التحليل الأساسي
XRayXRay is a comprehensive earnings analysis table for TradingView that displays historical quarterly earnings data, year-over-year growth trends, and future estimates in an easy-to-read format directly on your chart.
Column & Description
✅ Date - Earnings report date (MMM-YY format)
✅ EPS ($) - Actual earnings per share in dollars
✅ %Chg (YoY) - EPS year-over-year percentage change
✅ Sales (Mil) - Total revenue in millions
✅ %Chg (YoY) - Sales year-over-year percentage change
✅ Price - Configurable: earnings day close, next trading day close, or current price
✅ %Chg (YoY) - Stock price year-over-year percentage change
Benefits:
✅ All-in-one earnings dashboard - No need to leave your chart
✅ Smart visual encoding - Color, bold, symbols make patterns obvious
✅ Flexible configuration - Adapts to your trading style
✅ Future-looking - Includes analyst estimates for next quarter
Use Cases:
✅ Quick earnings screening - Instantly see growth trends across multiple quarters
✅ Fundamental analysis - Track sales and earnings consistency
✅ Growth acceleration detection - Spot companies accelerating or decelerating
✅ Earnings quality assessment - Compare actual vs. estimates
✅ Position sizing decisions - Evaluate risk based on earnings volatility
✅ Long-term trend analysis - See up to 20 quarters of historical performance
SOP CYCLE UP (MYX:FCPOH2026)# SOP CYCLE TRAILING STRATEGY (MYX:FCPOH2026)
## Technical Overview
This strategy is designed specifically for **FCPO (Crude Palm Oil)** using the "SOP Cycle" algorithm optimized for "Exponential Growth". This technique combines the precision of Scalping with the profit potential of Trend Following.
**Timeframe:** 1 Hour (H1)
**Asset:** MYX:FCPOH2026
## How to Use (Trade Rules)
### 1. Indicator (Visual)
Add the `indicator.pine` file to your TradingView chart.
* **Green Line**: BUY Zone (Cycle Up)
* **Red Line**: SELL Zone (Cycle Down)
* **Label**: Look for "BUY" or "SELL" signals.
### 2. Strategy (Auto/Manual)
Use the `strategy.pine` file for backtesting or automation.
**Entry Rules:**
* **BUY**: When the Cycle changes from Red to **Green** (Confirmed Bar).
* **SELL**: When the Cycle changes from Green to **Red** (Confirmed Bar).
**Exit Rules (Trailing Logic):**
This strategy does not use a fixed Take Profit target. It uses a smart **Trailing Stop**:
1. Trade runs until profit reaches **3 Points** (Activation).
2. Stop Loss will automatically rise, following the price at a distance of **1 Point** (Offset).
* *Advantage*: If price rallies 50 points, we capture huge profits. If price reverses, we lock in a minimum profit.
3. **Trend Change**: If the trend reverses drastically, the system will "Force Close" to prevent large losses.
### 3. Risk Management
* **Initial Stop Loss**: 8 Points (To protect account from sudden spikes).
* **Leverage**: FCPO requires margin, ensure sufficient equity.
---
## Performance
* **Win Rate**: ~High Probability
* **Style**: Hybrid Scalp-Trend
Good Luck!
Stablecoin Depeg & Risk Monitor [SANKTOV]Stablecoin Depeg & Risk Detector
This indicator is a comprehensive monitoring tool designed for professional traders and liquidity providers to track the stability of major stablecoins ( USDT, USDC, and FDUSD ) against the US Dollar. Unlike simple price alerts, this script utilizes multi-layer detection logic to separate market noise from genuine systemic risk.
Key Features
Multi-Asset Monitoring: Simultaneously tracks USDT, USDC, and FDUSD depeg events using high-precision data retrieval from institutional-grade feeds.
Volatility-Adjusted Thresholds: Automatically widens or tightens depeg sensitivity based on ATR (Average True Range) to reduce false positives.
Multi-Timeframe (MTF) Confirmation: Prevents "wick-induced" alerts by requiring confirmation from higher timeframes before flagging a severe event.
Systemic Risk Detection (Sync Depeg): Specialized logic that triggers when multiple stablecoins depeg simultaneously, signaling a broad market crisis.
Spread & Rotation Analysis: Visualizes the spread between USDT and USDC to detect "flight to safety" rotations or capital outflows.
Visualizations & Dashboard
Risk Histogram: Color-coded bars showing the severity of depegs (Moderate, Severe, Extreme) for each asset.
Heat Ribbon & Spread Visualization: A dynamic ribbon at the bottom showing rotation intensity and direction.
Real-time Status Table: A clean HUD providing instant prices, basis point deviations, and systemic status.
Historical Markers: Automatic labels and shapes on the chart to review past depeg events for correlation analysis.
Professional Alert System
Individual Asset Alerts: Specific triggers for both downside depegs and upside premiums.
Synchronous Alerts: Critical alerts for systemic events where multiple pegs are failing at once.
Composite Alerts: Streamlined notification management for "Any Severe" or "Any Extreme" market events.
How to use
This indicator is best used on lower timeframes (1m to 15m) for real-time monitoring while keeping the MTF confirmation set to 1H. It is an essential tool for anyone holding large stablecoin positions or managing DeFi liquidity pools.
Aggregate Bull & Bear IndexAggregate Bull and Bear Index
The Aggregate Bull and Bear Index represents a systematic approach to measuring market sentiment through the aggregation of multiple fundamental market factors. This indicator draws conceptual inspiration from the Bank of America Bull and Bear Indicator, a widely followed institutional sentiment gauge that has demonstrated significant predictive value for market turning points over multiple market cycles (Hartnett, 2019). While the original Bank of America indicator relies on proprietary institutional data flows and internal metrics that remain inaccessible to individual investors, the Aggregate Bull and Bear Index provides a methodologically similar framework using publicly available market data, thereby democratizing access to sentiment analysis previously reserved for institutional participants.
The theoretical foundation of sentiment based investing rests on decades of behavioral finance research demonstrating that market participants systematically exhibit predictable psychological biases during periods of extreme optimism and pessimism. Shiller (2000) documented how irrational exuberance manifests in asset prices through feedback loops of investor enthusiasm, while Kahneman and Tversky (1979) established that human decision making under uncertainty deviates substantially from rational expectations. These behavioral patterns create opportunities for contrarian strategies that exploit the tendency of crowds to overreact at market extremes. The Aggregate Bull and Bear Index quantifies these psychological states by synthesizing information from diverse market segments into a unified scale ranging from zero to ten, where readings below two indicate extreme fear and readings above eight signal extreme greed.
Methodology and Calculation Framework
The methodology underlying the Aggregate Bull and Bear Index incorporates statistical normalization techniques that transform raw market data into comparable standardized scores. Each component factor is processed through a calculation that measures how far current values deviate from historical norms, effectively capturing whether specific market metrics exhibit unusual readings relative to their own history. These normalized components are then aggregated using a weighting scheme designed to balance information from different market segments while minimizing noise and false signals. The final composite undergoes percentile ranking over a trailing lookback period to produce the familiar zero to ten scale that facilitates intuitive interpretation.
The indicator incorporates several important features designed to enhance signal quality and reduce the probability of acting on spurious readings. A consensus filter examines whether multiple underlying components align in the same direction, adding weight to signals when broad agreement exists across different market factors and discounting readings that rest on narrow evidence. Dynamic threshold adjustment allows the extreme zones to adapt to changing market volatility regimes, recognizing that the appropriate definition of extreme varies depending on ambient market conditions. These refinements reflect lessons learned from decades of quantitative finance research on signal processing and regime detection.
Professional Application and Portfolio Integration
Professional portfolio managers have long recognized the value of sentiment indicators as a complementary tool to fundamental and technical analysis. The fundamental insight underlying sentiment based strategies is elegantly simple yet empirically robust. When market participants become uniformly bullish, marginal buyers become exhausted and the probability of price declines increases substantially. Conversely, when pessimism reaches extreme levels, forced selling creates attractive entry points for patient capital. Bank of America research found that their Bull and Bear Indicator generated a remarkable track record when deployed as a contrarian signal, with extreme fear readings historically preceding positive forward returns in equity markets (Bank of America Global Research, 2020). The Aggregate Bull and Bear Index applies this same contrarian logic while adapting the methodology to accommodate the data constraints facing individual investors.
For institutional investors operating with fiduciary responsibilities and substantial capital, the Aggregate Bull and Bear Index serves as one input among many in comprehensive risk management frameworks. Large asset managers might use extreme readings to trigger portfolio review processes, stress testing exercises, or adjustments to tactical allocation overlays. The indicator proves particularly valuable when it diverges from consensus expectations, as such divergences often precede meaningful market inflections. Hedge fund managers implementing systematic strategies can incorporate the index as a conditioning variable that adjusts position sizing or strategy weights based on the prevailing sentiment environment.
The integration of sentiment analysis into investment practice finds support in the concept of informational efficiency and the limits thereof. While efficient market hypothesis suggests that prices reflect all available information, the behavioral finance literature demonstrates that information processing by market participants exhibits systematic biases that create temporary mispricings (Barberis and Thaler, 2003). Sentiment indicators capture the psychological dimension of this information processing, providing insight into how market participants collectively interpret and react to fundamental developments. Extreme sentiment readings often indicate that psychological factors have pushed prices away from levels justified by fundamentals alone, creating opportunities for those willing to act against prevailing market opinion.
Practical Implementation for Individual Investors
The practical implementation of the indicator follows straightforward principles that both sophisticated institutions and individual retail traders can apply within their existing investment frameworks. When the index falls into the extreme fear zone below a reading of two, this suggests that market participants have become excessively pessimistic and that risk assets may offer favorable risk reward characteristics. Traders might consider this an opportune moment to increase equity exposure or reduce hedging positions. When the index rises into the extreme greed zone above eight, the opposite dynamic applies and a defensive posture becomes prudent. This could manifest as reducing equity allocations, increasing cash reserves, or implementing protective hedging strategies. The neutral zone between these extremes suggests no strong directional bias from a sentiment perspective, during which time other analytical frameworks should take precedence in decision making.
Individual retail investors can derive substantial benefit from the indicator even without sophisticated infrastructure or large capital bases. The most straightforward application involves treating extreme readings as alerts that warrant careful examination of existing portfolio positioning. A reading in the extreme fear zone might prompt consideration of whether recent market declines have created opportunities to deploy excess cash or rebalance toward equities. A reading in the extreme greed zone could trigger review of whether current equity exposure exceeds target allocations and whether risk reduction measures merit consideration. Importantly, the indicator should inform rather than dictate investment decisions, serving as one valuable perspective within a broader analytical framework.
Retail investors frequently find themselves at a psychological disadvantage during market extremes because emotional responses to portfolio losses or gains often prompt actions contrary to long term wealth accumulation. The academic literature on investor behavior consistently documents that individual investors tend to buy near market peaks when confidence runs highest and sell near market bottoms when fear dominates (Barber and Odean, 2000). A systematic sentiment indicator provides an objective framework for recognizing these emotional extremes and consciously acting against natural psychological impulses. By externalizing the assessment of market mood into a quantifiable metric, investors create psychological distance from their own emotional state and gain perspective on the collective sentiment environment.
The decision to implement a sentiment indicator within an investment process requires thoughtful consideration of how it complements existing analytical approaches. Technical analysts may find that sentiment readings help contextualize chart patterns and momentum signals, with extreme fear adding conviction to bullish technical setups and extreme greed warranting caution even when price trends appear strong. Fundamental investors can use sentiment as a timing tool that helps avoid the common mistake of being right on valuation but wrong on timing. Quantitative investors might incorporate sentiment factors into multi factor models or use them to adjust position sizing across strategies.
Trading Behavior and Strategy Characteristics
The Aggregate Bull and Bear Index employs a contrarian investment methodology that fundamentally diverges from trend following approaches prevalent in systematic trading. The trading logic rests upon the principle of accumulating positions when collective fear pervades market sentiment and liquidating those positions when greed dominates investor psychology. This approach stands in direct opposition to momentum strategies that amplify existing market movements rather than positioning against them.
The observation that the indicator frequently initiates long positions despite subsequent downward price movement represents not a flaw but an inherent characteristic of contrarian strategies. When the indicator signals extreme fear, this indicates that market participants have already engaged in substantial selling and pessimistic expectations have become embedded in asset prices. However, this emphatically does not guarantee that the ultimate trough has been reached. Fear can intensify, panic selling can escalate, and fundamental deterioration can trigger additional price declines before stabilization occurs. The indicator identifies phases where the statistical probability distribution of future returns appears favorable rather than pinpointing exact inflection points. Academic research by De Bondt and Thaler (1985) demonstrated that markets systematically overreact to both positive and negative information, creating opportunities for patient contrarian investors willing to endure interim volatility.
Risk Profile and Investment Considerations
This characteristic produces a distinctive risk profile that investors must thoroughly comprehend before implementation. The primary danger manifests in what practitioners colloquially term catching a falling knife. Purchasing assets during declining markets exposes capital to potentially severe interim drawdowns even when the ultimate investment thesis proves correct. The backtest evidence reveals numerous instances where positions experienced double digit percentage declines before eventually generating positive returns or triggering exit signals. Investors lacking the psychological fortitude to maintain positions through such adversity will inevitably abandon the strategy at precisely the wrong moment, crystallizing losses that patient adherents would have recovered. Behavioral research by Odean (1998) documented that individual investors exhibit a strong disposition effect, holding losing positions too long in some contexts while selling winners prematurely, yet paradoxically abandoning systematic strategies during drawdowns when discipline matters most.
The temporal dimension of contrarian investing demands particular attention. Unlike trend following strategies that can generate returns relatively quickly by riding established momentum, contrarian approaches often require extended holding periods before mean reversion materializes. The indicator may signal fear and initiate positions that subsequently experience weeks or months of continued decline before sentiment shifts and prices recover. This extended timeline conflicts with human psychological preferences for immediate gratification and creates substantial opportunity for doubt and strategy abandonment. Investors must recognize that the strategy optimizes for terminal wealth accumulation over extended horizons rather than minimizing short term discomfort.
A critical risk factor involves the possibility of genuine regime changes that invalidate historical relationships. While extreme fear readings have historically preceded favorable forward returns, this pattern assumes that pessimism eventually proves excessive and fundamentals stabilize or improve. In scenarios involving structural economic transformation, permanent impairment of earnings power, or systemic financial crisis, fear may prove entirely justified rather than excessive. The indicator cannot distinguish between irrational panic creating buying opportunities and rational recognition of deteriorating fundamentals. This limitation underscores the importance of using the indicator as one input among many rather than as a standalone decision mechanism.
Risk management applications deserve particular attention given the indicator's historical tendency to signal market stress before price declines fully materialize. Portfolio managers charged with protecting capital during drawdowns can use rising greed readings as an early warning system that justifies defensive measures such as reducing beta exposure, increasing cash allocations, or purchasing portfolio protection through options strategies. The contrarian nature of the indicator means that protective action occurs when markets appear strongest rather than weakest, avoiding the common trap of implementing risk reduction after substantial losses have already occurred.
Opportunity Set and Compounding Benefits
The opportunity set presented by contrarian sentiment investing derives from persistent behavioral biases that academic research has extensively documented. Extrapolation bias leads investors to assume recent trends will continue indefinitely, causing excessive optimism after gains and excessive pessimism after losses (Greenwood and Shleifer, 2014). Herding behavior amplifies these tendencies as investors observe and mimic the actions of others, creating self reinforcing cycles of buying or selling that push prices away from fundamental values. The Aggregate Bull and Bear Index systematically exploits these patterns by positioning against the prevailing emotional consensus.
The compounding benefits of buying during fear merit emphasis. When the indicator signals extreme pessimism, asset prices by definition trade at depressed levels relative to recent history. Investors who accumulate positions at these reduced valuations capture not only potential price recovery but also enhanced long term compound returns from reinvesting dividends and earnings at favorable prices. This mathematical advantage compounds over decades, explaining why legendary investors from Benjamin Graham to Warren Buffett have emphasized the importance of purchasing during periods of market distress despite the psychological difficulty such actions entail.
Investor Suitability and Implementation Requirements
Regarding suitability, the Aggregate Bull and Bear Index aligns most appropriately with investors possessing specific characteristics. First, a genuinely long term investment horizon measured in years rather than months proves essential. The strategy will underperform during extended bull markets when momentum approaches dominate and will experience painful interim drawdowns during crisis periods. Only investors capable of maintaining positions through these challenging phases will capture the strategy's full return potential. Second, psychological resilience to act against consensus and tolerate portfolio volatility represents a prerequisite. Research by Goetzmann and Kumar (2008) demonstrated that most individual investors lack the temperament for contrarian strategies despite their theoretical appeal. Third, sufficient financial reserves to avoid forced liquidation during drawdowns ensures that temporary price declines do not become permanent capital impairment.
The indicator proves less suitable for investors seeking steady returns with minimal volatility, those with short investment horizons or imminent liquidity needs, and individuals whose emotional responses to portfolio fluctuations compromise rational decision making. Institutional investors with quarterly performance pressures may find the strategy incompatible with their governance constraints despite its long term merits. Retirees depending on portfolio withdrawals must carefully consider whether interim drawdowns could force disadvantageous liquidations.
For appropriate investors, the Aggregate Bull and Bear Index offers a systematic framework for implementing time tested contrarian principles that have generated superior long term returns across multiple market cycles. By externalizing sentiment assessment into an objective metric, the indicator helps investors overcome the natural human tendency to capitulate at market bottoms and chase performance at market tops. The strategy demands patience, discipline, and genuine long term orientation, but rewards those characteristics with the potential for meaningful wealth accumulation over extended investment horizons.
Proprietary Elements and Limitations
The proprietary aspects of the indicator's construction reflect both practical and theoretical considerations. From a practical standpoint, maintaining certain methodological details as proprietary preserves the informational advantage that the indicator provides and prevents degradation of signal quality that might occur if widespread adoption prompted market participants to trade directly against the underlying components. From a theoretical perspective, the specific parameter choices and weighting schemes represent empirical findings from extensive research that constitute intellectual property developed through substantial effort.
Academic research on sentiment indicators provides encouraging evidence regarding their predictive value while appropriately acknowledging limitations. Baker and Wurgler (2006) demonstrated that investor sentiment predicts the cross section of stock returns, with high sentiment periods followed by lower returns for speculative stocks prone to overvaluation during euphoric conditions. Brown and Cliff (2005) found that sentiment measures contain information about near term market returns beyond that captured by traditional risk factors. However, the same literature cautions that sentiment signals exhibit variable lead times and occasional false positives, reinforcing the importance of using such indicators as part of comprehensive analytical frameworks rather than standalone trading systems.
The Aggregate Bull and Bear Index ultimately represents an attempt to bridge the gap between institutional grade sentiment analysis and the tools available to broader investor populations. By providing a systematic framework for assessing collective market psychology, the indicator empowers users to recognize emotional extremes and consider contrarian positioning when conditions warrant. The historical tendency of markets to reverse from extreme sentiment readings creates opportunities for those willing to act against crowd psychology, while the indicator's multi factor construction and quality filters help distinguish genuine extremes from temporary fluctuations. Whether deployed by professional money managers seeking to refine risk management practices or individual investors striving to overcome behavioral biases, the Aggregate Bull and Bear Index offers a valuable perspective on the eternal struggle between fear and greed that drives financial markets.
References
Baker, M. and Wurgler, J. (2006) Investor sentiment and the cross section of stock returns. The Journal of Finance, 61(4), pp. 1645 to 1680.
Bank of America Global Research (2020) The Bull and Bear Indicator: A contrarian timing tool. Bank of America Securities Research Report.
Barber, B.M. and Odean, T. (2000) Trading is hazardous to your wealth: The common stock investment performance of individual investors. The Journal of Finance, 55(2), pp. 773 to 806.
Barberis, N. and Thaler, R. (2003) A survey of behavioral finance. Handbook of the Economics of Finance, 1, pp. 1053 to 1128.
Brown, G.W. and Cliff, M.T. (2005) Investor sentiment and asset valuation. The Journal of Business, 78(2), pp. 405 to 440.
De Bondt, W.F.M. and Thaler, R. (1985) Does the stock market overreact? The Journal of Finance, 40(3), pp. 793 to 805.
Goetzmann, W.N. and Kumar, A. (2008) Equity portfolio diversification. Review of Finance, 12(3), pp. 433 to 463.
Greenwood, R. and Shleifer, A. (2014) Expectations of returns and expected returns. The Review of Financial Studies, 27(3), pp. 714 to 746.
Hartnett, M. (2019) Flow Show: Bull and Bear Indicator methodology and applications. Bank of America Merrill Lynch Investment Strategy.
Kahneman, D. and Tversky, A. (1979) Prospect theory: An analysis of decision under risk. Econometrica, 47(2), pp. 263 to 291.
Odean, T. (1998) Are investors reluctant to realize their losses? The Journal of Finance, 53(5), pp. 1775 to 1798.
Shiller, R.J. (2000) Irrational Exuberance. Princeton University Press.
سكربت مدفوع
Market State Fear & Greed Bubble Index V1Market State Fear & Greed Bubble Index V1
📊 Comprehensive Market Sentiment Analyzer
This advanced indicator measures market psychology through a multi-dimensional scoring system, combining demand/supply pressure, trend momentum, and statistical extremes to identify fear/greed cycles and trading opportunities.
🎯 Core Features
Five-Factor Fear & Greed Score
Weighted sentiment analysis:
Demand/Supply (25%): Real-time buying/selling pressure
RSI (25%): Momentum extremes
KDJ (20%): Overbought/oversold detection
Bollinger Band % (20%): Statistical positioning
ADX Trend (10%): Trend strength confirmation
Multi-Layer Market State Detection
Extreme Fear/Greed: Statistical bubble identification
Trend Bias: Bullish/Bearish/Neutral classification
Confidence Scoring: Setup reliability assessment
Reversal Alerts: Early trend change signals
Visual Dashboard
Top-right information panel displays:
Fear & Greed Score (0-100)
Market State Classification
Trend Bias & Confidence
Signal Quality & Alerts
📈 Key Components
Fear & Greed Gauge
0-30: Extreme Fear (buying opportunities)
30-47: Fear (accumulation zones)
47-70: Neutral (consolidation)
70-90: Greed (caution zones)
90-100: Extreme Greed (selling opportunities)
Deviation Zones
Red Zone (±17.065): Critical reversal areas
Yellow Zone (±34.135): Warning levels
Blue Zone (±47.72): Statistical extremes where reversals are highly likely. These occur when asset prices are in a bubble that's about to pop.
Signal Types
Buy/Sell Labels: Primary entry/exit signals
Scalp Signals: Short-term opportunities
Bottom/Top Detectors: Extreme reversal zones
Whale Indicators: Institutional activity markers
🚀 Trading Applications
Extreme Fear Setups Conditions:
Fear & Greed Score < 34.135
BB% < 0 or < J-inverted line
RSI < 34.135
Confidence score > 68%
Bullish divergence present
Action: Accumulation positions, scaled entries
Extreme Greed Setup Conditions:
Fear & Greed Score > 68.2
BB% > 100 or > 80 with divergence
RSI > 68.2
ADX showing trend exhaustion
Multiple timeframe resistance
Action: Profit-taking, protective stops
Trend Following
Bullish Conditions:
Sentiment score rising from fear zones
DMI+ above DMI- and rising
Confidence > 75%
Volume supporting moves
Bearish Conditions:
Sentiment declining from greed zones
DMI- above DMI+ and rising
Distribution patterns
Multiple resistance failures
⚙️ Customization Options
Adjustable Parameters:
DMI Settings: DI lengths, ADX smoothing
KDJ Periods: Customizable sensitivity
BB% Range: Statistical band adjustments
Smoothing Options: Demand/Supply filtering
Alert Thresholds: Custom signal levels
Visual Customization:
Color schemes for different market states
Line thickness and style preferences
Information panel display options
Alert sound/visual preferences
📊 Signal Interpretation
Primary Signals:
Green 'B': Strong buy opportunity
Red 'S': Strong sell opportunity
White 'Scalp': Short-term trade
Trade Area: Accumulation/distribution zones
Visual Markers:
🔥: Bullish momentum building
🐻: Bear exhaustion building
🐳: Whale/institutional activity
Color-coded fills: Market state visualization
Confidence Levels:
≥80%: High reliability setups
60-79%: Moderate confidence
<60%: Low confidence, avoid or reduce size
⚠️ Risk Management Guidelines
Critical Rules:
Never trade against extreme sentiment (Extreme Fear → buy, Extreme Greed → sell)
Require multiple confirmation signals
Use confidence scores for position sizing
Avoid When:
Conflicting signals between components
Low volume participation
Confidence score < 50%
Major news events pending
Extreme volatility conditions
💡 Advanced Strategies
Sentiment Cycle Trading
Identify sentiment extremes
Wait for confirmation reversals
Enter with trend confirmation
Exit at opposite sentiment extreme
Use confidence scores and fear & greed scores to scale:
Fear & greed scores < 30 = buy area
Fear & greed score > 60 = sell area
Trend Momentum
Exit: At extreme greed with divergence
Enter: At extreme fear with divergence
📊 Market State Classification
Five Primary States:
EXTREME FEAR (BB% <0, RSI <34, Score <34)
FEAR (Score 34-47, bearish momentum)
NEUTRAL (Score 47-70, consolidation)
GREED (Score 70-90, bullish momentum)
EXTREME GREED (Score >90, BB% >100)
State Transitions:
Fear → Neutral: Early accumulation
Neutral → Greed: Trend development
Greed → Extreme Greed: Distribution
Extreme → Reversal: Trend change
🔍 Information Panel Guide
Real-Time Metrics:
FEAR & GREED: Current sentiment score
Market State: Classification and bias
Trend Bias: Bullish/Bearish/Neutral
Confidence: Setup reliability percentage
Momentum: Current directional strength
Volatility: Market condition assessment
Signal Quality: Trade recommendation
Reversal Imminent: Early warning alerts
🌟 Unique Advantages
Psychological Edge:
Quantifies market emotion through multiple indicators
Identifies bubbles before they pop
Provides statistical confidence for each setup
Combines technical extremes with sentiment analysis
Offers clear visual cues for decision making
Professional Features:
Multi-timeframe sentiment analysis
Real-time confidence scoring
Comprehensive alert system
Institutional activity detection
Clear risk/reward visualization
📚 Educational Value
This indicator teaches:
Market psychology cycles
Statistical extreme identification
Multi-indicator confirmation
Risk quantification methods
Professional trade management
Perfect for traders seeking to understand and profit from market sentiment cycles.
Disclaimer: For educational purposes. Trading involves risk. Past performance doesn't guarantee future results.
Linear Regression Market State IndexStandard Deviation Market Structure Indicator
A Comprehensive Multi-Timeframe Market Analysis Tool
🎯 Overview
The Standard Deviation Market Structure (SDMS) indicator is a sophisticated technical analysis tool that integrates multiple proven methodologies to identify market structure, trend direction, and potential reversal zones. By combining price action, statistical analysis, and momentum indicators across multiple timeframes, SDMS provides traders with a comprehensive view of market dynamics.
✨ Key Features
Multi-Timeframe Integration
Primary analysis on current timeframe
1-hour statistical confirmation for support/resistance levels
Order block extension across 500 future bars
Comprehensive Technical Suite
RSI with Deviation Analysis
Dynamic Order Block Detection
Gaussian Filter Channels
Linear Regression with Statistical Bands
Standard deviation to detect price outliers
Directional Movement Index (DMI/ADX)
Bollinger Band % Analysis
Support/Resistance Line System
Visual Clarity
Color-coded signals and zones
Automatic level management
Clean, intuitive display
📊 Core Components Explained
1. Order Block System
What Are Order Blocks?
Order blocks are price zones where institutional activity has occurred, creating future support or resistance levels. SDMS automatically detects these critical zones.
Detection Logic:
Bullish Order Blocks: Form when price breaks above recent highs following bearish candles
Bearish Order Blocks: Form when price breaks below recent lows following bullish candles
Visual Identification:
Green boxes with "BuOB" labels (support zones)
Red boxes with "BeOB" labels (resistance zones)
Each block shows its boundary price for easy reference
Dynamic Management:
Automatically extends 300 bars into the future
Self-cleaning: removes blocks when price breaches their boundaries
Real-time adjustment to changing market structure
2. Statistical Support/Resistance System
How It Works:
SDMS creates support and resistance lines based on statistical extremes confirmed on the 1-hour timeframe.
Trigger Conditions:
Support Lines (Green): Trigger when 1H Bollinger Band % crosses above 0 and bearish momentum subsides.
Resistance Lines (Red): Trigger when 1H Bollinger Band % crosses below 1 and bullish momentum subsides
The Science Behind BB%:
BB% = (Price - Lower Band) / (Upper Band - Lower Band)
BB% <= 0: Price at statistical oversold extreme; also indicated by white candles.
BB% > 1: Price at statistical overbought extreme; also indicated by white candles.
Line Management:
Maximum of 15 active lines
Oldest lines automatically removed
Lines extend across chart for ongoing reference
3. Trend Analysis Suite
Hull Moving Average (HMA):
55-period smoothed trend indicator
Color-coded: Green = bullish, Red = bearish
Visual band shows trend acceleration/deceleration
Gaussian Channel:
Advanced filtering of market noise
Dynamic channel based on true range volatility
Helps identify mean reversion opportunities
Form a yellow band when price is overbought or oversold zones.
Linear Regression System:
Statistical price modeling
Multiple standard deviation bands (up to 3SD)
Regression-based candlestick visualization
Candles turn white when in overbought zones. Yellow candles indicate extremely overbought zones. Blue candles indicate a bullish trend with high volume.
Bearish candles are bluish-purple when volume is high and red when the volume is within normal ranges or low.
4. Momentum & Oscillator Integration
RSI with Deviation Tracking:
21-period RSI with 30-period smoothing
Tracks deviation from moving average based off linear regression
Identifies momentum divergences
Directional Movement Index:
Multi-period DMI/ADX analysis
Used to detect overbought and oversold zones within the indicator calculations.
Combines with RSI for enhanced signals
Momentum confirmation for all entries/exits
🎯 Trading Signals & Alerts
Buy Signals (Yellow "Buy" Labels)
Multi-Condition Confirmation Required:
RSI Oversold Reversal: RSI crosses above 30
Trend Alignment: HMA showing bullish structure
Momentum Confirmation: DMI alignment
Statistical Support: Price at or near support zones
Risk Management: Multiple confirming indicators
Strong Buy Conditions:
Confluence of order block support + BB% support line
Multiple timeframe alignment
Volume confirmation at key levels
Sell Signals (Red/Yellow "Sell" Labels)
Multi-Condition Confirmation Required:
RSI Overbought Reversal: RSI crosses below 70
Trend Exhaustion: HMA showing bearish structure
Momentum Divergence: DMI bearish alignment
Statistical Resistance: Price at or near resistance zones
Timeframe Confirmation: 1H BB% bearish signals
Strong Sell Conditions:
Confluence of order block resistance + BB% resistance line
Multiple timeframe distribution
Volume surge at resistance
Additional Alerts
RSI Divergence Signals: Triangles showing momentum shifts
Extreme Price Alerts: Circles at statistical extremes
Structure Breaks: Visual cues for order block violations
🎨 Visual System Guide
Color Coding System
Green: Bullish conditions, support zones, rising trends
Red: Bearish conditions, resistance zones, falling trends
Blue: Statistical channels, neutral zones
Yellow: Alert conditions, extreme signals
White: Transition zones, neutral signals
Zone Identification
Buying Pressure Zones: Green/blue tinted areas below price or white candles with white dots within the moving average center line
Selling Pressure Zones: Red tinted areas above price with white dots within the moving average center line
Standard Deviation Zones: Gradient colors showing statistical extremes
⚙️ Customization Options
Adjustable Parameters
RSI Settings: Period, oversold/overbought levels, sensitivity
Order Block Detection: Lookback period, ATR multiplier, extension
Statistical Settings: Gaussian filter poles, regression periods
Support/Resistance: Maximum lines, BB% settings
Visual Preferences: Colors, band displays, alert styles
Input Groups
RSI Trading Strategy
Order Block Configuration
Gaussian Channel Settings
Linear Regression Parameters
DMI/ADX Configuration
Bollinger Band % Settings
📈 Practical Trading Applications
For Swing Traders
Identify Key Levels: Use order blocks + BB% lines for entry/exit planning
Trend Confirmation: HMA + Gaussian channel for trend direction
Risk Management: Standard deviation bands for stop placement
Timing Entries: RSI/DMI alignment for optimal entry timing
For Day Traders
Intraday Levels: Order blocks provide immediate S/R for day trading
Momentum Signals: Real-time RSI/DMI signals for quick moves
Statistical Edges: Gaussian channel for mean reversion plays
Breakout Confirmation: Order block breaks with volume
For Position Traders
Higher Timeframe Structure: 1H BB% lines for major levels
Trend Persistence: HMA for long-term trend identification
Accumulation/Distribution Zones: Order blocks show institutional activity
Multi-Timeframe Alignment: Confirmation across timeframes
🔍 How to Use SDMS Effectively
Step 1: Market Structure Assessment
Identify active order blocks (green/red boxes)
Note BB% support/resistance lines (horizontal lines)
Assess HMA and moving average trend direction (color)
Check Gaussian channel position (preferably outside 2SD)
Step 2: Signal Confirmation
Wait for multiple indicator alignment
look for doji candles.
Confirm with green (bullish) or red (bearish) candles
Confirm with volume if available
Check for confluence of levels
Assess risk/reward based on nearby levels
Step 3: Trade Management
Enter at confirmed support/resistance
Place stops beyond opposite levels
Take profits at next statistical level
Monitor for structure changes
Step 4: Risk Management
Use standard deviation bands for volatility assessment
Never risk more than 1-2% per trade
Adjust position size based on confluence strength
Have predefined exit rules
💡 Advanced Strategies
Strategy 1: Confluence Trading
Setup: Order block + BB% line at same level
Entry: Price tests confluence zone with RSI signal
Stop: Beyond the confluence zone
Target: Next statistical level
Strategy 2: Breakout Trading
Setup: Price approaching order block boundary
Entry: Break with volume + RSI/DMI confirmation
Stop: Re-entry into order block
Target: Next BB% line extension
Strategy 3: Mean Reversion
Setup: Price at Gaussian channel extremes
Entry: RSI reversal signal at channel boundary
Stop: Beyond channel extreme
Target: Channel midline or opposite boundary
⚠️ Important Considerations
Best Market Conditions
Trending Markets: Excellent performance in clear trends
Breakout Scenarios: Strong identification of break levels
Range Markets: Works well with defined ranges
Limitations
Choppy Markets: May give false signals in consolidation
News Events: Fundamental shocks can override technical levels
Timeframe Specific: Optimal on 15-minute to daily charts
Risk Management Rules
Always use stops
Never rely on single signals
Consider market context
Adjust for volatility changes
Keep position sizes consistent
🔧 Technical Specifications
Maximum Lines: 500
Maximum Bars Back: 1000
Maximum Boxes: 500
Calculation Efficiency: Optimized for real-time use
🏆 Why SDMS Stands Out
Unique Advantages
Integrated Approach: Combines multiple methodologies into one tool
Self-Adjusting: Automatically adapts to market changes
Multi-Timeframe: Provides both immediate and higher timeframe context
Visual Clarity: Clean, intuitive display of complex data
Professional Grade: Institutional-level analysis accessible to all traders
Educational Value: Learn how different indicators interact
Understand market structure development
See institutional order flow patterns
Develop disciplined trading habits
📚 Learning Resources
Recommended Study Approach
Start Simple: Focus on order blocks and BB% lines first
Add Complexity: Gradually incorporate other indicators
Paper Trade: Practice without risk
Keep Journal: Document setups and outcomes
Review Regularly: Analyze both wins and losses
Common Pitfalls to Avoid
Overtrading: Wait for high-quality setups
Ignoring Context: Consider overall market conditions
Chasing Signals: Enter at planned levels, not after moves
Risk Mismanagement: Always know your risk before entering
Confirmation Bias: Be objective about signals
🤝 Community & Support
Getting the Most from SDMS
Start with Defaults: Use default settings initially
Adjust Gradually: Make small changes as you understand the tool
Combine with Fundamentals: Use for timing within fundamental context
Stay Disciplined: Follow your trading plan consistently
Continuous Improvement
SDMS is designed for continuous learning. As you use the indicator, you'll develop insights into:
Market microstructure
Institutional trading patterns
Statistical edge identification
Risk management optimization
Risk management is more important than signal accuracy
Patience is required for high-quality setups
Success Factors
Discipline: Following your plan consistently
Patience: Waiting for proper setups
Risk Management: Protecting your capital
Continuous Learning: Improving your skills over time
🌟 Final Thoughts
The Standard Deviation Market Structure indicator represents a sophisticated approach to technical analysis, combining the best elements of price action, statistical analysis, and momentum indicators. While powerful, remember that no indicator guarantees success. SDMS is a tool – your skill, discipline, and risk management determine your trading results.
Use SDMS as part of a comprehensive trading plan, combine it with proper risk management, and continue developing your trading skills. The markets are always teaching – stay humble, stay disciplined, and trade well.
Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Trading involves risk of loss. Always consult with a qualified financial professional before making investment decisions.
SMC + Dual UT Bot buy and sell AlertsMise a jour avec un EMA 20/50 et vwap
his script is a composite indicator for TradingView (Pine Script v5) that merges Smart Money Concepts (SMC) with a Dual-instance UT Bot. It has been styled with a high-contrast "Neon Cyberpunk" theme (Cyan/Pink) and is fully compliant with the CC BY-NC-SA 4.0 license.
Here is a breakdown of its two main components:
1. Smart Money Concepts (SMC)
This portion, originally by LuxAlgo, is designed to identify institutional price levels and structural market shifts. It provides a detailed map of market structure rather than simple entry/exit signals.
Market Structure (BOS & CHoCH):
BOS (Break of Structure): Marks trend continuation (e.g., breaking a higher high in an uptrend).
CHoCH (Change of Character): Marks potential trend reversals (e.g., the first time a higher low is broken in an uptrend).
Order Blocks (OB):
Highlights specific candles where institutional buying or selling likely occurred. These act as high-probability support/resistance zones.
Neon Blue/Cyan for Bullish OBs.
Neon Pink for Bearish OBs.
Fair Value Gaps (FVG):
Identifies imbalances (gaps) in price action where the market often returns to "fill" orders.
Neon Mint for Bullish FVGs.
Neon Red for Bearish FVGs.
Premium/Discount Zones: Automatically plots the range equilibrium (50% level) to help you buy in "Discount" (low) and sell in "Premium" (high) areas.
Liquidity (EQH/EQL): Automatically detects "Equal Highs" and "Equal Lows," which are magnets for price as they represent liquidity pools (stop losses).
2. Dual UT Bot Alerts
This portion provides the actual Entry Signals. It runs two separate instances of the "UT Bot" strategy simultaneously with different sensitivity settings to filter noise.
Instance 1 (Buy Only):
Settings: Key Value = 4, ATR Period = 10 (Faster, more sensitive).
Visual: Plots a Neon Cyan "Buy" label.
Function: Looks for bullish reversals earlier to catch the start of a move.
Instance 2 (Sell Only):
Settings: Key Value = 7, ATR Period = 20 (Slower, smoother).
Visual: Plots a Neon Pink "Sell" label.
Function: Uses a wider ATR band to avoid getting shaken out of shorts too early, focusing on major downtrends.
How to Use It
The strength of this script is confluence.
Wait for a Signal: Look for a UT Bot "Buy" or "Sell" tag.
Confirm with SMC: Check if the signal aligns with SMC concepts.
Example Buy: Did the UT Bot give a "Buy" signal while price was bouncing off a Bullish Order Block?
Example Buy: Did price just sweep Liquidity (EQL) before the Buy signal?
Example Sell: Is the "Sell" signal happening inside a Premium Zone or a Bearish Fair Value Gap?
avant-hier
Notes de version
1. "Pro" Badge Buy/Sell Labels
The standard text signals have been replaced with modern, professional Badge Labels that provide more information at a glance.
Visuals: Instead of simple text, the script now uses label.new to create high-visibility badges.
BUY: A Neon Cyan badge with a Rocket icon (🚀).
SELL: A Neon Pink badge with a Chart icon (📉).
Price Details: Each badge displays the exact Entry Price directly on the label.
Tooltips: If you hover your mouse over a Buy or Sell badge, a tooltip will appear showing the exact Take Profit (TP) and Stop Loss (SL) prices calculated for that trade.
2. Dynamic Take Profit (TP)
The script now automatically calculates a profit target for every trade the moment a signal is generated.
Calculation: It measures the distance between your Entry Price and the initial Stop Loss (the ATR Trailing Stop).
Risk:Reward: It multiplies that distance by your chosen Risk:Reward Ratio (default is 1.5) to project a TP target.
Visual Line: A Green Line is drawn on the chart at the TP level. It remains active until price hits it or the stop loss.
3. Active Trailing Stop Loss (SL)
The Stop Loss is no longer static; it is now "alive" and manages the trade for you.
Trailing Logic: If Use Trailing SL? is enabled (default), the SL line will automatically move up (for longs) or move down (for shorts) as the trend continues in your favor. It locks in profit by following the UT Bot's ATR trailing band.
Visual Line: A Red Line is drawn at the SL level. You can see it physically step up or down on the chart as the trend progresses.
4. Real-Time Trade Simulation
The script now simulates the lifecycle of a trade directly on the chart:
Active State: When a trade is live, the TP and SL lines extend to the right of the current candle (bar_index + 1), showing you exactly where your exit points are in real-time.
Closed State: Once the price hits either the Green TP line or the Red SL line, the script detects the "Exit." The lines stop extending and turn dotted, indicating that the trade is closed and waiting for the next signal.
Summary of New Settings
You will find a new group in the settings panel called "UT Bot: Trade Management":
TP Risk:Reward Ratio: Adjust this to change how far the Green TP line is placed (e.g., set to 2.0 for 2x return).
Use Trailing SL?: Uncheck this if you want the Red SL line to stay fixed at the initial entry risk level.
avant-hier
Notes de version
1. Live Strategy Performance Dashboard (Backtester)
Since this is an indicator, TradingView does not automatically calculate PnL (Profit and Loss). I have built a custom Simulation Engine inside the script that tracks every UT Bot signal as if you had taken the trade.
Location: Bottom Right of your chart.
Win Rate: Displays the percentage of trades that hit the Take Profit target versus the Stop Loss.
Trades (W/L): Shows the total number of signals generated, broken down by Wins and Losses.
Net Profit (R): Calculates your theoretical profit in "R-Multiples" (Risk Units).
Example: If you set your Risk:Reward to 2.0, every win adds +2R, and every loss subtracts -1R.
Dynamic Colors: The Win Rate and Profit cells turn Neon Cyan if positive (>50% or >0R) and Neon Pink if negative.
2. Multi-Timeframe Trend Dashboard
A new panel at the Top Right gives you an instant "Market Bias" reading so you don't have to scan the whole chart.
SMC Trend: Reads the Smart Money structure (Break of Structure/Change of Character) to determine if the high-level timeframe is BULLISH or BEARISH.
UT Bot Status: Displays the current active signal state:
BUY (Active): You are currently in a Long trade.
SELL (Active): You are currently in a Short trade.
NEUTRAL: No active signal or the last trade hit TP/SL.
3. Integrated Alert System
I have connected the visual lines to the alert system. You can now set a single alert on this indicator, and it will trigger for:
Entry Signals: "UT Long Entry" / "UT Short Entry"
Exits: "Take Profit Hit" / "Stop Loss Hit"
4. Consolidated Settings
To make the script easier to manage, I organized the settings into clear groups:
Dashboards: Toggle the visibility of the new panels or move the Performance Panel to a different corner.
UT Bot: Trade Management: Quickly adjust your Risk:Reward Ratio (e.g., change from 1.5 to 2.0) to see how it affects your Win Rate in real-time on the dashboard.
avant-hier
Notes de version
1. Multi-Timeframe (MTF) Trend Scanner
I have replaced the basic "Market Bias" panel with a comprehensive MTF Trend Dashboard located at the Top Right of your chart.
What it tracks: It simultaneously monitors the trend direction on 5 distinct timeframes:
15 Minute
1 Hour
4 Hour
Daily
Weekly
How it works: It runs a background calculation (using UT Bot settings Key=5, ATR=15) on these higher timeframes without you needing to switch charts.
Visuals:
BULLISH: Highlighted in Neon Cyan.
BEARISH: Highlighted in Neon Pink.
2. Strategic Confluence (How to use it)
This new dashboard transforms the script from a simple "signal generator" into a complete trading system by allowing you to filter trades based on the bigger picture.
The "All-Green" Rule: If you are scalping on a 5-minute chart and you get a BUY signal, check the dashboard. If the 1H, 4H, and Daily are all Neon Cyan (Bullish), that trade has a significantly higher probability of success.
Avoid Counter-Trend Trades: If your main chart says BUY, but the dashboard shows the 4H and Daily are Neon Pink (Bearish), you are trading against the major trend. You might want to skip that trade or reduce your risk size.
3. Summary of Dashboards
You now have two professional-grade panels on your screen:
Bottom Right (Performance): Shows the past results of the strategy on your current timeframe (Win Rate, Profit Factor).
Top Right (Trend): Shows the current state of the market across all timeframes.
Mi script📝 DESCRIPTION
This indicator is based on the WaveTrend oscillator, designed as a momentum and timing filter, not as an automatic trading system.
The logic is simple and disciplined:
📊 Mid-range zone → no trades
🔴 Upper zones → look for short opportunities only with confluence
🟢 Lower zones → look for long opportunities only with confluence
WaveTrend cross signals are used only as confirmation, never as standalone entries.
Features included:
Main WaveTrend line + signal line
Clear overbought and oversold zones
Optional histogram
Candle coloring for quick market reading
Customizable alerts
This indicator is intended to be combined with:
RSI
Stochastic
Market structure
Support and resistance levels
⚠️ Not financial advice.
For educational purposes only. Use at your own risk
P/E, EPS, Price & Price-to-Sales DisplayThis indicator displays key fundamental valuation metrics for the selected stock.
It shows:
Earnings Per Share (EPS)
Price-to-Earnings (P/E) ratio
Calculated theoretical price based on P/E × EPS
Price-to-Sales (P/S) ratio
These values help traders quickly assess valuation without switching to separate financial panels.
🛠 Instructions for Use
Add the indicator to your chart.
Click on the three dots (⋯) next to the indicator name.
Select Move to → New pane above.
Minimize the indicator pane to display only the numerical values.
Hide the plotted lines if you want a clean, numbers-only view.
This setup allows you to monitor fundamental metrics efficiently without cluttering the price chart.
COT Commercials Base vs Quote Strength (Dynamic)This indicator measures and compares Commercial (Smart Money) positions of the Base and Quote currencies in a Forex pair, displaying their relative strength as a smooth, dynamic line.
It calculates a 0–100 strength index:
100 → Base Commercials are strongly dominant (bullish for the pair)
50 → Neutral, no clear dominance
0 → Quote Commercials are strongly dominant (bearish for the pair)
Unlike traditional binary COT signals, this indicator shows continuous changes in positioning. Small shifts in Commercial activity slightly move the line, while larger imbalances push it toward the extremes.
This makes it ideal for:
Identifying trend strength and market bias
Spotting early reversals and divergences
Confirming breakouts or trend continuation
Understanding the relative influence of Smart Money in Forex markets
It provides a clear, real-time view of which currency in a pair is favored by Commercial traders, giving a professional edge in market analysis.
Sultan Gold Levels (SMC, Sessions & Structure)This indicator is a comprehensive "Smart Money Concepts" (SMC) and Market Structure suite designed to declutter charts by combining multiple technical analysis tools into a single, cohesive overlay.
Instead of using separate indicators for Sessions, Market Structure, and Fibonacci levels, this script integrates them to help traders identify "Confluence" areas—specifically where structural levels align with session opens or psychological price points.
█ HOW IT WORKS & CALCULATIONS
1. Market Structure (BOS / CHoCH):
The script utilizes a Pivot High/Low algorithm (user-defined length, default 5) to identify structural points (HH, LL, LH, HL).
- Break of Structure (BOS): Triggered when price closes beyond a previous pivot. The script includes a "Real vs. Fake" validation filter.
- Validation Logic: A "Real" BOS requires the candle body to close past the level with specific volume and displacement thresholds (ATR based). Wicks piercing a level are marked as "Fake" or weak breaks.
2. Order Blocks (OB) & FVG:
- Order Blocks are identified by analyzing the last opposing candle before a significant move that breaks structure. The script filters these based on a volume/ATR strength multiplier to ensure only significant institutional candles are highlighted.
- Mitigation: The script automatically removes Order Blocks once price has revisited (mitigated) them, keeping the chart clean.
3. Session Ranges:
The script tracks and plots the Highs and Lows of major trading sessions (Asian, London, New York).
- Logic: It uses `time()` functions to capture the highest and lowest points during specific UTC hours. These levels often act as liquidity pools for the subsequent session.
4. Fibonacci & Liquidity:
- Auto-Fibonacci: Automatically anchors to the most recent significant swing high/low sequence to project retracement levels (specifically the 50% and 61.8% "Golden Pocket").
- Liquidity: Detects "Equal Highs" (EQH) and "Equal Lows" (EQL) by comparing adjacent pivot points within a percentage threshold (0.15% default), highlighting areas where stop-losses may reside.
█ FEATURES
- Multi-Timeframe Dashboard: Displays trend bias (D1, H4, H1) and current session status.
- Previous Day/Week/Month Levels: Auto-plots PDH/PDL, PWH/PWL as static support/resistance lines.
- Psychological Levels: Auto-plots round numbers (e.g., xx00, xx50).
- Customizable Alerts: Alerts for BOS, OB formation, and level touches.
█ SETTINGS
- Structure Length: Adjusts the sensitivity of the pivot detection.
- Session Times: Fully customizable time inputs for Asia/London/NY.
- Styling: Toggle specific elements (like Sessions or FVGs) on/off to suit your trading style.
█ CREDITS
This script utilizes standard Smart Money Concept theories widely discussed in the technical analysis community. The pivot detection logic is based on standard high/low comparisons common in Pine Script open-source libraries.
FVG Nexus IFVG Break FrameworkThis strategy implements an IFVG (Inverted Fair Value Gap) framework using a structured multi-timeframe approach.
Concept:
The script identifies Fair Value Gaps (FVGs) on a higher timeframe (HTF) to define market context. Instead of trading the initial FVG reaction, it waits for a confirmed invalidation of that HTF gap. Only after this invalidation occurs does the strategy search for a confirming Fair Value Gap on the lower timeframe (LTF) in the direction of the break.
This creates a two-step logic:
1) Detect HTF Fair Value Gap and wait for price to interact with it.
2) After invalidation of the HTF zone, enter only on a newly formed LTF Fair Value Gap aligned with the break direction.
Key Characteristics:
– Invalidation-based logic (IFVG), not standard FVG continuation
– Strict multi-timeframe structure (HTF context, LTF execution)
– Rule-based entries and exits without discretionary input
– Designed for backtesting, alerts, and automated execution
– Optional session filtering and risk-controlled trade management
How to Use:
Apply the strategy on the lower timeframe specified in the settings. Select a higher timeframe for contextual structure. Trades are only triggered after a confirmed HTF invalidation followed by a valid LTF Fair Value Gap.
This script is intended as a structured trading methodology for studying market behavior and systematic execution. It does not provide financial advice.
[MetaMasters] COT INDEXThe COT Index converts the weekly net positions of Commercial traders into a normalized, cycle-based mathematical model.
Rather than showing raw net positioning, the COT Index applies a cyclical normalization algorithm—most commonly over 26 weeks, with 52 weeks as an alternative. This process highlights bullish and bearish extremes in Commercial behavior more clearly. The resulting index is displayed as a color-coded line:
• Green Zone – Commercials classified as bullish.
Historically, strong Commercial buying activity often coincides with upward market pressure.
• Red Zone – Commercials classified as bearish.
This typically reflects increased downside pressure in the underlying market.
• Neutral Zone – No clear directional bias; positioning sits in the mid-range.
Because COT data is updated only once per week and the index is derived from multi-week cyclical analysis, the indicator is designed strictly for the weekly timeframe. Lower timeframes do not align with the structure or cadence of the underlying data.
The chosen cycle length (commonly 26 or 52 weeks) determines how net positions are compared and normalized, influencing how quickly the index reaches its extreme zones.
Overall, the COT Index offers an objective, systematic way to interpret Commercial trader sentiment and identify potential directional bias in the market.
[MetaMasters] Asset Value Comparisson OscillatorThe Asset Value Comparison Oscillator evaluates the currently opened asset against a user-selected reference symbol to highlight periods of relative overvaluation or undervaluation.
Its logic follows the principle that markets continually gravitate toward fair value. When an asset strays too far from a meaningful benchmark, it typically reverts toward equilibrium. This indicator captures that relationship and converts it into a clear, visual oscillator:
• Green Zone (Undervalued) – Indicates the asset is priced lower than the reference symbol.
This suggests potential upward pressure as markets often correct undervalued conditions.
• Red Zone (Overvalued) – Indicates the asset is priced higher than the reference symbol.
This may signal increased chances of a downward move as the asset seeks balance.
Users can assign any reference instrument—commodities, indices, currency pairs, or other assets. The oscillator measures valuation gaps using a configurable cycle length; a Cycle setting of 10 is recommended for balanced and responsive signals.
Because the indicator reflects broader valuation behavior, it is intended exclusively for the daily timeframe, as lower intervals may fail to capture meaningful fundamental relationships.
Overall, the Asset Value Comparison Oscillator helps traders spot when an asset appears cheap or expensive relative to another, adding a layer of fundamental insight to strengthen directional trading decisions.
[MetaMasters] SeasonalityThe Seasonality Indicator evaluates the average historical performance of the selected asset by analyzing a user-defined number of past years (for example, the last 10).
You can adjust the number of years included in the calculation directly from the settings panel.
Using this historical window, the indicator generates an average seasonal curve that reflects how the market has typically behaved throughout each part of the year. This curve serves as a forward-looking guide, highlighting periods in which the market has historically shown consistent tendencies.
Traders can use this seasonal projection to pinpoint time periods with a higher statistical likelihood of upward or downward movement.
The indicator is especially effective when paired with the Seasonality Analysis Tool, which helps identify specific historical windows and further strengthens seasonal decision-making.
This indicator is designed exclusively for the daily timeframe, as all calculations rely on daily candle data. Other timeframes will not produce accurate seasonal structures.
Overall, the Seasonality Indicator offers a clear, data-driven view of recurring annual patterns, helping traders understand when historical tendencies may influence future price action.
SYNTAX 1.1SYNTAX is a precision-built trading indicator focused on clarity, structure, and consistency. It delivers clean chart visuals, predefined trade levels, and objective guidance that minimizes emotional interference. Designed for traders who value discipline over noise, SYNTAX helps streamline execution, reduce chart clutter, and support confident decision-making across varying market conditions.
MW Futures Liquidity ScalperMW Futures Liquidity Scalper - ICT-Inspired Algorithmic Trading
A comprehensive ICT (Inner Circle Trader) inspired strategy that automates liquidity pool detection, fair value gap (FVG) analysis, and precision entries for futures and forex markets. This strategy implements institutional trading concepts with customizable filters, multi-timeframe confirmation, and complete risk management.
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🎯 What This Strategy Does
This strategy scans the market for areas where stop losses cluster (liquidity pools), identifies price imbalances (FVGs), and places precision entries when conditions align. It automates the "liquidity hunt" concept: tracking where institutions sweep stops before price reverses.
The key principle: Time first, then price. Configure when to trade, which liquidity to target, and how to enter - the strategy handles the rest.
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📊 How The Algorithm Works
Step 1 - Liquidity Mapping: Calculates session highs (buy-side liquidity/BSL) and lows (sell-side liquidity/SSL) at your chosen intervals
Step 2 - Bias Detection: More BSL than SSL = bearish bias. More SSL than BSL = bullish bias
Step 3 - FVG Search: Finds the first valid Fair Value Gap matching your size requirements and current bias
Step 4 - Filter Check: Validates all enabled filters (EMA, NWOG/NDOG, orderflow, correlation, macro time)
Step 5 - Entry Placement: Places limit order at FVG boundary with configured slippage
Step 6 - Exit Management: Sets take profits at opposing liquidity pools, manages trailing stops and breakeven
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🔑 Core Concepts Explained
Liquidity Pools
Areas where stop losses cluster - above swing highs (BSL/blue lines) or below swing lows (SSL/red lines). Institutions often sweep these zones before reversing. Darker colors indicate pools that have been purged.
Fair Value Gaps (FVGs)
Price imbalances from aggressive moves where 3-candle wicks don't overlap. These act as entry zones. Green = bullish, Red = bearish, Blue = invalid/neutral.
First Presentation
The first FVG after session start (Asia 18:30, London 00:30, NY AM 09:30, NY PM 13:30 NY time). Used until the next session begins.
2022 Model
Only searches for FVGs after a liquidity pool is purged. Loops backward from the sweep to find the enabling FVG - often used for IFVG (Inverse FVG) trades.
Volume Imbalance
When candle bodies don't touch within an FVG, extends the FVG boundaries for more precise entries.
Premium/Discount
Above 50% of a range = premium (favorable for shorts). Below 50% = discount (favorable for longs).
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⚙️ Key Features
Liquidity Detection
• Configurable calculation intervals: 15-minute, 30-minute, or hourly
• Optional AM Opening Range (09:30-10:00 NY)
• Daily reset at 18:00 NY time
• Visual tracking of BSL (blue) and SSL (red) levels
FVG Analysis
• Minimum/maximum FVG size filters (handles)
• Skip invalid FVGs to find next valid one
• Volume imbalance integration
• Four session-based first presentation options
• 2022 Model for post-purge entries
Orderflow Filters
• Short-Term (STH/STL) - 3-candle swings (yellow)
• Intermediate-Term (ITH/ITL) - higher-degree swings (purple)
• Long-Term (LTH/LTL) - major swing structure (green)
• Premium/discount zones for each level
• Automatic bias shift when levels are taken
Direction Filters
• NDOG: New Day Opening Gap - gap between 16:59 and 18:00
• NWOG: New Week Opening Gap - Friday close to Sunday open
• EMA Filters: 9/18 EMA crossovers on daily, weekly, or custom timeframes
• Macro Time: Trade only during xx:50 to xx:10 windows
• Midnight Filter: Use 00:00 NY close as bias reference
Correlation Filters
• Compare with any ticker using 9/18 EMA
• Positive correlation: both must align
• Negative correlation: must be opposite (e.g., NQ long when DXY short)
• Available on weekly, daily, and custom timeframes
Risk Management
• Three stoploss placement methods (FVG boundary, 2nd candle, 1st candle)
• Configurable min/max stoploss sizes
• Trailing stoploss (close-based or high/low)
• Auto-breakeven after first TP with handle offset
• Option to skip breakeven during avoidance times
Position Sizing
• Topstep 50k/100k/150k presets with proper limits
• AMP Live margin-based sizing
• Custom daily loss, drawdown, and contract limits
• Max risk per trade with automatic contract scaling
Entry Precision
• Entry slippage: positive = outside FVG, negative = inside FVG
• Close above/below requirement before entry
• 75% body closure filter to avoid wick-driven signals
Exit Management
• Take profits at opposing liquidity pools
• Runner contracts for extended trends
• TP clustering to merge nearby targets
• Max trades per hour limiter
Time Controls
• Configurable timezone (9 major zones)
• Liquidity search windows
• Trading hours restrictions
• Day-specific avoidance times
• Close all positions time
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📋 Building Your Model (Step-by-Step)
1. Define Time: When do you want to trade? (NY open 09:30-11:30 recommended)
2. Choose Liquidity: 15-minute, 30-minute, hourly, or AM opening range
3. Select FVG Method: First presentation, timed intervals, or 2022 model
4. Set Entry Rules: Slippage, close confirmation, body filter
5. Configure Stoploss: Placement method, min/max sizes, trailing
6. Add Orderflow: STH/STL, ITH/ITL, LTH/LTL with premium/discount
7. Apply Direction Filters: EMA, NWOG/NDOG, macro, correlation
8. Set Profit Targets: Min distance, max TP, runners, clustering
Tip: Start simple with steps 1-3, then optimize incrementally. Don't enable all filters at once.
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📁 Settings Groups
Time Settings - Trading Periods: Timezone, start date, liquidity windows, trading hours
Liquidity Settings: Calculation intervals, AM opening range
FVG Settings: Size filters, first presentation, 2022 model, volume imbalance
Entry Settings: Slippage, close confirmation, body filter
Stoploss Settings: Placement, min/max, trailing, alerts
Breakeven Settings: Amount, trigger conditions, avoidance time behavior
Orderflow Filters: STH/STL, ITH/ITL, LTH/LTL with premium/discount
Line Filters: Daily matrix, midnight filter, custom hourly/minute
Direction Filters: NDOG, NWOG, EMA daily/weekly/custom, macro time
Correlation Settings: Weekly/daily/custom with ticker and type
Profit Targets: Min range, max TP, runners, clustering
Funded Account Rules: Account type, loss limits, margin, contracts
Time Settings - Avoidance: Macro first 2 minutes, day-specific blocks
Miscellaneous: Visual colors for FVGs, liquidity, labels
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💡 Usage Guidelines
Use on 1-minute timeframe (warning displays otherwise)
Designed for futures (ES, NQ, MES, MNQ) and forex
Enable bar magnifier for realistic backtesting
TradingView Premium recommended for extended history
Commission: $0.62/contract for futures accuracy
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📈 Optimization Tips
Focus on ONE trading model - don't combine everything
Trade high-liquidity sessions (NY open is most active)
Optimize in stages: time → filters → stoploss → trailing → avoidance
Use realistic commission and slippage settings
Avoid over-optimization - keep models simple
Test across multiple market conditions
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⚠️ Risk Considerations
Execution Risk: Fast markets can cause slippage beyond settings
False Signals: Not all FVGs lead to profitable trades
Time Sensitivity: Liquidity concepts work best during active sessions
Market Conditions: Performance varies in trending vs ranging markets
Capital Risk: Futures require appropriate margin and risk capital
Leverage: Futures amplify both gains and losses
Over-Optimization: Past performance does not guarantee future results
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⚠️ IMPORTANT DISCLAIMER
Trading futures, forex, and other leveraged products involves substantial risk of loss and is not suitable for all investors. You could lose more than your initial investment. Never trade with money you cannot afford to lose.
Past performance shown in backtests is NOT indicative of future results. No trading strategy guarantees profits. Markets are inherently unpredictable, and historical patterns may not repeat.
This strategy is provided for EDUCATIONAL and INFORMATIONAL purposes only. It does not constitute financial advice, trading advice, or any other type of advice. The concepts are based on ICT (Inner Circle Trader) methodology as interpreted by the author.
Before trading:
• Understand the risks involved
• Use proper position sizing
• Always use stop-losses
• Test thoroughly on demo accounts
• Only trade with capital designated for risk
By using this strategy, you acknowledge that you understand and accept these risks. Trade responsibly.
***CILGIN INDIKATOR***ÇILGIN INDICATOR – User Guide
OVERVIEW
ÇILGIN INDICATOR is a multi-layer trend and momentum confirmation tool designed for discretionary traders.
It combines Relative RSI, EMA structure, SuperTrend logic, Momentum, and optional CCI & ADX filters into a single visual system.
Purpose:
Filter market noise, confirm trend strength, and highlight high-probability Buy / Sell zones.
The indicator works on all symbols and all timeframes.
RELATIVE RSI & MOMENTUM
The indicator can work in two modes:
NORMAL MODE (Formula OFF)
RSI is calculated directly from the chart symbol.
FORMULA MODE (Formula ON)
RSI is calculated from a relative price formula:
Base Symbol / Denominator 1 / Denominator 2
This allows relative strength analysis against indices, sectors, or benchmarks.
RSI SIGNAL LOGIC
RSI Signal Line = SMA of RSI
RSI 50 Level = Trend bias reference
BUY SIGNAL
RSI crosses above the signal line
Optional: RSI must also cross above 50 (Double Confirmation)
SELL SIGNAL
RSI crosses below the signal line
Optional: RSI must also cross below 50
Small arrows on the chart represent RSI-based Buy and Sell signals.
EMA STRUCTURE
Five adaptive EMAs are plotted: EMA 1
EMA 5
EMA 21
EMA 50
EMA 100
EMA lengths automatically adapt to timeframe speed.
EMA BUY LOGIC
Fast EMA crosses above any slower EMA.
EMA SELL LOGIC
Fast EMA crosses below any slower EMA.
EMAs define:
Trend direction
Dynamic support and resistance
Momentum shifts
SUPERTREND SYSTEM
A custom ATR-based SuperTrend is used.
Features:
Optional candle wick usage
Dynamic trailing stop
Visual Buy / Sell labels
SUPERTREND BUY
Trend flips from bearish to bullish.
SUPERTREND SELL
Trend flips from bullish to bearish.
Colored zones visualize the active trend direction.
STRONG BUY & STRONG SELL SIGNALS
A Strong Signal is generated only when multiple conditions agree.
STRONG BUY
RSI Buy Signal
SuperTrend Buy Signal
Optional CCI Filter confirmation
Optional ADX Filter confirmation
STRONG SELL
RSI Sell Signal
SuperTrend Sell Signal
Optional CCI Filter confirmation
Optional ADX Filter confirmation
Strong signals are displayed as large labeled markers: “STRONG BUY”
“STRONG SELL”
Designed for trend-following entries, not market noise.
CCI & ADX FILTERS (OPTIONAL)
CCI FILTER
Buy allowed only if CCI > 0
Sell allowed only if CCI < 0
ADX FILTER
ADX must be above minimum level
Direction confirmed using +DI and -DI
These filters help avoid sideways markets and weak trends.
INFORMATION PANELS
PANEL A (Top Right)
Daily percentage change
Weekly percentage change
Monthly percentage change
Daily volume (millions)
PANEL B (Bottom Right)
Relative RSI value
RSI signal value
Relative momentum
Market status (Bull / Bear)
Provides instant market context without extra indicators.
ALERTS
Built-in alerts are available for:
STRONG BUY
STRONG SELL
Suitable for automation and watchlist monitoring.
BEST PRACTICES
Use Formula Mode for relative strength analysis
Enable CCI & ADX filters on higher timeframes
Combine signals with price action and key levels
Do not use as a standalone trading system
DISCLAIMER
This indicator is a decision-support tool and does not provide financial advice.
Always manage risk and confirm signals with your own analysis.
LQC UNFILLED ORDERS + FVGLQC UNFILLED ORDERS + FVG (LQC UIO)
The Legendary Quantum Complete Standard for Institutional Order Flow
LQC UIO is a professional-grade overlay indicator that combines two of the most powerful concepts in modern price action trading: Unfilled Institutional Orders and Fair Value Gaps (FVG). Built on the LQC Standard (Confirmation, Clean, Customizable), this tool provides a crystal-clear view of where institutional interest lies.
KEY FEATURES:
✅ Institutional Order Zones - Automatically detects high-probability BUY and SELL zones based on small-candle-to-impulse-move patterns
✅ Fair Value Gap Detection - Identifies both Bullish (green) and Bearish (red) FVGs with clean boxes (NO LINES)
✅ FVG Mitigation Tracking - Labels change from "FVG" to "MITIGATED" when filled, with color-coded checkmarks
✅ Volume Confirmation - Validates zone reactions with volume surge
✅ Heiken Ashi Mode - Toggle for cleaner trend detection
✅ Professional Dashboard - Shows all statistics: zones, reactions, FVGs, mitigations
✅ Clean & Customizable - Fully customizable colors, extensions, and settings
✅ Intelligent Alerts - Comprehensive alert system for zones, FVGs, and mitigations
HOW IT WORKS:
1. Unfilled Orders: Detects small indecisive candle + large impulse candle pattern (institutional footprint)
2. Fair Value Gaps: Identifies market inefficiencies that act as price magnets
3. Confirmation: Volume-confirmed reactions ensure institutional participation
HOW TO USE:
- Look for confluence when Order Zones align with FVGs (highest probability setups)
- Use zone touches or FVG mitigations as entry triggers
- Wait for volume confirmation before entering trades
- Zones auto-delete when broken (optional setting)
Built for traders who want to move beyond basic support/resistance and trade with institutional order flow.
Angle-able Thick Linean options to get thicker/thick trendlines. personally i dont think 4 pixels is wide enough so i made this, here you go
Daily/Weekly FVG by KrisThis indicator is a Multi-Timeframe (MTF) tool designed to automatically identify and project Fair Value Gaps (Imbalances) from Daily and Weekly timeframes onto your current chart. It helps traders locate higher-timeframe Areas of Interest (POI) and liquidity voids without manually switching charts.
How it works:
The script utilizes `request.security` to fetch High and Low data from Daily and Weekly timeframes. It identifies a Fair Value Gap (FVG) based on the 3-candle formation logic where price moves inefficiently, leaving a gap between the wicks.
- Bullish FVG: Identified when the current Daily/Weekly Low is greater than the High of the candle from 2 periods ago.
- Bearish FVG: Identified when the current Daily/Weekly High is lower than the Low of the candle from 2 periods ago.
The indicator draws a box extending to the right to visualize the zone, along with a dotted midline which often acts as a sensitive support/resistance level.
Unique Feature: Smart Mitigation (Auto-Hide)
To keep your chart clean and focused on relevant data, the script includes a "Full Fill" logic. It continuously monitors price action relative to existing FVG boxes.
- If price completely crosses through a box (fully fills the gap), the indicator considers it "mitigated" and automatically hides the box and its midline (sets transparency to 100%).
- This ensures you only see "fresh" or unfilled gaps that are still relevant for trading.
Settings:
- TF Checkboxes (Daily/Weekly FVG): Toggle the visibility of Daily or Weekly gaps independently based on your analysis needs.
- Design Mode:
Colored: Uses classic Green (Bullish) and Red (Bearish) colors for easy trend identification.
Monochrome: Uses Gray tones for a minimalist look that reduces visual noise on the chart.
Usage:
Use these zones to identify potential reversal points or liquidity targets. Since these are higher-timeframe levels, they often carry more weight than intraday imbalances.
