Multi-Timeframe Trend Analysis [BigBeluga]Multi-Timeframe Trend Analysis
A powerful trend-following dashboard designed to help traders monitor and compare trend direction across multiple higher timeframes. By analyzing EMA conditions from five customizable timeframes, this tool gives a clear visual breakdown of short- to long-term trend alignment.
🔵Key Features:
Multi-Timeframe EMA Dashboard:
➣ Displays a table in the top-right corner showing trend direction across 5 user-defined timeframes.
➣ Each row shows whether ema is rising or falling its corresponding EMA for that timeframe.
➣ Green arrows (🢁) indicate uptrends, purple arrows (🢃) signal downtrends.
Custom Timeframe Selection:
➣ Traders can input any 5 timeframes (e.g., 1h, 2h, 3h, etc.) with individual EMA lengths for flexible trend mapping.
➣ The tool auto-adjusts to match and align external timeframe EMAs to the current chart for seamless overlay.
Dynamic Chart Arrows:
➣ On-chart arrows mark when EMA rising or falling EMAs from the current chart timeframe.
➣ Each EMA arrows has a unique transparency level—shorter EMA arrows are more transparent, longer EMA arrows are more vivid. (Hover Mouse over the arrow to see which EMAs it is)
Gradient EMA Plotting:
➣ All five EMAs are plotted with gradually increasing opacity.
➣ Gradient fills between EMAs enhance visual structure, making it easier to track convergence/divergence.
🔵Usage:
Trend Confirmation: Use the dashboard to confirm multi-timeframe trend alignment before entering trades.
Entry Filtering: Avoid countertrend trades by spotting when higher timeframes disagree with the current one.
Momentum Insight: Track the transition of arrows from lighter to stronger opacity to visualize trend shifts over time.
Scalping or Swinging: Customize timeframes depending on your strategy—from intraday scalps to longer-term swings.
Multi-Timeframe Trend Analysis is the ultimate visual companion for traders who want clarity on how price behaves across multiple time horizons. With its smart EMA mapping and dashboard feedback, it keeps you aligned with dominant trend directions and transition zones at all times.
Indicadores e estratégias
RSI Support & Resistance Breakouts with OrderblocksThis tool is an overly simplified method of finding market squeeze and breakout completely based on a dynamic RSI calculation. It is designed to draw out areas of price levels where the market is pushing back against price action leaving behind instances of short term support and resistance levels you otherwise wouldn't see with the common RSI.
It uses the changes in market momentum to determine support and resistance levels in real time while offering price zone where order blocks exist in the short term.
In ranging markets we need to know a couple things.
1. External Zone - It's important to know where the highs and lows were left behind as they hold liquidity. Here you will have later price swings and more false breakouts.
2. Internal Zone - It's important to know where the highest and lowest closing values were so we can see the limitations of that squeeze. Here you will find the stronger cluster of orders often seen as orderblocks.
In this tool I've added a 200 period Smoothed Moving Average as a trend filter which causes the RSI calculation to change dynamically.
Regular Zones - without extending
The Zones draw out automatically but are often too small to work with.
To solve this problem, you can extend the zones into the future up to 40 bars.
This allows for more visibility against future price action.
--------------------------------------------
Two Types of Zones
External Zones - These zones give you positioning of the highest and lowest price traded within the ranging market. This is where liquidity will be swept and often is an ultimate breaking point for new price swings.
How to use them :
External Zones - External zones form at the top of a pullback. After this price should move back into its impulsive wave.
During the next corrective way, if price breaches the top of the previous External Zone, this is a sign of trend weakness. Expect a divergence and trend reversal.
Internal Zones - (OrderBlocks) Current price will move in relation to previous internal zones. The internal zone is where a majority of price action and trading took place. It's a stronger SQUEEZE area. Current price action will often have a hard time closing beyond the previous Internal Zones high or low. You can expect these zones to show you where the market will flip over. In these same internal zones you'll find large rejection candles.
**Important Note** Size Doesn't Matter
The size of the internal zone does not matter. It can be very small and still very powerful.
Once an internal zone has been hit a few times, its often not relevant any longer.
Order Block Zone Examples
In this image you can see the Internal Zone that was untouched had a STRONG price reaction later on.
Internal Zones that were touched multiple times had weak reactions later as price respected them less over time.
Zone Overlay Breakdown
The Zones form and update in real time until momentum has picked up and price begins to trend. However it leaves behind the elements of the inducement area and all the key levels you need to know about for future price action.
Resistance Fakeout : Later on after the zone has formed, price will return to this upper zone of price levels and cause fakeouts. A close above this zone implies the market moves long again.
Midline Equilibrium : This is simply the center of the strongest traded area. We can call this the Point of Control within the orderblock. If price expands through both extremes of this zone multiple times in the future, it eliminates the orderblock.
Support Fakeout : Just like its opposing brother, price will wick through this zone and rip back causing inducement to trap traders. You would need a clear close below this zone to be in a bearish trend.
BARCOLOR or Candle Color: (Optional)
Bars are colored under three conditions
Bullish Color = A confirmed bullish breakout of the range.
Bearish Color = A confirmed bearish breakout of the range.
Squeeze Color = Even if no box is formed a candle or candles can have a squeeze color. This means the ranging market happened within the high and low of that singular candle.
Volumatic Trend [ChartPrime]
A unique trend-following indicator that blends trend logic with volume visualization, offering a dynamic view of market momentum and activity. It automatically detects trend shifts and paints volume histograms at key levels, allowing traders to easily spot strength or weakness within trends.
⯁ KEY FEATURES
Trend Detection System:
Uses a custom combination of weighted EMA (swma) and regular EMA to detect trend direction.
A diamond appears on trend shift, indicating the starting point of a new bullish or bearish phase.
Volume Histogram Zones:
At each new trend, the indicator draws two horizontal zones (top and bottom) and visualizes volume activity within that trend using dynamic histogram candles.
Gradient-Based Candle Coloring:
Candle color is blended with a gradient based on volume intensity. This helps highlight where volume spikes occurred, making it easy to identify pressure points.
Volume Summary Labels:
A label at the end of each trend zone displays two critical values:
- Delta: net volume difference between bullish and bearish bars.
- Total: overall volume accumulated during the trend.
⯁ HOW TO USE
Monitor diamond markers to identify when a new trend begins.
Use volume histogram spikes to assess if the trend is supported by strong volume or lacking participation.
A high delta with strong total volume in a trend indicates institutional support.
Compare gradient strength of candles—brighter areas represent higher-volume trading activity.
Can be used alone or combined with other confirmation tools like structure breaks, liquidity sweeps, or order blocks.
⯁ CONCLUSION
Volumatic Trend gives you more than just trend direction—it provides insight into the force behind it. With volume-graded candles and real-time histogram overlays, traders can instantly assess whether a trend is backed by conviction or fading strength. A perfect tool for swing traders and intraday strategists looking to add volume context to their directional setups.
Deadzone Pro @DaviddTechDeadzone Pro by @DaviddTech – Adaptive Multi-Strategy NNFX Trading System
Deadzone Pro by @DaviddTech is a meticulously engineered trading indicator that strictly adheres to the No-Nonsense Forex (NNFX) methodology. It integrates adaptive trend detection, dual confirmation indicators, advanced volatility filtering, and dynamic risk management into one powerful, visually intuitive system. Ideal for traders seeking precision and clarity, this indicator consistently delivers high-probability trade setups across all market conditions.
🔥 Key Features:
The Setup:
Adaptive Hull Moving Average Baseline: Clearly identifies trend direction using an advanced, gradient-colored Hull MA that intensifies based on trend strength, providing immediate visual clarity.
Dual Confirmation Indicators: Combines Waddah Attar Explosion (momentum detector) and Bull/Bear Power (strength gauge) for robust validation, significantly reducing false entries.
Volatility Filter (ADX): Ensures entries are only made during strong trending markets, filtering out weak, range-bound scenarios for enhanced trade accuracy.
Dynamic Trailing Stop Loss: Implements a SuperTrend-based trailing stop using adaptive ATR calculations, managing risk effectively while optimizing exits.
Dashboard:
💎 Gradient Visualization & User Interface:
Dynamic gradient colors enhance readability, clearly indicating bullish/bearish strength.
Comprehensive dashboard summarizes component statuses, real-time market sentiment, and entry conditions at a glance.
Distinct and clear buy/sell entry and exit signals, with adaptive stop-loss levels visually plotted.
Candlestick coloring based on momentum signals (Waddah Attar) for intuitive market reading.
📈 How to Interpret Signals:
Bullish Signal: Enter when Hull MA baseline trends upward, both confirmation indicators align bullish, ADX indicates strong trend (>25), and price breaks above the previous trailing stop.
Bearish Signal: Enter short or exit long when Hull MA baseline trends downward, confirmations indicate bearish momentum, ADX confirms trend strength, and price breaks below previous trailing stop.
📊 Recommended Usage:
Timeframes: Ideal on 1H, 4H, and Daily charts for swing trading; effective on shorter (5M, 15M) charts for day trading.
Markets: Compatible with Forex, Crypto, Indices, Stocks, and Commodities.
The Entry & Exit:
🎯 Trading Styles:
Choose from three distinct trading modes:
Conservative: Requires full alignment of all indicators for maximum accuracy.
Balanced (Default): Optimized balance between signal frequency and reliability.
Aggressive: Fewer confirmations needed for more frequent trading signals.
📝 Credits & Originality:
Deadzone Pro incorporates advanced concepts inspired by:
Hull Moving Average by @Julien_Eche
Waddah Attar Explosion by @LazyBear
Bull Bear Power by @Pinecoders
ADX methodology by @BeikabuOyaji
This system has been significantly refactored and enhanced by @DaviddTech to maximize synergy, clarity, and usability, standing apart distinctly from its original components.
Deadzone Pro exemplifies precision and discipline, aligning fully with NNFX principles to provide traders with a comprehensive yet intuitive trading advantage.
Correlation Heatmap█ OVERVIEW
This indicator creates a correlation matrix for a user-specified list of symbols based on their time-aligned weekly or monthly price returns. It calculates the Pearson correlation coefficient for each possible symbol pair, and it displays the results in a symmetric table with heatmap-colored cells. This format provides an intuitive view of the linear relationships between various symbols' price movements over a specific time range.
█ CONCEPTS
Correlation
Correlation typically refers to an observable statistical relationship between two datasets. In a financial time series context, it usually represents the extent to which sampled values from a pair of datasets, such as two series of price returns, vary jointly over time. More specifically, in this context, correlation describes the strength and direction of the relationship between the samples from both series.
If two separate time series tend to rise and fall together proportionally, they might be highly correlated. Likewise, if the series often vary in opposite directions, they might have a strong anticorrelation . If the two series do not exhibit a clear relationship, they might be uncorrelated .
Traders frequently analyze asset correlations to help optimize portfolios, assess market behaviors, identify potential risks, and support trading decisions. For instance, correlation often plays a key role in diversification . When two instruments exhibit a strong correlation in their returns, it might indicate that buying or selling both carries elevated unsystematic risk . Therefore, traders often aim to create balanced portfolios of relatively uncorrelated or anticorrelated assets to help promote investment diversity and potentially offset some of the risks.
When using correlation analysis to support investment decisions, it is crucial to understand the following caveats:
• Correlation does not imply causation . Two assets might vary jointly over an analyzed range, resulting in high correlation or anticorrelation in their returns, but that does not indicate that either instrument directly influences the other. Joint variability between assets might occur because of shared sensitivities to external factors, such as interest rates or global sentiment, or it might be entirely coincidental. In other words, correlation does not provide sufficient information to identify cause-and-effect relationships.
• Correlation does not predict the future relationship between two assets. It only reflects the estimated strength and direction of the relationship between the current analyzed samples. Financial time series are ever-changing. A strong trend between two assets can weaken or reverse in the future.
Correlation coefficient
A correlation coefficient is a numeric measure of correlation. Several coefficients exist, each quantifying different types of relationships between two datasets. The most common and widely known measure is the Pearson product-moment correlation coefficient , also known as the Pearson correlation coefficient or Pearson's r . Usually, when the term "correlation coefficient" is used without context, it refers to this correlation measure.
The Pearson correlation coefficient quantifies the strength and direction of the linear relationship between two variables. In other words, it indicates how consistently variables' values move together or in opposite directions in a proportional, linear manner. Its formula is as follows:
𝑟(𝑥, 𝑦) = cov(𝑥, 𝑦) / (𝜎𝑥 * 𝜎𝑦)
Where:
• 𝑥 is the first variable, and 𝑦 is the second variable.
• cov(𝑥, 𝑦) is the covariance between 𝑥 and 𝑦.
• 𝜎𝑥 is the standard deviation of 𝑥.
• 𝜎𝑦 is the standard deviation of 𝑦.
In essence, the correlation coefficient measures the covariance between two variables, normalized by the product of their standard deviations. The coefficient's value ranges from -1 to 1, allowing a more straightforward interpretation of the relationship between two datasets than what covariance alone provides:
• A value of 1 indicates a perfect positive correlation over the analyzed sample. As one variable's value changes, the other variable's value changes proportionally in the same direction .
• A value of -1 indicates a perfect negative correlation (anticorrelation). As one variable's value increases, the other variable's value decreases proportionally.
• A value of 0 indicates no linear relationship between the variables over the analyzed sample.
Aligning returns across instruments
In a financial time series, each data point (i.e., bar) in a sample represents information collected in periodic intervals. For instance, on a "1D" chart, bars form at specific times as successive days elapse.
However, the times of the data points for a symbol's standard dataset depend on its active sessions , and sessions vary across instrument types. For example, the daily session for NYSE stocks is 09:30 - 16:00 UTC-4/-5 on weekdays, Forex instruments have 24-hour sessions that span from 17:00 UTC-4/-5 on one weekday to 17:00 on the next, and new daily sessions for cryptocurrencies start at 00:00 UTC every day because crypto markets are consistently open.
Therefore, comparing the standard datasets for different asset types to identify correlations presents a challenge. If two symbols' datasets have bars that form at unaligned times, their correlation coefficient does not accurately describe their relationship. When calculating correlations between the returns for two assets, both datasets must maintain consistent time alignment in their values and cover identical ranges for meaningful results.
To address the issue of time alignment across instruments, this indicator requests confirmed weekly or monthly data from spread tickers constructed from the chart's ticker and another specified ticker. The datasets for spreads are derived from lower-timeframe data to ensure the values from all symbols come from aligned points in time, allowing a fair comparison between different instrument types. Additionally, each spread ticker ID includes necessary modifiers, such as extended hours and adjustments.
In this indicator, we use the following process to retrieve time-aligned returns for correlation calculations:
1. Request the current and previous prices from a spread representing the sum of the chart symbol and another symbol ( "chartSymbol + anotherSymbol" ).
2. Request the prices from another spread representing the difference between the two symbols ( "chartSymbol - anotherSymbol" ).
3. Calculate half of the difference between the values from both spreads ( 0.5 * (requestedSum - requestedDifference) ). The results represent the symbol's prices at times aligned with the sample points on the current chart.
4. Calculate the arithmetic return of the retrieved prices: (currentPrice - previousPrice) / previousPrice
5. Repeat steps 1-4 for each symbol requiring analysis.
It's crucial to note that because this process retrieves prices for a symbol at times consistent with periodic points on the current chart, the values can represent prices from before or after the closing time of the symbol's usual session.
Additionally, note that the maximum number of weeks or months in the correlation calculations depends on the chart's range and the largest time range common to all the requested symbols. To maximize the amount of data available for the calculations, we recommend setting the chart to use a daily or higher timeframe and specifying a chart symbol that covers a sufficient time range for your needs.
█ FEATURES
This indicator analyzes the correlations between several pairs of user-specified symbols to provide a structured, intuitive view of the relationships in their returns. Below are the indicator's key features:
Requesting a list of securities
The "Symbol list" text box in the indicator's "Settings/Inputs" tab accepts a comma-separated list of symbols or ticker identifiers with optional spaces (e.g., "XOM, MSFT, BITSTAMP:BTCUSD"). The indicator dynamically requests returns for each symbol in the list, then calculates the correlation between each pair of return series for its heatmap display.
Each item in the list must represent a valid symbol or ticker ID. If the list includes an invalid symbol, the script raises a runtime error.
To specify a broker/exchange for a symbol, include its name as a prefix with a colon in the "EXCHANGE:SYMBOL" format. If a symbol in the list does not specify an exchange prefix, the indicator selects the most commonly used exchange when requesting the data.
Note that the number of symbols allowed in the list depends on the user's plan. Users with non-professional plans can compare up to 20 symbols with this indicator, and users with professional plans can compare up to 32 symbols.
Timeframe and data length selection
The "Returns timeframe" input specifies whether the indicator uses weekly or monthly returns in its calculations. By default, its value is "1M", meaning the indicator analyzes monthly returns. Note that this script requires a chart timeframe lower than or equal to "1M". If the chart uses a higher timeframe, it causes a runtime error.
To customize the length of the data used in the correlation calculations, use the "Max periods" input. When enabled, the indicator limits the calculation window to the number of periods specified in the input field. Otherwise, it uses the chart's time range as the limit. The top-left corner of the table shows the number of confirmed weeks or months used in the calculations.
It's important to note that the number of confirmed periods in the correlation calculations is limited to the largest time range common to all the requested datasets, because a meaningful correlation matrix requires analyzing each symbol's returns under the same market conditions. Therefore, the correlation matrix can show different results for the same symbol pair if another listed symbol restricts the aligned data to a shorter time range.
Heatmap display
This indicator displays the correlations for each symbol pair in a heatmap-styled table representing a symmetric correlation matrix. Each row and column corresponds to a specific symbol, and the cells at their intersections correspond to symbol pairs . For example, the cell at the "AAPL" row and "MSFT" column shows the weekly or monthly correlation between those two symbols' returns. Likewise, the cell at the "MSFT" row and "AAPL" column shows the same value.
Note that the main diagonal cells in the display, where the row and column refer to the same symbol, all show a value of 1 because any series of non-na data is always perfectly correlated with itself.
The background of each correlation cell uses a gradient color based on the correlation value. By default, the gradient uses blue hues for positive correlation, orange hues for negative correlation, and white for no correlation. The intensity of each blue or orange hue corresponds to the strength of the measured correlation or anticorrelation. Users can customize the gradient's base colors using the inputs in the "Color gradient" section of the "Settings/Inputs" tab.
█ FOR Pine Script® CODERS
• This script uses the `getArrayFromString()` function from our ValueAtTime library to process the input list of symbols. The function splits the "string" value by its commas, then constructs an array of non-empty strings without leading or trailing whitespaces. Additionally, it uses the str.upper() function to convert each symbol's characters to uppercase.
• The script's `getAlignedReturns()` function requests time-aligned prices with two request.security() calls that use spread tickers based on the chart's symbol and another symbol. Then, it calculates the arithmetic return using the `changePercent()` function from the ta library. The `collectReturns()` function uses `getAlignedReturns()` within a loop and stores the data from each call within a matrix . The script calls the `arrayCorrelation()` function on pairs of rows from the returned matrix to calculate the correlation values.
• For consistency, the `getAlignedReturns()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences.
• A Pine script can execute up to 40 or 64 unique `request.*()` function calls, depending on the user's plan. The maximum number of symbols this script compares is half the plan's limit, because `getAlignedReturns()` uses two request.security() calls.
• This script can use the request.security() function within a loop because all scripts in Pine v6 enable dynamic requests by default. Refer to the Dynamic requests section of the Other timeframes and data page to learn more about this feature, and see our v6 migration guide to learn what's new in Pine v6.
• The script's table uses two distinct color.from_gradient() calls in a switch structure to determine the cell colors for positive and negative correlation values. One call calculates the color for values from -1 to 0 based on the first and second input colors, and the other calculates the colors for values from 0 to 1 based on the second and third input colors.
Look first. Then leap.
BB Breakout + Momentum Squeeze [Strategy]This Strategy is Based on 3 free indicators
- Bollinger Bands Breakout Oscillator: Link
- TTM Squeeze Pro: Link
- Rolling ATR Bands: Link
Bollinger Bands Breakout Oscillator - This tool shows how strong a market trend is by measuring how often prices move outside their normal Bollinger bands range. It helps you see whether prices are strongly moving in one direction or just moving sideways. By looking at how much and how frequently prices push beyond their typical boundaries, you can identify which direction the market is heading over your selected time period.
TM Squeeze Pro - This is a custom version of the TTM Squeeze indicator.
It's designed to help traders spot consolidation phases in the market (when price is coiling or "squeezing") and to catch breakouts early when volatility returns. The logic is based on the relationship between Bollinger Bands and Keltner Channels, combined with a momentum oscillator to show direction and strength.
Rolling ATR Bands - This indicator combines volatility bands (ATR) with momentum and trend signals to show where the market might be breaking out, retesting, or trending. It's highly visual and helpful for traders looking to time entries/exits during trending or volatile moves.
Logic Of the Strategy:
We are going to use the Bollinger Bands Breakout to determine the direction of the market. Than check the Volatility of the price by looking at the TTM Squeeze indicator. And use the ATR Bands to determine dynamic Stop Losses and based on the calculate the Take Profit targets and quantity for each position dynamically.
For the Long Setup:
1. We need to see the that Bull Power (Green line of the Bollinger Bands Breakout Oscilator) is crossing the level of 50.
2. Check the presence of volatility (Green dot based on the TTM Squeeze indicator)
For the Short Setup:
1. We need to see the that Bear Power (Red line of the Bollinger Bands Breakout Oscilator) is crossing the level of 50.
2. Check the presence of volatility (Green dot based on the TTM Squeeze indicator)
Stop Loss is determined by the Lower ATR Band (for the Long entry) and Upper ATR Band (For the Short entry)
Take Profit is 1:1.5 risk reward ration, which means if the Stop loss is 1% the TP target will be 1.5%
Move stop Loss to Breakeven: If the price will go in the direction of the trade for at least half of the Risk Reward target then the stop will automatically be adjusted to the entry price. For Example: the Stop Loss is 1%, the price has move at least 0.5% in the direction of your trade and that will move the Stop Loss level to the Entry point.
You can Adjust the parameters for each indicator used in that script and also adjust the Risk and Money management block to see how the PnL will change.
SanAlgo V3This is an indicator which uses VWAP and ATR indicators.
Buy / Sell signals are plotted with the breakout of ATR deviations and filtered using VWAP.
You can change deviation as per your need.
Alerts have been added to suit your preference.
Explore additional settings, toggle between options
This indicator works on all types of assets, and all timeframes.
Advanced Auto Zones + Smart Buy/Sell SignalsAdvanced Auto Zones + Smart RSI/EMA Signals
This indicator automatically draws dynamic support/resistance zones based on recent price action and confirms Buy/Sell signals using RSI crossovers with EMA trend filtering and candle confirmation.
🟥 Red Zone – Resistance
🟦 Blue Zone – Equilibrium
🟩 Green Zones – Support
✅ Buy Signal: RSI crosses above oversold + price above EMA + bullish candle
❌ Sell Signal: RSI crosses below overbought + price below EMA + bearish candle
Includes customizable zone width/height, real-time alerts, and clean visual design. Ideal for trend traders, scalpers, and zone-based strategies.
Scalping Strategy: EMA + RSIthis is best for 1 to 3 min scalping,this stratagy base on long ema and short ema, i use rsi level 30 to 70, fpr comfarmation .
Smarter Money Concepts - OBs [PhenLabs]📊 Smarter Money Concepts - OBs
Version: PineScript™ v6
📌 Description
Smarter Money Concepts - OBs (Order Blocks) is an advanced technical analysis tool designed to identify and visualize institutional order zones on your charts. Order blocks represent significant areas of liquidity where smart money has entered positions before major moves. By tracking these zones, traders can anticipate potential reversals, continuations, and key reaction points in price action.
This indicator incorporates volume filtering technology to identify only the most significant order blocks, eliminating low-quality signals and focusing on areas where institutional participation is likely present. The combination of price structure analysis and volume confirmation provides traders with high-probability zones that may attract future price action for tests, rejections, or breakouts.
🚀 Points of Innovation
Volume-Filtered Block Detection : Identifies only order blocks formed with significant volume, focusing on areas with institutional participation
Advanced Break of Structure Logic : Uses sophisticated price action analysis to detect legitimate market structure breaks preceding order blocks
Dynamic Block Management : Intelligently tracks, extends, and removes order blocks based on price interaction and time-based expiration
Structure Recognition System : Employs technical analysis algorithms to find significant swing points for accurate order block identification
Dual Directional Tracking : Simultaneously monitors both bullish and bearish order blocks for comprehensive market structure analysis
🔧 Core Components
Order Block Detection : Identifies institutional entry zones by analyzing price action before significant breaks of structure, capturing where smart money has likely positioned before moves.
Volume Filtering Algorithm : Calculates relative volume compared to a moving average to qualify only order blocks formed with significant market participation, eliminating noise.
Structure Break Recognition : Uses price action analysis to detect legitimate breaks of market structure, ensuring order blocks are identified only at significant market turning points.
Dynamic Block Management : Continuously monitors price interaction with existing blocks, extending, maintaining, or removing them based on current market behavior.
🔥 Key Features
Volume-Based Filtering : Filter out insignificant blocks by requiring a minimum volume threshold, focusing only on zones with likely institutional activity
Visual Block Highlighting : Color-coded boxes clearly mark bullish and bearish order blocks with customizable appearance
Flexible Mitigation Options : Choose between “Wick” or “Close” methods for determining when a block has been tested or mitigated
Scan Range Adjustment : Customize how far back the indicator looks for structure points to adapt to different market conditions and timeframes
Break Source Selection : Configure which price component (close, open, high, low) is used to determine structure breaks for precise block identification
🎨 Visualization
Bullish Order Blocks : Blue-colored rectangles highlighting zones where bullish institutional orders were likely placed before upward moves, representing potential support areas.
Bearish Order Blocks : Red-colored rectangles highlighting zones where bearish institutional orders were likely placed before downward moves, representing potential resistance areas.
Block Extension : Order blocks extend to the right of the chart, providing clear visualization of these significant zones as price continues to develop.
📖 Usage Guidelines
Order Block Settings
Scan Range : Default: 25. Defines how many bars the indicator scans to determine significant structure points for order block identification.
Bull Break Price Source : Default: Close. Determines which price component is used to detect bullish breaks of structure.
Bear Break Price Source : Default: Close. Determines which price component is used to detect bearish breaks of structure.
Visual Settings
Bullish Blocks Color : Default: Blue with 85% transparency. Controls the appearance of bullish order blocks.
Bearish Blocks Color : Default: Red with 85% transparency. Controls the appearance of bearish order blocks.
General Options
Block Mitigation Method : Default: Wick, Options: Wick, Close. Determines how block mitigation is calculated - “Wick” uses high/low values while “Close” uses close values for more conservative mitigation criteria.
Remove Filled Blocks : Default: Disabled. When enabled, order blocks are removed once they’ve been mitigated by price action.
Volume Filter
Volume Filter Enabled : Default: Enabled. When activated, only shows order blocks formed with significant volume relative to recent average.
Volume SMA Period : Default: 15, Range: 1-50. Number of periods used to calculate the average volume baseline.
Min. Volume Ratio : Default: 1.5, Range: 0.5-10.0. Minimum volume ratio compared to average required to display an order block; higher values filter out more blocks.
✅ Best Use Cases
Identifying high-probability support and resistance zones for trade entries and exits
Finding optimal stop-loss placement behind significant order blocks
Detecting potential reversal areas where price may react after extended moves
Confirming breakout trades when price clears major order blocks
Building a comprehensive market structure map for medium to long-term trading decisions
Pinpointing areas where smart money may have positioned before major market moves
⚠️ Limitations
Most effective on higher timeframes (1H and above) where institutional activity is more clearly defined
Can generate multiple signals in choppy market conditions, requiring additional filtering
Volume filtering relies on accurate volume data, which may be less reliable for some securities
Recent market structure changes may invalidate older order blocks not yet automatically removed
Block identification is based on historical price action and may not predict future behavior with certainty
💡 What Makes This Unique
Volume Intelligence : Unlike basic order block indicators, this script incorporates volume analysis to identify only the most significant institutional zones, focusing on quality over quantity.
Structural Precision : Uses sophisticated break of structure algorithms to identify true market turning points, going beyond simple price pattern recognition.
Dynamic Block Management : Implements automatic block tracking, extension, and cleanup to maintain a clean and relevant chart display without manual intervention.
Institutional Focus : Designed specifically to highlight areas where smart money has likely positioned, helping retail traders align with institutional perspectives rather than retail noise.
🔬 How It Works
1. Structure Identification Process :
The indicator continuously scans price action to identify significant swing points and structure levels within the specified range, establishing a foundation for order block recognition.
2. Break Detection :
When price breaks an established structure level (crossing below a significant low for bearish breaks or above a significant high for bullish breaks), the indicator marks this as a potential zone for order block formation.
3. Volume Qualification :
For each potential order block, the algorithm calculates the relative volume compared to the configured period average. Only blocks formed with volume exceeding the minimum ratio threshold are displayed.
4. Block Creation and Management :
Valid order blocks are created, tracked, and managed as price continues to develop. Blocks extend to the right of the chart until they are either mitigated by price action or expire after the designated timeframe.
5. Continuous Monitoring :
The indicator constantly evaluates price interaction with existing blocks, determining when blocks have been tested, mitigated, or invalidated, and updates the visual representation accordingly.
💡 Note:
Order Blocks represent areas where institutional traders have likely established positions and may defend these zones during future price visits. For optimal results, use this indicator in conjunction with other confluent factors such as key support/resistance levels, trendlines, or additional confirmation indicators. The most reliable signals typically occur on higher timeframes where institutional activity is most prominent. Start with the default settings and adjust parameters gradually to match your specific trading instrument and style.
Institutional Quantum Momentum Impulse [BullByte]## Overview
The Institutional Quantum Momentum Impulse (IQMI) is a sophisticated momentum oscillator designed to detect institutional-level trend strength, volatility conditions, and market regime shifts. It combines multiple advanced technical concepts, including:
- Quantum Momentum Engine (Hilbert Transform + MACD Divergence + Stochastic Energy)
- Fractal Volatility Scoring (GARCH + Keltner-based volatility)
- Dynamic Adaptive Bands (Self-adjusting thresholds based on efficiency)
- Market Phase Detection (Volume + Momentum alignment)
- Liquidity & Cumulative Delta Analysis
The indicator provides a Z-score normalized momentum reading, making it ideal for mean-reversion and trend-following strategies.
---
## Key Features
### 1. Quantum Momentum Core
- Combines Hilbert Transform, MACD divergence, and Stochastic Energy into a single composite momentum score.
- Normalized using a Z-score for statistical significance.
- Smoothed with EMA/WMA/HMA for cleaner signals.
### 2. Dynamic Adaptive Bands
- Upper/Lower bands adjust based on volatility and efficiency ratio .
- Acts as overbought/oversold zones when momentum reaches extremes.
### 3. Market Phase Detection
- Identifies bullish , bearish , or neutral phases using:
- Volume-Weighted MA alignment
- Fractal momentum extremes
### 4. Volatility & Liquidity Filters
- Fractal Volatility Score (0-100 scale) shows market instability.
- Liquidity Check ensures trades are taken in favorable spread conditions.
### 5. Dashboard & Visuals
- Real-time dashboard with key metrics:
- Momentum strength, volatility, efficiency, cumulative delta, and market regime.
- Gradient coloring for intuitive momentum visualization .
---
## Best Trade Setups
### 1. Trend-Following Entries
- Signal :
- QM crosses above zero + Market Phase = Bullish + ADX > 25
- Cumulative Delta rising (buying pressure)
- Confirmation :
- Efficiency > 0.5 (strong momentum quality)
- Liquidity = High (tight spreads)
### 2. Mean-Reversion Entries
- Signal :
- QM touches upper band + Volatility expanding
- Market Regime = Ranging (ADX < 25)
- Confirmation :
- Efficiency < 0.3 (weak momentum follow-through)
- Cumulative Delta divergence (price high but delta declining)
### 3. Breakout Confirmation
- Signal :
- QM holds above zero after a pullback
- Market Phase shifts to Bullish/Bearish
- Confirmation :
- Volatility rising (expansion phase)
- Liquidity remains high
---
## Recommended Timeframes
- Intraday (5M - 1H): Works well for scalping & swing trades.
- Swing Trading (4H - Daily): Best for trend-following setups.
- Position Trading (Weekly+): Useful for macro trend confirmation.
---
## Input Customization
- Resonance Factor (1.0 - 3.618 ): Adjusts MACD divergence sensitivity.
- Entropy Filter (0.382/0.50/0.618) : Controls stochastic damping.
- Smoothing Type (EMA/WMA/HMA) : Changes momentum responsiveness.
- Normalization Period : Adjusts Z-score lookback.
---
The IQMI is a professional-grade momentum indicator that combines institutional-level concepts into a single, easy-to-read oscillator. It works across all markets (stocks, forex, crypto) and is ideal for traders who want:
✅ Early trend detection
✅ Volatility-adjusted signals
✅ Institutional liquidity insights
✅ Clear dashboard for quick analysis
Try it on TradingView and enhance your trading edge! 🚀
Happy Trading!
- BullByte
(US) Historical Trade WarsHistorical U.S. Trade Wars Indicator
Overview
This indicator visualizes major U.S. trade wars and disputes throughout modern economic history, from the McKinley Tariff of 1890 to recent U.S.-China tensions. This U.S.-focused timeline is perfect for macro traders, economic historians, and anyone looking to understand how America's trade conflicts correlate with market movements.
Features
Comprehensive U.S. Timeline: Covers 130+ years of U.S.-centered trade disputes with historically accurate dates.
Color-Coded Events:
🔴 Red: Marks the beginning of a U.S. trade war or major dispute.
🟡 Yellow: Highlights significant events within a trade conflict.
🟢 Green: Shows resolutions or ends of trade disputes.
Global Partners/Rivals: Tracks U.S. trade relations with China, Japan, EU, Canada, Mexico, Brazil, Argentina, and others.
Country Flags: Uses emoji flags for easy visual identification of nations in trade relations with the U.S.
Major Trade Wars Covered:
McKinley Tariff (1890-1894)
Smoot-Hawley Tariff Act (1930-1934)
U.S.-Europe Chicken War (1962-1974)
Multifiber Arrangement Quotas (1974-2005)
Japan-U.S. Trade Disputes (1981-1989)
NAFTA and Softwood Lumber Disputes
Clinton and Bush-Era Steel Tariffs
Obama-Era China Tire Tariffs
Rare Earth Minerals Dispute (2012-2014)
Solar Panel Dispute (2012-2015)
TPP and TTIP Negotiations
U.S.-China Trade War (2018-present)
Airbus-Boeing Dispute
Usage
Analyze how markets historically responded to trade war initiations and resolutions.
Identify patterns in market behavior during periods of trade tensions.
Use as an overlay with price action to examine correlations.
Perfect companion for macro analysis on daily, weekly, or monthly charts.
About
This indicator is designed as a historical reference tool for traders and economic analysts focusing on U.S. trade policy and its global impact. The dates and events have been thoroughly researched for accuracy. Each label includes emojis to indicate the U.S. and its trade partners/rivals, making it easy to track America's evolving trade relationships across time.
Note: This indicator works best on larger timeframes (daily, weekly, monthly) due to the historical span covered.
False Breakout PRO📌 False Breakout PRO – Enhanced False Breakout Detection Tool
False Breakout PRO is an advanced version of the original "False Breakout (Expo)" indicator by .
This tool is designed to help traders detect bullish and bearish false breakouts with high precision. By offering a more customizable and smarter interface, it helps reduce noise and false signals through various filtering and visualization options.
🔍 How It Works
The script continuously scans for new highs or lows based on a user-defined period.
It identifies false breakouts when price briefly breaks out of a recent high/low but then quickly reverses. These are often seen as market traps, and this indicator aims to highlight them early.
✅ Key Features in the PRO Version
📌 Toggle to display all signals or only the most recent one
💬 Price labels with clean text and optional visibility
📊 Smart summary table for instant signal reference
📈 Auto-extended lines that follow price action
⚡ Lightweight and optimized for speed and real-time responsiveness
🛠 Configurable Settings
False breakout detection period
Signal validity window (how long a signal is considered active)
Smoothing types: Raw (💎), WMA, or HMA
Aggressive mode for early signal generation
Enable or disable:
Price labels
Summary table
Only latest signal mode
⚠️ License Notice
This script is derived from @Zeiierman’s original work and is published under the Creative Commons BY-NC-SA 4.0 license.
🔒 Commercial use is NOT allowed. Attribution to the original author is required.
🇸🇦 False Breakout PRO – أداة متقدمة لكشف الكسر الكاذب
False Breakout PRO هو إصدار مطور من السكريبت الأصلي "False Breakout (Expo)" من تطوير ، وتم تحسينه لتقديم تجربة استخدام أكثر احترافية ومرونة للمستخدمين للكشف عن الكسر الكاذب
🔍 آلية العمل
يقوم السكريبت بمراقبة القمم والقيعان الجديدة بناءً على فترة يتم تحديدها من قبل المستخدم.
ثم يحدد الكسر الكاذب عندما يكسر السعر مستوى مرتفعًا أو منخفضًا ثم يعود بسرعة. هذه الحركة غالبًا ما تكون خداعًا للمضاربين، ويقوم المؤشر بكشفها مبكرًا.
✅ أهم ميزات النسخة PRO
📌 التبديل بين عرض جميع الإشارات أو أحدث إشارة فقط
💬 عرض سعر الإشارة بنص نظيف واختياري
📊 جدول ملخص ذكي لعرض آخر الإشارات بسرعة
📈 تمديد تلقائي للخطوط لمتابعة حركة السعر
⚡ واجهة خفيفة وسريعة ومناسبة للعرض اللحظي
🛠 الإعدادات القابلة للتعديل
فترة تحديد الكسر الكاذب
مدة صلاحية الإشارة
أنواع الفلترة: 💎 خام، WMA، أو HMA
وضع الكشف العدواني (Aggressive)
خيارات العرض:
إظهار أو إخفاء السعر
إظهار أو إخفاء الجدول
عرض آخر إشارة فقط
⚠️ رخصة الاستخدام
تم تطوير هذا السكريبت بالاعتماد على السكريبت الأصلي من @Zeiierman
وهو مرخص بموجب Creative Commons BY-NC-SA 4.0
🔒 الاستخدام التجاري غير مسموح. ويجب نسب الفضل للمطور الأصلي.
Half Causal EstimatorOverview
The Half Causal Estimator is a specialized filtering method that provides responsive averages of market variables (volume, true range, or price change) with significantly reduced time delay compared to traditional moving averages. It employs a hybrid approach that leverages both historical data and time-of-day patterns to create a timely representation of market activity while maintaining smooth output.
Core Concept
Traditional moving averages suffer from time lag, which can delay signals and reduce their effectiveness for real-time decision making. The Half Causal Estimator addresses this limitation by using a non-causal filtering method that incorporates recent historical data (the causal component) alongside expected future behavior based on time-of-day patterns (the non-causal component).
This dual approach allows the filter to respond more quickly to changing market conditions while maintaining smoothness. The name "Half Causal" refers to this hybrid methodology—half of the data window comes from actual historical observations, while the other half is derived from time-of-day patterns observed over multiple days. By incorporating these "future" values from past patterns, the estimator can reduce the inherent lag present in traditional moving averages.
How It Works
The indicator operates through several coordinated steps. First, it stores and organizes market data by specific times of day (minutes/hours). Then it builds a profile of typical behavior for each time period. For calculations, it creates a filtering window where half consists of recent actual data and half consists of expected future values based on historical time-of-day patterns. Finally, it applies a kernel-based smoothing function to weight the values in this composite window.
This approach is particularly effective because market variables like volume, true range, and price changes tend to follow recognizable intraday patterns (they are positive values without DC components). By leveraging these patterns, the indicator doesn't try to predict future values in the traditional sense, but rather incorporates the average historical behavior at those future times into the current estimate.
The benefit of using this "average future data" approach is that it counteracts the lag inherent in traditional moving averages. In a standard moving average, recent price action is underweighted because older data points hold equal influence. By incorporating time-of-day averages for future periods, the Half Causal Estimator essentially shifts the center of the filter window closer to the current bar, resulting in more timely outputs while maintaining smoothing benefits.
Understanding Kernel Smoothing
At the heart of the Half Causal Estimator is kernel smoothing, a statistical technique that creates weighted averages where points closer to the center receive higher weights. This approach offers several advantages over simple moving averages. Unlike simple moving averages that weight all points equally, kernel smoothing applies a mathematically defined weight distribution. The weighting function helps minimize the impact of outliers and random fluctuations. Additionally, by adjusting the kernel width parameter, users can fine-tune the balance between responsiveness and smoothness.
The indicator supports three kernel types. The Gaussian kernel uses a bell-shaped distribution that weights central points heavily while still considering distant points. The Epanechnikov kernel employs a parabolic function that provides efficient noise reduction with a finite support range. The Triangular kernel applies a linear weighting that decreases uniformly from center to edges. These kernel functions provide the mathematical foundation for how the filter processes the combined window of past and "future" data points.
Applicable Data Sources
The indicator can be applied to three different data sources: volume (the trading volume of the security), true range (expressed as a percentage, measuring volatility), and change (the absolute percentage change from one closing price to the next).
Each of these variables shares the characteristic of being consistently positive and exhibiting cyclical intraday patterns, making them ideal candidates for this filtering approach.
Practical Applications
The Half Causal Estimator excels in scenarios where timely information is crucial. It helps in identifying volume climaxes or diminishing volume trends earlier than conventional indicators. It can detect changes in volatility patterns with reduced lag. The indicator is also useful for recognizing shifts in price momentum before they become obvious in price action, and providing smoother data for algorithmic trading systems that require reduced noise without sacrificing timeliness.
When volatility or volume spikes occur, conventional moving averages typically lag behind, potentially causing missed opportunities or delayed responses. The Half Causal Estimator produces signals that align more closely with actual market turns.
Technical Implementation
The implementation of the Half Causal Estimator involves several technical components working together. Data collection and organization is the first step—the indicator maintains a data structure that organizes market data by specific times of day. This creates a historical record of how volume, true range, or price change typically behaves at each minute/hour of the trading day.
For each calculation, the indicator constructs a composite window consisting of recent actual data points from the current session (the causal half) and historical averages for upcoming time periods from previous sessions (the non-causal half). The selected kernel function is then applied to this composite window, creating a weighted average where points closer to the center receive higher weights according to the mathematical properties of the chosen kernel. Finally, the kernel weights are normalized to ensure the output maintains proper scaling regardless of the kernel type or width parameter.
This framework enables the indicator to leverage the predictable time-of-day components in market data without trying to predict specific future values. Instead, it uses average historical patterns to reduce lag while maintaining the statistical benefits of smoothing techniques.
Configuration Options
The indicator provides several customization options. The data period setting determines the number of days of observations to store (0 uses all available data). Filter length controls the number of historical data points for the filter (total window size is length × 2 - 1). Filter width adjusts the width of the kernel function. Users can also select between Gaussian, Epanechnikov, and Triangular kernel functions, and customize visual settings such as colors and line width.
These parameters allow for fine-tuning the balance between responsiveness and smoothness based on individual trading preferences and the specific characteristics of the traded instrument.
Limitations
The indicator requires minute-based intraday timeframes, securities with volume data (when using volume as the source), and sufficient historical data to establish time-of-day patterns.
Conclusion
The Half Causal Estimator represents an innovative approach to technical analysis that addresses one of the fundamental limitations of traditional indicators: time lag. By incorporating time-of-day patterns into its calculations, it provides a more timely representation of market variables while maintaining the noise-reduction benefits of smoothing. This makes it a valuable tool for traders who need to make decisions based on real-time information about volume, volatility, or price changes.
Multi-Factor Reversal AnalyzerMulti-Factor Reversal Analyzer – Quantitative Reversal Signal System
OVERVIEW
Multi-Factor Reversal Analyzer is a comprehensive technical analysis toolkit designed to detect market tops and bottoms with high precision. It combines trend momentum analysis, price action behavior, wave oscillation structure, and volatility breakout potential into one unified indicator.
This tool is ideal for traders seeking to catch reversals, filter false breakouts, and enhance entry/exit timing through a blend of leading and lagging signals. Whether you’re a discretionary trader or building a systematic strategy, this multi-dimensional model provides clarity across market regimes.
IMPLEMENTATION PRINCIPLES
1. Trend Strength Detector
Analyzes price and volume momentum using directional bias and volume-weighted trend scoring to quantify bullish or bearish strength.
2. Price Action Index
Measures trend stability and directional momentum through a composite score based on price volatility, stochastic behavior, and signal-to-noise dispersion metrics.
3. Wave Trend Oscillator
Identifies turning points and potential divergences using normalized smoothed lines and histogram differentials.
4. Volatility Gold Zone
Detects moments of extremely compressed volatility, signaling potential large-move breakout conditions.
5. Multi-Divergence Detection
Tracks regular and hidden bullish/bearish divergences across multiple oscillators for reversal confirmation.
KEY FEATURES
1. Multi-Layer Reversal Logic
• Combines trend scoring, oscillator divergence, and volatility squeezes for triangulated reversal detection.
• Helps traders distinguish between trend pullbacks and true reversals.
2. Advanced Divergence Detection
• Detects both regular and hidden divergences using pivot-based confirmation logic.
• Customizable lookback ranges and pivot sensitivity provide flexible tuning for different market styles.
3. Gold Zone Volatility Compression
• Highlights pre-breakout zones using custom oscillation models (RSI, harmonic, Karobein, etc.).
• Improves anticipation of breakout opportunities following low-volatility compressions.
4. Trend Direction Context
• PAI and Trend Score components provide top-down insight into prevailing bias.
• Built-in “Straddle Area” highlights consolidation zones; breakouts from this area often signal new trend phases.
5. Flexible Visualization
• Color-coded trend bars, reversal markers, normalized oscillator plots, and trend strength labels.
• Designed for both visual discretionary traders and data-driven system developers.
USAGE GUIDELINES
1. Applicable Markets
• Suitable for stocks, crypto, futures, and forex
• Supports reversal, mean-reversion, and breakout trading styles
2. Recommended Timeframes
• Short-term traders: 5m / 15m / 1H — use Wave Trend divergence + Gold Zone
• Swing traders: 4H / Daily — rely on Price Action Index and Trend Detector
• Macro trend context: use PAI HTF mode for higher timeframe overlays
3. Reversal Strategy Flow
• Watch for divergence (WT/PAI) + Gold Zone compression
• Confirm with Trend Score weakening or flipping
• Use Straddle Area breakout for final trigger
• Optional: enable bar coloring or labels for visual reinforcement
• The indicator performs optimally when used in conjunction with a harmonic pattern recognition tool
4. Additional Note on the Gold Zone
The “Gold Zone” does not directly indicate a market bottom. Since it is displayed at the bottom of the chart, it may be misunderstood as a bullish signal. In reality, the Gold Zone represents a compression of price momentum and volatility, suggesting that a significant directional move is about to occur. The direction of that move—upward or downward—should be determined by analyzing the histogram:
• If histogram momentum is weakening, the Gold Zone may precede a downward move.
• If histogram momentum is strengthening, it may signal an upcoming rebound or rally.
Treat the Gold Zone as a warning of impending volatility, and always combine it with trend indicators for accurate directional judgment.
RISK DISCLAIMER
• This indicator calculates trend direction based on historical data and cannot guarantee future market performance. When using this indicator for trading, always combine it with other technical analysis tools, fundamental analysis, and personal trading experience for comprehensive decision-making.
• Market conditions are uncertain, and trend signals may result in false positives or lag. Traders should avoid over-reliance on indicator signals and implement stop-loss strategies and risk management techniques to reduce potential losses.
• Leverage trading carries high risks and may result in rapid capital loss. If using this indicator in leveraged markets (such as futures, forex, or cryptocurrency derivatives), exercise caution, manage risks properly, and set reasonable stop-loss/take-profit levels to protect funds.
• All trading decisions are the sole responsibility of the trader. The developer is not liable for any trading losses. This indicator is for technical analysis reference only and does not constitute investment advice.
• Before live trading, it is recommended to use a demo account for testing to fully understand how to use the indicator and apply proper risk management strategies.
CHANGELOG
v1.0: Initial release featuring integrated Price Action Index, Trend Strength Scoring, Wave Trend Oscillator, Gold Zone Compression Detection, and dual-type divergence recognition. Supports higher timeframe (HTF) synchronization, visual signal markers, and diversified parameter configurations.
⚔️ ScalperX: Trap Sniper Pro
## ⚙️ **ScalperX: Trap Sniper Pro **
This script is a **smart money trap detector** built for scalpers and day traders who want to catch **reversals at liquidity sweeps** — before the big moves start.
It identifies **fakeouts**, **stop hunts**, and **trap wicks** by combining:
- Swing high/low sweeps
- Candle body confirmation
- VWAP bias
- Minimum volatility filter
---
### 🔍 Core Features:
- **Trap Wick Detection**
Detects if price sweeps a recent high or low and immediately rejects — classic liquidity grab behavior.
- **VWAP Trend Bias**
Ensures signals are only taken in the direction of institutional flow.
- **Minimum Movement Filter**
Filters out small or irrelevant candles — only signals when price range exceeds a set percentage (e.g., 0.3%).
- **Visual Debug Markers**
Triangles show sweep zones, circles show valid volatility — so you can see *why* a signal did or didn’t fire.
- **BUY / SELL Labels**
Signals are shown clearly when all trap and trend conditions align.
- **Alerts Built-In**
Set notifications for when trap signals appear in real time.
---
### 🧠 Strategy Logic:
**BUY Trap (Long Entry):**
- Price sweeps a recent low
- Candle closes bullish above VWAP
- Minimum range (e.g., 0.3%)
**SELL Trap (Short Entry):**
- Price sweeps a recent high
- Candle closes bearish below VWAP
- Minimum range (e.g., 0.3%)
---
### 🧪 Ideal For:
- Crypto scalpers (1m, 5m, 15m)
- Stop hunt reversal traders
- Smart money + liquidity-style systems
---
15 Minute Volume Reversal PointsVolume marks reversal points on 15-Minute chart. Tells Support and Resistance Levels.
Multi Oscillator OB/OS Signals v3 - Scope TestIndicator Description: Multi Oscillator OB/OS Signals
Purpose:
The "Multi Oscillator OB/OS Signals" indicator is a TradingView tool designed to help traders identify potential market extremes and momentum shifts by monitoring four popular oscillators simultaneously: RSI, Stochastic RSI, CCI, and MACD. Instead of displaying these oscillators in separate panes, this indicator plots distinct visual symbols directly onto the main price chart whenever specific predefined conditions (typically related to overbought/oversold levels or line crossovers) are met for each oscillator. This provides a consolidated view of potential signals from these different technical tools.
How It Works:
The indicator calculates the values for each of the four oscillators based on user-defined settings (like length periods and price sources) and then checks for specific signal conditions on every bar:
Relative Strength Index (RSI):
It monitors the standard RSI value.
When the RSI crosses above the user-defined Overbought (OB) level (e.g., 70), it plots an "Overbought" symbol (like a downward triangle) above that price bar.
When the RSI crosses below the user-defined Oversold (OS) level (e.g., 30), it plots an "Oversold" symbol (like an upward triangle) below that price bar.
Stochastic RSI:
This works similarly to RSI but is based on the Stochastic calculation applied to the RSI value itself (specifically, the %K line of the Stoch RSI).
When the Stoch RSI's %K line crosses above its Overbought level (e.g., 80), it plots its designated OB symbol (like a downward arrow) above the bar.
When the %K line crosses below its Oversold level (e.g., 20), it plots its OS symbol (like an upward arrow) below the bar.
Commodity Channel Index (CCI):
It tracks the CCI value.
When the CCI crosses above its Overbought level (e.g., +100), it plots its OB symbol (like a square) above the bar.
When the CCI crosses below its Oversold level (e.g., -100), it plots its OS symbol (like a square) below the bar.
Moving Average Convergence Divergence (MACD):
Unlike the others, MACD signals here are not based on fixed OB/OS levels.
It identifies when the main MACD line crosses above its Signal line. This is considered a bullish crossover and is indicated by a specific symbol (like an upward label) plotted below the price bar.
It also identifies when the MACD line crosses below its Signal line. This is a bearish crossover, indicated by a different symbol (like a downward label) plotted above the price bar.
Visualization:
All these signals appear as small, distinct shapes directly on the price chart at the bar where the condition occurred. The shapes, their colors, and their position (above or below the bar) are predefined for each signal type to allow for quick visual identification. Note: In the current version of the underlying code, the size of these shapes is fixed (e.g., tiny) and not user-adjustable via the settings.
Configuration:
Users can access the indicator's settings to customize:
The calculation parameters (Length periods, smoothing, price source) for each individual oscillator (RSI, Stoch RSI, CCI, MACD).
The specific Overbought and Oversold threshold levels for RSI, Stoch RSI, and CCI.
The colors associated with each type of signal (OB, OS, Bullish Cross, Bearish Cross).
(Limitation Note: While settings exist to toggle the visibility of signals for each oscillator individually, due to a technical workaround in the current code, these toggles may not actively prevent the shapes from plotting if the underlying condition is met.)
Alerts:
The indicator itself does not automatically generate pop-up alerts. However, it creates the necessary "Alert Conditions" within TradingView's alert system. This means users can manually set up alerts for any of the specific signals generated by the indicator (e.g., "RSI Overbought Enter," "MACD Bullish Crossover"). When creating an alert, the user selects this indicator, chooses the desired condition from the list provided by the script, and configures the alert actions.
Intended Use:
This indicator aims to provide traders with convenient visual cues for potential over-extension in price (via OB/OS signals) or shifts in momentum (via MACD crossovers) based on multiple standard oscillators. These signals are often used as potential indicators for:
Identifying areas where a trend might be exhausted and prone to a pullback or reversal.
Confirming signals generated by other analysis methods or trading strategies.
Noting shifts in short-term momentum.
Disclaimer: As with any technical indicator, the signals generated should not be taken as direct buy or sell recommendations. They are best used in conjunction with other forms of analysis (price action, trend analysis, volume, fundamental analysis, etc.) and within the framework of a well-defined trading plan that includes risk management. Market conditions can change, and indicator signals can sometimes be false or misleading.
Pullback Entry Zone FinderPullback Entry Zone Finder
Overview:
This indicator is designed to help traders identify potential buying opportunities during short-term pullbacks, particularly when faster-moving averages show signs of converging back towards slower ones. It visually flags potential zones where price might find support and resume its upward movement, based on moving average dynamics and price proximity.
How It Works:
The indicator utilizes four customizable moving averages (Trigger, Short-term, Intermediate, and Long-term) and Average True Range (ATR) to pinpoint specific conditions:
Pullback Detection: It identifies when the fast 'Trigger MA' is below the 'Short-term MA', indicating a potential short-term pullback or consolidation phase.
MA Convergence: Crucially, it looks for signs that the pullback might be weakening by detecting when the gap between the Short-term MA and the Trigger MA is narrowing (maConverging). This suggests the faster average is starting to catch up, potentially preceding a move back up.
Base Buy Zone (Orange Diamond): This signal appears when both the Pullback and Convergence conditions are met simultaneously. It indicates the general area where conditions are becoming favourable for a potential entry.
Refined Entry Zones:
Prime Entry Zone (Green Diamond): This appears within a Base Buy Zone if the bar's low comes within a specified percentage (Max Distance %) of the Short-term MA. It suggests price has pulled back close to the dynamic support of the Short MA.
ATR Entry Zone (Purple Diamond): This appears within a Base Buy Zone if the bar's low comes within the specified percentage (Max Distance %) of an ATR-based target level. This target level (Buy ATR Target Level, plotted as a purple line when active) is calculated by adding a multiple (ATR Multiplier %) of the ATR to the Short-term MA, providing a volatility-adjusted potential entry area.
Visual Elements:
Moving Averages: Four lines representing the Trigger, Short-term, Intermediate, and Long-term MAs (colors and opacity are customizable). Use the Intermediate and Long-term MAs to gauge the broader market trend.
Orange Diamond (Below Bar): Indicates a 'Base Buy Zone' where a pullback and MA convergence are detected.
Green Diamond (Below Bar): Indicates a 'Prime Entry Zone' where price is close to the Short-term MA during a Base Buy Zone.
Purple Diamond (Below Bar): Indicates an 'ATR Entry Zone' where price is close to the ATR-based target level during a Base Buy Zone.
Purple Line: Plots the calculated 'Buy ATR Target Level' only when the Base Buy Zone condition is active.
Input Parameters:
Moving Averages: Customize the Length and Type (EMA, SMA, WMA, VWMA) for all four moving averages.
ATR Settings: Adjust the ATR Length, the ATR Multiplier % (for calculating the target level), and the Max Distance % (for triggering the Prime and ATR Entry Zones).
Visualization: Set the colors for the four Moving Average lines.
How to Use:
Look for the Orange Diamond as the initial signal that pullback/convergence conditions are met.
The Green and Purple Diamonds suggest price has reached potentially more optimal entry levels within that zone, based on proximity to the Short MA or the ATR target, respectively.
Always consider the signals within the context of the broader trend, indicated by the Intermediate and Long-term MAs. This indicator is generally more effective when used to find entries during pullbacks within an established uptrend (e.g., Intermediate MA > Long MA).
Combine these signals with other forms of analysis, such as chart patterns, support/resistance levels, volume analysis, or other indicators for confirmation.
Disclaimer:
You should always use proper risk management techniques and conduct your own analysis before making any trading decisions. This indicator, or any other, will be of no use if you don't have good risk management.
Bright Future Enhanced v2"Bright Future Enhanced v2" Scalping Indicator
This sophisticated Pine Script indicator combines 12+ technical tools for 5-minute scalping, featuring multi-timeframe confirmation, adaptive filters, and professional risk management. Here's the breakdown:
Core Components
Core Components
EWO Hybrid Oscillator
Dual MA ratio (3/21 EMAs or 5/34 SMAs)
Signal line with adjustable delay (3 periods)
Requires 0.05 gap threshold for valid crossover
Trend Quad-Filter System
ADX (6-period) with 25+ strength threshold
Heikin Ashi Smoothed Bias (30-period EMA)
Higher TF ADX alignment (15-min timeframe)
MA Filter (20-period EMA/SMA price position)
Momentum Confirmation
RSI (6-period) with 75/25 thresholds
CCI (6-period) with 75-level cross
Rate of Change (5-period)
Awesome Oscillator (5/34 differential)
Smart Risk Management
ATR-Based Stops
profitTarget = 1.5 * ATR(10) | stopLoss = 1 * ATR(10)
Volatility Filter
Allows trades only when ATR is between 0.3-1.2x of 14-period average
Signal Reset Logic
Cancels opposite positions on counter-signals
Price Up and Down Percentage NACHOMIXCRYPTOThis Pine Script indicator, titled "Price Up and Down Percentage NACHOMIXCRYPTO", is designed to calculate and display the percentage increase and decrease of the price for a given day. Here’s how it works:
1. Indicator Purpose
The indicator tracks the highest and lowest price points of the day.
It calculates the percentage price increase from the lowest price to the current closing price.
It also calculates the percentage price decrease from the highest price to the current closing price.
Additionally, it shows the average change and the combined percentage of both movements.
2. Key Features
Customizable Visuals:
You can adjust the line colors, widths, label colors, and text alignment.
Labels for percentage changes are displayed near the current price.
Daily Highs and Lows:
The indicator resets the lowest and highest price at the start of a new day.
Percentage Calculations:
PriceRise: The percentage change from the day’s lowest price to the current close.
PriceDrop: The percentage change from the day’s highest price to the current close.
AvgChange: The average of the rise and drop percentages.
Total+-: The sum of the price rise and drop, providing a combined market movement view.
3. Visual Representation
Lines:
A green line represents the upward movement (from the lowest price to the current price).
A red line represents the downward movement (from the highest price to the current price).
Labels:
The percentage increase is labeled in green, and the percentage decrease is labeled in red.
The labels are positioned with an adjustable offset for clarity.
Table Display:
A table in the bottom-right corner displays all the calculated values for quick reference.
4. Practical Use
Trend Analysis: Helps identify if the market has shown significant upward or downward movement during the day.
Volatility Assessment: Traders can evaluate the volatility based on the total percentage movement.
Decision Support: Provides a clear indication of how much the price has moved relative to its daily high and low.
Overall, this indicator is useful for intraday traders to monitor price movements and make informed trading decisions.
Delta vs Price Candle DivergenceDelta vs Price Candle Divergence
This indicator highlights potential turning points by identifying single-bar divergences between the direction of the price candle and the net volume delta for that same bar.
How it Works:
* Bearish Candle Divergence (Maroon Background): The background is highlighted when the main price candle closes higher than its open (a "green" price candle), but the net volume delta for that bar is negative (a "red" delta candle). This suggests buying activity lacked strong conviction, or significant selling occurred despite the upward price close.
* Bullish Candle Divergence (Lime Background): The background is highlighted when the main price candle closes lower than its open (a "red" price candle), but the net volume delta for that bar is positive (a "green" delta candle). This suggests selling activity lacked strong conviction, or significant buying occurred despite the downward price close.
The volume delta is calculated by analyzing data from a lower timeframe to approximate the buying and selling volume within each bar of the main chart. You can configure this lower timeframe in the settings; using a smaller timeframe (like the 10-seconds mentioned) provides more granular delta data.
Example Scenario:
Observing the London session today, instances of these divergences might appear. For example, using a 10-second lower timeframe setting for delta calculation, you might see several bars showing a Bearish Candle Divergence (price candle up, delta candle down) near a session high, potentially indicating weakening buying pressure and suggesting a possible reversal setup. Conversely, Bullish Candle Divergences near lows could signal potential exhaustion of selling pressure.
Important Note:
Divergences are signals of potential pressure shifts, not guaranteed reversal indicators. However, when used in conjunction with confirming lower timeframe price action following a signal, they can help identify potentially powerful entry opportunities. Always use these signals alongside other technical analysis methods, price action context, and robust risk management strategies.
Credits:
* The core concept of Volume Delta calculation builds upon the indicator by @TradingView
* Candle divergence logic and background color enhancement credit to smiley1910.
Explore More:
Feel free to check out my other indicators available on TradingView!
Moving Average Shift WaveTrend StrategyOverview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system, designed to be overlayed on TradingView charts. It utilizes conditions based on volatility, session timing, trend direction, and a custom oscillator to trigger trades.
Strategy Objectives
Enter trades in the direction of the prevailing trend and exit on opposite momentum signals.
Filter out false signals using time and volatility constraints.
Employ automatic Take Profit (TP), Stop Loss (SL), and trailing stop mechanisms for risk management.
Key Features
Multiple selectable moving average (MA) types: SMA, EMA, SMMA (RMA), WMA, VWMA.
Combined filters using MA and a custom oscillator.
Time-based and volatility-based trade filtering.
[Trailing stop and custom TP/SL logic.
"In-wave" flag to prevent re-entry during the same trend wave.
Trading Rules
Long Entry Conditions:
Price is above the selected MA.
Oscillator is positive and rising.
Long-term EMA trend is upward.
Trade occurs within allowed session hours and under sufficient volatility.
Not currently in a wave.
Short Entry Conditions:
Price is below the MA.
Oscillator is negative and falling.
Long-term EMA trend is downward.
All other long entry criteria apply.
Exit Conditions:
Hit TP or SL.
Oscillator and MA provide opposing signals.
Trailing stop is triggered.
Risk Management Parameters
Pair : ETH/USD
Timeframe : 4H
Starting Capital : $3,000
Commission : 0.02%
Slippage : 2 pips
Risk per Trade : 5% of account equity (can be adjusted for sustainable practice)
Total Trades : 224 (backtested on selected dataset)
Backtesting range May 24, 2016, 05:00 — Apr 07, 2025, 17:00
Note: Risk parameters are fully configurable and should be tailored to individual trading setups and broker requirements.
Trading Parameters & Considerations
Time Filter : Trades only between 9:00 and 17:00 (exchange time)
Volatility Condition : ATR must exceed its median value
Long-Term Trend Filter : 200-period EMA
MA Settings
MA Type: SMA
Length: 40
Source: hl2
Oscillator Settings
Length: 15
Threshold: 0.5
Risk Settings
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
Visual Support
MA and oscillator color changes offer clear visual signals.
Entry and exit points are visually represented on the chart.
Trailing stops and custom TP/SL conditions are transparently managed.
Strategy Improvements & Uniqueness
In-wave flag prevents overtrading within the same trend phase.
Sophisticated filtering through session, volatility, and trend conditions helps reduce noise.
Dynamic tracking of high/low since entry allows precise trailing stop placement.
Inspirations & Attribution
This strategy is inspired by the excellent work of:
ChartPrime – “Moving Average Shift”
Leveraging the Moving Average Shift technique for intuitive signal generation.
Summary
The Moving Average Shift WaveTrend Strategy is a robust trend-following system that operates based on the alignment of multiple filters and signals. With built-in time and volatility constraints and clear risk management logic, it minimizes the need for discretionary decision-making, offering a consistent and stable trading environment.
