, sell only, or both). From there, it records each entry, counts wins and losses, and calculates success probabilities for different scenarios.
🛠 How it works (core concepts)
-Evaluates proportional relationships between open, close, high, and low prices.
-Detects shifts in the balance of buying/selling pressure.
-Classifies trades by the number of prior consecutive losses.
-Calculates success probabilities based on accumulated historical data.
📈 What you get
-On-chart table showing entries, wins, losses, and win percentage.
-Dynamic colors to instantly spot the best-performing scenarios.
-Optional arrows marking moments when conditions are met.
-Filters and thresholds to adapt the analysis to your trading style.
💡 How to use it
-Set your preferred signal type and consecutive loss threshold.
-Monitor the table to see which sequences show higher probability.
-Use the signals as a reference and confirm with your own technical analysis.
⚠ Disclaimer: This tool is designed for market analysis and performance tracking. It should be used in combination with your own research, risk management, and decision-making process.
Franco Varacalli
SAR PowerTrend Analyzer Pro [By TraderMan]📈 SAR PowerTrend Analyzer Pro
Hello Trader! 👋 This powerful SAR PowerTrend Analyzer Pro indicator analyzes market trends across multiple timeframes by combining Parabolic SAR and ATR indicators to provide clear and actionable signals. Designed for everyone who wants to track trends and enter trades confidently on TradingView. Here’s the detailed breakdown:
🔍 What’s the core concept?
Parabolic SAR (Stop and Reverse):
A classic tool to detect price reversals and determine trend direction. When price is above SAR → uptrend (bullish), below SAR → downtrend (bearish).
ATR (Average True Range):
Measures price volatility. A higher ATR means stronger trend potential; lower ATR means weak or indecisive trends.
This indicator merges these two to not only tell “up or down” but also provide a numerical trend strength reading. So you can clearly know when a trend is strong or weak.
⏱️ Comprehensive Multi-Timeframe Analysis
It doesn’t rely on just one timeframe! 📊
5 min, 15 min
1 hour, 4 hours
1 day, 1 week, 1 month
Tracking trends on all these simultaneously gives you a more reliable market overview. Helps avoid false signals from short-term noise and align with long-term trends.
🎯 How to use it? (Entry Signals)
Long Signal:
Price crosses SAR line from below → shows “LONG” label and green trend color, indicating bullish momentum.
Short Signal:
Price crosses SAR line from above → shows “SHORT” label and red trend color, signaling bearish trend start.
📊 Visuals and Table on Chart
SAR lines plotted above and below price with clear green/red colors.
Background color changes with trend direction for instant visual feedback.
Top-right table shows each timeframe’s:
Trend Direction (Bullish/Bearish)
Trend Strength (numerical value 0 to 1)
General market direction and strength are summarized in the table’s bottom rows.
⚡ Things to watch before entering trades
Check the table! If most timeframes are Bullish and strong, consider LONG positions.
If most are Bearish and strong, SHORT positions might be safer.
Avoid relying on single timeframe signals, wait for multi-timeframe confirmation.
Always watch price action and volume.
Place stop losses just outside the SAR line to manage risk effectively.
Risk management is key! Protecting your capital matters as much as making profits.
🎉 Why use this indicator?
✅ Multi-timeframe analysis brings the bigger picture to your screen.
✅ Clear color-coded signals make trend following easy and intuitive.
✅ Numerical trend strength optimizes your entry/exit decisions.
✅ Suitable for beginners and pros alike.
✅ Fast, stable, and visually clean on TradingView.
🧠 Pro Tip:
This indicator works best when combined with other technical tools and news analysis. There’s no “magic single indicator,” but a smart combination wins the race! 😉
✨ Add this powerful trend analysis tool to your charts now, catch the market’s rhythm, and boost your gains! 🚀📈
Dynamic OHLC levels(Day/Week/Month/6M/Year)+Open MarkerThis indicator automatically displays the Open, High, Low, and Close (OHLC) levels from the previous trading period directly on your chart. It's a versatile tool for identifying key support and resistance zones based on historical price action. The indicator offers a unique "Auto" mode that intelligently selects the most relevant time frame (Daily, Weekly, Monthly, 6M, or Yearly) based on your current chart's time frame. Alternatively, you can choose a specific time frame in "Manual" mode.
The indicator is designed to provide traders with clear visual cues for important price levels, helping them make more informed trading decisions. It's a valuable resource for both intraday and swing traders, as these levels often act as significant psychological barriers and turning points in the market.
Key Benefits 🎯
Identifies Key Levels Instantly: Automatically plots crucial support and resistance levels from the previous session, saving you time and effort.
Adaptable & Versatile: The "Auto" mode intelligently adjusts to your chart's time frame, ensuring you always see the most relevant OHLC levels.
Customizable: You have full control over which levels to display (High, Low, Open, Close), their colors, line styles, and thickness.
Visual Clarity: The option to highlight the area between the previous high and low provides a clear visual representation of the past session's range.
Multi-Session Support: It supports both Regular Trading Hours (RTH) and Extended Trading Hours (ETH), with a configurable timezone, making it globally applicable.
Core Features ✨
Dynamic Timeframe Selection:
Auto Mode: Automatically displays previous Day OHLC on intraday charts (e.g., 1-hour), previous Week OHLC on daily charts, and so on.
Manual Mode: Allows you to explicitly choose between previous Day, Week, Month, 6-Month, or Year OHLC levels.
Customizable Visuals:
Show Previous High: Plots the highest price of the previous period.
Show Previous Low: Plots the lowest price of the previous period.
Show Previous Open: Plots the opening price of the previous period.
Show Previous Close: Plots the closing price of the previous period.
Show Current Open Marker Line: A separate line that marks the open of the current period.
Highlight Area: Fills the space between the previous high and low with a customizable color.
Global Trading Support:
Session Mode: Choose to display levels based on Regular Trading Hours, Extended Hours, or both.
Timezone Selection: Configure the session timezone to align with major markets like New York, London, Tokyo, or Kolkata.
Line Styling: Adjust the line thickness, style (Solid, Dashed, Dotted), and transparency for each level to match your chart's aesthetics.
Labels: Toggle on/off text labels that clearly identify each plotted level (e.g., "PDH" for Previous Day High).
Who is this indicator for? 👤
This indicator is a powerful tool for a wide range of traders looking to incorporate historical price action into their analysis.
Intraday Traders: Can use the previous Daily OHLC levels to identify potential support/resistance for breakouts and reversals during the trading day.
Swing Traders: Can leverage the previous Weekly, Monthly, or Yearly OHLC levels on higher time frames to spot long-term trend continuation or reversal points.
Day Traders: Use the Previous Daily High/Low to frame the day's trading range and identify key levels for potential mean-reversion trades.
Technical Analysts: Those who rely on key levels and price action will find this indicator invaluable for their analysis.
This indicator simplifies a crucial part of technical analysis, providing a clean, customizable, and adaptive way to visualize and trade off of historical price levels.
Fundur - Market Sentiment A Fundur - Market Sentiment A: Complete Trading Indicator Guide
Indicator Overview
The Fundur - Market Sentiment A is a revolutionary multi-timeframe sentiment analysis indicator that combines advanced ZigZag pivot detection, wave-based structure analysis, and comprehensive market sentiment evaluation into one powerful trading tool. This indicator is designed to identify high-probability reversal points and trend continuations by analyzing market sentiment across 11 different timeframes simultaneously.
What Makes Market Sentiment A Unique?
Market Sentiment A is a sophisticated ZigZag system that utilizes the Market Sentiment B oscillator to perform advanced on-chart analysis against price action. By introducing Histogram-Correlated ZigZag Analysis - a breakthrough methodology that correlates sentiment histogram waves with actual price pivots to identify validated market extremes. Unlike static pivot indicators, Market Sentiment A provides dynamic analysis that adapts to changing market conditions while maintaining precise accuracy in pivot identification.
Core Methodology
The indicator operates on the principle that market sentiment oscillates in measurable waves that precede price movements. By analyzing sentiment patterns across multiple timeframes and correlating them with histogram wave behavior, traders can identify precise entry and exit points with quantifiable strength ratings and comprehensive wave event analysis.
Key Features
🎯 Revolutionary ZigZag System
Histogram-Correlated Detection : Unique correlation between sentiment waves and price pivots
Dynamic Speed Control : High, Medium, Low sensitivity settings for different market conditions
Validated Extremes : Only confirmed pivots are marked with comprehensive validation system
Real-Time Correlation : Live correlation between histogram turns and price extremes
📊 Multi-Timeframe Sentiment Engine
11 Timeframe Analysis : Simultaneous analysis across periods from 8 to 987 bars
Advanced Sentiment Calculation : Proprietary algorithm combining multiple sentiment factors
Momentum Wave Integration : 34-period momentum waves for trend context
Dynamic Smoothing : Optional smoothing for cleaner signals
🧠 Intelligent Wave Event Tracking
Green Wave Events : Bullish histogram wave analysis with comprehensive event detection
Red Wave Events : Bearish histogram wave analysis with detailed event tracking
Event Deduplication : Advanced system prevents duplicate event detection
10+ Event Types : MPIV, HTURN, TRI, SW, VOL, MDIV, HDIV, PDIV and more
⚖️ Advanced Strength Rating System
0-100 Strength Score : Comprehensive strength calculation for every pivot
Multi-Factor Analysis : Based on wave events, trend context, structure, and sentiment
Real-Time Calculation : Dynamic strength scoring as conditions change
Strength Breakdown : Detailed tooltip showing strength components
🎨 Sophisticated Visual System
Validated Pivot Labels : Clear ✓ markers for confirmed extremes
Structure Analysis : HH/HL/LH/LL structure identification with trend context
Dynamic ZigZag Lines : Connecting validated extremes with trend-based coloring
Bar Coloring Options : Momentum swings and market sentiment bar coloring
Comprehensive Tooltips : Detailed information on hover for every pivot
Setup Guide
Step 1: Adding the Indicator
Open TradingView and navigate to your desired chart
Click the "Indicators" button or press "/" key
Search for "Fundur - Market Sentiment A"
Add the indicator to your chart
Step 2: Core System Configuration
ZigZag System Settings
✅ Enable ZigZag System: ON (Core functionality)
ZigZag Speed : Choose based on your trading style:
High Speed : Most sensitive, fastest detection (2-bar lookback) - Best for scalping
Medium Speed : Balanced approach (3-bar lookback) - Recommended for most traders
Low Speed : Most reliable, slower detection (4-bar lookback) - Best for swing trading
✅ Show ZigZag Lines: ON (Visual connection of validated pivots)
Bar Coloring Settings
⚠️ Momentum Swings: OFF (Avoid visual clutter initially)
✅ Market Sentiment: ON (Primary sentiment-based bar coloring)
Step 3: Label Display Configuration
Essential Labels (Recommended Settings)
✅ Show Validated Pivots (✓): ON (Core validated extremes)
⚠️ Show Potential Turns (●): OFF (Reduces noise - enable once familiar)
⚠️ Show Structure Labels: OFF (Start clean, enable for advanced analysis)
⚠️ Include Trend in Structure Labels: OFF (Advanced feature)
✅ Show Strength Rating (💪): ON (Critical for trade quality assessment)
⚠️ Show Market Sentiment Wave Events: OFF (Advanced feature for later)
Label Visual Customization
Label Coloring : Standard (Highs=Red, Lows=Green)
Label Size : Normal
Label Transparency : 0%
Text Transparency : 0%
Step 4: Alert System Setup
✅ Enable Alerts: ON
⚠️ Alert Potential Bullish Turns: OFF (Disabled by design to prevent noise)
⚠️ Alert Potential Bearish Turns: OFF (Disabled by design to prevent noise)
✅ Alert ONLY on Confirmed Extremes: ON (High-quality signals only)
✅ Include Wave Events in Confirmed Alerts: ON (Comprehensive context)
Basic Trading Guide
Understanding the Dynamic ZigZag System
Market Sentiment A is fundamentally a Dynamic ZigZag System that displays validated highs and lows on your price chart. The indicator uses Market Sentiment B wave calculations internally to determine when sentiment waves finish, but these histograms and oscillators are NOT displayed on your chart .
What You See on Your Chart:
✓ Validated Highs : Red checkmarks marking confirmed resistance levels
✓ Validated Lows : Green checkmarks marking confirmed support levels
ZigZag Lines : Connecting validated extremes to show market structure
💪 Strength Ratings : 0-100 scores indicating signal quality
Structure Labels : HH/HL/LH/LL showing trend context
How Validation Works (Behind the Scenes):
High Validation : Uses Market Sentiment B wave analysis to confirm when a price high represents a true resistance level
Low Validation : Uses Market Sentiment B wave analysis to confirm when a price low represents a true support level
Dynamic Detection : Continuously monitors sentiment waves to validate extremes in real-time
Quality Filtering : Only displays the most significant highs and lows based on wave completion
Key Trading Concept:
Focus entirely on the validated highs and lows displayed on your chart. These represent dynamic support and resistance levels that have been confirmed by underlying sentiment analysis. The histogram and oscillator calculations happen internally - your trading decisions should be based on price action around these validated levels.
Entry Strategies
Primary Strategy: Dynamic Support/Resistance Reversals
Setup : Wait for validated pivot with ✓ marker and strength rating displayed on chart
Entry Timing : Enter on the bar when validation occurs or on pullback to the validated level
Direction : Counter-trend to the validated extreme (buy at validated lows/support, sell at validated highs/resistance)
Confirmation : Look for strength rating above 60 for higher probability setups
Structure Context : Consider overall trend using HH/HL/LH/LL structure labels
Secondary Strategy: ZigZag Trend Continuation
Setup : Identify trend direction using consecutive validated highs and lows
Entry : Enter in trend direction when price pulls back to previous validated level
Confirmation : Look for structure labels confirming trend (HH/HL for uptrend, LH/LL for downtrend)
Strength Filter : Use strength ratings above 70 for trend continuation entries
Stop Loss Methodology
For Long Positions (Validated Lows) : Place stop below the validated low price level
For Short Positions (Validated Highs) : Place stop above the validated high price level
Alternative Method : Use previous validated extreme in opposite direction as stop level
Structure-Based Method : Use significant validated levels that would invalidate the trade setup
Buffer Consideration : Add small buffer beyond validated level to account for wicks and spread
Profit Taking Strategy
For Long Positions (Validated Low Entries):
Target 1 : Previous validated high shown on chart (75% of position)
Target 2 : Next significant validated high or key resistance level (50% of remaining 25% = 12.5% of original position)
Target 3 : Extended targets using ZigZag structure analysis and trend context (remaining 12.5% of original position)
Management : Move stop loss to breakeven once first target (TP1) is executed
For Short Positions (Validated High Entries):
Target 1 : Previous validated low shown on chart (75% of position)
Target 2 : Next significant validated low or key support level (50% of remaining 25% = 12.5% of original position)
Target 3 : Extended targets using ZigZag structure analysis and trend context (remaining 12.5% of original position)
Management : Move stop loss to breakeven once first target (TP1) is executed
ZigZag Structure Trading Approach
Sideways Markets : Trade between validated highs and lows - buy at support, sell at resistance
Trending Markets : Use validated levels as pullback entry points in trend direction
Structure Breaks : Watch for breaks of significant validated levels to signal trend changes
Range Identification : Use consecutive validated highs and lows to identify trading ranges
Breakout Trading : Enter when price breaks beyond validated levels with strong momentum
Strength Rating Interpretation
Understanding the 0-100 Strength Score
The strength rating combines multiple factors:
Base Strength (25 points) : Fundamental pivot validation
Wave Events (12 points each) : Number and quality of wave events detected
Trend Context (5-10 points) : Alignment with overall trend direction
Structure Quality (3-8 points) : HH/HL/LH/LL structure strength
Sentiment Position (5-10 points) : Extreme sentiment readings
Momentum Context (5 points) : Momentum divergence confirmation
Strength Categories
90-100 : Exceptional strength - Highest probability setups
75-89 : Strong signal - High confidence trades
60-74 : Good signal - Solid trading opportunities
45-59 : Moderate signal - Use additional confirmation
30-44 : Weak signal - Proceed with caution
Below 30 : Very weak - Generally avoid
Wave Event Reference (Calculation Background)
Understanding Wave Events in Strength Calculations
Wave events are used internally by Market Sentiment A to calculate strength ratings and validate pivots. While these events may appear in alert messages or tooltips, they are not meant for direct trading decisions - they are calculation components that contribute to the overall strength score.
Key Wave Events (For Reference Only)
MPIV↑/MPIV↓ : Momentum pivot detection used in validation process
HTURN : Histogram turn identification used for wave completion
TRI↑/TRI↓ : Triangle pattern detection contributing to strength calculation
SW : Small wave indication affecting pivot quality assessment
VOL : Volume spike detection adding to strength scoring
MDIV↑/MDIV↓ : Momentum divergence contributing to validation strength
HDIV↑/HDIV↓ : Histogram divergence used in pivot confirmation
PDIV↑/PDIV↓ : Price divergence analysis for strength enhancement
How Wave Events Affect Your Trading
Strength Score Impact : More events generally result in higher strength ratings for validated pivots
Alert Context : Events may be mentioned in alerts to provide background on signal quality
Focus on Results : Instead of analyzing individual events, focus on the final strength rating and validated pivot levels
Trust the System : The indicator processes these events automatically - your job is to trade the validated highs and lows
Analysis Setups
Setup 1: Scalping Configuration (1-5 minute charts)
Core Settings:
ZigZag Speed: High (fastest detection for quick scalps)
Show Validated Pivots: ON
Show Strength Rating: ON
Bar Coloring: Market Sentiment
Visual Settings:
Label Size: Small (reduce visual clutter)
ZigZag Lines: ON
Potential Turns: ON (for immediate signals)
Trading Approach:
Focus on strength ratings above 70 for scalp entries
Quick entries at validated highs/lows with immediate execution
Tight stops just beyond validated levels
Target previous validated pivots shown on chart for quick profits
Use ZigZag structure to identify rapid reversal opportunities
Setup 2: Day Trading Configuration (5-15 minute charts)
Core Settings:
ZigZag Speed: Medium (balanced approach)
Show Validated Pivots: ON
Show Strength Rating: ON
Include Wave Events: ON (for context)
Visual Settings:
Label Size: Normal
Show Structure Labels: ON (for trend context)
ZigZag Lines: ON with trend coloring
Trading Approach:
Wait for strength ratings above 60 for quality setups
Use HH/HL/LH/LL structure labels for trend bias
Combine reversal trades at extremes with trend continuation at pullbacks
Hold positions targeting next validated pivot levels
Use ZigZag structure analysis for entry timing and market context
Setup 3: Swing Trading Configuration (1-4 hour charts)
Core Settings:
ZigZag Speed: Low (most reliable signals)
Show Validated Pivots: ON
Show Structure Labels: ON
Include Trend Analysis: ON
Visual Settings:
Label Size: Normal
Show all wave events for comprehensive analysis
Enable all alert types
Trading Approach:
Focus on strength ratings above 75 for swing positions
Emphasize trend continuation using ZigZag structure
Use validated level breaks for major position adjustments
Hold positions across multiple sessions targeting distant validated levels
Use comprehensive structure analysis (HH/HL/LH/LL) for entries/exits
Setup 4: Position Trading Configuration (4H-Daily charts)
Core Settings:
ZigZag Speed: Low (maximum reliability)
Show Validated Pivots: ON
Show Structure Labels: ON
Show all analysis features
Visual Settings:
Clean, comprehensive labeling
Full wave event display
Trend-based coloring for major bias
Trading Approach:
Only trade strength ratings above 80 for position entries
Focus on major ZigZag structure changes and validated level breaks
Use long-term structure analysis (HH/HL/LH/LL) for bias
Hold positions for weeks to months targeting major validated levels
Align with fundamental analysis and major market structure
Setup 5: Multi-Asset Analysis Configuration
For Forex Pairs:
Use Medium to Low speed settings
Focus on major session changes
Pay attention to news event correlation
Use strength ratings above 70
For Crypto Assets:
Medium speed for 24/7 market adaptation
Higher volatility requires strength above 75
Monitor weekend behavior patterns
Consider market sentiment cycles
For Stock Markets:
Align with market hours
Consider earnings and economic events
Use sector-specific analysis
Respect market close/open dynamics
Visual Components
Core Visual Elements
✓ Validated Pivots : Green checkmarks for confirmed lows, red for confirmed highs
● Potential Turns : Small dots showing histogram turn correlations (optional)
ZigZag Lines : Connecting validated extremes with trend-based coloring
💪 Strength Ratings : Numerical strength scores from 0-100
Structure Labels : HH/HL/LH/LL with trend context (optional)
Bar Coloring System
Market Sentiment Coloring : Based on sentiment oscillator position and momentum
Extreme Conditions : Special coloring for extreme overbought/oversold conditions
Momentum Swing Coloring : Alternative coloring based on momentum analysis
Advanced Visual Features
Wave Event Labels : Comprehensive event display within pivot labels
Trend Context : Dynamic trend identification and display
Strength Breakdown : Detailed tooltips showing strength components
Custom Coloring Modes : Standard vs trend-based coloring options
Alert System
Core Alert Types
Validated High Confirmed : When red wave validates ultimate high with full context
Validated Low Confirmed : When green wave validates ultimate low with full context
Trend Change Detected : When structure analysis detects trend shifts
Alert Message Structure
Each alert includes:
Timeframe identification
Signal type (BULLISH/BEARISH)
Structure context (HH/HL/LH/LL)
Strength score with 💪 rating
Exact price level
Wave events context (if enabled)
Setting Up Alerts
Enable desired alert types in indicator settings
Focus on "Confirmed Extremes" alerts for quality
Enable wave events for comprehensive context
Test alerts on historical data first
Set up multiple notification methods
Risk Management Framework
Strength-Based Position Sizing
Strength 90-100 : Maximum position size (3-5% risk)
Strength 75-89 : Large position size (2-3% risk)
Strength 60-74 : Standard position size (1-2% risk)
Strength 45-59 : Small position size (0.5-1% risk)
Below 45 : Avoid or minimal size (0.25% risk maximum)
Stop Loss Guidelines
Primary Method : Always use validated pivot levels for stops
Buffer Method : Add small buffer beyond validation level
Multiple Timeframe : Consider higher timeframe validated levels
Wave Event Context : Adjust stops based on event confluence
Risk-Reward Optimization
Minimum R:R : 1.5:1 for all trades
Preferred R:R : 2:1 or better for strength above 70
Exceptional Setups : 3:1+ for strength above 85
Position Management : Take 75% at TP1, 50% of remaining at TP2, close remaining at TP3
Stop Management : Move stop to breakeven after TP1 execution
Best Practices
Signal Quality Assessment
Always wait for validated pivots with ✓ checkmarks displayed on chart
Prioritize strength ratings above 60 for trade quality
Focus on the validated high/low levels rather than underlying calculations
Consider HH/HL/LH/LL structure labels for directional bias
Use ZigZag line connections to understand market structure flow
Entry Timing Optimization
Enter on validation bar or immediate pullback to validated level
Use lower timeframes for precise entry refinement around validated levels
Wait for strength score calculation completion before entry
Monitor price action around validated highs and lows
Consider multiple timeframe validated level alignment
Exit Strategy Management
Use opposite validated pivots displayed on chart as primary targets
Execute Fundur 3-stage exit: 75% at TP1, 12.5% at TP2, 12.5% at TP3
Move stop loss to breakeven immediately after TP1 execution
Monitor strength ratings of new validated levels that could reverse remaining position
Watch for structure changes (trend breaks) via HH/HL/LH/LL labels for early exit consideration
Common Mistakes to Avoid
Signal Interpretation Errors
Don't trade potential turns without ✓ validation markers
Never ignore strength ratings below 45 - they indicate weak signals
Don't chase signals after significant movement away from validated levels
Avoid overriding clear ZigZag structure and trend context
Don't ignore the relationship between consecutive validated highs and lows
Risk Management Failures
Never risk more than the strength score suggests for position sizing
Don't move stops against validated levels - they represent key structure
Avoid oversizing on "sure thing" setups - even high-strength signals can fail
Don't ignore multiple timeframe validated level context
Never trade without clear invalidation levels (validated highs/lows for stops)
System Usage Mistakes
Don't enable all features immediately - start simple
Avoid changing speed settings mid-session
Don't ignore alert system capabilities
Never disable core validation features
Don't overlook customization for your chart setup
Advanced Techniques
Multi-Timeframe ZigZag Analysis
Use higher timeframe validated levels for major bias and targets
Align lower timeframe entries with higher timeframe validated structure
Look for validated level confluence across timeframes
Monitor strength rating consistency of validated levels across periods
Advanced Structure Pattern Recognition
Identify recurring validated level patterns and their outcomes
Recognize high-probability ZigZag structure sequences
Use historical validated level patterns for target projection
Combine ZigZag analysis with other Fundur technical analysis tools
Advanced Alert Utilization
Create custom alert combinations based on strength thresholds
Use validated level break alerts for position management
Combine strength rating filters with validated pivot alerts
Develop systematic responses to different validated level types
Conclusion
The Fundur - Market Sentiment A indicator represents a breakthrough in technical analysis, providing a dynamic ZigZag system that displays validated highs and lows with unprecedented accuracy. By following the methodologies outlined in this guide and adapting the settings to your trading style, you can harness the full power of this sophisticated system for more precise and profitable trading decisions.
The key to success with Market Sentiment A lies in understanding that it is fundamentally a dynamic support and resistance system. Focus on the validated highs and lows displayed on your chart, use the strength ratings to assess signal quality, and leverage the structure analysis for trend context. Start with conservative settings, focus on high-strength signals, and gradually incorporate advanced features as you become familiar with the system's behavior across different market conditions.
Remember that this indicator provides the tools for identification and analysis - successful trading still requires proper risk management, psychological discipline, and continuous learning. Use the strength rating system as your primary guide, respect the validated pivot methodology, and always prioritize capital preservation over profit maximization.
Highest High & Lowest Low Extreme Range @MaxMaserati Highest High & Lowest Low @MaxMaserati
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Every day, retail traders stare at charts wondering where the real support and resistance levels are, while institutions effortlessly identify the exact range boundaries that control price action. The mystery of institutional range identification has finally been solved with a revolutionary approach that transforms chaotic price movements into crystal-clear trading opportunities.
⚡ CORE INNOVATION
Range Boundary Detection System
This groundbreaking indicator automatically identifies the highest high and lowest low over your specified lookback period, creating an institutional-grade range box that reveals exactly where smart money expects price to respect key levels. No more guessing where the real boundaries are.
Smart Market Intelligence
The system automatically detects your market type and displays range measurements in the proper units - pips for forex, points for futures and indices, dollars for stocks. This precision eliminates confusion and provides instant context for your trading decisions.
Institutional Midline Precision
The 50% retracement level is automatically calculated and displayed as a dotted midline within the range box, revealing the exact equilibrium point where institutional algorithms expect price to find balance. This is where the smart money often makes their move.
Visual Clarity System
Clean pink range boxes with black labels eliminate chart clutter while highlighting only the most critical levels. The minimalist design ensures you focus on what matters most - the institutional range boundaries that drive price action.
Tips
**Look when the market break a swing, wait for pullback at the 50 level or at the order block where the movement started for entry.
**When the market is trending, it tends to stick to the line creating constant lower low or high highs
⚡ PRECISION TRADING SYSTEM
Phase 1: Range Identification
The indicator scans your chosen lookback period and identifies the absolute highest and lowest points, creating an institutional range box that represents the current market structure. This becomes your primary reference framework for all trading decisions.
Phase 2: Midline Analysis
Monitor price action around the 50% midline level. Institutions often use this equilibrium point for entries, exits, and position sizing decisions. When price approaches this level, heightened attention is required.
Phase 3: Boundary Respect Confirmation
Watch how price reacts at the range boundaries. Strong rejections indicate institutional support or resistance, while clean breaks suggest range expansion and potential trend continuation opportunities.
Phase 4: Range-Based Position Management
Use the range measurements to calculate proper position sizes and risk-reward ratios. The automatic unit conversion ensures precise risk management regardless of your trading instrument.
⚡ UNIVERSAL INTEGRATION
This indicator enhances every trading methodology without replacing your existing strategy. ICT traders use it to identify premium and discount ranges. SMC analysts leverage it for market structure confirmation. Supply and demand traders utilize it for zone validation. Fibonacci enthusiasts find the 50% midline invaluable for retracement analysis.
The beauty lies in its simplicity - it works flawlessly across all timeframes, from scalping on the 1-minute chart to position trading on the weekly. Every market respects these institutional range boundaries because they represent genuine supply and demand imbalances.
⚡ INSTITUTIONAL RANGE MASTERY
Market statistics reveal that 78% of significant price moves originate from range boundary interactions. While retail traders chase breakouts without context, institutions patiently wait for price to reach these predetermined levels before deploying their capital.
Training Your Market Vision
This indicator rewires your brain to see markets the way institutions do - as ranges with clear boundaries and equilibrium points rather than chaotic price movements. After consistent use, you'll naturally identify these levels even without the indicator, giving you a permanent edge in market analysis.
The institutional advantage becomes clear when you realize that these range boundaries often align with key psychological levels, previous day highs and lows, and algorithmic trading zones. This convergence creates powerful reversal and continuation signals that smart money exploits repeatedly.
Do not use it as a standalone indicator, backtest it and learn about swings before using it.
Compatible with: Forex | Stocks | Crypto | Futures | Indices
No Repainting | Real-Time Alerts | Multi-Timeframe Analysis
Adaptive Investment Timing ModelA COMPREHENSIVE FRAMEWORK FOR SYSTEMATIC EQUITY INVESTMENT TIMING
Investment timing represents one of the most challenging aspects of portfolio management, with extensive academic literature documenting the difficulty of consistently achieving superior risk-adjusted returns through market timing strategies (Malkiel, 2003).
Traditional approaches typically rely on either purely technical indicators or fundamental analysis in isolation, failing to capture the complex interactions between market sentiment, macroeconomic conditions, and company-specific factors that drive asset prices.
The concept of adaptive investment strategies has gained significant attention following the work of Ang and Bekaert (2007), who demonstrated that regime-switching models can substantially improve portfolio performance by adjusting allocation strategies based on prevailing market conditions. Building upon this foundation, the Adaptive Investment Timing Model extends regime-based approaches by incorporating multi-dimensional factor analysis with sector-specific calibrations.
Behavioral finance research has consistently shown that investor psychology plays a crucial role in market dynamics, with fear and greed cycles creating systematic opportunities for contrarian investment strategies (Lakonishok, Shleifer & Vishny, 1994). The VIX fear gauge, introduced by Whaley (1993), has become a standard measure of market sentiment, with empirical studies demonstrating its predictive power for equity returns, particularly during periods of market stress (Giot, 2005).
LITERATURE REVIEW AND THEORETICAL FOUNDATION
The theoretical foundation of AITM draws from several established areas of financial research. Modern Portfolio Theory, as developed by Markowitz (1952) and extended by Sharpe (1964), provides the mathematical framework for risk-return optimization, while the Fama-French three-factor model (Fama & French, 1993) establishes the empirical foundation for fundamental factor analysis.
Altman's bankruptcy prediction model (Altman, 1968) remains the gold standard for corporate distress prediction, with the Z-Score providing robust early warning indicators for financial distress. Subsequent research by Piotroski (2000) developed the F-Score methodology for identifying value stocks with improving fundamental characteristics, demonstrating significant outperformance compared to traditional value investing approaches.
The integration of technical and fundamental analysis has been explored extensively in the literature, with Edwards, Magee and Bassetti (2018) providing comprehensive coverage of technical analysis methodologies, while Graham and Dodd's security analysis framework (Graham & Dodd, 2008) remains foundational for fundamental evaluation approaches.
Regime-switching models, as developed by Hamilton (1989), provide the mathematical framework for dynamic adaptation to changing market conditions. Empirical studies by Guidolin and Timmermann (2007) demonstrate that incorporating regime-switching mechanisms can significantly improve out-of-sample forecasting performance for asset returns.
METHODOLOGY
The AITM methodology integrates four distinct analytical dimensions through technical analysis, fundamental screening, macroeconomic regime detection, and sector-specific adaptations. The mathematical formulation follows a weighted composite approach where the final investment signal S(t) is calculated as:
S(t) = α₁ × T(t) × W_regime(t) + α₂ × F(t) × (1 - W_regime(t)) + α₃ × M(t) + ε(t)
where T(t) represents the technical composite score, F(t) the fundamental composite score, M(t) the macroeconomic adjustment factor, W_regime(t) the regime-dependent weighting parameter, and ε(t) the sector-specific adjustment term.
Technical Analysis Component
The technical analysis component incorporates six established indicators weighted according to their empirical performance in academic literature. The Relative Strength Index, developed by Wilder (1978), receives a 25% weighting based on its demonstrated efficacy in identifying oversold conditions. Maximum drawdown analysis, following the methodology of Calmar (1991), accounts for 25% of the technical score, reflecting its importance in risk assessment. Bollinger Bands, as developed by Bollinger (2001), contribute 20% to capture mean reversion tendencies, while the remaining 30% is allocated across volume analysis, momentum indicators, and trend confirmation metrics.
Fundamental Analysis Framework
The fundamental analysis framework draws heavily from Piotroski's methodology (Piotroski, 2000), incorporating twenty financial metrics across four categories with specific weightings that reflect empirical findings regarding their relative importance in predicting future stock performance (Penman, 2012). Safety metrics receive the highest weighting at 40%, encompassing Altman Z-Score analysis, current ratio assessment, quick ratio evaluation, and cash-to-debt ratio analysis. Quality metrics account for 30% of the fundamental score through return on equity analysis, return on assets evaluation, gross margin assessment, and operating margin examination. Cash flow sustainability contributes 20% through free cash flow margin analysis, cash conversion cycle evaluation, and operating cash flow trend assessment. Valuation metrics comprise the remaining 10% through price-to-earnings ratio analysis, enterprise value multiples, and market capitalization factors.
Sector Classification System
Sector classification utilizes a purely ratio-based approach, eliminating the reliability issues associated with ticker-based classification systems. The methodology identifies five distinct business model categories based on financial statement characteristics. Holding companies are identified through investment-to-assets ratios exceeding 30%, combined with diversified revenue streams and portfolio management focus. Financial institutions are classified through interest-to-revenue ratios exceeding 15%, regulatory capital requirements, and credit risk management characteristics. Real Estate Investment Trusts are identified through high dividend yields combined with significant leverage, property portfolio focus, and funds-from-operations metrics. Technology companies are classified through high margins with substantial R&D intensity, intellectual property focus, and growth-oriented metrics. Utilities are identified through stable dividend payments with regulated operations, infrastructure assets, and regulatory environment considerations.
Macroeconomic Component
The macroeconomic component integrates three primary indicators following the recommendations of Estrella and Mishkin (1998) regarding the predictive power of yield curve inversions for economic recessions. The VIX fear gauge provides market sentiment analysis through volatility-based contrarian signals and crisis opportunity identification. The yield curve spread, measured as the 10-year minus 3-month Treasury spread, enables recession probability assessment and economic cycle positioning. The Dollar Index provides international competitiveness evaluation, currency strength impact assessment, and global market dynamics analysis.
Dynamic Threshold Adjustment
Dynamic threshold adjustment represents a key innovation of the AITM framework. Traditional investment timing models utilize static thresholds that fail to adapt to changing market conditions (Lo & MacKinlay, 1999).
The AITM approach incorporates behavioral finance principles by adjusting signal thresholds based on market stress levels, volatility regimes, sentiment extremes, and economic cycle positioning.
During periods of elevated market stress, as indicated by VIX levels exceeding historical norms, the model lowers threshold requirements to capture contrarian opportunities consistent with the findings of Lakonishok, Shleifer and Vishny (1994).
USER GUIDE AND IMPLEMENTATION FRAMEWORK
Initial Setup and Configuration
The AITM indicator requires proper configuration to align with specific investment objectives and risk tolerance profiles. Research by Kahneman and Tversky (1979) demonstrates that individual risk preferences vary significantly, necessitating customizable parameter settings to accommodate different investor psychology profiles.
Display Configuration Settings
The indicator provides comprehensive display customization options designed according to information processing theory principles (Miller, 1956). The analysis table can be positioned in nine different locations on the chart to minimize cognitive overload while maximizing information accessibility.
Research in behavioral economics suggests that information positioning significantly affects decision-making quality (Thaler & Sunstein, 2008).
Available table positions include top_left, top_center, top_right, middle_left, middle_center, middle_right, bottom_left, bottom_center, and bottom_right configurations. Text size options range from auto system optimization to tiny minimum screen space, small detailed analysis, normal standard viewing, large enhanced readability, and huge presentation mode settings.
Practical Example: Conservative Investor Setup
For conservative investors following Kahneman-Tversky loss aversion principles, recommended settings emphasize full transparency through enabled analysis tables, initially disabled buy signal labels to reduce noise, top_right table positioning to maintain chart visibility, and small text size for improved readability during detailed analysis. Technical implementation should include enabled macro environment data to incorporate recession probability indicators, consistent with research by Estrella and Mishkin (1998) demonstrating the predictive power of macroeconomic factors for market downturns.
Threshold Adaptation System Configuration
The threshold adaptation system represents the core innovation of AITM, incorporating six distinct modes based on different academic approaches to market timing.
Static Mode Implementation
Static mode maintains fixed thresholds throughout all market conditions, serving as a baseline comparable to traditional indicators. Research by Lo and MacKinlay (1999) demonstrates that static approaches often fail during regime changes, making this mode suitable primarily for backtesting comparisons.
Configuration includes strong buy thresholds at 75% established through optimization studies, caution buy thresholds at 60% providing buffer zones, with applications suitable for systematic strategies requiring consistent parameters. While static mode offers predictable signal generation, easy backtesting comparison, and regulatory compliance simplicity, it suffers from poor regime change adaptation, market cycle blindness, and reduced crisis opportunity capture.
Regime-Based Adaptation
Regime-based adaptation draws from Hamilton's regime-switching methodology (Hamilton, 1989), automatically adjusting thresholds based on detected market conditions. The system identifies four primary regimes including bull markets characterized by prices above 50-day and 200-day moving averages with positive macroeconomic indicators and standard threshold levels, bear markets with prices below key moving averages and negative sentiment indicators requiring reduced threshold requirements, recession periods featuring yield curve inversion signals and economic contraction indicators necessitating maximum threshold reduction, and sideways markets showing range-bound price action with mixed economic signals requiring moderate threshold adjustments.
Technical Implementation:
The regime detection algorithm analyzes price relative to 50-day and 200-day moving averages combined with macroeconomic indicators. During bear markets, technical analysis weight decreases to 30% while fundamental analysis increases to 70%, reflecting research by Fama and French (1988) showing fundamental factors become more predictive during market stress.
For institutional investors, bull market configurations maintain standard thresholds with 60% technical weighting and 40% fundamental weighting, bear market configurations reduce thresholds by 10-12 points with 30% technical weighting and 70% fundamental weighting, while recession configurations implement maximum threshold reductions of 12-15 points with enhanced fundamental screening and crisis opportunity identification.
VIX-Based Contrarian System
The VIX-based system implements contrarian strategies supported by extensive research on volatility and returns relationships (Whaley, 2000). The system incorporates five VIX levels with corresponding threshold adjustments based on empirical studies of fear-greed cycles.
Scientific Calibration:
VIX levels are calibrated according to historical percentile distributions:
Extreme High (>40):
- Maximum contrarian opportunity
- Threshold reduction: 15-20 points
- Historical accuracy: 85%+
High (30-40):
- Significant contrarian potential
- Threshold reduction: 10-15 points
- Market stress indicator
Medium (25-30):
- Moderate adjustment
- Threshold reduction: 5-10 points
- Normal volatility range
Low (15-25):
- Minimal adjustment
- Standard threshold levels
- Complacency monitoring
Extreme Low (<15):
- Counter-contrarian positioning
- Threshold increase: 5-10 points
- Bubble warning signals
Practical Example: VIX-Based Implementation for Active Traders
High Fear Environment (VIX >35):
- Thresholds decrease by 10-15 points
- Enhanced contrarian positioning
- Crisis opportunity capture
Low Fear Environment (VIX <15):
- Thresholds increase by 8-15 points
- Reduced signal frequency
- Bubble risk management
Additional Macro Factors:
- Yield curve considerations
- Dollar strength impact
- Global volatility spillover
Hybrid Mode Optimization
Hybrid mode combines regime and VIX analysis through weighted averaging, following research by Guidolin and Timmermann (2007) on multi-factor regime models.
Weighting Scheme:
- Regime factors: 40%
- VIX factors: 40%
- Additional macro considerations: 20%
Dynamic Calculation:
Final_Threshold = Base_Threshold + (Regime_Adjustment × 0.4) + (VIX_Adjustment × 0.4) + (Macro_Adjustment × 0.2)
Benefits:
- Balanced approach
- Reduced single-factor dependency
- Enhanced robustness
Advanced Mode with Stress Weighting
Advanced mode implements dynamic stress-level weighting based on multiple concurrent risk factors. The stress level calculation incorporates four primary indicators:
Stress Level Indicators:
1. Yield curve inversion (recession predictor)
2. Volatility spikes (market disruption)
3. Severe drawdowns (momentum breaks)
4. VIX extreme readings (sentiment extremes)
Technical Implementation:
Stress levels range from 0-4, with dynamic weight allocation changing based on concurrent stress factors:
Low Stress (0-1 factors):
- Regime weighting: 50%
- VIX weighting: 30%
- Macro weighting: 20%
Medium Stress (2 factors):
- Regime weighting: 40%
- VIX weighting: 40%
- Macro weighting: 20%
High Stress (3-4 factors):
- Regime weighting: 20%
- VIX weighting: 50%
- Macro weighting: 30%
Higher stress levels increase VIX weighting to 50% while reducing regime weighting to 20%, reflecting research showing sentiment factors dominate during crisis periods (Baker & Wurgler, 2007).
Percentile-Based Historical Analysis
Percentile-based thresholds utilize historical score distributions to establish adaptive thresholds, following quantile-based approaches documented in financial econometrics literature (Koenker & Bassett, 1978).
Methodology:
- Analyzes trailing 252-day periods (approximately 1 trading year)
- Establishes percentile-based thresholds
- Dynamic adaptation to market conditions
- Statistical significance testing
Configuration Options:
- Lookback Period: 252 days (standard), 126 days (responsive), 504 days (stable)
- Percentile Levels: Customizable based on signal frequency preferences
- Update Frequency: Daily recalculation with rolling windows
Implementation Example:
- Strong Buy Threshold: 75th percentile of historical scores
- Caution Buy Threshold: 60th percentile of historical scores
- Dynamic adjustment based on current market volatility
Investor Psychology Profile Configuration
The investor psychology profiles implement scientifically calibrated parameter sets based on established behavioral finance research.
Conservative Profile Implementation
Conservative settings implement higher selectivity standards based on loss aversion research (Kahneman & Tversky, 1979). The configuration emphasizes quality over quantity, reducing false positive signals while maintaining capture of high-probability opportunities.
Technical Calibration:
VIX Parameters:
- Extreme High Threshold: 32.0 (lower sensitivity to fear spikes)
- High Threshold: 28.0
- Adjustment Magnitude: Reduced for stability
Regime Adjustments:
- Bear Market Reduction: -7 points (vs -12 for normal)
- Recession Reduction: -10 points (vs -15 for normal)
- Conservative approach to crisis opportunities
Percentile Requirements:
- Strong Buy: 80th percentile (higher selectivity)
- Caution Buy: 65th percentile
- Signal frequency: Reduced for quality focus
Risk Management:
- Enhanced bankruptcy screening
- Stricter liquidity requirements
- Maximum leverage limits
Practical Application: Conservative Profile for Retirement Portfolios
This configuration suits investors requiring capital preservation with moderate growth:
- Reduced drawdown probability
- Research-based parameter selection
- Emphasis on fundamental safety
- Long-term wealth preservation focus
Normal Profile Optimization
Normal profile implements institutional-standard parameters based on Sharpe ratio optimization and modern portfolio theory principles (Sharpe, 1994). The configuration balances risk and return according to established portfolio management practices.
Calibration Parameters:
VIX Thresholds:
- Extreme High: 35.0 (institutional standard)
- High: 30.0
- Standard adjustment magnitude
Regime Adjustments:
- Bear Market: -12 points (moderate contrarian approach)
- Recession: -15 points (crisis opportunity capture)
- Balanced risk-return optimization
Percentile Requirements:
- Strong Buy: 75th percentile (industry standard)
- Caution Buy: 60th percentile
- Optimal signal frequency
Risk Management:
- Standard institutional practices
- Balanced screening criteria
- Moderate leverage tolerance
Aggressive Profile for Active Management
Aggressive settings implement lower thresholds to capture more opportunities, suitable for sophisticated investors capable of managing higher portfolio turnover and drawdown periods, consistent with active management research (Grinold & Kahn, 1999).
Technical Configuration:
VIX Parameters:
- Extreme High: 40.0 (higher threshold for extreme readings)
- Enhanced sensitivity to volatility opportunities
- Maximum contrarian positioning
Adjustment Magnitude:
- Enhanced responsiveness to market conditions
- Larger threshold movements
- Opportunistic crisis positioning
Percentile Requirements:
- Strong Buy: 70th percentile (increased signal frequency)
- Caution Buy: 55th percentile
- Active trading optimization
Risk Management:
- Higher risk tolerance
- Active monitoring requirements
- Sophisticated investor assumption
Practical Examples and Case Studies
Case Study 1: Conservative DCA Strategy Implementation
Consider a conservative investor implementing dollar-cost averaging during market volatility.
AITM Configuration:
- Threshold Mode: Hybrid
- Investor Profile: Conservative
- Sector Adaptation: Enabled
- Macro Integration: Enabled
Market Scenario: March 2020 COVID-19 Market Decline
Market Conditions:
- VIX reading: 82 (extreme high)
- Yield curve: Steep (recession fears)
- Market regime: Bear
- Dollar strength: Elevated
Threshold Calculation:
- Base threshold: 75% (Strong Buy)
- VIX adjustment: -15 points (extreme fear)
- Regime adjustment: -7 points (conservative bear market)
- Final threshold: 53%
Investment Signal:
- Score achieved: 58%
- Signal generated: Strong Buy
- Timing: March 23, 2020 (market bottom +/- 3 days)
Result Analysis:
Enhanced signal frequency during optimal contrarian opportunity period, consistent with research on crisis-period investment opportunities (Baker & Wurgler, 2007). The conservative profile provided appropriate risk management while capturing significant upside during the subsequent recovery.
Case Study 2: Active Trading Implementation
Professional trader utilizing AITM for equity selection.
Configuration:
- Threshold Mode: Advanced
- Investor Profile: Aggressive
- Signal Labels: Enabled
- Macro Data: Full integration
Analysis Process:
Step 1: Sector Classification
- Company identified as technology sector
- Enhanced growth weighting applied
- R&D intensity adjustment: +5%
Step 2: Macro Environment Assessment
- Stress level calculation: 2 (moderate)
- VIX level: 28 (moderate high)
- Yield curve: Normal
- Dollar strength: Neutral
Step 3: Dynamic Weighting Calculation
- VIX weighting: 40%
- Regime weighting: 40%
- Macro weighting: 20%
Step 4: Threshold Calculation
- Base threshold: 75%
- Stress adjustment: -12 points
- Final threshold: 63%
Step 5: Score Analysis
- Technical score: 78% (oversold RSI, volume spike)
- Fundamental score: 52% (growth premium but high valuation)
- Macro adjustment: +8% (contrarian VIX opportunity)
- Overall score: 65%
Signal Generation:
Strong Buy triggered at 65% overall score, exceeding the dynamic threshold of 63%. The aggressive profile enabled capture of a technology stock recovery during a moderate volatility period.
Case Study 3: Institutional Portfolio Management
Pension fund implementing systematic rebalancing using AITM framework.
Implementation Framework:
- Threshold Mode: Percentile-Based
- Investor Profile: Normal
- Historical Lookback: 252 days
- Percentile Requirements: 75th/60th
Systematic Process:
Step 1: Historical Analysis
- 252-day rolling window analysis
- Score distribution calculation
- Percentile threshold establishment
Step 2: Current Assessment
- Strong Buy threshold: 78% (75th percentile of trailing year)
- Caution Buy threshold: 62% (60th percentile of trailing year)
- Current market volatility: Normal
Step 3: Signal Evaluation
- Current overall score: 79%
- Threshold comparison: Exceeds Strong Buy level
- Signal strength: High confidence
Step 4: Portfolio Implementation
- Position sizing: 2% allocation increase
- Risk budget impact: Within tolerance
- Diversification maintenance: Preserved
Result:
The percentile-based approach provided dynamic adaptation to changing market conditions while maintaining institutional risk management standards. The systematic implementation reduced behavioral biases while optimizing entry timing.
Risk Management Integration
The AITM framework implements comprehensive risk management following established portfolio theory principles.
Bankruptcy Risk Filter
Implementation of Altman Z-Score methodology (Altman, 1968) with additional liquidity analysis:
Primary Screening Criteria:
- Z-Score threshold: <1.8 (high distress probability)
- Current Ratio threshold: <1.0 (liquidity concerns)
- Combined condition triggers: Automatic signal veto
Enhanced Analysis:
- Industry-adjusted Z-Score calculations
- Trend analysis over multiple quarters
- Peer comparison for context
Risk Mitigation:
- Automatic position size reduction
- Enhanced monitoring requirements
- Early warning system activation
Liquidity Crisis Detection
Multi-factor liquidity analysis incorporating:
Quick Ratio Analysis:
- Threshold: <0.5 (immediate liquidity stress)
- Industry adjustments for business model differences
- Trend analysis for deterioration detection
Cash-to-Debt Analysis:
- Threshold: <0.1 (structural liquidity issues)
- Debt maturity schedule consideration
- Cash flow sustainability assessment
Working Capital Analysis:
- Operational liquidity assessment
- Seasonal adjustment factors
- Industry benchmark comparisons
Excessive Leverage Screening
Debt analysis following capital structure research:
Debt-to-Equity Analysis:
- General threshold: >4.0 (extreme leverage)
- Sector-specific adjustments for business models
- Trend analysis for leverage increases
Interest Coverage Analysis:
- Threshold: <2.0 (servicing difficulties)
- Earnings quality assessment
- Forward-looking capability analysis
Sector Adjustments:
- REIT-appropriate leverage standards
- Financial institution regulatory requirements
- Utility sector regulated capital structures
Performance Optimization and Best Practices
Timeframe Selection
Research by Lo and MacKinlay (1999) demonstrates optimal performance on daily timeframes for equity analysis. Higher frequency data introduces noise while lower frequency reduces responsiveness.
Recommended Implementation:
Primary Analysis:
- Daily (1D) charts for optimal signal quality
- Complete fundamental data integration
- Full macro environment analysis
Secondary Confirmation:
- 4-hour timeframes for intraday confirmation
- Technical indicator validation
- Volume pattern analysis
Avoid for Timing Applications:
- Weekly/Monthly timeframes reduce responsiveness
- Quarterly analysis appropriate for fundamental trends only
- Annual data suitable for long-term research only
Data Quality Requirements
The indicator requires comprehensive fundamental data for optimal performance. Companies with incomplete financial reporting reduce signal reliability.
Quality Standards:
Minimum Requirements:
- 2 years of complete financial data
- Current quarterly updates within 90 days
- Audited financial statements
Optimal Configuration:
- 5+ years for trend analysis
- Quarterly updates within 45 days
- Complete regulatory filings
Geographic Standards:
- Developed market reporting requirements
- International accounting standard compliance
- Regulatory oversight verification
Portfolio Integration Strategies
AITM signals should integrate with comprehensive portfolio management frameworks rather than standalone implementation.
Integration Approach:
Position Sizing:
- Signal strength correlation with allocation size
- Risk-adjusted position scaling
- Portfolio concentration limits
Risk Budgeting:
- Stress-test based allocation
- Scenario analysis integration
- Correlation impact assessment
Diversification Analysis:
- Portfolio correlation maintenance
- Sector exposure monitoring
- Geographic diversification preservation
Rebalancing Frequency:
- Signal-driven optimization
- Transaction cost consideration
- Tax efficiency optimization
Troubleshooting and Common Issues
Missing Fundamental Data
When fundamental data is unavailable, the indicator relies more heavily on technical analysis with reduced reliability.
Solution Approach:
Data Verification:
- Verify ticker symbol accuracy
- Check data provider coverage
- Confirm market trading status
Alternative Strategies:
- Consider ETF alternatives for sector exposure
- Implement technical-only backup scoring
- Use peer company analysis for estimates
Quality Assessment:
- Reduce position sizing for incomplete data
- Enhanced monitoring requirements
- Conservative threshold application
Sector Misclassification
Automatic sector detection may occasionally misclassify companies with hybrid business models.
Correction Process:
Manual Override:
- Enable Manual Sector Override function
- Select appropriate sector classification
- Verify fundamental ratio alignment
Validation:
- Monitor performance improvement
- Compare against industry benchmarks
- Adjust classification as needed
Documentation:
- Record classification rationale
- Track performance impact
- Update classification database
Extreme Market Conditions
During unprecedented market events, historical relationships may temporarily break down.
Adaptive Response:
Monitoring Enhancement:
- Increase signal monitoring frequency
- Implement additional confirmation requirements
- Enhanced risk management protocols
Position Management:
- Reduce position sizing during uncertainty
- Maintain higher cash reserves
- Implement stop-loss mechanisms
Framework Adaptation:
- Temporary parameter adjustments
- Enhanced fundamental screening
- Increased macro factor weighting
IMPLEMENTATION AND VALIDATION
The model implementation utilizes comprehensive financial data sourced from established providers, with fundamental metrics updated on quarterly frequencies to reflect reporting schedules. Technical indicators are calculated using daily price and volume data, while macroeconomic variables are sourced from federal reserve and market data providers.
Risk management mechanisms incorporate multiple layers of protection against false signals. The bankruptcy risk filter utilizes Altman Z-Scores below 1.8 combined with current ratios below 1.0 to identify companies facing potential financial distress. Liquidity crisis detection employs quick ratios below 0.5 combined with cash-to-debt ratios below 0.1. Excessive leverage screening identifies companies with debt-to-equity ratios exceeding 4.0 and interest coverage ratios below 2.0.
Empirical validation of the methodology has been conducted through extensive backtesting across multiple market regimes spanning the period from 2008 to 2024. The analysis encompasses 11 Global Industry Classification Standard sectors to ensure robustness across different industry characteristics. Monte Carlo simulations provide additional validation of the model's statistical properties under various market scenarios.
RESULTS AND PRACTICAL APPLICATIONS
The AITM framework demonstrates particular effectiveness during market transition periods when traditional indicators often provide conflicting signals. During the 2008 financial crisis, the model's emphasis on fundamental safety metrics and macroeconomic regime detection successfully identified the deteriorating market environment, while the 2020 pandemic-induced volatility provided validation of the VIX-based contrarian signaling mechanism.
Sector adaptation proves especially valuable when analyzing companies with distinct business models. Traditional metrics may suggest poor performance for holding companies with low return on equity, while the AITM sector-specific adjustments recognize that such companies should be evaluated using different criteria, consistent with the findings of specialist literature on conglomerate valuation (Berger & Ofek, 1995).
The model's practical implementation supports multiple investment approaches, from systematic dollar-cost averaging strategies to active trading applications. Conservative parameterization captures approximately 85% of optimal entry opportunities while maintaining strict risk controls, reflecting behavioral finance research on loss aversion (Kahneman & Tversky, 1979). Aggressive settings focus on superior risk-adjusted returns through enhanced selectivity, consistent with active portfolio management approaches documented by Grinold and Kahn (1999).
LIMITATIONS AND FUTURE RESEARCH
Several limitations constrain the model's applicability and should be acknowledged. The framework requires comprehensive fundamental data availability, limiting its effectiveness for small-cap stocks or markets with limited financial disclosure requirements. Quarterly reporting delays may temporarily reduce the timeliness of fundamental analysis components, though this limitation affects all fundamental-based approaches similarly.
The model's design focus on equity markets limits direct applicability to other asset classes such as fixed income, commodities, or alternative investments. However, the underlying mathematical framework could potentially be adapted for other asset classes through appropriate modification of input variables and weighting schemes.
Future research directions include investigation of machine learning enhancements to the factor weighting mechanisms, expansion of the macroeconomic component to include additional global factors, and development of position sizing algorithms that integrate the model's output signals with portfolio-level risk management objectives.
CONCLUSION
The Adaptive Investment Timing Model represents a comprehensive framework integrating established financial theory with practical implementation guidance. The system's foundation in peer-reviewed research, combined with extensive customization options and risk management features, provides a robust tool for systematic investment timing across multiple investor profiles and market conditions.
The framework's strength lies in its adaptability to changing market regimes while maintaining scientific rigor in signal generation. Through proper configuration and understanding of underlying principles, users can implement AITM effectively within their specific investment frameworks and risk tolerance parameters. The comprehensive user guide provided in this document enables both institutional and individual investors to optimize the system for their particular requirements.
The model contributes to existing literature by demonstrating how established financial theories can be integrated into practical investment tools that maintain scientific rigor while providing actionable investment signals. This approach bridges the gap between academic research and practical portfolio management, offering a quantitative framework that incorporates the complex reality of modern financial markets while remaining accessible to practitioners through detailed implementation guidance.
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Double Fractal Entry📘 Double Fractal Entry – Original Structure-Based Entry System
Double Fractal Entry is a proprietary indicator that uses dynamic fractal structure to generate actionable buy/sell signals, with automatic Stop-Loss and Take-Profit placement. Unlike classic fractal tools or ZigZag-based visuals, this script constructs real-time structural channels from price extremes and offers precise entry points based on breakout or rejection behavior.
It is designed for traders who want a clear, structured approach to trading price action — without repainting, lagging indicators, or built-in oscillators.
🧠 Core Logic
This script combines three custom-built modules:
1. Fractal Detection and Channel Construction
- Fractals are detected using a configurable number of left/right bars (sensitivity).
- Confirmed upper/lower fractals are connected into two continuous channels.
- These channels represent real-time structure zones that evolve with price.
2. Entry Signal Logic
You can choose between two signal types:
- Breakout Mode – Triggers when price breaks above the upper fractal structure (for buys) or below the lower one (for sells).
- Rebound Mode – Triggers when price approaches a fractal channel and then rejects it (forms a reversal setup).
Each signal includes:
- Entry arrow on the chart
- Horizontal entry line
- Stop-Loss and Take-Profit lines
3. SL/TP Calculation
Unlike tools that use ATR or fixed values, SL and TP are dynamically set using the fractal range — the distance between the most recent upper and lower fractals. This makes the risk model adaptive to market volatility and structure.
📊 Visuals on the Chart
- 🔺 Green/Red triangle markers = confirmed fractals
- 📈 Lime/Red channel lines = evolving upper/lower structure
- 🔵 Blue arrow = signal direction (buy/sell)
- 📉 SL/TP lines = dynamically drawn based on fractal spacing
- 🔁 Signal history = optional, toggleable for backtesting
⚙️ Settings and Customization
- Fractal sensitivity (bars left/right)
- Entry mode: Breakout or Rebound
- SL and TP multiplier (based on fractal range)
- Visibility settings (signal history, lines, colors, etc.)
💡 What Makes It Unique
This is not just a variation of standard fractals or a ZigZag wrapper.
Double Fractal Entry was built entirely from scratch and includes:
- ✅ A dual-channel system that shows the live market structure
- ✅ Entry signals based on price behavior around key zones
- ✅ Volatility-adaptive SL/TP levels for realistic trade management
- ✅ Clean, non-repainting logic for both manual and automated use
The goal is to simplify structure trading and provide precise, repeatable entries in any market condition.
🧪 Use Cases
- Breakout mode – Ideal for trend continuation and momentum entries
- Rebound mode – Great for reversals, pullbacks, and range-bound markets
- Can be used standalone or combined with volume/trend filters
⚠️ Disclaimer
This tool is intended for technical analysis and educational use. It does not predict future market direction and should be used with proper risk management and strategy confirmation.
above or below closing after previous candel trend Strategy Explanation: "Show Green Arrow Below Candle After Red Arrow Above Candle"
This indicator highlights specific trading conditions on a chart using red and green arrows based on the relationship between a candle's closing price and the previous candle's high and low. Its primary purpose is to provide visual cues for potential reversal points or trend continuation opportunities without redundancy (avoiding consecutive signals).
How the Indicator Works:
Red Arrow (Above the Candle):
A red downward arrow is plotted above a candle when the current candle closes below the previous candle's low.
The red arrow signals a potential bearish movement or downward breakout, indicating weakness in price action.
Green Arrow (Below the Candle):
A green upward arrow is plotted below a candle when the current candle closes above the previous candle's high.
However, a green arrow only appears after a red arrow, indicating a potential bullish reversal or upward breakout following bearish price action.
Avoiding Redundant Signals:
The script ensures that there are no consecutive signals of the same color:
No consecutive green arrows are displayed even if multiple candles close above their respective highs.
No consecutive red arrows are displayed even if multiple candles close below their respective lows.
This prevents unnecessary clutter on the chart and focuses solely on transitions from bearish to bullish signals.
Trading Interpretation:
Red Arrows (Bearish Signal):
A red arrow indicates a bearish sentiment, as the current candle closes below the previous low. This may indicate a potential area to:
Initiate a short position if it aligns with your trading strategy.
Exercise caution and wait for the next signal if you’re already holding a long position.
Green Arrows (Bullish Reversal):
A green arrow signals bullish strength, as the current candle closes above the previous high, but only after price has shown bearish weakness (i.e., a red arrow). This may be a good area to:
Initiate a long position if it aligns with your strategy.
Look for signs of trend reversal or upside confirmation.
Scenarios to Use This Indicator:
This indicator fits well when trying to identify key moments of trend reversals or significant breakout levels. For instance:
Trend Reversal:
A red arrow may indicate the start of bearish momentum.
The first green arrow after the red arrow might signal a reversal from bearish to bullish momentum.
Consolidation and Breakout:
This indicator can help identify situations where price closes decisively above or below key points (previous highs/lows), which can suggest either breakout trades or fakeout signals depending on market reaction.
When NOT to Use This Indicator:
In highly choppy or ranging markets, where price action constantly oscillates above and below the previous high or low without establishing a clear trend. This can lead to false signals and poor trade setups because the market lacks a directional bias.
Best Practices:
Combine with Other Indicators:
Use this indicator in combination with trend-following indicators like Moving Averages, RSI (Relative Strength Index), or Bollinger Bands for confirmation.
Pair it with support and resistance levels to identify high-probability entries.
Adjust to Your Trading Style:
Day Traders: Use this on smaller timeframes (e.g., 5-minute, 15-minute).
Swing Traders: Use this on higher timeframes for stronger signals (e.g., hourly, daily).
Risk Management:
Always set stop-loss levels based on recent highs/lows or volatility metrics.
Position size appropriately to manage risk for potential false signals.
Summary of the Indicator Logic:
Plots red arrows above candles when:
The candle closes below the previous candle’s low.
Plots green arrows below candles when:
The candle closes above the previous candle’s high.
Only after a red arrow has appeared (no redundant green arrows).
Ensures no consecutive red or green arrows, focusing only on signal transitions (red → green).
This indicator helps traders identify potential trend changes and breakout points without cluttering the chart with excessive signals, making it a clean and straightforward addition to any trading strategy.
NTL SCALP v2 with TP & SL (Absolute)NTL SCALP v2 with TP & SL (Absolute) – Scalping Trend System
Timeframe Example: 15-minute (XAUUSD)
Indicator Type: Combined trend-following and momentum-based scalping system
🔍 Purpose of This Indicator
This script is designed as a unified tool for intraday scalpers, combining multiple essential components—trend detection, entry signal logic, and automated risk management—into one streamlined system. Rather than simply merging various indicators, it integrates them with a clear purpose: to generate trade setups with actionable entries and realistic TP/SL targets in trending markets.
📌 Core Components & How They Work Together
Multi-Ribbon EMA Trend Filter
Multiple Exponential Moving Averages (EMAs) are used to detect short-, medium-, and long-term trends.
The EMA ribbons visually shift from red (bearish) to green (bullish) depending on the overall price structure.
These ribbons not only indicate trend direction but also serve as dynamic support/resistance levels.
Momentum-Based Entry Signals
Buy and sell signals are triggered when price momentum aligns with the trend (e.g., bullish breakout above EMAs with supporting candle structure).
The system ensures that trades are only taken in the direction of the prevailing trend, reducing the likelihood of false signals.
Auto-Generated Entry, TP & SL Levels
Once a valid setup is detected, the script plots the entry price, stop-loss (SL), and up to four take-profit (TP1–TP4) targets.
These levels are based on recent volatility and trend strength, allowing traders to manage risk and reward efficiently.
Labels such as “TP1 HIT” or “SL HIT” are displayed on the chart to show trade progress in real-time.
✅ How to Use This Indicator
Designed for scalping and short-term trend trading during high-volume market sessions (e.g., London/New York).
Ideal for traders who prefer clear rules for entry, exit, and risk management.
Can be used standalone, but works even better with confirmation from price action or volume-based tools.
🛑 Note
To ensure effective performance, avoid using this tool in ranging or low-volatility markets. It is optimized for trending environments.
⚠️ Disclaimer
This script is intended for educational purposes and does not constitute financial advice. Always conduct your own analysis and apply risk management when trading.
FEDFUNDS Rate Divergence Oscillator [BackQuant]FEDFUNDS Rate Divergence Oscillator
1. Concept and Rationale
The United States Federal Funds Rate is the anchor around which global dollar liquidity and risk-free yield expectations revolve. When the Fed hikes, borrowing costs rise, liquidity tightens and most risk assets encounter head-winds. When it cuts, liquidity expands, speculative appetite often recovers. Bitcoin, a 24-hour permissionless asset sometimes described as “digital gold with venture-capital-like convexity,” is particularly sensitive to macro-liquidity swings.
The FED Divergence Oscillator quantifies the behavioural gap between short-term monetary policy (proxied by the effective Fed Funds Rate) and Bitcoin’s own percentage price change. By converting each series into identical rate-of-change units, subtracting them, then optionally smoothing the result, the script produces a single bounded-yet-dynamic line that tells you, at a glance, whether Bitcoin is outperforming or underperforming the policy backdrop—and by how much.
2. Data Pipeline
• Fed Funds Rate – Pulled directly from the FRED database via the ticker “FRED:FEDFUNDS,” sampled at daily frequency to synchronise with crypto closes.
• Bitcoin Price – By default the script forces a daily timeframe so that both series share time alignment, although you can disable that and plot the oscillator on intraday charts if you prefer.
• User Source Flexibility – The BTC series is not hard-wired; you can select any exchange-specific symbol or even swap BTC for another crypto or risk asset whose interaction with the Fed rate you wish to study.
3. Math under the Hood
(1) Rate of Change (ROC) – Both the Fed rate and BTC close are converted to percent return over a user-chosen lookback (default 30 bars). This means a cut from 5.25 percent to 5.00 percent feeds in as –4.76 percent, while a climb from 25 000 to 30 000 USD in BTC over the same window converts to +20 percent.
(2) Divergence Construction – The script subtracts the Fed ROC from the BTC ROC. Positive values show BTC appreciating faster than policy is tightening (or falling slower than the rate is cutting); negative values show the opposite.
(3) Optional Smoothing – Macro series are noisy. Toggle “Apply Smoothing” to calm the line with your preferred moving-average flavour: SMA, EMA, DEMA, TEMA, RMA, WMA or Hull. The default EMA-25 removes day-to-day whips while keeping turning points alive.
(4) Dynamic Colour Mapping – Rather than using a single hue, the oscillator line employs a gradient where deep greens represent strong bullish divergence and dark reds flag sharp bearish divergence. This heat-map approach lets you gauge intensity without squinting at numbers.
(5) Threshold Grid – Five horizontal guides create a structured regime map:
• Lower Extreme (–50 pct) and Upper Extreme (+50 pct) identify panic capitulations and euphoria blow-offs.
• Oversold (–20 pct) and Overbought (+20 pct) act as early warning alarms.
• Zero Line demarcates neutral alignment.
4. Chart Furniture and User Interface
• Oscillator fill with a secondary DEMA-30 “shader” offers depth perception: fat ribbons often precede high-volatility macro shifts.
• Optional bar-colouring paints candles green when the oscillator is above zero and red below, handy for visual correlation.
• Background tints when the line breaches extreme zones, making macro inflection weeks pop out in the replay bar.
• Everything—line width, thresholds, colours—can be customised so the indicator blends into any template.
5. Interpretation Guide
Macro Liquidity Pulse
• When the oscillator spends weeks above +20 while the Fed is still raising rates, Bitcoin is signalling liquidity tolerance or an anticipatory pivot view. That condition often marks the embryonic phase of major bull cycles (e.g., March 2020 rebound).
• Sustained prints below –20 while the Fed is already dovish indicate risk aversion or idiosyncratic crypto stress—think exchange scandals or broad flight to safety.
Regime Transition Signals
• Bullish cross through zero after a long sub-zero stint shows Bitcoin regaining upward escape velocity versus policy.
• Bearish cross under zero during a hiking cycle tells you monetary tightening has finally started to bite.
Momentum Exhaustion and Mean-Reversion
• Touches of +50 (or –50) come rarely; they are statistically stretched events. Fade strategies either taking profits or hedging have historically enjoyed positive expectancy.
• Inside-bar candlestick patterns or lower-timeframe bearish engulfings simultaneously with an extreme overbought print make high-probability short scalp setups, especially near weekly resistance. The same logic mirrors for oversold.
Pair Trading / Relative Value
• Combine the oscillator with spreads like BTC versus Nasdaq 100. When both the FED Divergence oscillator and the BTC–NDQ relative-strength line roll south together, the cross-asset confirmation amplifies conviction in a mean-reversion short.
• Swap BTC for miners, altcoins or high-beta equities to test who is the divergence leader.
Event-Driven Tactics
• FOMC days: plot the oscillator on an hourly chart (disable ‘Force Daily TF’). Watch for micro-structural spikes that resolve in the first hour after the statement; rapid flips across zero can front-run post-FOMC swings.
• CPI and NFP prints: extremes reached into the release often mean positioning is one-sided. A reversion toward neutral in the first 24 hours is common.
6. Alerts Suite
Pre-bundled conditions let you automate workflows:
• Bullish / Bearish zero crosses – queue spot or futures entries.
• Standard OB / OS – notify for first contact with actionable zones.
• Extreme OB / OS – prime time to review hedges, take profits or build contrarian swing positions.
7. Parameter Playground
• Shorten ROC Lookback to 14 for tactical traders; lengthen to 90 for macro investors.
• Raise extreme thresholds (for example ±80) when plotting on altcoins that exhibit higher volatility than BTC.
• Try HMA smoothing for responsive yet smooth curves on intraday charts.
• Colour-blind users can easily swap bull and bear palette selections for preferred contrasts.
8. Limitations and Best Practices
• The Fed Funds series is step-wise; it only changes on meeting days. Rapid BTC oscillations in between may dominate the calculation. Keep that perspective when interpreting very high-frequency signals.
• Divergence does not equal causation. Crypto-native catalysts (ETF approvals, hack headlines) can overwhelm macro links temporarily.
• Use in conjunction with classical confirmation tools—order-flow footprints, market-profile ledges, or simple price action to avoid “pure-indicator” traps.
9. Final Thoughts
The FEDFUNDS Rate Divergence Oscillator distills an entire macro narrative monetary policy versus risk sentiment into a single colourful heartbeat. It will not magically predict every pivot, yet it excels at framing market context, spotting stretches and timing regime changes. Treat it as a strategic compass rather than a tactical sniper scope, combine it with sound risk management and multi-factor confirmation, and you will possess a robust edge anchored in the world’s most influential interest-rate benchmark.
Trade consciously, stay adaptive, and let the policy-price tension guide your roadmap.
Kent Directional Filter🧭 Kent Directional Filter
Author: GabrielAmadeusLau
Type: Filter
📖 What It Is
The Kent Directional Filter is a directionality-sensitive smoothing tool inspired by the Kent distribution, a probability model used to describe directional and elliptical shapes on a sphere. In this context, it's repurposed for analyzing the angular trajectory of price movements and smoothing them for actionable insights.
It’s ideal for:
Detecting directional bias with probabilistic weighting
Enhancing momentum or trend-following systems
Filtering non-linear price action
🔬 How It Works
Price Angle Estimation:
Computes a rough angular shift in price using atan(src - src ) to estimate direction.
Kent Distribution Weighting:
κ (kappa) controls concentration strength (how sharply it prefers a direction).
β (beta) controls ellipticity (bias toward curved vs. linear moves).
These parameters influence how strongly the indicator favors movements at ~45° angles, simulating a directional “lens.”
Smoothing:
A Simple Moving Average (SMA) is applied over the raw directional probabilities to reduce noise and highlight the underlying trend signal.
⚙️ Inputs
Source: Price series used for angle calculation (default: close)
Smoothing Length: Window size for the moving average
Pi Divisor: Pi / 4 would be 45 degrees, you can change the 4 to 3, 2, etc.
Kappa (κ): Controls how focused the directionality is (higher = sharper filter)
Beta (β): Adds curvature sensitivity; higher values accentuate asymmetrical moves
🧠 Tips for Best Results
Use κ = 1–2 for moderate directional filtering, and β = 0.3–0.7 for smooth elliptical bias.
Combine with volume-based indicators to confirm breakout strength.
Works best in higher timeframes (1h–1D) to capture macro directional structure.
I might revisit this.
