Tillson T3 Moving Average by KIVANÇ fr3762Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend.
The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions:
If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform.
Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions.
Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend.
And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend .
And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions.
I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses.
Developed by Tim Tillson
Pesquisar nos scripts por "moving average crossover"
MA Table [RanaAlgo]The "MA Table " indicator is a comprehensive and visually appealing tool for tracking moving average signals in TradingView. Here's a short summary of its usefulness:
Key Features:
Dual MA Support:
Tracks both EMA (Exponential Moving Average) and SMA (Simple Moving Average) signals (10, 20, 30, 50, 100 periods).
Users can toggle visibility for EMA/SMA separately.
Clear Signal Visualization:
Displays Buy (▲) or Sell (▼) signals based on price position relative to each MA.
Color-coded (green for buy, red for sell) for quick interpretation.
Customizable Table Design:
Adjustable position (9 placement options), colors, text size, and border styling.
Alternating row colors improve readability.
Optional MA Plots:
Can display the actual MA lines on the chart for visual confirmation (with distinct colors/styles).
Usefulness:
Quick Overview: The table consolidates multiple MA signals in one place, saving time compared to checking each MA individually.
Trend Confirmation: Helps confirm trend strength when multiple MAs align (e.g., price above all MAs → strong uptrend).
Flexible: Suitable for both short-term (10-20 period) and long-term (50-100 period) traders.
Aesthetic: Professional design enhances chart clarity without clutter.
Ideal For:
Traders who rely on moving average crossovers or price-MA relationships.
Multi-timeframe analysis when combined with other tools.
Beginners learning MA strategies (clear visual feedback).
52SIGNAL RECIPE Directional Consistency Index═══ 52SIGNAL RECIPE Directional Consistency Index (DCI) ═══
◆ Overview
52SIGNAL Directional Consistency Index (DCI) is a technical indicator that measures the directional consistency of market movements. This indicator focuses on the consistency of direction rather than the magnitude of price changes, analyzing the strength of market trends and providing more reliable trend analysis by filtering out noise to reflect only meaningful price movements.
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◆ Key Features
• Direction-Focused Analysis: Concentrates solely on directional consistency rather than magnitude of price changes
• Noise Filtering: Ignores insignificant price movements through minimum percentage change settings
• Trend Exhaustion Detection: Identifies potential trend reversals as values approach ±0.5 levels
• Intuitive Visualization: Instant recognition of trend direction through color changes based on rising/falling zones
• Multi-Market Application: Adaptable to various financial markets including stocks, cryptocurrencies, and forex
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◆ Technical Foundation
■ Directional Calculation
• Basic Principle: Counts only the up/down movement of each candle to measure directional consistency
• Calculation Method: Determines direction based on percentage change between current close and previous close
• Direction Values: Simplified into Rising (+1), Falling (-1), or Insignificant Change (0)
• Averaging: DCI calculated as the moving average of direction values over the specified period
■ Noise Filtering Mechanism
• Minimum Percentage Change: The minimum percent change required to consider a price movement significant
• Filtering Effect: Movements smaller than the minimum change are excluded from direction calculation (treated as 0)
• Enhanced Reliability: Adjustable filtering strength for optimization across different market environments
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◆ Practical Applications
■ Trend Identification & Reversal Prediction
• Early Uptrend Detection:
▶ When DCI enters the 0 to +0.3 range
▶ When recent directional consistency begins to consistently rise
• Early Downtrend Detection:
▶ When DCI enters the 0 to -0.3 range
▶ When recent directional consistency begins to consistently fall
• Trend Reversal Signals:
▶ When DCI approaches +0.5 (uptrend exhaustion, potential downward reversal)
▶ When DCI approaches -0.5 (downtrend exhaustion, potential upward reversal)
■ Trading Strategy Implementation
• Trend Following Strategies:
▶ Consider buying when DCI crosses above the 0 line
▶ Consider selling when DCI crosses below the 0 line
• Reversal Trading:
▶ Consider taking profits or short positions when DCI approaches +0.5
▶ Consider long positions when DCI approaches -0.5
• Divergence Confirmation:
▶ Weakening uptrend signal when price rises but DCI weakens
▶ Weakening downtrend signal when price falls but DCI strengthens
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◆ Advanced Setting Options
■ Period (Length) Settings
• Short-term Analysis: 5-10 days (faster signals, more sensitive responses)
• Medium-term Analysis: 10-20 days (balanced signals, recommended default)
• Long-term Analysis: 20-30 days (slower signals, long-term trend identification)
■ Minimum Percentage Change Settings
• Low Volatility Markets: 0.05-0.2% (suitable for forex markets)
• Medium Volatility Markets: 0.3-0.5% (suitable for stock markets)
• High Volatility Markets: 0.5-1.0% (suitable for cryptocurrency markets)
■ Settings by Trading Style
• Scalping: Lower period (5-10), lower minimum change (0.05-0.1%)
• Day Trading: Medium period (10-15), medium minimum change (0.2-0.3%)
• Swing Trading: Higher period (15-25), higher minimum change (0.3-0.5%)
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◆ Synergy with Other Indicators
• Moving Averages: Strengthen signals by confirming moving average crossovers when DCI crosses the 0 line
• RSI: Combine DCI trend direction with RSI overbought/oversold levels to confirm entry points
• MACD: Enhance reliability by pairing DCI directional signals with MACD momentum confirmation
• Bollinger Bands: Analyze volatility by checking Bollinger Band expansion/contraction when DCI approaches ±0.5
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◆ Conclusion
52SIGNAL Directional Consistency Index (DCI) is a powerful tool for objectively measuring market directionality and visualizing trend strength. The noise filtering through minimum percentage change settings can be adjusted to match your trading style and market characteristics for optimal results. Its ability to identify early trend stages and detect overextended zones provides traders with important entry and exit points. When used in conjunction with other technical indicators, it can significantly enhance the reliability of trading decisions.
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※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══ 52SIGNAL 방향성 일관성 지수 (DCI) ═══
◆ 개요
52SIGNAL 방향성 일관성 지수(DCI)는 시장의 방향성 일관성을 측정하는 기술적 지표입니다. 이 지표는 가격 변화의 크기가 아닌 방향의 일관성에 중점을 두어 시장의 추세 강도를 분석하고, 노이즈 필터링 기능을 통해 의미 있는 가격 변동만을 반영하여 더 신뢰할 수 있는 추세 분석을 제공합니다.
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◆ 주요 특징
• 방향성 중심 분석: 가격 변화의 크기가 아닌 방향성에만 집중하여 추세의 일관성 측정
• 노이즈 필터링: 최소 변화율 설정을 통해 의미 없는 작은 가격 변동을 무시
• 추세 과열 감지: ±0.5 수준에 접근할 때 추세 전환 가능성 식별
• 직관적인 시각화: 상승/하락 구간에 따른 색상 변화로 추세 방향 즉각 인식
• 다양한 시장 적용: 주식, 암호화폐, 외환 등 다양한 금융 시장에 적용 가능
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◆ 기술적 기반
■ 방향성 계산
• 기본 원리: 각 캔들의 상승/하락 여부만 카운트하여 방향의 일관성 측정
• 계산 방법: 현재 종가와 이전 종가의 퍼센트 변화를 기준으로 방향 판단
• 방향 값: 상승(+1), 하락(-1), 의미 없는 변화(0)로 단순화
• 평균화: 설정된 기간 동안의 방향 값의 이동평균으로 DCI 산출
■ 노이즈 필터링 메커니즘
• 최소 변화율: 의미 있는 가격 변동으로 인정할 최소 퍼센트 변화
• 필터링 효과: 최소 변화율보다 작은 변동은 방향 계산에서 제외(0으로 처리)
• 신뢰도 향상: 필터링 강도 조절을 통해 다양한 시장 환경에 최적화 가능
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◆ 실용적 응용
■ 추세 식별 및 전환점 예측
• 상승 추세 초입:
▶ DCI가 0에서 +0.3 사이로 진입할 때
▶ 최근 방향성이 일관되게 상승하기 시작할 때
• 하락 추세 초입:
▶ DCI가 0에서 -0.3 사이로 진입할 때
▶ 최근 방향성이 일관되게 하락하기 시작할 때
• 추세 전환 신호:
▶ DCI가 +0.5에 가까워질 때 (상승 추세 과열, 하락 전환 가능성)
▶ DCI가 -0.5에 가까워질 때 (하락 추세 과열, 상승 전환 가능성)
■ 트레이딩 전략 적용
• 추세 추종 전략:
▶ DCI가 0선을 위로 돌파할 때 매수 고려
▶ DCI가 0선을 아래로 돌파할 때 매도 고려
• 반전 트레이딩:
▶ DCI가 +0.5에 근접할 때 이익실현 또는 매도 포지션 고려
▶ DCI가 -0.5에 근접할 때 매수 포지션 고려
• 다이버전스 확인:
▶ 가격은 상승하나 DCI가 약화될 때 상승 추세 약화 신호
▶ 가격은 하락하나 DCI가 강화될 때 하락 추세 약화 신호
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◆ 고급 설정 옵션
■ 기간(Length) 설정
• 단기 분석: 5-10일 (빠른 신호, 민감한 반응)
• 중기 분석: 10-20일 (균형 잡힌 신호, 기본 권장)
• 장기 분석: 20-30일 (느린 신호, 장기 추세 식별)
■ 최소 변화율(Minimum % Change) 설정
• 저변동성 시장: 0.05-0.2% (외환 시장에 적합)
• 중변동성 시장: 0.3-0.5% (주식 시장에 적합)
• 고변동성 시장: 0.5-1.0% (암호화폐 시장에 적합)
■ 트레이딩 스타일별 설정
• 스캘핑: 낮은 기간(5-10), 낮은 최소 변화율(0.05-0.1%)
• 데이 트레이딩: 중간 기간(10-15), 중간 최소 변화율(0.2-0.3%)
• 스윙 트레이딩: 높은 기간(15-25), 높은 최소 변화율(0.3-0.5%)
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◆ 다른 지표와의 시너지
• 이동평균선: DCI가 0선을 돌파할 때 이동평균 교차 확인으로 신호 강화
• RSI: DCI의 추세 방향과 RSI의 과매수/과매도 수준을 결합하여 진입점 확인
• MACD: DCI의 방향성 신호와 MACD의 모멘텀 확인을 결합하여 신뢰도 향상
• 볼린저 밴드: DCI가 ±0.5에 근접할 때 볼린저 밴드 확장/수축 확인으로 변동성 분석
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◆ 결론
52SIGNAL 방향성 일관성 지수(DCI)는 시장의 방향성을 객관적으로 측정하고 추세의 강도를 시각화하는 강력한 도구입니다. 최소 변화율 설정을 통한 노이즈 필터링은 각자의 트레이딩 성향과 시장 특성에 맞게 조정할 수 있어 최적의 효과를 누릴 수 있습니다. 추세의 초기 단계를 식별하고 과열 구간을 감지하는 능력은 트레이더에게 중요한 진입 및 퇴출 포인트를 제공합니다. 다른 기술적 지표와 함께 사용하면 트레이딩 결정의 신뢰도를 크게 향상시킬 수 있습니다.
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※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
52SIGNAL RECIPE RSI Linreg Bands═══ 52SIGNAL RECIPE RSI Linreg Bands ═══
◆ Overview
52SIGNAL RECIPE RSI Linreg Bands is an advanced technical indicator that combines the RSI (Relative Strength Index) with Linear Regression Bands. This indicator visualizes the volatility of the RSI using linear regression bands, helping to clearly identify overbought/oversold areas and more accurately capture potential trend reversal points.
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◆ Key Features
• RSI-Based Overbought/Oversold Analysis: Uses the traditional RSI indicator to identify overbought/oversold conditions in the market
• Integrated Linear Regression Bands: Applies linear regression analysis to the RSI to visually represent the direction and strength of trends
• Dual Overbought/Oversold Levels: Sets overbought/oversold levels for both RSI and Linear Regression Bands to increase the accuracy of signals
• Advanced Visualization: Intuitive chart analysis is possible with color changes according to trend direction and clear band display
• Multiple Alert Settings: Alert functions for various conditions ensure you don't miss important trading moments
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◆ Technical Foundation
■ RSI (Relative Strength Index)
• Basic Settings: 14-period RSI with 5-period Weighted Moving Average (WMA) applied
• Calculation Method: Measures the relative strength of gains and losses, expressed as a value between 0-100
• Overbought/Oversold Levels: Default values set to 70 (overbought) and 30 (oversold)
■ Linear Regression Bands
• Period: Default value of 100 days
• Deviation: Default value of 2.5 standard deviations
• Center Line: The center line of the linear regression analysis for the RSI values
• Band Width: Displays the range of volatility around the center line based on the calculated standard deviation
• Overbought/Oversold Levels: Default values set to 85 (overbought) and 15 (oversold)
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◆ Practical Applications
■ Identifying Trading Signals
• Buy Signal:
▶ When the RSI falls below the oversold level (30)
▶ When the lower band of the Linear Regression Bands falls below the oversold level (15)
▶ When both conditions are met simultaneously (extreme oversold state) - a strong buy signal
• Sell Signal:
▶ When the RSI rises above the overbought level (70)
▶ When the upper band of the Linear Regression Bands rises above the overbought level (85)
▶ When both conditions are met simultaneously (extreme overbought state) - a strong sell signal
■ Trend Analysis
• Uptrend: When the linear regression center line is rising and the RSI is moving above the midline (50)
• Downtrend: When the linear regression center line is falling and the RSI is moving below the midline (50)
• Trend Strength: The wider the gap between the bands, the greater the volatility; the narrower, the more stable the trend
■ Divergence Confirmation
• Bearish Divergence: Price forms a new high, but the RSI is lower than the previous high (potential bearish signal)
• Bullish Divergence: Price forms a new low, but the RSI is higher than the previous low (potential bullish signal)
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◆ Advanced Setting Options
■ RSI Setting Adjustments
• RSI Source: Selectable options include Close (default), Open, High, Low, HL2, HLC3, OHLC4, etc.
• RSI Length: Adjust to lower values for short-term volatility, higher values for long-term trends
■ Linear Regression Setting Adjustments
• Period: Use lower values (20-50) for short-term analysis, higher values (100-200) for long-term analysis
• Deviation: Higher values create wider bands (more signals), lower values create narrower bands (more accurate signals)
■ Overbought/Oversold Level Adjustments
• RSI Levels: Adjust to more extreme values (80/20) in highly volatile markets
• Linear Regression Band Levels: Adjustable to 90/10 or 80/20 depending on market conditions
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◆ Synergy with Other Indicators
• Bollinger Bands: Use alongside Bollinger Bands on the price chart to compare price volatility with RSI volatility
• MACD: Use with MACD for momentum and trend confirmation
• Fibonacci Retracement: Check RSI Linreg Bands signals with key support/resistance levels
• Moving Averages: Combine moving average crossovers with RSI Linreg Bands signals to improve reliability
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◆ Conclusion
52SIGNAL RECIPE RSI Linreg Bands provides a powerful and accurate technical analysis tool by combining traditional RSI with linear regression analysis. The dual overbought/oversold system increases the accuracy of trading signals and clearly visualizes trend direction and strength to help traders make decisions. You can achieve optimal results by adjusting various settings to match your trading style and market conditions.
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※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE RSI 선형회귀 밴드 ═══
◆ 개요
52SIGNAL RECIPE RSI 선형회귀 밴드는 RSI(상대강도지수)와 선형회귀 밴드를 결합한 고급 기술적 지표입니다. 이 지표는 선형회귀 밴드를 사용하여 RSI의 변동성을 시각화하여 과매수/과매도 영역을 명확하게 식별하고 잠재적인 추세 반전 지점을 더 정확하게 포착하는 데 도움을 줍니다.
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◆ 주요 특징
• RSI 기반 과매수/과매도 분석: 전통적인 RSI 지표를 사용하여 시장의 과매수/과매도 상태를 식별
• 통합된 선형회귀 밴드: RSI에 선형회귀 분석을 적용하여 추세의 방향과 강도를 시각적으로 표현
• 이중 과매수/과매도 레벨: RSI와 선형회귀 밴드 모두에 과매수/과매도 레벨을 설정하여 신호의 정확도 향상
• 고급 시각화: 추세 방향에 따른 색상 변화와 명확한 밴드 표시로 직관적인 차트 분석 가능
• 다중 알림 설정: 다양한 조건에 대한 알림 기능으로 중요한 트레이딩 시점을 놓치지 않도록 보장
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◆ 기술적 기반
■ RSI (상대강도지수)
• 기본 설정: 14기간 RSI에 5기간 가중이동평균(WMA) 적용
• 계산 방법: 상승과 하락의 상대적 강도를 측정하여 0-100 사이의 값으로 표현
• 과매수/과매도 레벨: 기본값으로 70(과매수)과 30(과매도) 설정
■ 선형회귀 밴드
• 기간: 기본값 100일
• 편차: 기본값 2.5 표준편차
• 중심선: RSI 값에 대한 선형회귀 분석의 중심선
• 밴드 폭: 계산된 표준편차에 기반하여 중심선 주변의 변동성 범위 표시
• 과매수/과매도 레벨: 기본값으로 85(과매수)와 15(과매도) 설정
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◆ 실용적 응용
■ 트레이딩 신호 식별
• 매수 신호:
▶ RSI가 과매도 레벨(30) 아래로 떨어질 때
▶ 선형회귀 밴드의 하단이 과매도 레벨(15) 아래로 떨어질 때
▶ 두 조건이 동시에 충족될 때(극단적 과매도 상태) - 강한 매수 신호
• 매도 신호:
▶ RSI가 과매수 레벨(70) 위로 상승할 때
▶ 선형회귀 밴드의 상단이 과매수 레벨(85) 위로 상승할 때
▶ 두 조건이 동시에 충족될 때(극단적 과매수 상태) - 강한 매도 신호
■ 추세 분석
• 상승 추세: 선형회귀 중심선이 상승하고 RSI가 중간선(50) 위로 움직일 때
• 하락 추세: 선형회귀 중심선이 하락하고 RSI가 중간선(50) 아래로 움직일 때
• 추세 강도: 밴드 사이의 간격이 넓을수록 변동성이 크고, 좁을수록 추세가 안정적
■ 다이버전스 확인
• 약세 다이버전스: 가격이 신고점을 형성하지만 RSI가 이전 고점보다 낮을 때(잠재적 약세 신호)
• 강세 다이버전스: 가격이 신저점을 형성하지만 RSI가 이전 저점보다 높을 때(잠재적 강세 신호)
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◆ 고급 설정 옵션
■ RSI 설정 조정
• RSI 소스: 선택 가능한 옵션에는 종가(기본값), 시가, 고가, 저가, HL2, HLC3, OHLC4 등이 포함
• RSI 길이: 단기 변동성을 위해 낮은 값으로, 장기 추세를 위해 높은 값으로 조정
■ 선형회귀 설정 조정
• 기간: 단기 분석을 위해 낮은 값(20-50), 장기 분석을 위해 높은 값(100-200) 사용
• 편차: 높은 값은 더 넓은 밴드(더 많은 신호), 낮은 값은 더 좁은 밴드(더 정확한 신호) 생성
■ 과매수/과매도 레벨 조정
• RSI 레벨: 변동성이 큰 시장에서는 더 극단적인 값(80/20)으로 조정
• 선형회귀 밴드 레벨: 시장 상황에 따라 90/10 또는 80/20으로 조정 가능
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◆ 다른 지표와의 시너지
• 볼린저 밴드: 가격 차트의 볼린저 밴드와 함께 사용하여 가격 변동성과 RSI 변동성 비교
• MACD: 모멘텀과 추세 확인을 위해 MACD와 함께 사용
• 피보나치 되돌림: RSI 선형회귀 밴드 신호를 주요 지지/저항 레벨과 함께 확인
• 이동평균선: 이동평균 교차와 RSI 선형회귀 밴드 신호를 결합하여 신뢰성 향상
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◆ 결론
52SIGNAL RECIPE RSI 선형회귀 밴드는 전통적인 RSI와 선형회귀 분석을 결합하여 강력하고 정확한 기술적 분석 도구를 제공합니다. 이중 과매수/과매도 시스템은 트레이딩 신호의 정확도를 높이고 추세 방향과 강도를 명확하게 시각화하여 트레이더의 의사 결정을 돕습니다. 다양한 설정을 트레이딩 스타일과 시장 상황에 맞게 조정하여 최적의 결과를 얻을 수 있습니다.
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※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
Waldo Momentum Cloud Bollinger Bands (WMCBB)
Title: Waldo Momentum Cloud Bollinger Bands (WMCBB)
Description:
Introducing the "Waldo Momentum Cloud Bollinger Bands (WMCBB)," an innovative trading tool crafted for those who aim to deepen their market analysis by merging two dynamic technical indicators: Dynamic RSI Bollinger Bands and the Waldo Cloud.
What is this Indicator?
WMCBB integrates the volatility-based traditional Bollinger Bands with a momentum-sensitive approach through the Relative Strength Index (RSI). Here’s how it works:
Dynamic RSI Bollinger Bands: These bands dynamically adjust according to the RSI, which tracks the momentum of price movements. By scaling the RSI to align with price levels, we generate bands that not only reflect market volatility but also the underlying momentum, offering a refined view of overbought and oversold conditions.
Waldo Cloud: This feature adds a layer of traditional Bollinger Bands, visualized as a 'cloud' on your chart. It employs standard Bollinger Band methodology but enhances it with additional moving average layers to better define market trends.
The cloud's color changes dynamically based on various market conditions, providing visual signals for trend direction and potential trend reversals.
Why Combine These Indicators?
Combining Dynamic RSI Bollinger Bands with the Waldo Cloud in WMCBB aims to:
Enhance Trend Identification: The Waldo Cloud's color-coded system aids in recognizing the overarching market trend, while the Dynamic RSI Bands give insights into momentum changes within that trend, offering a comprehensive view.
Improve Volatility and Momentum Analysis: While traditional Bollinger Bands measure market volatility, integrating RSI adds a layer of momentum analysis, potentially leading to more accurate trading signals.
Visual Clarity: The unified color scheme for both sets of bands, which changes according to RSI levels, moving average crossovers, and price positioning, simplifies the process of gauging market sentiment at a glance.
Customization: Users have the option to toggle the visibility of moving averages (MA) through the settings, allowing for tailored analysis based on individual trading strategies.
Usage:
Utilize WMCBB to identify potential trend shifts by observing price interactions with the dynamic bands or changes in the Waldo Cloud's color.
Watch for divergences between price movements and RSI to forecast potential market reversals or continuations.
This combination shines in sideways markets where traditional indicators might fall short, as it provides additional context through RSI momentum analysis.
Settings:
Customize parameters for both the Dynamic RSI and Waldo Cloud Bollinger Bands, including the calculation source, standard deviation factors, and moving average lengths.
WMCBB is perfect for traders seeking to enhance their market analysis through the synergy of momentum and volatility, all while maintaining visual simplicity. Trade with greater insight using the Waldo Momentum Cloud Bollinger Bands!
[blackcat] L1 Another Improved MACD IndicatorLevel: 1
Background
The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line.
Function
L1 Another Improved MACD Indicator improves MACD histogram by customized an algorithm and add three levels of long entry alerts derived from ema ().
Key Signal
diff --> classic MACD diff fast line in white
dea --> classic MACD dea slow line in yellow
macd --> classic difference histogram,but I did not use it directly in the plot.
macd1 --> ema3 of macd
Pros and Cons
Pros:
1. more clear sub level trend change with new histograms
Cons:
1. need sophisticated knowledge of MACD to use this well
2. this still requires a lot of MACD experience to obtain reliable trading signals
Remarks
Another improved MACD on histogram
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
ZenAlgo - Aggregated DeltaZenAlgo - Aggregated Delta is an advanced market analysis tool designed to provide traders with a holistic view of market sentiment by leveraging multi-exchange volume aggregation, cumulative delta analysis, and divergence detection. Unlike traditional indicators that rely on a single data source, this tool aggregates order flow data from multiple exchanges, reducing the impact of exchange-specific anomalies and liquidity disparities.
This indicator is ideal for traders looking to enhance their understanding of market dynamics, trend confirmations, and order flow patterns. By intelligently combining multiple analytical components, it eliminates the need for manually interpreting separate indicators and offers traders a streamlined approach to market analysis.
This indicator was inspired by aggregated volume analysis techniques. Independently developed with a focus on cumulative delta and divergence detection.
Key Features & Their Interaction
Multi-Exchange Volume Aggregation: Aggregates buy and sell volumes from up to nine major exchanges, including Binance, Bybit, Coinbase, and Kraken. Unlike traditional single-source indicators, this ensures a robust, diversified measure of market sentiment and smooths out exchange-specific volume fluctuations.
Cumulative Delta Analysis: Tracks the net difference between buy and sell volumes across all aggregated exchanges, helping traders identify true buying/selling pressure rather than misleading short-term volume spikes.
Advanced Divergence Detection: Unlike basic divergence indicators, this tool detects divergences not only between price and cumulative delta but also across multiple analytical layers, including moving averages and temperature zones, offering deeper confirmation signals.
Dynamic Market Temperature Zones: Unlike fixed overbought/oversold indicators, this feature applies adaptive standard deviation-based filtering to classify market conditions dynamically as "Extreme Hot," "Hot," "Neutral," "Cold," and "Extreme Cold."
Intelligent Market State Classification: Determines whether the market is in a Full Bull, Bearish, or Neutral state by analyzing multi-exchange volume flow, cumulative delta positioning, and market-wide liquidity trends.
Real-Time Alerts & Adaptive Visualization: Provides fully configurable real-time alerts for trend shifts, divergences, and market conditions, allowing traders to act immediately on high-confidence signals.
What Makes ZenAlgo - Aggregated Delta Unique?
Unlike free or open-source alternatives, ZenAlgo - Aggregated Delta applies a multi-layered data processing approach to smooth inconsistencies and improve signal reliability. Instead of using raw exchange feeds, the system incorporates adaptive volume aggregation and standard deviation-based market classification to ensure accuracy and reduce noise. These enhancements lead to more precise trend signals and a clearer representation of market sentiment.
Multi-Exchange Order Flow Validation: Unlike single-source indicators that rely on individual exchange feeds, this tool ensures cross-market consistency by aggregating volume data dynamically.
Fractal-Based Divergence Detection: Detects divergences using fractal logic rather than contextual volume trends, reducing false-positive divergence signals while maintaining accuracy.
Automated Sentiment Analysis: Classifies market sentiment into structured phases (Full Bull, Bearish, etc.), reducing the manual effort needed to interpret order flow trends.
How It Works (Technical Breakdown)
Multi-Exchange Volume Aggregation: The system fetches and validates buy/sell volume data from multiple exchanges, applying volume aggregation techniques to smooth out inconsistencies. It ensures that data from low-liquidity exchanges does not disproportionately influence the analysis.
Cumulative Delta Computation: Cumulative delta is computed as the net difference between buy and sell volumes over a given period. By summing up these values across multiple exchanges, traders can identify real accumulation or distribution zones, reducing false signals from isolated exchange anomalies.
Divergence Detection Methodology: The tool uses a fractal-based logic approach to detect high-confidence divergences across price, volume, and delta trends. This allows for a more structured detection process compared to simple peak/trough analysis, reducing noise in the signals.
Temperature Zones Filtering: Market conditions are dynamically classified using a rolling standard deviation model, ensuring that hot/cold states adjust automatically based on recent volatility levels. This means that instead of using arbitrary fixed thresholds, the tool adapts based on historical data behavior.
Market Sentiment State Calculation: The tool evaluates liquidity conditions, volume trends, and cumulative delta flow, categorizing the market into predefined states (Bullish, Bearish, Neutral). This helps traders assess the broader context of price movements rather than reacting to isolated signals.
Real-Time Adaptive Alerts: The system provides fully configurable alerts that notify traders about key trend shifts, high-confidence divergences, and changes in market conditions as they occur. This ensures that traders can make timely and well-informed decisions.
Why This Approach Works
By aggregating data from multiple exchanges, it reduces the impact of exchange-specific liquidity disparities and anomalies, leading to a more holistic view of order flow.
The cumulative delta analysis ensures that price movements are validated by actual buying/selling pressure, filtering out misleading short-term spikes.
Dynamic market classification adapts to current conditions rather than using outdated fixed thresholds, making it more relevant in different market regimes.
Fractal-based divergence detection avoids common pitfalls of traditional divergence analysis, reducing false signals while maintaining accuracy.
Combining real-time adaptive alerts with well-structured classification improves traders’ ability to respond to market shifts efficiently.
Practical Use Cases
Identifying High-Probability Trend Reversals: If cumulative delta shows bullish divergence while the market is in an Extreme Cold zone, it signals a strong potential for reversal.
Confirming Trend Continuation: When bullish moving average crossovers align with a rising cumulative delta, traders can enter positions with higher confidence.
Detecting Exhaustion in Market Moves: If price enters an "Extreme Hot" zone but cumulative delta starts declining, this suggests trend exhaustion and a possible reversal.
Filtering False Breakouts: If price breaks a resistance level but aggregated buy volume fails to increase, this invalidates the breakout, helping traders avoid bad trades.
Cross-Exchange Sentiment Confirmation: If cumulative delta on aggregated exchanges contradicts price action on an individual exchange, traders can identify localized exchange-based distortions.
Customization & Settings Overview
Exchange Selection: Traders can fine-tune exchange sources for aggregation, allowing for custom market-specific insights.
Adaptive Divergence Settings: Configure detection thresholds, lookback periods, and divergence filtering options to reduce noise and focus on high-confidence signals.
Moving Average Adjustments: Select custom MA types, lengths, and visualization preferences to match different trading styles.
Market Temperature Thresholds: Adjust hot/cold sensitivity to align with preferred risk levels and volatility expectations.
Configurable Alerts & Theme Customization: Full control over notification triggers, color themes, and label formatting to enhance user experience.
Important Considerations
Market Context Dependency: This tool provides order flow analysis, which should be used in conjunction with broader market context and risk management.
Data Source Variability: While multi-exchange aggregation improves reliability, some exchanges may report inaccurate or delayed data.
Extreme Volatility Handling: Large price swings can temporarily distort delta readings, so traders should always validate with additional context.
Liquidity Limitations: In low-liquidity conditions, order flow signals may be less reliable due to fragmented market participation.
UVR Crypto TrendINDICATOR OVERVIEW: UVR CRYPTO TREND
The UVR Crypto Trend indicator is a custom-built tool designed specifically for cryptocurrency markets, utilizing advanced volatility, momentum, and trend-following techniques. It aims to identify trend reversals and provide buy and sell signals by analyzing multiple factors, such as price volatility(UVR), RSI (Relative Strength Index), CMF (Chaikin Money Flow), and EMA (Exponential Moving Average). The indicator is optimized for CRYPTO MARKETS only.
KEY FEATURES AND HOW IT WORKS
Volatility Analysis with UVR
The UVR (Ultimate Volatility Rate) is a proprietary calculation that measures market volatility by comparing significant price extremes and smoothing the data over time.
Purpose: UVR aims to reduce noise in low-volatility environments and highlight significant movements during higher-volatility periods. While it strives to improve filtering in low-volatility conditions, it does not guarantee perfect performance, making it a balanced and adaptable tool for dynamic markets like cryptocurrency.
HOW UVR (ULTIMATE VOLATILITY RATE) IS CALCULATED
UVR is calculated using a method that ensures precise measurement of market volatility by comparing price extremes across consecutive candles:
Volatility Components:
Two values are calculated to represent potential price fluctuations:
The absolute difference between the current candle's high and the previous candle's low:
Volatility Component 1=∣High−Low ∣
The absolute difference between the previous candle's high and the current candle's low:
Volatility Component 2=∣High −Low∣
Volatility Ratio:
The larger of the two components is selected as the Volatility Ratio, ensuring UVR captures the most significant movement:
Volatility Ratio=max(Volatility Component 1,Volatility Component 2)
Smoothing with SMMA:
To stabilize the volatility calculation, the Volatility Ratio is smoothed using a Smoothed Moving Average (SMMA) over a user-defined period (e.g., 14 candles):
UVR=(UVR(Previous)×(Period−1)+Volatility Ratio)/Period
This calculation ensures UVR adapts dynamically to market conditions, focusing on significant price movements while filtering out noise.
RSI FOR MOMENTUM DETECTION
RSI (Relative Strength Index) identifies overbought and oversold conditions.
Trend Confirmation at the 50 Level
RSI values crossing above 50 signal the potential start of an upward trend.
RSI values crossing below 50 indicate the potential start of a downward trend.
Key Reversals at Extreme Levels
RSI detects trend reversals at overbought (>70) and oversold (<30) levels.
For example:
Overbought Trend Reversal: RSI >70 followed by bearish price action signals a potential downtrend.
Oversold Trend Reversal: RSI <30 with bullish confirmation signals a potential uptrend.
Rare Extreme RSI Readings
Extreme levels, such as RSI <12 (oversold) or RSI >88 (overbought), are used to identify rare yet powerful reversals.
---HOW IT DIFFERS FROM OTHER INDICATORS---
Using UVR High and Low Values
The Ultimate Volatility Rate (UVR) focuses on analyzing the high and low price ranges of the market to measure volatility.
Unlike traditional trend indicators that rely primarily on momentum or moving average crossovers, UVR leverages price extremes to better identify trend reversals.
This approach ensures fewer false signals during low-volatility phases and more accurate trend detection during high-volatility conditions.
UVR as the Core Component
The indicator is fundamentally built around UVR as the primary filter, while supporting tools like RSI (momentum detection), CMF (volume confirmation), and EMA (trend validation) complement its functionality.
By integrating these additional components, the indicator provides a multidimensional analysis rather than relying solely on a single approach.
Dynamic Adaptation to Volatility
UVR dynamically adjusts to market conditions, striving to improve filtering in low-volatility phases. While not flawless, this approach minimizes false signals and adapts more effectively to varying levels of market activity.
Trend Clouds for Visual Guidance
UVR-based dynamic clouds visually mark high and low price areas, highlighting potential consolidation or retracement zones.
These clouds serve as guides for setting stop-loss or take-profit levels, offering clear risk management strategies.
BUY AND SELL SIGNAL LOGIC
BUY CONDITIONS
Momentum-Based Buy-Entry
RSI >50, CMF >0, and the close price is above EMA50.
The price difference between open and close exceeds a threshold based on UVR.
Oversold Reversal
RSI <30 and CMF >0 with a strong bullish candle (close > open and UVR-based sensitivity filter).
Breakout Confirmation
The price breaks above a previously identified resistance, with conditions for RSI and CMF supporting the breakout.
Reversal from Oversold RSI Extreme
RSI <12 on the previous candle with a strong rebound on the current candle with UVR confirmation filter.
SELL CONDITIONS
Momentum-Based Sell-Entry
RSI <50, CMF <0, and the close price is below EMA50.
The price difference between open and close exceeds the UVR threshold.
Overbought Reversal
RSI >70 with bearish price action (open > close and UVR-based sensitivity filter).
Breakdown Confirmation
The price breaks below a previously identified support, with RSI and CMF supporting the breakdown.
Reversal from Overbought RSI Extreme
RSI >88 on the previous candle with a bearish confirmation on the current candle with UVR confirmation filter.
BUY AND SELL SIGNALS VISUALIZATION
The UVR Crypto Trend Indicator visually represents buy and sell conditions using dynamic plots, making it easier for traders to interpret and act on the signals. Below is an explanation of the visual representation:
Buy Signals and Visualization
Signal Trigger:
A buy signal is generated when one of the defined Buy Conditions is met (e.g., RSI >50, CMF >0, price above EMA50).
Visual Representation:
A blue upward arrow appears at the candle where the buy condition is triggered.
A blue cloud forms above the price candles, representing the strength of the bullish trend. The cloud dynamically adapts to market volatility, using the UVR calculation to mark support zones or consolidation levels.
Purpose of the Blue Cloud:
It acts as a visual guide for price movements and stay horizontal when the trend is not moving up
Sell Signals and Visualization
Signal Trigger:
A sell signal is generated when one of the defined Sell Conditions is met (e.g., RSI <50, CMF <0, price below EMA50).
Visual Representation:
A red downward arrow appears at the candle where the sell condition is triggered.
A red cloud forms below the price candles, representing the strength of the bearish trend. Like the blue cloud, it uses the UVR calculation to dynamically mark resistance zones or potential retracement levels.
Purpose of the Red Cloud:
It acts as a visual guide for price movements and stay horizontal when the trend is not moving down.
CONCLUSION
The UVR Crypto Trend indicator provides a powerful tool for trend reversal detection by combining volatility analysis, momentum confirmation, and trend-following techniques. Its unique use of the Ultimate Volatility Rate (UVR) as a core element, supported by proven indicators like RSI, CMF, and EMA, ensures reliable and actionable signals tailored for the crypto market's dynamic nature. By leveraging UVR’s high and low price range analysis, it achieves a level of precision that traditional indicators lack, making it a high-performing system for cryptocurrency traders.
Relative Strength Index Custom [BRTLab]RSI Custom — Strategy-Oriented RSI with Multi-Timeframe Precision
The Relative Strength Index Custom is designed with a focus on developing robust trading strategies. This powerful indicator leverages the logic of calculating RSI on higher timeframes (HTFs) while allowing traders to execute trades on lower timeframes (LTFs). Its unique ability to extract accurate RSI data from higher timeframes without waiting for those candles to close provides a real-time advantage, eliminating the "look-ahead" bias that often
distorts backtest results.
Key Features
Multi-Timeframe RSI for Strategy Development
This indicator stands out by allowing you to calculate RSI on higher timeframes, even while operating on lower timeframe charts. This means you can, for example, calculate RSI on the 1-hour or daily chart and execute trades on a 1-minute chart without needing to wait for the higher timeframe candle to close. This feature is crucial for strategy-building as it eliminates backtesting issues where data from the future is inadvertently used, providing more reliable backtest results.
Example: On a 15-minute chart, you can use the 1-hour RSI to open positions based on higher timeframe momentum, but you get this signal in real-time, improving timing and accuracy.
Accurate Data Extraction from Higher Timeframes
The indicator's custom logic ensures that accurate RSI data is retrieved from higher timeframes, providing an edge by delivering timely information for lower timeframe decisions. This prevents delayed signals often encountered when waiting for higher timeframe candles to close, which is crucial for high-frequency and intraday traders looking for precise entries based on multi-timeframe data.
Customizable RSI Settings for Strategy Tuning
The script offers full customization of the RSI, including length and source price (close, open, high, or low), allowing traders to tailor the RSI to fit specific trading strategies. These settings are housed in the "RSI Settings" section, enabling precise adjustments that align with your overall strategy.
No Future-Looking in Backtests
Traditional backtests often suffer from "future-looking" bias, where calculations unintentionally use data from candles that haven’t yet closed. This indicator is specifically designed to prevent such issues by calculating RSI values in real-time. This is particularly important when creating and testing strategies, as it ensures that the conditions under which trades would have been made are accurately represented in historical tests.
RSI-Based Moving Average for Additional Filtering
The built-in moving average (MA) based on RSI values helps filter out noise, making it easier to identify genuine trend shifts. This is particularly useful in strategies where moving average crossovers act as additional confirmation for trade entries and exits.
Overbought and Oversold Zone Detection
Visual gradient fills on the RSI chart help traders identify overbought and oversold zones (above 70 and below 30, respectively). These zones are crucial for timing reversal trades or confirming momentum-based strategies.
How This Indicator Enhances Your Strategy
Increased Accuracy for Intraday Strategies
For traders who operate on lower timeframes, using higher timeframe RSI data gives a broader perspective of market momentum while still maintaining precision for short-term trade entries. The real-time data extraction means you don't need to wait for HTF candles to close, which can dramatically improve your entry timing.
Strategic Edge in Backtesting
One of the greatest challenges in backtesting strategies is avoiding future-looking bias. This indicator is built to overcome this by using real-time multi-timeframe data, ensuring the accuracy and reliability of historical strategy testing, which provides confidence in your strategies when applied to live markets.
Advanced Filtering for Trend Strategies
By combining the RSI values with a customizable moving average (MA) and visualizing key momentum zones with overbought/oversold fills, the indicator allows for more refined trade filters. This ensures that signals generated by your strategy are based on solid momentum data and not short-term price fluctuations.
Average sector correlations to SPYHello Traders!
This is our latest addition to MFR TradingView account: Average sector correlations to SPY.
The Average Sector Correlation indicator is a powerful tool designed to give insights into the interconnectedness of different SPY sectors in relation to the SPY itself. As an introduction, know that this indicator presents the average correlation of all SPY sectors, serving as a barometer for overall market cohesion and relative performance.
At Myfractalrange, we monitor correlations extensively as we know they serve as warning for reversals, bullish rallies, bear market allies, etc.
Before going into how subscribers can use this script, let't have a look at the different data points:
In this script, we are calculating the average sector correlations to the SPY (S&P 500 ETF).
The following data points are used for the calculation:
- XLK: Technology Select Sector SPDR Fund
- XLE: Energy Select Sector SPDR Fund
- XLF: Financial Select Sector SPDR Fund
- XLU: Utilities Select Sector SPDR Fund
- XLV: Health Care Select Sector SPDR Fund
- XLP: Consumer Staples Select Sector SPDR Fund
- XLI: Industrial Select Sector SPDR Fund
- XLY: Consumer Discretionary Select Sector SPDR Fund
- XLC: Communication Services Select Sector SPDR Fund
- XLRE: Real Estate Select Sector SPDR Fund
- XLB: Materials Select Sector SPDR Fund
These data points represent different sectors of the stock market.
The user can modify the "period" variable to specify the lookback period for calculating the correlation.
By changing the value of "Period," the user can adjust the number of historical data points used in the correlation calculation. Default value is 10 days.
How does the script work?
The script uses the ta.correlation function from TradingView's Pine Script to calculate the correlation between the daily returns of each sector ETF and the SPY. The daily return is calculated as the percentage change in price from the previous day.
The correlation calculation is performed for each sector ETF and the SPY, using the specified lookback period. The correlations are then averaged to obtain the average sector correlation to the SPY.
The resulting average sector correlation is plotted on the chart using a blue line.
How to use correlations when trading?
This script can be used to assess the overall market sentiment by measuring the average sector correlation to the SPY. When the average sector correlation is positive, it indicates that the sectors are generally moving in the same direction as the broader market (SPY). This suggests a strong market trend.
Traders can use this information to make informed trading decisions. For example, if the average sector correlation is strongly positive, it may be a signal to consider bullish positions in individual stocks or ETFs from sectors with high positive correlations. Conversely, if the average sector correlation is negative or weak, it may indicate a lack of market direction or potential sector rotation, requiring caution in trading decisions.
Furthermore, when correlation values are high and growing, it may signify a build-up of risk, suggesting that the sectors are moving in tandem due to widespread market forces. This can often be a signal of broader market participants chasing trends or reacting to panic. Therefore, this indicator can serve as a valuable tool for traders and investors who want to understand market sentiment and systemic risk at a glance.
The Average Sector Correlation indicator also provides the capability to monitor average correlations across multiple timeframes concurrently. This feature allows users to track the fluctuations of sector correlations over short, medium, and long-term periods, all simultaneously.
This function offers a more comprehensive view of the market dynamics and can alert users to changes in correlation patterns over various time horizons. Thus, users can gain insights into the immediate temperament of the market while also maintaining awareness of larger trends that may be forming or diminishing over extended periods. It presents a holistic image of market behaviour, enhancing the user's decision-making process.
Why use Correlations in combination with other indicators?
To enhance trading strategies, this script can be used in combination with other technical indicators or signals. By incorporating additional indicators such as moving averages, trend lines, or oscillators, traders can build a comprehensive trading system.
For example, traders can use the average sector correlation as a confirmation signal for other technical analysis tools. If a bullish signal is generated by another indicator, such as a moving average crossover or a breakout, the positive average sector correlation can provide additional confidence to enter or hold a long position.
Conversely, if a bearish signal is generated by another indicator, a negative average sector correlation can act as a confirmation signal to consider short positions or reduce exposure to sectors with low or negative correlations.
By combining multiple signals and indicators, traders can develop a well-rounded trading strategy that incorporates market breadth (sector correlations) along with other technical factors to increase the probability of successful trades.
It's important to note that while Correlations are a useful tool, it should not be relied upon solely for making trading decisions. It's recommended to use it in conjunction with other technical analysis tools and consider other factors such as Trend, market conditions, risk management, and fundamental analysis.
We hope that you will find these explanations useful.
Enjoy!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorised. This script is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. Myfractalrange is not responsible for any losses you may incur. Please invest wisely.
Oliver Velez IndicatorOliver Velez is a well-known trader and educator who has developed multiple trading strategies. One of them is the 20-200sma strategy, which is a basic moving average crossover strategy. The strategy involves using two simple moving averages (SMAs) - a short-term SMA with a period of 20 and a long-term SMA with a period of 200 - on a 2-minute timeframe chart.
When the short-term SMA crosses above the long-term SMA, it signals a potential bullish trend and traders may look for opportunities to enter a long position. Conversely, when the short-term SMA crosses below the long-term SMA, it signals a potential bearish trend and traders may look for opportunities to enter a short position.
Traders using this strategy may also look for additional confirmations, such as price action signals or other technical indicators, before entering or exiting a trade. It is important to note that no trading strategy can guarantee profits, and traders should always use risk management techniques to limit potential losses.
This script is an implementation of the 2 SMA's (can also choose other types of MA's), with Elephant Bar Indicator (EBI) and the Tail Bars Indicator in TradingView.
The Elephant Bar Indicator is a technical indicator used in trading to identify potential trend reversals in the market. It is named after the large size of the bullish or bearish candlestick that it represents. The Tail Bars Indicator is a pattern recognition technique that identifies candlestick patterns with long tails or wicks.
The script starts by defining the input parameters for both indicators. For the Elephant Bar Indicator, the user inputs the lookback period and the size multiplier. For the Tail Bars Indicator, the user inputs the tail ratio and opposite wick ratio.
Next, the script calculates the moving averages of the closing price over the defined short and long periods using the Moving Average function. The script then calculates the average candle size and volume over the lookback period.
The script then identifies the Elephant Bars and Tail Bars using the input parameters and additional conditions. For Elephant Bars, the script identifies bullish and bearish bars that meet certain criteria, such as a size greater than the average candle size and volume greater than the average volume.
For Tail Bars, the script identifies bullish and bearish bars that have long tails or wicks and meet certain criteria such as opposite wick size less than or equal to the tail size multiplied by the input opposite wick ratio.
Finally, the script plots the Elephant Bar and Tail Bar signals on the chart using different colors and shapes. The script also plots the moving averages and Keltner Channels to help traders identify potential trend reversals.
It is still under development, so please, if someone has ideas to add, more than welcome
Arch1tect's New ToyDescription:
Arch1tect's New Toy tries to predict market trends by simply utilising 2 moving averages crossovers.
How it works:
Buy signals are triggered when the faster MA crosses over the slower MA from the downside to the upside.
Sell signals are triggered when the faster MA crosses under the slower MA from the upside to the downside.
How to use:
Take buys when buy signal is triggered AND close existing sell position
Take sells when sell signal is triggered AND close existing buy position
Note:
Settings are optimised for XAUUSD on the M1 chart.
Extra:
Alerts are included.
You can toggle between EMA , WMA and SMA to your liking.
Strategy Tester version:
Patreon Moving AverageThe Patreon moving average (PMA) is an adaptive moving average specifically designed to provide an optimal fit with the price while having a minimum amount of lag. The PMA can act as a fast-moving average for moving averages crossover system, detect trends, and filter out noisy variations from the price. The PMA is simple to use and interpret, and can be a really nice addition to your strategies, especially if they are based on moving averages.
The PMA integrates alerts based on the trend direction detected by the PMA.
Settings
Length: Determine the degree of filtering of the PMA.
Factor: Determine the sensitivity of the PMA to price variations, with higher values making the PMA less sensitive to price variations.
Decay: When higher than 0, introduce progressive smoothing, values closer to 0 return a faster progressive smoothing.
Src: Source input of the indicator.
Detect Trends With The PMA
The color of the PMA is related to the detected trend, with a blue color associated with an up-trend and a red color associated with a down-trend.
Higher values of Factor allows us to spot longer-term trends as well as filtering retracement in a trend.
Lower values of Length can also be used with higher values of Factor , this combination allows the PMA to actually be way less sensitive to price variations, thus returning less false signals while keeping a good fit with the price.
PMA As A Fast Moving Average
The PMA tries to provide crosses with a slow-moving average at the exact moment price cross the slow MA while minimizing the number of false signals.
PMA (In blue), EMA (in green), and SMA as a slow-moving average (in red), the PMA provide faster crosses while returning less false signals.
Progressive Smoothing
Progressive smoothing is obtained by using the Decay setting and allows the PMA to fit the price during extremely volatile markets and allows to preserve the structure of higher high's and lower low's.
Progressive smoothing can also minimize false signals.
In green/orange the PMA without progressive smoothing, in blue/red the PMA with progressive smoothing.
Finally progressive smoothing can give predictive and accurate estimates of the price central tendency
In green the mean of the price with a window size equal to the period the PMA is red, we can see that the PMA converges toward it extremely fast.
How To Access
The indicator is one of the "Patreon trend following indicators", and can only be used by my Patreons, you can become a Patreon by using the link on my signature.
4K+ Candlestacks/ColumnCandles Plus PerksFor all candle analysis enthusiasts out there, this is my cutting edge "4K+ Candlestacks/ColumnCandles Plus Perks" that I spontaneously invented long ago. Just when you may have thought it was the end of the evolutionary line for candle technology, it's not! There are candlesticks and now "candlestacks". Your eyes are presently gazing upon a NEW candle type intended for destiny well into the 21st century and onward to support much higher graphics resolutions including 4K, 8K, 16K+ yielding enhanced chart analytics. With extremely high resolution display technologies arriving within the affordable range, having thin 1 pixel wide traditional candle wicks are going to become more and more visually apprehensible. Particularly for folks with a visual acuity that is not par at 20/20 or have some degree of color blindness, the candlestacks have a "large" amount of different color schemes to select from.
"Candlestick charts" are suspected to have been invented by Munehisa Homma well over 200 years ago. We have been using technology that is older than the age of distributed electricity and the modern car combined with billions at stake, hour to hour of each day. While candlesticks are effective, by having an abundance of computing power, the old candlestick wick width is becoming indistinguishably lost in the fog of a plenitude of plots. After a short time of contemplating about it linguistically in Pine Script, I arrived at a eureka moment having an actual working candle that was entirely novel. However, I didn't want to stop there. It required color finesse for diagnosed visual impairments combined with methods such as Heikin Ashi variants. My intention while inventing this was to provide the ultimate experience in candle technology that could potentially exist.
"Candlestacks" are just like the original OHLC candlesticks, however the "wick" portion is more like a column displaying visually increased situational awareness. Immediately at first sight, I originally conceived of the name "ColumnCandles" upon initial inspection of the plot, being it was remarkably similar to overlapping column charts I have been seeing for years with data metrics. In my attempt to formulate a worthier name, I noticed their appearance looks like stacks of blocks. Stacks, sticks, it sounded rhythmically sweet. I decided candlestacks would be a more appropriate name for this candle type distinguishable from candlesticks, but all to similarly sounding. I am hopeful I chose candlestacks as a fitting name that the rest of the world may come to appreciate one day when the planet is powered by nuclear "compact fusion" reactors and everyone has personal aerial transportation availability. "Candlestacks" vs "ColumnCandles", leave your opinion below in the comments if you are compelled to do so, providing a consensus. I respect your opinion either way...
Heikin Ashi, with it's advantages of identifying current short term trends, seemed worthy of inclusion, so I decided to expand on candlestacks with three different formulations to select from, including a fourth OHLC basic type. There are two distinct methods of Hieken Ashi employing pre-smoothing and post-smoothing techniques, each of which having capabilities of using different smoothing filters that are selectable.
Other features include a brightening option for the first descending candle which is best suited while using Heikin Ashi. The candlestacks wick transparency is independently controllable. Descending candlestacks have a darker wick than the ascending kind. With the Heikin Ashi smoothing techniques, I included a selection to see traditional candlestick wicks in a supplementary fashion. Also, there is an option to control the amount of candlestacks that are displayable. This is also a multicator including my "SWIFT Moving Average Crossover", which is complimentary to the candlestacks, especially in one of the Heikin Ashi modes. This moving average crossover(MAC), having multiple color schemes, limits the divergences between the leading and lagging lines. Of notable mention, the crossover dots on the SWIFT MAC you see, are actually one bar late. Lastly, with this flagship indicator, I included a multi-color "neon source" line to view close, hl2, etc... in combination with the candlestacks yielding the best of both worlds selectively. Any one of the individual indicators may actually be enabled/disabled independently. Being this is an overlay chart, I "may" include other overlay indicators in the future where they provide an added benefit to what is already included.
I provided multiple color schemes for those of you who may have color blindness vision impairments. You may contact me in private, if these color schemes are not suitable for your diagnosed visual impairment, and you wish to contribute to seeing the color schemes improved along with other future indicators I shall release.
I.P.O.C.S.: "Initial Public Offering Clean Start" proprietary technology. Firstly, many of my other indicators already possess this capability. It allows suitable plotting from day one, minute one of IPO, remedying visually delayed signal analysis. It's basically accurate plotting from the very first bar (bar_index==0) on Tradingview. If you don't know what this is, most people don't, go back to the VERY beginning of any stock on the "All" chart and compare it to other similar indicators. What's so special about this? It is extremely difficult to get a healthy plot from bar_index==0 on any platform. However, I have become exceedingly talented performing this feat in most cases, but not all depending on the algorithm. This indicator is a successful accomplishment implementing IPOCS. It's inherent value is predominantly for IPO traders who in the past have had to wait 20, 50, and 150 bars before they obtain a precise indicator measurement for the simplest of algorithms in order to make a properly informed decision to potentially invest in an asset. How is this achieved? It's a highly protected secret of mine... but I will say I rarely use Pine built-in functions at all. When I do, I use them scarcely due to currently existing Pine language limitations.
Features List Includes:
I.P.O.C.S.(Initial Public Offering Clean Start) Technology
Enable/disable dark background for enhanced visibility
Color schemes for individual indicators
Controls for Heikin Ashi candlestacks smoothing
Historical bar controls
"Neon Source" options
Many, many more previously described...
This is not a freely available indicator, FYI. To witness my Pine poetry in action, properly negotiated requests for unlimited access, per indicator, may ONLY be obtained by direct contact with me using TV's "Private Chats" or by "Message" hidden in my member name above. The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section if you do have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I will implement more ideas when they present themselves as worthy additions. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Simple Moving Averages Alert Scriptcan set alerts on 3 moving averages (crossovers) , experiment with different moving average lengths in the input settings menu, there is also a toggle switch which turns off the 3rd moving average being used as a stop.
will add a backtesting version at some point
Predictive EMAFrom the MQL5 Indicator database, here is what the author said about the script,
"Goal of this indicator:
Given three EMA's of varying lengths, use their values
for a estimator of "where we are now" or will be in the near future.
This is a very simplistic method, better ones are probably found
in the signal processing and target tracking literature.
A Kalman filter has been known since the 1950's 1960's and there
is better still. Nevertheless this is easily programmable in the
typical environments of a retail trading application like Metatrader4.
Method:
An an exponential moving average (EMA) or a simple moving average (SMA), for that
matter, have a bandwidth parameter 'L', the effective length of the window. This
is in units of time or, really, inverse of frequency. Higher L means a lower
frequency effect.
With a parameter L, the weighted time index of the EMA and SMA is (L-1)/2. Example:
take an SMA of the previous 5 values: -5 -4 -3 -2 -1 now. The average "amount of time"
back in the past of the data which go in to the SMA is hence -3, or (L-1)/2. Same applies
for an EMA. The standard parameterization makes this correspondence between EMA
and SMA.
Therefore the idea here is to take two different EMA's, a longer, and
a shorter of lengths L1 and L2 (L2 <L1). Now take the pairs:
which defines a line.
Extrapolate to , solve for y and that is the predictive EMA estimate.
Application:
Traditional moving averages, as simple-minded linear filters, have significant group delay.
In engineering that isn't so important as nobody cares if your sound from your iPod is delayed
a few milliseconds after it is first processed. But in markets, you can't
trade on the smoothed price, only the actual noisy, market price now. Hence you
ought to estimate better.
This statistic (what math/science people call what technical analysts call an 'indicator')
may be useful as the "fast" moving average in a moving average crossover trading system.
It could also be useful for the slow moving average as well.
For instance, on a 5 minute chart:
try for the fast: (will be very wiggly, note)
LongPeriod 25.0
ShortPeriod 8.0
ExtraTimeForward 1.0
and for the slow:
LongPeriod 500.0
ShortPeriod 50.0 to 200.0
ExtraTimeForward 0.0
But often a regular MA for the slow can work as well or better, it appears from visual inspection.
Enjoy.
In chaos there is order, and in that order there is chaos and order inside again.
Then, surrounding everything, pointy haired bosses. "
I may have done it incorrectly, feel free to revise
52SIGNAL RECIPE VWAP Quantum Matrix Pro═══52SIGNAL RECIPE VWAP Quantum Matrix Pro ═══
◆ Overview
52SIGNAL RECIPE VWAP Quantum Matrix Pro is an advanced technical indicator based on Volume Weighted Average Price (VWAP), integrating volatility-adjusted bands and Fibonacci levels to provide multi-dimensional analysis of price movements.
It automatically applies optimized lookback periods for different timeframes, providing customized analysis for various trading styles, and helps traders effectively identify critical support/resistance zones through precise price level identification.
─────────────────────────────────────
◆ Key Features
• **Adaptive VWAP Bands**: Automatically adjusting upper and lower bands based on market volatility
• **Fibonacci Integration**: Fibonacci levels (23.6%, 38.2%, 50%, 61.8%, 78.6%) extended around VWAP center
• **Timeframe Optimization**: Automatic lookback period adjustment for each chart cycle
• **Pivot Point Analysis**: Core support/resistance levels based on volume-weighted highs and lows
• **Precision Labeling**: Accurate numerical display for all major price levels
• **Visual Gradation**: Intuitive visualization through color gradation for each Fibonacci level
─────────────────────────────────────
◆ Technical Foundation
■ VWAP Calculation Principles
• **Volume Weighting**: Calculation of real equilibrium price considering volume rather than simple price averaging
• **Standard Deviation Bands**: Statistical fluctuation range setting around VWAP center
• **Volatility Adjustment Mechanism**: Dynamic band width adjustment using current ATR to historical ATR ratio
• **Precise Price Range**: Identification of highest/lowest price range within specified lookback period
■ Fibonacci Band Implementation
• **VWAP-Centered Extension**: Division of distance from centerline (VWAP) to standard deviation bands by Fibonacci ratios
• **Symmetrical Upper/Lower Structure**: Application of identical Fibonacci ratios in both upward and downward directions
• **Color Gradation**: Progressive color changes for each Fibonacci level providing visual depth
─────────────────────────────────────
◆ Practical Applications
■ Price Movement Interpretation
• **Central Reference Point**:
▶ VWAP serves as intraday/period equilibrium price providing balance point of buying/selling pressure
▶ Movement above/below VWAP can be interpreted as short-term bullish/bearish signals
• **Band Reaction Patterns**:
▶ Reaching outer bands (100%) signals overbought/oversold conditions
▶ Reaction patterns between Fibonacci levels provide basis for trend strength and persistence judgment
■ Trading Strategy Utilization
• **Range-bound Trading**:
▶ Short-term trading utilizing bounce patterns between Fibonacci levels
▶ Oscillation trading between centerline (VWAP) and Fibonacci levels
• **Trend Following Strategy**:
▶ Breakout of Fibonacci levels aligned above/below VWAP signals trend strengthening
▶ Strong momentum confirmation when re-entering after outer band breakout
─────────────────────────────────────
◆ Advanced Configuration Options
■ Input Parameter Guide
• **Base Standard Deviation** (Default: 2.0)
▶ 1.0-1.5: Narrow bands, suitable for short-term trading
▶ 1.8-2.2: Balanced bands, optimal for general market conditions
▶ 2.5-3.0: Wide bands, suitable for long-term positions
• **Maximum/Minimum Standard Deviation** (Default: 3.0/1.0)
▶ Maximum: Cryptocurrency (4.0), Stocks/Forex (3.0), Low volatility (2.5)
▶ Minimum: Intraday trading (0.8), General (1.0), Long-term (1.5)
• **Volatility Measurement Period** (Default: 20)
▶ Short-term (10-14): Fast response, intraday trading
▶ Medium-term (15-25): Balanced response, swing trading
▶ Long-term (30-50): Noise filtering, long-term investment
• **Use Volatility Adjustment** (Default: On)
▶ On: Automatic band width adjustment based on current market volatility (recommended)
▶ Off: Fixed standard deviation bands usage
■ Timeframe-Specific Optimal Settings
• **Intraday Trading** (15min-1hr): Base standard deviation 1.8, volatility period 14
• **Swing Trading** (4hr-daily): Base standard deviation 2.0, volatility period 20
• **Position Trading** (daily-weekly): Base standard deviation 2.5, volatility period 30
■ Market-Specific Optimal Settings
• **Stock Market**: Base standard deviation 2.0, volatility period 20
• **Forex Market**: Base standard deviation 1.8, volatility period 25
• **Cryptocurrency Market**: Base standard deviation 2.5, volatility period 14, maximum standard deviation 4.0
─────────────────────────────────────
◆ Synergy with Other Indicators
• **Moving Averages**: VWAP and major moving average crossovers strengthen trend reversal signals
• **RSI/Stochastic**: Combination of VWAP band reactions in overbought/oversold zones improves reversal signal accuracy
• **Bollinger Bands**: VWAP Quantum Matrix and Bollinger Band convergence/divergence patterns are useful for volatility change prediction
• **Fibonacci Retracement**: Strong support/resistance formation when trend-direction Fibonacci retracement matches VWAP Fibonacci levels
• **Horizontal Support/Resistance**: Reaction probability significantly increases when past important price levels match VWAP Fibonacci levels
─────────────────────────────────────
◆ Conclusion
VWAP Quantum Matrix Pro provides deep insights into price action by integrating volatility-adjusted bands and Fibonacci theory into traditional VWAP analysis.
It dynamically responds to market environment changes through volume weighting and volatility adaptation mechanisms, and can be flexibly applied to various trading styles through timeframe-optimized lookback period settings.
Through appropriate input parameter configuration, the indicator can be optimized to match each trader's style and objectives, and through combination with other technical indicators, it strengthens confidence in trading decisions, ultimately enabling more precise and systematic market approaches.
─────────────────────────────────────
※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══52SIGNAL RECIPE VWAP Quantum Matrix Pro ═══
◆ 개요
52SIGNAL RECIPE VWAP Quantum Matrix Pro는 거래량 가중 평균 가격(VWAP)을 기반으로 하는 고급 기술적 지표로, 변동성 조정 밴드와 피보나치 레벨을 통합하여 가격 움직임을 다차원적으로 분석합니다.
타임프레임별로 최적화된 룩백 기간을 자동 적용하여 다양한 거래 스타일에 맞춤화된 분석을 제공하며, 정밀한 가격 레벨 식별을 통해 트레이더가 중요한 지지/저항 구간을 효과적으로 파악할 수 있도록 돕습니다.
─────────────────────────────────────
◆ 주요 특징
• **적응형 VWAP 밴드**: 시장 변동성에 따라 자동으로 조정되는 상하단 밴드 제공
• **피보나치 통합**: VWAP 중심으로 피보나치 레벨(23.6%, 38.2%, 50%, 61.8%, 78.6%) 확장
• **타임프레임 최적화**: 각 차트 주기에 맞춰 자동으로 룩백 기간 조정
• **피봇 포인트 분석**: 거래량 가중 고저가 기반의 핵심 지지/저항 레벨 표시
• **정밀 레이블링**: 모든 주요 가격 레벨에 정확한 수치 표시
• **시각적 그라데이션**: 피보나치 레벨별 컬러 그라데이션으로 직관적인 시각화
─────────────────────────────────────
◆ 기술적 기반
■ VWAP 계산 원리
• **거래량 가중치**: 단순 가격 평균이 아닌 거래량을 고려한 실질적 균형 가격 계산
• **표준편차 밴드**: VWAP 중심으로 통계적 변동 범위 설정
• **변동성 조정 메커니즘**: 현재 ATR과 과거 ATR 비율을 활용한 동적 밴드폭 조정
• **정밀 가격 범위**: 지정된 룩백 기간 내 최고/최저 가격 범위 식별
■ 피보나치 밴드 구현
• **VWAP 중심 확장**: 중심선(VWAP)에서 표준편차 밴드까지의 거리를 피보나치 비율로 분할
• **상하단 대칭 구조**: 상승과 하락 방향으로 동일한 피보나치 비율 적용
• **색상 그라데이션**: 피보나치 레벨별 점진적 색상 변화로 시각적 깊이감 제공
─────────────────────────────────────
◆ 실용적 응용
■ 가격 움직임 해석
• **중심 기준점**:
▶ VWAP은 일중/기간 내 균형가격으로 매수/매도 압력의 균형점 제공
▶ VWAP 위/아래 움직임은 단기 강세/약세 신호로 해석 가능
• **밴드 반응 패턴**:
▶ 외부 밴드(100%)에 도달 시 과매수/과매도 상태 시그널
▶ 피보나치 레벨 간 반응 패턴은 추세 강도와 지속성 판단 근거
■ 트레이딩 전략 활용
• **범위 내 거래**:
▶ 피보나치 레벨 간 바운스 패턴 활용한 단기 매매
▶ 중심선(VWAP)과 피보나치 레벨 간 오실레이션 거래
• **추세 추종 전략**:
▶ VWAP 위/아래 정렬된 피보나치 레벨 돌파는 추세 강화 신호
▶ 외부 밴드 돌파 후 다시 진입 시 강한 모멘텀 확인
─────────────────────────────────────
◆ 고급 설정 옵션
■ 인풋 파라미터 가이드
• **기본 표준 편차 (Base Standard Deviation)** (기본값: 2.0)
▶ 1.0-1.5: 좁은 밴드, 단기 거래에 적합
▶ 1.8-2.2: 균형 잡힌 밴드, 일반적 시장 환경에 최적
▶ 2.5-3.0: 넓은 밴드, 장기 포지션에 적합
• **최대/최소 표준 편차 (Maximum/Minimum Standard Deviation)** (기본값: 3.0/1.0)
▶ 최대: 암호화폐(4.0), 주식/외환(3.0), 저변동성(2.5)
▶ 최소: 일중 거래(0.8), 일반(1.0), 장기(1.5)
• **변동성 측정 기간 (Volatility Measurement Period)** (기본값: 20)
▶ 단기(10-14): 빠른 반응, 일중 거래
▶ 중기(15-25): 균형 잡힌 반응, 스윙 트레이딩
▶ 장기(30-50): 노이즈 필터링, 장기 투자
• **변동성 조정 사용 (Use Volatility Adjustment)** (기본값: 켜짐)
▶ 켜짐: 현재 시장 변동성에 따라 밴드 폭 자동 조정 (권장)
▶ 꺼짐: 고정된 표준편차 밴드 사용
■ 타임프레임별 최적 설정
• **일중 거래** (15분-1시간): 기본 표준편차 1.8, 변동성 기간 14
• **스윙 트레이딩** (4시간-일봉): 기본 표준편차 2.0, 변동성 기간 20
• **포지션 트레이딩** (일봉-주봉): 기본 표준편차 2.5, 변동성 기간 30
■ 시장별 최적 설정
• **주식 시장**: 기본 표준편차 2.0, 변동성 기간 20
• **외환 시장**: 기본 표준편차 1.8, 변동성 기간 25
• **암호화폐 시장**: 기본 표준편차 2.5, 변동성 기간 14, 최대 표준편차 4.0
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◆ 다른 지표와의 시너지
• **이동평균선**: VWAP과 주요 이동평균선 교차는 추세 전환 신호 강화
• **RSI/스토캐스틱**: 과매수/과매도 구간에서 VWAP 밴드 반응과 결합 시 반전 신호 정확도 향상
• **볼린저 밴드**: VWAP Quantum Matrix와 볼린저 밴드 수렴/발산 패턴은 변동성 변화 예측에 유용
• **피보나치 리트레이스먼트**: 추세 방향 피보나치 리트레이스먼트와 VWAP 피보나치 레벨 일치 시 강력한 지지/저항 형성
• **수평 지지/저항**: 과거 중요 가격대와 VWAP 피보나치 레벨 일치 시 반응 확률 대폭 증가
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◆ 결론
VWAP Quantum Matrix Pro는 전통적인 VWAP 분석에 변동성 조정 밴드와 피보나치 이론을 통합하여 가격 행동에 대한 깊이 있는 통찰력을 제공합니다.
거래량 가중치와 변동성 적응 메커니즘을 통해 시장 환경 변화에 동적으로 대응하며, 타임프레임별 최적화된 룩백 기간 설정으로 다양한 거래 스타일에 유연하게 적용할 수 있습니다.
적절한 인풋 파라미터 설정을 통해 각 트레이더의 스타일과 목표에 맞게 지표를 최적화할 수 있으며, 다른 기술적 지표들과의 조합을 통해 트레이딩 결정에 대한 확신을 강화하고, 궁극적으로 더 정밀하고 체계적인 시장 접근을 가능하게 합니다.
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※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Liquidity Market Seeking SwiftEdgeThis indicator is designed to identify potential liquidity levels on the chart by detecting swing highs and lows, which are often areas where stop-loss orders or significant orders accumulate. It visualizes these levels with horizontal lines and labels on the right side of the chart, color-coded based on volume to help traders understand where the market might seek liquidity.
How It Works
Swing Highs and Lows: The indicator uses the ta.pivothigh and ta.pivotlow functions to identify significant swing points over a user-defined lookback period (Swing Length). These points are considered potential liquidity levels where stop-loss orders might be placed.
Volume Analysis: The indicator compares the volume at each swing point to the average volume over a specified period (Volume Average Length). Levels with above-average volume are colored red, indicating higher liquidity, while levels with below-average volume are colored green.
Liquidity Visualization: Horizontal dashed lines are drawn at each identified level, extending across the chart. Labels on the right side display the estimated liquidity amount (simulated based on volume and a multiplier, Volume Multiplier for Liquidity).
Sell Signal: A "SELL NOW" label appears when the price approaches a liquidity level after an uptrend (detected using a simple moving average crossover). This suggests a potential reversal as the market may target liquidity at that level.
Strategy Concept: Market Seeking Liquidity
The indicator is based on the concept that markets often move toward areas of high liquidity, such as clusters of stop-loss orders or significant order accumulations. These liquidity pools are typically found around swing highs and lows, where traders place their stop-losses or large orders. By identifying these levels and highlighting those with higher volume (red lines), the indicator aims to show where the market might move to "grab" this liquidity. For example, after an uptrend, the market may reverse at a swing high to take out stop-losses above that level, providing liquidity for larger players to enter or exit positions.
Settings
Swing Length: The number of bars to look back for detecting swing highs and lows. Default is 20.
Liquidity Threshold: The price threshold for merging nearby levels to avoid duplicates. Default is 0.001.
Volume Average Length: The period for calculating the average volume to compare against. Default is 20.
Volume Multiplier for Liquidity: A multiplier to scale the volume into a simulated liquidity amount (displayed as "K"). Default is 1000.
Usage Notes
Use this indicator on any timeframe, though it may be more effective on higher timeframes (e.g., 1H, 4H) where swing points are more significant.
Red lines indicate levels with higher volume, suggesting stronger liquidity pools that the market might target.
Green lines indicate levels with lower volume, which may be less significant.
The "SELL NOW" signal is a basic example of how to use liquidity levels for trading decisions. It appears when the price approaches a liquidity level after an uptrend, but it should be used in conjunction with other analysis.
Adjust the Volume Multiplier for Liquidity to scale the displayed liquidity amounts based on your instrument (e.g., forex pairs may need a higher multiplier than indices).
Traders Trend DashboardThe Traders Trend Dashboard (TTD) is a comprehensive trend analysis tool designed to assist traders in making informed trading decisions across various markets and timeframes. Unlike conventional trend-following scripts, TTD goes beyond simple trend detection by incorporating a unique combination of moving averages and a visual dashboard, providing traders with a clear and actionable overview of market trends. Here's how TTD stands out from the crowd:
Originality and Uniqueness:
TTD doesn't rely on just one moving average crossover to detect trends. Instead, it employs a dynamic approach by comparing two moving averages of distinct periods across multiple timeframes. This innovative methodology enhances trend detection accuracy and reduces false signals commonly associated with single moving average systems.
Market Applicability:
TTD is versatile and adaptable to various financial markets, including forex, stocks, cryptocurrencies, and commodities. Its flexibility ensures that traders can utilize it across different asset classes and capitalize on market opportunities.
Optimal Timeframe Utilization:
Unlike many trend indicators that work best on specific timeframes, TTD caters to traders with diverse trading preferences. It offers support for intraday trading (1m, 3m, 5m), short-term trading (15m, 30m, 1h), and swing trading (4h, D, W, M), making it suitable for a wide range of trading styles.
Underlying Conditions and Interpretation:
TTD is particularly effective during trending markets, where its multi-timeframe approach helps identify consistent trends across various time horizons. In ranging markets, TTD can indicate potential reversals or areas of uncertainty when moving averages converge or cross frequently.
How to Use TTD:
1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy.
2. Dashboard Interpretation: The TTD dashboard displays green (🟢) and red (🔴) symbols to indicate the relationship between two moving averages. A green symbol suggests that the shorter moving average is above the longer one, indicating a potential bullish trend. A red symbol suggests the opposite, indicating a potential bearish trend.
3. Confirmation and Strategy: Consider TTD signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate.
4. Risk Management: As with any indicator, use TTD in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan.
Conclusion:
The Traders Trend Dashboard (TTD) offers traders a powerful edge in trend analysis, combining innovation, versatility, and clarity. By understanding its unique methodology and integrating its signals with your trading strategy, you can make more informed trading decisions across various markets and timeframes. Elevate your trading with TTD and unlock a new level of trend analysis precision.
TWAP + MA crossover Study [Dynamic Signal Lab]Dear TV'ers,
Hereby the study for the TWAP/moving average crossover, with taking profit options.
moving averages include: EMA , WMA , DEMA , TEMA , VAR, WWMA, ZLEMA , TSF , HULL, TILL
It is also possible to gradually take profit, using:
* minimum consecutive green/red candles
* minimum amount of green/red candles in the last 2-8 candles
* both of the above criteria
The slightly transparent green fill shows how much you are in profit from your entry point
The current default properties should be modified to make this strategy cost-effective, but typically 15 minutes and higher timeframes (up to 6hr) seem to work well for larger (top10 cap) crypto projects. Don't use this script for small-caps as it will get you rekt, due to wild volatility.
Additionally, you'll also be able to continuously take profit, making sure you lock in all those sweet profits. For backtesting: use the strategy version of this script
Trend-Quality IndicatorBINANCE:BTCUSDT
Open source version of the Trend-Quality Indicator as described by David Sepiashvili in [ Stocks & Commodities V. 22:4 (14-20) ]
Q-Indicator and B-Indicator are available both separately or together
█ OVERVIEW
The Trend-Quality indicator is a trend detection and estimation tool that is based on a two-step filtering technique. It measures cumulative price changes over term-oriented semicycles and relates them to “noise”. The approach reveals congestion and trending periods of the price movement and focuses on the most important trends, evaluating their strength in the process. The indicator is presented in a centered oscillator (Q-Indicator) and banded oscillator format (B-Indicator).
Semicycles are determined by using a short term and a longer term EMAs. The starting points for the cycles are determined by the moving averages crossover.
Cumulative price change (CPC) indicator measures the amount that the price has changed from a fixed starting point within a given semicycle. The CPC indicator is calculated as a cumulative sum of differences between the current and previous prices over the period from the fixed starting point.
The trend within the given semicycle can be found by calculating the moving average of the cumulative price change.
The noise can be defined as the average deviation of the cumulative price change from the trend. To determine linear noise, we calculate the absolute value of the difference between CPC and trend, and then smooth it over the n-point period. The root mean square noise, similar to the conventional standard deviation, can be derived by summing the squares of the difference between CPC and trend over each of the preceding n-point periods, dividing the sum by n, and calculating the square root of the result.
█ Q-INDICATOR
The Q-Indicator is a centered oscillator that fluctuates around a zero line with no upper or lower limits, is calculated by dividing trend by noise.
The Q-Indicator is intended to measure trend activity. The further the Q is from 0, the less the risk of trading with a trend, and the more reliable the trading opportunity. Values exceeding +2 or -2 can be qualified as promising
Values:
in the -1 to +1 range (GRAY) indicate that the trend is buried beneath noise. It is preferable to stay out of this zone
in the +1 to +2 or -1 to -2 range (YELLOW) indicate weak trending
in the +2 to +5 range (BLUE) or -2 to -5 range (ORANGE) indicate moderate trending
above +5 range (GREEN) or below -5 (RED) indicate strong trending
Readings exceeding strong trending levels can indicate overbought or oversold conditions and signal that price action should be monitored closely.
█ B-INDICATOR
The B-Indicator is a banded oscillator that fluctuates between 0 and 100, is calculated by dividing the absolute value of trend by noise added to absolute value of trend, and scaling the result appropriately.
The B-indicator doesn’t show the direction of price movement, but only the existence of the trend and its strength. It requires additional tools for reversal manifestations.
The indicator’s interpretation is simple. The central line suggests that the trend and noise are in equilibrium (trend is equal to noise).
Values:
below 50 (GRAY) indicate ranging market
in the 50 to 65 range (YELLOW) indicate weak trending
in the 65 to 80 range (BLUE) indicate moderate trending
above 80 (GREEN) indicate strong trending
The 65 level can be thought of as the demarcation line of trending and ranging markets and can help determine which type of technical analysis indicator (lagging or leading) is better suited to current market conditions. Readings exceeding strong trending levels can indicate overbought or oversold conditions.
Buff Averages [CC]The Buff Averages were created by Buff Dormeier (Stocks and Commodities Feb 2001) and this is another hidden gem that is a combo of a volume weighted indicator and a moving average crossover system. It uses a special method to calculate the weighting based on volume. The colored line (fast buff) will follow the price closely and you use the other line to act as a trend confirmation. I have included strong buy and sell signals in addition to normal ones so strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish!
[blackcat] L1 Stick-Line Merged MACDLevel: 1
Background
The MACD is a superior derivative of moving average crossovers and was developed by Gerald Appel in 1979 as a market timing tool. MACD uses two exponential moving averages with different bar periods, which are then subtracted to form what Mr. Appel calls the Fast Line. A 9-period moving average of the fast line creates the slow line.
Function
L1 Stick-Line Merged MACD merges dif and dea lines with macd sticks by the same color candles. The generation of candles help to confirm the trend contiuation. E.g. yellow candles indicate up trend continuation while blue candles indicate down trend continuation
Key Signal
dif --> classic MACD diff fast line in yellow
dea --> classic MACD dea slow line in fuchsia
macd --> classic difference histogram
upslmerge --> up trend continuation yellow candle merge condition
dnslmerge --> down trend continuation blue candle merge condition
Pros and Cons
Pros:
1. merged line and stick with candles help confirm trend reversal
2. long entry signal is indicated.
Cons:
1. need sophisticated knowledge of MACD to use this well
2. this still requires a lot of MACD experience to obtain reliable trading signals
Remarks
Merge lines and sticks of MACD into candles. Better view of the trend
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.