US M2### Relevance and Functionality of the "US M2" Indicator
#### Relevance
The "US M2" indicator is relevant for several reasons:
1. **Macro-Economic Insight**: The M2 money supply is a critical indicator of the amount of liquidity in the economy. Changes in M2 can significantly impact financial markets, including equities, commodities, and cryptocurrencies.
2. **Trend Identification**: By analyzing the M2 money supply with moving averages, the indicator helps identify long-term and short-term trends, providing insights into economic conditions and potential market movements.
3. **Trading Signals**: The indicator generates bullish and bearish signals based on moving average crossovers and the difference between current M2 values and their moving averages. These signals can be useful for making informed trading decisions.
#### How It Works
1. **Data Input**:
- **US M2 Money Supply**: The indicator fetches the US M2 money supply data using the "USM2" symbol with a monthly resolution.
2. **Moving Averages**:
- **50-Period SMA**: Calculates the Simple Moving Average (SMA) over 50 periods (months) to capture short-term trends.
- **200-Period SMA**: Calculates the SMA over 200 periods to identify long-term trends.
3. **Difference Calculation**:
- **USM2 Difference**: Computes the difference between the current M2 value and its 50-period SMA to highlight deviations from the short-term trend.
4. **Amplification**:
- **Amplified Difference**: Multiplies the difference by 100 to make the deviations more visible on the chart.
5. **Bullish and Bearish Conditions**:
- **Bullish Condition**: When the current M2 value is above the 50-period SMA, indicating a positive short-term trend.
- **Bearish Condition**: When the current M2 value is below the 50-period SMA, indicating a negative short-term trend.
6. **Short-Term SMA of Amplified Difference**:
- **14-Period SMA**: Applies a 14-period SMA to the amplified difference to smooth out short-term fluctuations and provide a clearer trend signal.
7. **Plots and Visualizations**:
- **USM2 Plot**: Plots the US M2 data for reference.
- **200-Period SMA Plot**: Plots the long-term SMA to show the broader trend.
- **Amplified Difference Histogram**: Plots the amplified difference as a histogram with green bars for bullish conditions and red bars for bearish conditions.
- **SMA of Amplified Difference**: Plots the 14-period SMA of the amplified difference to track the trend of deviations.
8. **Moving Average Cross Signals**:
- **Bullish Cross**: Plots an upward triangle when the 50-period SMA crosses above the 200-period SMA, signaling a potential long-term uptrend.
- **Bearish Cross**: Plots a downward triangle when the 50-period SMA crosses below the 200-period SMA, signaling a potential long-term downtrend.
### Summary
The "US M2" indicator provides a comprehensive view of the US M2 money supply, highlighting significant trends and deviations. By combining short-term and long-term moving averages with amplified difference analysis, it offers valuable insights and trading signals based on macroeconomic liquidity conditions.
Pesquisar nos scripts por "moving average crossover"
Smart Money Analysis with Golden/Death Cross [YourTradingSensei]Description of the script "Smart Money Analysis with Golden/Death Cross":
This TradingView script is designed for market analysis based on the concept of "Smart Money" and includes the detection of Golden Cross and Death Cross signals.
Key features of the script:
Moving Averages (SMA):
Two moving averages are calculated: a short-term (50 periods) and a long-term (200 periods).
The intersections of these moving averages are used to determine Golden Cross and Death Cross signals.
High Volume:
The current trading volume is analyzed.
Periods of high volume are identified when the current volume exceeds the average volume by a specified multiplier.
Support and Resistance Levels:
Key support and resistance levels are determined based on the highest and lowest prices over a specified period.
Buy and Sell Signals:
Buy and sell signals are generated based on moving average crossovers, high volume, and the closing price relative to key levels.
Golden Cross and Death Cross:
A Golden Cross occurs when the short-term moving average crosses above the long-term moving average.
A Death Cross occurs when the short-term moving average crosses below the long-term moving average.
These signals are displayed on the chart with text color changes for better visualization.
Using the script:
The script helps traders visualize key signals and levels, aiding in making informed trading decisions based on the behavior of major market players and technical analysis.
Custom candle lighting(CCL) © 2024 by YourTradingSensei is licensed under CC BY-NC-SA 4.0. To view a copy of this license.
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.
Tillson T3 Moving Average MTFMULTIPLE TIME FRAME version of Tillson T3 Moving Average Indicator
Developed by Tim Tillson, the T3 Moving Average is considered superior -1.60% to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA , double EMA , triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend.
The T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner. Here are several assumptions:
If the price action is above the T3 Moving Average and the indicator is headed upward, then we have a bullish trend and should only enter long trades (advisable for novice/intermediate traders). If the price is below the T3 Moving Average and it is edging lower, then we have a bearish trend and should limit entries to short. Below you can see it visualized in a trading platform.
Although the T3 MA is considered as one of the best swing following indicators that can be used on all time frames and in any market, it is still not advisable for novice/intermediate traders to increase their risk level and enter the market during trading ranges (especially tight ones). Thus, for the purposes of this article we will limit our entry signals only to such in trending conditions.
Once the market is displaying trending behavior, we can place with-trend entry orders as soon as the price pulls back to the moving average (undershooting or overshooting it will also work). As we know, moving averages are strong resistance/support levels, thus the price is more likely to rebound from them and resume its with-trend direction instead of penetrating it and reversing the trend.
And so, in a bull trend, if the market pulls back to the moving average, we can fairly safely assume that it will bounce off the T3 MA and resume upward momentum, thus we can go long. The same logic is in force during a bearish trend .
And last but not least, the T3 Moving Average can be used to generate entry signals upon crossing with another T3 MA with a longer trackback period (just like any other moving average crossover). When the fast T3 crosses the slower one from below and edges higher, this is called a Golden Cross and produces a bullish entry signal. When the faster T3 crosses the slower one from above and declines further, the scenario is called a Death Cross and signifies bearish conditions.
I Personally added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the box in the input section. traders can combine the two lines to have Buy/Sell signals from the crosses.
Developed by Tim Tillson
RSI MA CrossBuilding onto the standard RSI indicator, with the following modification and improvements:
- Added signals for RSI moving average crossovers, which usually indicator a bull or bear trend
- Added option to use smoothed RSI line
- Added alert for crossover signals
Enjoy~~~!
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.
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!
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 & MA Crossover The Moving Average Crossover trading strategy is possibly the most popular
trading strategy in the world of trading. First of them were written in the
middle of XX century, when commodities trading strategies became popular.
This strategy is a good example of so-called traditional strategies.
Traditional strategies are always long or short. That means they are never
out of the market. The concept of having a strategy that is always long or
short may be scary, particularly in today’s market where you don’t know what
is going to happen as far as risk on any one market. But a lot of traders
believe that the concept is still valid, especially for those of traders who
do their own research or their own discretionary trading.
This version uses crossover of moving average and its exponential moving average.
52SIGNAL RECIPE CCI Linreg Bands═══ 52SIGNAL RECIPE CCI Linreg Bands ═══
◆ Overview
52SIGNAL RECIPE CCI Linreg Bands is an advanced technical indicator that combines the CCI (Commodity Channel Index) with Linear Regression Bands. This indicator visualizes the volatility of the CCI using linear regression bands, helping to clearly identify overbought/oversold areas and more accurately capture potential trend reversal points.
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◆ Key Features
• CCI-Based Overbought/Oversold Analysis: Uses the traditional CCI indicator to identify overbought/oversold conditions in the market
• Integrated Linear Regression Bands: Applies linear regression analysis to the CCI to visually represent the direction and strength of trends
• Dual Overbought/Oversold Levels: Sets overbought/oversold levels for both CCI and Linear Regression Bands to increase the accuracy of signals
• Advanced Visualization: Intuitive chart analysis is possible with color changes according to trend direction and clear band display
• Multiple Alert Settings: Alert functions for various conditions ensure you don't miss important trading moments
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◆ Technical Foundation
■ CCI (Commodity Channel Index)
• Basic Settings: 20-period CCI with Weighted Moving Average (WMA) applied
• Calculation Method: Measures the deviation from the average price normalized to a specific range
• Overbought/Oversold Levels: Default values set to +150 (overbought) and -150 (oversold)
■ Linear Regression Bands
• Period: Default value of 100 days
• Deviation: Default value of 4.5 standard deviations
• Center Line: The center line of the linear regression analysis for the CCI values
• Band Width: Displays the range of volatility around the center line based on the calculated standard deviation
• Overbought/Oversold Levels: Default values set to +250 (overbought) and -250 (oversold)
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◆ Practical Applications
■ Identifying Trading Signals
• Buy Signal:
▶ When the CCI falls below the oversold level (-150)
▶ When the lower band of the Linear Regression Bands falls below the oversold level (-250)
▶ When both conditions are met simultaneously (extreme oversold state) - a strong buy signal
• Sell Signal:
▶ When the CCI rises above the overbought level (+150)
▶ When the upper band of the Linear Regression Bands rises above the overbought level (+250)
▶ When both conditions are met simultaneously (extreme overbought state) - a strong sell signal
■ Trend Analysis
• Uptrend: When the linear regression center line is rising and the CCI is moving above the zero line
• Downtrend: When the linear regression center line is falling and the CCI is moving below the zero line
• Trend Strength: The wider the gap between the bands, the greater the volatility; the narrower, the more stable the trend
■ Divergence Confirmation
• Bearish Divergence: Price forms a new high, but the CCI is lower than the previous high (potential bearish signal)
• Bullish Divergence: Price forms a new low, but the CCI is higher than the previous low (potential bullish signal)
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◆ Advanced Setting Options
■ CCI Setting Adjustments
• CCI Source: Selectable options include Close (default), Open, High, Low, HL2, HLC3, OHLC4, etc.
• CCI Length: Adjust to lower values for short-term volatility, higher values for long-term trends
■ Linear Regression Setting Adjustments
• Period: Use lower values (20-50) for short-term analysis, higher values (100-200) for long-term analysis
• Deviation: Higher values create wider bands (more signals), lower values create narrower bands (more accurate signals)
■ Overbought/Oversold Level Adjustments
• CCI Levels: Adjust to more extreme values (±200) in highly volatile markets
• Linear Regression Band Levels: Adjustable to ±300 or ±200 depending on market conditions
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◆ Synergy with Other Indicators
• Bollinger Bands: Use alongside Bollinger Bands on the price chart to compare price volatility with CCI volatility
• MACD: Use with MACD for momentum and trend confirmation
• Fibonacci Retracement: Check CCI Linreg Bands signals with key support/resistance levels
• Moving Averages: Combine moving average crossovers with CCI Linreg Bands signals to improve reliability
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◆ Conclusion
52SIGNAL RECIPE CCI Linreg Bands provides a powerful and accurate technical analysis tool by combining traditional CCI with linear regression analysis. The dual overbought/oversold system increases the accuracy of trading signals and clearly visualizes trend direction and strength to help traders make decisions. You can achieve optimal results by adjusting various settings to match your trading style and market conditions.
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※ Disclaimer: Past performance does not guarantee future results. Always use appropriate risk management strategies.
═══ 52SIGNAL RECIPE CCI 선형회귀 밴드 ═══
◆ 개요
52SIGNAL RECIPE CCI 선형회귀 밴드는 CCI(Commodity Channel Index)와 선형회귀 밴드를 결합한 고급 기술적 지표입니다. 이 지표는 선형회귀 밴드를 사용하여 CCI의 변동성을 시각화하여 과매수/과매도 영역을 명확하게 식별하고 잠재적인 추세 반전 지점을 더 정확하게 포착하는 데 도움을 줍니다.
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◆ 주요 특징
• CCI 기반 과매수/과매도 분석: 전통적인 CCI 지표를 사용하여 시장의 과매수/과매도 상태를 식별
• 통합된 선형회귀 밴드: CCI에 선형회귀 분석을 적용하여 추세의 방향과 강도를 시각적으로 표현
• 이중 과매수/과매도 레벨: CCI와 선형회귀 밴드 모두에 과매수/과매도 레벨을 설정하여 신호의 정확도 향상
• 고급 시각화: 추세 방향에 따른 색상 변화와 명확한 밴드 표시로 직관적인 차트 분석 가능
• 다중 알림 설정: 다양한 조건에 대한 알림 기능으로 중요한 트레이딩 시점을 놓치지 않도록 보장
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◆ 기술적 기반
■ CCI (Commodity Channel Index)
• 기본 설정: 20기간 CCI에 가중이동평균(WMA) 적용
• 계산 방법: 평균 가격에 대한 편차를 측정하여 정규화한 값으로 표현
• 과매수/과매도 레벨: 기본값으로 +150(과매수)과 -150(과매도) 설정
■ 선형회귀 밴드
• 기간: 기본값 100일
• 편차: 기본값 4.5 표준편차
• 중심선: CCI 값에 대한 선형회귀 분석의 중심선
• 밴드 폭: 계산된 표준편차에 기반하여 중심선 주변의 변동성 범위 표시
• 과매수/과매도 레벨: 기본값으로 +250(과매수)와 -250(과매도) 설정
─────────────────────────────────────
◆ 실용적 응용
■ 트레이딩 신호 식별
• 매수 신호:
▶ CCI가 과매도 레벨(-150) 아래로 떨어질 때
▶ 선형회귀 밴드의 하단이 과매도 레벨(-250) 아래로 떨어질 때
▶ 두 조건이 동시에 충족될 때(극단적 과매도 상태) - 강한 매수 신호
• 매도 신호:
▶ CCI가 과매수 레벨(+150) 위로 상승할 때
▶ 선형회귀 밴드의 상단이 과매수 레벨(+250) 위로 상승할 때
▶ 두 조건이 동시에 충족될 때(극단적 과매수 상태) - 강한 매도 신호
■ 추세 분석
• 상승 추세: 선형회귀 중심선이 상승하고 CCI가 0선 위로 움직일 때
• 하락 추세: 선형회귀 중심선이 하락하고 CCI가 0선 아래로 움직일 때
• 추세 강도: 밴드 사이의 간격이 넓을수록 변동성이 크고, 좁을수록 추세가 안정적
■ 다이버전스 확인
• 약세 다이버전스: 가격이 신고점을 형성하지만 CCI가 이전 고점보다 낮을 때(잠재적 약세 신호)
• 강세 다이버전스: 가격이 신저점을 형성하지만 CCI가 이전 저점보다 높을 때(잠재적 강세 신호)
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◆ 고급 설정 옵션
■ CCI 설정 조정
• CCI 소스: 선택 가능한 옵션에는 종가(기본값), 시가, 고가, 저가, HL2, HLC3, OHLC4 등이 포함
• CCI 길이: 단기 변동성을 위해 낮은 값으로, 장기 추세를 위해 높은 값으로 조정
■ 선형회귀 설정 조정
• 기간: 단기 분석을 위해 낮은 값(20-50), 장기 분석을 위해 높은 값(100-200) 사용
• 편차: 높은 값은 더 넓은 밴드(더 많은 신호), 낮은 값은 더 좁은 밴드(더 정확한 신호) 생성
■ 과매수/과매도 레벨 조정
• CCI 레벨: 변동성이 큰 시장에서는 더 극단적인 값(±200)으로 조정
• 선형회귀 밴드 레벨: 시장 상황에 따라 ±300 또는 ±200으로 조정 가능
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◆ 다른 지표와의 시너지
• 볼린저 밴드: 가격 차트의 볼린저 밴드와 함께 사용하여 가격 변동성과 CCI 변동성 비교
• MACD: 모멘텀과 추세 확인을 위해 MACD와 함께 사용
• 피보나치 되돌림: CCI 선형회귀 밴드 신호를 주요 지지/저항 레벨과 함께 확인
• 이동평균선: 이동평균 교차와 CCI 선형회귀 밴드 신호를 결합하여 신뢰성 향상
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◆ 결론
52SIGNAL RECIPE CCI 선형회귀 밴드는 전통적인 CCI와 선형회귀 분석을 결합하여 강력하고 정확한 기술적 분석 도구를 제공합니다. 이중 과매수/과매도 시스템은 트레이딩 신호의 정확도를 높이고 추세 방향과 강도를 명확하게 시각화하여 트레이더의 의사 결정을 돕습니다. 다양한 설정을 트레이딩 스타일과 시장 상황에 맞게 조정하여 최적의 결과를 얻을 수 있습니다.
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※ 면책 조항: 과거 성과가 미래 결과를 보장하지 않습니다. 항상 적절한 리스크 관리 전략을 사용하세요.
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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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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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.
Triple Differential Moving Average BraidThe Triple Differential Moving Average Braid weaves together three distinct layers of moving averages—short-term, medium-term, and long-term—providing a structured view of market trends across multiple time horizons. It is an integrated construct optimized exclusively for the 1D timeframe. For multi-timeframe analysis and/or trading the lower 1h and 15m charts, it pairs well the Granular Daily Moving Average Ribbon ... adjust the visibility settings accordingly.
Unlike traditional moving average indicators that use a single moving average crossover, this braid-style system incorporates both SMAs and EMAs. The dual-layer approach offers stability and responsiveness, allowing traders to detect trend shifts with greater confidence.
Users can, of course, specify their own color scheme. The indicator consists of three layered moving average pairs. These are named per their default colors:
1. Silver Thread – Tracks immediate price momentum.
2. Royal Guard – Captures market structure and developing trends.
3. Golden Section – Defines major market cycles and overall trend direction.
Each layer is color-coded and dynamically shaded based on whether the faster-moving average is above or below its slower counterpart, providing a visual representation of market strength and trend alignment.
🧵 Silver Thread
The Silver Thread is the fastest-moving layer, comprising the 21D SMA and a 21D EMA. The choice of 21 is intentional, as it corresponds to approximately one full month of trading days in a 5-day-per-week market and is also a Fibonacci number, reinforcing its use in technical analysis.
· The 21D SMA smooths out recent price action, offering a baseline for short-term structure.
· The 21D EMA reacts more quickly to price changes, highlighting shifts in momentum.
· When the SMA is above the EMA, price action remains stable.
· When the SMA falls below the EMA, short-term momentum weakens.
The Silver Thread is a leading indicator within the system, often flipping direction before the medium- and long-term layers follow suit. If the Silver Thread shifts bearish while the Royal Guard remains bullish, this can signal a temporary pullback rather than a full trend reversal.
👑 Royal Guard
The Royal Guard provides a broader perspective on market momentum by using a 50D EMA and a 200D EMA. EMAs prioritize recent price data, making this layer faster-reacting than the Golden Section while still offering a level of stability.
· When the 50D EMA is above the 200D EMA, the market is in a confirmed uptrend.
· When the 50D EMA crosses below the 200D EMA, momentum has shifted bearish.
This layer confirms medium-term trend structure and reacts more quickly to price changes than traditional SMAs, making it especially useful for trend-following traders who need faster confirmation than the Golden Section provides.
If the Silver Thread flips bearish while the Royal Guard remains bullish, traders may be seeing a momentary dip in an otherwise intact uptrend. Conversely, if both the Silver Thread and Royal Guard shift bearish, this suggests a deeper pullback or possible trend reversal.
📜 Golden Section
The Golden Section is the slowest and most stable layer of the system, utilizing a 50D SMA and a 200D SMA—a classic combination used by long-term traders and institutions.
· When the 50D SMA is above the 200D SMA the market is in a strong, sustained uptrend.
· When the 50D SMA falls below the 200D SMA the market is structurally bearish.
Because SMAs give equal weight to past price data, this layer moves slowly and deliberately, ensuring that false breakouts or temporary swings do not distort the bigger picture.
Traders can use the Golden Section to confirm major market trends—when all three layers are bullish, the market is strongly trending upward. If the Golden Section remains bullish while the Royal Guard turns bearish, this may indicate a medium-term correction within a larger uptrend rather than a full reversal.
🎯 Swing Trade Setups
Swing traders can benefit from the multi-layered approach of this indicator by aligning their trades with the overall market structure while capturing short-term momentum shifts.
· Bullish: Look for Silver Thread and Royal Guard alignment before entering. If the Silver Thread flips bullish first, anticipate a momentum shift. If the Royal Guard follows, this confirms a strong medium-term move.
· Bearish: If the Silver Thread turns bearish first, it may signal an upcoming reversal. Waiting for the Royal Guard to follow adds confirmation.
· Confirmation: If the Golden Section remains bullish, a pullback may be an opportunity to enter a trend continuation trade rather than exit prematurely.
🚨 Momentum Shifts
· If the Silver Thread flips bearish but the Royal Guard remains bullish, traders may opt to buy the dip rather than exit their positions.
· If both the Silver Thread and Royal Guard turn bearish, traders should exercise caution, as this suggests a more significant correction.
· When all three layers align in the same direction the market is in a strong trending phase, making swing trades higher probability.
⚠️ Risk Management
· A narrowing of the shaded areas suggests trend exhaustion—consider tightening stop losses.
· When the Golden Section remains bullish, but the other two layers weaken, potential support zones to enter or re-enter positions.
· If all three layers flip bearish, this may indicate a larger trend reversal, prompting an exit from long positions and/or consideration of short setups.
The Triple Differential Moving Average Braid is layered, structured tool for trend analysis, offering insights across multiple timeframes without requiring traders to manually compare different moving averages. It provides a powerful and intuitive way to read the market. Swing traders, trend-followers, and position traders alike can use it to align their trades with dominant market trends, time pullbacks, and anticipate momentum shifts.
By understanding how these three moving average layers interact, traders gain a deeper, more holistic perspective of market structure—one that adapts to both momentum-driven opportunities and longer-term trend positioning.
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.
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.
Gabriels Trend Regularity Adaptive Moving Average Dragon This is an improved version of the trend following Williams Alligator, through the use of five Trend Regularity Adaptive Moving Averages (TRAMA) instead of three smoothed averages (SMMA). This indicator can double as a TRAMA Ribbon indicator by reducing the offset to zero. Whereas the active offset can double as a forecasting indicator for options and futures.
This indicator uses five TRAMAs, set at 8, 21, 55, 144, and 233 periods. They make up the Lips, Teeth, Jaws, Wings, and Tail of the Dragon. This indicator uses convergence-divergence relationships to build trading signals, with the Tail making the slowest turns and the Lips making the fastest turns. The Lips crossing downwards through the other lines signal a short opportunity, whereas Lips crossing upwards through other lines signal a buying opportunity. The downward cross can be referred to as the Dragon "Sleeping" , and the upward cross as the Dragon "Awakening" .
In particular, but not limited to, the Wings and Tail movements possess a Roar-like forecast effect on the market. Respectively, they can be referred to as the Dragon "Spreading its Wings" or "Swinging its Tail" .
The first three lines, stretching apart and constantly moving higher or lower, denote periods in which long or short equity positions should be managed and maintained. This can be referred to as the Dragon "Eating with a mouth wide open" . Whereas indicator lines converging into narrow bands and shifting into a horizontal position can denote a trending period coming to an end, signaling the need for profit-taking and position realignment. Conversely, a previous flat line moving can denote a new trending period starting.
This indicator can double as a Multiple TRAMAs indicator by reducing the offset to zero. As such, very interesting results can be observed when used in a moving average crossover system such as the Williams Alligator or as trailing support and resistance.
The following moving average adapts to the average of the highest high and lowest low made over a specific period, thus adapting to trend strength. The TRAMA can be used like most moving averages, with the advantage of being smoother during ranging markets because it is calculated through exponential averaging.
It is calculating, using a smoothing factor, the squared simple moving average of the number of highest highs or lowest lows previously made. Where the highest highs and lowest lows are calculated using rolling maximums and minimums. Therefore, squaring allows the moving average to penalize lower values, thus appearing stationary during ranging markets.
As with all moving averages, it is still a lagging indicator, and it can suffer whipsaws when the market moves too violently or when it consolidates in ranging conditions. Despite it working in all timeframes, it won't be as formidable in the 1–5-minute scalping timeframes due to that. I would suggest 5 to 45 minutes if you are a swing trader, or hourly, daily, and weekly if you are a long-term investor.
I hope you enjoy this indicator! It's the first indicator I made, so constructive criticism would be appreciated. Thanks!
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.
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
Easy Loot Golden CrossGolden/Death Cross Moving Average Indicator
30, 100 & 200 period Simple Moving Average (SMA).
30 = Yellow
100 = Green
200 = Black
Black crosses mark the 'golden crosses' as well as the 'death crosses'. These black crosses appear when the 30 crosses the 100 & when the 100 crosses the 200. These black crosses don't tell you when to buy/sell, but simply indicate interest in the market.
This code is open-source so feel free to add this indicator to your chart and play around with the different moving average timeframes & color schemes.
Golden Cross
The golden cross occurs when a short-term moving average crosses over a major long-term moving average to the upside and is interpreted by analysts and traders as signaling a definitive upward turn in a market. Basically, the short-term average trends up faster than the long-term average, until they cross.
There are three stages to a golden cross:
A downtrend that eventually ends as selling is depleted
A second stage where the shorter moving average crosses up through the longer moving average
Finally, the continuing uptrend, hopefully leading to higher prices
Death Cross
Conversely, a similar downside moving average crossover constitutes the death cross and is understood to signal a decisive downturn in a market. The death cross occurs when the short term average trends down and crosses the long-term average, basically going in the opposite direction of the golden cross.
The death cross preceded the economic downturns in 1929, 1938, 1974, and 2008.
Combo Strategy 123 Reversal & EMA & MA Crossover This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The Moving Average Crossover trading strategy is possibly the most popular
trading strategy in the world of trading. First of them were written in the
middle of XX century, when commodities trading strategies became popular.
This strategy is a good example of so-called traditional strategies.
Traditional strategies are always long or short. That means they are never
out of the market. The concept of having a strategy that is always long or
short may be scary, particularly in today’s market where you don’t know what
is going to happen as far as risk on any one market. But a lot of traders
believe that the concept is still valid, especially for those of traders who
do their own research or their own discretionary trading.
This version uses crossover of moving average and its exponential moving average.
WARNING:
- For purpose educate only
- This script to change bars colors.
(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.
