RSI Distribution [Kodexius]RSI Distribution is a statistics driven visualization companion for the classic RSI oscillator. In addition to plotting RSI itself, it continuously builds a rolling sample of recent RSI values and projects their distribution as a forward drawn histogram, so you can see where RSI has spent most of its time over the selected lookback window.
The indicator is designed to add context to oscillator readings. Instead of only treating RSI as a single point estimate that is either “high” or “low”, you can evaluate the current RSI level relative to its own recent history. This makes it easier to recognize when the market is operating inside a familiar regime, and when RSI is pushing into rarer tail conditions that tend to appear during momentum bursts, exhaustion, or volatility expansion.
To complement the histogram, the script can optionally overlay a Gaussian curve fitted to the sample mean and standard deviation. It also runs a Jarque Bera normality check, based on skewness and excess kurtosis, and surfaces the result both visually and in a compact dashboard. On the oscillator panel itself, RSI is presented with a clean gradient line and standard overbought and oversold references, with fills that become more visible when RSI meaningfully extends beyond key thresholds.
🔹 Features
1. Distribution Histogram of Recent RSI Values
The script stores the last N RSI values in an internal sample and uses that rolling window to compute a frequency distribution across a user selected number of bins. The histogram is drawn into the future by a configurable width in bars, which keeps it readable and prevents it from colliding with the active RSI plot. The result is a compact visual summary of where RSI clusters most often, whether it is spending more time near the center, or shifting toward higher or lower regimes.
2. Gaussian Overlay for Shape Intuition
If enabled, a fitted bell curve is drawn on top of the histogram using the sample mean and standard deviation. This overlay is not intended as a direct trading signal. Its purpose is to provide a fast visual comparator between the empirical RSI distribution and a theoretical normal shape. When the histogram diverges strongly from the curve, you can quickly spot skew, heavy tails, or regime changes that often occur when market structure or volatility conditions shift.
3. Jarque Bera Normality Check With Clear PASS/FAIL Feedback
The script computes skewness and excess kurtosis from the RSI sample, then forms the Jarque Bera statistic and compares it to a fixed 95% critical value. When the distribution is closer to normal under this test, the status is marked as PASS, otherwise it is marked as FAIL. This result is displayed in the dashboard and can also influence the histogram styling, giving immediate feedback about whether the recent RSI behavior resembles a bell shaped distribution or a more distorted, regime driven profile.
Jarque Bera is a goodness of fit test that evaluates whether a dataset looks consistent with a normal distribution by checking two shape properties: skewness (asymmetry) and kurtosis (tail heaviness, expressed here as excess kurtosis where a perfect normal has 0). Under the null hypothesis of normality, skewness should be near 0 and excess kurtosis should be near 0. The test combines deviations in both into a single statistic, which is then compared to a chi square threshold. A PASS in this script means the sample does not show strong evidence against normality at the chosen threshold, while a FAIL means the sample is meaningfully skewed, heavy tailed, or both. In practical trading terms, a FAIL often suggests RSI is behaving in a regime where extremes and asymmetry are more common, which is typical during strong trends, volatility expansions, or one sided market pressure. It is still a statistical diagnostic, not a prediction tool, and results can vary with lookback length and market conditions.
4. Integrated Stats Dashboard
A compact table in the top right summarizes key distribution moments and the normality result: Mean, StdDev, Skewness, Kurtosis, and the JB statistic with PASS/FAIL text. Skewness is color coded by sign to quickly distinguish right skew (more time at higher RSI) versus left skew (more time at lower RSI), which can be helpful when diagnosing trend bias and momentum persistence.
5. RSI Visual Quality and Context Zones
RSI is plotted with a gradient color scheme and standard overbought and oversold reference lines. The overbought and oversold areas are filled with a smart gradient so visual emphasis increases when RSI meaningfully extends beyond the 70 and 30 regions, improving readability without overwhelming the panel.
🔹 Calculations
This section summarizes the main calculations and transformations used internally.
1. RSI Series
RSI is computed from the selected source and length using the standard RSI function:
rsi_val = ta.rsi(rsi_src, rsi_len)
2. Rolling Sample Collection
A float array stores recent RSI values. Each bar appends the newest RSI, and if the array exceeds the configured lookback, the oldest value is removed. Conceptually:
rsi_history.push(rsi_val)
if rsi_history.size() > lookback
rsi_history.shift()
This maintains a fixed size window that represents the most recent RSI behavior.
3. Mean, Variance, and Standard Deviation
The script computes the sample mean across the array. Variance is computed as sample variance using (n - 1) in the denominator, and standard deviation is the square root of that variance. These values serve both the dashboard display and the Gaussian overlay parameters.
4. Skewness and Excess Kurtosis
Skewness is calculated from the standardized third central moment with a small sample correction. Kurtosis is computed as excess kurtosis (kurtosis minus 3), so the normal baseline is 0. These two metrics summarize asymmetry and tail heaviness, which are the core ingredients for the Jarque Bera statistic.
5. Jarque Bera Statistic and Decision Rule
Using skewness S and excess kurtosis K, the Jarque Bera statistic is computed as:
JB = (n / 6.0) * (S^2 + 0.25 * K^2)
Normality is flagged using a fixed critical value:
is_normal = JB < 5.991
This produces a simple PASS/FAIL classification suitable for fast chart interpretation.
6. Histogram Binning and Scaling
The RSI domain is treated as 0 to 100 and divided into a configurable number of bins. Bin size is:
bin_size = 100.0 / bins
Each RSI sample maps to a bin index via floor(rsi / bin_size), with clamping to ensure the index stays within valid bounds. The script counts occurrences per bin, tracks the maximum frequency, and normalizes each bar height by freq/max_freq so the histogram remains visually stable and comparable as the window updates.
7. Gaussian Curve Overlay (Optional)
The Gaussian overlay uses the normal probability density function with mu as the sample mean and sigma as the sample standard deviation:
normal_pdf(x) = (1 / (sigma * sqrt(2*pi))) * exp(-0.5 * ((x - mu)/sigma)^2)
For drawing, the script samples x across the histogram width, evaluates the PDF, and normalizes it relative to its peak so the curve fits within the same visual height scale as the histogram.
Pesquisar nos scripts por "top"
FVG MTF Consensus OscillatorFVG MTF Consensus Oscillator
A multi-timeframe, multi-component oscillator that combines momentum, deviation, and slope analysis across multiple timeframes using Zeiierman's Chebyshev-filtered trend calculation. This indicator identifies potential turning points with zone-based signal classification and timeframe consensus filtering.
Backed by ML/Deep Learning evaluation on ES Futures data from 2015-2024.
🎯 Concept
Traditional oscillators suffer from two major weaknesses:
Single measurement - relying on one metric makes them susceptible to noise
Single timeframe - missing the bigger picture leads to fighting the trend
The FVG MTF Consensus Oscillator addresses both issues by combining three independent measurements across three timeframes into a weighted consensus signal.
The Three Components
Momentum - How fast is the trend moving?
Deviation - How far has price stretched from the trend?
Slope - What is the short-term directional bias?
The Three Timeframes
TF1 (Chart) - Your current chart timeframe (lowest weight)
TF2 (Medium) - Typically 1H or 4H (medium weight)
TF3 (High) - Typically 4H or Daily (highest weight)
By requiring agreement across multiple components AND multiple timeframes, the oscillator filters out noise while capturing meaningful, high-probability market movements.
🔧 How It Works
The Core: Chebyshev Type 1 Filter
At its heart, this indicator uses a Chebyshev Type 1 low-pass filter (inspired by Zeiierman's FVG Trend) to extract a clean trend line from price action. Unlike simple moving averages, the Chebyshev filter offers:
Sharper cutoff between trend and noise
Minimal lag for a given smoothness level
Controlled overshoot via the ripple parameter
Three Oscillator Components
1. Momentum Component
Momentum = Current Trend Value - Previous Trend Value
Measures the velocity of the trend. High positive values indicate strong upward acceleration, while high negative values show downward acceleration.
2. Deviation Component
Deviation = Close Price - Trend Value
Measures how far price has stretched away from the trend line. Useful for identifying overextended conditions and mean reversion opportunities.
3. Slope Component
Slope = Change in Trend over 3 bars
Captures the short-term directional bias of the trend itself, helping confirm trend changes.
Normalization & Component Consensus
Each component is individually normalized to a -100 to +100 scale using adaptive scaling. The oscillator output is a weighted average of all three components, allowing you to emphasize different aspects based on your trading style.
Multi-Timeframe Weighting
The final oscillator value combines all three timeframes using configurable weights:
Combined = (TF1 × Weight1 + TF2 × Weight2 + TF3 × Weight3) / Total Weight
Default weights (1, 2, 3) ensure higher timeframes have more influence, keeping you aligned with the dominant trend while timing entries on lower timeframes.
📊 Zone System
The oscillator uses a fuzzy zone system to classify market conditions:
ZoneRangeInterpretationSignal ColorNeutral-5 to +5No clear bias, avoid tradingGrayContinuation±5 to ±25Trend pullback, continuation setupsAquaDeep Swing±25 to ±50Extended move, stronger setupsGreenReversalBeyond ±50Extreme extension, reversal potentialOrange
When "Show Zone Background" is enabled, the background shading darkens as the oscillator moves into more extreme zones, providing instant visual feedback.
📈 Signal Interpretation
Turn Signals
The indicator plots triangular markers when the oscillator changes direction:
▲ Triangle Up (bottom): Oscillator turning up from a low
▼ Triangle Down (top): Oscillator turning down from a high
Signal Quality by Zone
Not all signals are equal. The signal color indicates which zone the turn occurred in:
ColorZoneProbabilityBest UseGrayNeutralLowAvoid or use very tight stopsAquaContinuationModerateTrend continuation entriesGreenDeep SwingHigherSwing trade entriesOrangeReversalHighestCounter-trend with caution
Timeframe Consensus Filter
Signals only fire when the required number of timeframes agree on direction. With default settings (TF Consensus = 2), at least 2 of 3 timeframes must be moving in the same direction for a signal to trigger.
This prevents:
Taking longs when higher timeframes are bearish
Taking shorts when higher timeframes are bullish
Whipsaws during timeframe disagreement
Trend Coloring
The combined oscillator line changes color based on trend direction:
Light purple (RGB 240, 174, 252): Majority of timeframes trending up
Dark purple (RGB 84, 19, 95): Majority of timeframes trending down
Info Table
When MTF is enabled, a table in the top-right corner displays:
Current oscillator values for each timeframe (TF1, TF2, TF3)
Combined value (CMB)
Color coding: Green = rising, Red = falling
⚙️ Settings Guide
Timeframe Settings
SettingDefaultDescriptionEnable Multi-TimeframeOnMaster switch for MTF functionalityTF1 (Chart)"" (current)First timeframe, typically your chart TFTF2 (Medium)60Second timeframe, typically 1HTF3 (High)240Third timeframe, typically 4HTF1/TF2/TF3 Weight1 / 2 / 3Influence of each TF on combined signal
Timeframe Tips:
Keep TF1 ≤ TF2 ≤ TF3 (ascending order)
For day trading: 5m / 15m / 1H
For swing trading: 1H / 4H / Daily
For position trading: 4H / Daily / Weekly
Display Settings
SettingDefaultDescriptionShow All TimeframesOffDisplay individual TF oscillator linesShow Combined LineOnDisplay the weighted combined oscillatorShow Zone BackgroundOffShade background based on current zone
Trend Filter Settings
SettingDefaultDescriptionTrend Ripple4.0Filter responsiveness (1-10). Higher = faster but more overshootTrend Cutoff0.1Cutoff frequency (0.01-0.5). Lower = smoother trendNormalization Length50Lookback for scaling. Longer = more stable
Component Weights
SettingDefaultDescriptionMomentum Weight1.0Emphasis on trend speedDeviation Weight1.0Emphasis on price stretch from trendSlope Weight1.0Emphasis on short-term trend direction
Component Tips:
For trend-following: Increase Momentum and Slope weights
For mean reversion: Increase Deviation weight
Set any weight to 0 to disable that component
Zone Thresholds
SettingDefaultDescriptionNeutral Zone5Inner boundary (±5 = neutral)Continuation Zone25Middle boundary for continuation setupsDeep Swing Zone50Outer boundary for reversal zone
Adjust based on instrument volatility. More volatile instruments may need wider zones.
Signal Filters
SettingDefaultDescriptionSignal Cooldown3Minimum bars between signalsMin Turn Size2.0Minimum oscillator change for valid turnTF Consensus Required2Minimum TFs agreeing for signal (1-3)
💡 Usage Examples
Example 1: Trend Continuation (Dip Buying)
Setup: Uptrend confirmed by higher timeframes
Check the info table - TF2 and TF3 should show green (rising)
Wait for TF1 to pull back, oscillator enters Continuation zone
Enter on Aqua ▲ signal (turn up with TF consensus)
Stop below recent swing low
Target: Previous high or next resistance
Why it works: You're buying a dip in an established uptrend with multi-timeframe confirmation.
Example 2: Deep Swing Entry
Setup: Extended move showing exhaustion
Oscillator reaches Deep Swing zone (±25 to ±50)
At least 2 TFs start showing the same direction
Enter on Green signal indicating momentum exhaustion
Use tighter stop as the move is already extended
Target: Return to Continuation zone or trend line
Why it works: Extended moves tend to mean-revert. The zone system identifies these opportunities.
Example 3: Reversal Setup (Advanced)
Setup: Extreme extension with diverging timeframes
Oscillator reaches Reversal zone (beyond ±50)
Watch for TF1 to turn while TF3 is still extended
Enter on Orange signal - this is counter-trend!
Use smaller position size and wider stops
Target: Return to Deep Swing or Continuation zone
Why it works: Extreme extensions eventually correct. The orange signal marks high-probability reversal points.
Example 4: Avoiding Bad Trades
What to avoid:
Gray signals in Neutral zone - No edge, random noise
Signals against TF3 direction - Fighting the dominant trend
Signals without TF consensus - Timeframe disagreement = choppy market
Multiple signals in quick succession - Let cooldown filter work
🔬 Multi-Timeframe Analysis Tips
Reading the Info Table
The info table shows real-time oscillator values:
| TF1 | TF2 | TF3 | CMB |
| 23.5 | 45.2 | 67.8 | 52.1 |
All green: Strong uptrend across all timeframes
All red: Strong downtrend across all timeframes
Mixed colors: Potential transition or consolidation
Timeframe Alignment States
TF1TF2TF3Interpretation↑↑↑Strong bull - look for long entries↓↓↓Strong bear - look for short entries↑↑↓Pullback in downtrend - caution on longs↓↓↑Pullback in uptrend - caution on shorts↑↓↑Choppy - reduce position size↓↑↓Choppy - reduce position size
The Power of Consensus
With TF Consensus = 2, signals only fire when 2+ timeframes agree. This single filter eliminates most whipsaws and keeps you aligned with the dominant trend.
For more conservative trading, set TF Consensus = 3 (all timeframes must agree).
⚠️ Important Notes
This indicator does not predict the future. It measures current market conditions and momentum across multiple timeframes.
Always use proper risk management. No indicator is 100% accurate.
Combine with price action. The oscillator works best when confirmed by support/resistance, candlestick patterns, or other confluence factors.
Respect the higher timeframe. When TF3 disagrees, trade smaller or sit out.
Zone signals are probabilistic. Orange (reversal) signals have higher probability but aren't guaranteed reversals.
Adjust settings per instrument. Default settings are optimized for ES Futures but may need tuning for other markets.
🧪 ML/Deep Learning Background
The default parameters and zone thresholds were evaluated using machine learning techniques on ES Futures data spanning 2015-2024. This included:
Optimization of component weights
Zone threshold calibration
Timeframe weight balancing
Signal filter tuning
While past performance doesn't guarantee future results, the parameters represent a data-driven starting point rather than arbitrary defaults.
🙏 Credits
This indicator is inspired by Zeiierman's Multitimeframe Fair Value Gap (FVG) indicator, specifically utilizing concepts from his Chebyshev Type 1 filter implementation for trend calculation.
Original indicator: Multitimeframe Fair Value Gap – FVG (Zeiierman)
📝 Changelog
v1.0
Initial release
Three-component consensus oscillator (Momentum, Deviation, Slope)
Multi-timeframe support with weighted combination
Fuzzy zone classification system
Configurable component and timeframe weights
TF consensus filter for signal quality
Signal cooldown and minimum turn size filters
Real-time info table with TF values
Optional zone background shading
Consolidation Zones Volume Delta | Flux ChartsGENERAL OVERVIEW:
The Consolidation Zones Volume Delta | Flux Charts indicator is designed to identify and visualize consolidation zones on the chart. Rather than only outlining areas of sideways price movement, the indicator analyzes volume activity occurring inside each consolidation zone. This is done by aggregating lower-timeframe volume data into the higher-timeframe consolidation range, allowing users to see how buying and selling activity evolves while price remains in a range.
What is the theory behind the indicator?:
The indicator is built around three core analytical concepts that guide how consolidation zones are detected and evaluated.
1. Consolidation as a structural phase
Periods of consolidation are characterized by reduced directional movement and compressed price ranges. During these phases, price action often alternates within a defined high–low boundary, creating a structure that can be objectively measured and tracked over time.
2. Volume behavior inside consolidation
While price may appear balanced within a consolidation range, volume activity inside that range can vary. The indicator evaluates volume contributions occurring within the vertical boundaries of the consolidation zone by using lower-timeframe data and weighting each candle’s volume based on its overlap with the zone. This produces an internal volume delta profile that reflects how buying and selling volume accumulates throughout the consolidation.
Delta behavior inside a zone may show:
Persistent dominance of buying or selling volume
Alternating shifts between buyers and sellers
Periods of relatively balanced participation
3. Markets consolidate in multiple ways, one detection method is not enough
Markets do not consolidate in a single, uniform way. To account for this, the indicator includes three distinct consolidation detection methods. Each method is calculated objectively, does not repaint, and targets a different type of sideways or low-expansion price behavior:
Candle Compression
ADX Low Trend Strength
Visual Range Boundaries
CONSOLIDATION ZONES VOLUME DELTA FEATURES:
The Consolidation Zones Volume Delta indicator includes 4 main features:
Consolidation Zones
Volume Delta
Standard Deviation Bands
Alerts
CONSOLIDATION ZONES:
🔹What is a Consolidation Zone?
A consolidation zone is a defined price range where market movement becomes compressed and price remains contained within clear upper and lower boundaries for a sustained period of time. During this phase, price does not establish a strong directional trend and instead oscillates within a relatively narrow range.
🔹Consolidation Zone Detection
The indicator automatically detects consolidation zones using three independent, rule-based methods. Each method evaluates a different market condition and can be selected individually depending on how you want consolidation to be defined. Regardless of the method used, all zones are calculated objectively and finalized once confirmed.
◇ Candles (Candle Compression)
The Candles method identifies consolidation by detecting periods of candle compression and reduced range expansion. A candle is considered part of a consolidation sequence when:
The candle body is small relative to its total range
The candle’s high–low range is smaller than the short-term Average True Range (ATR)
ATR is calculated using a 4-period average true range and is used as a volatility reference. If consecutive candles continue to meet these compression conditions, the indicator increments an internal count.
Under the Consolidation Candles section in the settings, you’ll find two controls.
Min. Consolidation Candles setting
This defines how many consecutive compressed candles are required before a consolidation zone is confirmed. Candle compression is determined using candle structure and short-term ATR, ensuring that only periods of reduced range expansion are counted. Once the minimum threshold is reached, the indicator creates a consolidation zone using the highest high and lowest low formed during the compressed sequence.
Mark Consolidation Candles
When enabled, the indicator highlights candles that meet the compression criteria, making it easy to visually identify which candles contributed to the formation of the consolidation zone.
◇ ADX (Low Trend Strength)
The ADX method identifies consolidation based on weak or declining trend strength rather than candle structure. This method uses the Average Directional Index (ADX) to determine when directional movement is reduced.
ADX is calculated using directional movement values that are smoothed over time. When ADX remains below a user-defined threshold, price is treated as being in a low-trend market. While this condition persists, the indicator tracks the highest high and lowest low formed during the low-trend period.
Under the ADX Settings section in the settings, you’ll find the following controls.
ADX Length
Defines the lookback period used to calculate directional movement for ADX.
ADX Smoothing
Controls the smoothing applied to the ADX calculation.
ADX Threshold
Sets the level below which ADX must remain for the market to be considered consolidating.
Consolidation Strength
Defines how many consecutive candles’ ADX must stay below the threshold before a consolidation zone is confirmed. Once this requirement is met, the indicator creates a consolidation zone using the accumulated high and low from the low-trend window.
Mark Candles Below Threshold
When enabled, the indicator highlights candles where ADX remains below the threshold.
◇ Visual Range
The Visual Range method identifies consolidation by detecting clearly defined horizontal price ranges where price remains contained for a sustained period of time. The indicator continuously tracks the rolling highest high and lowest low across recent candles. When price remains inside the same high–low boundaries without breaking above or below the range, an internal counter advances.
Under the Visual Range section in the settings, you’ll find the following control.
Min. Candles in Range
Defines how many consecutive candles must remain fully contained within the same high–low range before a consolidation zone is confirmed. Once this requirement is met, the indicator creates a consolidation zone using the established range boundaries.
🔹Consolidation Zone Settings
◇ Invalidation Method
Users can choose how Consolidation Zones are invalidated, selecting between Close Break or Wick Break.
Close Break: A Consolidation Zone is invalidated when a candle closes above/below the zone.
Wick Break: A Consolidation Zone is invalidated when a candle’s wick goes above/below the zone.
◇ Merge Overlapping Zones
When enabled, overlapping Consolidation Zones are automatically combined into one unified zone.
◇ Show Last
This setting determines how many Consolidation Zones are displayed on your chart. For example, setting this to 5 will display the 5 most recent zones.
VOLUME DELTA:
Delta Volume visualizes how buying and selling volume accumulates inside each consolidation zone. Instead of using the full candle volume, the indicator isolates only the volume that occurs within the vertical boundaries of the zone. This allows you to see whether bullish or bearish volume is dominating while price remains range-bound. The visualization updates in real time while the zone is active and reflects cumulative participation rather than individual candles.
🔹How Volume Delta is Calculated
Delta Volume is calculated using lower-timeframe data and applied to the higher-timeframe consolidation zone.
Each candle’s volume is split into bullish or bearish volume based on candle direction.
Lower-timeframe candles are pulled using the selected delta timeframe.
For each lower-timeframe candle, only the portion of volume that vertically overlaps the consolidation zone is counted.
Volume is weighted by the amount of overlap between the candle’s range and the zone’s range.
Bullish and bearish volume are accumulated over time to form a running, cumulative delta profile for the zone.
🔹Volume Delta Settings
◇ Enable
Turns the Delta Volume visualization on or off. Consolidation zones continue to plot when disabled.
◇ Show Delta %
Displays the percentage breakdown of bullish versus bearish volume inside the consolidation zone. Percentages are derived from cumulative volume totals.
◇ 3D Visual
When enabled, the delta blocks are extended diagonally using a depth offset derived from the instrument’s daily ATR. This creates visible side faces and top faces for the delta blocks, simulating depth without altering any calculations. The 3D effect is purely visual. It does not change how volume is calculated, weighted, or accumulated.
Users can control the intensity of the 3D effect choosing a value between 1 and 5. Increasing this value increases:
The horizontal offset of the delta blocks
The vertical depth projection applied to the volume faces
Higher values produce a more pronounced 3D appearance by pushing the delta visualization further away from the consolidation box. Lower values keep the visualization flatter and closer to the box boundaries. The depth scaling is normalized using ATR, so the effect adapts proportionally to the instrument’s volatility.
◇ Volume Delta Display Style
Controls how bullish and bearish volume are displayed inside the Consolidation Zone:
Horizontal: Volume is split top-to-bottom within the zone
Vertical: Volume is split left-to-right across the zone
◇ Timeframe
Defines the lower timeframe used for Volume Delta calculations. When a timeframe is selected, the indicator pulls lower-timeframe price and volume data and maps it into the higher-timeframe consolidation zone. Each lower-timeframe candle is evaluated individually. Only the portion of its volume that vertically overlaps the consolidation zone is included, and that volume is weighted based on the candle’s overlap with the zone’s price range. If the Timeframe field is left empty, the indicator defaults to using the chart’s current timeframe for delta calculations.
Using a lower timeframe increases the granularity of the delta calculation, allowing volume changes inside the zone to be measured more precisely. Using a higher timeframe produces a smoother, less granular delta profile.
Please Note: Delta rendering is automatically limited to available lower-timeframe data to prevent incomplete or distorted visuals when historical lower-timeframe volume is unavailable due to TradingView data limits.
STANDARD DEVIATION BANDS:
Standard Deviation Bands project measured price distance away from a confirmed consolidation zone using the size of that zone as the reference unit. Rather than calculating volatility from historical price dispersion, the bands are derived directly from the height of the consolidation range itself. Each band represents a fixed multiple of the consolidation zone’s height and is plotted symmetrically above and below the zone.
🔹How the bands are calculated
Once a consolidation zone is finalized, the indicator calculates the zone height as:
Zone Height = Zone High − Zone Low
This value becomes the base measurement for all deviation calculations. For each enabled band:
Upper bands are placed above the consolidation zone’s high
Lower bands are placed below the consolidation zone’s low
The distance of each band from the zone is calculated by multiplying the zone height by the selected band multiplier. These band levels are fixed relative to the consolidation zone and do not recalculate based on future price movement.
🔹Standard Deviation Band Settings
◇ Band 1
Enables the first deviation band above and below the consolidation zone. The Band 1 multiplier defines how far the band is placed from the zone in terms of zone height. For example, a multiplier of 1 plots the band one full zone height above and below the consolidation range.
◇ Band 2
Enables a second deviation band at a greater distance from the consolidation zone. Band 2 uses its own multiplier and is calculated independently of Band 1, allowing multiple expansion levels to be displayed simultaneously.
◇ Fill Bands
When enabled, the area between the consolidation zone and each deviation band is filled with a semi-transparent color. Upper fills apply to bands above the zone, and lower fills apply to bands below the zone. Fills are static and tied directly to the consolidation zone boundaries.
◇ Color Customization
Each deviation band has independent color controls for:
Upper band lines and fills
Lower band lines and fills
This allows users to visually distinguish between bullish and bearish extensions as well as between multiple deviation levels.
ALERTS:
Users can create alerts for the following:
New Consolidation Zone Formed
Consolidation Zone Break
UNIQUENESS:
This indicator combines multiple consolidation detection methods with lower-timeframe volume delta analysis inside each consolidation zone. It visualizes bullish and bearish volume using weighted overlap logic and optional 3D rendering for improved clarity. Users can choose how volume is displayed, apply structure-based deviation bands, and enable alerts for new zones and zone breaks. All features are rule-based, configurable, and designed to work together within a single framework.
VR Volume Ratio + Divergence (Pro)成交量比率 (Volume Ratio, VR) 是一項通過分析股價上漲與下跌日的成交量，來研判市場資金氣氛的技術指標。本腳本基於傳統 VR 公式進行了優化，增加了**「趨勢變色」與「自動背離偵測」**功能，幫助交易者更精準地捕捉量價轉折點。
Introduction
Volume Ratio (VR) is a technical indicator that measures the strength of a trend by comparing the volume on up-days versus down-days. This script enhances the classic VR formula with "Trend Color Coding" and "Auto-Divergence Detection", helping traders identify volume-price reversals more accurately.
核心功能與參數
公式原理： VR = (Qu + Qf/2) / (Qd + Qf/2) * 100
Qu: 上漲日成交量 (Up volume)
Qd: 下跌日成交量 (Down volume)
Qf: 平盤日成交量 (Flat volume)
參數 (Length)：預設為 26 日，這是市場公認最有效的短中線參數。
關鍵水位線 (Key Levels)：
< 40% (底部區)：量縮極致，市場情緒冰點，常對應股價底部，適合尋找買點。
100% (中軸)：多空分界線。
> 260% (多頭警戒)：進入強勢多頭行情，但需注意過熱。
> 450% (頭部區)：成交量過大，市場情緒亢奮，通常為頭部訊號。
視覺優化 (Visuals)：
紅漲綠跌：當 VR 數值大於前一日顯示為紅色（動能增強）；小於前一日顯示為綠色（動能退潮）。
背離訊號 (Divergence)：自動標記量價背離。
▲ 底背離 (Bullish)：股價創新低，但 VR 指標墊高（主力吸籌）。
▼ 頂背離 (Bearish)：股價創新高，但 VR 指標走弱（買氣衰竭）。
Features & Settings
Formula Logic: Calculated as VR = (Qu + Qf/2) / (Qd + Qf/2) * 100.
Default Length: 26, widely regarded as the optimal setting for short-to-medium term analysis.
Key Zones:
< 40% (Oversold/Bottom): Extreme low volume, often indicating a market bottom and potential buying opportunity.
100% (Neutral): The balance point between bulls and bears.
> 260% (Bullish Zone): Strong uptrend, volume is expanding.
> 450% (Overbought/Top): Extreme high volume, often indicating a market top and potential reversal.
Visual Enhancements:
Color Coding: Line turns Red when VR rises (Momentum Up) and Green when VR falls (Momentum Down).
Divergence Signals: Automatically marks divergence points on the chart.
▲ Bullish Divergence: Price makes a lower low, but VR makes a higher low (Accumulation).
▼ Bearish Divergence: Price makes a higher high, but VR makes a lower high (Distribution).
應用策略建議
抄底策略：當 VR 跌破 40% 後，指標線由綠翻紅，或出現「▲底背離」訊號時，為極佳的波段進場點。
逃頂策略：當 VR 衝過 450% 進入高檔區，一旦指標線由紅翻綠，或出現「▼頂背離」訊號時，建議分批獲利了結。
Strategy Guide
Bottom Fishing: Look for entries when VR drops below 40% and turns red, or when a "▲ Bullish Divergence" label appears.
Taking Profit: Consider selling when VR exceeds 450% and turns green, or when a "▼ Bearish Divergence" label appears.
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. / 本腳本僅供參考，不構成投資建議。
GARCH Volume Volatility [MarkitTick]Title: GARCH Volume Volatility
Description
Overview
The GARCH Volume Volatility (GV) indicator is a sophisticated quantitative tool designed to analyze the rate of change in market participation. While the vast majority of technical indicators focus on Price Volatility (how much price moves), this script focuses on Volume Volatility (how unstable the participation is).
Market volume is rarely distributed evenly; it tends to cluster. Periods of high activity are often followed by more high activity, and periods of calm tend to persist. This behavior is known as "heteroskedasticity." This script utilizes an Exponentially Weighted Moving Average (EWMA) model—a core component of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) frameworks—to model these changing variance regimes.
By isolating volume volatility from raw volume data, this tool helps traders distinguish between sustainable liquidity flows and erratic, unsustainable volume shocks that often precede market reversals or breakouts.
Methodology and Calculations
1. Logarithmic vs. Percentage Returns
The foundation of this indicator is the calculation of "Volume Returns"—the period-over-period change in volume.
- The script defaults to Logarithmic Returns. In financial statistics, log returns are preferred because they normalize data that can vary wildly in magnitude (such as cryptocurrency volume spikes), providing a more symmetric view of changes.
- Users can opt for standard percentage changes if they prefer a linear approach.
2. Variance Proxy (Squared Returns)
To measure volatility, the direction of the volume change (up or down) matters less than the magnitude. The script squares the returns to create a "Variance Proxy." This ensures that a massive drop in volume is treated with the same statistical weight as a massive spike in volume—both represent a significant change in the volatility of participation.
3. GARCH-Style Smoothing (EWMA)
Standard Moving Averages (SMA) treat all data points in the lookback period equally. However, volatility is dynamic. This script uses an EWMA model with a tunable "Lambda" (Decay Factor).
- The Recursive Formula: The current calculation relies on a weighted average of the current variance and the previous period's smoothed variance.
- Memory Effect: This allows the indicator to "remember" recent volatility shocks while gradually letting their influence fade. This mimics the GARCH process of conditional variance.
4. Dynamic Statistical Thresholds
The final output is the Volatility (square root of variance). To make this data actionable, the script calculates a dynamic upper and lower limit based on the standard deviation (Z-Score) of the volatility itself over a user-defined lookback period.
How to Use
The indicator plots a histogram that categorizes the market into four distinct volatility regimes:
1. High Volatility (Red Histogram)
Trigger: Volatility > High Band (Upper Standard Deviation).
Interpretation: This signals an extreme anomaly in volume stability. This is not just "high volume," but "erratic volume behavior." This often occurs at:
- Capitulation bottoms (panic selling).
- Euphoric tops (blow-off tops).
- Major news events or earnings releases.
2. Elevated Volatility (Maroon Histogram)
Trigger: Volatility > Mean Average.
Interpretation: The market is in an active state. Participation is changing rapidly, but within statistically normal bounds. This is common during healthy, trending moves where new participants are entering the market steadily.
3. Normal/Low Volatility (Green Histogram)
Trigger: Volatility is within the lower bands.
Interpretation: The market volume is stable. There are no sudden shocks in participation. This is typical of consolidation phases or "creeping" trends where the price drifts without significant volume conviction.
4. Extremely Low Volatility (Bright Green/Transparent)
Trigger: Volatility < Low Band.
Interpretation: The "calm before the storm." When volume volatility collapses to near-zero, it implies that the market has reached a state of equilibrium or disinterest. Historically, volatility is cyclical; periods of extreme compression often lead to violent expansion.
Settings and Configuration
Core Settings
- Use EWMA: When checked (Default), uses the recursive GARCH-style calculation. If unchecked, it reverts to a simple SMA of variance, which is less sensitive to recent shocks but more stable.
- Log Returns: Uses natural log for calculations. Highly recommended for assets with exponential growth or large volume ranges.
- Length: The baseline period for the calculation.
- Threshold Lookback: The number of bars used to calculate the Mean and Standard Deviation bands.
- EWMA Lambda: The decay factor (0.0 to 1.0). A value of 0.94 is standard for risk metrics.
-- Higher Lambda (e.g., 0.98): The indicator reacts slower and is smoother (long memory).
-- Lower Lambda (e.g., 0.80): The indicator reacts very fast to new data (short memory).
Visuals
- Show Thresholds: Toggles the visibility of the statistical bands on the chart.
- High Band (StdDev): The multiplier for the upper warning zone. Default is 1.5 deviations. Increasing this to 2.0 or 3.0 will filter for only the most extreme events.
Disclaimer This tool is for educational and technical analysis purposes only. Breakouts can fail (fake-outs), and past geometric patterns do not guarantee future price action. Always manage risk and use this tool in conjunction with other forms of analysis.
ATR Trailing StopATR Trailing Stop (Dynamic Volatility Regimes)
==============================================
This indicator implements an adaptive ATR-based trailing stop for long positions. The stop automatically adjusts based on stock volatility, tightening during fast movements and widening during calm periods. It is designed as a trade management tool to help protect profits while staying aligned with strong trends.
How It Works
------------
* Tracks the highest high over a configurable lookback window and ensures this “top” never moves downward.
* Computes the trailing stop as:**Top – ATR × Dynamic Multiplier**
* The ATR multiplier changes depending on volatility:
* Low volatility → Wide stop (slower trailing)
* Medium volatility → Standard trailing
* High volatility → Tight stop (faster trailing)
* The trailing stop only moves upward; it never decreases.
* If price falls significantly below the stop (default: 5%), the system resets and begins trailing from a new top.
* An optional price-scale label displays:
* Current stop value
* Volatility regime (LOW / MID / HIGH)
* ATR percentage and active multiplier
Alerts
------
Two alert conditions are included:
### Trailing Stop – Near
Triggers when price moves within a user-defined percentage above the stop.
### Trailing Stop – Hit
Triggers when price touches or closes below the stop.
How to Use
----------
1. Add the indicator to any chart (daily timeframe recommended).
2. Configure:
* ATR length
* Lookback bars
* Volatility thresholds
* ATR multipliers
3. Set alerts for early warnings or stop-hit events.
4. Use the stop line as a dynamic risk-management tool to guide exit decisions and protect profits.
Notes
-----
* Designed for long-only trailing logic.
* This indicator does not generate entry signals; it is intended for stop management.
Double&Triple Pattern[TS_Indie]📌 Description – Double & Triple Pattern Indicator
The Double & Triple Pattern Indicator is developed to help traders systematically and clearly identify Double Top, Double Bottom, Triple Top, and Triple Bottom chart patterns.
⚙️ Core Logic & Working Mechanism
The Double & Triple Pattern Indicator is built on the concept of price swing formation, based on the logic of Trend Entry_0 , which focuses on structured market analysis and price action behavior.
The indicator detects three main swing points (Swing 1, Swing 2, and Swing 3). A Fibonacci Box is then created using Swing A and Swing B as reference points to define the swing detection zone.
When all three swings remain inside the defined Fibonacci Box, the structure is considered a valid Price Action setup.
The indicator then plots key lines on the chart:
➩ Break Line – used to confirm the signal (confirmation)
➩ Cancel Line – used to invalidate the price action if price moves against the conditions
➛ When price breaks the Break Line , the structure is confirmed and a Pending Order is placed at Swing B , with the Stop Loss set at Swing 1.
➛ If price breaks the Cancel Line first, the price action structure is immediately invalidated.
⚙️ Fibonacci Entry Zone & Change SL Settings
➩ When Fibo Entry Zone is set to 0, the Pending Order is placed directly at Swing B.
➩ When the value is greater than 0, the Pending Order is calculated using Fibonacci levels drawn from Swing B to the Stop Loss level.
➩ Change SL allows switching the Stop Loss reference between Swing 1 and Swing A.
⚙️ Min & Max Control for Swing Size : xATR
When enabling Control Size Swing : xATR , the indicator filters Swing B based on the defined Min and Max range.
This allows traders to selectively test larger or smaller swing-based price actions , depending on their trading strategy.
⭐ Pending Order Cancellation Conditions
A Pending Order will be canceled under the following conditions:
1.A new Price Action signal appears on either the Buy or Sell side.
2.When Time Session is enabled, the Pending Order is canceled once price exits the selected session.
🕹 Order Management Rule
When there is an active open position, the indicator restricts the creation of new Pending Orders to prevent overlapping positions.
💡 Double Pattern Example
💡 Triple Pattern Example
⚠️ Disclaimer
This indicator is designed for technical analysis purposes only and does not constitute investment advice.
Users should apply proper risk management and make decisions at their own discretion.
🥂 Community Sharing
If you find parameter settings that work well or produce strong statistical results, feel free to share them with the community so we can improve and develop this indicator together.
Ripster Clouds + Saty Pivot + RVOL + Trend1. Ripster EMA Clouds (local + higher timeframe)
Local timeframe (your chart TF):
Plots up to 5 EMA clouds (8/9, 5/12, 34/50, 72/89, 180/200 – configurable).
Each cloud is:
One short EMA and one long EMA.
A filled band between them.
Color logic:
Cloud is bullish when short EMA > long EMA (green/blue-ish tone).
Bearish when short EMA < long EMA (red/orange/pink tone).
You can choose:
EMA vs SMA,
Whether to show the lines,
Per-cloud toggles.
MTF Clouds:
Two higher-timeframe EMA clouds:
Cloud 1: 50/55
Cloud 2: 20/21
Computed on a higher TF (default D, but configurable).
Show as thin lines + transparent bands.
Used for:
Visual higher-TF trend,
Optional signal filter (MTF must agree for trades).
2. Saty Pivot Ribbon (time-warped EMAs)
This is basically your Saty Pivot Ribbon integrated:
Uses a “Time Warp” setting to overlay EMAs from another timeframe.
EMAs:
Fast, Pivot, Slow (defaults 8 / 21 / 34).
Clouds:
Fast cloud between fast & pivot EMAs.
Slow cloud between pivot & slow EMAs.
Bullish/bearish colors are distinct from Ripster colors.
Optional highlights:
Can highlight fast/pivot/slow lines separately.
Conviction EMAs:
13 and 48 EMAs (configurable).
When fast conviction EMA crosses over/under slow:
You get triangle arrows (bullish/bearish conviction).
Bias candles:
If enabled, candles are recolored based on:
Price vs Bias EMA,
Candle up/down/doji,
So you see bullish/bearish “bias” directly in candle colors.
3. DTR vs ATR panel (range vs average)
In a small table panel (bottom-center by default):
Computes higher-TF ATR (default 14, TF auto D/W/M, smoothing type selectable).
Measures current range (high–low) on that TF.
Displays:
DTR: X vs ATR: Y Z% (+/-Δ% vs prev)
Where:
Z% = current range / ATR * 100.
Δ% = change vs previous bar’s Z%.
Background color:
Greenish for low move (<≈70%),
Red for high move (≥≈90%),
Yellow in between,
Slightly dimmed when price is below bias EMA.
This tells you: “Is today an average, quiet, or explosive day compared to normal?”
4. SMA Divergence panel
Separate histogram & line panel:
Fast and slow SMAs (default 14 & 30).
Computes price divergence vs SMA in %:
% above/below slow SMA,
% above/below fast SMA.
Shows:
Slow SMA divergence as a semi-transparent column,
Fast SMA divergence as a solid column on top,
EMA of the slow divergence (trend line) colored:
Blue when rising,
Orange/red when falling.
Static upper/lower bands with fill, plus optional zero line.
This gives you a feel for how stretched price is vs its anchors.
5. RVOL table (relative volume)
Small 3×2 table (bottom-right by default):
Inputs:
Average length (default 50 bars),
Optionally show previous candle RVOL.
Calculates:
RVOL now = volume / avg(volume N bars) * 100,
RVOL prev,
RVOL momentum (now – prev) for data window only.
Table columns:
Candle Vol,
RVOL (Now),
RVOL (Prev).
Colors:
200% → “high RVOL” color,
100–200% → “medium RVOL” color,
<100% → “low RVOL” color,
Slightly dimmer if price is below bias EMA.
This is used both visually and optionally as a signal filter (e.g., only trade when RVOL ≥ threshold).
6. Trend Dashboard (Price + 34/50 + 5/12)
Top-right trend box with 3 rows:
Price Action row:
Uses either Bias EMA or custom EMA on close to say:
Bullish (close > trend EMA),
Bearish (close < trend EMA),
Flat.
Ripster 34/50 Cloud row:
Uses 34/50 EMAs: bullish if 34>50, bearish if 34<50.
Ripster 5/12 Cloud row:
Uses 5/12 EMAs: bullish if 5>12, bearish if 5<12.
Then it does a vote:
Counts bullish votes (Price, 34/50, 5/12),
Counts bearish votes,
Depending on mode:
Majority (2 of 3) or Strict (3 of 3).
Output:
Overall Bullish / Bearish / Sideways.
You also get an optional label on the chart like
Overall: Bullish trend with color, and an optional background tint (green/red for bull/bear).
7. VWAP + Buy/Sell Signals
VWAP is plotted as a white line.
Fast “trend” cloud mid: average of 5 & 12 EMAs.
Slow “trend” cloud mid: average of 34 & 50 EMAs.
Buy condition:
5/12 crosses above 34/50 (bullish cloud flip),
Price > VWAP,
Optional filter: MTF Cloud 1 bullish (50/55 on higher TF),
Optional filter: RVOL >= threshold.
Sell condition:
5/12 crosses below 34/50,
Price < VWAP,
Optional same filters but bearish.
When conditions are met:
Plots BUY triangle up below price (distinct teal/green tone).
Plots SELL triangle down above price (distinct magenta/orange tone).
Alert conditions are defined for:
BUY / SELL signals,
Overall Bullish / Bearish / Sideways change,
MTF Cloud 1 trend flips.
8. Data Window metrics
For easy backtesting / inspection via TradingView’s data window, it exposes:
DTR% (Current) and DTR% Momentum,
RVOL% (Now), RVOL% (Prev), RVOL% Momentum.
TL;DR – What does this script do for you?
It turns your chart into a multi-framework trend and momentum dashboard:
Ripster EMA clouds for short/medium trend & S/R.
Saty Ribbon for higher-TF pivot structure and conviction.
RVOL + DTR/ATR for context (is this a big and well-participated move?).
SMA divergence panel for overextension/stretch.
A compact trend table that tells you Price vs 34/50 vs 5/12 in one glance.
Buy/Sell markers + alerts when:
short-term Ripster trend (5/12) flips over/under medium (34/50),
price agrees with VWAP,
plus optional filters (MTF trend and / or RVOL).
Basically: it’s a trend + confirmation + context system wrapped into one indicator, with most knobs configurable in the settings.
Momentum Gamma StraddleExact definition of what that script does
1) Purpose
The script is a decision aid for intraday expiry-day ATM straddle trades. It detects intraday structure breakouts and signals candidate long straddle entries for Nifty or Sensex using price structure, volume, RSI momentum, and a user-supplied combined ATM premium value (CE + PE). It draws support/resistance, shows an info box, and raises alerts.
2) Inputs the user can change
Trading time window: startHour, startMin, endHour, endMin.
Structure lookback: res_lookback (how many candles to use to compute resistance/support).
Minimum candle body as fraction of candle range: min_body_pct.
Volume multiplier threshold: vol_mult (breakout candle volume must exceed vol_mult * sma5).
RSI length and thresholds: rsi_len, rsi_bull_thresh, rsi_bear_thresh.
Combined premium source: choose Manual or Symbol. If Manual, set manual_combined. If Symbol, provide a TradingView symbol that returns CE+PE combined ATM premium.
Combined premium acceptable band: min_combined_ok and max_combined_ok.
Profit target percent and SL percent (target_pct and sl_pct).
Misc pattern heuristics: min_res_hits (min tests of resistance inside lookback), low_slope_min (used to detect rising lows).
Micro-confirmation toggle, micro timeframe, nonrepaint option, show_entry_label toggle (in the later fixed versions some of these were added, but the earlier fixed script had basic combined_symbol options and a lookahead fallback).
3) Data calculated on each bar
Safety check hasEnough: true when bar_index >= res_lookback.
resistance: the highest high over res_lookback bars.
support: the lowest low over res_lookback bars.
res_hits: count of bars within lookback whose high is within a tolerance of resistance. Tolerance is 10 percent of the range between resistance and support.
low_slope: simple slope of lows over res_lookback bars.
body_pct: the candle body as a fraction of its high-low range. strong_body true when body_pct >= min_body_pct.
bull_breakout: true if hasEnough and current close > resistance and strong_body and res_hits >= min_res_hits.
bear_breakout: true if hasEnough and current close < support and strong_body and res_hits >= min_res_hits.
vol_sma5 and vol_ok: vol_ok true when current volume > vol_mult * vol_sma5.
rsi and rsi checks: rsi_bull_ok true if rsi >= rsi_bull_thresh; rsi_bear_ok true if rsi <= rsi_bear_thresh.
combined_premium: either the manual_combined input or the value read from combined_symbol via request.security. The script attempted a fallback to manual when the symbol was not valid.
combined_ok: true if combined_premium lies between min_combined_ok and max_combined_ok.
final signals: bull_signal when in_time_window and bull_breakout and vol_ok and rsi_bull_ok and combined_ok. bear_signal similar for bearish breakout.
4) Visual output and alerts
Plots resistance and support lines on the chart.
Plots a label shape "STRADDLE BUY" below the bar for bull_signal and above the bar for bear_signal.
Creates an info label (on last bar) that shows TimeOK, VolOK and vol ratio, RSI, Combined premium and whether it is OK, ResHits and LowSlope.
Sets two alertcondition events: "Bull Straddle BUY" and "Bear Straddle BUY" with a short candidate message. The alerts fire when the corresponding signal is true.
5) Execution assumptions you must follow manually
The script does not place any orders or compute option strike-level prices or greeks. It only flags candidate entry bars.
When combined_source is Manual you must type CE+PE yourself. The indicator will only accept the manual number and treat it as the combined premium.
When combined_source is Symbol the script uses request.security to read that symbol. For historical bars the indicator may repaint depending on lookahead settings. The earlier fixed script attempted to use request.security inside a conditional which leads to runtime or compile errors. You experienced that exact error.
6) Known implementation caveats and bugs you encountered
Pine typing issue with low_slope. The earlier version set low_slope = na without explicit type. That triggers the Pine error: "Value with NA type cannot be assigned to a variable that was defined without type keyword". This required changing to float low_slope = na.
The earlier version attempted to call request.security() inside an if block or conditional. Pine prohibits request.security in conditional blocks unless allowed patterns are followed. That produced the error you saw: "Cannot use request.* call within loops or conditional structures" or similar. The correct pattern is to call request.security at top-level and decide later which value to use.
If combined_symbol is invalid or not available on your TradingView subscription, request.security can return na and the script must fall back to manual value. The earlier fixed script attempted fallback but compiled errors prevented reliable behavior.
The earlier script did not include micro-confirmation or advanced nonrepaint controls. Those were added in later versions. Because of that, the earlier script may have given signals that appear to repaint on historical bars or may have thrown errors when using combined_symbol.
7) Decision logic summary (exact)
Only operate if current chart time is inside user set time window.
Only consider trade candidates when enough history exists for res_lookback.
Identify a resistance level as the highest high in the lookback. Count how many times that resistance was tested. Ensure the breakout candle has a strong body and volume spike. Ensure RSI is aligned with breakout direction.
Require combined ATM premium to be inside a user preferred band. If combined_symbol is used the script tries to read that value and use it; otherwise it uses manual_combined input.
If all the above conditions are true on a confirmed bar, the script plots a STRADDLE BUY label and triggers an alertcondition.
8) What the script does not do
It does not calculate CE and PE prices by strike. It only consumes or accepts combined premium number.
It does not compute greeks, IV, or OI. OI and IV checks must be done manually.
It does not manage positions. No SL management or automatic exits are executed by the script.
It does not simulate fills or account for bid/ask spreads or slippage.
It cannot detect off-exchange block trades or read exchange-level auction states beyond raw volume bars.
It may repaint historical labels if the combined_symbol was read with lookahead_on or the script used request.security in a way that repainted. The corrected final version uses nonrepaint options.
9) Manual checks you must always perform even when the script signals BUY
Confirm the live combined ATM premium and the bid/ask for CE and PE.
Check ATM IV and recent IV movement for a potential IV crush risk.
Check option OI distribution and recent OI changes for strike pinning or large player exposure.
Confirm CE and PE liquidity and depth. Wide spreads make fills unrealistic.
Confirm there is no scheduled news or auction within the next few minutes.
Confirm margin and position sizing fits your risk plan.
10) Quick testing checklist you can run now
Add the script to a 5-minute chart with combined_source = Manual.
Enter manual_combined equal to the real CE+PE at the moment you test.
Set startHour and endHour so the in_time_window is true for current time.
Look for STRADDLE BUY label on confirmed bars. Inspect the info box to see why it did or did not signal.
If you set combined_source = Symbol, verify the symbol exists and that TradingView returns values for it. If you previously saw the request.security error, that was caused by placing the request inside a conditional. The correct behavior is to call request.security unconditionally at top-level like in the final fixed version.
Multi-Distribution Volume Profile (Zeiierman)█ Overview
Multi-Distribution Volume Profile (Zeiierman) is a flexible, structure-first volume profile tool that lets you reshape how volume is distributed across price, from classic uniform profiles to advanced statistical curves like Gaussian, Lognormal, Student-t, and more.
Instead of forcing every market into a single "one-size-fits-all" profile, this tool lets you model how volume is likely concentrated inside each bar (body vs wicks, midpoint, tails, center bias, right-skew, heavy tails, etc.) and then stacks that behavior across a whole lookback window to build a rich, multi-distribution map of traded activity.
On top of that, it overlays a dynamic Center Band (value area) and a fade/gradient model that can color each price row by volume, hits, recency, volatility, reversals, or even liquidity voids, turning a plain profile into a multi-dimensional context map.
Highlights
Choose from multiple Profile Build Modes , including uniform, body-only, wick-only, midpoint/close/open, center-weighted, and a suite of probability-style distributions (Gaussian, Lognormal, Weibull, Student-t, etc.)
Flexible anchor layout: draw the profile on Right/Left (horizontal) or Bottom/Top (vertical) to fit any chart layout
Value Area / Center Band computed from volume quantiles around the POC.
Gradient-based Fade Metrics: volume, price hits, freshness (time decay), volatility impact, dwell time, reversal density, compression, and liquidity voids
Separate bullish vs bearish volume at each price row for directional structure insights
█ How It Works
⚪ Profile Construction
The script scans a user-defined Bars Included window and finds the full high–low span of that zone. It then divides this range into a user-controlled number of Price Levels (rows).
For each historical bar within the window:
It measures the candle’s price range, body, and wicks.
It assigns volume to rows according to the selected Profile Build Mode, for example:
* Range Uniform – volume spread evenly across the full high–low range.
* Range Body Only / Range Wick Only – concentrate volume inside the body or wicks only.
* Midpoint / Close / Open Only – allocate volume entirely into one price row (pinpoint modeling).
HL2 / Body Center Weighted – center weights around the middle of the range/body.
Recent-Weighted Volume – amplify newer bars using exponential time decay.
Volume Squared (Hard) – aggressively boost bars with large volume.
Up Bars Only / Down Bars Only – filter volume to only bullish or bearish bars.
For more advanced shapes, the script uses continuous distributions across the bar’s span:
Linear, Triangular, Exponential to High
Cosine Centered, PERT
Gaussian, Lognormal, Cauchy, Laplace
Pareto, Weibull, Logistic, Gumbel
Gamma, Beta, Chi-Square, Student-t, F-Shape
Each distribution produces a weight for each row within the bar’s range, normalized so the total volume remains consistent, but the shape of where that volume lands changes.
⚪ POC & Center Band (Value Area)
Once all rows are accumulated:
The row with the highest total volume becomes the Point of Control (POC)
The script computes cumulative volume and finds the band that wraps a user-defined Center of Profile % (e.g., 68%) around the center of distribution.
This range is displayed as a central band, often treated like a value area where price has spent the most “effort” trading.
⚪ Gradient Fade Engine
Each row also gets a fade metric, chosen in Fade Metric:
Volume – opacity based on relative volume.
Price Hits – how frequently that row was touched.
Blended (Vol+Hits) – average of volume & hits.
Freshness – emphasizes recent activity, controlled by Decay.
Volatility Impact – rows that saw larger ranges contribute more.
Dwell Time – where price “camped” the longest.
Reversal Density – where direction changes cluster.
Compression – tight-range compression zones.
Liquidity Void – inverse of volume (thin liquidity zones).
When Apply Gradient is enabled, the row’s bullish/bearish colors are tinted from faint to strong based on this chosen metric, effectively turning the profile into a heatmap of your chosen structural property.
█ How to Use
⚪ Explore Different Distribution Assumptions
Switch between multiple Profile Build Modes to see how your assumptions about intrabar volume affect structure:
Use Range Uniform for classical profile reading.
Deploy Gaussian, Logistic, or Cosine shapes to emphasize central clustering.
Try Pareto, Lognormal, or F-Shape to focus on tail / extremal activity.
Use Recent-Weighted Volume to prioritize the most recent structural behavior.
This is especially useful for traders who want to test how different modeling assumptions change perceived value areas and levels of interest.
⚪ Identify Value, Acceptance & Rejection Zones
Use the POC and Center of Profile (%) band to distinguish:
High-acceptance zones – wide central band, thick rows, strong gradient → fair value areas
Rejection zones & tails – thin extremes, low dwell time, high volatility or reversal density
These regions can be used as:
Targets and origin zones for mean reversion
Context for breakout validation (leaving value)
Bias reference for intraday rotations or swing rotations
⚪ Read Directional Structure Within the Profile
Because each row is split into bullish vs bearish contributions, you can visually read:
Where buyers dominated a price region (large bullish slice)
Where sellers absorbed or defended (large bearish slice)
Combining this with Fade Metrics like Reversal Density, Dwell Time, or Freshness turns the profile into a structural order-flow map, without needing raw tick-by-tick volume data.
⚪ Use Fade Metrics for Contextual Heatmaps
Each Fade Metric can be used for a different analytical lens:
Volume / Blended – emphasize where volume and activity are concentrated.
Freshness – highlight the most recently active zones that still matter.
Volatility Impact & Compression – spot areas of explosive moves vs coiled ranges.
Reversal Density – locate micro turning points and battle zones.
Liquidity Void – visually pop out thin regions that may act as speedways or magnets.
█ Settings
Profile Build Mode – Selects how each bar’s volume is distributed across its price range (uniform, body/wick, midpoint/close/open, center-weighted, or statistical distribution families).
Bars Included – Number of bars used to build the profile from the current bar backward.
Price Levels – Vertical resolution of the profile: more levels = smoother but heavier.
Anchor Side – Where the profile is drawn on the chart: Right, Left, Bottom, or Top.
Offset (bars) – Horizontal offset from the last bar to the profile when using Right/Left modes.
Apply Gradient – Toggles the fade/heatmap coloring based on the selected metric.
Fade Metric – Chooses the property driving row opacity (Volume, Hits, Freshness, Volatility Impact, Dwell Time, Reversal Density, Compression, Liquidity Void).
Decay – Time-decay factor for Freshness (values close to 1 keep older activity relevant for longer).
Profile Thickness – Relative thickness of the profile along the time axis, as a % of the lookback window.
Center of Profile (%) – Volume percentage used to define the central band (value area) around the POC.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Trinity ATR Real Move DetectorTrinity ATR Real Move Detector
This ATR Energy Table indicator is one of the simplest yet most powerful filters you can have on a chart when trading short-dated or 0DTE options or swing trades on any timeframe from 1-minute up to 4-hour. Its entire job is to answer the single most important question in intraday and swing trading: “Does the underlying actually have enough short-term explosive energy right now to make a directional position worth the theta and the spread, or is this just pretty candles that will die in ten minutes?”
Most losing 0DTE and short-dated option trades happen because people buy or sell direction on a “nice-looking” breakout or pullback while the underlying is actually in low-energy grind mode. The premium decays faster than the move develops, and you lose even when you’re “right” on direction. This little table stops that from ever happening again.
Here’s what it does in plain English:
Every bar it measures two things:
- The current ATR on whatever timeframe you are using (1 min, 3 min, 5 min, 10 min, etc.). This tells you how big the average true range of the last 14 bars has been — in other words, how violently the stock or index is actually moving right now.
- The daily ATR (14-period on the daily chart). This is your benchmark for “normal” daily movement over the last two–three weeks.
It then multiplies the daily ATR by a small number (the multiplier you set) and compares the two. If the short-term ATR is bigger than that percentage of the daily ATR, the table turns bright green and says “ENOUGH ENERGY”. If not, it stays red and says “NOT ENOUGH”.
Why this works so well:
- Real explosive moves that carry for 0DTE and 1–3 DTE options almost always show a short-term ATR spike well above the recent daily average. Quiet grind moves never do.
- The comparison is completely adaptive — on a high-vol day the threshold automatically rises, on a low-vol day it automatically drops. You never have to guess if “2 points on SPY is big today”.
- It removes emotion completely. You simply wait for green before you even think about clicking buy or sell on an option.
Key settings and what to do with them:
- Energy Multiplier — this is the only number you ever touch. It is expressed as a decimal (0.15 = 15 % of the daily ATR). Lower = more signals, higher = stricter and higher win rate. The tooltip gives you the exact sweet-spot numbers for every popular timeframe (0.09 for 1-minute scalping, 0.13 for 3-minute, 0.14–0.16 for 5-minute, 0.15–0.19 for 10-minute, etc.). Just pick your timeframe once and type the number — done forever.
- ATR Length — leave it at 14. That’s the standard and works perfectly.
- Table Position — move the table to wherever you want on the chart (top-right, bottom-right, bottom-left, top-left).
- Table Size — make the text Tiny, Small, Normal or Large depending on how much screen space you have.
How this helps you make money and stop losing it:
- On most days you will see red 80–90 % of the time — that’s good! It is forcing you to sit on your hands instead of overtrading low-energy chop that eats premium.
- When it finally flips green you know institutions are actually pushing size right now — follow-through probability jumps from ~40 % to 65–75 % depending on the stock and timeframe.
- You stop buying calls on every green candle and puts on every red candle. You only strike when the market is genuinely “awake”.
- Over a week you take dramatically fewer trades, but your win rate and average winner size go way up — which is exactly how consistent intraday option profits are made.
In short, this tiny table is the closest thing to an “edge on/off switch” that exists for short-dated options. Red = preserve capital and go do something else. Green = pull the trigger with confidence. Use it religiously and you’ll immediately feel the difference in your P&L.
Exhaustion IndicatorThe ScalpSQZ indicator is designed to identify four critical market states using volatility structure, momentum behavior, and exhaustion conditions. It enhances scalping precision by visually marking transitions between consolidation, squeeze conditions, and momentum reversals through color-coded candles.
1. Squeeze Conditions (Orange Candles)
Orange candles highlight volatility compression, detected when Bollinger Bands contract inside the Keltner Channels. This structure signals that market volatility is tightening and a significant expansion move is likely to follow. The squeeze represents a pre-breakout environment and serves as the earliest warning of a potential directional shift.
2. Consolidation Conditions (Yellow Candles)
Yellow candles identify phases of low directional momentum. These conditions occur when RSI remains near neutral values, MACD histogram activity is minimal, and the Rate of Change stays muted. This combination indicates that the market is balanced and non-trending, often preceding a volatility spike or a new trend. Consolidation helps traders avoid low-probability entries during indecisive price action.
3. Momentum Exhaustion — Overbought Fade (White Candles)
White candles signal potential top-side exhaustion. This occurs when RSI enters overbought territory while the MACD histogram begins to weaken compared to the previous bar. This condition does not necessarily call a reversal but warns that bullish momentum is deteriorating and upside continuation may be limited. It is particularly useful for identifying trend fatigue and tightening stop-loss placement.
4. Momentum Exhaustion — Oversold Fade (Purple Candles)
Purple candles identify bottom-side exhaustion and appear when RSI reaches oversold levels, MACD momentum begins improving, and the current close shows buyer defense relative to the previous low. This condition suggests selling pressure is diminishing and a potential reversal or relief bounce may be forming. Purple candles serve as an early indication of bearish trend exhaustion.
Color Priority System
The indicator follows a fixed hierarchy to ensure clarity:
Squeeze (orange) has the highest priority, followed by consolidation (yellow). Exhaustion signals (white for tops, purple for bottoms) apply only when no squeeze or consolidation conditions are active. This structure ensures that the most critical market states are always highlighted first.
Purpose and Application
ScalpSQZ helps traders identify optimal environments for breakouts, anticipate trend exhaustion, and avoid low-quality trades during choppy or low-momentum conditions. It is suitable for scalping, day trading, and swing trading across any asset class or timeframe.
Intermarket Swing Projection [LuxAlgo]The Intermarket Swing Projection allows traders to plot price movement swings from any user-selected asset directly onto the chart in the form of zigzags and/or horizontal support and resistance levels.
This tool rescale the external asset price on the user chart, enabling traders to make direct comparisons.
It answers the question of how different the price behavior is between two assets, accounting for each asset's volatility.
🔶 USAGE
This tool is based on swing detection of two different assets: the chart and a user-selected asset. It allows traders to compare two assets on an equal footing while accounting for volatility and price behavior.
Traders can customize the detection by selecting a custom ticker, timeframe, the number of swings and length for swing detection. This makes the tool a Swiss army knife for asset comparison.
As we can see in the image below, the Show Last, Pivot Length, and Spread parameters are key to defining the final output of the tool.
"Show Last" defines how many pivots are displayed. "Pivot Length" is used for pivot detection; a larger value will detect larger market structures. "Spread" defines how far apart the horizontal levels will be from their original location in terms of volatility.
🔹 Comparing different assets
This image shows the Nasdaq 100 futures contract compared to four other futures contracts: S&P 500, gold, bitcoin, and euro/U.S. dollar.
Plotting all of these assets in Nasdaq 100 terms makes it easy to compare and analyze price behaviors and identify key levels.
In the top left chart, we have NQ vs. ES. It's no surprise that they are practically an exact match; a large portion of the S&P 500 is technology.
In the top right chart, NQ vs. GC, we see totally different behaviors. We can clearly see the summer consolidation in gold and the resumption of the uptrend, which took gold above 29,200 NQ points, up from 21,200.
In the bottom right chart, we see bitcoin making new highs, way above the Nasdaq in May, July, and October. However, the last high was way below the Nasdaq prices on October 27—the first lower high in a while. Sellers are pushing down.
Finally, the bottom left chart is NQ vs. 6E. We can see large volatility in the uptrend since February, with NQ unable to catch up until now. The last swing low was almost a match, and 6E is in a range.
As we can see, this tool allows us to perform intermarket analysis properly by accounting for each asset's volatility and price behavior. Then, we plot them on the same scale on equal terms, which makes performing this kind of analysis easy.
As we can see in the chart above, the assets are the same as in the previous image, but the timeframe is 1H with different settings.
Note the horizontal levels acting as support and resistance, as well as how NQ prices react to the zones marked with white circles. These levels are derived from custom assets selected by the user.
🔹 Displaying Elements
Zig-zag allows traders to clearly see the path that the selected asset's price took, as well as its turning points.
Horizontal levels are displayed from those turning points to the present and can be used as support or resistance. Traders can adjust the spread parameter in the settings panel to expand or contract those levels' volatility.
There are two color modes for the levels: average and pivots. In the first mode, green is used for levels below the average and red for levels above the average. The second uses green for swing lows and red for swing highs.
The backpaint feature is enabled by default and allows the swings to be displayed in the correct location. With this feature disabled, the swings will be displayed in the current location when a new swing is detected.
🔶 DETAILS
On a more technical note, the rescaling is formed by calculating three main elements from all the swings detected on the custom and chart assets:
The chart asset's average of all swing points
The chart asset's standard deviation of all swing points
The custom asset's z-score for each swing point
Then, the re-scaled swing point is calculated as the average plus the z-score multiplied by the standard deviation. This makes it possible to plot AAPL swings on an NQ chart, for example.
Thanks to re-scaling, we can directly compare the price behavior of two assets with different price ranges and volatility on the same chart.
🔶 SETTINGS
🔹 Trendlines
Ticker: Select the custom ticker.
Timeframe: Select a custom timeframe.
Show Last: Select how many swing points to display.
Pivot Length: Select the size for swing point detection.
Spread: Volatility multiplier for horizontal levels. Larger values mean the levels are farther apart.
Backpaint: Enable or disable the backpaint feature. When enabled, the drawings will be displayed where they were detected. When disabled, the drawings will be displayed at the moment of detection.
🔹 Style
Show ZigZag: Enable or disable the ZigZag display and choose a line style.
Show Levels: Enable or disable the levels display and choose a line style.
Color Mode: Choose between Average Mode, which colors all levels below the average bullish and all levels above bearish, and Pivot Mode, which colors swing highs bearish and swing lows bullish.
Bullish: Select a bullish color.
Bearish: Select a bearish color.
ZigZag: Select the ZigZag color.
BTC - FRIC: Friction & Realized Intensity CompositeTitle: BTC - FRIC: Friction & Realized Intensity Composite
Data: IntoTheBlock
Overview & Philosophy
FRIC (Friction & Realized Intensity Composite) is a specialized on-chain oscillator designed to visualize the "psychological battlegrounds" of the Bitcoin network.
Most indicators focus on Price or Momentum. FRIC focuses on Cost Basis. It operates on the thesis that the market experiences maximum "Friction" when the price revisits the cost basis of a large number of holders. These are the zones where investors are emotionally triggered to react—either to exit "at breakeven" after a loss (creating resistance) or to defend their entry (creating support).
This indicator answers two questions simultaneously:
Intensity: Is the market hitting a Wall (High Friction) or a Vacuum (Low Friction)?
Valuation: Is this happening at a market bottom or a top?
The "Alpha" (Wall vs. Vacuum)
Why we visualize both extremes: This indicator filters out the "Noise" (the middle range) to show you only the statistically significant anomalies.
1. The "Wall" (Positive Z-Score Bars)
What it is : A statistically high number of addresses are at breakeven.
The Implication : Expect a grind. Price action often slows down or reverses here because "Bag Holders" are selling into strength to get out flat, or new buyers are establishing a floor.
2. The "Vacuum" (Negative Z-Score Bars)
What it is : A statistically low number of addresses are at breakeven.
The Implication : Expect acceleration. The price is moving through a zone where very few people have a cost basis. With no natural "breakeven supply" to block the path, price often enters Price Discovery or Free Fall.
Methodology
The indicator constructs a composite view using two premium metrics from IntoTheBlock:
1. The "Activity" (Friction Z-Score): We utilize the Breakeven Addresses Percentage. This measures the % of all addresses where the current price equals the average cost basis.
- Normalization: We apply a rolling Z-Score (Standard Deviation) to this data.
- The Filter: We hide the "Noise" (e.g., Z-Scores between -2.0 and +2.0) to isolate only the events where market structure is truly stretched.
2. The "Context" (Valuation Heatmap): We utilize the MVRV Ratio to color-code the friction.
Deep Value (< 1.0): Price is below the average "Fair Value" of the network.
Overheated (> 3.0): Price is significantly extended above the "Fair Value."
Credit: The MVRV Ratio was originally conceptualized by Murad Mahmudov and David Puell. It remains one of the gold standards for detecting Bitcoin's fair value deviations.
How to Read the Indicator
The chart is visualized as a Noise-Filtered Heatmap.
1. The Bars (Intensity)
Bars Above Zero: High Friction (Congestion). The market is fighting through a supply wall.
Bars Below Zero: Low Friction (Vacuum). The market is accelerating through thin air.
Gray/Ghosted: Noise. Routine market activity; no significant signal.
2. The Colors (Valuation Context) The color tells you why the friction is happening:
🟦 Deep Blue (The "Capitulation Buy"):
Signal: High Friction + Low MVRV.
Meaning : Investors are panic-selling at breakeven/loss, but the asset is fundamentally undervalued. Historically, these are high-conviction cycle bottoms.
🟥 Dark Red (The "FOMO Sell"):
Signal: High Friction + High MVRV.
Meaning : Investors are churning at high valuations. Smart money is often distributing to late retail arrivers. Historically marks cycle tops.
🟨 Yellow/Orange (The "Trend Battle"):
Signal: High Friction + Neutral MVRV.
Meaning : The market is contesting a level within a trend (e.g., a mid-cycle correction).
Visual Guide & Features
10-Zone Heatmap: A granular color gradient that shifts from Dark Blue (Deep Value) → Sky Blue → Grey (Neutral) → Orange → Dark Red (Top).
Noise Filter
A unique feature that "ghosts out" insignificant data, leaving only the statistically relevant signals visible.
Data Check Monitor
A diagnostic table in the bottom-right corner that confirms the live connection to IntoTheBlock data streams and displays the current regime in real-time.
Settings
Lookback Period (Default: 90): The rolling window used for the Z-Score calculation. Shortening this (e.g., to 30) makes the indicator more sensitive to local volatility; lengthening it (e.g., to 365) aligns it with macro cycles.
Noise Threshold (Default: 2.0): The strictness of the filter. Only friction events exceeding this Z-Score will be highlighted in full color.
Show Status Table : Toggles the on-screen dashboard.
Disclaimer
This script is for research and educational purposes only. It relies on third-party on-chain data which may be subject to latency or revision. Past performance of on-chain metrics does not guarantee future price action.
Tags
bitcoin, btc, on-chain, mvrv, intotheblock, friction, z-score, fundamental, valuation, cycle
Multi-MA + Trend StatusMulti-MA + Trend Status is a streamlined trend analysis tool designed to simplify market state identification using a robust Moving Average (MA) crossover logic. By analyzing the relationship between price and three key Moving Averages (Fast, Medium, and Slow), this indicator instantly classifies the market into one of 9 distinct trend phases, displayed as a clean, non-intrusive text overlay on your chart.
Created by ivanpsh (MIT License).
Key Features
9 Distinct Trend States: Automatically detects and displays specific market conditions:
🟢 Bullish Phases: Uptrend, Bullish Crossover, Fast Bullish Crossover, Bottom Bounce.
🔴 Bearish Phases: Downtrend, Bearish Crossover, Fast Bearish Crossover, Top Pullback, Dead Cat Bounce.
Visual Simplicity: Displays the current market status in a large, transparent text overlay (Bottom Right by default) that provides instant clarity without cluttering your analysis.
Multi-Timeframe (MTF) Support: Monitor the trend of a higher timeframe (e.g., Daily) while trading on a lower timeframe (e.g., 5-minute) without switching charts.
Fully Configurable MAs:
Types: Supports SMA, EMA, RMA (Wilder's), WMA, and VWMA.
Lengths: Fully adjustable lengths (Defaults: 20, 50, 250).
Source: Calculation source is customizable (Close, Open, High, Low, HL2, etc.).
Integrated MA Overlay: Optionally view the actual Moving Average lines on the chart.
Color Coded: Fast (Purple), Medium (Orange), and Slow (Red) for easy differentiation.
Toggle: Lines are visible by default but can be hidden instantly via settings.
How It Works
The indicator logic compares the current Price against three Moving Averages (Default: 20, 50, 250) to determine the market "Health":
Uptrend: Price > 20 > 50 > 250 (Strongest Bullish Signal)
Downtrend: Price < 20 < 50 < 250 (Strongest Bearish Signal)
Crossovers: Identifies early reversals when Fast/Medium MAs cross the Slow MA.
Bounces & Pullbacks: Identifies specific retracement patterns (e.g., "Bottom Bounce" or "Top Pullback") where price interacts with MAs in a counter-trend move.
Settings Guide
Indicator Timeframe: Select the timeframe used for calculations (Default: Chart).
MA Type: Choose the averaging method (Default: SMA).
Visuals: Customize text size, screen position, and opacity.
Show 'No Match' Text: By default, the text overlay hides if the market is choppy and fits none of the 9 specific states. You can enable this to see a "No Logic Match" status instead.
This script is open-source under the MIT license. Feel free to use, study, and modify it for your own trading systems.
Value Charts by Mark Helweg1. Introduction
This script is a simplified implementation of the Value Charts concept introduced by Mark Helweg and David Stendahl in their work on “Dynamic Trading Indicators”. It converts raw price into value units by normalizing distance from a dynamic fair‑value line, making it easier to see when price is relatively overvalued or undervalued across different markets and timeframes. The code focuses on plotting Value Chart candlesticks and clean visual bands, keeping the logic close to the original idea while remaining lightweight for intraday and swing trading.
2. Key Features
- Dynamic fair‑value axis
Uses a moving average of the chosen price source as the fair‑value line and a volatility‑based deviation (smoothed True Range) to scale all price moves into comparable value units.
- Normalized Value Chart candlesticks
OHLC prices are transformed into value units and displayed as a dedicated candlestick panel, visually similar to standard candles but detached from raw price, highlighting relative extremes instead of absolute levels.
- Custom upper and lower visual limits
User‑defined upper and lower bands frame the majority of action and emphasize extreme value zones, helping the trader spot potential exhaustion or mean‑reversion conditions at a glance.
- Clean, publishing‑friendly layout
Only the normalized candles and three simple reference lines (top, bottom, zero) are plotted, keeping the chart uncluttered and compliant with presentation standards for published scripts.
3. How to Use
1. Attach the indicator to a separate pane (overlay = false) on any market and timeframe you trade.
2. Set the “Period (Value Chart)” to control how fast the fair‑value line adapts: shorter values react more quickly, longer values smooth more.
3. Adjust the “Volatility Factor” so that most candles stay between the upper and lower limits, with only true extremes touching or exceeding them.
4. Use the Value Chart candlesticks as a relative overbought/oversold tool:
- Candles pressing into the Top band suggest overvalued conditions and potential for pullbacks or reversions.
- Candles pressing into the Bottom band suggest undervalued conditions and potential for bounces.
5. Combine the signals with your existing price‑action, volume, or trend‑filter rules on the main chart; the Value Chart panel is designed as a context and timing tool, not a standalone trading system.
HTF Frequency Zone [BigBeluga]🔵 OVERVIEW
HTF Frequency Zone highlights the dominant price level (Point of Control) and the full high–low expansion of any higher timeframe — Daily, Weekly, or Monthly. It captures the frequency of closes inside each HTF candle and plots the most traded “frequency zone”, allowing traders to easily see where price spent the most time and where buy/sell pressure accumulated.
This tool transforms each higher-timeframe bar into a fully visualized structure:
• Top = HTF high
• Bottom = HTF low
• Midline = HTF Frequency POC
• Color-coded zones = bullish or bearish bias
• Labels = counts of bullish and bearish candles inside the HTF range
It is designed to give traders an immediate understanding of high-timeframe balance, imbalance, and price attraction zones.
🔵 CONCEPTS
HTF Partitioning — Each Weekly/Daily/Monthly candle is converted into a dedicated zone with its own High, Low, and Frequency Point of Control.
Frequency POC (Most Touched Price) — The indicator divides the HTF range into 100 bins and counts how many times price closed near each level.
Dominant Zone — The level with the highest frequency becomes the HTF “Value Zone,” plotted as a bold central line.
Directional Bias —
• Bullish HTF zone
• Bearish HTF zone
Internal Candle Counting — Within each HTF period the indicator counts:
• Buy candles (close > open)
• Sell candles (close < open)
This reveals whether intraperiod flow was bullish or bearish.
HTF Structure Blocks — High, Low, and POC are connected across the entire higher-timeframe duration, showing the real shape of HTF balance.
🔵 FEATURES
Automatic HTF Zone Construction — Generates a complete price zone every time the selected timeframe flips (Daily / Weekly / Monthly).
Dynamic High & Low Extraction — The indicator scans every bar inside the HTF window to find true extremes of the range.
100-Level Frequency Scan — Each close within the period is assigned to a bin, creating a detailed distribution of price interaction.
HTF POC Highlighting — The most frequent price level is plotted with a bold red line for immediate visual clarity.
Bull/Bear Coloring —
• Green → Bullish HTF zone.
• Orange → Bearish HTF zone.
Zone Shading — High–Low range is filled with a semi-transparent color matching trend direction.
Buy/Sell Candle Counters — Printed at the top and bottom of each HTF block, showing how many internal candles were bullish or bearish.
POC Label — Displays frequency count (how many touches) at the POC level.
Adaptive Threshold Warning — If bars inside the HTF window are too few (<10), the indicator warns the trader to switch timeframe.
🔵 HOW TO USE
Higher-Timeframe Biasing — Read the zone color to determine if the HTF candle leaned bullish or bearish.
Value Zone Reactions — Price often reacts to the Frequency POC; use it as support/resistance or liquidity magnet.
Range Context — Identify when price is trading near HTF highs (breakout potential) or lows (reversal potential).
Momentum Evaluation — More bullish internal candles = internal buying pressure; more bearish = internal selling pressure.
Swing Trading — Use HTF zones as the “macro map,” then execute trades on lower timeframes aligned with the zone structure.
Liquidity Awareness — The HTF POC often aligns with algorithmic liquidity levels, making it a strong reaction point.
🔵 CONCLUSION
HTF Frequency Zone transforms raw higher-timeframe candles into detailed distribution zones that reveal true market behavior inside the HTF structure. By showing highs, lows, buying/selling activity, and the most interacted price level (Frequency POC), this tool becomes invaluable for traders who want to align executions with powerful HTF levels, liquidity magnets, and structural zones.
Execution Heatmap v8 — Classic Blocks (Final Logic)This indicator visualizes real-time market context through a structured execution heatmap, representing multiple analytic dimensions in a compact on-chart panel. Designed for traders who rely on confluence-based decision making, it tracks the shifting behavior of price, volume, and structural regimes to help identify momentum shifts, exhaustion points, and directional conviction.
🔶 Overview
The Execution Heatmap v8 consolidates key elements from trend, volume, and momentum analysis into a single panel. Each row represents a core component of the execution model, colored dynamically to reflect bullish, bearish, neutral, or mixed states. The final block produces a BUY, SELL, or SELL-ALERT classification — fully aligned with the internal logic of the GOLDMASTER‑HUD framework.
🔸 Core Logic Components
VWAP Direction: Detects price bias relative to VWAP (overextended, below value, or neutral).
Impulse Engine: Evaluates momentum using RSI and MFI thresholds to determine directional energy.
Volume Surge: Highlights aggressive volume imbalances and determines the dominant side (bull or bear).
Fake Break Detection: Identifies false breakouts at recent swing extremes to flag potential reversals.
Regime Filter: Measures underlying trend structure using dual‑EMA alignment (20/50 EMA).
Pattern Recognition: Detects emerging HL (higher low) or LH (lower high) structures.
Structure Strength: Maps strong vs. weak structural phases based on regime and pattern alignment.
Final Signal Engine: Synthesizes all modules into actionable classifications:
BUY: Price structure supports trend continuation.
SELL‑ALERT: Early weakness or exhaustion detected within a strong up‑trend.
SELL: Confirmed reversal alignment (momentum, VWAP, volume, and structure all bearish).
WAIT: Caution when conditions remain inconclusive.
🟩🟥 Color‑Coded Heat Blocks
Each metric is represented as a colored cell:
Green: Bullish / upward bias
Red: Bearish / downward bias
Yellow: Neutral / weak / mixed
Dark gray: Undefined or transitional
⚙️ Customization
Adjustable panel position (bottom‑right, bottom‑left, top‑right, top‑left).
Non‑intrusive table layout optimized for overlaying on active charts.
Lightweight execution with minimal resource load, ideal for intraday use.
Relative Strength Line by QuantxThe Relative Strength Line compares the price performance of a stock against a benchmark index (e.g., NIFTY, S&P 500, Bank Nifty, etc.).
It does not indicate momentum of the stock itself — it indicates whether the stock is outperforming or underperforming the market.
🔍 How To Read It
RSL Behavior Meaning
RSL moving up Stock is outperforming the benchmark (strong leadership)
RSL moving down Stock is underperforming the benchmark (weakness vs market)
RSL breaking above previous highs Strong institutional demand, leadership candidate
RSL trending sideways Stock is performing similar to the index (no leadership)
📈 Why It Matters
Institutional traders and top-performing strategies focus on stocks showing relative strength BEFORE price breakout.
A stock making new RSL highs even before a price breakout often becomes a top performer in the coming trend.
🧠 Core Trading Edge
You don’t need to predict the market.
Just identify which stocks are being accumulated and leading the market right now — that’s what the Relative Strength Line reveals.
BuLLzEyE_MNQ FVG/IFVG SystemFVG Boxes
These are the main trading zones. The indicator automatically detects Fair Value Gaps and draws boxes on your chart:
• GREEN boxes = Bullish FVG (potential buy zone)
• RED boxes = Bearish FVG (potential sell zone)
• YELLOW boxes = IFVG (Inverse FVG - filled gaps that now act as support/resistance)
• GRAY boxes = Mitigated FVG (gap has been filled)
• WHITE dashed line = 50% level (optimal entry point within the FVG)
Session Boxes
Session boxes show you the high/low range of each major trading session. This helps identify where liquidity sits:
• PURPLE = Asia Session (6:00 PM - 3:00 AM ET)
• BLUE = London Session (3:00 AM - 12:00 PM ET)
• ORANGE = New York Session (9:30 AM - 4:00 PM ET)
• TEAL = Sydney Session (5:00 PM - 2:00 AM ET)
• LIME GREEN = Kill Zone / London-NY Overlap (8:00 AM - 11:00 AM ET) - BEST TRADING TIME
Entry Signals
• GREEN triangle pointing UP = Long entry signal at a Bullish FVG (not 100% reliable)
• RED triangle pointing DOWN = Short entry signal at a Bearish FVG (not 100% reliable)
Liquidity Sweeps
• RED X with 'SWEEP' = Previous Day High (PDH) was swept
• GREEN X with 'SWEEP' = Previous Day Low (PDL) was swept
• Dotted lines = PDH (red) and PDL (green) levels
Information Tables
HTF Bias Table (Top Right): Shows whether the higher timeframe (default 15m) is bullish or bearish, the number of active FVGs, and whether you're in the trading session.
Risk Calculator Table (Bottom Right): Shows your risk amount and calculates how many contracts you can trade for different stop loss sizes (5pt, 10pt, 15pt).
How It Works
What is a Fair Value Gap?
A Fair Value Gap (FVG) is a 3-candle pattern where aggressive buying or selling creates a price void. Specifically, it's when the wick of the first candle doesn't overlap with the wick of the third candle, leaving a gap in between. Price tends to return to these gaps to 'rebalance' before continuing in the original direction.
What is an Inverse FVG?
When an FVG gets filled (price returns and closes through the gap), it becomes an Inverse FVG (IFVG). These zones flip their polarity - a filled Bullish FVG becomes resistance, and a filled Bearish FVG becomes support. The indicator automatically converts mitigated FVGs to yellow IFVG boxes.
The 50% Entry Level
The dashed white line in each FVG represents the 50% level (also called Consequent Encroachment). This is considered the optimal entry point - it's the middle of the imbalance where price is most likely to react.
Suggested Trading Strategy
1. Check HTF Bias (top right table) - only trade in that direction
2. Wait for a liquidity sweep (SWEEP label appears)
3. Look for an FVG to form AFTER the sweep
4. Enter when price returns to the 50% level (dashed line)
5. Place stop loss below/above the FVG (add 2 ticks buffer)
6. Take profit at 1:2 or 1:3 risk-to-reward ratio
Settings Explained
FVG Settings
• Min FVG Size: Minimum gap size in points to be considered valid (default: 2.0)
• Max FVG Age: How many bars until an FVG is removed from chart (default: 50)
• Show 50% Entry Level: Toggle the dashed entry line on/off
Session Settings
• Show Session Boxes: Toggle all session boxes on/off
• Max Sessions to Show: How many historical sessions to display (default: 5)
• Individual Session Toggles: Turn each session (Asia/London/NY/Sydney/Kill Zone) on or off
Risk Calculator Settings
• Account Size: Your trading account balance
• Risk Per Trade: Percentage of account to risk per trade (default: 0.5%)
• Tick Value/Size: Contract specifications for MNQ ($0.50 per tick, 0.25 point tick size)
Tips for Best Results
1. Trade during the Kill Zone (8:00-11:00 AM ET) for best volatility and liquidity
2. Always align trades with HTF bias - don't fight the trend
3. Wait for liquidity sweeps before entering - this confirms smart money activity
4. Use the 50% level for entries - it offers the best risk-to-reward
5. Watch for IFVG zones as additional confluence for entries
6. Use the risk calculator to size positions properly - never risk more than you can afford
7. Session boxes help identify where stops are clustered - sweeps of these levels often precede reversals
Available Alerts
• New FVG Formed (Bullish or Bearish)
• Price Touching 50% Entry Level
• FVG Mitigated (gap filled)
• Long Entry Signal
• Short Entry Signal
• PDH/PDL Liquidity Sweep
─────────────────────────────────────
Created by BullyTrading
Designed for MNQ Prop Firm Trading
T Minus 4 HoursSupport and Resistance is a large part of price structure. However many complicate it with increasing exotic (and often valueless) derivatives and permutations.
This is very simple, it plots the high and low of the first 4 hours of the day. Think of it as a frame of reference, if the day is mean reversion or neutral (about 70% of the time) price bounces around these levels quite frequently.
If price travels to the bottom of the box, and moves below, and then re-enters the box, hit the buy button. If price travels to the top of the box, and moves above, and then re-enters the box, hit the sell button.
If price travels down to the bottom of the box, and moves below, and then tests the box, if that test fails and price continues down - hit the sell button.
If price travels up to the top of the box, and move above, and then tests the box, if that test fails and price continues up - hit the buy button.
Back to the FutureSupport and Resistance is a large part of price structure. However many complicate it with increasing exotic (and often valueless) derivatives and permutations.
This is very simple, it plots the high and low of yesterday. Think of it as a frame of reference, if the day is mean reversion or neutral (about 70% of the time) price bounces around these levels quite frequently.
If price travels to the bottom of the box, and moves below, and then re-enters the box, hit the buy button. If price travels to the top of the box, and moves above, and then re-enters the box, hit the sell button.
If price travels down to the bottom of the box, and moves below, and then tests the box, if that test fails and price continues down - hit the sell button.
If price travels up to the top of the box, and move above, and then tests the box, if that test fails and price continues up - hit the buy button.
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
