Moving Average CombinationsThis moving average indicator is used to plot either EMA or SMA as per users choice. User also has the options to choose different type of sources for each of the moving average lines like high, low, close etc. Again, flexibility is added to plot moving averages of different timeframe than the current timeframe of the chart. By doing so in daily chart user can plot averages of different timeframe like hourly, weekly or monthly and vice versa. Length is also as per the choice of the user.
So for a example, in a daily timeframe chart you can plot 9SMA High Daily, 200EMA Close 1Hr, 200EMA Close 2Hr, 200EMA Close Daily, 9SMA High Weekly and so on. This will help in play moving average crossovers and contractions.
Label for each moving average line is also added.
스크립트에서 "moving average crossover"에 대해 찾기
trend_vol_forecastNote: The following description is copied from the script's comments. Since TradingView does not allow me to edit this description, please refer to the comments and release notes for the most up-to-date information.
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USAGE
This script compares trend trading with a volatility stop to "buy and hold".
Trades are taken with the trend, except when price exceeds a volatility
forecast. The trend is defined by a moving average crossover. The forecast
is based on projecting future volatility from historical volatility.
The trend is defined by two parameters:
- long: the length of a long ("slow") moving average.
- short: the length of a short ("fast") moving average.
The trend is up when the short moving average is above the long. Otherwise
it is down.
The volatility stop is defined by three parameters:
- volatility window: determines the number of periods in the historical
volatility calculation. More periods means a slower (smoother)
estimate of historical volatility.
- stop forecast periods: the number of periods in the volatility
forecast. For example, "7" on a daily chart means that the volatility
will be forecasted with a one week lag.
- stop forecast stdev: the number of standard deviations in the stop
forecast. For example, "2" means two standard deviations.
EXAMPLE
The default parameters are:
- long: 50
- short: 20
- volatility window: 30
- stop forecast periods: 7
- stop forecast standard deviations: 1
The trend will be up when the 20 period moving average is above the 50
period moving average. On each bar, the historical volatility will be
calculated from the previous 30 bars. If the historical volatility is 0.65
(65%), then a forecast will be drawn as a fuchsia line, subtracting
0.65 * sqrt(7 / 365) from the closing price. If price at any point falls
below the forecast, the volatility stop is in place, and the trend is
negated.
OUTPUTS
Plots:
- The trend is shown by painting the slow moving average green (up), red
(down), or black (none; volatility stop).
- The fast moving average is shown in faint blue
- The previous volatility forecasts are shown in faint fuchsia
- The current volatility forecast is shown as a fuchsia line, projecting
into the future as far as it is valid.
Tables:
- The current historical volatility is given in the top right corner, as a
whole number percentage.
- The performance table shows the mean, standard deviation, and sharpe
ratio of the volatility stop trend strategy, as well as buy and hold.
If the trend is up, each period's return is added to the sample (the
strategy is long). If the trend is down, the inverse of each period's
return is added to the sample (the strategy is short). If there is no
trend (the volatility stop is active), the period's return is excluded
from the sample. Every period is added to the buy-and-hold strategy's
sample. The total number of periods in each sample is also shown.
Shapeshifting Moving Average - Switching From Low-Lag To SmoothThe term "shapeshifting" is more appropriate when used with something with a shape that isn't supposed to change, this is not the case of a moving average whose shape can be altered by the length setting or even by an external factor in the case of adaptive moving averages, but i'll stick with it since it describe the purpose of the proposed moving average pretty well.
In the case of moving averages based on convolution, their properties are fully described by the moving average kernel ( set of weights ), smooth moving averages tend to have a symmetrical bell shaped kernel, while low lag moving averages have negative weights. One of the few moving averages that would let the user alter the shape of its kernel is the Arnaud Legoux moving average, which convolve the input signal with a parametric gaussian function in which the center and width can be changed by the user, however this moving average is not a low-lagging one, as the weights don't include negative values.
Other moving averages where the user can change the kernel from user settings where already presented, i posted a lot of them, but they only focused on letting the user decrease or increase the lag of the moving average, and didn't included specific parameters controlling its smoothness. This is why the shapeshifting moving average is proposed, this parametric moving average will let the user switch from a smooth moving average to a low-lagging one while controlling the amount of lag of the moving average.
Settings/Kernel Interaction
Note that it could be possible to design a specific kernel function in order to provide a more efficient approach to today goal, but the original indicator was a simple low-lag moving average based on a modification of the second derivative of the arc tangent function and because i judged the indicator a bit boring i decided to include this parametric particularity.
As said the moving average "kernel", who refer to the set of weights used by the moving average, is based on a modification of the second derivative of the arc tangent function, the arc tangent function has a "S" shaped curve, "S" shaped functions are called sigmoid functions, the first derivative of a sigmoid function is bell shaped, which is extremely nice in order to design smooth moving averages, the second derivative of a sigmoid function produce a "sinusoid" like shape ( i don't have english words to describe such shape, let me know if you have an idea ) and is great to design bandpass filters.
We modify this 2nd derivative in order to have a decreasing function with negative values near the end, and we end up with:
The function is parametric, and the user can change it ( thus changing the properties of the moving average ) by using the settings, for example an higher power value would reduce the lag of the moving average while increasing overshoots. When power < 3 the moving average can act as a slow moving average in a moving average crossover system, as weights would not include negative values.
Here power = 0 and length = 50. The shapeshifting moving average can approximate a simple moving average with very low power values, as this would make the kernel approximate a rectangular function, however this is only a curiosity and not something you should do.
As A Smooth Moving Average
“So smooth, and so tranquil. It doesn't get any quieter than this”
A smooth moving average kernel should be : symmetrical, not to width and not to sharp, bell shaped curve are often appropriates, the proposed moving average kernel can be symmetrical and can return extremely smooth results. I will use the Blackman filter as comparison.
The smooth version of the moving average can be used when the "smooth" setting is selected. Here power can only be an even number, if power is odd, power will be equal to the nearest lowest even number. When power = 0, the kernel is simply a parabola:
More smoothness can be achieved by using power = 2
In red the shapeshifting moving average, in green a Blackman filter of both length = 100. Higher values of power will create lower negative values near the border of the kernel shape, this often allow to retain information about the peaks and valleys in the input signal. Power = 6 approximate the Blackman filter pretty well.
Conclusion
A moving average using a modification of the 2nd derivative of the arc tangent function as kernel has been presented, the kernel is parametric and allow the user to switch from a low-lag moving average where the lag can be increased/decreased to a really smooth moving average.
As you can see once you get familiar with a function shape, you can know what would be the characteristics of a moving average using it as kernel, this is where you start getting intimate with moving averages.
On a side note, have you noticed that the views counter in posted ideas/indicators has been removed ? This is truly a marvelous idea don't you think ?
Thanks for reading !
ema_sw_alligatorA powerful and visually intuitive trading indicator that plots four exponential moving averages (EMA 8, 13, 48, 200) with customizable offsets and dynamic gradient visualization between the fast EMAs.
key features:
- four ema periods: displays ema 8, 13, 48, and 200 with customizable lengths
- customizable offsets: each ema can be shifted forward or backward in time (default: ema 200 offset 20, ema 48 offset 5, ema 13 offset 10, ema 8 offset 0)
- dynamic gradient system: visual color gradient between ema 8 and ema 13 that changes based on momentum:
-- green gradient when ema 8 crosses above ema 13 (bullish momentum)
-- red gradient when ema 8 crosses below ema 13 (bearish momentum)
- full customization:
- toggle individual ema visibility on/off
- customize colors for each ema line
- adjust gradient colors and transparency
- modify offset values for each ema
trading strategy:
ENTRY (Long)
- DAILY Chart
- 8 EMA crosses above 200 and 13 EMA
- Price remains above 200 EMA
- Break of Structure
Stay in:
- IF price stays above 8/13 and 48EMA after Entry
EXIT / STOP:
- Stop under recent swing low
- Exit when price crosses below 13 EMA IF under Entry
- Exit when price crosses below 48 EMA IF under Entry
trading applications:
- identify trend direction using the ema alignment
- spot potential entry points when ema 8 crosses ema 13 with gradient color confirmation
- use ema 48 and ema 200 as longer-term trend filters
- the offset feature helps anticipate potential support/resistance levels
- clear entry and exit rules based on EMA crossovers and price structure
settings overview:
- adjust ema lengths according to your trading style
- modify offsets to fine-tune the indicator's responsiveness
- customize colors for better visual clarity
- control gradient transparency to balance visibility and chart readability
perfect for swing traders, day traders, and anyone who uses moving average crossovers in their trading strategy. the visual gradient makes it easy to identify momentum shifts at a glance, while the clear trading rules provide a systematic approach to entries and exits.
FUMO MA Cross Matrix 9/21/50/100/200 FUMO MA Cross Matrix is a flexible and advanced indicator designed for traders who rely on moving average crossovers as part of their strategy.
🔹 Key Features:
Supports 5 types of Moving Averages: EMA, SMA, SMMA (RMA), WMA, HMA.
Includes 5 standard MAs: 9, 21, 50, 100, 200 (toggle on/off individually).
Choose which MA crosses to monitor (9×21, 21×50, 50×100, 100×200, and 6 extended combinations).
On-chart signals (labels) when crosses occur.
Alerts system for every selected cross and also summary alerts (“Any Cross Up/Down”).
Option to trigger signals only on confirmed bars (no repaint).
Fully adjustable label visibility and signal style.
🔹 Use Cases:
Detect trend shifts (short-term vs long-term).
Build scalping, swing, or position trading strategies.
Combine with price action or volume analysis for stronger setups.
Quickly react to Golden Cross and Death Cross events.
🔹 How to Use:
Select your preferred MA type (EMA, SMA, etc.).
Enable the MAs (9, 21, 50, 100, 200) you want to plot.
Choose which crossovers to track in the settings.
Enable/disable on-chart labels for better visualization.
Set up alerts:
“CROSS UP/DOWN X>Y” for specific pairs.
“ANY CROSS UP/DOWN” for aggregated signals.
📌 Example Alerts
MA Cross UP 9>21 on BTCUSDT 15m @ 65432
Any selected MA cross DOWN on AAPL 1D @ 195.2
52SIGNAL RECIPE Coinbase Institutional Smart Money DetectorCoinbase Institutional Smart Money Detector
◆ Overview
Coinbase Institutional Smart Money Detector is an innovative indicator that detects the buying and selling movements of institutional investors through Coinbase Prime in real-time. This powerful tool tracks the flow of funds from large institutions to provide valuable signals before significant market direction changes occur. It can be applied to Bitcoin charts on any exchange, allowing traders to follow the "smart money" movements of institutions anytime, anywhere.
The unique strength of this indicator lies in its comprehensive assessment of institutional investors' consecutive trading behaviors, volume patterns, and trend strength by analyzing Coinbase data in real-time. By providing clear visual representation of institutional fund flow data that is difficult for ordinary traders to access, you gain the opportunity to move alongside the big players in the market.
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◆ Key Features
• Coinbase Prime Data Analysis: Tracks institutional movements in real-time by analyzing data from Coinbase Prime, an institutional-only service
• Real-time Institutional Fund Flow Monitoring: Immediately detects large institutions' spot buying/selling activities, allowing positioning ahead of the market
• Universal Exchange Compatibility: Applicable to Bitcoin charts on any exchange, enabling use on your preferred trading platform
• Institutional Continuity Analysis: Identifies continuous institutional activity by tracking consecutive buying/selling patterns
• Smart Volume Analysis: Detects increased volume compared to averages and analyzes key trading time periods
• Trend Strength Measurement: Quantifies and displays the strength of upward/downward trends by analyzing candle patterns
• Intuitive Visualization: Clearly marks institutional activity points on charts through bar coloring and labels
• Real-time Strength Display: Calculates and displays current trend strength in a table in real-time
• Customizable Settings: Allows customization of key parameters to match your trading style
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◆ Understanding Signal Types
■ Institutional Buy Signal
• Definition: Occurs when institutional investors show consecutive buying activity through Coinbase Prime, accompanied by increased volume and strong upward trend
• Visual Representation: Translucent blue bar coloring and "Institution Buying Detected!" label on the candle where the buy signal occurs
• Market Interpretation: Indicates that institutional investors are actively buying spot Bitcoin, which is likely to lead to price increases
• Signal Strength Factors:
▶ Consecutive price increase patterns
▶ Above-average volume
▶ Strong upward trend strength measurement
▶ Significant price movement
■ Institutional Sell Signal
• Definition: Occurs when institutional investors show consecutive selling activity through Coinbase Prime, accompanied by increased volume and strong downward trend
• Visual Representation: Translucent pink bar coloring and "Institution Selling Detected!" label on the candle where the sell signal occurs
• Market Interpretation: Indicates that institutional investors are actively selling spot Bitcoin, which is likely to lead to price decreases
• Signal Strength Factors:
▶ Consecutive price decrease patterns
▶ Above-average volume
▶ Strong downward trend strength measurement
▶ Significant price movement
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◆ Understanding Trend Strength
■ Trend Strength Measurement Method
• Definition: Measures trend strength by analyzing the ratio of up/down candles over a recent period
• Visual Representation: Displayed in the table as "BULL STRENGTH" or "BEAR STRENGTH" with percentage value and "STRONG" or "WEAK" status
• Strength Threshold: Strong/weak determination according to user-configurable threshold
• Calculation Method:
▶ Upward trend strength = (Number of upward candles) / (Total analysis period)
▶ Downward trend strength = (Number of downward candles) / (Total analysis period)
▶ Displayed as "STRONG" when strength is above threshold, "WEAK" when below
■ Utilizing Trend Strength
• Signal Filtering: Generates signals only when trend strength is strong, reducing false signals
• Trend Confirmation: Evaluates the health and sustainability of the current market trend
• Entry/Exit Decisions: Consider entering in strong trends and exiting when trends weaken
• Risk Management: Develop strategies to reduce position size in weak trends and increase in strong trends
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◆ Practical Trading Applications
■ Institutional Buy Signal Strategy
• Trend Reversal Scenario:
▶ Setup: Strong institutional buy signal during a downtrend
▶ Entry: Buy after signal confirmation in the next candle
▶ Stop Loss: Below the low of the signal candle
▶ Take Profit: When reaching previous major resistance or when trend strength weakens
• Trend Continuation Scenario:
▶ Setup: Institutional buy signal after correction in an uptrend
▶ Entry: Buy after signal confirmation
▶ Stop Loss: Below recent major low
▶ Take Profit: Gradually take profits considering trend strength
■ Institutional Sell Signal Strategy
• Trend Reversal Scenario:
▶ Setup: Strong institutional sell signal during an uptrend
▶ Entry: Sell after signal confirmation in the next candle
▶ Stop Loss: Above the high of the signal candle
▶ Take Profit: When reaching previous major support or when trend strength weakens
• Trend Continuation Scenario:
▶ Setup: Institutional sell signal after bounce in a downtrend
▶ Entry: Sell after signal confirmation
▶ Stop Loss: Above recent major high
▶ Take Profit: Gradually take profits considering trend strength
■ Multi-Timeframe Approach
• Higher Timeframe Direction Confirmation:
▶ Check institutional signals and trend strength on daily/4-hour charts
▶ Use for setting main trading direction
• Lower Timeframe Entry Point Finding:
▶ Wait for lower timeframe signals that align with higher timeframe direction
▶ Use for capturing precise entry points
• Cross-Timeframe Signal Alignment:
▶ Signal strength increases when signals occur in the same direction across multiple timeframes
▶ Capture high-probability trading opportunities
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◆ Indicator Settings Guide
■ Main Setting Parameters
• Institutional Continuity Period:
▶ Purpose: Sets the period to check institutional consecutive buying/selling activity
▶ Lower value: Generates more signals, increases responsiveness
▶ Higher value: Reduces number of signals, increases reliability
• Trend Strength Threshold:
▶ Purpose: Sets the minimum threshold for determining strong trends
▶ Lower value: More signals, less filtering
▶ Higher value: Generates signals only in stronger trends, higher filtering
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◆ Synergy with Other Indicators
• Support/Resistance Levels:
▶ Institutional signals occurring at key support/resistance levels have higher probability
▶ Combination of key technical analysis levels and institutional activity provides powerful signals
• Moving Averages:
▶ Pay attention to institutional signals near key moving averages (50MA, 200MA)
▶ Strong trend change possibility when moving average crossovers coincide with institutional signals
• RSI/Momentum Indicators:
▶ Institutional buy signals in oversold conditions increase reversal probability
▶ Institutional sell signals in overbought conditions increase reversal probability
• Volume Profile:
▶ Institutional signals at high volume nodes confirm important price levels
▶ Institutional activity in key trading areas greatly impacts price direction
• Market Structure:
▶ Institutional signals near key market structures (higher highs/lows, lower highs/lows) suggest structural changes
▶ Coincidence of market structure changes and institutional activity indicates important trend turning points
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◆ Conclusion
Coinbase Institutional Smart Money Detector provides traders with valuable insights by tracking spot Bitcoin trading activities of institutional investors through Coinbase Prime in real-time. Because it can be applied to Bitcoin charts on any exchange, you can utilize it immediately on your preferred trading platform.
The core value of this indicator is providing intuitive visualization of institutional fund flow data that is difficult for ordinary traders to access. By comprehensively analyzing consecutive price movements, volume increases, and trend strength to capture institutional activity, you gain the opportunity to move alongside the big players in the market.
Clear buy/sell signals based on Coinbase Prime data and real-time trend strength measurements help traders quickly grasp market conditions and make strategic decisions. By integrating this powerful tool into your trading strategy, secure a competitive edge to understand where the market's smart money is flowing and position accordingly.
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※ Disclaimer: Like all trading tools, the Institutional Smart Money Detector should be used as a supplementary indicator and not relied upon exclusively for trading decisions. Past patterns of institutional behavior may not guarantee future market movements. Always employ appropriate risk management strategies in your trading.
Coinbase Institutional Smart Money Detector
◆ 개요
Coinbase Institutional Smart Money Detector는 코인베이스 프라임(Coinbase Prime)을 통한 기관 투자자들의 현물 비트코인 매수/매도 움직임을 실시간으로 감지하는 혁신적인 지표입니다. 이 강력한 도구는 대형 기관들의 자금 흐름을 추적하여 중요한 시장 방향 전환이 일어나기 전에 귀중한 신호를 제공합니다. 어떤 거래소의 비트코인 차트에도 적용 가능하여 트레이더들이 언제 어디서든 기관의 "스마트 머니" 움직임을 따라갈 수 있게 해줍니다.
이 지표의 독보적인 강점은 코인베이스 데이터를 실시간으로 분석하여 기관 투자자들의 연속적인 매매 행동, 거래량 패턴, 그리고 추세 강도를 종합적으로 평가한다는 점입니다. 일반 트레이더들이 접근하기 어려운 기관 자금 흐름 데이터를 시각적으로 명확하게 제공함으로써, 여러분은 시장의 큰 손들과 함께 움직일 수 있는 기회를 얻게 됩니다.
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◆ 주요 특징
• 코인베이스 프라임 데이터 분석: 기관 전용 서비스인 코인베이스 프라임의 데이터를 실시간으로 추적하여 기관의 움직임 포착
• 실시간 기관 자금 흐름 모니터링: 대형 기관들의 현물 매수/매도 활동을 즉각적으로 감지하여 시장에 앞서 포지셔닝 가능
• 모든 거래소 호환성: 어떤 거래소의 비트코인 차트에도 적용 가능하여 선호하는 트레이딩 플랫폼에서 활용 가능
• 기관 연속성 분석: 연속적인 매수/매도 패턴을 추적하여 기관의 지속적인 활동 식별
• 스마트 볼륨 분석: 평균 대비 거래량 증가를 감지하고 주요 거래 시간대를 분석
• 추세 강도 측정: 캔들 패턴을 분석해 상승/하락 추세의 강도를 수치화하여 표시
• 직관적 시각화: 바 컬러링과 라벨을 통해 기관 활동 지점을 차트에 명확하게 표시
• 실시간 강도 표시: 현재 추세의 강도를 실시간으로 계산하여 테이블에 표시
• 사용자 정의 설정: 주요 매개변수를 조정하여 자신의 트레이딩 스타일에 맞게 커스터마이징 가능
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◆ 신호 유형 이해하기
■ 기관 매수 신호
• 정의: 코인베이스 프라임을 통해 기관 투자자들이 연속적인 매수 활동을 보이며, 이와 함께 거래량 증가와 강한 상승 추세가 나타날 때 발생
• 시각적 표현: 매수 신호가 발생한 캔들에 반투명 파란색 바 컬러링과 함께 "Institution Buying Detected!" 라벨 표시
• 시장 해석: 기관 투자자들이 적극적으로 현물 비트코인을 매수하고 있으며, 이는 곧 가격 상승으로 이어질 가능성이 높음을 의미
• 신호 강도 요소:
▶ 연속적인 가격 상승 패턴
▶ 평균보다 높은 거래량
▶ 강한 상승 추세 강도 측정값
▶ 유의미한 가격 변동
■ 기관 매도 신호
• 정의: 코인베이스 프라임을 통해 기관 투자자들이 연속적인 매도 활동을 보이며, 이와 함께 거래량 증가와 강한 하락 추세가 나타날 때 발생
• 시각적 표현: 매도 신호가 발생한 캔들에 반투명 분홍색 바 컬러링과 함께 "Institution Selling Detected!" 라벨 표시
• 시장 해석: 기관 투자자들이 적극적으로 현물 비트코인을 매도하고 있으며, 이는 곧 가격 하락으로 이어질 가능성이 높음을 의미
• 신호 강도 요소:
▶ 연속적인 가격 하락 패턴
▶ 평균보다 높은 거래량
▶ 강한 하락 추세 강도 측정값
▶ 유의미한 가격 변동
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◆ 추세 강도 이해하기
■ 추세 강도 측정 방식
• 정의: 최근 일정 기간 동안의 상승/하락 캔들 비율을 분석하여 추세의 강도를 측정
• 시각적 표현: 테이블에 "BULL STRENGTH" 또는 "BEAR STRENGTH"로 표시되며, 백분율 값과 함께 "STRONG" 또는 "WEAK" 상태 표시
• 강도 임계값: 사용자가 설정 가능한 임계값에 따라 강함/약함 판정
• 계산 방식:
▶ 상승 추세 강도 = (상승 캔들 수) / (전체 분석 기간)
▶ 하락 추세 강도 = (하락 캔들 수) / (전체 분석 기간)
▶ 강도가 임계값 이상일 때 "STRONG", 미만일 때 "WEAK"로 표시
■ 추세 강도의 활용
• 신호 필터링: 추세 강도가 강할 때만 신호를 생성하여 허위 신호 감소
• 추세 확인: 현재 시장 추세의 건전성과 지속 가능성 평가
• 진입/퇴출 결정: 강한 추세에서 진입하고 약한 추세로 전환될 때 퇴출 고려
• 리스크 관리: 약한 추세에서는 포지션 크기를 줄이고, 강한 추세에서는 늘리는 전략 수립 가능
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◆ 실전 트레이딩 응용
■ 기관 매수 신호 활용 전략
• 추세 전환 시나리오:
▶ 설정: 하락 추세 중 강한 기관 매수 신호 발생
▶ 진입: 신호 확인 후 다음 캔들에서 매수
▶ 손절: 신호 캔들의 저점 아래
▶ 이익실현: 이전 주요 저항선 도달 시 또는 추세 강도가 약해질 때
• 추세 지속 시나리오:
▶ 설정: 상승 추세 중 조정 후 기관 매수 신호 발생
▶ 진입: 신호 확인 후 매수
▶ 손절: 최근 주요 저점 아래
▶ 이익실현: 추세 강도를 고려하여 단계적으로 이익실현
■ 기관 매도 신호 활용 전략
• 추세 전환 시나리오:
▶ 설정: 상승 추세 중 강한 기관 매도 신호 발생
▶ 진입: 신호 확인 후 다음 캔들에서 매도
▶ 손절: 신호 캔들의 고점 위
▶ 이익실현: 이전 주요 지지선 도달 시 또는 추세 강도가 약해질 때
• 추세 지속 시나리오:
▶ 설정: 하락 추세 중 반등 후 기관 매도 신호 발생
▶ 진입: 신호 확인 후 매도
▶ 손절: 최근 주요 고점 위
▶ 이익실현: 추세 강도를 고려하여 단계적으로 이익실현
■ 다중 시간프레임 접근법
• 상위 시간프레임 방향성 확인:
▶ 일봉/4시간봉에서 기관 신호 및 추세 강도 확인
▶ 주 트레이딩 방향 설정에 활용
• 하위 시간프레임 진입점 찾기:
▶ 상위 시간프레임 방향과 일치하는 하위 시간프레임 신호 대기
▶ 정밀한 진입점 포착에 활용
• 시간프레임 간 신호 일치 확인:
▶ 여러 시간프레임에서 동일한 방향의 신호가 발생할 때 신호 강도 증가
▶ 높은 확률의 트레이딩 기회 포착
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◆ 지표 설정 가이드
■ 주요 설정 매개변수
• Institutional Continuity Period (기관 연속성 확인 기간):
▶ 목적: 기관의 연속적인 매수/매도 활동을 확인할 기간 설정
▶ 낮은 값: 더 많은 신호 생성, 반응성 증가
▶ 높은 값: 신호 수 감소, 신뢰성 증가
• Trend Strength Threshold (추세 강도 임계값):
▶ 목적: 추세가 강하다고 판단할 최소 임계값 설정
▶ 낮은 값: 더 많은 신호, 낮은 필터링
▶ 높은 값: 더 강한 추세에서만 신호 생성, 높은 필터링
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◆ 다른 지표와의 시너지
• 지지/저항 레벨:
▶ 주요 지지/저항 레벨에서 발생하는 기관 신호는 확률이 더 높음
▶ 기술적 분석의 핵심 레벨과 기관 활동의 결합은 강력한 시그널 제공
• 이동평균선:
▶ 주요 이동평균선(50MA, 200MA) 근처에서 발생하는 기관 신호 주목
▶ 이동평균선 돌파와 기관 신호가 일치할 때 강한 추세 변화 가능성
• RSI/모멘텀 지표:
▶ 과매수/과매도 상태에서 발생하는 기관 신호는 반전 가능성 높임
▶ 모멘텀 다이버전스와 기관 신호의 일치는 강력한 반전 신호
• 볼륨 프로파일:
▶ 높은 볼륨 노드에서 발생하는 기관 신호는 중요한 가격 레벨 확인
▶ 주요 거래 영역에서의 기관 활동은 가격 방향에 큰 영향 미침
• 시장 구조:
▶ 주요 시장 구조(높은 고점/저점, 낮은 고점/저점) 근처에서 발생하는 기관 신호는 구조 변화 암시
▶ 시장 구조 변화와 기관 활동의 일치는 중요한 추세 전환점 표시
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◆ 결론
Coinbase Institutional Smart Money Detector는 코인베이스 프라임을 통한 기관 투자자들의 현물 비트코인 거래 활동을 실시간으로 추적하여 트레이더들에게 귀중한 통찰력을 제공합니다. 어떤 거래소의 비트코인 차트에도 적용 가능하기 때문에, 여러분이 선호하는 트레이딩 플랫폼에서 바로 활용할 수 있습니다.
이 지표의 핵심 가치는 일반 트레이더들이 접근하기 어려운 기관 자금 흐름 데이터를 직관적으로 시각화하여 제공한다는 점입니다. 연속적인 가격 움직임, 거래량 증가, 그리고 추세 강도를 종합적으로 분석하여 기관의 활동을 포착함으로써, 여러분은 시장의 큰 손들과 함께 움직일 수 있는 기회를 얻게 됩니다.
코인베이스 프라임 데이터를 기반으로 한 명확한 매수/매도 신호와 실시간 추세 강도 측정은 트레이더들이 시장 상황을 한눈에 파악하고 신속하게 전략적 결정을 내릴 수 있게 도와줍니다. 이 강력한 도구를 여러분의 트레이딩 전략에 통합함으로써, 시장의 스마트 머니가 어디로 흘러가는지 파악하고 그에 따라 포지셔닝할 수 있는 경쟁 우위를 확보하세요.
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※ 면책 조항: 모든 트레이딩 도구와 마찬가지로, Institutional Smart Money Detector는 보조 지표로 사용해야 하며 트레이딩 결정을 전적으로 의존해서는 안 됩니다. 과거의 기관 행동 패턴이 미래 시장 움직임을 보장하지는 않습니다. 항상 적절한 리스크 관리 전략을 트레이딩에 활용하세요.
Simple Multi-Timeframe Trends with RSI (Realtime)Simple Multi-Timeframe Trends with RSI Realtime Updates
Overview
The Simple Multi-Timeframe Trends with RSI Realtime Updates indicator is a comprehensive dashboard designed to give you an at-a-glance understanding of market trends across nine key timeframes, from one minute (M1) to one month (M).
It moves beyond simple moving average crossovers by calculating a sophisticated Trend Score for each timeframe. This score is then intelligently combined into a single, weighted Confluence Signal , which adapts to your personal trading style. With integrated RSI and divergence detection, SMTT provides a powerful, all-in-one tool to confirm your trade ideas and stay on the right side of the market.
Key Features
Automatic Trading Presets: The most powerful feature of the script. Simply select your trading style, and the indicator will automatically adjust all internal parameters for you:
Intraday: Uses shorter moving averages and higher sensitivity, focusing on lower timeframe alignment for quick moves.
Swing Trading: A balanced preset using medium-term moving averages, ideal for capturing trends that last several days or weeks.
Investment: Uses long-term moving averages and lower sensitivity, prioritizing the major trends on high timeframes.
Advanced Trend Scoring: The trend for each timeframe isn't just "up" or "down". The score is calculated based on a combination of:
Price vs. Moving Average: Is the price above or below the MA?
MA Slope: Is the trend accelerating or decelerating? A steep slope indicates a strong trend.
Price Momentum: How quickly has the price moved recently?
Volatility Adjustment: The score's quality is adjusted based on current market volatility (using ATR) to filter out choppy conditions.
Weighted Confluence Score: The script synthesizes the trend scores from all nine timeframes into a single, actionable signal. The weights are dynamically adjusted based on your selected Trading Style , ensuring the most relevant timeframes have the most impact on the final result.
Integrated RSI & Divergence: Each timeframe includes a smoothed RSI value to help you spot overbought/oversold conditions. It also flags potential bullish (price lower, RSI higher) and bearish (price higher, RSI lower) divergences, which can be early warnings of a trend reversal.
Clean & Customizable Dashboard: The entire analysis is presented in a clean, easy-to-read table on your chart. You can choose its position and optionally display the raw numerical scores for a deeper analysis.
How to Use It
1. Add to Chart: Apply the "Simple Multi-Timeframe Trends" indicator to your chart.
2. Select Your Style: This is the most important step. Go to the indicator settings and choose the Trading Style that best fits your strategy (Intraday, Swing Trading, or Investment). All calculations will instantly adapt.
3. Analyze the Dashboard:
Look at the Trend row to see the direction and strength of the trend on individual timeframes. Strong alignment (e.g., all green or all red) indicates a powerful, market-wide move.
Check the RSI row. Is the trend overextended (RSI > 60) or is there room to run? Look for the fuchsia color, which signals a divergence and warrants caution.
Focus on the Signal row. This is your summary. A "STRONG SIGNAL" with high alignment suggests a high-probability setup. A "NEUTRAL" or "Weak" signal suggests waiting for a better opportunity.
4. Confirm Your Trades: Use the SMTT dashboard as a confirmation tool. For example, if you are looking for a long entry, wait for the dashboard to show a "BULLISH" or "STRONG SIGNAL" to confirm that the broader market structure supports your trade.
Dashboard Legend
Trend Row
This row shows the trend direction and strength for each timeframe.
⬆⬆ (Dark Green): Ultra Bullish - Very strong, established uptrend.
⬆ (Green): Strong Bullish - Confident uptrend.
▲ (Light Green): Bullish - The beginning of an uptrend or a weak uptrend.
━ (Orange): Neutral - Sideways or consolidating market.
▼ (Light Red): Bearish - The beginning of a downtrend or a weak downtrend.
⬇ (Red): Strong Bearish - Confident downtrend.
⬇⬇ (Dark Red): Ultra Bearish - Very strong, established downtrend.
RSI Row
This row displays the smoothed RSI value and its condition.
Green Text: Oversold (RSI < 40). Potential for a bounce or reversal upwards.
Red Text: Overbought (RSI > 60). Potential for a pullback or reversal downwards.
Fuchsia (Pink) Text: Divergence Detected! A potential reversal is forming.
White Text: Neutral (RSI between 40 and 60).
Signal Row
This is the final, weighted confluence of all timeframes.
Label:
🚀 STRONG SIGNAL / 💥 STRONG SIGNAL: High confluence and strong momentum.
🟢 BULLISH / 🔴 BEARISH: Clear directional bias across relevant timeframes.
🟡 Weak + / 🟠 Weak -: Minor directional bias, suggests caution.
⚪ NEUTRAL: No clear directional trend; market is likely choppy or undecided.
Numerical Score: The raw weighted confluence score. The further from zero, the stronger the signal.
Alignment %: The percentage of timeframes (out of 9) that are showing a clear bullish or bearish trend. Higher percentages indicate a more unified market.
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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• .
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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Super Arma Institucional PRO v6.3Super Arma Institucional PRO v6.3
Description
Super Arma Institucional PRO v6.3 is a multifunctional indicator designed for traders looking for a clear and objective analysis of the market, focusing on trends, key price levels and high liquidity zones. It combines three essential elements: moving averages (EMA 20, SMA 50, EMA 200), dynamic support and resistance, and volume-based liquidity zones. This integration offers an institutional view of the market, ideal for identifying strategic entry and exit points.
How it Works
Moving Averages:
EMA 20 (orange): Sensitive to short-term movements, ideal for capturing fast trends.
SMA 50 (blue): Represents the medium-term trend, smoothing out fluctuations.
EMA 200 (red): Indicates the long-term trend, used as a reference for the general market bias.
Support and Resistance: Calculated based on the highest and lowest prices over a defined period (default: 20 bars). These dynamic levels help identify zones where the price may encounter barriers or supports.
Liquidity Zones: Purple rectangles are drawn in areas of significantly above-average volume, indicating regions where large market participants (institutional) may be active. These zones are useful for anticipating price movements or order absorption.
Purpose
The indicator was developed to provide a clean and institutional view of the market, combining classic tools (moving averages and support/resistance) with modern liquidity analysis. It is ideal for traders operating swing trading or position trading strategies, allowing to identify:
Short, medium and long-term trends.
Key support and resistance levels to plan entries and exits.
High liquidity zones where institutional orders can influence the price.
Settings
Show EMA 20 (true): Enables/disables the 20-period EMA.
Show SMA 50 (true): Enables/disables the 50-period SMA.
Show EMA 200 (true): Enables/disables the 200-period EMA.
Support/Resistance Period (20): Sets the period for calculating support and resistance levels.
Liquidity Sensitivity (20): Period for calculating the average volume.
Minimum Liquidity Factor (1.5): Multiplier of the average volume to identify high liquidity zones.
How to Use
Moving Averages:
Crossovers between the EMA 20 and SMA 50 may indicate short/medium-term trend changes.
The EMA 200 serves as a reference for the long-term bias (above = bullish, below = bearish).
Support and Resistance: Use the red (resistance) and green (support) lines to identify reversal or consolidation zones.
Liquidity Zones: The purple rectangles highlight areas of high volume, where the price may react (reversal or breakout). Consider these zones to place orders or manage risks.
Adjust the parameters according to the asset and timeframe to optimize the analysis.
Notes
The chart should be configured only with this indicator to ensure clarity.
Use on timeframes such as 1 hour, 4 hours or daily for better visualization of liquidity zones and support/resistance levels.
Avoid adding other indicators to the chart to keep the script output easily identifiable.
The indicator is designed to be clean, without explicit buy/sell signals, following an institutional approach.
This indicator is perfect for traders who want a visually clear and powerful tool to trade based on trends, key levels and institutional behavior.
Customizable 10‑MA SuiteCustomizable 10‑Moving‑Average Suite
OverviewPlot up to 10 independent moving averages on a single chart. Every line can be tailored to your trading style with adjustable length, timeframe, MA type (SMA, EMA, WMA, RMA, VWMA, HMA, LinReg), data source, colour, width, and plot style.
Key Features
True multi‑time‑frame support via request.security(): mix intraday and higher‑time‑frame MAs effortlessly.
Fine‑grained visibility control: toggle each MA on/off to keep charts clean and script performance high.
Versatile display options: choose between line, step, histogram, or area plots for every MA.
Typical Use‑Cases
Quickly compare short‑, medium‑, and long‑term trends.
Identify dynamic support/resistance and moving‑average crossovers.
Add confluence to existing strategies or discretionary setups.
Pro TipHighlight your primary trend MA with a thicker line and bolder colour, while setting secondary MAs to thinner or dashed styles—this keeps focus where it matters and prevents visual clutter.
Enjoy!
SynchroTrend Oscillator (STO) [PhenLabs]📊 SynchroTrend Oscillator
Version: PineScript™ v5
📌 Description
The SynchroTrend Oscillator (STO) is a multi-timeframe synchronization tool that combines trend information from three distinct timeframes into a single, easy-to-interpret oscillator ranging from -100 to +100.
This indicator solves the common problem of having to analyze multiple timeframe charts separately by consolidating trend direction and strength across different time horizons. The STO helps traders identify when markets are truly synchronized across timeframes, potentially indicating stronger trend conditions and higher probability trading opportunities.
Using either Moving Average crossovers or RSI analysis as the trend definition metric, the STO provides a comprehensive view of market structure that adapts to various trading strategies and market conditions.
🚀 Points of Innovation
Triple-timeframe synchronization in a single view eliminates chart switching
Dual trend detection methods (MA vs Price or RSI) for flexibility across different markets
Dynamic color intensity that automatically increases with signal strength
Scaled oscillator format (-100 to +100) for intuitive trend strength interpretation
Customizable signal thresholds to match your risk tolerance and trading style
Visual alerts when markets reach full synchronization states
🔧 Core Components
Trend Scoring System: Calculates a binary score (+1, -1, or 0) for each timeframe based on selected metrics, providing clear trend direction
Multi-Timeframe Synchronization: Combines and scales trend scores from all three timeframes into a single oscillator
Dynamic Visualization: Adjusts color transparency based on signal strength, creating an intuitive visual guide
Threshold System: Provides customizable levels for identifying potentially significant trading opportunities
🔥 Key Features
Triple Timeframe Analysis: Synchronizes three user-defined timeframes (default: 60min, 15min, 5min) into one view
Dual Trend Detection Methods: Choose between Moving Average vs Price or RSI-based trend determination
Adjustable Signal Smoothing: Apply EMA, SMA, or no smoothing to the oscillator output for your preferred signal responsiveness
Dynamic Color Intensity: Colors become more vibrant as signal strength increases, helping identify strongest setups
Customizable Thresholds: Set your own buy/sell threshold levels to match your trading strategy
Comprehensive Alerts: Six different alert conditions for crossing thresholds, zero line, and full synchronization states
🎨 Visualization
Oscillator Line: The main line showing the synchronized trend value from -100 to +100
Dynamic Fill: Area between oscillator and zero line changes transparency based on signal strength
Threshold Lines: Optional dotted lines indicating buy/sell thresholds for visual reference
Color Coding: Green for bullish synchronization, red for bearish synchronization
📖 Usage Guidelines
Timeframe Settings
Timeframe 1: Default: 60 (1 hour) - Primary higher timeframe for trend definition
Timeframe 2: Default: 15 (15 minutes) - Intermediate timeframe for trend definition
Timeframe 3: Default: 5 (5 minutes) - Lower timeframe for trend definition
Trend Calculation Settings
Trend Definition Metric: Default: “MA vs Price” - Method used to determine trend on each timeframe
MA Type: Default: EMA - Moving Average type when using MA vs Price method
MA Length: Default: 21 - Moving Average period when using MA vs Price method
RSI Length: Default: 14 - RSI period when using RSI method
RSI Source: Default: close - Price data source for RSI calculation
Oscillator Settings
Smoothing Type: Default: SMA - Applies smoothing to the final oscillator
Smoothing Length: Default: 5 - Period for the smoothing function
Visual & Threshold Settings
Up/Down Colors: Customize colors for bullish and bearish signals
Transparency Range: Control how transparency changes with signal strength
Line Width: Adjust oscillator line thickness
Buy/Sell Thresholds: Set levels for potential entry/exit signals
✅ Best Use Cases
Trend confirmation across multiple timeframes
Finding high-probability entry points when all timeframes align
Early detection of potential trend reversals
Filtering trade signals from other indicators
Market structure analysis
Identifying potential divergences between timeframes
⚠️ Limitations
Like all indicators, can produce false signals during choppy or ranging markets
Works best in trending market conditions
Should not be used in isolation for trading decisions
Past performance is not indicative of future results
May require different settings for different markets or instruments
💡 What Makes This Unique
Combines three timeframes in a single visualization without requiring multiple chart windows
Dynamic transparency feature that automatically emphasizes stronger signals
Flexible trend definition methods suitable for different market conditions
Visual system that makes multi-timeframe analysis intuitive and accessible
🔬 How It Works
1. Trend Evaluation:
For each timeframe, the indicator calculates a trend score (+1, -1, or 0) using either:
MA vs Price: Comparing close price to a moving average
RSI: Determining if RSI is above or below 50
2. Score Aggregation:
The three trend scores are combined and then scaled to a range of -100 to +100
A value of +100 indicates all timeframes show bullish conditions
A value of -100 indicates all timeframes show bearish conditions
Values in between indicate varying degrees of alignment
3. Signal Processing:
The raw oscillator value can be smoothed using EMA, SMA, or left unsmoothed
The final value determines line color, fill color, and transparency settings
Threshold levels are applied to identify potential trading opportunities
💡 Note:
The SynchroTrend Oscillator is most effective when used as part of a comprehensive trading strategy that includes proper risk management techniques. For best results, consider using the oscillator in conjunction with support/resistance levels, price action analysis, and other complementary indicators that align with your trading style.
ALMA 20, 50, 200The ALMA (Arnaud Legoux Moving Average) crossover strategy uses two ALMA lines (fast and slow) to generate buy/sell signals, aiming to reduce lag and noise compared to traditional moving averages, and is often combined with volume filters for improved accuracy.
Here's a more detailed explanation:
What it is:
The ALMA indicator is a moving average (MA) variant designed to reduce lag and improve responsiveness while maintaining a smooth curve, using a Gaussian filter.
How it works:
ALMA calculates two moving averages, one from left to right and one from right to left, and then processes the output through a customizable formula for increased smoothness or responsiveness.
Crossover Strategy:
A common ALMA strategy involves using two ALMA lines with different lengths (fast and slow). A buy signal is generated when the fast ALMA crosses above the slow ALMA, and a sell signal when the fast ALMA crosses below the slow ALMA.
Benefits:
ALMA offers advantages like reduced lag, smoothness, and filtering capabilities, making it useful for identifying trends and potential reversals.
Potential Risks:
Like any indicator, ALMA can produce false signals, so it's crucial to combine it with other indicators and analyze price action.
Parameters:
ALMA has parameters like "Length" (number of periods), "Sigma" (filter's range, affecting responsiveness), and "Offset" (for accessing data of different candles).
Other uses:
ALMA can also be used for trend identification, dynamic support and resistance, and combined with other indicators to enhance trading strategies.
Azlan MA Silang PLUS++Overview
Azlan MA Silang PLUS++ is an advanced moving average crossover trading indicator designed for traders who want to jump back into the market when they missed their first opportunity to take a trade. It implements a sophisticated dual moving average system with customizable settings and re-entry signals, making it suitable for both trend following and swing trading strategies.
Key Features
• Dual Moving Average System with multiple MA types (EMA, SMA, WMA, LWMA)
• Customizable price sources for each moving average
• Smart re-entry system with configurable maximum re-entries
• Visual signals with background coloring and shape markers
• Comprehensive alert system for both initial and re-entry signals
• Flexible parameter customization through input options
Input Parameters
Moving Average Configuration
• MA1 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA2 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA1 Length: Minimum value 1 (default: 8)
• MA2 Length: Minimum value 1 (default: 15)
• MA1 & MA2 Shift: Offset values for moving averages
• Price Sources: Configurable for each MA (Open, High, Low, Close, HL/2, HLC/3, HLCC/4)
Re-entry System
• Enable/Disable re-entry signals
• Maximum re-entries allowed (default: 3)
Technical Implementation
Price Source Calculation
The script implements a flexible price source system through the price_source() function:
• Supports standard OHLC values
• Includes compound calculations (HL/2, HLC/3, HLCC/4)
• Defaults to close price if invalid source specified
Moving Average Types
Implements four MA calculations:
1. SMA (Simple Moving Average)
2. EMA (Exponential Moving Average)
3. WMA (Weighted Moving Average)
4. LWMA (Linear Weighted Moving Average)
Signal Generation Logic
Initial Signals
• Buy Signal: MA1 crosses above MA2 with price above both MAs
• Sell Signal: MA1 crosses below MA2 with price below both MAs
Re-entry Signals
Re-entry system activates when:
1. Price crosses under MA1 in buy mode (or over in sell mode)
2. Price returns to cross back over MA1 (or under for sells)
3. Position relative to MA2 confirms trend direction
4. Number of re-entries hasn't exceeded maximum allowed
Visual Components
• MA1: Blue line (width: 2)
• MA2: Red line (width: 2)
• Background Colors:
o Green (60% opacity): Bullish conditions
o Red (60% opacity): Bearish conditions
• Signal Markers:
o Initial Buy/Sell: Up/Down arrows with "BUY"/"SELL" labels
o Re-entry Buy/Sell: Up/Down arrows with "RE-BUY"/"RE-SELL" labels
Alert System
Generates alerts for:
• Initial buy/sell signals
• Re-entry opportunities
• Alerts include ticker and timeframe information
• Configured for once-per-bar-close frequency
Usage Tips
1. Moving Average Selection
o Shorter periods (MA1) capture faster moves
o Longer periods (MA2) identify overall trend
o EMA responds faster to price changes than SMA
2. Re-entry System
o Best used in strong trending markets
o Limit maximum re-entries based on market volatility
o Monitor price action around MA1 for potential re-entry points
3. Risk Management
o Use additional confirmation indicators
o Set appropriate stop-loss levels
o Consider market conditions when using re-entry signals
Code Structure
The script follows a modular design with distinct sections:
1. Input parameter definitions
2. Helper functions for price and MA calculations
3. Main signal generation logic
4. Visual elements and plotting
5. Alert system implementation
This organization makes the code maintainable and easy to modify for custom needs.
G-Ron TrendCloudOverview
The G-Ron TrendCloud Indicator is a powerful trading tool designed to identify trend momentum and potential reversals across multiple timeframes. Using cloud-based visualizations, this indicator provides clear, actionable signals, making it ideal for all traders.
How Does It Work?
The G-Ron TrendCloud uses advanced differential calculations to pinpoint key momentum levels in the market. It identifies both trend continuation and reversals, highlighting strong momentum shifts with clear visual cues.
Key Features
Trend Cloud – This cloud highlights the dominant market trend, indicating whether the market is trending upwards or downwards.
Reversal Cloud – This cloud provides early warning signals of potential trend reversals, helping traders time entries and exits more effectively.
Trend Reversion Line – This line acts as a key pivot point in the market, indicating where the long-term trend is likely to shift.
The three components change color dynamically based on market conditions:
Yellow for uptrends
Red for downtrends
What Makes It Unique?
Many indicators rely on simple or exponential moving average crossovers. In contrast, the G-Ron TrendCloud utilizes differential equations to analyze the interaction between moving averages and pinpoint the precise price levels where significant momentum shifts—referred to as trend pivots—are likely to occur. These trend pivots are categorized by both term (short, medium, long) and direction (continuation or reversal). It's crucial to note that the components of the G-Ron TrendCloud are not moving averages, making it impossible to replicate its insights using any SMA or EMA settings.
Understanding The Components
Trend Cloud: represents the area between the short-term trend pivot line and the medium-term trend pivot line. It illustrates the prevailing market trend.
Reversal Cloud: represents the area between the medium-term trend pivot line and the reversal pivot line. It provides insights into the strength of the trend.
Trend Reversion Line: the long-term trend pivot line which acts as a mean reversion for the Trend Cloud.
How To Use It
Trend Continuation: When price is above or within the yellow Trend Cloud it signals a strong bullish trend continuation. When price is below or within the red Trend Cloud it signals a strong bearish trend continuation.
Reversal Signals: When price breaks through the Reversal Cloud it signals a change in the prevailing market trend.
Long-Term Confirmation: Bullish trends are stronger, and price is more likely to continue higher when the Trend Reversion Line is yellow. Bearish trends are stronger, and price is more likely to continue lower when the Trend Reversion Line is red.
Multi-Timeframe View: For deeper insights, use the indicator across various timeframes. Shorter timeframes are ideal for intraday trades, while longer timeframes offer better signals for position traders.
Recommended Settings
The Long-Term Timeframe interval setting should always be at least three times bigger than the current timeframe displayed on your chart.
Why It’s Invite Only
The G-Ron TrendCloud utilizes a unique methodology that cannot be replicated by standard indicators. It provides valuable insights and clear visual cues to help traders accurately identify market trends. It greatly improves decision making and timing for both trade entries and exits, increasing the likelihood of successful outcomes.
Please see the authors instructions below to get instant access to this indicator.
The Exact IndicatorStruggling to get in on a trade? Don't know where to take profits? This indicator might help - it only displays the Buy, Stop Loss and Take profit points when certain conditions are met.
The indicator combines a moving average crossover strategy with trend analysis to identify potential buy opportunities in the market. It utilises a short-term and long-term Simple Moving Average (SMA) to generate buy signals when the short-term SMA crosses above the long-term SMA. Additionally, it displays take profit and stop loss levels, along with a background colour indicating the overall trend strength.
Pros :
Clear Signals : Provides straightforward buy signals based on a well-known crossover strategy, making it easy for traders to identify entry points.
Visual Aids : The inclusion of take profit and stop loss levels, along with background trend colors, enhances decision-making and risk management.
Trend Awareness : The background colour changes based on trend strength, allowing traders to quickly assess market conditions.
Cons :
Lagging Indicator : Moving averages are inherently lagging, which can result in delayed signals, especially in volatile markets.
False Signals : Crossover strategies can produce false signals during sideways or choppy market conditions, leading to potential losses.
Limited Scope : The indicator focuses primarily on buy signals, potentially missing out on other trading opportunities (like short-selling) in a bearish market.
Overall, while this indicator can be a useful tool for identifying bullish trends and potential entry points, traders should use it in conjunction with other analysis methods and risk management strategies to mitigate its limitations.
MA Cross HeatmapThe Moving Average Cross Heatmap Created by Technicator , visualizes the crossing distances between multiple moving averages using a heat map style color coding.
The main purpose of this visualization is to help identify potential trend changes or trading opportunities by looking at where the moving averages cross over each other.
Key Features:
Can plot up to 9 different moving average with their cross lengths you set
Uses a heat map to show crossing distances between the MAs
Adjustable settings like crossing length percentage, color scheme, color ceiling etc.
Overlay style separates the heat map from the price chart
This is a unique way to combine multiple MA analysis with a visual heat map representation on one indicator. The code allows you to fine-tune the parameters to suit your trading style and preferences. Worth checking out if you trade using multiple moving average crossovers as part of your strategy.
LoTek - CT Moving Average Crossover Indicator - MTF [CT/LoTek]This is a shameless fork of Caretaker's excellent CT MAC indicator. This indicator has 2 new features. I've added the ability to select a different timeframe for each moving average. This way you can set a Daily 10, or a weekly 20 or any other of your favorite lines and it will always be there on your chart. The other new features is the ability to select VWMA as well as SMA and EMA for each moving average. VWMA is pretty nice to watch as well, and with 9 moving averages to mix and match, I'm sure you'll find something worth keeping.
To fork this, I created a new "resolution" variable for each MA. I also created a new function that uses the request.security call to get the specific timeframe resolution. I backtested this with CT's OG script and the numbers stay the same... but I have a sneaky suspicion that VWMAs are not showing proper crossover values. So keep that in mind. The drawn lines are fine, but the crossover data when using VWMA may be off. I wrote the new function to default to EMA, so if it fails at VWMA, it will just show you EMA data.
Let's see, what else... please tell me if you find any bugs or want any other features baked in.
EMA Slope/Angle OscillatorEMA Slope/Angle Oscillator, Multiple Moving Average Oscillator, Multiple type
Moving Averages HMA,EMA,WMA,SMA, VWMA,VWAP provided.
The angle is calculated between the Slow MA and Fast MA and the difference between the angle is plotted as Histogram.
Additionally Buy Sell Signals are plotted as green and red Dots.
its very easy to judge the movement of price Bearish/Bullish.
Bearish if price below 0 line
Bullish if price above 0 line
Zero crossing is Moving Average Crossover.
Trend Filter is provided to filter opposite signals.
Angle Threshold is provided to filter low angle false signals.
Dead zone is plotted around Zero Line. Trades can be taken after Threshold angle or Dead zone is crossed
Its interesting to see how different Moving Averages move along with price Action.
Portfolio Backtester Engine█ OVERVIEW
Portfolio Backtester Engine (PBTE). This tool will allow you to backtest strategies across multiple securities at once. Allowing you to easier understand if your strategy is robust. If you are familiar with the PineCoders backtesting engine , then you will find this indicator pleasant to work with as it is an adaptation based on that work. Much of the functionality has been kept the same, or enhanced, with some minor adjustments I made on the account of creating a more subjectively intuitive tool.
█ HISTORY
The original purpose of the backtesting engine (`BTE`) was to bridge the gap between strategies and studies . Previously, strategies did not contain the ability to send alerts, but were necessary for backtesting. Studies on the other hand were necessary for sending alerts, but could not provide backtesting results . Often, traders would have to manage two separate Pine scripts to take advantage of each feature, this was less than ideal.
The `BTE` published by PineCoders offered a solution to this issue by generating backtesting results under the context of a study(). This allowed traders to backtest their strategy and simultaneously generate alerts for automated trading, thus eliminating the need for a separate strategy() script (though, even converting the engine to a strategy was made simple by the PineCoders!).
Fast forward a couple years and PineScript evolved beyond these issues and alerts were introduced into strategies. The BTE was not quite as necessary anymore, but is still extremely useful as it contains extra features and data not found under the strategy() context. Below is an excerpt of features contained by the BTE:
"""
More than `40` built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
"""
Before I go any further, I want to be clear that the BTE is STILL a good tool and it is STILL very useful. The Portfolio Backtesting Engine I am introducing is only a tangental advancement and not to be confused as a replacement, this tool would not have been possible without the `BTE`.
█ THE PROBLEM
Most strategies built in Pine are limited by one thing. Data. Backtesting should be a rigorous process and researchers should examine the performance of their strategy across all market regimes; that includes, bullish and bearish markets, ranging markets, low volatility and high volatility. Depending on your TV subscription The Pine Engine is limited to 5k-20k historical bars available for backtesting, which can often leave the strategy results wanting. As a general rule of thumb, strategies should be tested across a quantity of historical bars which will allow for at least 100 trades. In many cases, the lack of historical bars available for backtesting and frequency of the strategy signals produces less than 100 trades, rendering your strategy results inconclusive.
█ THE SOLUTION
In order to be confident that we have a robust strategy we must test it across all market regimes and we must have over 100 trades. To do this effectively, researchers can use the Portfolio Backtesting Engine (PBTE).
By testing a strategy across a carefully selected portfolio of securities, researchers can now gather 5k-20k historical bars per security! Currently, the PTBE allows up to 5 securities, which amounts to 25k-100k historical bars.
█ HOW TO USE
1 — Add the indicator to your chart.
• Confirm inputs. These will be the most important initial values which you can change later by clicking the gear icon ⚙ and opening up the settings of the indicator.
2 — Select a portfolio.
• You will want to spend some time carefully selecting a portfolio of securities.
• Each security should be uncorrelated.
• The entire portfolio should contain a mix of different market regimes.
You should understand that strategies generally take advantage of one particular type of market regime. (trending, ranging, low/high volatility)
For example, the default RSI strategy is typically advantageous during ranging markets, whereas a typical moving average crossover strategy is advantageous in trending markets.
If you were to use the standard RSI strategy during a trending market, you might be selling when you should be buying.
Similarily, if you use an SMA crossover during a ranging market, you will find that the MA's may produce many false signals.
Even if you build a strategy that is designed to be used only in a trending market, it is still best to select a portfolio of all market regimes
as you will be able to test how your strategy will perform when the market does something unexpected.
3 — Test a built-in strategy or add your own.
• Navigate to gear icon ⚙ (settings) of strategy.
• Choose your options.
• Select a Main Entry Strat and Alternate Entry Strat .
• If you want to add your own strategy, you will need to modify the source code and follow the built-in example.
• You will only need to generate (buy 1 / sell -1/ neutral 0) signals.
• Select a Filter , by default these are all off.
• Select an Entry Stop - This will be your stop loss placed at the trade entry.
• Select Pyamiding - This will allow you to stack positions. By default this is off.
• Select Hard Exits - You can also think of these as Take Profits.
• Let the strategy run and take note of the display tables results.
• Portfolio - Shows each security.
• The strategy runs on each asset in your portfolio.
• The initial capital is equally distributed across each security.
So if you have 5 securities and a starting capital of 100,000$ then each security will run the strategy starting with 20,000$
The total row will aggregate the results on a bar by bar basis showing the total results of your initial capital.
• Net Profit (NP) - Shows profitability.
• Number of Trades (#T) - Shows # of trades taken during backtesting period.
• Typically will want to see this number greater than 100 on the "Total" row.
• Average Trade Length (ATL) - Shows average # of days in a trade.
• Maximum Drawdown (MD ) - Max peak-to-valley equity drawdown during backtesting period.
• This number defines the minimum amount of capital required to trade the system.
• Typically, this shouldn’t be lower than 34% and we will want to allow for at least 50% beyond this number.
• Maximum Loss (ML) - Shows largest loss experienced on a per-trade basis.
• Normally, don’t want to exceed more than 1-2 % of equity.
• Maximum Drawdown Duration (MDD) - The longest duration of a drawdown in equity prior to a new equity peak.
• This number is important to help us psychologically understand how long we can expect to wait for a new peak in account equity.
• Maximum Consecutive Losses (MCL) - The max consecutive losses endured throughout the backtesting period.
• Another important metric for trader psychology, this will help you understand how many losses you should be prepared to handle.
• Profit to Maximum Drawdown (P:MD) - A ratio for the average profit to the maximum drawdown.
• The higher the ratio is, the better. Large profits and small losses contribute to a good PMD.
• This metric allows us to examine the profit with respect to risk.
• Profit Loss Ratio (P:L) - Average profit over the average loss.
• Typically this number should be higher in trend following systems.
• Mean reversion systems show lower values, but compensate with a better win %.
• Percent Winners (% W) - The percentage of winning trades.
• Trend systems will usually have lower win percentages, since statistically the market is only trending roughly 30% of the time.
• Mean reversion systems typically should have a high % W.
• Time Percentage (Time %) - The amount of time that the system has an open position.
• The more time you are in the market, the more you are exposed to market risk, not to mention you could be using that money for something else right?
• Return on Investment (ROI) - Your Net Profit over your initial investment, represented as a percentage.
• You want this number to be positive and high.
• Open Profit (OP) - If the strategy has any open positions, the floating value will be represented here.
• Trading Days (TD) - An important metric showing how many days the strategy was active.
• This is good to know and will be valuable in understanding how long you will need to run this strategy in order to achieve results.
█ FEATURES
These are additional features that extend the original `BTE` features.
- Portfolio backtesting.
- Color coded performance results.
- Circuit Breakers that will stop trading.
- Position reversals on exit. (Simulating the function of always in the market. Similar to strategy.entry functionality)
- Whipsaw Filter
- Moving Average Filter
- Minimum Change Filter
- % Gain Equity Exit
- Popular strategies, (MACD, MA cross, supertrend)
Below are features that were excluded from the original `BTE`
- 2 stage in-trade stops with kick-in rules (This was a subjective decision to remove. I found it to be complex and thwarted my use of the `BTE` for some time.)
- Simple conversion from Study to Strategy modes. (Not possible with multiple securities)
- Coupling with your own external indicator (Not really practical to use with multiple securities, but could be used if signals were generated based on some indicator which was not based on the current chart)
- Use of the Data Window to show detailed bar by bar trade information and global statistics.
- Post Exit Analysis.
- Plotting of reminders and generation of alerts on in-trade events.
- Alerts (These may be added in the future by request when I find the time.)
█ THANKS
The whole PineCoders team for all their shared knowledge and original publication of the BTE and Richard Weismann for his ideas on building robust strategies.
═════════════════════════════════════════════════════════════════════════
Professor Snipe: A superadaptive moving average. Prof. Snipe is a superadaptive, multi-purpose indicator I developed in order to judge market trend strength and show high probability entry points.
The indicator is focused around a zero lag moving average algorithm (SUPER-MA, ), that changes its parameters depending on the volatility (ATR) and trend strength (ADX).
If the price (black 3 period MA) is above the Super-MA, this indicates market momentum and strength. If price is below the Super-MA, price and momentum are showing weakness.
Micro-Signals are given based on smaller lag-free moving average crossovers (blue and red arrows), but entries will depend on the location of price, with respect to the super-MA.
Furthermore, to judge the current price position with respect to high timeframe averages, the algo will automatically show the location of the nearest moving averages for support and resistance.
/////////////////////////
Entry Conditions example.:
For Longs:
Wait until the 4 hour trend flips bullish, price above Super-MA. Once it does, it will often retest the Super-MA as support. When that happens, use the next entry signal to go long.
For further safety, check the safety net (dotted hull moving average) to see if price has broken above that too, for an optimal long.
-- use caution when entering longs if: price is floating around the super-ma (very weak trend) and if price is below super-ma.
For Shorts:
Wait until the 4 hour trend flips bearish, price below Super-MA. Once it does, use lower timeframes to find short entry points using the MA signals.
-- use caution when entering shorts if: price is floating around the super-ma (very weak trend) and if price is above super-ma.
DYOR and test it yourself to find what works for you.
BE AWARE!
Just following the entry and exit signals (arrows) will not give you perfect results.
Summary:
Overall, this is probably the best indicator I have ever created, and has a very high success rate when used properly.
Best,
MM
EarlBMACDThis indicator looks for a crossover of the MACD moving averages (12ema and 26ema) to generate a buy/sell signal and a crossover
of the MACD line (12ema minus 26ema) and MACD signal line (9ema of MACD line) in order to generate a completely seperate buy/sell signal.
The two buy/sell signals are combined into a hybrid buy/sell/hold indicator which looks for one, neither, or both to be "buys."
If both signals are buys (fast crossed above slow), a "buy" signal is given (green bar color)
If only one signal is a buy, a "hold" signal is given (yellow bar color)
If neither signal is a buy, a "sell" signal is given (red bar color) Note: MACD moving averages crossing over is the same thing as the MACD line crossing the zero level in the MACD indicator
It makes sense to have the MACD indicator loaded as a reference when using this but it isn't required.
The lines plotted on the chart are the 12ema and a signal line which is the MACD signal line shown relative to the 12ema rather than the MACD line
The 26ema is not plotted on the chart because the chart becomes cluttered,
plus the moving averages crossover is indicated with the MACD indicator.
Dual Colored Least Squares Moving Average + Crossover AlertsDual Least Squares Moving Averages
Flexible Options (On/Off):
- Color change based on slope
- Background color change based on the slope of the slow moving average (LSMA 2).
- Crossover Arrows
- Crossover Alerts
How to Use on Your Own Chart & How to Set Alerts:
1. Click Add to Favorites
2. Add indicator to your chart, Click add Indicators > Favorites > Click on Dual LSMA
3. Click Add Alert, Select the condition Dual LSMA, then choose Long LSMA or Short LSMA
4. Click Create Alert
Let me know if it's useful for you! Also, if you have any new ideas and strategies based on this indicator, let me know. I love to hear (and learn) from all of the brilliant minds out there!
(13) Twists Swing/Day VS-478TWISTS adds a simple, but very effective twist to utilizing a multiple moving average crossover systems, enabling the effective and profitable trading of any stock, crypto or commodity. This enables trend, swing and day traders to dramatically improve their results over a similar, short-term simple, smoothed, exponential or weighted moving average crossover system.
Four distinct Laguerre filters are applied to the price, one fast, one medium one long and one very long. The default Laguerre settings are: Short = 0; Medium = 0.33, Long = 0.55 XLong = 0.77. The correlation between the length of time and the Laguerre output is adjustable in the format > inputs pane for this indicator and are referred to as gamma. The first three lengths produce two major bands or ribbons. During up trends the top band is filled with green and during down trends this top band will be filled with red. Obviously these bands or ribbons are twisting or flipping positions when the direction of the price trends change. Trading indicator dots are produced during both phases. Green dots for uptrends and red dots during down trends. During consolidation phases it is possible that there will be no dots produced because of the rule set applied to these Entry/hold and Exit/short indicator dots.
TWISTS is a triple moving average trading system using an advanced smoothing filter developed by John Ehlers. You can read about this dramatic advancement in moving averages in the following article: Time Warp -- Without Space Travel. You can find the link to this article on our site.
Access this Genie indicator for your Tradingview account, through our web site. (Links Below) This will provide you with additional educational information and reference articles, videos, input and setting options and trading strategies this indicator excels in.
