Linear % ST | QuantEdgeB🚀 Introducing Linear Percentile SuperTrend (Linear % ST) by QuantEdgeB
🛠️ Overview
Linear % SuperTrend (Linear % ST) by QuantEdgeB is a hybrid trend-following indicator that combines Linear Regression, Percentile Filters, and Volatility-Based SuperTrend Logic into one dynamic tool. This system is designed to identify trend shifts early while filtering out noise during choppy market conditions.
By utilizing percentile-based median smoothing and customized ATR multipliers, this tool captures both breakout momentum and pullback opportunities with precision.
✨ Key Features
🔹 Percentile-Based Median Filtering
Removes outliers and normalizes price movement for cleaner trend detection using the 50th percentile (median) of recent price action.
🔹 Linear Regression Smoothing
A smoothed baseline is computed with Linear Regression to detect the underlying trend while minimizing lag.
🔹 SuperTrend Structure with Adaptive Bands
The indicator implements an enhanced SuperTrend engine with custom ATR bands that adapt to trend direction. Bands tighten or loosen based on volatility and trend strength.
🔹 Dynamic Long/Short Conditions
Long and short signals are derived from the relationship between price and the SuperTrend threshold zones, clearly showing trend direction with optional "Long"/"Short" labels on the chart.
🔹 Multiple Visual Themes
Select from 6 built-in color palettes including Strategy, Solar, Warm, Cool, Classic, and Magic to match your personal style or strategy layout.
📊 How It Works
1️⃣ Percentile Filtering
The source price (default: close) is filtered using a nearest-rank 50th percentile over a custom lookback. This normalizes data to reflect the central tendency and removes noisy extremes.
2️⃣ Linear Regression Trend Base
A Linear Regression Moving Average (LSMA) is applied to the filtered median, forming the core trend line. This dynamic trendline provides a low-lag yet smooth view of market direction.
3️⃣ SuperTrend Engine
ATR is applied with custom multipliers (different for long and short) to create dynamic bands. The bands react to price movement and only shift direction after confirmation, preventing false flips.
4️⃣ Trend Signal Logic
• When price stays above the dynamic lower band → Bullish trend
• When price breaks below the upper band → Bearish trend
• Trend direction remains stable until violated by price.
⚙️ Custom Settings
• Percentile Length → Lookback for percentile smoothing (default: 35)
• LSMA Length → Determines the base trend via linear regression (default: 24)
• ATR Length → ATR period used in dynamic bands (default: 14)
• Long Multiplier → ATR multiplier for bullish thresholds (default: 0.8)
• Short Multiplier → ATR multiplier for bearish thresholds (default: 1.9)
✅ How to Use
1️⃣ Trend-Following Strategy
✔️ Go Long when price breaks above the lower ATR band, initiating an upward trend
✔️ Go Short when price falls below the upper ATR band, confirming bearish conditions
✔️ Remain in trend direction until the SuperTrend flips
2️⃣ Visual Confirmation
✔️ Use bar coloring and the dynamic bands to stay aligned with trend direction
✔️ Optional Long/Short labels highlight key signal flips
👥 Who Should Use Linear % ST?
✅ Swing & Position Traders → To ride trends confidently
✅ Trend Followers → As a primary directional filter
✅ Breakout Traders → For clean signal generation post-range break
✅ Quant/Systematic Traders → Integrate clean trend logic into algorithmic setups
📌 Conclusion
Linear % ST by QuantEdgeB blends percentile smoothing with linear regression and volatility bands to deliver a powerful, adaptive trend-following engine. Whether you're a discretionary trader seeking cleaner entries or a systems-based trader building logic for automation, Linear % ST offers clarity, adaptability, and precision in trend detection.
🔹 Key Takeaways:
1️⃣ Percentile + Regression = Noise-Reduced Core Trend
2️⃣ ATR-Based SuperTrend = Reliable Breakout Confirmation
3️⃣ Flexible Parameters + Color Modes = Custom Fit for Any Strategy
📈 Use it to spot emerging trends, filter false signals, and stay confidently aligned with market momentum.
📌 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.
Indicadores e estratégias
Filtered QQE + EMA + Supertrend (Alternating Signals)used qqe mod + supertrend + 20 ema to build perfectly working script.
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB
🛠️ Overview
Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions.
Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes.
✨ Key Features
🔹 Trend Following with Adaptive Sensitivity
The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum.
🔹 Volatility-Adjusted Filtering
The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility.
🔹 Clear Signal Generation
QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals.
🔹 Customizable Visual & Signal Settings
With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments.
📊 How It Works
1️⃣ DEMA Calculation
DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise.
2️⃣ SuperTrend with Percentile Filtering
The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data:
• Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier)
• Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier)
These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction.
3️⃣ Signal Generation
• Long Signal: Triggered when price crosses below the SuperTrend Lower Band
• Short Signal: Triggered when price crosses above the SuperTrend Upper Band
The indicator provides signals with corresponding trend direction based on these crossovers.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style.
• 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered.
• 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias.
👥 Who Should Use QDT?
✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets.
✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns.
✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods.
✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering.
⚙️ Customization & Default Settings
- DEMA Length(30): Controls the lookback period for DEMA calculation
- Percentile Length(10): Sets the lookback period for percentile filtering
- ATR Length(14): Defines the length for calculating ATR (used in SuperTrend)
- ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation
- SuperTrend Length(30):Defines the length for SuperTrend calculations
📌 How to Use QDT in Trading
1️⃣ Trend-Following Strategy
✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band).
✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band).
✔ Hold positions as long as QDT continues to provide the same direction.
2️⃣ Reversal Strategy
✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion.
3️⃣ Volatility-Driven Entries
✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets.
🧠 Why It Works
QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments.
🔹 Conclusion
The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points.
🔹 Key Takeaways:
1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection
2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic
3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation
📌 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.
Buy Sell CandleThis indicator is designed to detect BUY and SELL signals based on a price breakout pattern formed by two key historical candles.
1. How It Works
The indicator identifies two key candles to generate trading signals:
Candle #2: Always the 3rd candle from the current bar (offset = 3).
Candle #1: Searched within 4–8 bars before Candle #2.
BUY Signal Conditions:
✅ Condition 1: Candle #1 must have a higher High than Candle #2.
✅ Condition 2: The current closing price (Candle #5) must break above Candle #1’s High.
SELL Signal Conditions:
✅ Condition 1: Candle #1 must have a lower Low than Candle #2.
✅ Condition 2: The current closing price (Candle #5) must break below Candle #1’s Low.
2. Visual Representation on Chart
"BUY" arrow (green): Appears below Candle #2 when buy conditions are met.
"SELL" arrow (red): Appears above Candle #2 when sell conditions are met.
Alerts: Automatically triggers notifications when signals appear.
3. Strengths of the Indicator
✔ Simple & intuitive: Uses only price action (High, Low, Close).
✔ No repainting: Signals remain fixed once formed.
✔ Effective for breakout trading: Captures strong momentum moves.
4. Limitations & Considerations
⚠ No trend filter: May produce false signals in sideways markets.
⚠ No risk management: Should be combined with stop-loss/take-profit.
⚠ Best suited for H1+ timeframes to reduce noise.
5. Practical Applications
Trend following: Combine with MA/EMA for trend confirmation.
Breakout trading: Enter trades when key levels are breached.
Confirmation tool: Use alongside RSI, MACD for stronger signals.
👉 Recommendation: Backtest on multiple markets (forex, crypto, stocks) for optimization.
HILO Interpolation | QuantEdgeB🚀 Introducing HILO Interpolation by QuantEdgeB
🛠️ Overview
HILO Interpolation is a dynamic price-action based signal engine crafted to adapt across trending and ranging conditions. By leveraging percentile-based price band interpolation, it identifies high-confidence breakout and breakdown zones. This indicator is designed to serve both as a momentum trigger in trend phases and as a price-reactive entry system during range-bound consolidation.
By intelligently switching between percentile thresholds and interpolated logic, HILO minimizes noise and whipsaws commonly seen in traditional crossover systems.
✨ Key Features
🔹 Percentile Interpolation Engine
Tracks price breakouts using percentile thresholds, making it adaptable to volatility and asset-specific structure.
🔹 Price-Based Signal Confirmation
Signals are only triggered when price meaningfully crosses through key percentile thresholds (based on historical high/low logic).
🔹 Visual Trend Encoding
Color-coded candles, dynamic interpolation bands, and optional long/cash labels give clear visual cues for trend and trade direction.
🔹 Dynamic Threshold Switching
Interpolated threshold flips based on where price sits relative to percentile bands—providing adaptive long/short logic.
📊 How It Works
1️⃣ Percentile Zone Definition
HILO defines two key percentiles from the historical high and low:
• Upper Threshold: 75th Percentile of Highs
• Lower Threshold: 50th Percentile of Lows
These are calculated using linear interpolation to ensure smoother transitions across lookback periods.
2️⃣ Adaptive Signal Line
Instead of using static crossovers, HILO dynamically flips its signal based on whether price exceeds the upper threshold or falls below the lower one.
📌 If price > upper → Signal = Short threshold
📌 If price < lower → Signal = Long threshold
📌 If price remains between thresholds → no flip (trend continuation)
3️⃣ Signal Logic
✅ Long Signal → Price exceeds upper bound while lower bound acts as ceiling
❌ Short Signal → Price breaks below lower percentile while upper bound flips
This simple yet powerful mechanism creates early entries while maintaining high signal confidence.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Strategy, Solar, Warm, Cool, Classic, Magic
• 🔄 Dynamic Candle & Band Coloring
• 🏷️ Signal Labels: Optional “𝓛𝓸𝓷𝓰” and “𝓢𝓱𝓸𝓻𝓽” tags when trend flips
• 💬 Alerts Ready: Long/Short crossover conditions can trigger alerts instantly
👥 Who Should Use HILO?
✅ Breakout Traders – Catch early trend starts using percentile filters
✅ Swing Traders – Identify directional bias shifts in advance
✅ Range Strategists – Use band confluence zones to play reversions
✅ Quant & Rule-Based Traders – Incorporate percentile logic into broader systems
⚙️ Customization & Default Settings
Percentile Length:(Default 35) Lookback for calculating percentile thresholds
Lookback Period:(Default 4) Lag factor for interpolation responsiveness
Upper % Threshold: (Default 75) Defines breakout zone from historical highs
Lower % Threshold: (Default 50) Defines retest/accumulation zone from historical lows
📌 How to Use HILO in Trading
1️⃣ Trend-Following Strategy
✔ Enter long when price flips above the adaptive support line
✔ Exit or go short when price breaks below the interpolated resistance
✔ Continue position as long as trend color persists
2️⃣ Range-Reversion Strategy
✔ Buy when price tests the lower threshold and no short signal is triggered
✔ Sell or reduce when price hits the upper range boundary
🧠 Why It Works
HILO operates on the principle that historical price structure creates natural probabilistic thresholds. By interpolating between these using percentile logic, the system maintains adaptability to changing market conditions—without the lag of moving averages or the noise of fixed bands.
🔹 Conclusion
HILO Interpolation is a minimalist yet powerful signal engine built for adaptive breakout and reversion detection. Its percentile-based logic offers a novel way to identify structure shifts, giving traders an edge in both trend and range markets.
🔹 Key Takeaways:
1️⃣ Breakout Entry Logic – Uses percentile interpolation instead of static bands
2️⃣ Color-Driven Clarity – Visual clarity via gradient zone overlays
3️⃣ Trend Integrity – Avoids overfitting and responds only to significant price movements
📌 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.
Normalized MACD with RSI & Stoch RSI + SignalsNormalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
Here’s a clear and concise description of your updated Pine Script indicator:
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Normalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
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Key Components:
① MACD (Normalized):
• The Moving Average Convergence Divergence (MACD) originally has an unlimited numerical range.
• Normalization Method:
• Uses a custom tanh(x) function implemented directly in Pine Script:
\tanh(x) = \frac{e^{x}-e^{-x}}{e^{x}+e^{-x}}
• MACD values are scaled using this method to a range of 0–100, with the neutral line at exactly 50.
• Interpretation:
• Values above 50 indicate bullish momentum.
• Values below 50 indicate bearish momentum.
② RSI (Relative Strength Index):
• Measures market momentum on a 0–100 scale.
• Traditional RSI interpretation:
• Overbought conditions: RSI > 70–80.
• Oversold conditions: RSI < 30–20.
③ Stochastic RSI:
• Combines RSI and Stochastic Oscillator to give short-term, highly sensitive signals.
• Helps identify immediate market extremes:
• Above 80 → Short-term overbought.
• Below 20 → Short-term oversold.
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How the Indicator Works:
• Visualization:
• All three indicators (Normalized MACD, RSI, Stochastic RSI) share the same 0–100 scale.
• Clear visual lines and reference levels:
• Midline at 50 indicates neutral momentum.
• Dashed lines at 20 and 80 clearly mark oversold/overbought zones.
• Trading Signals (Recommended approach):
• Bullish Signal (Potential Buy):
• Normalized MACD crosses above 50.
• RSI below or approaching oversold zone (below 30–20).
• Stochastic RSI below 20, indicating short-term oversold conditions.
• Bearish Signal (Potential Sell):
• Normalized MACD crosses below 50.
• RSI above or approaching overbought zone (above 70–80).
• Stochastic RSI above 80, indicating short-term overbought conditions.
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Why Use This Indicator?
• Harmonized Signals:
Normalization of MACD significantly improves clarity and comparability with RSI and Stochastic RSI, providing a unified momentum picture.
• Intuitive Analysis:
Traders can rapidly and intuitively identify momentum shifts without needing multiple indicator windows.
• Improved Decision-Making:
Clear visual references and signals help reduce subjective interpretation, potentially improving trading outcomes.
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Suggested Usage:
• Combine with traditional support
Z-Score Normalized Volatility IndicesVolatility is one of the most important measures in financial markets, reflecting the extent of variation in asset prices over time. It is commonly viewed as a risk indicator, with higher volatility signifying greater uncertainty and potential for price swings, which can affect investment decisions. Understanding volatility and its dynamics is crucial for risk management and forecasting in both traditional and alternative asset classes.
Z-Score Normalization in Volatility Analysis
The Z-score is a statistical tool that quantifies how many standard deviations a given data point is from the mean of the dataset. It is calculated as:
Z = \frac{X - \mu}{\sigma}
Where X is the value of the data point, \mu is the mean of the dataset, and \sigma is the standard deviation of the dataset. In the context of volatility indices, the Z-score allows for the normalization of these values, enabling their comparison regardless of the original scale. This is particularly useful when analyzing volatility across multiple assets or asset classes.
This script utilizes the Z-score to normalize various volatility indices:
1. VIX (CBOE Volatility Index): A widely used indicator that measures the implied volatility of S&P 500 options. It is considered a barometer of market fear and uncertainty (Whaley, 2000).
2. VIX3M: Represents the 3-month implied volatility of the S&P 500 options, providing insight into medium-term volatility expectations.
3. VIX9D: The implied volatility for a 9-day S&P 500 options contract, which reflects short-term volatility expectations.
4. VVIX: The volatility of the VIX itself, which measures the uncertainty in the expectations of future volatility.
5. VXN: The Nasdaq-100 volatility index, representing implied volatility in the Nasdaq-100 options.
6. RVX: The Russell 2000 volatility index, tracking the implied volatility of options on the Russell 2000 Index.
7. VXD: Volatility for the Dow Jones Industrial Average.
8. MOVE: The implied volatility index for U.S. Treasury bonds, offering insight into expectations for interest rate volatility.
9. BVIX: Volatility of Bitcoin options, a useful indicator for understanding the risk in the cryptocurrency market.
10. GVZ: Volatility index for gold futures, reflecting the risk perception of gold prices.
11. OVX: Measures implied volatility for crude oil futures.
Volatility Clustering and Z-Score
The concept of volatility clustering—where high volatility tends to be followed by more high volatility—is well documented in financial literature. This phenomenon is fundamental in volatility modeling and highlights the persistence of periods of heightened market uncertainty (Bollerslev, 1986).
Moreover, studies by Andersen et al. (2012) explore how implied volatility indices, like the VIX, serve as predictors for future realized volatility, underlining the relationship between expected volatility and actual market behavior. The Z-score normalization process helps in making volatility data comparable across different asset classes, enabling more effective decision-making in volatility-based strategies.
Applications in Trading and Risk Management
By using Z-score normalization, traders can more easily assess deviations from the mean in volatility, helping to identify periods when volatility is unusually high or low. This can be used to adjust risk exposure or to implement volatility-based trading strategies, such as mean reversion strategies. Research suggests that volatility mean-reversion is a reliable pattern that can be exploited for profit (Christensen & Prabhala, 1998).
References:
• Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2012). Realized volatility and correlation dynamics: A long-run approach. Journal of Financial Economics, 104(3), 385-406.
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christensen, B. J., & Prabhala, N. R. (1998). The relation between implied and realized volatility. Journal of Financial Economics, 50(2), 125-150.
• Whaley, R. E. (2000). Derivatives on market volatility and the VIX index. Journal of Derivatives, 8(1), 71-84.
NEW Non-Directional Market StrategyFinal New Non Directional Trading Strategy! which can be used for all markets , the candles will turn grey during the choppy conditions.
WaveTrend + Multi-Timeframe AlertsThe WaveTrend SwipeUP Indicator is designed to provide clear buy and sell signals based on multi-timeframe analysis and dynamic support levels. This indicator combines WaveTrend calculations on 4-hour and 8-hour timeframes with a Lips line check on the daily timeframe to generate precise trading signals.
Main Components:
WaveTrend Calculation: Uses exponential moving average and absolute deviation to calculate the WaveTrend index (WT1) on 4-hour and 8-hour timeframes.
Lips Line: Calculates a simple moving average (SMA) of the closing price over a period of 280 days to determine the Lips line on the daily timeframe.
Overbought and Oversold Conditions: Checks if WT1 on 4-hour and 8-hour timeframes exceeds overbought levels (65) or falls below oversold levels (-65).
Price Position Relative to Lips Line: Checks if the closing price is above or below the Lips line on the daily timeframe.
Dynamic Support: Calculates a simple moving average of the low prices over a period of 50 to identify potential support levels.
Trading Signals:
Buy Signal: A green triangle appears below the bar when the indicator detects oversold conditions on both 4-hour and 8-hour timeframes, and the price is above the Lips line on the daily timeframe.
Sell Signal: A red triangle appears above the bar when the indicator detects overbought conditions on both 4-hour and 8-hour timeframes, and the price is below the Lips line on the daily timeframe.
Multi-Timeframe Alerts:
The WaveTrend SwipeUP Indicator includes an alert condition that combines buy and sell signals based on multi-timeframe analysis. Alerts are generated when the following conditions occur:
Buy Signal: When WT1 on 4-hour and 8-hour timeframes is below the oversold level (-65) and the closing price is above the Lips line on the daily timeframe.
Sell Signal: When WT1 on 4-hour and 8-hour timeframes is above the overbought level (65) and the closing price is below the Lips line on the daily timeframe.
These alerts can be configured to send notifications when trading signals are generated, allowing users to monitor buy and sell opportunities in real-time.
Majors Rotation System | OpusMajor Rotation System | Opus
Key Features ✨
The Major Rotation System (MRS) is a cutting-edge tool designed to dynamically optimize capital allocation across three leading cryptocurrencies:
Bitcoin
Ethereum
Solana
While seamlessly adapting to shifting market conditions. Harnessing advanced quantitative techniques, MRS integrates momentum analysis, trend-following strategies, and robust statistical processing to deliver precise portfolio adjustments.
Its sleek, user-friendly interface provides crystal-clear signals, empowering traders to make swift, informed decisions in fast-paced, high-frequency trading environments.
Methodology 🧠
MRS employs a sophisticated rotation strategy, reallocating capital among BTC, ETH, and SOL based on proven quantitative frameworks, with a core focus on momentum and relative strength analysis.
Momentum Analysis : This measures the speed and persistence of price movements over a defined lookback period, identifying which asset—BTC, ETH, or SOL—is exhibiting the strongest upward trajectory. MRS leverages this to prioritize assets with sustained price acceleration, filtering out noise to capture high-probability trends.
Relative Strength Analysis : This compares the performance of BTC, ETH, and SOL against each other, pinpointing the asset outperforming its peers in terms of price appreciation. By ranking their strength dynamically, MRS ensures capital flows to the leader while avoiding laggards.
The system continuously evaluates these metrics to signal optimal entry and exit points, indicating when to shift into cash or concentrate holdings in a single asset. This adaptive approach aims to sidestep significant drawdowns while outperforming traditional Buy-and-Hold strategies, offering a proactive shield against volatility and a pathway to superior returns.
Metrics and Equity 📊
Performance is the heartbeat of MRS, tracked through three powerful metrics:
Sharpe Ratio : This measures how much return you’re getting for the risk you’re taking. A higher Sharpe Ratio means better rewards without excessive ups and downs—think of it as your “bang for your buck” in trading.
Sortino Ratio : Unlike Sharpe, this focuses only on downside risk—those painful losses you want to avoid. A strong Sortino Ratio shows MRS is protecting your portfolio from the worst drops while still chasing gains.
Omega Ratio : This looks at the balance of wins versus losses, weighting the likelihood of profits against setbacks. A higher Omega Ratio signals that MRS is tilting the odds in your favor over time.
The system dynamically generates dual equity curves—comparing MRS performance against a Buy-and-Hold benchmark—ensuring transparency and reliability without the pitfalls of repainting. These metrics give traders—novice or pro—a clear, trustworthy view of how MRS performs.
Applications 💻
Tailored for discerning traders, the Major Rotation System is a precision instrument built for today’s volatile markets. With its asset-specific equity curve filter, reimagined momentum analysis, and streamlined UI, MRS is engineered to amplify gains during bull markets while prioritizing risk-adjusted performance.
Its high-resolution data processing and adaptive reallocation capabilities make it an ideal companion for capturing premium trends in blue-chip cryptocurrencies, regardless of market tempo. Whether navigating explosive rallies or choppy waters, MRS equips traders with the agility and insight to thrive.
Disclaimer ⚠️
The Major Rotation System (MRS) is a tool designed to assist traders in analyzing market trends and is not intended as financial advice. Trading and investing involve significant risks, including the potential loss of capital.
Past performance is not indicative of future results. Users should conduct their own research, assess their risk tolerance, and make independent investment decisions. The creators of MRS are not responsible for any financial outcomes resulting from its use.
Reversal Trading Bot Strategy[BullByte]Overview :
The indicator Reversal Trading Bot Strategy is crafted to capture potential market reversal points by combining momentum, volatility, and trend alignment filters. It uses a blend of technical indicators to identify both bullish and bearish reversal setups, ensuring that multiple market conditions are met before entering a trade.
Core Components :
Technical Indicators Used :
RSI (Relative Strength Index) :
Purpose : Detects divergence conditions by comparing recent lows/highs in price with the RSI.
Parameter : Length of 8.
Bollinger Bands (BB) :
Purpose : Measures volatility and identifies price levels that are statistically extreme.
Parameter : Length of 20 and a 2-standard deviation multiplier.
ADX (Average Directional Index) & DMI (Directional Movement Index) :
Purpose : Quantifies the strength of the trend. The ADX threshold is set at 20, and additional filters check for the alignment of the directional indicators (DI+ and DI–).
ATR (Average True Range) :
Purpose : Provides a volatility measure used to set stop levels and determine risk through trailing stops.
Volume SMA (Simple Moving Average of Volume ):
Purpose : Helps confirm strength by comparing the current volume against a 20-period average, with an optional filter to ensure volume is at least twice the SMA.
User-Defined Toggle Filters :
Volume Filter : Confirms that the volume is above average (or twice the SMA) before taking trades.
ADX Trend Alignment Filter : Checks that the ADX’s directional indicators support the trade direction.
BB Close Confirmation : Optionally refines the entry by requiring price to be beyond the upper or lower Bollinger Band rather than just above or below.
RSI Divergence Exit : Allows the script to close positions if RSI divergence is detected.
BB Mean Reversion Exit : Closes positions if the price reverts to the Bollinger Bands’ middle line.
Risk/Reward Filter : Ensures that the potential reward is at least twice the risk by comparing the distance to the Bollinger Band with the ATR.
Candle Movement Filter : Optional filter to require a minimum percentage move in the candle to confirm momentum.
ADX Trend Exit : Closes positions if the ADX falls below the threshold and the directional indicators reverse.
Entry Conditions :
Bullish Entry :
RSI Divergence : Checks if the current close is lower than a previous low while the RSI is above the previous low, suggesting bullish divergence.
Bollinger Confirmation : Requires that the price is above the lower (or upper if confirmation is toggled) Bollinger Band.
Volume & Trend Filters : Combines volume condition, ADX strength, and an optional candle momentum condition.
Risk/Reward Check : Validates that the trade meets a favorable risk-to-reward ratio.
Bearish Entry :
Uses a mirror logic of the bullish entry by checking for bearish divergence, ensuring the price is below the appropriate Bollinger level, and confirming volume, trend strength, candle pattern, and risk/reward criteria.
Trade Execution and Exit Strateg y:
Trade Execution :
Upon meeting the entry conditions, the strategy initiates a long or short position.
Stop Loss & Trailing Stops :
A stop-loss is dynamically set using the ATR value, and trailing stops are implemented as a percentage of the close price.
Exit Conditions :
Additional exit filters can trigger early closures based on RSI divergence, mean reversion (via the middle Bollinger Band), or a weakening trend as signaled by ADX falling below its threshold.
This multi-layered exit strategy is designed to lock in gains or minimize losses if the market begins to reverse unexpectedly.
How the Strategy Works in Different Market Conditions :
Trending Markets :
The ADX filter ensures that trades are only taken when the trend is strong. When the market is trending, the directional movement indicators help confirm the momentum, making the reversal signal more reliable.
Ranging Markets :
In choppy markets, the Bollinger Bands expand and contract, while the RSI divergence can highlight potential turning points. The optional filters can be adjusted to avoid false signals in low-volume or low-volatility conditions.
Volatility Management :
With ATR-based stop-losses and a risk/reward filter, the strategy adapts to current market volatility, ensuring that risk is managed consistently.
Recommendation on using this Strategy with a Trading Bot :
This strategy is well-suited for high-frequency trading (HFT) due to its ability to quickly identify reversal setups and execute trades dynamically with automated stop-loss and trailing exits. By integrating this script with a TradingView webhook-based bot or an API-driven execution system, traders can automate trade entries and exits in real-time, reducing manual execution delays and capitalizing on fast market movements.
Disclaimer :
This script is provided for educational and informational purposes only. It is not intended as investment advice. Trading involves significant risk, and you should always conduct your own research and analysis before making any trading decisions. The author is not responsible for any losses incurred while using this script.
New York Key LevelsThis indicator provides a collection of important New York market levels to assist with trading strategies. While it is still a work in progress, it currently includes the following:
15m Opening Range: Tracks the first 15-minute price action after the New York session opens, helping to define key levels of support and resistance for the day.
Stay tuned for additional features and levels as this tool evolves!
SwipeUP IndicatorThe "SwipeUP Indicator" is an advanced technical analysis tool designed to help traders identify buying and selling opportunities in the financial market.
This indicator uses a combination of exponential moving averages and volume filters to generate accurate and reliable signals based on overbought and oversold conditions.
Key Features:
Buy and Sell Signals: The "SwipeUP Indicator" generates bullish and bearish signals based on overbought and oversold conditions on multiple timeframes (4-hour and 8-hour).
Bullish signals are indicated by green arrows, while bearish signals are indicated by red arrows.
Volume Filters: The signals are confirmed by a volume filter, which ensures greater accuracy. The volume filter uses the 20- and 50-period exponential moving average of volume to confirm the validity of the signals.
Reference Line: The indicator checks the position of the price against a reference line calculated on a daily timeframe. This reference line is a simple moving average of the closing price over 280 periods.
Clear Visualization: The signals are displayed with colored arrows directly on the main chart, making it easy for the trader to interpret and take action.
Overbought and Oversold Levels: The indicator includes horizontal lines for overbought and oversold levels, with a background fill for better visualization.
These levels help traders identify when the market may be ready for a reversal.
How to Use:
Add the "SwipeUP Indicator" to your chart on TradingView.
Notice the red and green arrows indicating sell and buy signals respectively.
Use the signals in combination with other technical analysis tools to make informed trading decisions.
Note: This indicator is protected and available only to authorized users. Contact the author for information on how to gain access.
EMA 34 Crossover with Break Even Stop LossEMA 34 Crossover with Break Even Stop Loss Strategy
This trading strategy is based on the 34-period Exponential Moving Average (EMA) and aims to enter long positions when the price crosses above the EMA 34. The strategy is designed to manage risk effectively with a dynamic stop loss and take-profit mechanism.
Key Features:
EMA 34 Crossover:
The strategy generates a long entry signal when the closing price of the current bar crosses above the 34-period EMA, with the condition that the previous closing price was below the EMA. This crossover indicates a potential upward trend.
Risk Management:
Upon entering a trade, the strategy sets a stop loss at the low of the previous bar. This helps in controlling the downside risk.
A take profit level is set at a 10:1 risk-to-reward ratio, meaning the potential profit is ten times the amount risked on the trade.
Break-even Stop Loss:
As the price moves in favor of the trade and reaches a 3:1 risk-to-reward ratio, the strategy moves the stop loss to the entry price (break-even). This ensures that no loss will be incurred if the market reverses, effectively protecting profits.
Exit Conditions:
The strategy exits the trade when either the stop loss is hit (if the price drops below the stop loss level) or the take profit target is reached (if the price rises to the take profit level).
If the price reaches the break-even level (entry price), the stop loss is adjusted to lock in profits and prevent any loss.
Visualization:
The stop loss and take profit levels are plotted on the chart for easy visualization, helping traders track the status of their trade.
Trade Management Summary:
Long Entry: When price crosses above the 34-period EMA.
Stop Loss: Set to the low of the previous candle.
Take Profit: Set to a 10:1 risk-to-reward ratio.
Break-even: Stop loss is moved to entry price when a 3:1 risk-to-reward ratio is reached.
Exit: The trade is closed either when the stop loss or take profit levels are hit.
This strategy is designed to minimize losses by employing a dynamic stop loss and to maximize gains by setting a favorable risk-to-reward ratio, making it suitable for traders who prefer a structured, automated approach to risk management and trend-following.
Death Cross ReversalThis indicator tracks the recovery of the EMA20 slope after a death cross (when EMA200 crosses above EMA50). At the death cross, it records the current EMA20 slope as a baseline. As the slope improves from its negative baseline, the indicator plots sequential signals:
A Strength Signal when the slope recovers 50% of the baseline gap,
An Early Momentum Signal at 75% recovery, and
A Reversal Signal when the slope finally crosses above +50.
It also displays a histogram of the EMA20 slope (green for positive, gray for negative). Once the reversal signal fires, no further signals are generated until a golden cross resets the cycle.
Gold Silver Ratio Indicator by MossinNagantThis system is designed to trade manually in the gold-silver ratio.
It sells and buys at the percentage you specify in the lower and upper limits and sells and buys at the same rate for each subsequent increase or decrease you specify.
start_time: Gets the start date from the user (default: January 1, 2025).
initial_dollar_input: Initial balance (in USD, default: 10,000 USD). 50% of this balance will buy gold and 50% will buy silver.
threshold_high_input: Upper threshold level (default: 90).
threshold_low_input: Lower threshold level (default: 80).
step_input: Step size (in percentage, default: 2%).
trade_percent_input: Percentage rate to be sold in each transaction.
Transaction logic;
Transaction Logic:
sell_gold_basic and sell_gold_step: When the rate exceeds the upper threshold (threshold_high), gold is sold.
sell_silver_basic and sell_silver_step: When the rate falls below the lower threshold (threshold_low), silver is sold.
step: A new transaction is triggered with each additional step (e.g. 2% increments).
Transactions:
When gold is sold: 10% is sold (gold_sold), silver is bought with it (silver_bought).
When silver is sold: 10% is sold (silver_sold), gold is bought with it (gold_bought).
Sales and purchase transactions are shown on the chart with labels (label.new).
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M2 Global Liquidity IndexGlobal liquidity index calculated as
(ECONOMICS:CNM2 * FX_IDC:CNYUSD + ECONOMICS:USM2+ ECONOMICS:EUM * FX:EURUSD + ECONOMICS:JPM2 * FX_IDC:JPYUSD + ECONOMICS:GBM2 * FX:GBPUSD) / 1000000000000
Feel free to share your offsets in comments to find better sync between M2 and BTCUSDT
BTC/USDC 50x Futures Strategy with Multi-TPScript in the workings for btc/usdt 50x leverage trading at 1% portfolio margin. Please do not use to save your money
EMA 21 and SMA 50 Low ConditionsDescription:
This indicator highlights trend zones on a daily chart using the 21-day Exponential Moving Average (EMA) and 50-day Simple Moving Average (SMA). It’s designed to identify bullish conditions with two distinct background colors:
• Green Background: Signals a strong bullish trend. Appears when the low of the candle stays above the 21 EMA for 3 or more consecutive days, with either the 3rd or 4th day closing higher than its open (an “up” day). The green zone persists until a candle closes below the 21 EMA.
• Yellow Background: Indicates a potential support zone. Triggers when the low of the candle remains above the 50 SMA after the green condition ends, suggesting the price is still holding above a longer-term average. The yellow zone lasts until a candle closes below the 50 SMA.
Features:
• Plots the 21 EMA (blue line) and 50 SMA (orange line) for visual reference.
• Uses background colors to mark trend zones, making it easy to spot bullish phases and support levels.
• Optimized for daily timeframes, ideal for swing traders or long-term trend followers.
How to Use:
1. Apply the indicator to a daily chart.
2. Watch for the green background to identify strong bullish momentum (lows holding above the 21 EMA with an up close confirmation).
3. Look for the yellow background as a sign of potential support after the short-term trend weakens (lows above the 50 SMA).
4. Exit zones are triggered by closes below the respective averages (21 EMA for green, 50 SMA for yellow).
Notes:
• Best used on symbols with sufficient historical data to ensure accurate EMA and SMA calculations.
• The indicator prioritizes the green condition over yellow—green will override if both could apply.
Author’s Intent:
Created to help traders visualize sustained bullish trends and key support levels using simple moving average rules. Perfect for confirming uptrends and monitoring pullbacks within a broader bullish context.
Forex Market Strength Indicator [algo_aakash]📊 Forex Market Strength Indicator
This indicator visually displays the relative strength of major currencies by analyzing percentage changes in popular forex pairs like EURUSD, GBPUSD, USDJPY, and others.
💡 It presents each currency's strength using a color-coded bar system, making it easier to spot the strongest and weakest currencies at a glance.
No signals, no clutter — just a clean visual representation of forex market strength.
Created by @algo_aakash
Built using Pine Script v6.
Iron Condor Sideways Market Detector📘 Description: Iron Condor Sideways Market Detector
This indicator helps option traders find sideways markets for Iron Condor strategy.
🔍 What it does:
📏 Detects when the market is moving in a small range.
✅ Gives a signal when the price is not trending and staying flat.
📉 Shows a label below the candle when conditions are right for an Iron Condor setup.
📊 How it works:
RSI between 40 and 60
→ Market is not overbought or oversold.
ADX below 25
→ Market has low trend strength.
Bollinger Band width is small
→ Price volatility is low.
Price range is within a fixed %
→ Market is moving inside a tight range.
🔔 Alerts:
You get an alert when all sideways conditions are true.
Great for planning neutral option strategies like Iron Condor.
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⚠️ Risk Disclaimer
📈 Trading involves risk. Always trade with proper knowledge and money management.
💸 You can lose part or all of your capital. Only invest what you can afford to lose.
🧠 This indicator is a tool, not a guarantee of profit.
🕵️♂️ Always verify signals with your own analysis before taking any position.
🛠️ Past performance of any strategy or tool does not guarantee future results.
📊 Options strategies like Iron Condor require understanding of option greeks, volatility, and risk/reward balance.
Post-Death-Cross Reversaldentifies a “death cross” (EMA200 crossing above EMA50), then plots a small green triangle when EMA20’s slope is rising and its RSI crosses above 50—signaling a potential reversal. Also displays a histogram of EMA20’s slope as a momentum gauge.
ETF Rotation Strategy (India)Description of Strategy:
Suitable for ETFs or large-cap stock with very low frequency traders (2-3 trade per year). I have created for my use based on my own experience and knowledge, thought it could help more like me.
1. This ETF rotation strategy is based on trend tracking of 2 ETFs, moving averages standard,
2. One Benchmark ETF (that is selectable in Inputs) and 2nd that's you can plot on chart,
3. Strategy does comparison between the 2 ETFs in multiple time periods,
4. And prompts you for entry and exit on the plotted ETF in comparison with benchmark, suitable for investors or very low frequency traders. It may not give more than 2-3 trades per year,
5. Back testing result for plotted ETF will appear in tester, and combined both ETFs performance will appear in the table left top.
6. Combined back testing is done for past 5 years,
7. Option to select start year of back test is available in Input for combined result in table,
8. Its tested mostly on India liquid ETFs (12-15), included in table right bottom, Input has option to select or deselect this table to appear or disappear. When deselected script speed is better. Although global ETFs can be tested by changing benchmark ETF is Input and select watchlist accordingly,
9. May be tried on Large cap stocks, however tested for ETFs due less volatility in comparison to stocks,
10. User need to add most liquid ETF in watchlist and then when plot any ETF it will show its performance with benchmark and show entry /exit,
11. Future performance obviously will depend on market conditions time to time.
For Access to it, please contact me on email "ssukhjitkd@gmail.com" with your Tradingview account name and brief description of you, markets you trade and your trading interest.
