52SIGNAL RECIPE CME Gap Support & Resistance Detector═══ 52SIGNAL RECIPE CME Gap Support & Resistance Detector ═══
◆ Overview
The 52SIGNAL RECIPE CME Gap Support & Resistance Detector is an advanced technical indicator that automatically detects and visualizes all types of price gaps occurring in the CME Bitcoin futures market on trading charts. It captures not only gaps formed during weekend and holiday closures, but also those created during the daily 1-hour maintenance period on weekdays, and sudden price gaps resulting from economic indicator releases or news events.
The core value of this indicator lies beyond simply displaying gaps; it visualizes how these price discontinuities act as powerful support and resistance zones that influence future price movements. In real markets, these CME gaps have a high probability of either being "filled" or functioning as important reaction zones, providing traders with valuable entry and exit signals.
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◆ Key Features
• Comprehensive Gap Detection: Detects gaps in all market conditions
- Weekend/holiday closure gaps
- Weekday 1-hour maintenance period gaps
- Gaps from economic indicators/news events causing rapid price changes
• Intuitive Color Coding:
- Blue: When gaps act as support (price is above the gap)
- Red: When gaps act as resistance (price is below the gap)
- Gray: Filled gaps (price has completely passed through the gap area)
• Real-time Role Switching: Automatically changes colors as price moves above/below gaps, visualizing support↔resistance role transitions
• Status Tracking System: Automatically tracks whether gaps are "Filled" or "Unfilled"
• Dynamic Boxes: Clearly marks gap areas with boxes and dynamically changes colors based on price movement
• Precise Labeling: Accurately displays the price range of each gap to support trader decision-making
• Smart Filtering: Improved algorithm that solves consecutive gap detection issues for complete gap tracking
• Key Usage Points:
- Pay special attention when price approaches gap areas
- Color changes in gaps signal important market sentiment shifts
- Areas with multiple clustered gaps are particularly strong reaction zones
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◆ User Guide: Understanding Gap Roles Through Colors
■ Color System Interpretation
• Blue Gaps (Support Role):
▶ Meaning: Current price is above the gap, making the gap act as support
▶ Trading Application: Consider buying opportunities when price approaches blue gap areas
▶ Psychological Meaning: Buying pressure likely to increase at this price level
• Red Gaps (Resistance Role):
▶ Meaning: Current price is below the gap, making the gap act as resistance
▶ Trading Application: Consider selling opportunities when price approaches red gap areas
▶ Psychological Meaning: Selling pressure likely to increase at this price level
• Gray Gaps (Filled Gaps):
▶ Meaning: Price has completely passed through the gap area, filling the gap
▶ Reference Value: Still valuable as reference for past important reaction zones
▶ Trading Application: Used to confirm trend strength and identify key psychological levels
■ Understanding Color Transitions
• Blue → Red Transition:
▶ Meaning: Price has fallen below the gap, changing its role from support to resistance
▶ Market Interpretation: Breakdown of previous support strengthens bearish signals
▶ Trading Application: Consider potential further decline; check gap bottom as resistance during bounces
• Red → Blue Transition:
▶ Meaning: Price has risen above the gap, changing its role from resistance to support
▶ Market Interpretation: Breakout above previous resistance strengthens bullish signals
▶ Trading Application: Consider potential further rise; check gap top as support during pullbacks
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◆ Practical Application Guide
■ Basic Trading Scenarios
• Blue Gap Support Strategy:
▶ Entry Point: When price approaches the top of a blue gap and forms a bounce candle
▶ Stop Loss: Below the gap bottom (if price completely breaks down through the gap)
▶ Take Profit: Previous swing high or next resistance level above
▶ Probability Enhancers: Gap aligned with major moving averages, oversold RSI, strong bounce candle pattern
• Red Gap Resistance Strategy:
▶ Entry Point: When price approaches the bottom of a red gap and forms a rejection candle
▶ Stop Loss: Above the gap top (if price completely breaks up through the gap)
▶ Take Profit: Previous swing low or next support level below
▶ Probability Enhancers: Gap aligned with major moving averages, overbought RSI, strong rejection candle pattern
■ Advanced Pattern Applications
• Multiple Gap Cluster Identification:
▶ Several gaps in close price proximity form extremely powerful support/resistance zones
▶ Same-color gap clusters: Very strong single-direction reaction zones
▶ Mixed-color gap clusters: High volatility zones with bidirectional reactions expected
• Gap Sequence Analysis:
▶ Consecutive same-direction gaps: Strong trend confirmation signal
▶ Increasing gap size pattern: Trend acceleration signal
▶ Decreasing gap size pattern: Trend weakening signal
• News/Indicator Release Gap Utilization:
▶ Gaps formed immediately after economic indicators: Measure market shock intensity
▶ Gap color change observation: Track market reinterpretation of news
▶ Gap filling speed analysis: Evaluate news impact duration
• Key Attention Points:
▶ Pay special attention to the chart whenever price approaches gap areas
▶ Gap color changes signal important market sentiment shifts
▶ Areas with multiple concentrated gaps are likely to show strong price reactions
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◆ Technical Foundation
■ CME Gap Formation Principles
• Key Gap Formation Scenarios:
▶ Weekend Closures (Friday close → Monday open): Most common CME gap formation point
▶ Holiday Closures: Gaps occurring due to CME closures on US holidays
▶ Weekday 1-hour Maintenance: Gaps during daily CME maintenance period (16:00-17:00 CT)
▶ Major Economic Indicator Releases: Gaps from rapid price changes during US employment reports, FOMC decisions, CPI releases, etc.
▶ Significant News Events: Gaps from regulatory announcements, geopolitical events, market shocks, etc.
• Psychological Importance of Gaps:
▶ Zones where price formation did not occur, representing imbalance between buying/selling forces
▶ Gap areas have no actual trading, resulting in accumulated potential orders
▶ Reflect institutional investor positions and liquidity distribution in the CME futures market
■ Support/Resistance Mechanism
• Psychological Level Formation Mechanism:
▶ Unexecuted order accumulation in gap areas: Loss of ordering opportunity at those price levels
▶ Liquidity imbalance: No trading occurred in gap areas, creating liquidity voids
▶ Institutional activity: Institutional participants in CME futures markets pay attention to these gap areas
• Evidence of Support/Resistance Function:
▶ Statistical gap fill phenomenon: Most gaps eventually "fill" (price returns to gap area)
▶ Gap-based reactions: Increased frequency of price reactions (bounces/rejections) when reaching gap areas
▶ Market psychology impact: Influences traders' perceived value and fair price assessment
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◆ Advanced Configuration Options
■ Visualization Settings
• Show Gap Labels (Default: On)
▶ On: Displays price ranges of each gap numerically for precise support/resistance level identification
▶ Off: Hides labels for visual cleanliness
• Color Settings
▶ Filled Gap Color: Gray tones, shows gaps already traversed by price
▶ Unfilled Gap Color - Support: Blue, shows gaps currently acting as support
▶ Unfilled Gap Color - Resistance: Red, shows gaps currently acting as resistance
■ Data Management Settings
• Filled Gap Storage Limit (Default: 10)
▶ Sets maximum number of filled gaps to retain on chart
▶ Recommended settings: Short-term traders (5-8), Swing traders (8-12), Position traders (10-15)
• Maximum Gap Retention Period (Default: 12 months)
▶ Sets period after which old unfilled gaps are automatically removed
▶ Recommended settings: Short-term analysis (3-6 months), Medium-term analysis (6-12 months), Long-term analysis (12-24 months)
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◆ Synergy with Other Indicators
• Volume Profile: Greatly increased reaction probability when CME gaps align with Volume Profile value areas
• Fibonacci Retracements: Formation of powerful reaction zones when major Fibonacci levels coincide with gap areas
• Moving Averages: Areas where major moving averages overlap with CME gaps act as "composite support/resistance"
• Horizontal Support/Resistance: Very strong price reactions expected when historical key price levels align with CME gaps
• Market Sentiment Indicators (RSI/MACD): Assess reaction probability by checking oversold/overbought conditions when price approaches gap areas
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◆ Conclusion
The 52SIGNAL RECIPE CME Gap Support & Resistance Detector is not merely a gap display tool, but an advanced analytical tool that visualizes important support/resistance areas where price may strongly react, using intuitive color codes (blue=support, red=resistance). It detects all types of gaps without omission, whether from weekend and holiday closures, weekday 1-hour maintenance periods, important economic indicator releases, or market shock situations.
The core value of this indicator lies in clearly expressing through intuitive color coding that gaps are not simple price discontinuities, but psychological support/resistance areas that significantly influence future price action. Traders can instantly identify areas where blue gaps act as support and red gaps act as resistance, enabling quick and effective decision-making.
By referencing the color codes when price approaches gap areas to predict possible price reactions, and especially interpreting color transition moments (blue→red or red→blue) as signals of important market sentiment changes and integrating them into trading strategies, traders can capture higher-probability trading opportunities.
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※ Disclaimer: Like all trading tools, the CME Gap Detector should be used as a supplementary indicator and not relied upon alone for trading decisions. Past gap reaction patterns cannot guarantee the same behavior in the future. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE CME Gap Support & Resistance Detector ═══
◆ 개요
52SIGNAL RECIPE CME Gap Support & Resistance Detector는 CME 비트코인 선물 시장에서 발생하는 모든 유형의 가격 갭(Gap)을 자동으로 감지하여 트레이딩 차트에 시각화하는 고급 기술적 지표입니다. 주말과 공휴일 휴장은 물론, 평일 1시간 휴장 시간, 그리고 중요 경제지표 발표나 뉴스 이벤트 시 발생하는 급격한 가격 갭까지 누락 없이 포착합니다.
이 인디케이터의 핵심 가치는 단순히 갭을 표시하는 것을 넘어, 이러한 가격 불연속성이 미래 가격 움직임에 영향을 미치는 강력한 지지(Support)와 저항(Resistance) 영역으로 작용한다는 원리를 시각화하는 데 있습니다. 실제 시장에서 이러한 CME 갭은 높은 확률로 미래에 "매꿔지거나" 중요한 반응 구간으로 기능하여 트레이더에게 귀중한 진입/퇴출 신호를 제공합니다.
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◆ 주요 특징
• 전방위 갭 감지: 모든 시장 조건에서 발생하는 갭을 감지
- 주말/공휴일 휴장 갭
- 평일 1시간 휴장 시간 갭
- 경제지표/뉴스 이벤트 시 급격한 가격 변동 갭
• 직관적 색상 구분:
- 파란색: 갭이 지지 역할을 할 때(가격이 갭 위에 있을 때)
- 빨간색: 갭이 저항 역할을 할 때(가격이 갭 아래에 있을 때)
- 회색: 이미 매꿔진 갭(가격이 갭 영역을 완전히 통과)
• 실시간 역할 전환: 가격이 갭 위/아래로 이동함에 따라 지지↔저항 역할 전환을 자동으로 색상 변경으로 시각화
• 상태 추적 시스템: 갭이 "매꿔짐(Filled)" 또는 "매꿔지지 않음(Unfilled)" 상태를 자동 추적
• 다이나믹 박스: 갭 영역을 명확한 박스로 표시하고 가격 움직임에 따라 동적으로 색상 변경
• 정밀 레이블링: 각 갭의 가격 범위를 정확히 표시하여 트레이더의 의사결정 지원
• 스마트 필터링: 연속적 갭 감지 문제를 해결하는 개선된 알고리즘으로 누락 없는 갭 추적
• 핵심 활용 포인트:
- 가격이 갭 영역에 접근할 때 특별히 주목하세요
- 갭 색상 변경 시점은 중요한 시장 심리 변화 신호입니다
- 여러 갭이 밀집된 영역은 특히 강한 반응이 예상되는 구간입니다
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◆ 사용 가이드: 색상으로 이해하는 갭 역할
■ 색상 시스템 해석법
• 파란색 갭 (지지 역할):
▶ 의미: 현재 가격이 갭 위에 있어 갭이 지지선으로 작용
▶ 트레이딩 응용: 가격이 파란색 갭 영역으로 하락 접근 시 매수 기회 고려
▶ 심리적 의미: 매수세력이 이 가격대에서 수요 증가 가능성
• 빨간색 갭 (저항 역할):
▶ 의미: 현재 가격이 갭 아래에 있어 갭이 저항선으로 작용
▶ 트레이딩 응용: 가격이 빨간색 갭 영역으로 상승 접근 시 매도 기회 고려
▶ 심리적 의미: 매도세력이 이 가격대에서 공급 증가 가능성
• 회색 갭 (매꿔진 갭):
▶ 의미: 가격이 갭 영역을 완전히 통과하여 갭이 매꿔진 상태
▶ 참조 가치: 과거 중요 반응 구간으로 여전히 참고 가치 있음
▶ 트레이딩 응용: 추세 강도 확인 및 주요 심리적 레벨 식별에 활용
■ 색상 전환 이해하기
• 파란색 → 빨간색 전환:
▶ 의미: 가격이 갭 아래로 하락하여 갭이 지지에서 저항으로 역할 변경
▶ 시장 해석: 이전 지지선 붕괴로 약세 신호 강화
▶ 트레이딩 응용: 추가 하락 가능성 고려, 반등 시 갭 하단 저항 확인
• 빨간색 → 파란색 전환:
▶ 의미: 가격이 갭 위로 상승하여 갭이 저항에서 지지로 역할 변경
▶ 시장 해석: 이전 저항선 돌파로 강세 신호 강화
▶ 트레이딩 응용: 추가 상승 가능성 고려, 조정 시 갭 상단 지지 확인
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◆ 실전 활용 가이드
■ 기본 트레이딩 시나리오
• 파란색 갭 지지 전략:
▶ 진입 시점: 가격이 파란색 갭 상단에 접근하여 반등 캔들 형성 시
▶ 손절 위치: 갭 하단 아래(갭 완전히 하향 돌파 시)
▶ 이익실현: 이전 스윙 고점 또는 상방 다음 저항선
▶ 확률 증가 조건: 갭과 주요 이동평균선 일치, 과매도 RSI, 강한 반등 캔들
• 빨간색 갭 저항 전략:
▶ 진입 시점: 가격이 빨간색 갭 하단에 접근하여 거부 캔들 형성 시
▶ 손절 위치: 갭 상단 위(갭 완전히 상향 돌파 시)
▶ 이익실현: 이전 스윙 저점 또는 하방 다음 지지선
▶ 확률 증가 조건: 갭과 주요 이동평균선 일치, 과매수 RSI, 강한 거부 캔들
■ 고급 패턴 활용법
• 다중 갭 클러스터 식별:
▶ 여러 갭이 근접한 가격대에 있다면 더욱 강력한 지지/저항 존
▶ 동일 색상 갭 클러스터: 매우 강력한 단일 방향 반응 구간
▶ 색상 혼합 갭 클러스터: 심한 변동성과 양방향 반응 예상 구간
• 갭 시퀀스 분석:
▶ 연속적인 동일 방향 갭: 강한 추세 확인 신호
▶ 갭 크기 증가 패턴: 추세 가속화 신호
▶ 갭 크기 감소 패턴: 추세 약화 신호
• 뉴스/지표 발표 후 갭 활용:
▶ 경제지표 발표 직후 형성된 갭: 시장 충격 강도 측정
▶ 갭 색상 변화 관찰: 시장의 뉴스 재해석 과정 파악
▶ 갭 매꿈 속도 분석: 뉴스 임팩트의 지속성 평가
• 핵심 주목 포인트:
▶ 가격이 갭 영역에 접근할 때마다 차트를 특별히 주목하세요
▶ 갭 색상이 변경되는 시점은 중요한 시장 심리 변화를 의미합니다
▶ 여러 갭이 밀집된 영역은 가격이 강하게 반응할 가능성이 높습니다
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◆ 기술적 기반
■ CME 갭의 발생 원리
• 주요 갭 발생 상황:
▶ 주말 휴장 (금요일 종가 → 월요일 시가): 가장 일반적인 CME 갭 형성 시점
▶ 공휴일 휴장: 미국 공휴일에 따른 CME 휴장 시 발생
▶ 평일 1시간 휴장: CME 시장의 일일 정비 시간(16:00~17:00 CT) 동안 발생
▶ 주요 경제지표 발표: 미 고용지표, FOMC 결정, CPI 등 발표 시 급격한 가격 변동으로 인한 갭
▶ 중요 뉴스 이벤트: 규제 발표, 지정학적 이벤트, 시장 충격 등으로 인한 급격한 가격 변화
• 갭의 심리적 중요성:
▶ 가격 형성이 이루어지지 않은 구간으로, 매수/매도 세력의 불균형 영역
▶ 갭 구간에는 실제 거래가 없었기 때문에 잠재적 주문이 누적되는 영역
▶ 기관 투자자들의 선물 포지션과 유동성 분포가 반영된 중요한 가격 레벨
■ 지지/저항으로 작용하는 원리
• 심리적 레벨 형성 메커니즘:
▶ 갭 구간의 미실행 주문 축적: 갭 발생 시 해당 가격대에 대한 주문 기회 상실
▶ 유동성 불균형: 갭 구간에는 거래가 없었으므로 유동성 공백 발생
▶ 기관 투자자 활동: CME 선물 시장의 기관 참여자들은 이러한 갭 영역에 관심
• 지지/저항 작용 증거:
▶ 통계적 갭 필 현상: 대부분의 갭은 미래에 "매꿔짐"(가격이 갭 구간으로 회귀)
▶ 갭 기반 반응: 갭 영역에 도달 시 가격 반응(반등/거부) 발생 빈도 증가
▶ 시장 심리 영향: 트레이더들의 인지된 가치와 공정가격 평가에 영향
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◆ 고급 설정 옵션
■ 시각화 설정
• 라벨 표시 설정 (Show Gap Labels) (기본값: 켜짐)
▶ 켜짐: 각 갭의 가격 범위를 숫자로 표시하여 정확한 지지/저항 레벨 확인
▶ 꺼짐: 시각적 깔끔함을 위해 라벨 숨김
• 색상 설정
▶ 매꿔진 갭 색상(Filled Gap Color): 회색 계열, 이미 가격이 통과한 갭 표시
▶ 미매꿔진 갭 색상 - 지지(Support): 파란색, 현재 지지 역할을 하는 갭
▶ 미매꿔진 갭 색상 - 저항(Resistance): 빨간색, 현재 저항 역할을 하는 갭
■ 데이터 관리 설정
• 매꿔진 갭 저장 한도 (Filled Gap Storage Limit) (기본값: 10)
▶ 이미 매꿔진 갭을 최대 몇 개까지 차트에 유지할지 설정
▶ 권장 설정: 단기 트레이더(5-8), 스윙 트레이더(8-12), 포지션 트레이더(10-15)
• 최대 갭 보관 기간 (Maximum Gap Retention Period) (기본값: 12개월)
▶ 오래된 미매꿔진 갭을 자동으로 제거하는 기간 설정
▶ 권장 설정: 단기 분석(3-6개월), 중기 분석(6-12개월), 장기 분석(12-24개월)
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◆ 다른 지표와의 시너지
• 볼륨 프로파일: CME 갭과 볼륨 프로파일의 밸류 영역 일치 시 반응 확률 크게 증가
• 피보나치 리트레이스먼트: 주요 피보나치 레벨과 갭 영역 일치 시 강력한 반응 존 형성
• 이동평균선: 주요 이동평균선과 CME 갭이 겹치는 영역은 "복합 지지/저항"으로 작용
• 수평 지지/저항: 과거 중요 가격대와 CME 갭 일치 시 매우 강력한 가격 반응 예상 가능
• 시장 심리 지표(RSI/MACD): 갭 영역 접근 시 과매수/과매도 확인으로 반응 가능성 판단
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◆ 결론
52SIGNAL RECIPE CME Gap Support & Resistance Detector는 단순한 갭 표시 도구가 아닌, 가격이 강하게 반응할 수 있는 중요한 지지/저항 영역을 직관적인 색상 코드(파란색=지지, 빨간색=저항)로 시각화하는 고급 분석 도구입니다. 주말과 공휴일 휴장 시간뿐만 아니라, 평일 1시간 휴장 시간, 중요 경제지표 발표, 그리고 시장 충격 상황에서 발생하는 모든 유형의 갭을 누락 없이 감지합니다.
인디케이터의 핵심 가치는 갭이 단순한 가격 불연속성이 아닌, 미래 가격 행동에 중요한 영향을 미치는 심리적 지지/저항 영역임을 직관적인 색상 코드로 명확히 표현하는 데 있습니다. 파란색 갭은 지지 역할을, 빨간색 갭은 저항 역할을 하는 영역을 즉각적으로 식별할 수 있어 트레이더가 빠르고 효과적인 의사결정을 내릴 수 있도록 도와줍니다.
갭 영역에 접근할 때마다 색상 코드를 참고하여 가능한 가격 반응을 예측하고, 특히 색상 전환이 일어나는 순간(파란색→빨간색 또는 빨간색→파란색)은 중요한 시장 심리 변화 신호로 해석하여 트레이딩 전략에 통합한다면, 더 높은 확률의 거래 기회를 포착할 수 있을 것입니다.
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※ 면책 조항: 모든 트레이딩 도구와 마찬가지로, CME Gap Detector는 보조 지표로 사용되어야 하며 단독으로 거래 결정을 내리는 데 사용해서는 안 됩니다. 과거의 갭 반응 패턴이 미래에도 동일하게 작용한다고 보장할 수 없습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
Sentiment
Session Volatility Dashboard█ Session Volatility Dashboard: HOW IT WORKS
This tool is built on transparent, statistically-grounded principles to ensure reliability and build user trust.
Session Logic: The script accurately identifies session periods based on user-defined start and end times in conjunction with the selected UTC offset. This ensures the session boxes and data are correctly aligned regardless of your local timezone or daylight saving changes.
Volatility Calculation: The core of the volatility engine is a comparison of current and historical price action. The script calculates a rolling Average True Range (ATR) over a user-defined lookback period (e.g., the last 20 sessions). It then compares the current session's ATR to this historical baseline to generate a simple percentage. For example, a reading of "135%" indicates the current session is 35% more volatile than the recent average, while "80%" indicates a contraction in volatility.
Dashboard Population : The script leverages TradingView's table object to construct the dashboard. This powerful feature allows the data to be displayed in a fixed position on the screen (e.g., top-right corner). Unlike plotted text, this table does not scroll with the chart's price history, ensuring that the most critical, up-to-date information is always available at a glance.
█ ACTIONABLE INTELLIGENCE: TRADING STRATEGIES & USE CASES
Translate data into action with these practical trading concepts.
Strategy 1: The Breakout Trade: Identify a session with low, coiling volatility (e.g., a Volatility reading below 75%)—often the Asian session. Mark the session high and low plotted by the indicator. These levels become prime targets for a potential breakout trade during the high-volume, high-volatility open of the subsequent London session.
Strategy 2 : The Mean Reversion (Fade) Trade: In a session with extremely high volatility (e.g., >150% of average), watch for price to rapidly extend to a new session high or low and then print a clear reversal candlestick pattern (like a pin bar or engulfing candle). This can signal momentum exhaustion and a high-probability opportunity to "fade" the move back toward the session midpoint.
Strategy 3 : The Trend Continuation: During a clear trending day, use the session midpoint as a dynamic area of value. Look for price to pull back to the midpoint during the London or New York session. If the session's Bias in the dashboard remains aligned with the higher-timeframe trend, this can present a quality entry to rejoin the established momentum.
█ COMPLETE CUSTOMIZATION: SETTINGS
Session Times: Independently set the start and end times for Asia, London, and New York sessions.
Timezone: Select your preferred UTC offset to align all sessions correctly.
Volatility Lookback: Define the number of past sessions to use for calculating the average volatility baseline (default is 20).
Dashboard Settings: Choose the on-screen position of the table, text size, and colors.
Visual Elements: Toggle on/off session background colors, high/low lines, and midpoint lines. Customize all colors.
Alerts: Enable/disable and customize alerts for session high/low breaks and volatility threshold crossings.
Intra-bar Close/Open Gap [YuL]Just checking one idea: look at gaps between close and open bars on lower timeframe to try to estimate how much slippage exists there that may be a result of buying or selling pressure.
Perhaps it only useful in real time to see if situation of the current bar is changing.
Open to ideas and suggestions.
Top Crypto Above 28-Day AverageDescription
The “Top Crypto Above 28-Day Average” (CRYPTOTW) script scans a selectable universe of up to 120 top-capitalization cryptocurrencies (divided into customizable 40-symbol batches), then plots the count of those trading above their own 28-period simple moving average. It helps you gauge broad market strength and identify which tokens are showing momentum relative to their recent trend.
Key Features
• Batch Selection: Choose among “Top40,” “Mid40,” or “Low40” market-cap groups, or set a custom batch size (up to 40 symbols) to keep within the API limit.
• Dynamic Plot: Displays a live line chart of how many cryptos are above their 28-day MA on each bar.
• Reference Lines: Automatic horizontal lines at 25%, 50%, and 75% of your batch to provide quick visual thresholds.
• Background Coloration: The chart background shifts green/yellow/red based on whether more than 70%, 50–70%, or under 50% of the batch is above the MA.
• Optional Table: On the final bar, show a sortable table of up to 28 tickers currently above their 28-day MA, including current price, percent above MA, and “Above” status color-coding.
• Alerts:
• Strong Batch Performance: Fires when >70% of the batch is above the MA.
• Weak Batch Performance: Fires when <10 cryptos (i.e. <25%) are above the MA.
Inputs
• Show Results Table (show_table): Toggle the detailed table on/off.
• Table Position (table_position): Select one of the four corners for your table overlay.
• Max Cryptos to Display (max_display): Limit the number of rows in the results table.
• Current Batch (current_batch): Pick “Top40,” “Mid40,” or “Low40.”
• Batch Size (batch_size): Define the number of symbols (1–40) you want to include from the chosen batch.
How to Use
1. Add the CRYPTOTW indicator to any chart.
2. Select your batch and size to focus on the segment of the crypto market you follow.
3. Watch the plotted line to see the proportion of tokens with bullish momentum.
4. (Optional) Enable the results table to see exactly which tokens are outperforming their 28-day average.
5. Set alerts to be notified when the batch either overheats (strong performance) or cools off significantly.
Why It Matters
By tracking the share of assets riding their 28-day trend, you gain a macro-level view of market breadth—crucial for spotting emerging rallies or early signs of broad weakness. Whether you’re swing-trading individual altcoins or assessing overall market mood, this tool distills complex data into an intuitive, actionable signal.
Diamond Peaks [EdgeTerminal]The Diamond Peaks indicator is a comprehensive technical analysis tool that uses a few mathematical models to identify high-probability trading opportunities. This indicator goes beyond traditional support and resistance identification by incorporating volume analysis, momentum divergences, advanced price action patterns, and market sentiment indicators to generate premium-quality buy and sell signals.
Dynamic Support/Resistance Calculation
The indicator employs an adaptive algorithm that calculates support and resistance levels using a volatility-adjusted lookback period. The base calculation uses ta.highest(length) and ta.lowest(length) functions, where the length parameter is dynamically adjusted using the formula: adjusted_length = base_length * (1 + (volatility_ratio - 1) * volatility_factor). The volatility ratio is computed as current_ATR / average_ATR over a 50-period window, ensuring the lookback period expands during volatile conditions and contracts during calm periods. This mathematical approach prevents the indicator from using fixed periods that may become irrelevant during different market regimes.
Momentum Divergence Detection Algorithm
The divergence detection system uses a mathematical comparison between price series and oscillator values over a specified lookback period. For bullish divergences, the algorithm identifies when recent_low < previous_low while simultaneously indicator_at_recent_low > indicator_at_previous_low. The inverse logic applies to bearish divergences. The system tracks both RSI (calculated using Pine Script's standard ta.rsi() function with Wilder's smoothing) and MACD (using ta.macd() with exponential moving averages). The mathematical rigor ensures that divergences are only flagged when there's a clear mathematical relationship between price momentum and the underlying oscillator momentum, eliminating false signals from minor price fluctuations.
Volume Analysis Mathematical Framework
The volume analysis component uses multiple mathematical transformations to assess market participation. The Cumulative Volume Delta (CVD) is calculated as ∑(buying_volume - selling_volume) where buying_volume occurs when close > open and selling_volume when close < open. The relative volume calculation uses current_volume / ta.sma(volume, period) to normalize current activity against historical averages. Volume Rate of Change employs ta.roc(volume, period) = (current_volume - volume ) / volume * 100 to measure volume acceleration. Large trade detection uses a threshold multiplier against the volume moving average, mathematically identifying institutional activity when relative_volume > threshold_multiplier.
Advanced Price Action Mathematics
The Wyckoff analysis component uses mathematical volume climax detection by comparing current volume against ta.highest(volume, 50) * 0.8, while price compression is measured using (high - low) < ta.atr(20) * 0.5. Liquidity sweep detection employs percentage-based calculations: bullish sweeps occur when low < recent_low * (1 - threshold_percentage/100) followed by close > recent_low. Supply and demand zones are mathematically validated by tracking subsequent price action over a defined period, with zone strength calculated as the count of bars where price respects the zone boundaries. Fair value gaps are identified using ATR-based thresholds: gap_size > ta.atr(14) * 0.5.
Sentiment and Market Regime Mathematics
The sentiment analysis employs a multi-factor mathematical model. The fear/greed index uses volatility normalization: 100 - min(100, stdev(price_changes, period) * scaling_factor). Market regime classification uses EMA crossover mathematics with additional ADX-based trend strength validation. The trend strength calculation implements a modified ADX algorithm: DX = |+DI - -DI| / (+DI + -DI) * 100, then ADX = RMA(DX, period). Bull regime requires short_EMA > long_EMA AND ADX > 25 AND +DI > -DI. The mathematical framework ensures objective regime classification without subjective interpretation.
Confluence Scoring Mathematical Model
The confluence scoring system uses a weighted linear combination: Score = (divergence_component * 0.25) + (volume_component * 0.25) + (price_action_component * 0.25) + (sentiment_component * 0.25) + contextual_bonuses. Each component is normalized to a 0-100 scale using percentile rankings and threshold comparisons. The mathematical model ensures that no single component can dominate the score, while contextual bonuses (regime alignment, volume confirmation, etc.) provide additional mathematical weight when multiple factors align. The final score is bounded using math.min(100, math.max(0, calculated_score)) to maintain mathematical consistency.
Vitality Field Mathematical Implementation
The vitality field uses a multi-factor scoring algorithm that combines trend direction (EMA crossover: trend_score = fast_EMA > slow_EMA ? 1 : -1), momentum (RSI-based: momentum_score = RSI > 50 ? 1 : -1), MACD position (macd_score = MACD_line > 0 ? 1 : -1), and volume confirmation. The final vitality score uses weighted mathematics: vitality_score = (trend * 0.4) + (momentum * 0.3) + (macd * 0.2) + (volume * 0.1). The field boundaries are calculated using ATR-based dynamic ranges: upper_boundary = price_center + (ATR * user_defined_multiplier), with EMA smoothing applied to prevent erratic boundary movements. The gradient effect uses mathematical transparency interpolation across multiple zones.
Signal Generation Mathematical Logic
The signal generation employs boolean algebra with multiple mathematical conditions that must simultaneously evaluate to true. Buy signals require: (confluence_score ≥ threshold) AND (divergence_detected = true) AND (relative_volume > 1.5) AND (volume_ROC > 25%) AND (RSI < 35) AND (trend_strength > minimum_ADX) AND (regime = bullish) AND (cooldown_expired = true) AND (last_signal ≠ buy). The mathematical precision ensures that signals only generate when all quantitative conditions are met, eliminating subjective interpretation. The cooldown mechanism uses bar counting mathematics: bars_since_last_signal = current_bar_index - last_signal_bar_index ≥ cooldown_period. This mathematical framework provides objective, repeatable signal generation that can be backtested and validated statistically.
This mathematical foundation ensures the indicator operates on objective, quantifiable principles rather than subjective interpretation, making it suitable for algorithmic trading and systematic analysis while maintaining transparency in its computational methodology.
* for now, we're planning to keep the source code private as we try to improve the models used here and allow a small group to test them. My goal is to eventually use the multiple models in this indicator as their own free and open source indicators. If you'd like to use this indicator, please send me a message to get access.
Advanced Confluence Scoring System
Each support and resistance level receives a comprehensive confluence score (0-100) based on four weighted components:
Momentum Divergences (25% weight)
RSI and MACD divergence detection
Identifies momentum shifts before price reversals
Bullish/bearish divergence confirmation
Volume Analysis (25% weight)
Cumulative Volume Delta (CVD) analysis
Volume Rate of Change monitoring
Large trade detection (institutional activity)
Volume profile strength assessment
Advanced Price Action (25% weight)
Supply and demand zone identification
Liquidity sweep detection (stop hunts)
Wyckoff accumulation/distribution patterns
Fair value gap analysis
Market Sentiment (25% weight)
Fear/Greed index calculation
Market regime classification (Bull/Bear/Sideways)
Trend strength measurement (ADX-like)
Momentum regime alignment
Dynamic Support and Resistance Detection
The indicator uses an adaptive algorithm to identify significant support and resistance levels based on recent market highs and lows. Unlike static levels, these zones adjust dynamically to market volatility using the Average True Range (ATR), ensuring the levels remain relevant across different market conditions.
Vitality Field Background
The indicator features a unique vitality field that provides instant visual feedback about market sentiment:
Green zones: Bullish market conditions with strong momentum
Red zones: Bearish market conditions with weak momentum
Gray zones: Neutral/sideways market conditions
The vitality field uses a sophisticated gradient system that fades from the center outward, creating a clean, professional appearance that doesn't overwhelm the chart while providing valuable context.
Buy Signals (🚀 BUY)
Buy signals are generated when ALL of the following conditions are met:
Valid support level with confluence score ≥ 80
Bullish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bull market regime environment
RSI below 35 (oversold conditions)
Price action confirmation (Wyckoff accumulation, liquidity sweep, or large buying volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive buy signals)
Cooldown period expired (default 10 bars)
Sell Signals (🔻 SELL)
Sell signals are generated when ALL of the following conditions are met:
Valid resistance level with confluence score ≥ 80
Bearish momentum divergence detected (RSI or MACD)
Volume confirmation (1.5x average volume + 25% volume ROC)
Bear market regime environment
RSI above 65 (overbought conditions)
Price action confirmation (Wyckoff distribution, liquidity sweep, or large selling volume)
Minimum trend strength (ADX > 25)
Signal alternation check (prevents consecutive sell signals)
Cooldown period expired (default 10 bars)
How to Use the Indicator
1. Signal Quality Assessment
Monitor the confluence scores in the information table:
Score 90-100: Exceptional quality levels (A+ grade)
Score 80-89: High quality levels (A grade)
Score 70-79: Good quality levels (B grade)
Score below 70: Weak levels (filtered out by default)
2. Market Context Analysis
Use the vitality field and market regime information to understand the broader market context:
Trade buy signals in green vitality zones during bull regimes
Trade sell signals in red vitality zones during bear regimes
Exercise caution in gray zones (sideways markets)
3. Entry and Exit Strategy
For Buy Signals:
Enter long positions when premium buy signals appear
Place stop loss below the support confluence zone
Target the next resistance level or use a risk/reward ratio of 2:1 or higher
For Sell Signals:
Enter short positions when premium sell signals appear
Place stop loss above the resistance confluence zone
Target the next support level or use a risk/reward ratio of 2:1 or higher
4. Risk Management
Only trade signals with confluence scores above 80
Respect the signal alternation system (no overtrading)
Use appropriate position sizing based on signal quality
Consider the overall market regime before taking trades
Customizable Settings
Signal Generation Controls
Signal Filtering: Enable/disable advanced filtering
Confluence Threshold: Adjust minimum score requirement (70-95)
Cooldown Period: Set bars between signals (5-50)
Volume/Momentum Requirements: Toggle confirmation requirements
Trend Strength: Minimum ADX requirement (15-40)
Vitality Field Options
Enable/Disable: Control background field display
Transparency Settings: Adjust opacity for center and edges
Field Size: Control the field boundaries (3.0-20.0)
Color Customization: Set custom colors for bullish/bearish/neutral states
Weight Adjustments
Divergence Weight: Adjust momentum component influence (10-40%)
Volume Weight: Adjust volume component influence (10-40%)
Price Action Weight: Adjust price action component influence (10-40%)
Sentiment Weight: Adjust sentiment component influence (10-40%)
Best Practices
Always wait for complete signal confirmation before entering trades
Use higher timeframes for signal validation and context
Combine with proper risk management and position sizing
Monitor the information table for real-time market analysis
Pay attention to volume confirmation for higher probability trades
Respect market regime alignment for optimal results
Basic Settings
Base Length (Default: 25)
Controls the lookback period for identifying support and resistance levels
Range: 5-100 bars
Lower values = More responsive, shorter-term levels
Higher values = More stable, longer-term levels
Recommendation: 25 for intraday, 50 for swing trading
Enable Adaptive Length (Default: True)
Automatically adjusts the base length based on market volatility
When enabled, length increases in volatile markets and decreases in calm markets
Helps maintain relevant levels across different market conditions
Volatility Factor (Default: 1.5)
Controls how much the adaptive length responds to volatility changes
Range: 0.5-3.0
Higher values = More aggressive length adjustments
Lower values = More conservative length adjustments
Volume Profile Settings
VWAP Length (Default: 200)
Sets the calculation period for the Volume Weighted Average Price
Range: 50-500 bars
Shorter periods = More responsive to recent price action
Longer periods = More stable reference line
Used for volume profile analysis and confluence scoring
Volume MA Length (Default: 50)
Period for calculating the volume moving average baseline
Range: 10-200 bars
Used to determine relative volume (current volume vs. average)
Shorter periods = More sensitive to volume changes
Longer periods = More stable volume baseline
High Volume Node Threshold (Default: 1.5)
Multiplier for identifying significant volume spikes
Range: 1.0-3.0
Values above this threshold mark high-volume nodes with diamond shapes
Lower values = More frequent high-volume signals
Higher values = Only extreme volume events marked
Momentum Divergence Settings
Enable Divergence Detection (Default: True)
Master switch for momentum divergence analysis
When disabled, removes divergence from confluence scoring
Significantly impacts signal generation quality
RSI Length (Default: 14)
Period for RSI calculation used in divergence detection
Range: 5-50
Standard RSI settings apply (14 is most common)
Shorter periods = More sensitive, more signals
Longer periods = Smoother, fewer but more reliable signals
MACD Settings
Fast (Default: 12): Fast EMA period for MACD calculation (5-50)
Slow (Default: 26): Slow EMA period for MACD calculation (10-100)
Signal (Default: 9): Signal line EMA period (3-20)
Standard MACD settings for divergence detection
Divergence Lookback (Default: 5)
Number of bars to look back when detecting divergences
Range: 3-20
Shorter periods = More frequent divergence signals
Longer periods = More significant divergence signals
Volume Analysis Enhancement Settings
Enable Advanced Volume Analysis (Default: True)
Master control for sophisticated volume calculations
Includes CVD, volume ROC, and large trade detection
Critical for signal accuracy
Cumulative Volume Delta Length (Default: 20)
Period for CVD smoothing calculation
Range: 10-100
Tracks buying vs. selling pressure over time
Shorter periods = More reactive to recent flows
Longer periods = Broader trend perspective
Volume ROC Length (Default: 10)
Period for Volume Rate of Change calculation
Range: 5-50
Measures volume acceleration/deceleration
Key component in volume confirmation requirements
Large Trade Volume Threshold (Default: 2.0)
Multiplier for identifying institutional-size trades
Range: 1.5-5.0
Trades above this threshold marked as large trades
Lower values = More frequent large trade signals
Higher values = Only extreme institutional activity
Advanced Price Action Settings
Enable Wyckoff Analysis (Default: True)
Activates simplified Wyckoff accumulation/distribution detection
Identifies potential smart money positioning
Important for high-quality signal generation
Enable Supply/Demand Zones (Default: True)
Identifies fresh supply and demand zones
Tracks zone strength based on subsequent price action
Enhances confluence scoring accuracy
Enable Liquidity Analysis (Default: True)
Detects liquidity sweeps and stop hunts
Identifies fake breakouts vs. genuine moves
Critical for avoiding false signals
Zone Strength Period (Default: 20)
Bars used to assess supply/demand zone strength
Range: 10-50
Longer periods = More thorough zone validation
Shorter periods = Faster zone assessment
Liquidity Sweep Threshold (Default: 0.5%)
Percentage move required to confirm liquidity sweep
Range: 0.1-2.0%
Lower values = More sensitive sweep detection
Higher values = Only significant sweeps detected
Sentiment and Flow Settings
Enable Sentiment Analysis (Default: True)
Master control for market sentiment calculations
Includes fear/greed index and regime classification
Important for market context assessment
Fear/Greed Period (Default: 20)
Calculation period for market sentiment indicator
Range: 10-50
Based on price volatility and momentum
Shorter periods = More reactive sentiment readings
Momentum Regime Length (Default: 50)
Period for determining overall market regime
Range: 20-100
Classifies market as Bull/Bear/Sideways
Longer periods = More stable regime classification
Trend Strength Length (Default: 30)
Period for ADX-like trend strength calculation
Range: 10-100
Measures directional momentum intensity
Used in signal filtering requirements
Advanced Signal Generation Settings
Enable Signal Filtering (Default: True)
Master control for premium signal generation system
When disabled, uses basic signal conditions
Highly recommended to keep enabled
Minimum Signal Confluence Score (Default: 80)
Required confluence score for signal generation
Range: 70-95
Higher values = Fewer but higher quality signals
Lower values = More frequent but potentially lower quality signals
Signal Cooldown (Default: 10 bars)
Minimum bars between signals of same type
Range: 5-50
Prevents signal spam and overtrading
Higher values = More conservative signal spacing
Require Volume Confirmation (Default: True)
Mandates volume requirements for signal generation
Requires 1.5x average volume + 25% volume ROC
Critical for signal quality
Require Momentum Confirmation (Default: True)
Mandates divergence detection for signals
Ensures momentum backing for directional moves
Essential for high-probability setups
Minimum Trend Strength (Default: 25)
Required ADX level for signal generation
Range: 15-40
Ensures signals occur in trending markets
Higher values = Only strong trending conditions
Confluence Scoring Settings
Minimum Confluence Score (Default: 70)
Threshold for displaying support/resistance levels
Range: 50-90
Levels below this score are filtered out
Higher values = Only strongest levels shown
Component Weights (Default: 25% each)
Divergence Weight: Momentum component influence (10-40%)
Volume Weight: Volume analysis influence (10-40%)
Price Action Weight: Price patterns influence (10-40%)
Sentiment Weight: Market sentiment influence (10-40%)
Must total 100% for balanced scoring
Vitality Field Settings
Enable Vitality Field (Default: True)
Controls the background gradient field display
Provides instant visual market sentiment feedback
Enhances chart readability and context
Vitality Center Transparency (Default: 85%)
Opacity at the center of the vitality field
Range: 70-95%
Lower values = More opaque center
Higher values = More transparent center
Vitality Edge Transparency (Default: 98%)
Opacity at the edges of the vitality field
Range: 95-99%
Creates smooth fade effect from center to edges
Higher values = More subtle edge appearance
Vitality Field Size (Default: 8.0)
Controls the overall size of the vitality field
Range: 3.0-20.0
Based on ATR multiples for dynamic sizing
Lower values = Tighter field around price
Higher values = Broader field coverage
Recommended Settings by Trading Style
Scalping (1-5 minutes)
Base Length: 15
Volume MA Length: 20
Signal Cooldown: 5 bars
Vitality Field Size: 5.0
Higher sensitivity for quick moves
Day Trading (15-60 minutes)
Base Length: 25 (default)
Volume MA Length: 50 (default)
Signal Cooldown: 10 bars (default)
Vitality Field Size: 8.0 (default)
Balanced settings for intraday moves
Swing Trading (4H-Daily)
Base Length: 50
Volume MA Length: 100
Signal Cooldown: 20 bars
Vitality Field Size: 12.0
Longer-term perspective for multi-day moves
Conservative Trading
Minimum Signal Confluence: 85
Minimum Confluence Score: 80
Require all confirmations: True
Higher thresholds for maximum quality
Aggressive Trading
Minimum Signal Confluence: 75
Minimum Confluence Score: 65
Signal Cooldown: 5 bars
Lower thresholds for more opportunities
RSI with 2-Pole FilterA momentum indicator that tells you if a stock is overbought or oversold.
RSI goes between 0 and 100.
70 = overbought (might fall)
<30 = oversold (might rise)
It often looks jagged or choppy on volatile days.
Think of this filter like a momentum smoother:
It still follows RSI closely,
But it doesn’t react to every little jiggle in price,
Which helps avoid false signals.
it keeps track of:
The current RSI,
The last 2 RSI values (inputs), and
The last 2 outputs (filtered RSIs).
It uses feedback to shape the output based on previous values, making it smoother than a simple moving average.
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
BitDoctor Risk Appetite DashboardBitDoctor Risk Appetite Dashboard
The BitDoctor Risk Appetite Dashboard is a powerful tool for gauging market sentiment and risk appetite across major asset classes. It combines equity, credit, emerging markets, interest rates, and crypto signals into a single dashboard, giving traders a clear view of current market dynamics.
What it does:
- Calculates momentum for each key asset using a 14-day rate of change.
- Normalizes each signal and plots a composite Risk Appetite Strength Index (RASI) on the chart.
- Displays a dashboard table showing the momentum of each component in percentage terms alongside the composite RASI.
How to use it:
The plotted RASI line shows overall risk appetite:
- Positive readings suggest a stronger risk-on environment.
- Negative readings indicate risk-off sentiment.
The dashboard table (top-right corner by default) displays two columns:
- Asset : The tracked asset symbol.
- Momentum : The current 14-day rate of change as a percentage.
Interpreting the table:
Each row represents a component of market risk sentiment:
- SPY : US equities.
- HYG : High yield bonds (credit risk appetite).
- EEM : Emerging markets.
- 1/UST10Y : Inverted 10-year Treasury yield (lower yields support risk appetite).
- ETH : Ethereum (crypto risk proxy).
- RASI : The average of the above signals, indicating overall market risk appetite.
Higher positive values in the table suggest rising momentum in that asset, which contributes positively to the composite RASI. Conversely, negative values signal declining momentum. You can use these individual readings to see which sectors are driving the current risk sentiment and to time entries and exits accordingly.
Customization:
The indicator allows you to adjust the table's background color, text color, text size, cell padding, and position so it remains readable and unobtrusive regardless of your chart theme.
Use the BitDoctor Risk Appetite Dashboard as part of a broader analysis to align your trades with prevailing risk conditions. It is not a standalone trading signal but a context tool to support better decision-making.
Why these assets were chosen:
The dashboard uses a carefully selected mix of widely-followed proxies for global risk sentiment:
- SPY : Represents large-cap US equity market performance, a key barometer of investor confidence.
- HYG : Tracks high-yield corporate bonds, reflecting credit risk appetite in fixed income markets.
- EEM : Captures emerging market equities, which are highly sensitive to global risk-on/off dynamics.
- 1/UST10Y : The inverse of the US 10-year Treasury yield, as falling yields often accompany risk-on moves and vice versa.
- ETH : Ethereum as a representative crypto asset, offering insight into speculative risk appetite in digital assets.
This mix provides a comprehensive view of sentiment across traditional and alternative markets, making the dashboard a robust tool for gauging overall risk appetite.
Fractal Pullback Market StructureFractal Pullback Market Structure
Author: The_Forex_Steward
License: Mozilla Public License 2.0
The Fractal Pullback Market Structure indicator is a sophisticated price action tool designed to visualize internal structure shifts and break-of-structure (BoS) events with high accuracy. It leverages fractal pullback logic to identify market swing points and confirm whether a directional change has occurred.
This indicator detects swing highs and lows based on fractal behavior, drawing zigzag lines to connect these key pivot points. It classifies and labels each structural point as either a Higher High (HH), Higher Low (HL), Lower High (LH), or Lower Low (LL). Internal shifts are marked using triangle symbols on the chart, distinguishing bullish from bearish developments.
Break of Structure events are confirmed when price closes beyond the most recent swing high or low, and a horizontal line is drawn at the breakout level. This helps traders validate when a structural trend change is underway.
Users can configure the lookback period that defines the sensitivity of the pullback detection, as well as a timeframe multiplier to align the logic with higher timeframes such as 4H or Daily. There are visual customization settings for the zigzag lines and BoS markers, including color, width, and style (solid, dotted, or dashed).
Alerts are available for each key structural label—HH, HL, LH, LL—as well as for BoS events. These alerts are filtered through a selectable alert mode that separates signals by timeframe category: Low Timeframe (LTF), Medium Timeframe (MTF), and High Timeframe (HTF). Each mode allows the user to receive alerts only when relevant to their strategy.
This indicator excels in trend confirmation and reversal detection. Traders can use it to identify developing structure, validate internal shifts, and anticipate breakout continuation or rejection. It is particularly useful for Smart Money Concept (SMC) traders, swing traders, and those looking to refine entries and exits based on price structure rather than lagging indicators.
Visual clarity, adaptable timeframe logic, and precise structural event detection make this tool a valuable addition to any price action trader’s toolkit.
Economy RadarEconomy Radar — Key US Macro Indicators Visualized
A handy tool for traders and investors to monitor major US economic data in one chart.
Includes:
Inflation: CPI, PCE, yearly %, expectations
Monetary policy: Fed funds rate, M2 money supply
Labor market: Unemployment, jobless claims, consumer sentiment
Economy & markets: GDP, 10Y yield, US Dollar Index (DXY)
Options:
Toggle indicators on/off
Customizable colors
Tooltips explain each metric (in Russian & English)
Perfect for spotting economic cycles and supporting trading decisions.
Add to your chart and get a clear macro picture instantly!
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
Monday Swing Box# Monday Swing Box Indicator - Trading Applications
This "Monday Swing Box" indicator can be very useful in trading for several strategic reasons:
## 1. **"Monday Effect" Analysis**
* **Concept**: Mondays often have particular characteristics in the markets (opening gaps, weekend catch-up, different volumes)
* **Utility**: Allows visualization and quantification of these Monday-specific movements
* **Application**: Helps identify recurring patterns in your strategy
## 2. **Relative Volatility Measurement with ATR**
* **The ATR percentage tells you**:
* **< 50%**: Low volatility Monday (possible consolidation)
* **50-100%**: Normal volatility
* **> 100%**: Very volatile Monday (important event, potential breakout)
* **Advantage**: Contextualizes the movement relative to historical volatility
## 3. **Practical Trading Applications**
### **For Day Trading**:
* **Entry**: A Monday with >150% ATR may signal a strong movement to follow
* **Stop Loss**: Adjust stop sizes according to Monday's volatility
* **Targets**: Calibrate targets according to the movement's magnitude
### **For Swing Trading**:
* **Support/Resistance**: Monday's high/low often become key levels
* **Breakout**: Breaking above/below Monday's box may signal continuation
* **Retracement**: Return to Monday's box = support/resistance zone
### **For Risk Management**:
* **Sizing**: Adapt position sizes according to measured volatility
* **Timing**: Avoid trading abnormally volatile Mondays if you prefer stability
## 4. **Specific Possible Strategies**
### **"Monday Breakout"**:
* Wait for a break above/below Monday's box
* Enter in the direction of the breakout
* Stop at the other end of the box
### **"Monday Reversal"**:
* If Monday shows >200% ATR, look for a reversal
* The box becomes a resistance/support zone
### **"Monday Range"**:
* Trade bounces off the box limits
* Particularly effective if ATR % is normal (50-100%)
## 5. **Visualization Advantages**
* **Historical**: See past patterns across multiple Mondays
* **Comparison**: Compare current volatility to previous Mondays
* **Anticipation**: Prepare your strategy according to the type of Monday observed
## 6. **Limitations to Consider**
* Monday patterns can vary according to markets and periods
* Don't trade solely on this indicator, but use it as a complement
* Consider macroeconomic context and news
This indicator is therefore particularly useful for traders who want to exploit Monday's specificities and have an objective measure of this day's relative volatility compared to normal market conditions.
Intradayscanner – Institutional Interest (vs. RSP)This indicator measures volatility-adjusted Relative Residual Strength (RRS) of any symbol versus RSP (the Invesco S&P 500® Equal Weight ETF) to surface potential institutional interest overlooked by cap-weighted benchmarks.
Equal-weighted benchmark: Uses RSP instead of SPY, so each S&P 500 component carries equal influence—highlighting broad institutional flows beyond the largest names.
ATR normalization: Computes a “Divergence Index” by dividing RSP’s price move by its ATR(14), then adjusts the symbol’s move by that index and rescales by its own ATR(14). This isolates true outperformance.
Residual focus: RRS represents the portion of a symbol’s move unexplained by broad-market action, making it easier to spot when institutions rotate into specific stocks.
Visualization: Plots RRS as green/red histogram bars and overlays a 14-period EMA for trend smoothing.
Signalgo XSignalgo X
Signalgo X is a sophisticated indicator crafted for traders who demand a disciplined, multi-layered approach to market analysis and trade management. This overview will help you understand its capabilities, logic, and how it can elevate your trading.
Core Concept
Signalgo X is built to:
Scan multiple timeframes simultaneously for price, volume, and volatility patterns.
Filter out unreliable signals during periods of market hype or manipulation.
Automate trade management with dynamic take-profit (TP), stop-loss (SL), and trailing logic.
Deliver actionable, visual signals and alerts for timely, confident decisions.
Inputs & Controls
Preset System Parameters:
News Sensitivity: Determines how responsive the indicator is to price moves.
Hype Filter Strength: Sets how aggressively the system avoids volatile, manipulated, or news-driven periods.
User-Configurable:
Show TP/SL Logic: Turn on/off the display of take-profit and stop-loss levels directly on your chart.
How Signalgo X Works
1. Multi-Timeframe Market Analysis
Signalgo X continuously monitors:
Closing price
Trading volume
Volatility (ATR)
across six distinct timeframes, from 1 hour to 3 months. This layered approach ensures that signals are validated by both short-term momentum and long-term trends.
2. Price, Volume, and Volatility Synthesis
Price Change: The system tracks percentage changes over each timeframe to gauge momentum.
Volume Ratio: By comparing current volume to a moving average, it detects unusual spikes that may signal institutional activity or manipulation.
Volatility: Measures the intensity of price movements relative to average ranges, helping to identify breakout or exhaustion scenarios.
3. Proprietary Anti-Hype Filter
A unique scoring mechanism evaluates:
Volume spikes without corresponding price action
Sudden jumps in volatility
Conflicting signals across timeframes
Social hype proxies (e.g., sharp moves on low volume)
If the market is deemed “hyped,” all trading signals are suppressed and a clear warning is shown, keeping you out of unpredictable conditions.
4. Signal Classification & Mapping
Significant Moves: Only price actions that exceed a sensitivity threshold and are confirmed by volume/volatility are considered.
Bullish/Bearish Signals: Generated for each timeframe.
Signal Strength: Categorized as regular, or strong based on multi-timeframe agreement.
Entry & Exit Strategy
Entry Logic
Long (Buy) Entry: Triggered when bullish signals are detected (of any strength) and no hype is present.
Short (Sell) Entry: Triggered when bearish signals are detected and no hype is present.
Exit & Trade Management
Stop Loss (SL): Placed at a calculated distance from entry, adapting to recent volatility.
Take Profits (TP1, TP2, TP3): Three profit targets, each at a greater reward multiple.
Trailing Stop: After the first take-profit is hit, the stop-loss moves to breakeven and a trailing stop is activated to protect further gains.
Event Tracking: The indicator visually marks when each TP or SL is hit, providing real-time feedback.
Chart Plots: All relevant SL, TP, and trailing stop levels are clearly marked for both long and short trades.
Labels: Entry, exit, and signal strength events are color-coded and visually prominent.
Alerts: Built-in alert conditions allow you to set up TradingView notifications for strong/regular buy/sell signals and hype warnings.
Trading Strategy Application
Multi-Timeframe Confirmation: Only strong signals confirmed by several timeframes are acted upon, reducing false positives.
Volume & Volatility Awareness: The indicator avoids low-quality, “fakeout” signals by requiring confirmation from both price and volume/volatility.
Hype Avoidance: Keeps you out of the market during news-driven or manipulated periods, helping to protect your capital.
Automated Discipline: The TP/SL logic enforces a rules-based exit strategy, helping you lock in profits and limit losses without emotional interference.
Who Should Use Signalgo X?
Signalgo X is ideal for traders who want:
Systematic, high-confidence signals
Automated and disciplined trade management
Protection against unpredictable market events
Clear, actionable visuals and alerts
AD Line of S&P SectorsAdvance-Decline Line of S&P 500 Sectors
This indicator tracks the breadth strength of the S&P 500 by combining an unweighted Advance-Decline (A/D) Line and a market-cap weighted A/D Histogram across all 11 major S&P sectors.
Key Features
Sector A/D Histogram: Measures sector breadth based on whether each sector advanced or declined, then weights it by its current estimated market cap share.
Unweighted A/D Line: Smooth average of sectors equally weighted, giving an alternative breadth view that’s less biased by large sectors.
Top Weighted Stocks Tracker: Tracks the daily percentage change of the top 10 highest-weighted S&P 500 stocks, scaled by their index weights, and overlays them as a background area plot.
Zero Crossovers: Histogram and line crossing zero can help highlight broadening strength or weakness.
Customizable Sector Weights: Sector weights can be adjusted in the settings. It is recommended to review and update these periodically to reflect changes in S&P sector allocations.
Repaint Option: Uses a user-selectable repaint mode for flexible bar update logic.
How to Use
Trend Confirmation: When the weighted histogram and unweighted line are above zero together, it indicates broad sector strength; below zero suggests broad weakness.
Neutral Zone: Values between +0.5 and -0.5 (or your custom thresholds) may imply a ranging market or slower movement.
Top Names Context: The top-weighted stocks area shows how much the index’s largest components are pulling the market up or down, relative to the broader sector breadth.
⚠️ Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice. Always do your own research and consult with a qualified financial professional before making trading decisions. Use at your own risk.
Delta Spike Detector [GSK-VIZAG-AP-INDIA]📌 Delta Spike Detector – Volume Imbalance Ratio
By GSK-VIZAG-AP-INDIA
📘 Overview
This indicator highlights aggressive buying or selling activity by analyzing the imbalance between estimated Buy and Sell volume per candle. It flags moments when one side dominates the other significantly — defined by user-selectable volume ratio thresholds (10x, 15x, 20x, 25x).
📊 How It Works
Buy/Sell Volume Estimation
Approximates buyer and seller participation using candle structure:
Buy Volume = Proximity of close to low
Sell Volume = Proximity of close to high
Delta & Delta Ratio
Delta = Buy Volume − Sell Volume
Delta Ratio = Ratio of dominant volume side to the weaker side
When this ratio exceeds a threshold, it’s classified as a spike.
Spike Labels
Labels are plotted on the chart:
10x B, 15x B, 20x B, 25x B → Buy Spike Labels (below candles)
10x S, 15x S, 20x S, 25x S → Sell Spike Labels (above candles)
The color of each label reflects the spike strength.
⚙️ User Inputs
Enable/Disable Buy or Sell Spikes
Set custom delta ratio thresholds (default: 10x, 15x, 20x, 25x)
🎯 Use Cases
Spotting sudden aggressive activity (e.g. smart money moves, traps, breakouts)
Identifying short-term market exhaustion or momentum bursts
Complementing other trend or volume-based tools
⚠️ Important Notes
The script uses approximated Buy/Sell Volume based on price position, not actual order flow.
This is not a buy/sell signal generator. It should be used in context with other confirmation indicators or market structure.
✍️ Credits
Developed by GSK-VIZAG-AP-INDIA
For educational and research use only.
Jags Dynamic S/R with Breakout & Weakness SignalsThis script is designed to automatically identify and display significant support and resistance levels on your chart. It then goes a step further by actively monitoring for potential breakouts and signs of support weakness.
Core Functionality: Identifying Key Levels
At its heart, the script uses a pivot logic to find recent price highs and lows, which it then plots as horizontal lines representing potential resistance and support, respectively. You have full control over how these levels are identified:
Timeframe: You can choose to find these pivot points on the current chart's timeframe or a higher one (e.g., daily pivots on an hourly chart).
Lookback Period: You can define how many bars to the left and right of a pivot point the script should consider, allowing you to fine-tune the significance of the levels it identifies.
Line Management: To keep your chart clean, you can set the maximum number of support and resistance lines to display. The script also has a clever "merge" feature that combines new pivot levels with existing ones if they are very close together, preventing clutter.
Breakout Detection
A key feature of this indicator is its ability to signal when the price breaks through one of these identified support or resistance levels. You can enable or disable this feature and choose from several confirmation methods to suit your trading style:
Simple Price Action: A breakout is confirmed simply by the price closing above a resistance level or below a support level.
ATR (Average True Range): For a breakout to be valid, the price must close a certain distance (based on the ATR) beyond the level, filtering out minor fluctuations.
Volume: This option adds another layer of confirmation by requiring a significant increase in trading volume during the breakout, suggesting strong conviction behind the move.
Momentum: This method uses the RSI (Relative Strength Index) to confirm that the breakout is supported by strong underlying momentum.
Quantitative: A more advanced option that uses a combination of the Rate of Change (ROC) and a Volume-Weighted Moving Average (VWMA) to provide a robust, multi-faceted confirmation of the breakout.
When a confirmed breakout occurs, the script will:
Color the breakout bar green for a bullish breakout (upward) or red for a bearish breakout (downward).
Place an arrow below a bullish breakout or above a bearish breakout.
Trigger an alert to notify you of the event.
Support Weakness Detection
To provide an early warning of a potential breakdown, the script includes a unique "Support Weakness Detection" feature. When enabled, it looks for a specific confluence of bearish signals as the price approaches a support level:
The price is hovering just above a key support level.
The short-term trend has already turned bearish (based on a moving average).
Momentum is fading (indicated by a falling RSI).
If all these conditions are met, a blue down-arrow will appear above the price bar, signalling that the nearby support may not hold.
Multi SMA AnalyzerMulti SMA Analyzer with Custom SMA Table & Advanced Session Logic
A feature-rich SMA analysis suite for traders, offering up to 7 configurable SMAs, in-depth trend detection, real-time table, and true session-aware calculations.
Ideal for those who want to combine intraday, swing, and higher-timeframe trend analysis with maximum chart flexibility.
Key Features
📊 Multi-SMA Overlay
- 7 SMAs (default: 5, 20, 50, 100, 200, 21, 34)—individually configurable (period, source, color, line style)
- Show/hide each SMA, custom line style (solid, stepline, circles), and color logic
- Dynamic color: full opacity above SMA, reduced when below
⏰ Session-Aware SMAs
- Each SMA can be calculated using only user-defined session hours/days/timezone
- “Ignore extended hours” option for accurate intraday trend
📋 Smart Data Table
- Live SMA values, % distance from price, and directional arrows (↑/↓/→)
- Bull/Bear/Sideways trend classification
- Custom table position, size, colors, transparency
- Table can run on chart or custom (higher) timeframe for multi-TF analysis
🎯 Golden/Death Cross Detection
- Flexible crossover engine: select any two from (5, 10, 20, 50, 100, 200) for fast/slow SMA cross signals
- Plots icons (★ Golden, 💀 Death), optional crossover labels with custom size/colors
🏷️ SMA Labels
- Optional on-chart SMA period labels
- Custom placement (above/below/on line), size, color, offset
🚨 Signal & Trend Engine
- Bull/Bear/Sideways logic: price vs. multiple SMAs (not just one pair)
- Volume spike detection (2x 20-period SMA)
- Bullish engulfing candlestick detection
- All signals can use chart or custom table timeframe
🎨 Visual Customization
- Dynamic background color (Bull: green, Bear: red, Neutral: gray)
- Every visual aspect is customizable: label/table colors, transparency, size, position
🔔 Built-in Alerts
- Crossovers (SMA20/50, Golden/Death)
- Bull trend, volume spikes, engulfing pattern—all alert-ready
How It Works
- Session Filtering:
- SMAs can be set to count only bars from your chosen market session, for true intraday/trading-hour signals
Dynamic Table & Signals:
- Table and all signal logic run on your selected chart or custom timeframe
Flexible Crossover:
- Choose any pair (5, 10, 20, 50, 100, 200) for cross detection—SMA 10 is available for crossover even if not shown as an SMA line
Everything is modular:
- Toggle features, set visuals, and alerts to your workflow
🚨 How to Use Alerts
- All key signals (crossovers, trend shifts, volume spikes, engulfing patterns) are available as alert conditions.
To enable:
- Click the “Alerts” (clock) icon at the top of TradingView.
- Select your desired signal (e.g., “Golden Cross”) from the condition dropdown.
- Set your alert preferences and create the alert.
- Now, you’ll get notified automatically whenever a signal occurs!
Perfect For
- Multi-timeframe and swing traders seeking higher timeframe SMA confirmation
- Intraday traders who want to ignore pre/post-market data
- Anyone wanting a modern, powerful, fully customizable multi-SMA overlay
// P.S: Experiment with Golden Cross where Fast SMA is 5 and Slow SMA is 20.
// Set custom timeframe for 4 hr while monitoring your chart on 15 min time frame.
// Enable Background Color and Use Table Timeframe for Background.
// Uncheck Pine labels in Style tab.
Clean, open-source, and loaded with pro features—enjoy!
Like, share, and let me know if you'd like any new features added.
Floor and Roof Indicator with SignalsFloor and Roof Indicator with Trading Signals
A comprehensive support and resistance indicator that identifies premium and discount zones with automated signal generation.
Key Features:
Dynamic Support/Resistance Zones: Calculates floor (support) and roof (resistance) levels using price action and volatility
Premium/Discount Zone Identification: Highlights areas where price may find resistance or support
Customizable Signal Frequency: Control how often signals are displayed (every Nth occurrence)
Visual Signal Table: Optional table showing the last 5 long and short signal prices
Multiple Timeframe Compatibility: Works across all timeframes
Technical Details:
Uses ATR-based calculations for dynamic zone width adjustment
Combines Bollinger Bands with highest/lowest price analysis
Smoothing options for cleaner signal generation
Fully customizable colors and display options
How to Use:
Floor Zones (Blue): Potential support areas where long positions may be considered
Roof Zones (Pink): Potential resistance areas where short positions may be considered
Signal Crosses: Visual markers when price interacts with key levels
Signal Table: Track recent signal prices for analysis
Settings:
Length: Period for calculations (default: 200)
Smooth: Smoothing factor for cleaner signals
Zone Width: Adjust the thickness of support/resistance zones
Signal Frequency: Control signal display frequency
Visual Options: Customize colors and table position
Alerts Available:
Long signal alerts when price touches discount zones
Short signal alerts when price reaches premium zones
Educational Purpose: This indicator is designed to help traders identify potential support and resistance areas. Always combine with proper risk management and additional analysis.
This description focuses on the technical aspects and educational value while avoiding any language that could be interpreted as financial advice or guaranteed profits.
THE HISTORY By [VXN]
THE HISTORY By - Monthly Seasonal Analysis Indicator
Development Status: This indicator is currently in the development phase and is not yet finished. Features and functionality may change as development continues.
Overview:
This indicator provides comprehensive historical analysis of monthly price patterns, designed to help traders identify recurring seasonal behaviors and market tendencies for the current month across multiple years of data.
Key Features:
Historical Data Analysis:
- Analyzes up to 10 years of historical performance for the current month
- Calculates monthly returns, win rates, and statistical metrics
- Tracks maximum drawdowns and runups for risk assessment
- Requires daily timeframe for accurate monthly calculations
Pattern Recognition:
- Implements a three-period classification system that breaks each month into segments
- Uses visual indicators (🟢🔴🟡) to represent bullish, bearish, and neutral periods
- Helps identify recurring intra-month behavior patterns
Statistical Display:
- Presents historical data in an organized table format
- Shows year-by-year performance comparisons
- Calculates average returns, best/worst performance, and confidence levels
- Displays overall market bias (bullish/bearish tendency) for the current month
Dynamic Zone Overlays:
- Projects Fibonacci-based support/resistance levels based on historical volatility
- Adjusts zone positioning based on the month's historical bias
- Provides visual reference points for potential price targets or reversal areas
Practical Applications:
- Seasonal trading strategy development
- Risk management through historical context
- Understanding market cyclicality and recurring patterns
- Educational tool for studying price behavior over time
Note: This indicator is designed for analysis and education purposes, helping traders understand historical market patterns rather than providing direct trading signals. The data should be used in conjunction with other forms of analysis and proper risk management. As this is still under development, please expect updates and refinements to functionality.
xGhozt Wickless Candle Streak ProbabilityThe xGhozt Wickless Candle Streak Probability is a custom Pine Script indicator designed to identify and quantify the occurrence of consecutive "wickless" candles of the same trend (either bullish or bearish).
Key Features:
Wickless Candle Detection: It first identifies candles that lack an upper or lower wick (meaning their open/close is equal to their high/low, respectively).
Consecutive Streak Tracking: The indicator tracks how many wickless bullish candles occur in a row, and similarly for wickless bearish candles.
User-Defined Streak Length: You can specify a Streak Length in the indicator's settings. This defines how many consecutive wickless candles are needed to register a "streak."
Probability Calculation: For the chosen Streak Length, the indicator calculates the historical probability (as a percentage) of encountering such a streak for both bullish and bearish wickless candles. This is done by dividing the number of times a streak of that length has occurred by the total number of candles scanned.
On-Chart Display: The results, including the total wickless candles, total scanned candles, and the calculated streak probabilities, are displayed in a convenient table directly on your chart.
Purpose:
This indicator helps traders and analysts understand the historical likelihood of sustained, strong directional moves as indicated by consecutive wickless candles. By quantifying these probabilities, it can provide insights into potential continuation patterns or extreme market conditions, which might be useful for developing trading strategies or confirming market biases.
BANKNIFTY Contribution Table [GSK-VIZAG-AP-INDIA]1. Overview
This indicator provides a real-time visual contribution table of the 12 constituent stocks in the BANKNIFTY index. It displays key metrics for each stock that help traders quickly understand how each component is impacting the index at any given moment.
2. Purpose / Trading Use Case
The tool is designed for intraday and short-term traders who rely on index movement and its internal strength or weakness. By seeing which stocks are contributing positively or negatively, traders can:
Confirm trend strength or divergence within the index.
Identify whether a BANKNIFTY move is broad-based or driven by a few heavyweights.
Detect reversals when individual components decouple from index direction.
3. Key Features and Logic
Live LTP: Current price of each BANKNIFTY stock.
Price Change: Difference between current LTP and previous day’s close.
% Change: Percentage move from previous close.
Weight %: Static weight of each stock within the BANKNIFTY index (user-defined).
This estimates how much each stock contributes to the BANKNIFTY’s point change.
Sorted View: The stocks are sorted by their weight (descending), so high-impact movers are always at the top.
4. User Inputs / Settings
Table Position (tableLocationOpt):
Choose where the table appears on the chart:
top_left, top_right, bottom_left, or bottom_right.
This helps position the table away from your price action or indicators.
5. Visual and Plotting Elements
Table Layout: 6 columns
Stock | Contribution | Weight % | LTP | Change | % Change
Color Coding:
Green/red for positive/negative price changes and contributions.
Alternating background rows for better visibility.
BANKNIFTY row is highlighted separately at the top.
Text & Background Colors are chosen for both readability and direction indication.
6. Tips for Effective Use
Use this table on 1-minute or 5-minute intraday charts to see near real-time market structure.
Watch for:
A few heavyweight stocks pulling the index alone (can signal weak internal breadth).
Broad green/red across all rows (signals strong directional momentum).
Combine this with price action or volume-based strategies for confirmation.
Best used during market hours for live updates.
7. What Makes It Unique
Unlike other contribution tables that show only static data or require paid feeds, this script:
Updates in real time.
Uses dynamic calculated contributions.
Places BANKNIFTY at the top and presents the entire internal structure clearly.
Doesn’t repaint or rely on lagging indicators.
8. Alerts / Additional Features
No alerts are added in this version.
(Optional: Alerts can be added to notify when a certain stock contributes above/below a threshold.)
9. Technical Concepts Used
request.security() to pull both 1-minute and daily close data.
Conditional color formatting based on price change direction.
Dynamic table rendering using table.new() and table.cell().
Static weights assigned manually for BANKNIFTY stocks (can be updated if index weights change).
10. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a buy/sell recommendation.
Users should test and validate the tool on paper or demo accounts before applying it to live trading.
📌 Note: Due to internet connectivity, data delays, or broker feeds, real-time values (LTP, change, contribution, etc.) may slightly differ from other platforms or terminals. Use this indicator as a supportive visual tool, not a sole decision-maker.
Script Title: BANKNIFTY Contribution Table -
Author: GSK-VIZAG-AP-INDIA
Version: Final Public Release
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
Tsallis Entropy Market RiskTsallis Entropy Market Risk Indicator
What Is It?
The Tsallis Entropy Market Risk Indicator is a market analysis tool that measures the degree of randomness or disorder in price movements. Unlike traditional technical indicators that focus on price patterns or momentum, this indicator takes a statistical physics approach to market analysis.
Scientific Foundation
The indicator is based on Tsallis entropy, a generalization of traditional Shannon entropy developed by physicist Constantino Tsallis. The Tsallis entropy is particularly effective at analyzing complex systems with long-range correlations and memory effects—precisely the characteristics found in crypto and stock markets.
The indicator also borrows from Log-Periodic Power Law (LPPL).
Core Concepts
1. Entropy Deficit
The primary measurement is the "entropy deficit," which represents how far the market is from a state of maximum randomness:
Low Entropy Deficit (0-0.3): The market exhibits random, uncorrelated price movements typical of efficient markets
Medium Entropy Deficit (0.3-0.5): Some patterns emerging, moderate deviation from randomness
High Entropy Deficit (0.5-0.7): Strong correlation patterns, potentially indicating herding behavior
Extreme Entropy Deficit (0.7-1.0): Highly ordered price movements, often seen before significant market events
2. Multi-Scale Analysis
The indicator calculates entropy across different timeframes:
Short-term Entropy (blue line): Captures recent market behavior (20-day window)
Long-term Entropy (green line): Captures structural market behavior (120-day window)
Main Entropy (purple line): Primary measurement (60-day window)
3. Scale Ratio
This measures the relationship between long-term and short-term entropy. A healthy market typically has a scale ratio above 0.85. When this ratio drops below 0.85, it suggests abnormal relationships between timeframes that often precede market dislocations.
How It Works
Data Collection: The indicator samples price returns over specific lookback periods
Probability Distribution Estimation: It creates a histogram of these returns to estimate their probability distribution
Entropy Calculation: Using the Tsallis q-parameter (typically 1.5), it calculates how far this distribution is from maximum entropy
Normalization: Results are normalized against theoretical maximum entropy to create the entropy deficit measure
Risk Assessment: Multiple factors are combined to generate a composite risk score and classification
Market Interpretation
Low Risk Environments (Risk Score < 25)
Market is functioning efficiently with reasonable randomness
Price discovery is likely effective
Normal trading and investment approaches appropriate
Medium Risk Environments (Risk Score 25-50)
Increasing correlation in price movements
Beginning of trend formation or momentum
Time to monitor positions more closely
High Risk Environments (Risk Score 50-75)
Strong herding behavior present
Market potentially becoming one-sided
Consider reducing position sizes or implementing hedges
Extreme Risk Environments (Risk Score > 75)
Highly ordered market behavior
Significant imbalance between buyers and sellers
Heightened probability of sharp reversals or corrections
Practical Application Examples
Market Tops: Often characterized by gradually increasing entropy deficit as momentum builds, followed by extreme readings near the actual top
Market Bottoms: Can show high entropy deficit during capitulation, followed by normalization
Range-Bound Markets: Typically display low and stable entropy deficit measurements
Trending Markets: Often show moderate entropy deficit that remains relatively consistent
Advantages Over Traditional Indicators
Forward-Looking: Identifies changing market structure before price action confirms it
Statistical Foundation: Based on robust mathematical principles rather than empirical patterns
Adaptability: Functions across different market regimes and asset classes
Noise Filtering: Focuses on meaningful structural changes rather than price fluctuations
Limitations
Not a Timing Tool: Signals market risk conditions, not precise entry/exit points
Parameter Sensitivity: Results can vary based on the chosen parameters
Historical Context: Requires some historical perspective to interpret effectively
Complementary Tool: Works best alongside other analysis methods
Enjoy :)
