SMA Trend Filter Oscillator (Adaptive)The "SMA Trend Filter Oscillator (Adaptive)" indicator is a technical analysis tool that helps traders determine the direction and strength of a trend based on an adaptive Simple Moving Average (SMA). The oscillator calculates the difference between the closing price and the SMA value, allowing for the visualization of price deviation from the average and the assessment of current market dynamics.
Key Features of the Indicator:
Adaptation to Time Frame: The indicator automatically adjusts the SMA length based on the current time frame, making it versatile for use across different time intervals. For example:
Monthly Time Frame: SMA with a length of 50.
Weekly Time Frame: SMA with a length of 40.
Daily Time Frame: SMA with a length of 20.
Hourly Time Frame: SMA with a length of 10.
Intraday Time Frames: SMA with a length of 5 (for time frames up to 15 minutes) or 7 (for others).
SMA-Based Oscillator: The oscillator is calculated as the difference between the closing price and the SMA value. This allows:
Bullish Trend Identification: When the oscillator is above zero (price is above SMA).
Bearish Trend Identification: When the oscillator is below zero (price is below SMA).
Visualization: The oscillator is displayed as a histogram, where:
Green Color indicates a bullish trend.
Red Color indicates a bearish trend.
The Zero Line (Gray) serves as a reference for trend reversal.
How to Use the Indicator:
Trend Identification: If the oscillator is above zero and colored green, it signals a bullish trend. If it is below zero and colored red, it indicates a bearish trend.
Trend Strength: The larger the oscillator value (in either direction), the stronger the trend. Small oscillator values (close to zero) may indicate sideways movement or weak trend.
Entry and Exit Points:
Buy: When the oscillator crosses the zero line from below to above (transition from red to green).
Sell: When the oscillator crosses the zero line from above to below (transition from green to red).
Signal Filtering: Use the indicator in combination with other technical analysis tools (e.g., RSI, MACD, or support/resistance levels) to confirm signals.
Advantages of the Indicator:
Adaptability: Automatic adjustment of SMA length to the current time frame makes it versatile.
Simplicity: Intuitive histogram visualization allows for quick assessment of market conditions.
Flexibility: Can be used on any market (stocks, forex, cryptocurrencies) and time frame.
Limitations:
Lag: Like any SMA-based indicator, it can lag due to the use of average values.
False Signals: In sideways markets (flat), the indicator may generate false signals.
Risk Management:
Always set stop-losses and take-profits to minimize losses.
Test the indicator on historical data before using it on a live account.
The "SMA Trend Filter Oscillator (Adaptive)" is a powerful tool for traders seeking to quickly evaluate trends and their strength. Its adaptability and simplicity make it suitable for both novice and experienced traders.
Индикатор "SMA Trend Filter Oscillator (Adaptive)" — это инструмент технического анализа, который помогает трейдерам определять направление тренда и его силу на основе адаптивной скользящей средней (SMA). Осциллятор рассчитывает разницу между ценой закрытия и значением SMA, что позволяет визуализировать отклонение цены от среднего значения и оценивать текущую рыночную динамику.
Основные особенности индикатора:
Адаптация к таймфрейму
Индикатор автоматически подстраивает длину SMA в зависимости от текущего таймфрейма, что делает его универсальным для использования на различных временных интервалах. Например:
Месячный таймфрейм (Monthly): SMA с длиной 50.
Недельный таймфрейм (Weekly): SMA с длиной 40.
Дневной таймфрейм (Daily): SMA с длиной 20.
Часовой таймфрейм (Hourly): SMA с длиной 10.
Внутридневные таймфреймы (Intraday): SMA с длиной 5 (для таймфреймов до 15 минут) или 7 (для остальных).
Осциллятор на основе SMA
Осциллятор рассчитывается как разница между ценой закрытия и значением SMA. Это позволяет:
Определять бычий тренд, когда осциллятор выше нуля (цена выше SMA).
Определять медвежий тренд, когда осциллятор ниже нуля (цена ниже SMA).
Визуализация
Осциллятор отображается в виде гистограммы, где:
Зелёный цвет указывает на бычий тренд.
Красный цвет указывает на медвежий тренд.
Линия нуля (серая) служит ориентиром для определения смены тренда.
Как использовать индикатор:
Определение тренда
Если осциллятор находится выше нуля и окрашен в зелёный цвет, это сигнализирует о бычьем тренде.
Если осциллятор находится ниже нуля и окрашен в красный цвет, это указывает на медвежий тренд.
Сила тренда
Чем больше значение осциллятора (в положительную или отрицательную сторону), тем сильнее тренд.
Небольшие значения осциллятора (близкие к нулю) могут указывать на боковое движение или слабость тренда.
Точки входа и выхода
Покупка (Buy): Когда осциллятор пересекает нулевую линию снизу вверх (переход из красной зоны в зелёную).
Продажа (Sell): Когда осциллятор пересекает нулевую линию сверху вниз (переход из зелёной зоны в красную).
Фильтрация сигналов
Используйте индикатор в сочетании с другими инструментами технического анализа (например, RSI, MACD или уровнями поддержки/сопротивления) для подтверждения сигналов.
Преимущества индикатора:
Адаптивность: Автоматическая настройка длины SMA под текущий таймфрейм делает индикатор универсальным.
Простота: Интуитивно понятная визуализация в виде гистограммы позволяет быстро оценить рыночную ситуацию.
Гибкость: Может использоваться на любых рынках (акции, форекс, криптовалюты) и таймфреймах.
Ограничения:
Запаздывание: Как и любой индикатор на основе SMA, он может запаздывать из-за использования средних значений.
Ложные сигналы: В условиях бокового движения (флэта) индикатор может генерировать ложные сигналы.
Управление рисками: Всегда устанавливайте стоп-лоссы и тейк-профиты, чтобы минимизировать потери.
Тестирование: Перед использованием на реальном счёте протестируйте индикатор на исторических данных.
Индикатор "SMA Trend Filter Oscillator (Adaptive)" — это мощный инструмент для трейдеров, которые хотят быстро оценить тренд и его силу. Его адаптивность и простота делают его подходящим как для начинающих, так и для опытных трейдеров
Pengayun
Enhanced ROC - Savitzky–Golay [AIBitcoinTrend]👽 Adaptive ROC - Savitzky–Golay (AIBitcoinTrend)
The Adaptive ROC - Savitzky–Golay redefines traditional Rate of Change (ROC) analysis by integrating Savitzky–Golay smoothing with volatility-adaptive normalization, allowing it to dynamically adjust across different market conditions. Unlike the standard ROC, which reacts rigidly to price changes, this advanced version refines trend signals while maintaining responsiveness to volatility.
Additionally, this indicator features real-time divergence detection and an ATR-based trailing stop system, equipping traders with a powerful toolset for momentum analysis, reversals, and trend-following strategies.
👽 What Makes the Adaptive ROC - Savitzky–Golay Unique?
Unlike conventional ROC indicators, this enhanced version leverages volatility-adjusted scaling and Z-score normalization to improve signal consistency across different timeframes and assets.
✅ Savitzky–Golay Smoothing – Reduces noise while preserving trend structure for clearer signals.
✅ Volatility-Adaptive Normalization – Ensures that overbought and oversold thresholds remain consistent across different markets.
✅ Real-Time Divergence Detection – Identifies early bullish and bearish divergence signals for potential reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with dynamic stop levels.
👽 The Math Behind the Indicator
👾 Savitzky–Golay Smoothing
The indicator applies a Savitzky–Golay filter to the raw ROC data, creating a smoother curve while preserving key inflection points. This technique prevents excessive lag while maintaining the integrity of price movements.
sg_roc = (roc_raw + 3*roc_raw + 5*roc_raw + 7*roc_raw + 5*roc_raw + 3*roc_raw + roc_raw ) / 25
👾 Volatility-Adaptive Scaling
By dynamically adjusting the smoothed ROC using standard deviation, the indicator ensures that momentum readings remain relative to the market’s current volatility.
volatility = ta.stdev(close, rocLength)
dynamicFactor = 1 / (1 + volatility / 100)
advanced_sg_roc = sg_roc * dynamicFactor
👾 Z-Score Normalization
To maintain a stable Overbought/Oversold structure across different markets, the ROC is normalized using a Z-score transformation, ensuring its values remain statistically relevant.
rocMean = ta.wma(advanced_sg_roc, lenZ)
rocStdev = ta.stdev(advanced_sg_roc, lenZ)
zRoc = (advanced_sg_roc - rocMean) / rocStdev
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while the ROC forms a higher low.
A buy signal is confirmed when the ROC starts rising.
Bearish Divergence Setup:
Price makes a higher high, while the ROC forms a lower high.
A sell signal is confirmed when the ROC starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅ ROC crosses above the bullish trigger level → Buy Signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if price crosses below the stop.
Bearish Setup:
✅ ROC crosses below the bearish trigger level → Sell Signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Savitzky–Golay Filtering – Retains essential trend details while eliminating excessive noise.
Volatility-Adjusted Normalization – Makes overbought/oversold levels universally reliable across markets.
Real-Time Divergence Alerts – Identifies early reversal signals for optimal entries and exits.
ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
Works Across Markets & Timeframes - Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
ROC Period – Defines the number of bars used for ROC calculation.
Smoothing Strength – Adjusts the degree of Savitzky–Golay filtering.
Volatility Scaling – Enables or disables the adaptive volatility factor.
Enable Divergence Analysis – Turns on real-time divergence detection.
Lookback Period – Specifies the pivot detection period for divergences.
Enable Crosses Signals – Activates trade signals based on ROC crossovers.
ATR Multiplier – Controls the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
MACD Sniper [trade_lexx]📈 MACD Sniper — Improve your trading strategy with accurate signals!
Introducing the MACD Sniper , an advanced trading indicator designed for a comprehensive analysis of market conditions. This indicator combines MACD (Moving Average Convergence Divergence) with various types of moving averages (SMA, EMA, WMA, VWMA, KAMA, HMA, ZLEMA, TEMA, ALMA, DEMA), providing traders with a powerful tool for generating buy and sell signals. It is ideal for traders who need an advantage in detecting changes in trends and market conditions.
🔍 How the signals work
1. Histogram signals:
— A buy signal is generated when the MACD histogram is below zero and begins to grow after the minimum number of falling histogram columns, which are indicated in the indicator menu. This indicates that selling pressure has decreased, the market is oversold and ready for a rebound. The signals are displayed as green triangles labeled "H" under the histogram graph. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the MACD histogram is above zero and begins to fall after the minimum number of growing histogram columns, which are indicated in the indicator menu. This indicates that the buying pressure has decreased, the market is overbought and ready for correction. The signals are displayed as red triangles labeled "H" above the histogram graph. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
2. Moving Average Crossing Signals (MA):
— A buy signal is generated when the Fast Moving Average (MACD) crosses the Slow Moving Average (Signal Line) from bottom to top. This indicates a possible upward reversal of the market. The signals are displayed as green triangles labeled "MA" under the MACD chart. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the Fast Moving Average (MACD) crosses the slow Moving Average (Signal Line) from top to bottom. This indicates a possible downward reversal of the market. The signals are displayed as red triangles labeled "MA" above the MACD chart. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
🔧 Signal filtering
— Minimum number of bars between signals
This filter allows the user to set the minimum number of bars that must pass between the generation of two consecutive signals. This helps to avoid frequent false alarms and improves the quality of the generated signals. Setting this parameter allows you to filter out the noise in the market and make the signals more reliable. For example, if the value is set to 5, then a new signal will be generated only after 5 bars have passed since the previous signal.
— "Wait for the opposite signal" mode
In this mode, Buy and Sell signals are generated only after receiving the opposite signal. This means that a buy signal will be generated only after the previous sell signal, and vice versa. This approach adds an additional level of filtering and helps to avoid false positives. This is especially useful in conditions of high market volatility, when false signals often occur.
— RSI filter
The Relative Strength Index (RSI) is used for additional filtering of buy and sell signals. The RSI helps determine whether a market is overbought or oversold. The user can set overbought and oversold levels, and signals will be generated only when the RSI is in the specified ranges. For example, a buy signal will be generated only if the RSI is in the range between 10 and 30 (oversold), and a sell signal if the RSI is in the range between 70 and 90 (overbought). This helps to avoid false signals in extreme market conditions.
🔌 Connector Histogram, MA, Combined 🔌
These parameters allow you to connect the indicator to trading strategies and test the signals throughout the trading history. This makes the indicator an even more powerful tool for traders who want to test the effectiveness of their strategies on historical data.
Connector Histogram provides the ability to connect signals based on the MACD histogram to trading strategies.
Connector MA allows you to connect signals based on the intersection of moving averages (MA) of the MACD, which can also be used for automatic trading or strategy testing.
The combined connector combines signals based on both a histogram and the intersection of moving averages, making the analysis more comprehensive and reliable, which is especially useful for traders seeking to improve the quality of their trading decisions.
🔔 Alerts
The indicator provides the ability to set up notifications for buy and sell signals, which allows traders to keep abreast of important market events without having to constantly monitor the chart. Users can set up notifications that will alert them when buy or sell signals appear, helping them respond to market changes in a timely manner and make informed decisions. These notifications can be configured for various types of signals, such as signals based on the MACD histogram, moving average crossings, or all at once, which makes the indicator a more convenient and functional tool for active traders.
🎨 Customizable Appearance
Customize the appearance of the MACD Sniper according to your preferences to make the analysis more convenient and visually pleasing. In the indicator settings section, you can change the colors of the buy and sell signals so that they stand out on the chart and are easily visible. For example, buy signals can be green, and sell signals can be red. These settings allow traders to adapt the indicator to their individual needs, making it more flexible and user-friendly.
🔧 How it works
The MACD Sniper indicator starts by calculating the MACD values and moving averages for a specific period in order to assess market conditions. For this, fast and slow moving averages are used, as well as a signal line, which are calculated based on the set parameters. The indicator then analyzes the MACD histogram to determine whether the difference between the fast and slow moving averages is rising or falling. Based on this analysis, buy and sell signals are generated. Additionally, the indicator uses the RSI filter to filter out false signals in overbought or oversold market conditions. The user can set the minimum number of bars between the signals and the "Wait for the opposite signal" mode for additional filtering. The indicator dynamically adjusts to changes in the market, providing relevant signals in real time.
📚 Quick guide to using the MACD Sniper
— Add the indicator to your favorites by clicking on the rocket icon. Adjust the parameters such as the length of periods for fast and slow moving averages, the type of moving average (SMA, EMA, WMA, VWMA, KAMA, HMA, ZLEMA, TEMA, ALMA, DEMA) and the length of the signal line, according to your trading style, or leave all settings as default.
— Adjust the signal filters to improve their quality and avoid false alarms
— Turn on notifications so that you don't miss important trading opportunities and don't constantly sit at the chart. This will allow you to keep abreast of all key market events and respond to them in a timely manner, without being distracted from other business.
— Use signals, they will help you determine the optimal entry and exit points of positions.
— Use the Connector for deeper analysis and verification of the effectiveness of signals, connect them to your trading strategies. This will allow you to test signals throughout your trading history and evaluate their accuracy based on historical data.
— Include the indicator in your trading strategy and run testing to see how buy and sell signals have worked in the past.
— Analyze the test results to determine how reliable the signals are and how they can improve your trading strategy. This will help you make more informed decisions and increase your trading efficiency.
ReadyFor401ks Stoch + RSIThis indicator is a powerful tool that combines the classic Relative Strength Index (RSI) with a Stochastic RSI to provide traders with a more nuanced view of market momentum and potential reversal points. By blending these two techniques, the script offers a detailed insight into price action, highlighting when a market might be overbought or oversold. The RSI is calculated once and then used both for a traditional RSI plot and to derive the Stochastic RSI, ensuring consistency and efficiency in your analysis.
One of the standout features of this indicator is its dynamic visual presentation. A gradient color scheme is applied to the RSI line, which changes based on its position between customizable overbought and oversold levels. This visual cue allows traders to quickly identify critical zones without having to constantly monitor numerical values. Additionally, the background fill between these levels enhances clarity, making it easier to spot when conditions are ripe for a potential reversal.
The indicator is highly customizable, allowing you to adjust parameters such as the RSI period, Stochastic length, and smoothing factors. This flexibility means you can fine-tune the tool to suit different market conditions, whether you’re trading trending markets or range-bound environments. For example, an RSI crossover above the oversold level can signal an emerging upward trend, while a crossover below the overbought level may indicate a downturn, providing actionable alerts that can be integrated into your trading strategy.
Overall, the ReadyFor401k Stoch + RSI indicator is designed to offer a clear, concise, and visually engaging method for monitoring market momentum. It serves as an excellent complement to other technical analysis tools and can help improve your decision-making process by providing early warning signals for potential market reversals. Whether you’re a seasoned trader or just starting out, this indicator can be a valuable addition to your TradingView toolkit.
Volatility-Enhanced Williams %R [AIBitcoinTrend]👽 Volatility-Enhanced Williams %R (AIBitcoinTrend)
The Volatility-Enhanced Williams %R takes the classic Williams %R oscillator to the next level by incorporating volatility-adaptive smoothing, making it significantly more responsive to market dynamics. Unlike the traditional version, which uses a fixed calculation method, this indicator dynamically adjusts its smoothing factor based on market volatility, helping traders capture trends more effectively while filtering out noise.
Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, providing traders with enhanced risk management tools and early reversal signals.
👽 What Makes the Volatility-Enhanced Williams %R Unique?
Unlike the standard Williams %R, which applies a simple lookback-based formula, this version integrates adaptive smoothing and volatility-based filtering to refine its signals and reduce false breakouts.
✅ Volatility-Adaptive Smoothing – Adjusts dynamically based on standard deviation, enhancing signal accuracy.
✅ Real-Time Divergence Detection – Identifies bullish and bearish divergences for early trend reversal signals.
✅ Crossovers & Trailing Stops – Implements Williams %R crossovers with ATR-based trailing stops for intelligent trade management.
👽 The Math Behind the Indicator
👾 Volatility-Adaptive Smoothing
The indicator smooths the Williams %R calculation by applying an adaptive filtering mechanism, which adjusts its responsiveness based on market conditions. This helps to eliminate whipsaws and makes trend-following strategies more reliable.
The smoothing function is defined as:
clamp(x, lo, hi) => math.min(math.max(x, lo), hi)
adaptive(src, prev, len, divisor, minAlpha, maxAlpha) =>
vol = ta.stdev(src, len)
alpha = clamp(vol / divisor, minAlpha, maxAlpha)
prev + alpha * (src - prev)
Where:
Volatility Factor (vol) measures price dispersion using standard deviation.
Adaptive Alpha (alpha) dynamically adjusts smoothing strength.
Clamped Output ensures that the smoothing factor remains within a stable range.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while Williams %R forms a higher low.
Buy signal is confirmed when Williams %R reverses upward.
Bearish Divergence Setup:
Price makes a higher high, while Williams %R forms a lower high.
Sell signal is confirmed when Williams %R reverses downward.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ Williams %R crosses above trigger level → Buy signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if price crosses below the stop.
Bearish Setup:
✅ Williams %R crosses below trigger level → Sell signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Adaptive Filtering Mechanism – Avoids excessive noise while maintaining responsiveness.
Real-Time Divergence Alerts – Helps traders anticipate market reversals before they occur.
ATR-Based Risk Management – Stops dynamically adjust based on market volatility.
Multi-Market Compatibility – Works effectively across stocks, forex, crypto, and futures.
👽 Indicator Settings
Smoothing Factor – Controls how aggressively the indicator adapts to volatility.
Enable Divergence Analysis – Activates real-time divergence detection.
Lookback Period – Defines the number of bars for detecting pivot points.
Enable Crosses Signals – Turns on Williams %R crossover-based trade signals.
ATR Multiplier – Adjusts trailing stop sensitivity.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Normalised Price Crossover - MACD but TickersEver noticed two different tickers are correlated yet have different lags? Ever find one ticker moves first and when the other finally goes to catch up, the first one has already reversed?
So I thought to myself, would be wicked if I took the faster one and made it into a 'Signal Line' and the slow one and made it into a 'Slow Line' almost like a MACD if you will.
So that's what I did, I took the price charts of the tickers and I normalised the price data so they could actually cross, plotted it and sat back to see it generate signals, lo and behold!
Pretty neat, though I'd advise to use spreads and such for the different tickers to really feel the power of the indicator, works well when you use formulas that model actual mechanisms instead of arbitrary price data of different assets as correlation =/= causation.
Enjoy.
Bollinger Momentum Deviation | QuantEdgeBIntroducing Bollinger Momentum Deviation (BMD) by QuantEdgeB
🛠️ Overview
Bollinger Momentum Deviation (BMD) is a trend-following momentum indicator designed to identify strong price movements while also detecting overbought and oversold conditions in ranging markets.
By normalizing a simple moving average (SMA) with standard deviation, BMD captures momentum shifts, helping traders make data-driven entries and exits. In trending conditions, it acts as a momentum confirmation tool, while in ranging markets, it highlights mean-reversion opportunities for profit-taking or re-accumulation.
BMD combines the best of both worlds—a robust trend-following framework with an integrated volatility-based overbought/oversold detection system.
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✨ Key Features
🔹 Momentum & Trend-Following Core
Built upon a normalized SMA with standard deviation filtering, BMD efficiently tracks price movements while reducing lag.
🔹 Overbought/Oversold Market Detection
By dynamically adjusting its thresholds based on standard deviation, it identifies high-probability reversion zones in sideways markets.
🔹 Adaptive Normalization Mechanism
Ensures consistent signal reliability across different assets and timeframes by standardizing momentum fluctuations.
🔹 Customizable Visual & Signal Settings
Includes multiple color modes, extra plots, and trend labels, making it easy to align with different trading styles.
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📊 How It Works
1️⃣ Normalized Momentum Calculation
BMD computes a normalized momentum score using a simple moving average (SMA) combined with a standard deviation (SD) filter to create dynamic upper and lower bands. The final momentum score is derived by normalizing the price within this volatility-adjusted range. This normalization makes momentum readings comparable across different price levels and timeframes.
2️⃣ Standard Deviation Filtering
Unlike traditional approaches where standard deviation is derived from price as is the first SD, BMDs second SD is driven from the normalized momentum oscillator itself. This allows for a volatility-adjusted smoothing mechanism that adapts to momentum shifts rather than raw price fluctuations. This ensures that the trend signals remain dynamic and responsive, filtering out short-term noise while keeping the core momentum structure intact. By applying standard deviation directly to the oscillator, BMD achieves a self-regulating feedback loop, improving accuracy in both trending and range-bound conditions.
3️⃣ Signal Generation
✅ Long Signal → Upper BMD SD > Long Threshold (83)
❌ Short Signal → Lower BMD SD < Short Threshold (60)
📌 Additional Features:
- Overbought Zone → Values above 130 indicate price extension.
- Oversold Zone → Values below -10 suggest potential accumulation.
- Momentum Labels → Optional "Long" and "Short" markers for clear trade identification.
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👥 Who Should Use It?
✅ Trend Traders & Momentum Followers → Use BMD as a confirmation tool for strong directional trends.
✅ Range & Mean Reversion Traders → Identify reversal opportunities at extreme BMD levels.
✅ Swing & Position Traders → Utilize normalized momentum shifts for data-driven entries & exits.
✅ Systematic & Quant Traders → Implement BMD within algorithmic frameworks for adaptive market detection.
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⚙️ Customization & Default Settings
🔧 Key Custom Inputs:
- Base Length (Default: 40) → Defines the SMA calculation period.
- Standard Deviation Length (Default: 50) → Controls the volatility filter strength.
- SD Multiplier (Default: 0-7) → Adjusts the sensitivity of the momentum filter.
- Long Threshold (Default: 83) → Above this level, momentum is bullish.
- Short Threshold (Default: 60) → Below this level, momentum weakens.
- Visual Customizations → Multiple color themes, extra plots, and trend labels available.
🚀 By default, BMD is optimized for trend-following and momentum filtering while remaining adaptable to various trading strategies.
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📌 How to Use Bollinger Momentum Deviation (BMD) in Trading
1️⃣ Trend-Following Strategy (Momentum Confirmation)
✔ Enter long positions when BMD crosses above the long threshold (83), confirming upward momentum.
✔ Enter short positions when BMD crosses below the short threshold (60), confirming downward momentum.
✔ Stay in trades as long as BMD remains in trend direction, filtering out noise.
2️⃣ Mean Reversion Strategy (Overbought/Oversold Conditions)
✔ Take profits or hedge when BMD crosses above 130 (overbought).
✔ Re-accumulate positions when BMD drops below -10 (oversold).
📌 Why?
- In trending markets, follow BMD’s momentum confirmation.
- In ranging markets, use BMD’s normalized bands to buy at deep discounts and sell into strength.
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📌 Conclusion
Bollinger Momentum Deviation (BMD) is a versatile momentum indicator that combines trend-following mechanics with volatility-adjusted mean reversion zones. By normalizing SMA-based momentum shifts, BMD ensures robust signal reliability across different assets and timeframes.
🔹 Key Takeaways:
1️⃣ Momentum Confirmation & Trend Detection – Captures directional strength with dynamic filtering.
2️⃣ Overbought/Oversold Conditions – Identifies reversal opportunities in sideways markets.
3️⃣ Adaptive & Customizable – Works across different timeframes and trading styles.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Relative Vigor Index (RVI) with EMD [AIBitcoinTrend]👽 Adaptive Relative Vigor Index with EMD & Signals (AIBitcoinTrend)
The Adaptive Relative Vigor Index (RVI) with Empirical Mode Decomposition (EMD) is an enhanced version of the traditional RVI, designed to improve signal clarity and responsiveness to market conditions. By integrating EMD smoothing and adaptive volatility-based trailing stops.
👽 What Makes the Adaptive RVI with EMD Unique?
Unlike the standard RVI, which often lags in volatile markets, this version refines price momentum detection by applying Empirical Mode Decomposition (EMD), effectively filtering out noise. Additionally, it features ATR-based trailing stops for precise trade execution.
Key Features:
EMD-Enhanced RVI – Filters out short-term noise, improving signal accuracy.
Crossover & Crossunder Signals – Generates trade signals based on RVI trends.
ATR-Based Trailing Stop – Adjusts dynamically based on volatility for optimal risk management.
👽 The Math Behind the Indicator
👾 RVI Calculation with EMD Smoothing
The Relative Vigor Index (RVI) measures trend strength by comparing the relationship between closing and opening prices, relative to the high-low range. Traditional RVI uses fixed smoothing, whereas this version applies Empirical Mode Decomposition (EMD) to extract dominant price cycles and improve trend clarity.
How It Works:
The RVI is initially calculated using a weighted moving average (WMA) over a specified period.
EMD refines the RVI signal by removing high-frequency noise, creating a smoothed RVI component.
This results in a more stable and reliable trend indicator.
👽 How Traders Can Use This Indicator
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ RVI crosses above EMD → Buy signal.
✅ A bullish trailing stop is placed at low - ATR × Multiplier.
✅ Exit if price crosses below the stop.
Bearish Setup:
✅ RVI crosses below EMD → Sell signal.
✅ A bearish trailing stop is placed at high + ATR × Multiplier.
✅ Exit if price crosses above the stop.
👾 Detecting Overbought & Oversold Areas
This indicator helps traders identify potential reversal zones by highlighting overbought and oversold conditions.
Overbought Zone: When RVI moves above 0.4, the market may be overextended, signaling a potential reversal downward.
Oversold Zone: When RVI moves below -0.4, the market may be undervalued, suggesting a possible upward reversal.
Using these levels, traders can confirm entry and exit points alongside divergence signals for higher probability trades.
👽 Why It’s Useful for Traders
EMD-Based Signal Enhancement: Filters out noise, refining momentum signals.
Adaptive ATR-Based Risk Management: Automatically adjusts stop-loss levels to market conditions.
Works Across Multiple Markets & Timeframes: Effective for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
RVI Length – Defines the period for calculating the Relative Vigor Index.
EMD Period – Controls the level of EMD smoothing applied.
Final Smoothing – Adjusts the degree of additional signal filtering.
Lookback Period – Determines how many bars are used for detecting pivot points.
Enable Trailing Stop – Activates dynamic ATR-based trailing stops.
ATR Multiplier – Adjusts the stop-loss sensitivity.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Pure CocaPure Coca - Trend & Mean Reversion Indicator
Overview
The Pure Coca indicator is a trend and mean reversion analysis tool designed for identifying dynamic shifts in market behavior. By leveraging Z-score calculations, this indicator captures both trend-following and mean-reverting periods, making it useful for a wide range of trading strategies.
What It Does
📉 Detects Overbought & Oversold Conditions using a Z-score framework.
🎯 Identifies Trend vs. Mean Reversion Phases by analyzing the deviation of price from its historical average.
📊 Customizable Moving Averages (EMA, SMA, VWMA, etc.) for smoothing Z-score calculations.
🔄 Adaptable to Any Timeframe – Default settings are optimized for 2D charts but can be adjusted to suit different market conditions.
How It Works
Computes a Z-score of price movements, normalized over a lookback period.
Plots upper and lower boundaries to visualize extreme price movements.
Dynamic Midlines adjust entry and exit conditions based on market shifts.
Background & Bar Coloring help traders quickly identify trading opportunities.
Key Features & Inputs
✔ Lookback Period: Adjustable period for calculating Z-score.
✔ Custom MA Smoothing: Choose from EMA, SMA, WMA, VWAP, and more.
✔ Z-Score Thresholds: Set upper and lower bounds to define overbought/oversold conditions.
✔ Trend vs. Mean Reversion Mode: Enables traders to spot momentum shifts in real-time.
✔ Bar Coloring & Background Highlights: Enhances visual clarity for decision-making.
How to Use It
Trend Trading: Enter when the Z-score crosses key levels (upper/lower boundary).
Mean Reversion: Look for reversals when price returns to the midline.
Custom Optimization: Adjust lookback periods and MA types based on market conditions.
Why It's Unique
✅ Combines Trend & Mean Reversion Analysis in one indicator.
✅ Flexible Z-score settings & MA choices for enhanced adaptability.
✅ Clear visual representation of market extremes.
Final Notes
This indicator is best suited for discretionary traders, quantitative analysts, and systematic traders looking for data-driven market insights. As with any trading tool, use in conjunction with other analysis methods for optimal results.
Adaptive Stochastic Oscillator with Signals [AIBitcoinTrend]👽 Adaptive Stochastic Oscillator with Signals (AIBitcoinTrend)
The Adaptive Stochastic Oscillator with Signals is a refined version of the traditional Stochastic Oscillator, dynamically adjusting its lookback period based on market volatility. This adaptive approach improves responsiveness to market conditions, reducing lag while maintaining trend sensitivity. Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, allowing traders to manage risk and optimize trade exits effectively.
👽 What Makes the Adaptive Stochastic Oscillator Unique?
Unlike the standard Stochastic Oscillator, which uses a fixed lookback period, this version dynamically adjusts the period length using an ATR-based fractal dimension. This makes it more responsive to market conditions, filtering out noise while capturing key price movements.
Key Features:
Adaptive Lookback Calculation – Stochastic period changes dynamically based on volatility.
Real-Time Divergence Detection – Identify bullish and bearish divergences instantly.
Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Adaptive Lookback Period Calculation
Traditional Stochastic Oscillators use a fixed-length period for their calculations, which can lead to inaccurate signals in varying market conditions. This version automatically adjusts its lookback period based on market volatility using an ATR-based fractal dimension approach.
How it Works:
The fractal dimension (FD) is calculated using the ATR (Average True Range) over a defined period.
FD values dynamically adjust the Stochastic lookback period between a minimum and maximum range.
This results in a faster response in high-volatility conditions and smoother signals during low volatility.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Traders can anticipate trend reversals before they occur using real-time divergence detection.
Bullish Divergence Setup:
Identify price making a lower low while Stochastic %K makes a higher low.
Enter a long trade when Stochastic confirms upward momentum.
Bearish Divergence Setup:
Identify price making a higher high while Stochastic %K makes a lower high.
Enter a short trade when Stochastic confirms downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅Stochastic %K crosses above 90 → Buy signal.
✅A bullish trailing stop is placed at low - ATR × Multiplier.
✅Exit if the price crosses below the stop.
Bearish Setup:
✅Stochastic %K crosses below 10 → Sell signal.
✅A bearish trailing stop is placed at high + ATR × Multiplier.
✅Exit if the price crosses above the stop.
👽 Why It’s Useful for Traders
Adaptive Period Calculation: Dynamically adjusts to market volatility.
Real-Time Divergence Alerts: Helps traders identify trend reversals in advance.
ATR-Based Risk Management: Automatically adjusts stop levels based on price movements.
Works Across Multiple Markets & Timeframes: Useful for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
Min & Max Lookback Periods – Define the range for the adaptive Stochastic period.
Enable Divergence Analysis – Toggle real-time divergence detection.
Lookback Period – Set the number of bars for detecting pivot points.
Enable Trailing Stop – Activate the dynamic trailing stop feature.
ATR Multiplier – Adjust stop-loss sensitivity.
Line Width & Colors – Customize stop-loss visualization.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Uptrick: Portfolio Allocation DiversificationIntro
The Uptrick: Portfolio Allocation Diversification script is designed to help traders and investors manage multiple assets simultaneously. It generates signals based on various trading systems, allocates capital using different diversification methods, and displays real-time metrics and performance tables on the chart. The indicator compares active trading strategies with a separate long-term holding (HODL) simulation, allowing you to see how a systematic trading approach stacks up against a simple buy-and-hold strategy.
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Trading System Selection
1. No signals (none)
In this mode, the script does not produce bullish or bearish indicators; every asset stays in a neutral stance. This setup is useful if you prefer to observe how capital might be distributed based solely on the chosen diversification method, with no influence from directional signals.
2. rsi – neutral
This mode uses an index-based measure of whether an asset appears overbought or oversold. It generates a bearish signal if market conditions point to overbought territory, and a bullish signal if they indicate oversold territory. If neither extreme surfaces, it remains neutral. Some traders apply this in sideways or range-bound conditions, where overbought and oversold levels often hint at possible turning points. It does not specifically account for divergence patterns.
3. rsi – long only
In this setting, the system watches for instances where momentum readings strengthen even if the asset’s price is still under pressure or setting new lows. It also considers oversold levels as potential signals for a bullish setup. When such conditions emerge, the script flags a possible move to the upside, ignoring indications that might otherwise suggest a bearish trend. This approach is generally favored by those who want to concentrate exclusively on identifying price recoveries.
4. rsi – short only
Here, the script focuses on spotting signs of deteriorating momentum while an asset’s price remains relatively high or attempts further gains. It also checks whether the market is drifting into overbought territory, suggesting a potential decline. Under such conditions, it issues a bearish signal. It provides no bullish alerts, making it particularly suitable for traders who look to take advantage of overvalued scenarios or protect themselves against sudden downward moves.
5. Deviation from fair value
Under this system, the script judges how far the current price may have strayed from what is considered typical, taking into account normal fluctuations. If the asset appears to be trading at an unusually low level compared to that reference, it is flagged as bullish. If it seems abnormally high, a bearish signal is issued. This can be applied in various market environments to seek opportunities that arise from perceived mispricing.
6. Percentile channel valuation
In this mode, the script determines where an asset's price stands within a historical distribution, highlighting whether it has reached unusually high or low territory compared to its recent past. When the price reaches what is deemed an extreme reading, it may indicate that a reversal is more likely. This approach is often used by traders who watch for statistical outliers and potential reversion to a more typical trading range.
7. ATH valuation
This technique involves comparing an asset's current price with its previously recorded peak values. The script then interprets whether the price is positioned so far below the all-time high that it looks discounted, or so close to that high that it could be overextended. Such perspective is favored by market participants who want to see if an asset still has ample room to climb before matching historic extremes, or if it is nearing a possible ceiling.
8. Z-score system
Here, the script measures how far above or below a standard reference average an asset's price may be, translated into standardized units. Substantial negative readings can suggest a price that might be unusually weak, prompting a bullish indication, while large positive readings could signal overextension and lead to a bearish call. This method is useful for traders watching for abrupt deviations from a norm that often invite a reversion to more balanced levels.
RSI Divergence Period
This input is particularly relevant for the RSI - Long Only and RSI - Short Only modes. The period determines how many bars in the past you compare RSI values to detect any divergences.
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Diversification Method
Once the script has determined a bullish, bearish, or neutral stance for each asset, it then calculates how to distribute capital among all included assets. The diversification method sets the weighting logic.
1. None
Gives each asset an equal weight. For example, if you have five included assets, each might get 20 percent. This is a simple baseline.
2. Risk-Adjusted Expected Return Using Volatility Clustering
Emphasizes each asset’s average returns relative to its observed risk or volatility tendencies. Assets that exhibit good risk-adjusted returns combined with moderate or lower volatility may receive higher weights than more volatile or less appealing assets. This helps steer capital toward assets that have historically provided a better ratio of return to risk.
3. Relative Strength
Allocates more capital to assets that show stronger price strength compared to a reference (for example, price above a long-term moving average plus a higher RSI). Assets in clear uptrends may be given higher allocations.
4. Trend-Following Indicators
Examines trend-based signals, like positive momentum measurements or upward-trending strength indicators, to assign more weight to assets demonstrating strong directional moves. This suits those who prefer to latch onto trending markets.
5. Volatility-Adjusted Momentum
Looks for assets that have strong price momentum but relatively subdued volatility. The script tends to reward assets that are trending well yet are not too volatile, aiming for stable upward performance rather than massive swings.
6. Correlation-Based Risk Parity
Attempts to weight assets in such a way that the overall portfolio risk is more balanced. Although it is not an advanced correlation matrix approach in a strict sense, it conceptually scales each asset’s weight so no single outlier heavily dominates.
7. Omega Ratio Maximization
Gives preference to assets with higher omega ratios. This ratio can be interpreted as the probability-weighted gains versus losses. Assets with a favorable skew are given more capital.
8. Liquidity-Weighted Valuation
Considers each asset’s average trading liquidity, such as the combination of volume and price. More liquid assets typically receive a higher allocation because they can be entered or exited with lower slippage. If the trading system signals bullishness, that can further boost the allocation, and if it signals bearishness, the allocation might be set to zero or reduced drastically.
9. Drawdown-Controlled Allocation (DCA)
Examines each asset’s maximum drawdown over a recent window. Assets experiencing lighter drawdowns (thus indicating somewhat less downside volatility) receive higher allocations, aiming for a smoother overall equity curve.
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Portfolio and Allocation Settings
Portfolio Value
Defines how much total capital is available for the strategy-based investment portion. For example, if set to 10,000, then each asset’s monetary allocation is determined by the percentage weighting times 10,000.
Use Fixed Allocation
When enabled, the script calculates the initial allocation percentages after 50 bars of data have passed. It then locks those percentages for the remainder of the backtest or real-time session. This feature allows traders to test a static weighting scenario to see how it differs from recalculating weights at each bar.
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HODL Simulator
The script has a separate simulation that accumulates positions in an asset whenever it appears to be recovering from an undervalued state. This parallel tracking is intended to contrast a simple buy-and-hold approach with the more adaptive allocation methods used elsewhere in the script.
HODL Buy Quantity
Each time an asset transitions from an undervalued state to a recovery phase, the simulator executes a purchase of a predefined quantity. For example, if set to 0.5 units, the system will accumulate this amount whenever conditions indicate a shift away from undervaluation.
HODL Buy Threshold
This parameter determines the level at which the simulation identifies an asset as transitioning out of an undervalued state. When the asset moves above this threshold after previously being classified as undervalued, a buy order is triggered. Over time, the performance of these accumulated positions is tracked, allowing for a comparison between this passive accumulation method and the more dynamic allocation strategy.
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Asset Table and Display Settings
The script displays data in multiple tables directly on your chart. You can toggle these tables on or off and position them in various corners of your TradingView screen.
Asset Info Table Position
This table provides key details for each included asset, displaying:
Symbol – Identifies the trading pair being monitored. This helps users keep track of which assets are included in the portfolio allocation process.
Current Trading Signal – Indicates whether the asset is in a bullish, bearish, or neutral state based on the selected trading system. This assists in quickly identifying which assets are showing potential trade opportunities.
Volatility Approximation – Represents the asset’s historical price fluctuations. Higher volatility suggests greater price swings, which can impact risk management and position sizing.
Liquidity Estimate – Reflects the asset’s market liquidity, often based on trading volume and price activity. More liquid assets tend to have lower transaction costs and reduced slippage, making them more favorable for active strategies.
Risk-Adjusted Return Value – Measures the asset’s returns relative to its risk level. This helps in determining whether an asset is generating efficient returns for the level of volatility it experiences, which is useful when making allocation decisions.
2. Strategy Allocation Table Position
Displays how your selected diversification method converts each asset into an allocation percentage. It also shows how much capital is being invested per asset, the cumulative return, standard performance metrics (for example, Sharpe ratio), and the separate HODL return percentage.
Symbol – Displays the asset being analyzed, ensuring clarity in allocation distribution.
Allocation Percentage – Represents the proportion of total capital assigned to each asset. This value is determined by the selected diversification method and helps traders understand how funds are distributed within the portfolio.
Investment Amount – Converts the allocation percentage into a dollar value based on the total portfolio size. This shows the exact amount being invested in each asset.
Cumulative Return – Tracks the total return of each asset over time, reflecting how well it has performed since the strategy began.
Sharpe Ratio – Evaluates the asset’s return in relation to its risk by comparing excess returns to volatility. A higher Sharpe ratio suggests a more favorable risk-adjusted performance.
Sortino Ratio – Similar to the Sharpe ratio, but focuses only on downside risk, making it more relevant for traders who prioritize minimizing losses.
Omega Ratio – Compares the probability of achieving gains versus losses, helping to assess whether an asset provides an attractive risk-reward balance.
Maximum Drawdown – Measures the largest percentage decline from an asset’s peak value to its lowest point. This metric helps traders understand the worst-case loss scenario.
HODL Return Percentage – Displays the hypothetical return if the asset had been bought and held instead of traded actively, offering a direct comparison between passive accumulation and the active strategy.
3. Profit Table
If the Profit Table is activated, it provides a summary of the actual dollar-based gains or losses for each asset and calculates the overall profit of the system. This table includes separate columns for profit excluding HODL and the combined total when HODL gains are included. As seen in the image below, this allows users to compare the performance of the active strategy against a passive buy-and-hold approach. The HODL profit percentage is derived from the Portfolio Value input, ensuring a clear comparison of accumulated returns.
4. Best Performing Asset Table
Focuses on the single highest-returning or highest-profit asset at that moment. It highlights the symbol, the asset’s cumulative returns, risk metrics, and other relevant stats. This helps identify which asset is currently outperforming the rest.
5. Most Profitable Asset
A simpler table that underscores the asset producing the highest absolute dollar profit across the portfolio.
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Multi Asset Selection
You can include up to ten different assets (such as BTCUSDT, ETHUSDT, ADAUSDT, and so on) in this script. Each asset has two inputs: one to enable or disable its inclusion, and another to select its trading pair symbol. Once you enable an asset, the script requests the relevant market data from TradingView.
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Uniqness and Features
1. Multiple Data Fetches
Each asset is pulled from the chart’s timeframe, along with various metrics such as RSI, volatility approximations, and trend indicators.
2. Various Risk and Performance Metrics
The script internally keeps track of different measures, like Sharpe ratio (a measure of average return adjusted for risk), Sortino ratio (which focuses on downside volatility), Omega ratio, and maximum drawdown. These metrics feed into the strategy allocation table, helping you quickly assess the risk-and-return profile of each asset.
3. Real-Time Tables
Instead of having to set up complex spreadsheets or external dashboards, the script updates all tables on every new bar. The color schemes in these tables are designed to draw attention to bullish or bearish signals, positive or negative returns, and so forth.
4. HODL Comparison
You can visually compare the active strategy’s results to a separate continuous buy-on-dips accumulation strategy. This allows for insight into whether your dynamic approach truly beats a simpler, more patient method.
5. Locking Allocations
The Use Fixed Allocation input is convenient for those who want to see how holding a fixed distribution of capital performs over time. It helps in distinguishing between constant rebalancing vs a fixed, set-and-forget style.
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How to use
1. Add the Script to Your Chart
Once added, open the settings panel to configure your asset list, choose a trading system, and select the diversification approach.
2. Select Assets
Pick up to ten symbols to monitor. Disable any you do not want included. Each included asset is then handled for signals, diversification, and performance metrics.
3. Choose Trading System
Decide if you prefer RSI-based signals, a fair-value approach, or a percentile-based method, among others. The script will then flag assets as bullish, bearish, or neutral according to that selection.
4. Pick a Diversification Method
For example, you might choose Trend-Following Indicators if you believe momentum stocks or cryptocurrencies will continue their trends. Or you could use the Omega Ratio approach if you want to reward assets that have had a favorable upside probability.
5. Set Portfolio Value and HODL Parameters
Enter how much capital you want to allocate in total (for the dynamic strategy) and adjust HODL buy quantities and thresholds as desired. (HODL Profit % is calculated from the Portfolio Value)
6. Inspect the Tables
On the chart, the script can display multiple tables showing your allocations, returns, risk metrics, and which assets are leading or lagging. Monitor these to make decisions about capital distribution or see how the strategy evolves.
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Additional Remarks
This script aims to simplify multi-asset portfolio management in a single tool. It emphasizes user-friendliness by color-coding the data in tables, so you do not need extra spreadsheets. The script is also flexible in letting you lock allocations or compare dynamic updates.
Always remember that no script can guarantee profitable outcomes. Real markets involve unpredictability, and real trading includes fees, slippage, and liquidity constraints not fully accounted for here. The script uses real-time and historical data for demonstration and educational purposes, providing a testing environment for various systematic strategies.
Performance Considerations
Due to the complexity of this script, users may experience longer loading times, especially when handling multiple assets or using advanced allocation methods. In some cases, calculations may time out if too many settings are adjusted simultaneously. If this occurs, removing and reapplying the indicator to the chart can help reset the process. Additionally, it is recommended to configure inputs gradually instead of adjusting all parameters at once, as excessive changes can extend the script’s loading duration beyond TradingView’s processing limits.
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Originality
This script stands out by integrating multiple asset management techniques within a single indicator, eliminating the need for multiple scripts or external portfolio tools. Unlike traditional single-asset strategies, it simultaneously evaluates multiple assets, applies systematic allocation logic, and tracks risk-adjusted performance in real time. The script is designed to function within TradingView’s script limitations while still allowing for complex portfolio simulations, making it an efficient tool for traders managing diverse holdings. Additionally, its combination of systematic trading signals with allocation-based diversification provides a structured approach to balancing exposure across different market conditions. The dynamic interplay between adaptive trading strategies and passive accumulation further differentiates it from conventional strategy indicators that focus solely on directional signals without considering capital allocation.
Conclusion
Uptrick: Portfolio Allocation Diversification pulls multiple assets into one efficient workflow, where each asset’s signal, volatility, and performance is measured, then assigned a share of capital according to your selected diversification method. The script accommodates both dynamic rebalancing and a locked allocation style, plus an ongoing HODL simulation for passive accumulation comparison. It neatly visualizes the entire process through on-chart tables that are updated every bar.
Traders and investors looking for ways to manage multiple assets under one unified framework can explore the different modules within this script to find what suits their style. Users can quickly switch among trading systems, vary the allocation approach, or review side-by-side performance metrics to see which method aligns best with their risk tolerance and market perspective.
RSI Failure Swing Pattern (with Alerts & Targets)RSI Failure Swing Pattern Indicator – Detailed Description
Overview
The RSI Failure Swing Pattern Indicator is a trend reversal detection tool based on the principles of failure swings in the Relative Strength Index (RSI). This indicator identifies key reversal signals by analyzing RSI swings and confirming trend shifts using predefined overbought and oversold conditions.
Failure swing patterns are one of the strongest RSI-based reversal signals, initially introduced by J. Welles Wilder. This indicator detects these patterns and provides clear buy/sell signals with labeled entry, stop-loss, and profit target levels. The tool is designed to work across all timeframes and assets.
How the Indicator Works
The RSI Failure Swing Pattern consists of two key structures:
1. Bullish Failure Swing (Buy Signal)
Occurs when RSI enters oversold territory (below 30), recovers, forms a higher low above the oversold level, and finally breaks above the intermediate swing high in RSI.
Step 1: RSI dips below 30 (oversold condition).
Step 2: RSI rebounds and forms a local peak.
Step 3: RSI retraces but does not go below the previous low (higher low confirmation).
Step 4: RSI breaks above the previous peak, confirming a bullish trend reversal.
Buy signal is triggered at the breakout above the RSI peak.
2. Bearish Failure Swing (Sell Signal)
Occurs when RSI enters overbought territory (above 70), declines, forms a lower high below the overbought level, and then breaks below the intermediate swing low in RSI.
Step 1: RSI rises above 70 (overbought condition).
Step 2: RSI declines and forms a local trough.
Step 3: RSI bounces but fails to exceed the previous high (lower high confirmation).
Step 4: RSI breaks below the previous trough, confirming a bearish trend reversal.
Sell signal is triggered at the breakdown below the RSI trough.
Features of the Indicator
Custom RSI Settings: Adjustable RSI length (default 14), overbought/oversold levels.
Buy & Sell Signals: Buy/sell signals are plotted directly on the price chart.
Entry, Stop-Loss, and Profit Targets:
Entry: Price at the breakout of the RSI failure swing pattern.
Stop-Loss: Lowest low (for buy) or highest high (for sell) of the previous two bars.
Profit Targets: Two levels calculated based on Risk-Reward ratios (1:1 and 1:2 by default, customizable).
Labeled Price Levels:
Entry Price Line (Blue): Marks the point of trade entry.
Stop-Loss Line (Red): Shows the calculated stop-loss level.
Target 1 Line (Orange): Profit target at 1:1 risk-reward ratio.
Target 2 Line (Green): Profit target at 1:2 risk-reward ratio.
Alerts for Trade Execution:
Buy/Sell signals trigger alerts for real-time notifications.
Alerts fire when price reaches stop-loss or profit targets.
Works on Any Timeframe & Asset: Suitable for stocks, forex, crypto, indices, and commodities.
Why Use This Indicator?
Highly Reliable Reversal Signals: Unlike simple RSI overbought/oversold strategies, failure swings filter out false breakouts and provide strong confirmation of trend reversals.
Risk Management Built-In: Stop-loss and take-profit levels are automatically set based on historical price action and risk-reward considerations.
Easy-to-Use Visualization: Clearly marked entry, stop-loss, and profit target levels make it beginner-friendly while still being valuable for experienced traders.
How to Trade with the Indicator
Buy Trade Example (Bullish Failure Swing)
RSI drops below 30 and recovers.
RSI forms a higher low and then breaks above the previous peak.
Entry: Buy when RSI crosses above its previous peak.
Stop-Loss: Set below the lowest low of the previous two candles.
Profit Targets:
Target 1 (1:1 Risk-Reward Ratio)
Target 2 (1:2 Risk-Reward Ratio)
Sell Trade Example (Bearish Failure Swing)
RSI rises above 70 and then declines.
RSI forms a lower high and then breaks below the previous trough.
Entry: Sell when RSI crosses below its previous trough.
Stop-Loss: Set above the highest high of the previous two candles.
Profit Targets:
Target 1 (1:1 Risk-Reward Ratio)
Target 2 (1:2 Risk-Reward Ratio)
Final Thoughts
The RSI Failure Swing Pattern Indicator is a powerful tool for traders looking to identify high-probability trend reversals. By using the RSI failure swing concept along with built-in risk management tools, this indicator provides a structured approach to trading with clear entry and exit points. Whether you’re a day trader, swing trader, or long-term investor, this indicator helps in capturing momentum shifts while minimizing risk.
Would you like any modifications or additional features? 🚀
RSI Signal with filters by S.Kodirov📌 English
RSI Signal with Multi-Timeframe Filters
This TradingView indicator generates RSI-based buy and sell signals on the 15-minute timeframe with additional filtering from other timeframes (5M, 30M, 1M).
🔹 Signal Types:
✅ 15/5B & 15/5S – RSI 15M filtered by 5M
✅ 15/30/1B & 15/30/1S – RSI 15M filtered by 30M & 1M
✅ 15B & 15S – RSI 15M without filters
🔹 How It Works:
Signals are displayed as colored triangles on the chart.
Labels indicate the type of signal (e.g., 15/5B, 15S).
Alerts notify users when a signal appears.
🚀 Best for short-term trading with RSI confirmation from multiple timeframes!
📌 Русский
Индикатор RSI с мульти-таймфрейм фильтрами
Этот индикатор для TradingView генерирует сигналы покупки и продажи на 15-минутном таймфрейме, используя фильтрацию с других таймфреймов (5M, 30M, 1M).
🔹 Типы сигналов:
✅ 15/5B & 15/5S – RSI 15M с фильтром 5M
✅ 15/30/1B & 15/30/1S – RSI 15M с фильтрами 30M и 1M
✅ 15B & 15S – RSI 15M без фильтров
🔹 Как это работает:
Сигналы отображаются как цветные треугольники на графике.
Подписи показывают тип сигнала (например, 15/5B, 15S).
Алерты уведомляют трейдера о появлении сигнала.
🚀 Идеально для краткосрочной торговли с подтверждением RSI на нескольких таймфреймах!
📌 O'zbekcha
Ko'p vaqt oralig‘idagi RSI signallari
Ushbu TradingView indikatori 15 daqiqalik vaqt oralig‘ida RSI asosida sotib olish va sotish signallarini yaratadi. Bundan tashqari, boshqa vaqt oralig‘idagi (5M, 30M, 1M) RSI filtrlarini ham hisobga oladi.
🔹 Signal turlari:
✅ 15/5B & 15/5S – 5M bilan filtrlangan RSI 15M
✅ 15/30/1B & 15/30/1S – 30M va 1M bilan filtrlangan RSI 15M
✅ 15B & 15S – Filtrsiz RSI 15M
🔹 Qanday ishlaydi?
Signallar rangli uchburchaklar shaklida ko‘rsatiladi.
Yozuvlar signal turini ko‘rsatadi (masalan, 15/5B, 15S).
Xabarnomalar yangi signal paydo bo‘lganda treyderni ogohlantiradi.
🚀 Ko‘p vaqt oralig‘ida RSI tasdig‘i bilan qisqa muddatli savdo uchun ideal!
Zippo Traffic v2Zippo Traffic v2
Fiyat hareketlerini analiz ederek trend yönünü belirleyen gelişmiş bir trend takip sistemidir. Alış ve satış sinyalleri üretmekle kalmaz, aynı zamanda belirsiz dönemleri sarı barlarla göstererek, işlem yapılmaması gereken durumları da işaret eder.
Nasıl Çalışır?
Bu sistem bir trafik ışığı mantığıyla çalışır:
🟡 Sarı barlar: Piyasada belirsizlik – yeni pozisyon açmayın, mevcut pozisyonu koruyorsanız dikkatli olun.
🟢 Yeşil barlar: Long / Al sinyali – yükseliş trendi.
🔴 Kırmızı barlar: Short / Sat sinyali – düşüş trendi.
Alligator (3 EMA) parametreleri (JawLen, TeethLen, LipsLen) kullanıcı tarafından değiştirilebilir; diğer teknik göstergeler ve hesaplamalar sabittir.
Bu sayede aşırı optimizasyon ve yanlış sinyal alma riski azalır; sistemin temel mantığı korunur.
Öne Çıkan Özellikler:
Nötr Bölgeler: Klasik trend takip indikatörlerinden farklı olarak, sadece “Al” ve “Sat” sinyalleri değil, aynı zamanda piyasada nötr bölgeleri (sarı barlar) belirler.
Momentum + Trend Analizi: Piyasanın yönünü daha doğru analiz etmek için birden fazla kriteri bir arada kullanır.
Standart Fiyat Verisi: Hesaplamalar, standart OHLC değerlerine dayanır. Heikin Ashi veya diğer mum çeşitleri, sadece daha net görsellik amacıyla tercih edilebilir; sinyal üretiminde etkisi yoktur.
Nasıl Kullanılır?
🟢 Yeşil barlar: Güçlü yükseliş trendi (Long).
🔴 Kırmızı barlar: Düşüş trendi (Short).
🟡 Sarı barlar: Trendin belirsiz olduğu alanlardır; bu dönemlerde yeni pozisyon açmaktan kaçının.
Zaman Dilimi ve Kullanım Önerileri
Hacimsiz hisselerde veya düşük likiditeli varlıklarda sinyal kalitesi düşük olabilir.
En iyi sonuçlar için 30 dakika ve üzeri zaman dilimleri önerilir.
Özellikle 4 saatlik, 8 saatlik ve günlük grafiklerde başarılı sonuçlar alınmıştır.
Daha kısa zaman dilimlerinde de kullanılabilir, ancak fiyat oynaklığı yüksek olduğundan sinyallerin doğruluğu düşebilir.
Önemli Uyarı..
Bu indikatör, teknik analiz amaçlı geliştirilmiştir ve yatırım tavsiyesi içermez. Piyasa koşulları hızla değişebilir; tek bir mum bile destek veya direnci kırabilir. Sarı barlar, mevcut pozisyonu kapatıp beklemenizi veya trendin netleşmesini takip etmenizi sağlar. Tüm yatırım kararlarınızı kendi araştırmalarınız ve risk yönetimi stratejileriniz doğrultusunda vermelisiniz.
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Zippo Traffic v2
Zippo Traffic v2 is an advanced trend-following system that analyzes price movements to determine market direction. Not only does it generate buy and sell signals, but it also highlights uncertain market periods with yellow bars, signaling when new positions should not be opened.
How It Works
This system operates on a traffic light principle:
🟡 Yellow Bars: Indicate market uncertainty – refrain from opening new positions and exercise caution if you are already in a trade.
🟢 Green Bars: Signal a Long/Buy – indicating an uptrend.
🔴 Red Bars: Signal a Short/Sell – indicating a downtrend.
The Alligator (3 EMA) parameters (JawLen, TeethLen, LipsLen) are the only inputs that users can modify; all other technical indicators and calculations are fixed. This minimizes the risk of over-optimization and false signals, preserving the system’s core methodology.
Key Features
Neutral Zones: Unlike conventional trend-following indicators that only provide buy and sell signals, this indicator also identifies neutral areas (yellow bars) in the market.
Momentum + Trend Analysis: It combines multiple criteria to more accurately analyze the market direction.
Standard Price Data: All calculations are based on standard OHLC values. While Heikin Ashi or other candlestick styles may be used solely for enhanced visual clarity, they do not affect signal generation.
How to Use
🟢 Green Bars: Indicate a strong uptrend (Long).
🔴 Red Bars: Indicate a downtrend (Short).
🟡 Yellow Bars: Represent uncertain market conditions; avoid opening new positions during these periods.
Timeframe and Usage Recommendations
Signal quality may be poor in low-volume or illiquid securities.
For optimal results, it is recommended to use timeframes of 30 minutes or higher.
It has proven particularly effective on 4-hour, 8-hour, and daily charts.
Although it can be applied to shorter timeframes, increased price volatility may reduce signal accuracy.
Important Notice
This indicator is developed solely for technical analysis purposes and does not constitute investment advice. Market conditions can change rapidly— even a single candle can break through support or resistance levels. Yellow bars indicate that you should close your existing position and wait, or monitor for trend clarification, but do not necessarily signal an imminent trend reversal. All investment decisions should be made based on your own research and risk management strategies.
Market Participation Index [PhenLabs]📊 Market Participation Index
Version: PineScript™ v6
📌 Description
Market Participation Index is a well-evolved statistical oscillator that constantly learns to develop by adapting to changing market behavior through the intricate mathematical modeling process. MPI combines different statistical approaches and Bayes’ probability theory of analysis to provide extensive insight into market participation and building momentum. MPI combines diverse statistical thinking principles of physics and information and marries them for subtle changes to occur in markets, levels to become influential as important price targets, and pattern divergences to unveil before it is visible by analytical methods in an old-fashioned methodology.
🚀 Points of Innovation:
Automatic market condition detection system with intelligent preset selection
Multi-statistical approach combining classical and advanced metrics
Fractal-based divergence system with quality scoring
Adaptive threshold calculation using statistical properties of current market
🚨 Important🚨
The ‘Auto’ mode intelligently selects the optimal preset based on real-time market conditions, if the visualization does not appear to the best of your liking then select the option in parenthesis next to the auto mode on the label in the oscillator in the settings panel.
🔧 Core Components
Statistical Foundation: Multiple statistical measures combined with weighted approach
Market Condition Analysis: Real-time detection of market states (trending, ranging, volatile)
Change Point Detection: Bayesian analysis for finding significant market structure shifts
Divergence System: Fractal-based pattern detection with quality assessment
Adaptive Visualization: Dynamic color schemes with context-appropriate settings
🔥 Key Features
The indicator provides comprehensive market analysis through:
Multi-statistical Oscillator: Combines Z-score, MAD, and fractal dimensions
Advanced Statistical Components: Includes skewness, kurtosis, and entropy analysis
Auto-preset System: Automatically selects optimal settings for current conditions
Fractal Divergence Analysis: Detects and grades quality of divergence patterns
Adaptive Thresholds: Dynamically adjusts overbought/oversold levels
🎨 Visualization
Color-coded Oscillator: Gradient-filled oscillator line showing intensity
Divergence Markings: Clear visualization of bullish and bearish divergences
Threshold Lines: Dynamic or fixed overbought/oversold levels
Preset Information: On-chart display of current market conditions
Multiple Color Schemes: Modern, Classic, Monochrome, and Neon themes
Classic
Modern
Monochrome
Neon
📖 Usage Guidelines
The indicator offers several customization options:
Market Condition Settings:
Preset Mode: Choose between Auto-detection or specific market condition presets
Color Theme: Select visual theme matching your chart style
Divergence Labels: Choose whether or not you’d like to see the divergence
✅ Best Use Cases:
Identify potential market reversals through statistical divergences
Detect changes in market structure before price confirmation
Filter trades based on current market condition (trending vs. ranging)
Find optimal entry and exit points using adaptive thresholds
Monitor shifts in market participation and momentum
⚠️ Limitations
Requires sufficient historical data for accurate statistical analysis
Auto-detection may lag during rapid market condition changes
Advanced statistical calculations have higher computational requirements
Manual preset selection may be required in certain transitional markets
💡 What Makes This Unique
Statistical Depth: Goes beyond traditional indicators with advanced statistical measures
Adaptive Intelligence: Automatically adjusts to current market conditions
Bayesian Analysis: Identifies statistically significant change points in market structure
Multi-factor Approach: Combines multiple statistical dimensions for confirmation
Fractal Divergence System: More robust than traditional divergence detection methods
🔬 How It Works
The indicator processes market data through four main components:
Market Condition Analysis:
Evaluates trend strength, volatility, and price patterns
Automatically selects optimal preset parameters
Adapts sensitivity based on current conditions
Statistical Oscillator:
Combines multiple statistical measures with weights
Normalizes values to consistent scale
Applies adaptive smoothing
Advanced Statistical Analysis:
Calculates higher-order statistical moments
Applies information-theoretic measures
Detects distribution anomalies
Divergence Detection:
Uses fractal theory to identify pivot points
Detects and scores divergence quality
Filters signals based on current market phase
💡 Note:
The Market Participation Index performs optimally when used across multiple timeframes for confirmation. Its statistical foundation makes it particularly valuable during market transitions and periods of changing volatility, where traditional indicators often fail to provide clear signals.
Bollinger Bands MTF & Kalman Filter | Flux Charts📈 Multi-Timeframe Kalman Filtered Bollinger Bands Indicator
Introducing our MTF Kalman Filtered Bollinger Bands – a powerful multi-timeframe Bollinger Bands (BB) indicator enhanced with Kalman filtering for superior smoothing and trend analysis. This indicator dynamically adapts Bollinger Bands across multiple timeframes while incorporating volume-based gradient transparency to highlight significant price movements. This indicator is better optimized for lower timeframes.
❓ How to Interpret the Bands & Volume Gradient:
Our indicator combines Lower Timeframe (LTF) and Higher Timeframe (HTF) Bollinger Bands to provide a comprehensive trend analysis. It applies Kalman filtering to the LTF bands, ensuring smoother, noise-reduced signals. The color gradient and relative volume-based transparency offer deeper insights into price strength.
🔹 LTF Bollinger Bands: Shorter-period bands filtered with a Kalman smoothing algorithm, reducing lag and noise.
🔹 HTF Bollinger Bands: Traditional Bollinger Bands plotted on a higher timeframe, offering macro trend analysis.
🔹 Volume Gradient Transparency: The bands adjust their opacity based on relative buy/sell volume, allowing traders to assess momentum strength.
📌 How Does It Work?
1️⃣ Multi-Timeframe Bollinger Bands Calculation
The LTF BB uses Kalman filtering for a smoother price representation, helping to reduce false signals.
The HTF BB is EMA-smoothed for improved trend clarity.
2️⃣ Adaptive Gradient Transparency
The opacity of the fill color between the bands is determined by relative buy/sell volume.
Higher buy volume = stronger bullish signal (greener bands).
Higher sell volume = stronger bearish signal (redder bands).
3️⃣ Dynamic Trend Signals & Breakouts
Buy Signal: When price breaks below the HTF lower band and LTF bands start rising.
Sell Signal: When price breaks above the HTF upper band and LTF bands start falling.
⚙️ Settings & Customization:
🛠 LTF and HTF Bollinger Bands Settings:
Multiplier: The multiplier applied to the BB to determine the upper and lower bands
Length: Define the number of bars determines the BB calculations.
Custom Timeframe Selection: Choose from predefined options (e.g., 5m, 15m, 1H, 4H, etc).
🎨 Gradient & Transparency Settings:
Bullish/Bearish Color Options: Customize colors for uptrend and downtrend conditions.
Max & Min Opacity: Adjust the transparency levels based on volume intensity.
Solid vs. Gradient Mode: Choose between a gradient fill or a solid color mode for clarity.
📌 Recommended Settings for Optimal Use:
1️⃣ Timeframe Selection (LTF -> HTF):
1 min -> 5 min
2 min -> 5 min
3 min -> 15 min
5 min -> 15 min
15 min -> 1 hr
1 hr -> 4 hr
4 hr -> 1 day
2️⃣ Multiplier: Use 2.0 for LTF and 2.25 for HTF
3️⃣Length: Use a length of 20 - 30 bars
🚀 Why Use This Indicator?
✅ Multi-Timeframe Bollinger Bands with Kalman Filtering – Ideal for traders looking for reduced lag and clearer trend signals.
✅ Volume-Based Transparency – See momentum shifts instantly with adaptive opacity.
✅ Dynamic Buy & Sell Signals – Alerts based on price action + volume trends.
✅ Customizable for Any Strategy – Adjust colors, timeframes, and filtering options for personalized trading.
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
Stochastic Momentum Triangles[TheJackrabbit]This code is invite-only and in the experimental phase. Please contact the author if you are interested in testing.
**Stochastic Momentum Triangles ** is a custom indicator designed to integrate multiple dimensions of market momentum into a single, visual framework. Rather than relying on generic oscillators, this tool brings together stochastic calculations, price mapping, velocity measurement, and dynamic visual feedback to offer a layered view of market conditions.
#### Key Features and Components
- **Stochastic Calculations Mapped to Price Levels**
The indicator starts by computing the traditional stochastic oscillator values—%K, %D, and %J—over a user-defined period. These values are then mapped to the current price range. This mapping is achieved via a dedicated function that uses an exponential moving average and a rounding option, thereby linking momentum metrics directly with price dynamics.
- **Momentum Velocity and Its RSI**
To quantify the rate of change, the script calculates a “velocity” by measuring the difference in the price-mapped stochastic values over a specified lookback period. The resulting velocity values are then processed through a Relative Strength Index (RSI) calculation. This additional layer helps to provide a clearer picture of how rapidly market momentum is changing.
- **Triangle Area Measurement as a Volatility Proxy**
For each of the K, D, and J series, the indicator identifies the highest and lowest values within a user-specified lookback window and constructs triangles by connecting these extremes with the current value. The area of these triangles is computed, serving as an abstract measure of volatility and the range of price momentum. These areas are displayed alongside the velocity readings in an on-chart table for easy reference.
- **Dynamic Interpretation Label**
The tool also generates a concise reading in English that summarizes the relationships among the areas and velocity values. For example, it notes when one series, such as J, exhibits both the largest triangle area and the highest velocity. In such cases—suggesting an extended move or potential overextension—the label’s text color changes (to red) to visually alert the trader to an increased likelihood of a reversal. This approach allows traders to quickly assimilate the indicator’s data without overwhelming them with subjective language.
- **Additional Visual Elements**
Beyond the core calculations, the indicator includes a “momentum box” that captures the range of the stochastic-derived values over recent bars, as well as radial lines that provide a visual connection from the box’s reference point to current values. These elements together offer a structured, multi-faceted view of market dynamics.
#### Significance and Effects
This indicator takes a measured approach to integrating multiple aspects of market analysis. By combining price-based mapping with traditional stochastic and momentum measurements, it provides traders with:
- **A structured framework** to assess market range and momentum changes.
- **Visual cues** (such as the dynamic label and color changes) that highlight conditions warranting closer attention.
- **Tangible, calculated metrics**—triangle areas and velocity RSIs—that may assist in identifying potential reversal points.
Stochastic Momentum Triangles is intended to serve as a supplementary tool for traders who appreciate a quantitative perspective on market behavior. Its design focuses on clear, measurable outputs rather than relying on broad claims, allowing for a calm and thoughtful evaluation of market conditions.
Adaptive RSI with Real-Time Divergence [AIBitcoinTrend]👽 Adaptive RSI Trailing Stop (AIBitcoinTrend)
The Adaptive RSI Trailing Stop is an indicator that integrates Gaussian-weighted RSI calculations with real-time divergence detection and a dynamic ATR-based trailing stop. This advanced approach allows traders to monitor momentum shifts, identify divergences early, and manage risk with adaptive trailing stop levels that adjust to price action.
👽 What Makes the Adaptive RSI with Signals and Trailing Stop Unique?
Unlike traditional RSI indicators, this version applies a Gaussian-weighted smoothing algorithm, making it more responsive to price action while reducing noise. Additionally, the trailing stop feature dynamically adjusts based on volatility and trend conditions, allowing traders to:
Detects real-time divergences (bullish/bearish) with a smart pivot-based system.
Filter noise with Gaussian weighting, ensuring smoother RSI transitions.
Utilize crossover-based trailing stop activation, for systematic trade management.
👽 The Math Behind the Indicator
👾 Gaussian Weighted RSI Calculation
Traditional RSI calculations rely on simple averages of gains and losses. Instead, this indicator weights recent price changes using a Gaussian distribution, prioritizing more relevant data points while maintaining smooth transitions.
Key Features:
Exponential decay ensures recent price changes are weighted more heavily.
Reduces short-term noise while maintaining responsiveness.
👾 Real-Time Divergence Detection
The indicator detects bullish and bearish divergences using pivot points on RSI compared to price action.
👾 Dynamic ATR-Based Trailing Stop
Bullish Trailing Stop: Activates when RSI crosses above 20 and dynamically adjusts based on low - ATR multiplier.
Bearish Trailing Stop: Activates when RSI crosses below 80 and adjusts based on high + ATR multiplier
This allows traders to:
Lock in profits systematically by adjusting stop-losses dynamically.
Stay in trades longer while maintaining adaptive risk management.
👽 How It Adapts to Market Movements
✔️ Gaussian Filtering ensures smooth RSI transitions while preventing excessive lag.
✔️ Real-Time Divergence Alerts provide early trade signals based on price-RSI discrepancies.
✔️ ATR Trailing Stop dynamically expands or contracts based on market volatility.
✔️ Crossover-Based Activation enables the stop-loss system only when RSI confirms a momentum shift.
👽 How Traders Can Use This Indicator
👾 Divergence Trading
Traders can use real-time divergence detection to anticipate reversals before they happen.
Bullish Divergence Setup:
Look for RSI making a higher low, while price makes a lower low.
Enter long when RSI confirms upward momentum.
Bearish Divergence Setup:
Look for RSI making a lower high, while price makes a higher high.
Enter short when RSI confirms downward momentum.
👾 Trailing Stop Signals
Bullish Signal and Trailing Stop Activation:
When RSI crosses above 20, a trailing stop is placed using low - ATR multiplier.
If price crosses below the stop, it exits the trade and removes the stop.
Bearish Signal and Trailing Stop Activation:
When RSI crosses below 80, a trailing stop is placed using high + ATR multiplier.
If price crosses above the stop, it exits the trade and removes the stop.
This makes trend-following strategies more efficient, while ensuring proper risk management.
👽 Why It’s Useful for Traders
✔️ Dynamic and Adaptive: Adjusts to changing market conditions automatically.
✔️ Noise Reduction: Gaussian-weighted RSI reduces short-term price distortions.
✔️ Comprehensive Strategy Tool: Combines momentum detection, divergence analysis, and automated risk management into a single indicator.
✔️ Works Across Markets & Timeframes: Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
RSI Length: Defines the lookback period for RSI smoothing.
Gaussian Sigma: Controls how much weight is given to recent data points.
Enable Signal Line: Option to display an RSI-based moving average.
Divergence Lookback: Configures how far back pivot points are detected.
Crossover/crossunder values for signals: Set the crossover/crossunder values that triggers signals.
ATR Multiplier: Adjusts trailing stop sensitivity to market volatility.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Weighted Relative Strength Index [SeerQuant]Weighted Relative Strength Index (WRSI)
The Weighted Relative Strength Index (WRSI) is an advanced momentum oscillator that enhances the traditional RSI by incorporating customizable weighting methods and moving average smoothing. With dynamic threshold logic, color-coded visuals, and optional candle coloring, the WRSI provides traders with a versatile tool for identifying trends, overbought/oversold conditions, and momentum shifts.
⚙️ How It Works
1. Weighted Momentum Calculation
The indicator calculates price changes (delta) and applies a user-defined weighting method (e.g., Volume, Momentum, Volatility, or Reversion Factor) to emphasize specific market dynamics.
2. Custom Moving Average Integration
Weighted upward and downward price movements are smoothed using a selectable moving average type (e.g., SMA, EMA, TEMA, etc.), producing a weighted RSI that blends momentum and trend data.
3. Smoothed RSI Output
An additional moving average is applied to the weighted RSI for a smoothed version, offering a clearer view of momentum trends.
4. Threshold Logic
Bullish (Uptrend): WRSI exceeds the upper neutral zone boundary (50 + Neutral Zone).
Bearish (Downtrend): WRSI falls below the lower neutral zone boundary (50 - Neutral Zone).
Neutral: WRSI remains within the neutral zone.
Extreme overbought (90+) and oversold (20-) levels are marked with X’s for quick identification.
5. Dynamic Visual Representation
A color-coded line reflects the WRSI, adjusting hues based on trend direction.
Gradient fills highlight overbought/oversold zones and neutral areas.
Optional candle coloring ties price action to WRSI or smoothed RSI values.
A histogram-style fill between the WRSI and midline enhances trend strength visibility.
✨ Customizable Settings
Calculation Settings:
Calculation Source: Select the price source (default: close).
Calculation Length: Set the lookback period for RSI calculation (default: 14).
Moving Average Type: Choose from SMA, EMA, RMA, WMA, VWMA, LSMA, HMA, ALMA, DEMA, or TEMA (default: RMA).
Moving Average Length: Adjust the smoothing period for the weighted RSI (default: 8).
Neutral Zone Range: Define the width of the neutral zone around the midline (default: 5).
RSI Weighting Method:
Volume: Weights by trading volume.
Momentum: Weights by absolute price momentum.
Volatility: Weights by standard deviation.
Reversion Factor: Weights inversely to variance for mean-reversion emphasis (default: Momentum).
Style Settings:
Colour Choice: Pick from predefined schemes: Default, Modern, Cool, or Monochrome (default: Default).
Use Custom Colors?: Toggle to use custom bull, bear, and neutral colors (default: false).
Bull/Bear/Neutral Colors: Set custom colors when enabled (default: green/red/gray).
Candle Color Mode: Color candles based on WRSI or smoothed RSI (default: RSI).
Color Candles?: Enable/disable candle coloring (default: false).
🚀 Features and Benefits
Weighted Momentum Analysis: Enhances RSI with dynamic weighting for deeper market insights.
Flexible Smoothing: Multiple MA types and adjustable lengths adapt to various trading styles.
Visual Intuition: Color-coded outputs, gradient fills, and optional candle coloring simplify trend analysis.
Customizable Thresholds: Neutral zone and extreme levels cater to individual strategies.
Overbought/Oversold Signals: Clear markers for extreme conditions improve decision-making.
📜 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always consult a licensed financial advisor before making trading decisions. Use at your own risk.
Strategy SuperTrend SDI WebhookThis Pine Script™ strategy is designed for automated trading in TradingView. It combines the SuperTrend indicator and Smoothed Directional Indicator (SDI) to generate buy and sell signals, with additional risk management features like stop loss, take profit, and trailing stop. The script also includes settings for leverage trading, equity-based position sizing, and webhook integration.
Key Features
1. Date-based Trade Execution
The strategy is active only between the start and end dates set by the user.
times ensures that trades occur only within this predefined time range.
2. Position Sizing and Leverage
Uses leverage trading to adjust position size dynamically based on initial equity.
The user can set leverage (leverage) and percentage of equity (usdprcnt).
The position size is calculated dynamically (initial_capital) based on account performance.
3. Take Profit, Stop Loss, and Trailing Stop
Take Profit (tp): Defines the target profit percentage.
Stop Loss (sl): Defines the maximum allowable loss per trade.
Trailing Stop (tr): Adjusts dynamically based on trade performance to lock in profits.
4. SuperTrend Indicator
SuperTrend (ta.supertrend) is used to determine the market trend.
If the price is above the SuperTrend line, it indicates an uptrend (bullish).
If the price is below the SuperTrend line, it signals a downtrend (bearish).
Plots visual indicators (green/red lines and circles) to show trend changes.
5. Smoothed Directional Indicator (SDI)
SDI helps to identify trend strength and momentum.
It calculates +DI (bullish strength) and -DI (bearish strength).
If +DI is higher than -DI, the market is considered bullish.
If -DI is higher than +DI, the market is considered bearish.
The background color changes based on the SDI signal.
6. Buy & Sell Conditions
Long Entry (Buy) Conditions:
SDI confirms an uptrend (+DI > -DI).
SuperTrend confirms an uptrend (price crosses above the SuperTrend line).
Short Entry (Sell) Conditions:
SDI confirms a downtrend (+DI < -DI).
SuperTrend confirms a downtrend (price crosses below the SuperTrend line).
Optionally, trades can be filtered using crossovers (occrs option).
7. Trade Execution and Exits
Market entries:
Long (strategy.entry("Long")) when conditions match.
Short (strategy.entry("Short")) when bearish conditions are met.
Trade exits:
Uses predefined take profit, stop loss, and trailing stop levels.
Positions are closed if the strategy is out of the valid time range.
Usage
Automated Trading Strategy:
Can be integrated with webhooks for automated execution on supported trading platforms.
Trend-Following Strategy:
Uses SuperTrend & SDI to identify trend direction and strength.
Risk-Managed Leverage Trading:
Supports position sizing, stop losses, and trailing stops.
Backtesting & Optimization:
Can be used for historical performance analysis before deploying live.
Conclusion
This strategy is suitable for traders who want to automate their trading using SuperTrend and SDI indicators. It incorporates risk management tools like stop loss, take profit, and trailing stop, making it adaptable for leverage trading. Traders can customize settings, conduct backtests, and integrate it with webhooks for real-time trade execution. 🚀
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
AntoQQE - HistogramThis script displays a QQE-based momentum histogram, derived from the RSI line’s deviation around a neutral 50 level. It uses a smoothed RSI, monitors volatility with a dynamically adjusted multiplier, and then plots a color-coded histogram that helps traders see when the RSI is entering strong bullish or bearish territory:
• Smoothed RSI Calculation
The script calculates RSI for a user-defined period and then smooths it with an EMA. This reduces noise in the indicator’s readings.
• Dynamic Average Range (DAR)
The script computes volatility by taking the absolute change of the smoothed RSI, applying two EMAs, and multiplying by a QQE factor. This produces a band around the RSI that adapts to changes in market volatility.
• Histogram Centering and Thresholds
Rather than plotting the RSI itself, the script subtracts 50 from the RSI to center it around zero. Columns are plotted for each bar:
Blue when momentum is significantly above zero (over a threshold value).
Red when momentum is significantly below zero (under a negative threshold).
Gray when momentum is within a neutral range.
• Usage
By observing when columns turn blue or red—and how far they extend above or below zero—traders can quickly gauge the market’s momentum. The horizontal threshold lines (dashed by default) provide clear breakout levels for bullish or bearish conditions, which can help confirm entries or exits based on shifting market sentiment. It is best paired with the AntoQQE - Bars indicator for better chart visualization.
AntoQQE - BarsThis script is a variation on the QQE (Quantitative Qualitative Estimation) concept applied to RSI. It calculates a smoothed RSI line, then determines a “Dynamic Average Range” around that line. By tracking the RSI’s movement relative to these upper (shortBand) and lower (longBand) levels, it determines when price momentum shifts enough to suggest a possible trend flip. The script plots color-coded candles based on these momentum conditions:
• RSI Calculation and Smoothing
An RSI value is obtained over a specified period, then smoothed by an EMA. This smoothed RSI serves as the core measure of momentum.
• Dynamic Average Range (DAR)
The script computes the volatility of the smoothed RSI using two EMAs of its bar-to-bar movements. It multiplies this volatility factor by a QQE multiplier to create upper and lower bands that adapt to changes in RSI volatility.
• Trend Flips
When the smoothed RSI crosses above or below its previous band level (shortBand or longBand), the script interprets this as a shift in momentum and sets a trend state accordingly (long or short).
• Candle Coloring
Finally, the script colors each candle according to how far the smoothed RSI is from a neutral baseline of 50:
Candles turn green when the RSI is sufficiently above 50, suggesting bullish momentum.
Candles turn red when the RSI is sufficiently below 50, indicating bearish momentum.
Candles turn orange when they are near the 50 level, reflecting a more neutral or transitional phase.
Traders can use these colored candles to quickly see when the RSI’s momentum has moved into overbought/oversold zones—or is shifting between bullish and bearish conditions—without needing to consult a separate oscillator window. The adaptive nature of the band calculations can help in spotting significant shifts in market sentiment and volatility.
