Machine Learning Moving Average [BackQuant]Machine Learning Moving Average
A powerful tool combining clustering, pseudo-machine learning, and adaptive prediction, enabling traders to understand and react to price behavior across multiple market regimes (Bullish, Neutral, Bearish). This script uses a dynamic clustering approach based on percentile thresholds and calculates an adaptive moving average, ideal for forecasting price movements with enhanced confidence levels.
What is Percentile Clustering?
Percentile clustering is a method that sorts and categorizes data into distinct groups based on its statistical distribution. In this script, the clustering process relies on the percentile values of a composite feature (based on technical indicators like RSI, CCI, ATR, etc.). By identifying key thresholds (lower and upper percentiles), the script assigns each data point (price movement) to a cluster (Bullish, Neutral, or Bearish), based on its proximity to these thresholds.
This approach mimics aspects of machine learning, where we “train” the model on past price behavior to predict future movements. The key difference is that this is not true machine learning; rather, it uses data-driven statistical techniques to "cluster" the market into patterns.
Why Percentile Clustering is Useful
Clustering price data into meaningful patterns (Bullish, Neutral, Bearish) helps traders visualize how price behavior can be grouped over time.
By leveraging past price behavior and technical indicators, percentile clustering adapts dynamically to evolving market conditions.
It helps you understand whether price behavior today aligns with past bullish or bearish trends, improving market context.
Clusters can be used to predict upcoming market conditions by identifying regimes with high confidence, improving entry/exit timing.
What This Script Does
Clustering Based on Percentiles : The script uses historical price data and various technical features to compute a "composite feature" for each bar. This feature is then sorted and clustered based on predefined percentile thresholds (e.g., 10th percentile for lower, 90th percentile for upper).
Cluster-Based Prediction : Once clustered, the script uses a weighted average, cluster momentum, or regime transition model to predict future price behavior over a specified number of bars.
Dynamic Moving Average : The script calculates a machine-learning-inspired moving average (MLMA) based on the current cluster, adjusting its behavior according to the cluster regime (Bullish, Neutral, Bearish).
Adaptive Confidence Levels : Confidence in the predicted return is calculated based on the distance between the current value and the other clusters. The further it is from the next closest cluster, the higher the confidence.
Visual Cluster Mapping : The script visually highlights different clusters on the chart with distinct colors for Bullish, Neutral, and Bearish regimes, and plots the MLMA line.
Prediction Output : It projects the predicted price based on the selected method and shows both predicted price and confidence percentage for each prediction horizon.
Trend Identification : Using the clustering output, the script colors the bars based on the current cluster to reflect whether the market is trending Bullish (green), Bearish (red), or is Neutral (gray).
How Traders Use It
Predicting Price Movements : The script provides traders with an idea of where prices might go based on past market behavior. Traders can use this forecast for short-term and long-term predictions, guiding their trades.
Clustering for Regime Analysis : Traders can identify whether the market is in a Bullish, Neutral, or Bearish regime, using that information to adjust trading strategies.
Adaptive Moving Average for Trend Following : The adaptive moving average can be used as a trend-following indicator, helping traders stay in the market when it’s aligned with the current trend (Bullish or Bearish).
Entry/Exit Strategy : By understanding the current cluster and its associated trend, traders can time entries and exits with higher precision, taking advantage of favorable conditions when the confidence in the predicted price is high.
Confidence for Risk Management : The confidence level associated with the predicted returns allows traders to manage risk better. Higher confidence levels indicate stronger market conditions, which can lead to higher position sizes.
Pseudo Machine Learning Aspect
While the script does not use conventional machine learning models (e.g., neural networks or decision trees), it mimics certain aspects of machine learning in its approach. By using clustering and the dynamic adjustment of a moving average, the model learns from historical data to adjust predictions for future price behavior. The "learning" comes from how the script uses past price data (and technical indicators) to create patterns (clusters) and predict future market movements based on those patterns.
Why This Is Important for Traders
Understanding market regimes helps to adjust trading strategies in a way that adapts to current market conditions.
Forecasting price behavior provides an additional edge, enabling traders to time entries and exits based on predicted price movements.
By leveraging the clustering technique, traders can separate noise from signal, improving the reliability of trading signals.
The combination of clustering and predictive modeling in one tool reduces the complexity for traders, allowing them to focus on actionable insights rather than manual analysis.
How to Interpret the Output
Bullish (Green) Zone : When the price behavior clusters into the Bullish zone, expect upward price movement. The MLMA line will help confirm if the trend remains upward.
Bearish (Red) Zone : When the price behavior clusters into the Bearish zone, expect downward price movement. The MLMA line will assist in tracking any downward trends.
Neutral (Gray) Zone : A neutral market condition signals indecision or range-bound behavior. The MLMA line can help track any potential breakouts or trend reversals.
Predicted Price : The projected price is shown on the chart, based on the cluster's predicted behavior. This provides a useful reference for where the price might move in the near future.
Prediction Confidence : The confidence percentage helps you gauge the reliability of the predicted price. A higher percentage indicates stronger market confidence in the forecasted move.
Tips for Use
Combining with Other Indicators : Use the output of this indicator in combination with your existing strategy (e.g., RSI, MACD, or moving averages) to enhance signal accuracy.
Position Sizing with Confidence : Increase position size when the prediction confidence is high, and decrease size when it’s low, based on the confidence interval.
Regime-Based Strategy : Consider developing a multi-strategy approach where you use this tool for Bullish or Bearish regimes and a separate strategy for Neutral markets.
Optimization : Adjust the lookback period and percentile settings to optimize the clustering algorithm based on your asset’s characteristics.
Conclusion
The Machine Learning Moving Average offers a novel approach to price prediction by leveraging percentile clustering and a dynamically adapting moving average. While not a traditional machine learning model, this tool mimics the adaptive behavior of machine learning by adjusting to evolving market conditions, helping traders predict price movements and identify trends with improved confidence and accuracy.
Trading
Binary Options Gold Scalping [TradingFinder] 1 & 5 Min Strategy🔵 Introduction
In binary options trading, price movements are often driven by the market’s tendency to reach key liquidity zones. These areas include Liquidity, Fair Value Gaps (FVGs), and Order Blocks (OBs), zones where a large number of pending orders are concentrated.
When price reaches one of these zones, it typically enters a Liquidity Sweep phase to collect available liquidity. After this process, the market often reacts sharply, either reversing direction or continuing its move with renewed momentum. Understanding this cycle forms the foundation of most smart money-based binary options strategies.
In this analytical approach, a Liquidity Sweep is usually seen as a False Breakout, often recognized through a distinctive candle confirmation pattern. The pattern appears when price briefly breaks a level to trigger stops, then quickly returns within range. This formation is one of the most reliable reversal signals for short-term trades and plays a central role in many binary options strategies.
After a liquidity sweep, price often returns to Fair Value Gap (FVG) or Order Block (OB) areas to restore balance in the market. These are zones where institutional orders are typically placed, and reactions around them can create high-probability trade setups. In binary options trading, this quick reaction following a sweep and retrace into an FVG or OB provides one of the best entry opportunities for short-term trades.
By combining the concepts of Liquidity Sweep, Fair Value Gap, and Order Block, traders can build a precise binary options strategy based on smart money behavior, allowing them to identify market reversals with greater confidence and enter at the optimal moment.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator is built on the Smart Money Concept (SMC) framework and serves as a core tool for accurately detecting Liquidity Sweeps, Order Blocks, and Fair Value Gaps in binary options trading.
Its logic is simple yet powerful : when price reaches high-interest liquidity zones and shows reversal signs, the indicator issues an entry signal immediately after a Candle Confirmation is complete.
Signals only activate when both the market structure and the candle confirmation pattern align, ensuring high accuracy in spotting genuine reversals.
🟣 Long Position
A bullish signal appears when the market, after a downward move, reaches sell-side liquidity zones where liquidity has built up below previous lows. In such conditions, a bullish Order Block or Fair Value Gap often exists in the same region, acting as a potential reversal point.
When the indicator detects the presence of liquidity, an imbalance zone (FVG), and a valid candle confirmation simultaneously, it triggers a green Call signal.
In a binary options strategy, the best entry moment is immediately after the candle confirmation closes, as this is when the probability of reversal is highest and the market tends to react strongly within the next few candles.
In the example below, after the liquidity sweep and candle confirmation, price quickly rallied, resulting in a Binary Win setup.
🟣 Short Position
A bearish signal occurs when price, after an upward move, reaches an area of buy-side liquidity and collects liquidity above recent highs. At this stage, the market is typically overbought and ready to reverse. If a bearish Order Block or Fair Value Gap exists in the same area and a candle confirmation pattern forms, the indicator displays a red Put signal.
This setup is highly accurate because multiple structural confirmations occur simultaneously : liquidity has been absorbed, price is rebalancing, and the confirmation candle has closed.
In binary options trading, this is the ideal moment to enter a Put (Sell) position, as the price reaction to the downside is usually quick and decisive.
In the example chart, the indicator generated a bearish signal right after the candle confirmation and completion of the liquidity sweep, price then dropped within minutes, resulting in another Binary Win.
🔵 Settings
Time Frame : Select the desired timeframe for analysis. If left blank, the indicator uses the chart’s current timeframe.
Swing Period : Defines how many candles are used to detect structural pivots (swing highs and lows). A higher value increases accuracy but reduces the number of signals.
Candle Pattern : Enables candle-based confirmation logic. When turned on, the indicator issues signals only if a valid reversal pattern is detected. You can also choose the confirmation filter strength, tighter filters show fewer but more precise signals.
🔵 Conclusion
A deep understanding of Liquidity Sweeps, Order Blocks, and Fair Value Gaps can make a decisive difference between ordinary and professional traders in the binary options market.
This indicator, combining smart money logic with candle confirmation, is one of the most precise tools for detecting true market reversals. When liquidity is collected and structural reversal signs emerge, the indicator automatically recognizes the price reaction and generates a reliable Call or Put signal.
Using this tool alongside market structure analysis and FVG detection allows traders to enter high-probability setups while filtering out false breakouts. For that reason, this binary options strategy is not only suitable for short-term trading but also valuable for understanding deeper smart-money behavior across timeframes.
Ultimately, success with this system comes down to two key principles: understanding the logic of the liquidity sweep and waiting for the candle confirmation to close. When these two conditions align, the indicator can pinpoint the best entry points with remarkable precision, helping you build a structured, intelligent, and profitable binary options strategy.
PO3 Entry 15m + Time Lines - Range Logic TradingPO3 Entry 15m + Time Lines - Professional Indicator for NY Sessions
🎯 DESCRIPTION:
Advanced indicator designed for traders operating in New York sessions. Combines customizable trading zones with key time lines for perfect visual management of your strategy.
🌟 KEY FEATURES:
🕒 STRATEGIC TIME LINES
Vertical lines at key times: 1:00 AM, 5:00 AM, and 9:00 AM (NY Time)
Perfect for identifying 4H candle openings and session changes
Configurable colors and styles (solid, dashed, dotted)
Visible only for the last 5 days to keep charts clean
📊 10 CUSTOMIZABLE TRADING ZONES
10 fully configurable zones with specific time ranges
Each zone displays an expanding box during its active period
Automatic High/Low tracking during zone duration
Informative labels with customizable names
Individual colors and styles for each zone
⚙️ COMPLETE CONFIGURATION:
Time Zone: America/New_York, UTC, Europe/London, Asia/Tokyo
Days to Show: 1-30 days (5 by default)
Individual activation for each zone and time lines
Customizable colors for every element
Line Styles: Solid, Dashed, Dotted
🎨 PROFESSIONAL VISUALIZATION:
Semi-transparent boxes that don't obstruct price action
Extendable lines from top to bottom of chart
Automatic daily reset to prevent accumulation
500 box limit for optimal performance
📈 IDEAL FOR:
NY Session traders (1:00 AM - 12:00 PM EST)
Time-based trading strategies
Visual identification of interest zones
Session management and planning
🛠️ RECOMMENDED USE:
Configure the 10 zones with your trading hours
Activate time lines for visual reference
Adjust colors according to your preference
Set days to display based on your strategy
Optimize your trading with this all-in-one indicator that combines time precision with flexible custom trading zones!
Killzone Session High/Low Levels [SmartFoxy]Killzone Session High/Low Levels
The Killzone Session High/Low Levels indicator by SmartFoxy provides a complete intraday framework for understanding session-based liquidity, market structure rotation, and breakout behavior across global trading sessions.
It automatically plots the High/Low ranges for each selected session, highlights session killzones, and tracks breakout events with optional alerts.
This tool is designed for traders who rely on session dynamics (Asia, Frankfurt, London, New York) to identify liquidity targets, sweep zones, key ranges, and continuation/reversal opportunities.
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How It Works
The indicator detects the active trading sessions for each day and builds structural High/Low ranges for them:
• Asia Session Range (High/Low);
• Frankfurt Session Range;
• London Session Range;
• New York Session Range;
• Optional custom session (NY Open, or any killzone).
For each session, the script can display:
• Session box or column;
• High/Low levels;
• Labels for every range (H/L);
• True session boundaries using user-defined timezone;
• Auto-extended levels up to the latest candle;
• Break levels after a breakout;
• Conditional removal or recoloring after a level is breached.
This gives traders a clean visual map of session liquidity and how price interacts with it throughout the day.
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Key Features
1. Multiple Global Sessions •➤ Asia, Frankfurt, London, New York, plus one custom session for advanced killzone mapping.
2. Session High/Low Liquidity Levels •➤ Automatic plotting of every session’s High and Low, with optional labels and price markers.
3. Session Boxes or Columns •➤ Two display modes allow traders to visualize the session either as a filled box or a clear vertical column.
4. Breakout Logic & Temporary Levels .
When price breaks a session High/Low:
• Levels can be extended for a selected number of bars
• Or removed instantly after a breakout
• Or recolored to highlight the sweep event
This enables clean identification of liquidity grabs, breakouts, and continuation setups.
5. Alerts for Session Breakouts .
Set alerts when price breaks:
• Any session level
• Only levels formed on the current day
Perfect for traders who want real-time notifications of sweeps or key structure breaks.
6. Full Customization
You can configure:
• Session times;
• Timezone;
• Colors;
• Labels;
• Line styles and widths;
• Breakout behavior;
• Killzone range handling.
Everything is adjustable to match any trading style.
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How to Use
1. Enable the sessions you want to track •➤ Asia, Frankfurt, London, New York, or custom.
2. Choose display mode
Box mode for visual range blocks;
Column mode for clean vertical alignment.
3. Enable High/Low Levels .
These act as liquidity magnets and key rejection zones.
4. Turn on Breakout Levels (optional)
Useful for spotting sweeps and continuation setups.
5. Turn on Alerts if you want notifications when price breaks levels.
6. Use session levels as liquidity reference points .
They work exceptionally well with smart money concepts (SMC), ICT, and intraday structure analysis.
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Why This Indicator Is Useful
Shows exactly where liquidity is placed each session;
Highlights market structure transitions as sessions hand over control;
Helps identify stop hunts, sweeps, reversals, and continuation patterns;
Provides real-time alerts for structural breaks;
Organizes the chart and reduces noise;
Works with any intraday timeframe and any market.
This makes it valuable for scalpers, day traders, and SMC/ICT-style analysts.
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Summary
Killzone Session High/Low Levels delivers a complete, highly customizable intraday mapping system based on global trading sessions.
It clarifies the session structure, reveals liquidity targets, and empowers traders to make confident trading decisions using clean, objective market data.
MTF Liquidity Levels Pro (D/W/M) [SmartFoxy]✅ SCRIPT DESCRIPTION (Premium MTF High-Low Levels)
Overview
This indicator automatically plots key High/Low levels across three major timeframes:
Daily (D) , Weekly (W) , and Monthly (M) .
It includes:
• Current period highs/lows (DH/DL, WH/WL, MH/ML);
• Previous period highs/lows (PDH/PDL, PWH/PWL, PMH/PML);
• Open levels (Day Open, Day True Open, Week Open, Month Open);
• Visual elements such as separators, period boxes, labels, and price markers;
• A fully customizable breakout alert system .
The indicator is designed for precise market structure analysis with a focus on liquidity, MTF mechanics, and clean price action.
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How It Works
The script tracks historical High/Low levels on each timeframe and displays:
✅ Current High/Low Levels :
Daily;
Weekly;
Monthly.
✅ Previous High/Low levels from the previous day, week, and month:
PDH / PDL;
PWH / PWL;
PMH / PML.
You can select how many previous levels to display (1, 2, 3…).
✅ Open Levels:
Day Open;
Week Open;
Month Open.
Includes optional True Day Open with time offset.
✅ Visual Period Boxes highlighting each session (Day Box, Week Box, Month Box) to help identify intraday and intraperiod structure.
✅ Vertical Separators for the start of each day, week, and month.
✅ Customizable Labels & Price Markers with positions, sizes, and optional price display.
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Alerts
A flexible alert module is built in:
✅ Breakout of Any Previous Level (D/W/M) •➤ Triggers when price breaks any previous High/Low:
PDH/PDL;
PWH/PWL;
PMH/PML.
✅ Breakout of Previous Level 1 (D/W/M) •➤ Triggers only for the closest previous levels:
PDH1/PDL1;
PWH1/PWL1;
PMH1/PML1.
✅ Custom Breakout •➤ Choose a specific level:
PDH / PDL;
PWH / PWL;
PMH / PML.
and select which level number (1, 2, 3…) the alert should track.
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How to Use
Select which timeframes (D/W/M) to display.
Choose how many previous levels to plot.
Enable Open, Boxes, Separators, or Labels as needed.
Enable True Day Open with offset if required.
Activate Alerts and choose the breakout logic:
• All previous levels;
• Only the nearest level;
• Custom level selection.
Create an alert in TradingView using “Any alert() function call”.
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Why This Indicator Is Useful
✅ Instantly reveals key High/Low liquidity zones across multiple timeframes
✅ Helps synchronize market structure across D/W/M levels
✅ Useful for identifying impulses, breakouts, reversals, and liquidity runs
✅ Highlights levels price frequently revisits
✅ Eliminates the need for additional MTF tools
✅ Alerts automate breakout detection for both intraday and swing traders
Suitable for all markets : Forex, Crypto, Indices, Stocks, Futures.
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
Previous D/W/M HLOCHey traders,
Here's a simple Multi-Timeframe indicator that essentially turns time and price into a box. It'll take the previous high, low, opening price, or closing price from one of the three timeframes of your choice (day, week, or month). For whatever reason I can't get the opening price to function consistently so if you find improvements feel free to let me know, this will help traders who prefer to use opening price over closing price.
Naturally this form of charting is classical and nature and some key figures you could use to study its usage are
- Richard W. Schabacker (1930s)
- Edwards & Magee (1948)
- Peter Brandt
- Stacey Burke (more on the intraday side - typically our preference)
It's usage put plainly:
- Quantifying Accumulation or Distribution
- Revealing Energy Build-Up (Compression)
- Framing Breakouts and False Breakouts
- Structuring Time
- Identifying opportunities to trade a daily, weekly, or monthly range.
Demand/Supply Oscillator_immyDemand/Supply Oscillator, probably the only D/S oscillator on TV which doesn't draw the lines on the chart but to show you the actual reasons behind the price moves.
Concept Overview
A demand/supply oscillator would aim to look for the hidden spots/order which institutes place in small quantities to not to upset the trend and suddenly place one big order to liquidate the retailers and make a final big move.
The lite color candles in histogram shows the hidden demand/supply which is the reason behind the sudden price pullback, even for short period of time.
Measure demand and supply based on volume, price movement, or candle structure
Identify price waves or impulses (e.g., using fractals, zigzag, or swing high/low logic)
Detect hidden demand/supply (e.g., low volume pullbacks or absorption zones)
Plotted on histogram boxes to visualize strength and direction of each wave
What “Hidden Demand” Means?
Hidden demand refers to buying pressure that isn’t immediately obvious from price action — in other words, buyers are active “behind the scenes” even though the price doesn’t yet show strong upward movement.
What Hidden supply Means?
refers to selling pressure that isn’t obvious yet on the price chart. It means smart money (big players) are quietly selling or distributing positions, even though the price might not be dropping sharply yet.
It usually appears when:
The price is pulling back slightly (down candle),
But volume or an oscillator (like RSI, MACD, or OBV) shows bullish strength (e.g., higher low or positive divergence).
That suggests smart money is accumulating (buying quietly) while the public may think it’s just a normal dip.
💹 Price Reaction — Up or Down?
If there is hidden demand, it’s generally a bullish signal → meaning price is likely to go up afterward.
However, on that exact candle, the price may still be down or neutral, because:
Hidden demand is “hidden” — buyers are absorbing supply quietly.
The move up usually comes after the hidden demand signal, not necessarily on the same candle.
📊 Example
Suppose:
Price makes a slightly lower low,
But RSI makes a higher low → this is bullish (hidden) divergence, or “hidden demand.”
➡️ Interpretation:
Smart buyers are stepping in → next few candles likely move up.
The current candle might still be red or show a small body — that’s okay. The key is the shift in underlying strength.
🧭 Quick Summary
Term Meaning Candle Effect Expected Move After
Hidden Demand Buyers active below surface Candle may still go down or stay flat
Hidden Supply Sellers active behind the scenes Price likely to rise soon
🛠️ Key Components
Best results with Price/Action e.g. Use swing high/low or zigzag to segment price into waves.
Optionally apply fractal logic for more refined wave detection
Combine with other indicators (e.g., RSI, OBV) for confirmation
Include zone strength metrics (e.g., “Power Number” as seen in some indicators)
Demand/Supply Calculation
Demand: Strong bullish candles, increasing volume, breakout zones
Supply: Strong bearish candles, volume spikes on down moves
Hidden Demand/Supply: Pullbacks with low volume or absorption candles
Histogram Visualization
Use plot() or plotshape() to draw histogram bars
Color-code bars: e.g., green for demand, red for supply, lite colors for hidden zones
Add alerts for wave transitions or hidden zone detection
How It Works
Demand/Supply: Detected when price moves strongly with volume spikes.
Hidden Zones: Detected when price moves but volume is low (potential absorption).
Histogram Values:
+2: Strong Demand
+1: Hidden Demand
-1: Hidden Supply
-2: Strong Supply
0: Neutral
Feature Demand (Visible) Hidden Demand
Visibility Clearly seen on price charts Subtle, often masked in consolidation
Participants Retail + Institutional Primarily Institutional
Price Behavior Sharp rallies from zone Sideways movement, low volatility
Tools to Identify Candlestick patterns, support zones Volume profile, order flow, price clusters
Risk/Reward Moderate (widely known) High (less crowded, early entry potential)
Kameniczki RSI MASTERKAMENICZKI RSI MASTER is a professional trading indicator based on RSI (Relative Strength Index) with advanced features for precise identification of trading opportunities. The indicator combines classic RSI analysis with intelligent Zig Zag system and smoothing techniques for maximum signal accuracy.
Features:
RSI Analysis with Gradient Display
The indicator displays RSI in the lower panel with color gradient - blue for overbought zones and pink for oversold zones. RSI is calculated with adjustable period (recommended 14 for daily charts, 7-9 for shorter timeframes).
Zig Zag Signal System
Intelligent Zig Zag system generates BUY and SELL signals based on RSI extremes. The system automatically identifies swing points and creates clear visual markings with blue BUY and pink SELL labels.
Smoothing Moving Average
Advanced smoothing techniques supporting SMA, EMA, SMMA, WMA and VWMA. MA is displayed in price chart with dual-color system - blue for rising trend, pink for falling trend.
Bollinger Bands Integration
Optional Bollinger Bands around RSI and price for volatility identification and potential breakouts. Bands automatically adapt to market conditions.
Comprehensive Alert System
Extensive alert system includes Zig Zag signals, RSI levels, MA direction changes, BB touches and combined strong signals for maximum trading accuracy.
Real-Time Trend Analysis
Instant trend identification with priority for actual price direction. System displays current trend (BUY/SELL/WAIT) and risk analysis with visual table.
Risk Management
Automatic volatility and risk level analysis with percentage expression. System identifies high and low risk periods for safer trading.
Recommended Timeframes:
- 1H, 4H, 1D - optimal for swing trading
- 15M, 30M - for day trading
- 1W - for position trading
Success Rate:
- Zig Zag signals: 75-85% accuracy
- Combined strong signals: 80-90% accuracy
- Trend identification: 70-80% accuracy
- Overall system success: 75-85% with proper settings
⚠️ IMPORTANT WARNING: Zig Zag signals may cause repainting on lower timeframes. For live trading, use higher timeframes (15M, 1H+) or wait for signal confirmation to avoid false signals.
The indicator is suitable for all types of traders - from beginners to professionals, with detailed parameter adjustment options according to individual needs.
Volume Surprise [LuxAlgo]The Volume Surprise tool displays the trading volume alongside the expected volume at that time, allowing users to spot unexpected trading activity on the chart easily.
The tool includes an extrapolation of the estimated volume for future periods, allowing forecasting future trading activity.
🔶 USAGE
We define Volume Surprise as a situation where the actual trading volume deviates significantly from its expected value at a given time.
Being able to determine if trading activity is higher or lower than expected allows us to precisely gauge the interest of market participants in specific trends.
A histogram constructed from the difference between the volume and expected volume is provided to easily highlight the difference between the two and may be used as a standalone.
The tool can also help quantify the impact of specific market events, such as news about an instrument. For example, an important announcement leading to volume below expectations might be a sign of market participants underestimating the impact of the announcement.
Like in the example above, it is possible to observe cases where the volume significantly differs from the expected one, which might be interpreted as an anomaly leading to a correction.
🔹 Detecting Rare Trading Activity
Expected volume is defined as the mean (or median if we want to limit the impact of outliers) of the volume grouped at a specific point in time. This value depends on grouping volume based on periods, which can be user-defined.
However, it is possible to adjust the indicator to overestimate/underestimate expected volume, allowing for highlighting excessively high or low volume at specific times.
In order to do this, select "Percentiles" as the summary method, and change the percentiles value to a value that is close to 100 (overestimate expected volume) or to 0 (underestimate expected volume).
In the example above, we are only interested in detecting volume that is excessively high, we use the 95th percentile to do so, effectively highlighting when volume is higher than 95% of the volumes recorded at that time.
🔶 DETAILS
🔹 Choosing the Right Periods
Our expected volume value depends on grouping volume based on periods, which can be user-defined.
For example, if only the hourly period is selected, volumes are grouped by their respective hours. As such, to get the expected volume for the hour 7 PM, we collect and group the historical volumes that occurred at 7 PM and average them to get our expected value at that time.
Users are not limited to selecting a single period, and can group volume using a combination of all the available periods.
Do note that when on lower timeframes, only having higher periods will lead to less precise expected values. Enabling periods that are too low might prevent grouping. Finally, enabling a lot of periods will, on the other hand, lead to a lot of groups, preventing the ability to get effective expected values.
In order to avoid changing periods by navigating across multiple timeframes, an "Auto Selection" setting is provided.
🔹 Group Length
The length setting allows controlling the maximum size of a volume group. Using higher lengths will provide an expected value on more historical data, further highlighting recurring patterns.
🔹 Recommended Assets
Obtaining the expected volume for a specific period (time of the day, day of the week, quarter, etc) is most effective when on assets showing higher signs of periodicity in their trading activity.
This is visible on stocks, futures, and forex pairs, which tend to have a defined, recognizable interval with usually higher trading activity.
Assets such as cryptocurrencies will usually not have a clearly defined periodic trading activity, which lowers the validity of forecasts produced by the tool, as well as any conclusions originating from the volume to expected volume comparisons.
🔶 SETTINGS
Length: Maximum number of records in a volume group for a specific period. Older values are discarded.
Smooth: Period of a SMA used to smooth volume. The smoothing affects the expected value.
🔹 Periods
Auto Selection: Automatically choose a practical combination of periods based on the chart timeframe.
Custom periods can be used if disabling "Auto Selection". Available periods include:
- Minutes
- Hours
- Days (can be: Day of Week, Day of Month, Day of Year)
- Months
- Quarters
🔹 Summary
Method: Method used to obtain the expected value. Options include Mean (default) or Percentile.
Percentile: Percentile number used if "Method" is set to "Percentile". A value of 50 will effectively use a median for the expected value.
🔹 Forecast
Forecast Window: Number of bars ahead for which the expected volume is predicted.
Style: Style settings of the forecast.
My setup [Pro] (fadi)My Setup is a powerful TradingView indicator that visualizes your trading strategy, helping you find high-probability setups with precision and discipline. It combines Higher Timeframe (HTF) context with Lower Timeframe (LTF) entries on a single chart, streamlining your trading process.
What It Does
Tracks your chosen timeframe and its paired higher timeframe for custom trade setups, so you don’t have to stay glued to the screen.
Plots clear Entry, Stop Loss, and Take Profit levels when your conditions align.
Customizes to your strategy with HTF triggers (e.g., sweeps, liquidity grabs) and LTF entries (e.g., Order Blocks, FVGs, Breakers).
Ensures discipline by only showing setups that meet all your rules, eliminating emotional trading and FOMO.
Backtest your edge by visualizing past setups to refine entries, stops, and confluences.
How It Works
Set Your HTF Trigger: Choose a market event like a sweep of a high/low, pivot point, or liquidity grab on the paired higher timeframe (e.g., 1H for a 5m chart).
Define Your LTF Entry: Select your entry model from a range of institutional concepts, such as Order Block, Fair Value Gap (FVG), Inverted FVG (iFVG), Breaker Block, Unicorn Model, and more, on the chart’s timeframe.
Add Confluence Filters: Stack conditions like requiring an FVG + Breaker for higher-probability setups.
See It on Your Chart: When a setup forms, it’s instantly plotted with Entry, Stop Loss, and Take Profit levels based on your Risk-to-Reward ratio.
Key Features
Multi-Timeframe Sync: Pair your chart’s timeframe (e.g., 5m) with a higher timeframe (e.g., 1H) for seamless analysis.
Institutional Tools: Supports a comprehensive suite of ICT concepts, including Order Blocks, FVGs, iFVGs, Breakers, Unicorn Model, and additional entry models.
Custom Risk Management: Set your Stop Loss and Take Profit levels with fixed R:R or measured moves using large range of entry and stop levels.
Session Filtering: Limit setups to specific trading sessions (e.g., London, New York) with timezone support.
Visual Clarity: Displays HTF candles and key levels on your chart for context, with customizable colors and styles.
Alerts: Get notified the moment a valid setup appears, even on live candles.
Who It’s For
Traders who want to systematize their ICT-based strategy on a single chart.
Those seeking to trade with discipline and avoid impulsive decisions.
Anyone looking to backtest and optimize their setups with clear, visual feedback.
Busy traders who need a tool to track their chart while they focus on life.
Why Choose My Setup ?
Save Time: Let the indicator track your chart and its paired timeframe.
Trade Confidently: Only take A+ setups that match your exact rules.
Learn and Improve: Analyze historical setups to refine your strategy.
Disclaimer of Warranties and Limitation of Liability for [My Setup ]
Please read this disclaimer carefully before using the [My Setup ] indicator (hereafter referred to as "the Software").
1. No Financial Advice
The Software is provided for educational and informational purposes only. The data, calculations, and signals generated by the Software are not, and should not be interpreted as, financial advice, investment advice, trading advice, or a recommendation or solicitation to buy, sell, or hold any security or financial instrument.
2. Assumption of Risk You acknowledge that trading and investing are inherently risky activities that carry a high potential for significant financial loss. All actions you take in the market, including but not limited to trade execution and risk management, are your sole responsibility. You agree to use the Software at your own sole risk. The creator shall not be held responsible or liable for any financial losses or damages you may incur as a result of using the Software.
3. No Warranty; "AS IS" Provision
The Software is provided "AS IS" and "AS AVAILABLE", without any warranties of any kind, either express or implied. The creator disclaims all warranties, including, but not limited to, implied warranties of merchantability, fitness for a particular purpose, accuracy, timeliness, completeness, and non-infringement.
The creator does not warrant that the Software will be error-free, uninterrupted, secure, or free of bugs, viruses, or other harmful components. You acknowledge that software is never wholly free from defects, and you are responsible for implementing your own procedures for data accuracy and security.
4. Limitation of Liability
TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT SHALL THE CREATOR, FADI ZEIDAN, BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT, OR OTHERWISE, ARISING FROM, OUT OF, OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
This limitation of liability applies to any and all damages, including but not limited to:
Direct, indirect, incidental, special, consequential, or exemplary damages.
Loss of profits, revenue, data, or use.
Financial losses resulting from trading decisions made based on the Software.
Damages arising from software defects, interruptions, or inaccuracies.
5. Indemnification
You agree to indemnify, defend, and hold harmless the creator, Fadi Zeidan, from and against any and all claims, liabilities, damages, losses, or expenses, including reasonable attorneys' fees and costs, arising out of or in any way connected with your access to or use of the Software.
6. Acknowledgment and Agreement
By accessing, installing, or using the [My Setup ] indicator, you acknowledge that you have read, understood, and agree to be bound by the terms of this disclaimer. If you do not agree with these terms, you must not use the Software.
VWAP Entry Assistant (v1.0)Description:
Anchored VWAP with a lightweight assistant for VWAP reversion trades.
It shows the distance to VWAP, an estimated hit probability for the current bar, the expected number of bars to reach VWAP, and a recommended entry price.
If the chance of touching VWAP is low, the script suggests an adjusted limit using a fraction of ATR.
The VWAP line is white by default, and a compact summary table appears at the bottom-left.
Educational tool. Not financial advice. Not affiliated with TradingView or any exchange. Always backtest before use.
Momentum-Based Fair Value Gaps [BackQuant]Momentum-Based Fair Value Gaps
A precision tool that detects Fair Value Gaps and color-codes each zone by momentum, so you can quickly tell which imbalances matter, which are likely to fill, and which may power continuation.
What is a Fair Value Gap
A Fair Value Gap is a 3-candle price imbalance that forms when the middle candle expands fast enough that it leaves a void between candle 1 and candle 3.
Bullish FVG : low > high . This marks a bullish imbalance left beneath price.
Bearish FVG : high < low . This marks a bearish imbalance left above price.
These zones often act as magnets for mean reversion or as fuel for trend continuation when price respects the gap boundary and runs.
Why add momentum
Not all gaps are equal. This script measures momentum with RSI on your chosen source and paints each FVG with a momentum heatmap. Strong-momentum gaps are more likely to hold or propel continuation. Weak-momentum gaps are more likely to fill.
Core Features
Auto FVG Detection with size filters in percent of price.
Momentum Heatmap per gap using RSI with smoothing. Multiple palettes: Gradient, Discrete, Simple, and scientific schemes like Viridis, Plasma, Inferno, Magma, Cividis, Turbo, Jet, plus Red-Green and Blue-White-Red.
Bull and Bear Modes with independent toggles.
Extend Until Filled : keep drawing live to the right until price fully fills the gap.
Auto Remove Filled for a clean chart.
Optional Labels showing the smoothed RSI value stored at the gap’s birth.
RSI-based Filters : only accept bullish gaps when RSI is oversold and bearish gaps when RSI is overbought.
Performance Controls : cap how many FVGs to keep on chart.
Alerts : new bullish or bearish FVG, filled FVG, and extreme RSI FVGs.
How it works
Source for Momentum : choose Returns, Close, or Volume.
Returns computes percent change over a short lookback to focus on impulse quality.
RSI and Smoothing : RSI length and a small SMA smooth the signal to stabilize the color coding.
Gap Scan : each bar checks for a 3-candle bullish or bearish imbalance that also clears your minimum size filter in percent of price.
Heatmap Color : the gap is painted at creation with a color from your palette based on the smoothed RSI value, preserving the momentum signature that formed it.
Lifecycle : if Extend Unfilled is on, the zone projects forward until price fully trades through the far edge. If Auto Remove is on, a filled gap is deleted immediately.
How to use it
Scan for structure : turn on both bullish and bearish FVGs. Start with a moderate Min FVG Size percent to reduce noise. You will see stacked clusters in trends and scattered singletons in chop.
Read the colors : brighter or stronger palette values imply stronger momentum at gap formation. Weakly colored gaps are lower conviction.
Decide bias : bullish FVGs below price suggest demand footprints. Bearish FVGs above price suggest supply footprints. Use the heatmap and RSI value to rank importance.
Choose your playbook :
Mean reversion : target partial or full fills of opposing FVGs that were created on weak momentum or that sit against higher timeframe context.
Trend continuation : look for price to respect the near edge of a strong-momentum FVG, then break away in the direction of the original impulse.
Manage risk : in continuation ideas, invalidation often sits beyond the opposite edge of the active FVG. In reversion ideas, invalidation sits beyond the gap that should attract price.
Two trade playbooks
Continuation - Buy the hold of a bullish FVG
Context uptrend.
A bullish FVG prints with strong RSI color.
Price revisits the top of the gap, holds, and rotates up. Enter on hold or first higher low inside or just above the gap.
Invalidation: below the gap bottom. Targets: prior swing, measured move, or next LV area.
Reversion - Fade a weak bearish FVG toward fill
Context range or fading trend.
A bearish FVG prints with weak RSI color near a completed move.
Price fails to accelerate lower and rotates back into the gap.
Enter toward mid-gap with confirmation.
Invalidation: above gap top. Target: opposite edge for a full fill, or the gap midline for partials.
Key settings
Max FVG Display : memory cap to keep charts fast. Try 30 to 60 on intraday.
Min FVG Size % : sets a quality floor. Start near 0.20 to 0.50 on liquid markets.
RSI Length and Smooth : 14 and 3 are balanced. Increase length for higher timeframe stability.
RSI Source :
Returns : most sensitive to true momentum bursts
Close : traditional.
Volume : uses raw volume impulses to judge footprint strength.
Filter by RSI Extremes : tighten rules so only the most stretched gaps print as signals.
Heatmap Style and Palette : pick a palette with good contrast for your background. Gradient for continuous feel, Discrete for quick zoning, Simple for binary, Palette for scientific schemes.
Extend Unfilled - Auto Remove : choose live projection and cleanup behavior to match your workflow.
Reading the chart
Bullish zones sit beneath price. Respect and hold of the upper boundary suggests demand. Strong green or warm palette tones indicate impulse quality.
Bearish zones sit above price. Respect and hold of the lower boundary suggests supply. Strong red or cool palette tones indicate impulse quality.
Stacking : multiple same-direction gaps stacked in a trend create ladders. Ladders often act as stepping stones for continuation.
Overlapping : opposing gaps overlapping in a small region usually mark a battle zone. Expect chop until one side is absorbed.
Workflow tips
Map higher timeframe trend first. Use lower timeframe FVGs for entries aligned with the higher timeframe bias.
Increase Min FVG Size percent and RSI length for noisy symbols.
Use labels when learning to correlate the RSI numbers with your palette colors.
Combine with VWAP or moving averages for confluence at FVG edges.
If you see repeated fills and refills of the same zone, treat that area as fair value and avoid chasing.
Alerts included
New Bullish FVG
New Bearish FVG
Bullish FVG Filled
Bearish FVG Filled
Extreme Oversold FVG - bullish
Extreme Overbought FVG - bearish
Practical defaults
RSI Length 14, Smooth 3, Source Returns.
Min FVG Size 0.25 percent on liquid majors.
Heatmap Style Gradient, Palette Viridis or Turbo for contrast.
Extend Unfilled on, Auto Remove on for a clean live map.
Notes
This tool does not predict the future. It maps imbalances and momentum so you can frame trades with clearer context, cleaner invalidation, and better ranking of which gaps matter. Use it with risk control and in combination with your broader process.
Institutional Orderflow Pro — VWAP, Delta, and Liquidity
Institutional Orderflow Pro is a next-generation order flow analysis indicator designed to help traders identify institutional participation, directional bias, and exhaustion zones in real time.
Unlike traditional volume-based indicators, it merges VWAP dynamics, cumulative delta, relative volume, and liquidity proximity into a single unified dashboard that updates tick-by-tick — without repainting.
The indicator is open-source, transparent, and educational. It aims to provide traders with a clearer read on who controls the market — buyers or sellers — and where liquidity lies.
The indicator combines multiple institutional-grade analytics into one framework:
RVOL (Relative Volume) = Compares current volume against the average of recent bars to identify strong institutional participation.
zΔ (Delta Z-Score) = Normalizes the buying/selling delta to reveal unusually aggressive market behavior.
CVDΔ (Cumulative Volume Delta Change) = Shows which side (buyers/sellers) is dominating this bar’s order flow.
VWAP Direction & Slope = Determines whether price is trading above/below VWAP and whether VWAP is trending or flat.
PD Distance (Prev Day Confluence) = Measures the current price’s distance from previous day’s high, low, close, and VWAP in ATR units — highlighting liquidity zones.
ABS/EXH Detection = Identifies institutional absorption and exhaustion patterns where momentum may reverse.
Bias Computation = Combines VWAP direction + slope to give a simplified regime signal: UP, DOWN, or FLAT.
All metrics are displayed through a color-coded, non-repainting HUD:
🟢 = bullish / favorable conditions
🔴 = bearish / weak conditions
⚫ = neutral / flat
🟡 = absorption (potential trap zone)
🟠 = exhaustion (momentum fading)
| Metric | Signal | Meaning |
| ---------------------- | ------- | ---------------------------------------------- |
| **RVOL ≥ 1.3** | 🟢 | High institutional activity — valid setup zone |
| **zΔ ≥ 1.2 / ≤ -1.2** | 🟢 / 🔴 | Unusual buy/sell aggression |
| **CVDΔ > 0** | 🟢 | Buyers dominate this bar |
| **VWAP dir ↑ / ↓** | 🟢 / 🔴 | Institutional bias long/short |
| **Slope ok = YES** | 🟢 | Trending market |
| **PD dist ≤ 0.35 ATR** | 🟢 | Near key liquidity zones |
| **Bias = UP/DOWN** | 🟢 / 🔴 | Trend-aligned environment |
| **ABS/EXH active** | 🟡 / 🟠 | Caution — possible reversal zone |
How to Use
Confirm Volume Context → RVOL > 1.2
Align with Bias → Take longs only when Bias = UP, shorts only when Bias = DOWN.
Check Slope and VWAP Dir → Ensure trending context (Slope = YES).
Confirm CVD and zΔ → Flow should agree with price direction.
Avoid ABS/EXH Triggers → These signal exhaustion or absorption by large players.
Enter Near PD Zones → Ideal trade zones are within 0.35 ATR of prior-day levels.
This multi-factor confirmation reduces noise and focuses only on high-probability institutional setups.
Originality
This script was written from scratch in Pine v6.
It does not reuse existing public indicators except for standard built-ins (ta.vwap, ta.atr, etc.).
The unique combination of delta z-scoring, VWAP slope filtering, and real-time confluence zones distinguishes it from typical orderflow tools or cumulative delta overlays.
The core innovation is its merged real-time HUD that integrates institutional metrics and natural-language feedback directly on the chart, allowing traders to read market context intuitively rather than decode multiple subplots.
Notes & Disclaimers
This indicator does not repaint.
It’s intended for educational and analytical purposes only — not as financial advice or a guaranteed signal system.
Works best on liquid instruments (Futures, Indices, FX majors).
Avoid non-standard chart types (Heikin Ashi, Renko, etc.) for accurate readings.
Open-source, modifiable, and compatible with Pine v6.
Recommended Use
Apply it with clean charts and standard candles for the best clarity.
Use alongside a basic structure or volume profile to contextualize institutional bias zones.
Author: Dhawal Ranka
Category - Orderflow / VWAP / Institutional Analysis
Version: Pine Script™ v6
License: Open Source (Educational Use)
Binary Options Fast Scalping [TradingFinder] M1 & M5 Signals🔵 Introduction
In the structure of financial markets, spiky moments and sudden price movements play a key role in Liquidity Grabs and Market Structure Resets. These movements usually occur after the accumulation of orders in Buy Side or Sell Side Liquidity zones and are accompanied by rapid breaks in the form of Break of Structure (BoS) or Change of Character (CHoCH).
At this stage, the market temporarily moves in the direction of liquidity to trigger counter orders and then enters a Retracement or Pullback phase, a point where professional traders using the Smart Money Concept (SMC) look for candle confirmation to enter with precision.
This strategy is built upon the same logic : an initial spiky move as a signal of institutional or liquidity driven algorithms, followed by a controlled pullback toward areas such as the Order Block, Fair Value Gap (FVG), or Imbalance Zone, and finally an entry based on a strong confirmation candle (Engulf, Rejection, Breaker) that defines the true direction of order flow.
This combination of price behavior, especially on lower timeframes such as M1 or M5, provides an ideal setup for fast Scalping, Micro Structure Trading, and even short term directional prediction in Binary Options Trading.
Since the main focus of this method is on identifying liquidity phases, structural confirmations, and momentum confirmation candles, the trader can design entries with high probability and logical stop loss placement using the concepts of Fractal Market Structure and Multi Timeframe Confirmation.
In the scalping version, the main objective is to capture the move toward the next liquidity pool or opposite demand and supply zone, while in the binary version, only the prediction of the next candle’s direction matters. This strategy inherently operates based on Smart Money Behavior, Liquidity Engineering, and Order Flow Dynamics, allowing the extraction of fast and profitable moves from the internal logic of market structure.
🔵 How to Use
The operational logic of this strategy is based on Liquidity Sweep, Pullback, and Confirmation Candle. The trader should first identify the initial Impulse Move, which is often accompanied by liquidity absorption around Buy Side or Sell Side Liquidity areas. After that, the market enters the Retracement phase and returns to structural zones such as the Order Block or the Fair Value Gap (FVG).
At this point, a position is taken only when a confirmation candle (Engulf, Breaker, or Rejection Candle) closes in the direction of continuation and aligns with the new structure (BOS or CHoCH). Applying this model on lower timeframes offers the highest precision for fast Scalping or for predicting the next candle’s direction in Binary Option trading.
🟣 Bullish Setup
In the bullish setup, the market first forms a spiky upward move with a sudden increase in momentum, indicating the activation of liquidity flow in the Buy Side Liquidity zone. This movement is usually accompanied by a Break of Structure (BOS) to the upside and marks the beginning of the Impulse Move phase. After this move, the price enters the Pullback phase and returns to structural areas such as the Bullish Order Block, Fair Value Gap (FVG), or Mitigation zone.
At this stage, the trader waits for a bullish confirmation candle (Bullish Engulf or Breaker Candle) to validate the end of the retracement. Entry is made at the close of the confirmation candle or on a minor pullback, with the stop loss placed below the Swing Low or below the pullback zone. The target is set at the next Buy Side Liquidity or Equal Highs. In the binary version, only the direction of the next candle matters and the entry takes place immediately after the confirmation candle.
🟣 Bearish Setup
In the bearish setup, the market first forms a spiky downward move, signaling increased selling pressure and liquidity absorption at the Sell Side Liquidity zone. This movement is accompanied by a Break of Structure (BOS) to the downside and represents the beginning of a bearish momentum phase. After the spike, the price enters the Retracement phase and returns to the Bearish Order Block or bearish Fair Value Gap zone. Within these areas, the formation of a bearish confirmation candle (Bearish Engulf, Breaker, or Rejection Candle) validates the continuation of the downtrend.
The entry is taken at the close of the confirmation candle, with the stop loss placed above the Swing High or above the pullback zone, and the target set toward the next Sell Side Liquidity or Equal Lows. In binary applications, only the direction of the next candle is considered and the confirmation candle serves as the entry trigger.
🔵 Conclusion
This strategy, by combining the principles of the Smart Money Concept, Liquidity Dynamics, and Candle Confirmation Logic, offers a precise and multi functional approach to market entry. Its core structure, identifying the initial spiky movement, waiting for a structural pullback, and entering based on a confirmation candle allows quick interpretation of institutional liquidity behavior and provides trading opportunities with high accuracy and controlled risk.
On lower timeframes, this logic becomes a powerful tool for Scalping and Micro Structure Trading, while in binary markets it delivers high success rates due to its focus on predicting the next candle’s direction. Built upon the foundations of Order Flow, Market Structure, and Fractal Liquidity Behavior, this strategy demonstrates that even in the fastest and noisiest market conditions, the order of Smart Money remains observable and exploitable.
Kalman Exponentialy Weighted Moving Average | MisinkoMasterThe Kalman Exponentialy Weighted Moving Average is a technical analysis tool providing users with more responsive and smoother signals, providing crystal-clear signals and giving investors valuable insights on market trends, however it could be used in many cases.
A deeper dive into the indicator:
When going through my creation of strategies, I had stumbled on an indicator called "EWMA", which worked decently, but it was far too simple in my opinion so I decided to combine the EMA & WMA, but with a little more complexity, and it has worked .
I began by learning how both MAs work, I already knew how WMA works, but EMA I did not.
After learning both I found out they were quite simple in principle and that there was a way to combine them in such way that you would get really good signals, however it was way too noisy.
While it could avoid major dumps that were not avoided by most indicators, it would lose that edge because of being too noisy.
After testing out many conditions, combinations & more, the best working one was this one:
WMA > KEWMA = long
WMA < KEWMA = short
I will explain this later, but this gave fast signals, and while it still was noisy it was better then before.
To smooth it out, I started testing price filters => Gaussian Filter and many more were tested out, but they either slowed it down to the point it was no longer of much use, or did not smooth it at all.
After testing the Kalman filter on this thing, I was shocked.
It was just right and made the indicator a lot better, smoothed it and kept most of the responsivness it had.
Now to the big question: "How is it calculated?"
Now first it needs to calculate the Kalman source, which smooths the source which will be used.
After that, we calculate the Weighted Moving Average for " n " period on the Kalman source.
Now that we have our WMA values, we need to calculate " a ".
a is calculated in the following formula:
a = 2/(1+ n )
where n is the user defined length
Now for the last part:
KEWMA = WMAyesterday * (1-a) + WMAtoday * a
This creates a very accurate and reactive indicator, that can prove useful in many uses, beyond those I will and did talk about.
For the trend logic as mentioned before:
Long = WMA > KEWMA
Short = WMA < KEWMA
This worked best, but you might find better ways of using it.
I think that is all I have to say about it, I left it open source so you can all code it in your strategies and play around with it.
Enjoy Gs!
TT ToniTrading Adjustable Price Fee Band [%]Simple but perfectly functional indicator with Trading fee bands.
Crypto Trading is with fees and very small trades often don't make sense due to the fees we need to pay. With this band you can visualize your fees before entering a trade and take smarter decisions for tight daytrading and scalping.
You type in the fee for just one trade, the Taker Fee for a Market Order. The bands show the fees in % times 2, so what you will pay for opening and closing the trade in reality. The band therefore shows the real break-even point, with included payed fees.
It additionally helps taking trading decisions or not with very small trades (Scalping).
You can smooth the bands if you want and you can addtionally show the true datapoints if you prefer smoothend bands. I recommend no bigger smoothing than 2, if you don't want to show the datapoints. Additionally you can fill the band, and of course adjust transperency, colour and all the general TradingView stuff.
Fee Overview in the current market for the indicator input field:
BingX with 10% fee reduction code = 0,045 %
BingX: Normal = 0,050 %
Bitget, ByBit, BitUnix, Blofin, Phemex: Normal = 0,060 %
Bitget, ByBit, BitUnix, Blofin, Phemex: with 20% fee reduction code = 0,048 %
Have fun Trading, Happy Profits!
Greetings
ToniTrading
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
PulseGrid Universal Scalper - Adaptive Pulse and Symmetric SpansInstrument agnostic. Works on any symbol and timeframe supported by TradingView.
Message or hit me up in chat for full access .
Purpose and scope
PulseGrid is a short timeframe strategy designed to read intrabar structure and recent path so that entries align with actionable momentum and context. The strategy is private. The description below provides all the information needed to understand how it behaves, how it sizes risk, how to tune it responsibly, and how to evaluate results without making unrealistic claims. The design is instrument agnostic. It runs on any asset class that prints open high low close bars on TradingView. That includes commodities such as Gold and WTI, currencies, crypto, equity indices, and single stocks. Performance will always depend on the symbol’s liquidity, spread, slippage, and session structure, which is why the description focuses on principles and safe parameter ranges instead of hard promises.
What the strategy does at a glance
It builds a composite entry signal named Pulse from five normalized bar features that reflect short term pressure and follow through.
It applies regime guards that keep the strategy inactive when the tape is either too quiet, too bursty, or too directionally random.
It optionally uses a directional filter where a fast and a slow exponential average must agree and their gap must be material relative to recent true range.
When a signal is allowed, risk is sized using symmetric spans that come from nearby untraded price distances above and below the market. The strategy sets a single stop and a single take profit from those spans.
Lines for entry, stop, and take profit are drawn on the chart. A compact on chart table shows trade counts, win rate, average R per trade, and profit factor for all trades, longs only, and shorts only.
This combination yields entries that are reactive but not chaotic, and risk lines that respect the market’s recent path instead of generic pip or point targets.
Why the design is original and useful
The core originality is the union of a composite entry that adapts to volatility and a geometry based risk model. The entry uses five different viewpoints on the same bar space instead of relying on a single technical indicator. The risk model uses spans that come from actual untraded distance rather than fixed multipliers of a generic volatility measure. The result is a framework that is simple to read on a chart and simple to evaluate, yet it avoids the traps of curve fitting to one symbol or one month of data. Because everything is normalized locally, the same logic translates across asset classes with only modest tuning.
The Pulse composite in detail
Pulse is a weighted blend of the following normalized features.
Impulse imbalance. The script sums upward and downward impulses over a short window. An upward impulse is the extension of highs relative to the prior bar. A downward impulse is the extension of lows relative to the prior bar. The net imbalance, scaled by the local range, captures whether extension pressure is building or fading.
Wick and close location. Inside each bar, the distance between the close and the extremes carries information about rejection or acceptance. A bar that closes near the high with relatively heavier lower wick suggests upward acceptance. A bar that closes near the low with heavier upper wick suggests downward acceptance. A weight controls the contribution of wick skew versus close location so that users can favor reversal or momentum behaviour.
Shock touches. Within the recent range window, touches that occur very near the top decile or bottom decile are marked. A short sliding window counts recent shocks. Frequent top shocks in a rising context suggest supply tests. Frequent bottom shocks in a declining context suggest demand tests. The count is normalized by window length.
Breakout ledger. The script compares current extremes to lagged extremes and keeps a simple count of recent upside and downside breakouts. The difference behaves as a short term polarity meter.
Curvature. A simple second difference in closing price acts as a curvature term. It is normalized by the recent maximum of absolute one bar returns so that the value remains bounded and comparable to other terms.
Pulse is smoothed over a fraction of the main signal length. Smoothing removes impulse spikes without destroying the quick reaction that scalpers need. The absolute value of smoothed Pulse can be used with an adaptive gate so that only the top percentile of energy for the recent environment is eligible for entries. A small floor prevents accidental entries during very quiet periods.
Regime guards that keep the strategy selective
Three guards must all pass before any entry can occur.
Auction Balance Factor. This is the proportion of closes that land inside a mid band of the prior bar’s high to low range. High values indicate balanced chop where breakouts tend to fail. Low values indicate directional conditions. The strategy requires ABF to sit below a user chosen maximum.
Dispersion via a Gini style measure on absolute returns. Very low dispersion means bars are small and uniform. Very high dispersion means a few outsized bars dominate and slippage risk can be elevated. The strategy allows the user to require the dispersion measure to remain inside a band that reflects healthy activity.
Binary entropy of direction. Over the core window, the proportion of up closes is used to compute a simple entropy. Values near one indicate coin flip behaviour. Values near zero indicate one sided sequences. The guard requires entropy below a ceiling so that random directionality does not produce noise entries.
An optional directional filter asks that a fast and a slow exponential average agree on direction and that their gap, when divided by an average true range, exceed a threshold. This filter can be enabled on symbols that trend cleanly and disabled when the composite entry is already selective enough.
Risk sizing with symmetric spans
Instead of fixed points or a pure ATR multiplier, the strategy sizes stops and targets from a pair of spans. The upward span reflects recent untraded distance above the market. The downward span reflects recent untraded distance below the market. Each span is floored by a fallback that comes from the maximum of a short simple range average and a standard average true range. A tick based floor prevents microscopic stops on instruments with high tick precision. An asymmetry cap prevents one span from becoming many times larger than the other. For long entries the stop is a multiple of the downward span and the target is a multiple of the upward span. For short entries the stop is a multiple of the upward span and the target is a multiple of the downward span. This creates a risk box that is symmetric by construction yet adaptive to recent voids and gaps.
Execution, ties, and housekeeping
Entries evaluate at bar close. Exits are tested from the next bar forward. If both stop and target are hit within the same bar, the outcome can be resolved in a consistent way that favors the stop or the target according to a single user setting. A short cooldown in bars prevents flip flops. Users can restrict entries to specific sessions such as London and New York. The chart renders entry, stop, and target lines for each trade so that every action is visible. The table in the top right shows trade counts, take profit and stop counts, win rate, average R per trade, and profit factor for the whole set and by direction.
Defaults and responsible backtesting
The default properties in the script use a realistic initial capital and commission value. Users should also set slippage in the strategy properties to reflect their broker and symbol. Small timeframe trading is sensitive to friction and the strategy description does not claim immunity to that reality. The strategy is intended to be tested on a dataset that produces a meaningful sample of trades. A sample in the range of a hundred trades or more is preferred because variance in short samples can be large. On thin symbols or periods with little regular trading, users should either change timeframe, change sessions, or use more selective thresholds so that the sample contains only liquid scenarios.
Universal usage across markets
The strategy is universal by design. It will run and produce lines on any open high low close series on TradingView. The composite entry is made of normalized parts. The regime guards use proportions and bounded measures. The spans use untraded distance and range floors measured in the local price scale. This allows the same logic to function on a currency pair, a commodity, an index future, a stock, or a crypto pair. What changes is calibration.
A safe approach for universal use is as follows.
Start with the default signal length and wick weight.
If the chart prints many weak signals, enable the directional filter and raise the normalized gap threshold slightly.
If the chart is too quiet, lower the adaptive percentile or, with adaptive off, lower the fixed pulse threshold by a small amount.
If stops are too tight in quiet regimes, raise the fallback span multiplier or raise the minimum tick floor in ticks.
If you observe long one sided days, lower the maximum entropy slightly so that entries only occur when directionality is genuine rather than alternating.
Because the logic is bounded and local, these simple steps carry over across symbols. That is why the strategy can be used literally on any asset that you can load on a TradingView chart. The code does not depend on a specific tick size or a specific exchange calendar. It will still remain true that symbols with higher spread or fewer regular trading hours demand stricter thresholds and larger floors.
Suggested parameter ranges for common cases
These ranges are guidelines for one to five minute bars. They are not promises of performance. They reflect the balance between having enough signals to learn from and keeping noise controlled.
Signal length between 18 and 34 for liquid commodities and large capitalization equities.
Wick weight between 0.30 and 0.50 depending on whether you want reversal recognition or close momentum.
Adaptive gate percentile between 85 and 93 when adaptive is enabled. Fixed threshold between 0.10 and 0.18 when adaptive is disabled. Use a non zero floor so very quiet periods still require some energy.
Auction Balance Factor maximum near 0.70 for symbols with clear session bursts. Slightly higher if you prefer to include more balanced prints.
Dispersion band with a lower bound near 0.18 and an upper bound near 0.68 for most session instruments. Tighten the band if you want to skip very bursty days or very flat days.
Entropy maximum near 0.90 so coin flip phases are filtered. Lower the ceiling slightly if the symbol whipsaws frequently.
Stop multiplier near one and take profit multiplier between two and three for a single target approach. Larger target multipliers reduce hit rate and lengthen holding time.
These are safe starting points across commodities, currencies, indices, equities, and crypto. From there, small increments are preferred over dramatic changes.
How to evaluate responsibly
A clean chart and a direct test process help avoid confusion. Use standard candles for signals and exits. If you use a non standard chart type such as Heikin Ashi or Renko, do so only for visualization and not for the strategy’s signal computation, as those chart types can produce unrealistic fills. Turn off other indicators on the published chart unless they are needed to demonstrate a specific property of this strategy. When you post results or discuss outcomes, include the symbol, timeframe, commission and slippage settings, and the session settings used. This makes the context clear and avoids misleading readers.
When you look at results, consider the following.
The distribution of R per trade. A positive average R with a moderate profit factor suggests that exits are sized appropriately for the symbol.
The balance between long and short sides. The HUD table separates the two so you can see if one side carries the edge for that symbol.
The sensitivity to the tie preference. If many bars hit both stop and take profit, the market is chopping inside the risk box and you may need larger floors or stricter regime guards.
The session effect. Session hours matter for many instruments. Align your session filter with where liquidity and volatility concentrate.
Known limitations and honest warnings
PulseGrid is not a guarantee of future profit. It is a systematic way to read short term structure and to size risk in a way that reflects recent path. It assumes that the data feed reflects the exchange reality. It assumes that slippage and spread are non zero and uses explicit commission and user provided slippage to approximate that. It does not place multiple targets. It does not trail stops. It is not a high frequency system and does not attempt to model queue priority or microsecond fills. On illiquid symbols or very short timeframes outside regular hours, signals will be less reliable. Users are responsible for choosing realistic settings and for evaluating whether the symbol’s conditions are suitable.
First use checklist
Load the symbol and timeframe you care about.
If the instrument has clear sessions, turn on the session filter and select realistic London and New York hours or other sessions relevant to the instrument.
Set commission and slippage in the strategy properties to values that match your broker or exchange.
Run the strategy with defaults. Look at the HUD summary and the lines.
Decide whether to enable the directional filter. If you see frequent reversals around the entry line, enable it and raise the normalized gap threshold slightly.
Adjust the adaptive gate. If the chart floods, raise the percentile. If the chart starves, lower it or use a slightly lower fixed threshold.
Adjust the fallback span multiplier and tick floor so that stops are never microscopic.
Review per session performance. If one session underperforms, restrict entries to the better one.
This simple process takes minutes and transfers to any other symbol.
Why this script is private
The source remains private so that the underlying method and its implementation details are not copied or republished. The description here is complete and self contained so that users can understand the purpose, originality, usage, and limitations without needing to inspect the source. Privacy does not change the strategy’s on chart behavior. It only protects the specific coding details.
Guarantee and compliance statements
This description does not contain advertising, solicitations, links, or contact information. It does not make performance promises. It explains how the script is original and how it works. It also warns about limitations and the need for realistic assumptions. The strategy is not investment advice and is not created only for qualified investors. It can be tested and used for educational and research purposes. Users should read TradingView’s documentation on script properties and backtesting. Users should avoid non standard chart types for signal computation because those produce unrealistic results. Users should select realistic account sizes and friction settings. Users should not post claims without showing the settings used.
Closing summary
PulseGrid is a compact framework for short timeframe trading that combines a composite entry built from multiple normalized bar features with a symmetric span model for risk. The entry adapts to volatility. The regime guards keep the strategy inactive when the tape is either too quiet or too erratic. The risk geometry respects recent untraded spans instead of arbitrary distances. The entire design is instrument agnostic. It will run on any symbol that TradingView supports and it will behave consistently across asset classes with modest tuning. Use it with a clean chart, realistic friction, and enough trades to make your evaluation meaningful. Use sessions if the instrument concentrates activity in specific hours. Adjust one control at a time and prefer small increments. The goal is not to find a magic parameter. The goal is to maintain a stable rule set that reads market structure in a way you can trust and audit.
Bollinger Band Screener [Pineify]Multi-Symbol Bollinger Band Screener Pineify – Advanced Multi-Timeframe Market Analysis
Unlock the power of rapid, multi-asset scanning with this original TradingView Pine Script. Expose trends, volatility, and reversals across your favorite tickers—all in a single, customizable dashboard.
Key Features
Screens up to 8 symbols simultaneously with individual controls.
Covers 4 distinct timeframes per symbol for robust, multi-timeframe analysis.
Integrates advanced Bollinger Band logic, adaptable with 11+ moving average types (SMA, EMA, RMA, HMA, WMA, VWMA, TMA, VAR, WWMA, ZLEMA, and TSF).
Visualizes precise state changes: Open/Parallel Uptrends & Downtrends, Consolidation, Breakouts, and more.
Highly interactive table view for instant signal interpretation and actionable alerts.
Flexible to any market: crypto, stocks, forex, indices, and commodities.
How It Works
For each chosen symbol and timeframe, the script calculates Bollinger Bands using your specified source, length, standard deviation, and moving average method.
Real-time state recognition assigns one of several states (Open Rising, Open Falling, Parallel Rising, Parallel Falling), painting the table with unique color codes.
State detection is rigorously defined: e.g., “Open Rising” is set when both bands and the basis rise, indicating strong up momentum.
All bands, signals, and strategies dynamically update as new bars print or user inputs change.
Trading Ideas and Insights
Identify volatility expansions and compressions instantly, spotting breakouts and breakdowns before they play out.
Spot multi-timeframe confluences—when trends align across several TFs, conviction increases for potential trades.
Trade reversals or continuations based on unique Bollinger Band patterns, such as squeeze-break or persistent parallel moves.
Harness this tool for scalping, swing trading, or systematic portfolio screens—your logic, your edge!
How Multiple Indicators Work Together
This screener’s core strength is its integration of multiple moving average types into Bollinger Band construction, not just standard SMA. Each average adapts the bands’ responsiveness to trend and noise, so traders can select the underlying logic that matches their market environment (e.g., HMA for fast moves or ZLEMA for smoothed lag). Overlaying 4 timeframes per symbol ensures trends, reversals, and volatility shifts never slip past your radar. When all MAs and bands synchronize across symbols and TFs, it becomes easy to separate real opportunity from market noise.
Unique Aspects
Perhaps the most flexible Bollinger Band screener for TradingView—choose from over 10 moving average methods.
Powerful multi-timeframe and multi-asset design, rare among Pine scripts.
Immediate visual clarity with color-coded table cells indicating band state—no need for guesswork or chart clutter.
Custom configuration for each asset and time slice to suit any trading style.
How to Use
Add the script to your TradingView chart.
Use the user-friendly input settings to specify up to 8 symbols and 4 timeframes each.
Customize the Bollinger Band parameters: source (price type), band length, standard deviation, and type of moving average.
Interpret the dashboard: Color codes and “state” abbreviations show you instantly which symbols and timeframes are trending, consolidating, or breaking out.
Take trades according to your strategy, using the screener as a confirmation or primary scan tool.
Customization
Fully customize: symbols, timeframes, source, band length, standard deviation multiplier, and moving average type.
Supports intricate watchlists—anything TradingView allows, this script tracks.
Adapt for cryptos, equities, forex, or derivatives by changing symbol inputs.
Conclusion
The Multi-Symbol Bollinger Band Screener “Pineify” is a comprehensive, SEO-optimized Pine Script tool to supercharge your market scanning, trend spotting, and decision-making on TradingView. Whether you trade crypto, stocks, or forex—its fast, intuitive, multi-timeframe dashboard gives you the informational edge to stay ahead of the market.
Try it now to streamline your trading workflow and see all the bands, all the trends, all the time!
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend
A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model.
Original Script Link
This indicator is built on top of my volume sampling engine. See the base implementation here:
Why Volume Sampling
Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals.
Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally:
filters dead time by skipping low volume chop;
standardizes the information content per bar, improving comparability across regimes;
stabilizes volatility estimates used inside banded indicators;
gives trend and breakout logic cleaner state transitions with fewer micro flips.
What this tool does
It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock.
Core Features
Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user.
Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles.
Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars.
Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme.
Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats.
Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series.
How it works
Sampling
Pick Sampling Method = Volume or Dollar Bars.
Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant.
The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation.
Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic.
Supertrend on the sampled stream
Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle.
Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR .
Apply classic trailing band and direction rules to produce Supertrend and trend state.
Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints.
Reading the display
Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls.
Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1.
Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles.
Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop.
Settings you will use most
Data Settings
Sampling Method - Volume or Dollar Bars.
Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother.
Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes.
Max Stored Samples - Ring buffer limit for performance.
Indicator Settings
SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout.
Supertrend Source - Price field from the synthetic candle.
ATR Period and Factor - Standard Supertrend controls applied on the synthetic series.
Visuals and UI
Show Synthetic Bars - Turn synthetic candles on or off.
Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive.
Mark new samples - Puts a dot when a bucket closes.
Show Time Bars - Overlay regular candles for comparison.
Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction.
Line Width , Colors , and Stats Table toggles.
Some workflow notes:
Trend Following
Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples.
Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars.
Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries.
Breakout and Continuation
Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend.
The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts.
Mean Reversion
In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens.
Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting.
Stats table (top right)
Method and Total Samples - Sampling regime and current synthetic history length.
Current Vol or Dollar and Threshold - Live bucket fill versus the trigger.
Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress.
Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes.
Why this reduces noise
Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs.
Notes and tips
Use Dollar Bars on assets where nominal price varies widely over time or across symbols.
Median filter can resist single burst outliers when setting dynamic thresholds.
If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests.
Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching.
Link again for reference
Original Volume Based Sampling engine:
Bottom line
When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Multiple Symbol Trend Screener [Pineify]Multiple Symbol Trend Screener Pineify – Ultimate Multi-Indicator Scanner for TradingView
Empower your trading with deep market insights across multiple symbols using this feature-rich Pine Script screener. The Multiple Symbol Trend Screener Pineify enables traders to monitor and compare trends, reversals, and consolidations in real-time across the biggest equity symbols on TradingView, through a synergistic blend of popular technical indicators.
Key Features
Monitor up to 15 symbols and their trends simultaneously
Integrates 7 professional-grade indicators: MA Distance, Aroon, Parabolic SAR (PSAR), ADX, Supertrend, Keltner Channel, and BBTrend
Color-coded table display for instant visual assessment
Customizable lookback periods, indicator types, and calculation methods
SEO optimized for multi-symbol trend detection, screener, and advanced TradingView indicator
How It Works
This indicator leverages TradingView’s Pine Script v6 and request.security() to process multiple symbols across selected timeframes. Data populates a dynamic table, updating each cell based on the calculated value of every underlying indicator. MA Distance highlights deviation from moving averages; Aroon flags emerging trend strength; PSAR marks potential trend reversals; ADX assesses trend momentum; Supertrend detects bullish/bearish phases; Keltner Channel and BBTrend offer volatility and power insights.
Set up your preferred symbols and timeframes
Each indicator runs its calculation per symbol using its parameter group
All results are displayed in a table for a comprehensive dashboard view
Trading Ideas and Insights
Traders can use this screener for cross-market comparison, directional bias, entry/exit filtering, and comprehensive trend evaluation. The screener is excellent for swing trading, day trading, and portfolio tracking. It enables confirmation across multiple frameworks — for example, spotting momentum with ADX before confirming direction with Supertrend and PSAR.
Identify correlated movements or divergences across selected assets
Spot synchronized trend changes for basket trading ideas
Filter symbols by volatility, strength, or trend status for precise trade selection
How Multiple Indicators Work Together
The screener’s edge lies in its intelligent correlation of popular indicators. MA Distance measures the proximity to chosen moving averages, ideal for spotting overbought/oversold conditions. Aroon reveals the strength of new price trends, PSAR indicates reversal signals, and ADX quantifies the momentum of these trends. Supertrend provides a directional phase, while Keltner Channel & BBTrend analyze volatility shifts and band compressions. This amalgamation allows for a robust, multi-dimensional market snapshot, capturing details missed by single-indicator tools.
By displaying all key metrics side-by-side, the screener enables holistic decision-making, revealing confluence zones and contradiction areas across multiple tickers and timeframes.
Unique Aspects
Original implementation combining seven independent trend and momentum indicators for each symbol
Rich customization for symbols, timeframes, and all indicator parameters
Intuitive color-coding for quick reading of bullish/bearish/neutral signals
Comprehensive dashboard for instant actionable insights
How to Use
Load the indicator onto your TradingView chart
Go to the script’s settings and input your preferred symbols and relevant timeframes
Set your desired parameters for each indicator group: Moving Average type, Aroon length, PSAR values, ADX smoothing, etc.
Observe the results in the top-right table, then use it to filter candidates and validate trade setups
The screener is suitable for all timeframes and asset classes available on TradingView. Make sure your chart’s timeframe matches the one used in the scanner for optimal accuracy.
Customization
Choose up to 15 symbols to monitor in a single dashboard
Customize lookback periods, indicator types, colors, and display settings
Configure alerting options and thresholds for advanced trade automation
Conclusion
The Multiple Symbol Trend Screener Pineify sets a new standard for multi-asset screening on TradingView. By elegantly merging seven proven technical indicators, the screener delivers powerful trend detection, reversal analysis, and volatility monitoring — all in one dashboard. Take your trading to new heights with in-depth, customizable market surveillance.
