Open Interest (Multiple Exchanges for Crypto)On some cryptocurrencies and exchanges the OI data is nonexistent or deplorable. With this indicator you can see OI data from multiple exchanges (or just the best one) from USD,USDT, or USD+USDT pairs whether you are using a perpetuals chart or not.
Hope you all like it!
Analisis Trend
New Daily Low with Offset Alert FeatureThis indicator plots the current day’s low as a horizontal line on your chart and provides an optional offset line above it. It’s designed for traders who want to monitor when price is near or breaking below the daily low. You can set alerts based on the built-in alert conditions to be notified whenever the market approaches or crosses below these key levels.
How to Use With Alerts:
1. Add the indicator to your chart and choose a timeframe (e.g., 15 minutes).
2. In the script inputs, enable or adjust the daily low line and any offset percentage if desired.
3. Open the “Alerts” menu in TradingView and select the corresponding alert condition:
• Cross Below Daily Low to detect when price dips below the day’s low.
• Cross Below Daily Low + Offset if you prefer a small cushion above the actual low.
4. Configure the alert’s frequency and notifications to stay updated on potential breakdowns.
This setup helps you catch new lows or near-breakdowns quickly, making it useful for both intraday traders and swing traders watching key support levels.
MTF Support & Resistance📌 Multi-Timeframe Support & Resistance (MTF S&R) Indicator
🔎 Overview:
The MTF Support & Resistance Indicator is a powerful tool designed to help traders identify critical price levels where the market is likely to react. This indicator automatically detects support and resistance zones based on a user-defined lookback period and extends these levels dynamically on the chart. Additionally, it provides multi-timeframe (MTF) support and resistance zones, allowing traders to view higher timeframe key levels alongside their current timeframe.
Support and resistance levels are crucial for traders as they help in determining potential reversal points, breakout zones, and trend continuation signals. By incorporating multi-timeframe analysis, this indicator enhances decision-making by providing a broader perspective of price action.
✨ Key Features & Benefits:
✅ Automatic Support & Resistance Detection – No need to manually plot levels; the indicator calculates them dynamically based on historical price action.
✅ Multi-Timeframe (MTF) Levels – Enables traders to see higher timeframe S&R levels on their current chart for better trend confirmation.
✅ Customizable Lookback Period – Adjust sensitivity by modifying the number of historical bars considered when calculating support and resistance.
✅ Color-Coded Visualization –
Green Line → Support on the current timeframe
Red Line → Resistance on the current timeframe
Dashed Blue Line → Higher timeframe support
Dashed Orange Line → Higher timeframe resistance
✅ Dynamic Extension of Levels – Levels extend left and right for better visibility across multiple bars.
✅ Real-Time Updates – Automatically refreshes as new price data comes in.
✅ Non-Repainting – Ensures reliable support and resistance levels that do not change after the bar closes.
📈 How to Use the Indicator:
Identify Key Price Levels:
The green line represents support, where price may bounce.
The red line represents resistance, where price may reject.
The blue dashed line represents support on a higher timeframe, making it a stronger level.
The orange dashed line represents higher timeframe resistance, helping identify major breakout zones.
Trend Trading:
Look for price action around these levels to confirm breakouts or reversals.
Combine with trend indicators (like moving averages) to validate trade entries.
Range Trading:
If the price is bouncing between support and resistance, consider range trading strategies (buying at support, selling at resistance).
Breakout Trading:
If the price breaks above resistance, it could indicate a bullish trend continuation.
If the price breaks below support, it could signal a bearish trend continuation.
⚙️ Indicator Settings:
Lookback Period: Determines the number of historical bars used to calculate support and resistance.
Show Higher Timeframe Levels (MTF): Enable/disable MTF support and resistance levels.
Extend Bars: Extends the drawn lines for better visualization.
Support/Resistance Colors: Allows users to customize the appearance of the lines.
⚠️ Important Notes:
This indicator does NOT generate buy/sell signals—it serves as a technical tool to improve trading analysis.
Best Used With Other Indicators: Consider combining it with volume, moving averages, RSI, or price action strategies for more reliable trade setups.
Works on Any Market & Timeframe: Forex, stocks, commodities, indices, and cryptocurrencies.
Use Higher Timeframe Levels for Stronger Confirmations: If a higher timeframe support/resistance level aligns with a lower timeframe level, it may indicate a stronger price reaction.
🎯 Who Should Use This Indicator?
📌 Scalpers & Day Traders – Identify short-term support and resistance levels for quick trades.
📌 Swing Traders – Utilize higher timeframe levels for position entries and exits.
📌 Trend Traders – Confirm breakout zones and key price levels for trend-following strategies.
📌 Reversal Traders – Spot potential reversal zones at significant S&R levels.
Anchored VWAP with Buy/Sell SignalsAnchored VWAP Calculation:
The script calculates the AVWAP starting from a user-defined anchor point (anchor_date).
The AVWAP is calculated using the formula:
AVWAP
=
∑
(
Volume
×
Average Price
)
∑
Volume
AVWAP=
∑Volume
∑(Volume×Average Price)
where the average price is
(
h
i
g
h
+
l
o
w
+
c
l
o
s
e
)
/
3
(high+low+close)/3.
Buy Signal:
A buy signal is generated when the price closes above the AVWAP (ta.crossover(close, avwap)).
Sell Signal:
A sell signal is generated when the price closes below the AVWAP (ta.crossunder(close, avwap)).
Plotting:
The AVWAP is plotted on the chart.
Buy and sell signals are displayed as labels on the chart.
Background Highlighting:
The background is highlighted in green for buy signals and red for sell signals (optional).
highs&lowsone of my first strategy: highs&lows
This strategy takes the highest high and the lowest low of a specified timeframe and specified bar count.
It will then takes the average between these two extremes to create a center line.
This creates a range of high middle and low.
Then the strategy takes the current market movement
which is the direct average(no specified timeframe and specified bar count) of the current high and low.
Using this "current market movement" within the range of high middle and low it determins when to buy and then sell the asset.
*********note***************
-this strategy is (bullish)
-works good with most futures assets that have volatility/ decent movement
(might add more details if I forget any)
(work in progress)
Support and Resistance with Buy/Sell SignalsSwing Highs and Lows:
The script identifies swing highs and lows using the ta.highest and ta.lowest functions over a user-defined swing_length period.
Swing highs are treated as resistance levels.
Swing lows are treated as support levels.
Buy Signal:
A buy signal is generated when the price closes above the resistance level (ta.crossover(close, swing_high)).
Sell Signal:
A sell signal is generated when the price closes below the support level (ta.crossunder(close, swing_low)).
Plotting:
Support and resistance levels are plotted on the chart.
Buy and sell signals are displayed as labels on the chart.
Background Highlighting:
The background is highlighted in green for buy signals and red for sell signals (optional).
Tri-Fold BB(Trend-Strength)*indicator isn't preset to look as displayed, do so accordingly*
"Tri-Fold BB" is an indicator that utilizes three Bollinger Bands, each of different length as a way to represent trend strength. This allows one to see the trend strength relative to multiple timeframes: short, mid, and long term trend strength. This is helpful because it provides the user with a holistic view of the asset.
How it Works
The indicator is preset to utilizing three different Bollinger Bands with length: 20, 50, and 100. This indicator simply plots the price of an asset relative to its specified Bollinger Band. For an example, if the price of the asset were to surpass its 20BB standard deviations, it would display so accordingly, though from the perspective of lets say... the 100, it may have looked like it barely moved up a standard deviation relative to 100BB because the standard deviations of a 100BB are more spread out.
Its important to view the trend strength from multiple lengths because it allows one to gauge whether the short term trend strength is likely to hold or not. A better way to speculate on asset behavior.
Another way to view this indicator is similar to that of the BB% indicator, except this indicator allows us to view price relative to standard deviations, across multiple timeframes. More holistic, more utility provided.
Basic Understanding:
Each line = Standard Deviation (3 upper, 3 lower)
Mid-Line = Basis relative to BB(20sma, 50sma, 100sma)
If price goes under Basis, that means it crossed below their specified sma(significant bull or bear signal)
I've also added HMA's relative to each BB incase one were to decide in creating some sort of trading strategy with it. I personally don't use them but I understand that it could be helpful to some so I left it in there. If you don't like them then simply deselect them and then save your desired setup as default.
In regard to regular indications of bullish or bearishness, i'd like to add that I use this indicator for the sole purpose of providing an idea of trend strength. I personally am unsure to state that cross overs directly indicate that there is a bull or bear move because I've seen instances where the price of an asset went in a direction contrary to what it 'should' have if we were to use that cross over strategy. Though of course, feel free to use this indicator as desired.
Son Model ICT [TradingFinder] HTF DOL H1 + Sweep M15 + FVG M1🔵 Introduction
The ICT Son Model setup is a precise trading strategy based on market structure and liquidity, implemented across multiple timeframes. This setup first identifies a liquidity level in the 1-hour (1H) timeframe and then confirms a Market Structure Shift (MSS) in the 5-minute (5M) timeframe to validate the trend. After confirmation, the price forms a new swing in the 5-minute timeframe, absorbing liquidity.
Once this level is broken, traders typically drop to the 30-second (30s) timeframe and enter trades based on a Fair Value Gap (FVG). However, since access to the 30-second timeframe is not available to most traders, we take the entry signal directly from the 5-minute timeframe, using the same liquidity zones and confirmed breakouts to execute trades. This approach simplifies execution and makes the strategy accessible to all traders.
This model operates in two setups :
Bullish ICT Son Model and Bearish ICT Son Model. In the bullish setup, liquidity is first accumulated at the lows of the 1-hour timeframe, and after confirming a market structure shift, a long position is initiated. Conversely, in the bearish setup, liquidity is first drawn from higher levels, and upon confirmation of a bearish trend, a short position is executed.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The ICT Son Model setup is designed around liquidity analysis and market structure shifts and can be applied in both bullish and bearish market conditions. The strategy first identifies a liquidity level in the 1-hour (1H) timeframe and then confirms a Market Structure Shift (MSS) in the 5-minute (5M) timeframe.
After this shift, the price forms a new swing, absorbing liquidity. When this level is broken in the 5-minute timeframe, the trader enters based on a Fair Value Gap (FVG). While the ideal entry is in the 30-second (30s) timeframe, due to accessibility constraints, we take entry signals directly from the 5-minute timeframe.
🟣 Bullish Setup
In the Bullish ICT Son Model, the 1-hour timeframe first identifies liquidity at the market lows, where price sweeps this level to absorb liquidity. Then, in the 5-minute timeframe, an MSS confirms the bullish shift.
After confirmation, the price forms a new swing, absorbing liquidity at a higher level. The price then retraces into a Fair Value Gap (FVG) created in the 5-minute timeframe, where the trader enters a long position, placing the stop-loss below the FVG.
🟣 Bearish Setup
In the Bearish ICT Son Model, liquidity at higher market levels is identified in the 1-hour timeframe, where price sweeps these levels to absorb liquidity. Then, in the 5-minute timeframe, an MSS confirms the bearish trend.
After confirmation, the price forms a new swing, absorbing liquidity at a lower level. The price then retraces into a Fair Value Gap (FVG) created in the 5-minute timeframe, where the trader enters a short position, placing the stop-loss above the FVG.
🔵 Settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
FVG Length : Default is 120 Bar.
MSS Length : Default is 80 Bar.
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
🔵 Conclusion
The ICT Son Model setup is a structured and precise method for trade execution based on liquidity analysis and market structure shifts. This strategy first identifies a liquidity level in the 1-hour timeframe and then confirms a trend shift using the 5-minute timeframe.
Trade entries are executed based on Fair Value Gaps (FVGs), which highlight optimal entry points. By applying this model, traders can leverage existing market liquidity to enter high-probability trades. The bullish setup activates when liquidity is swept from market lows and a market structure shift confirms an upward trend, whereas the bearish setup is used when liquidity is drawn from market highs, confirming a downtrend.
This approach enables traders to identify high-probability trade setups with greater precision compared to many other strategies. Additionally, since access to the 30-second timeframe is limited, the strategy remains fully functional in the 5-minute timeframe, making it more practical and accessible for a wider range of traders.
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
Dual SD Median | QuantEdgeBIntroducing Dual SD Median by QuantEdgeB
The Dual SD Median indicator is a powerful statistical tool designed to enhance market analysis through median-based trend detection and standard deviation filtering. By leveraging median price smoothing, adaptive standard deviation bands, and normalized statistical filtering, it provides traders with a structured approach to identifying breakouts, reversals, and stable market trends.
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1. Key Features
🔹 Median-Based Trend Calculation: Uses the median price instead of simple moving averages to create a more robust and stable trend baseline, reducing noise in volatile markets.
🔹 Standard Deviation Bands: Dynamically adjusts upper and lower bands based on market volatility, helping traders spot key breakout zones and trend reversals.
🔹 Normalized Filtering: Incorporates a normalized median structure, ensuring that trends are identified with greater accuracy, and filtering out insignificant price fluctuations.
🔹 Multi-Market Adaptability: Optimized for crypto, but its calibration settings allow adaptation to other markets through adjustable SD multipliers and other inputs.
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2. How It Works
The Dual SD Median calculates a smoothed median price over a defined period, providing a stable central value for trend tracking. It then applies standard deviation bands to dynamically adjust to market conditions.
To further enhance precision, the indicator normalizes the median price against the underlying asset’s price fluctuations, ensuring that only significant trend shifts trigger signals.
Long & Short Signals:
✔ Long Signal: Triggered when the price breaks above both the upper SD median band and the normalized median threshold.
✔ Short Signal: Activated when the price drops below the lower SD median band and the normalized threshold.
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3. How to Use it
📌 Trend Confirmation: Use this indicator to confirm trends by observing breakouts beyond the SD bands. A strong price move past the median SD zone signals potential continuation.
📌 Reversal Identification: If price moves aggressively into SD bands but fails to sustain momentum, it may indicate overextension and reversal potential.
📌 Volatility-Based Trading: Traders can adjust the SD multipliers to match different asset classes and market conditions.
📌 Cross-Market Applicability: While optimized for crypto, the system can be fine-tuned for stocks, forex, and commodities through custom parameter adjustments.
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4. Customization Options
⚙️ SD Median Length (Default: 14) – Defines the median price calculation window.
⚙️ Normalized Median Length (Default: 50) – Smooths long-term trends for stability.
⚙️ Standard Deviation Length (Default: 30) – Adjusts volatility sensitivity.
⚙️ SD Multipliers (Default: 0.98 for Longs, 1.06 for Shorts) – Determines breakout thresholds.
⚙️ Smoothing Factors (Default: 1) – Fine-tunes signal sensitivity.
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Conclusion
The Dual SD Median is a versatile, statistically-driven tool that helps traders navigate volatile market conditions with greater accuracy. By combining median smoothing, standard deviation filtering, and normalized trend detection, it reduces noise while maintaining responsiveness to 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.
Universal Strategy | QuantEdgeBIntroducing the Universal Strategy by QuantEdgeB
The Universal Strategy | QuantEdgeB is a dynamic, multi-indicator strategy designed to operate across various asset classes with precision and adaptability. This cutting-edge system utilizes four sophisticated methodologies, each integrating advanced trend-following, volatility filtering, and normalization techniques to provide robust signals. Its modular architecture and customizable features ensure suitability for diverse market conditions, empowering traders with data-driven decision-making tools. Its adaptability to different price behaviors and volatility levels makes it a robust and versatile tool, equipping traders with data-driven confidence in their market decisions.
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1. Core Methodologies and Features
1️⃣ DEMA ATR
Strength : Fast responsiveness to trend shifts.
The double exponential moving average is inherently aggressive, designed to reduce lag and quickly identify early signs of trend reversals or breakout opportunities. ATR bands add a volatility-sensitive layer, dynamically adjusting the breakout thresholds to match current market conditions, ensuring it remains responsive while filtering out noise
How It Fits :
This indicator is the first responder, providing early signals of potential trend shifts. While its aggressiveness can result in quick entries, it may occasionally overreact in noisy markets. This is where the smoother indicators step in to confirm signals.
2️⃣ Gaussian - VIDYA ATR (Variable Index Dynamic Average)
Strength : Smooth, adaptive trend identification.
Unlike DEMA, VIDYA adapts to market volatility through its standard deviation-based formula, making it smoother and less reactive to short-term fluctuations. ATR filtering ensures the indicator remains effective in volatile markets by dynamically adjusting its sensitivity.
How It Fits :
The smoother complement to DEMA ATR, VIDYA ATR filters out false signals from minor price movements. It provides confirmation for the trends identified by DEMA ATR, ensuring entries are based on robust, sustained price movements.
3️⃣ VIDYA Loop Trend Scoring
Strength : Historical trend scoring for consistent momentum detection.
This module evaluates the relative strength of trends by comparing the current VIDYA value to its historical values over a defined range. The loop mechanism provides a trend confidence score, quantifying the momentum behind price movements.
How It Fits :
VIDYA For-Loop adds a quantitative measure of trend strength, ensuring that trades are backed by sustained momentum. It balances the early signals from DEMA ATR and the smoothness of VIDYA ATR by providing a statistical check on the underlying trend.
4️⃣ Median SD with Normalization
Strength : Precision in breakout detection and market normalization.
The Median price serves as a robust baseline for detecting breakouts and reversals.
SD bands expand dynamically during periods of high volatility, making the indicator particularly effective for spotting strong trends or breakout opportunities. Normalization ensures the indicator adapts seamlessly across different assets and timeframes, providing consistent performance.
How It Fits :
The Median SD module provides final confirmation by focusing on price breakouts and market normalization. While the other indicators focus on momentum and trend strength, Median SD emphasizes precision, ensuring entries align with significant price movements rather than random fluctuations.
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2. How The Single Components Work Together
1️⃣ Balance of Speed and Smoothness :
The strategy blends quick responsiveness (DEMA ATR) with smooth and adaptive confirmation (VIDYA ATR & For-Loop), ensuring timely reactions without overreacting to market fluctuations. Median SD with Normalization refines breakout detection and stabilizes performance across assets using statistical anchors like price median and standard deviation.
Adaptability to Market Dynamics:
2️⃣ Adaptability to Market Dynamics :
The indicators complement each other seamlessly in trending markets, with the DEMA ATR and Median SD with Normalization quickly identifying shifts and confirming sustained momentum. In volatile or choppy markets, normalization and SD bands work together to filter out noise and reduce false signals, ensuring precise entries and exits. Meanwhile, the For-Loop scoring and Gaussian-Filtered VIDYA ATR focus on providing smoother, more reliable trend detection, offering consistent performance regardless of market conditions.
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3. Scoring and Signal Confirmation
The Universal Strategy consolidates signals from all four methodologies, calculating a Trend Probability Index (TPI). The four core indicators operate independently but contribute to a unified TPI, enabling highly adaptive behavior across asset classes.
- Each methodology generates a trend score: 1 for bullish trends, -1 for bearish trends.
- The TPI averages the scores, creating a unified signal.
- Long Position: Triggered when the TPI exceeds the long threshold (default: 0).
- Short Position: Triggered when the TPI falls below the short threshold (default: 0).
The strategy’s customizable settings allow traders to tailor its behavior to different market conditions—whether smoother trends in low-volatility assets or quick reaction to high-volatility breakouts. The long and short thresholds can be fine-tuned to match a trader’s risk tolerance and preferences.
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4. Use Cases:
The Universal Strategy | QuantEdgeB is designed to excel across a wide range of trading scenarios, thanks to its modular architecture and adaptability. Whether you're navigating trending, volatile, or range-bound markets, this strategy offers robust tools to enhance your decision-making. Below are the key use cases for its application:
1️⃣ Trend Trading
The strategy’s Gaussian-Filtered DEMA ATR and VIDYA ATR modules are perfect for identifying and riding sustained trends.
Ideal For: Traders looking to capture long-term momentum or position trades.
2️⃣ Breakout and Volatility-Based Strategies
With its Median SD with Normalization, the strategy excels in detecting volatility breakouts and significant price movements.
Ideal For: Traders aiming to capitalize on sudden market movements, especially in assets like cryptocurrencies and commodities.
3️⃣ Momentum and Strength Assessment
By generating a trend confidence score, the VIDYA For-Loop quantifies momentum strength—helping traders distinguish temporary spikes from sustainable trends.
Ideal For: Swing traders and those focusing on momentum-driven setups.
4️⃣ Adaptability Across Multiple Assets
The strategy’s robust framework ensures it performs consistently across different assets and timeframes.
Ideal For: Traders managing diverse portfolios or shifting between asset classes.
5️⃣ Backtesting and Optimization
Built-in backtesting and equity visualization tools make this strategy ideal for testing and refining parameters in real-world conditions.
• How It Helps: The strategy equity curve and metrics table offer a clear picture of performance, helping traders identify optimal settings for their chosen market and timeframe.
• Ideal For: Traders focused on rigorous testing and long-term optimization.
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5. Signal Composition Table:
This table presents a real-time breakdown of each indicator’s trend score (+1 bullish, -1 bearish) alongside the final aggregated signal. By visualizing the contribution of each methodology, traders gain greater transparency, confidence, and clarity in identifying long or short opportunities.
6. Customized Settings:
1️⃣ General Inputs
• Strategy Long Threshold (Lu): 0
• Strategy Short Threshold (Su): 0
2️⃣ Gaussian Filter
• Gaussian Length (len_FG): 4
• Gaussian Source (src_FG): close
• Gaussian Sigma (sigma_FG): 2.0
3️⃣ DEMA ATR
• DEMA Length (len_D): 30
• DEMA Source (src_D): close
• ATR Length (atr_D): 14
• ATR Multiplier (mult_D): 1.0
4️⃣ VIDYA ATR
• VIDYA Length (len_V1): 9
• SD Length (len_VHist1): 30
• ATR Length (atr_V): 14
• ATR Multiplier (mult_V): 1.7
5️⃣ VIDYA For-Loop
• VIDYA Length (len_V2): 2
• SD Length (len_VHist2): 5
• VIDYA Source (src_V2): close
• Start Loop (strat_loop): 1
• End Loop (end_loop): 60
• Long Threshold (long_t): 40
• Short Threshold (short_t): 8
6️⃣ Median SD
• Median Length (len_m): 24
• Normalized Median Length (len_msd): 50
• SD Length (SD_len): 32
• Long SD Weight (w1): 0.98
• Short SD Weight (w2): 1.02
• Long Normalized Smooth (smooth_long): 1
• Short Normalized Smooth (smooth_short): 1
Conclusion
The Universal Strategy | QuantEdgeB is a meticulously crafted, multi-dimensional trading system designed to thrive across diverse market conditions and asset classes. By combining Gaussian-Filtered DEMA ATR, VIDYA ATR, VIDYA For-Loop, and Median SD with Normalization, this strategy provides a seamless balance between speed, smoothness, and adaptability. Each component complements the others, ensuring traders benefit from early responsiveness, trend confirmation, momentum scoring, and breakout precision.
Its modular structure ensures versatility across trending, volatile, and consolidating markets. Whether applied to equities, forex, commodities, or crypto, it delivers data-driven precision while minimizing reliance on randomness, reinforcing confidence in decision-making.
With built-in backtesting tools, traders can rigorously evaluate performance under real-world conditions, while customization options allow fine-tuning for specific market dynamics and individual trading styles.
Why It Stands Out
The Universal Strategy | QuantEdgeB isn’t just a trading algorithm—it’s a comprehensive framework that empowers traders to make confident, informed decisions in the face of ever-changing market conditions. Its emphasis on precision, reliability, and transparency makes it a powerful tool for both professional and retail traders seeking consistent performance and enhanced risk management.
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🔹 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.
Iron Bot Statistical Trend Filter📌 Iron Bot Statistical Trend Filter
📌 Overview
Iron Bot Statistical Trend Filter is an advanced trend filtering strategy that combines statistical methods with technical analysis.
By leveraging Z-score and Fibonacci levels, this strategy quantitatively analyzes market trends to provide high-precision entry signals.
Additionally, it includes an optional EMA filter to enhance trend reliability.
Risk management is reinforced with Stop Loss (SL) and four Take Profit (TP) levels, ensuring a balanced approach to risk and reward.
📌 Key Features
🔹 1. Statistical Trend Filtering with Z-Score
This strategy calculates the Z-score to measure how much the price deviates from its historical mean.
Positive Z-score: Indicates a statistically high price, suggesting a strong uptrend.
Negative Z-score: Indicates a statistically low price, signaling a potential downtrend.
Z-score near zero: Suggests a ranging market with no strong trend.
By using the Z-score as a filter, market noise is reduced, leading to more reliable entry signals.
🔹 2. Fibonacci Levels for Trend Reversal Detection
The strategy integrates Fibonacci retracement levels to identify potential reversal points in the market.
High Trend Level (Fibo 23.6%): When the price surpasses this level, an uptrend is likely.
Low Trend Level (Fibo 78.6%): When the price falls below this level, a downtrend is expected.
Trend Line (Fibo 50%): Acts as a midpoint, helping to assess market balance.
This allows traders to visually confirm trend strength and turning points, improving entry accuracy.
🔹 3. EMA Filter for Trend Confirmation (Optional)
The strategy includes an optional 200 EMA (Exponential Moving Average) filter for trend validation.
Price above 200 EMA: Indicates a bullish trend (long entries preferred).
Price below 200 EMA: Indicates a bearish trend (short entries preferred).
Enabling this filter reduces false signals and improves trend-following accuracy.
🔹 4. Multi-Level Take Profit (TP) and Stop Loss (SL) Management
To ensure effective risk management, the strategy includes four Take Profit levels and a Stop Loss:
Stop Loss (SL): Automatically closes trades when the price moves against the position by a certain percentage.
TP1 (+0.75%): First profit-taking level.
TP2 (+1.1%): A higher probability profit target.
TP3 (+1.5%): Aiming for a stronger trend move.
TP4 (+2.0%): Maximum profit target.
This system secures profits at different stages and optimizes risk-reward balance.
🔹 5. Automated Long & Short Trading Logic
The strategy is built using Pine Script®’s strategy.entry() and strategy.exit(), allowing fully automated trading.
Long Entry:
Price is above the trend line & high trend level.
Z-score is positive (indicating an uptrend).
(Optional) Price is also above the EMA for stronger confirmation.
Short Entry:
Price is below the trend line & low trend level.
Z-score is negative (indicating a downtrend).
(Optional) Price is also below the EMA for stronger confirmation.
This logic helps filter out unnecessary trades and focus only on high-probability entries.
📌 Trading Parameters
This strategy is designed for flexible capital management and risk control.
💰 Account Size: $5000
📉 Commissions and Slippage: Assumes 94 pips commission per trade and 1 pip slippage.
⚖️ Risk per Trade: Adjustable, with a default setting of 1% of equity.
These parameters help preserve capital while optimizing the risk-reward balance.
📌 Visual Aids for Clarity
To enhance usability, the strategy includes clear visual elements for easy market analysis.
✅ Trend Line (Blue): Indicates market midpoint and helps with entry decisions.
✅ Fibonacci Levels (Yellow): Highlights high and low trend levels.
✅ EMA Line (Green, Optional): Confirms long-term trend direction.
✅ Entry Signals (Green for Long, Red for Short): Clearly marked buy and sell signals.
These features allow traders to quickly interpret market conditions, even without advanced technical analysis skills.
📌 Originality & Enhancements
This strategy is developed based on the IronXtreme and BigBeluga indicators,
combining a unique Z-score statistical method with Fibonacci trend analysis.
Compared to conventional trend-following strategies, it leverages statistical techniques
to provide higher-precision entry signals, reducing false trades and improving overall reliability.
📌 Summary
Iron Bot Statistical Trend Filter is a statistically-driven trend strategy that utilizes Z-score and Fibonacci levels.
High-precision trend analysis
Enhanced accuracy with an optional EMA filter
Optimized risk management with multiple TP & SL levels
Visually intuitive chart design
Fully customizable parameters & leverage support
This strategy reduces false signals and helps traders ride the trend with confidence.
Try it out and take your trading to the next level! 🚀
MTF Ichimoku Conversion Line SMA with H/L mirrored levelsWelcome to MTF Ichimoku Conversion Line with SMA Highs/Lows Extended Lines!
1. Overview
It is designed to provide a multi-timeframe view of market trends and potential support/resistance levels by obtaining a Simple Moving Average (SMA) of the Conversion Line of Ichimoku Equibilium (Ichimoku Kinko-Hyo), which acts as a substantial trend line on the candlestick chart. The SMA of the conversion line smooths out price fluctuations and indicates the overall trend direction—if the candles are above it, the trend can be read as an uptrend, while below it, the trend can be read as a downtrend.
2. Calculation
The indicator first calculates the Conversion Line (see the description of Ichimoku theory anywhere, e.g., Wikipedia), as the average of the highest high and lowest low over a user-defined period (Conversion Line Length, default is 9, also recommended is 9).
It then retrieves this Conversion Line from a higher timeframe (MTF Timeframe) to add a broader perspective. Using a specified period (SMA Length)., an SMA is computed on this multi-timeframe conversion line. This SMA serves as a trend line that visually represents the prevailing price trend, making it easier to assess market direction.
3. Pivot Highs/low detection and drawing their extensions
In addition, the indicator identifies pivot highs and lows from the SMA data using a defined pivot length. When these pivots occur, horizontal lines are drawn and extended across the chart. These extended lines (drawn in a yellowish color by default) include a full extension, a half extension, and a middle extension line representing the midpoint between the high and low pivot.
4. Mirror lines
The indicator also offers optional mirror line features. When the Mirror Upside option is enabled, five additional lines are drawn above the highest extended yellow line at equal intervals. Similarly, when the Mirror Downside option is enabled, five lines are drawn below the lowest extended yellow line. These light gray mirror lines serve as extra reference levels, which can help identify potential support or resistance zones.
5. Parameters
User parameters include:
- Conversion Line Length: The period used to calculate the conversion line.
- MTF Timeframe: The higher timeframe from which the conversion line is obtained.
- SMA Length: The period over which the SMA is calculated on the conversion line.
- SMA Mode: A toggle to display either the SMA or the raw conversion line (SMA recommended).
- SMA Line Width: The thickness of the SMA line.
- Pivot Length for SMA Highs/Lows: The period used to detect pivot highs and lows in the SMA.
- Horizontal Extension: Number of bars by which the pivot and extended lines are drawn across the chart
- Colors for High and Low Pivot Lines and Extended Lines: Customizable colors are used to draw the lines.
Mirror Upside and Mirror Downside: These options enable drawing additional mirror lines above and below the extended lines.
- Hide Old Lines: An option to hide previous pivot lines once new ones are drawn for a cleaner chart. Turned on by default.
6. Conclusion
Overall, the Conversion Line SMA in this indicator smooths out the conversion line data and effectively functions as a trend line for the candlestick chart, helping traders visually interpret the underlying market trend. The extended and mirror lines provide further context for potential price reversal or continuation areas, making this a powerful tool for multi-timeframe technical analysis.
Market Phase MAMarket Phase MA is an advanced trend-following indicator designed to provide traders with a dynamically colored moving average that adapts to market conditions. It uses a powerful combination of Average True Range (ATR) and Average Directional Index (ADX) to classify market trends in real-time. The indicator integrates a fully customizable moving average (SMA or EMA) to highlight trend phases clearly and effectively.
Key Features & Advantages:
✔ Adaptive Trend Classification: Detects uptrends, downtrends, and sideways markets using a refined mix of ATR and ADX for more precise trend identification.
✔ Color-Coded Moving Average: The moving average dynamically changes color based on trend classification, providing a clean visual representation of market sentiment.
✔ Advanced ATR & ADX Filtering:
- ATR measures market volatility and identifies ranging periods.
- ADX confirms trend strength, reducing false signals.
- A weighted approach balances ATR and ADX, ensuring reliability.
✔ Fully Customizable Moving Average: Traders can select between SMA and EMA while adjusting the moving average length directly from the settings panel.
✔ Smooth & Responsive Adjustments: The smoothing factor can be fine-tuned to control signal sensitivity and noise reduction, making it suitable for scalping, swing trading, and long-term trend monitoring.
What Makes It Unique:
- Unlike traditional trend indicators, Market Phase MA provides **direct visual feedback** on a moving average rather than using a separate oscillator.
- It **adapts dynamically** to market conditions instead of relying on fixed thresholds.
- The combination of **volatility and trend strength analysis** enhances precision in identifying valid trends.
- Users can optimize **reaction speed vs. reliability** with adjustable parameters for better decision-making.
How to Use It:
- Identify Market Phases: The moving average color shifts based on trend type—**teal** for uptrends, **red** for downtrends, and **gray** for sideways markets.
- Confirm Trend Strength: Persistent color shifts indicate strong trends, while frequent changes may suggest market indecision.
- Use as a Trade Confirmation Tool: Complement it with **support & resistance zones, price action analysis, and volume indicators** for stronger confirmation signals.
Market Phase MA is designed for traders seeking a clear, efficient, and highly adaptable moving average trend detection system. Whether you are a day trader, swing trader, or long-term investor, this indicator will help you identify and follow trends with confidence.
Smoothed Low-Pass Butterworth Filtered Median [AlphaAlgos]Smoothed Low-Pass Butterworth Filtered Median
This indicator is designed to smooth price action and filter out noise while maintaining the dominant trend. By combining a Butterworth low-pass filter with a median-based smoothing approach , it effectively reduces short-term fluctuations, allowing traders to focus on the true market direction.
How It Works
Median Smoothing: The indicator calculates the 50th percentile (median) of closing prices over a customizable period , making it more robust against outliers compared to traditional moving averages.
Butterworth Filtering: A low-pass filter is applied using an approximation of the Butterworth formula , controlled by the Cutoff Frequency , helping to eliminate high-frequency noise while preserving trends.
EMA Refinement: A 7-period EMA is applied to further smooth the signal, providing a more reliable trend representation.
Features
Trend Smoothing: Reduces market noise and highlights the dominant trend.
Dynamic Color Signals: The EMA line changes color to indicate trend strength and direction.
Configurable Parameters: Customize the median length, cutoff frequency, and EMA length to fit your strategy.
Versatile Use Case: Suitable for both trend-following and mean-reversion strategies.
How to Use
Bullish Signal: When the EMA is below the price and rising , indicating upward momentum.
Bearish Signal: When the EMA is above the price and falling , signaling a potential downtrend.
Reversal Zones: Monitor for trend shifts when the color of the EMA changes.
This indicator provides a clear, noise-free view of market trends , making it ideal for traders seeking improved trend identification and entry signals .
Blockchain Fundamentals: Liquidity & BTC YoYLiquidity & BTC YoY Indicator
Overview:
This indicator calculates the Year-over-Year (YoY) percentage change for two critical metrics: a custom Liquidity Index and Bitcoin's price. The Liquidity Index is derived from a blend of economic and forex data representing the M2 money supply, while the BTC price is obtained from a reliable market source. A dedicated limit(length) function is implemented to handle limited historical data, ensuring that the YoY calculations are available immediately—even when the chart's history is short.
Features Breakdown:
1. Limited Historical Data Workaround
- Functionality: limit(length) The function dynamically adjusts the lookback period when there isn’t enough historical data. This prevents delays in displaying YoY metrics at the beginning of the chart.
2. Liquidity Calculation
- Data Sources: Combines multiple data streams:
USM2, ECONOMICS:CNM2, USDCNY, ECONOMICS:JPM2, USDJPY, ECONOMICS:EUM2, USDEUR
- Formula:
Liquidity Index = USM2 + (CNM2 / USDCNY) + (JPM2 / USDJPY) + (EUM2 / USDEUR)
[b3. Bitcoin Price Calculation
- Data Source: Retrieves Bitcoin's price from BITSTAMP:BTCUSD on the user-selected timeframe for its historical length.
4. Year-over-Year (YoY) Percent Change Calculation
- Methodology:
- The indicator uses a custom function, to autodetect the proper number of bars, based on the selected timeframe.
- It then compares the current value to that from one year ago for both the Liquidity Index and BTC price, calculating the YoY percentage change.
5. Visual Presentation
- Plotting:
- The YoY percentage changes for Liquidity (plotted in blue) and BTC price (plotted in orange) are clearly displayed.
- A horizontal zero line is added for visual alignment, making it easier to compare the two copies of the metric. You add one copy and only display the BTC YoY. Then you add another copy and only display the M2 YoY.
-The zero lines are then used to align the scripts to each other by interposing them. You scale each chart the way you like, then move each copy individually to align both zero lines on top of each other.
This indicator is ideal for analysts and investors looking to monitor macroeconomic liquidity trends alongside Bitcoin's performance, providing immediate insights.
