RSI Multi Levels kiawosch [TradingFinder] 7-14-42 Consolidation🔵 Introduction
The Relative Strength Index or RSI is a tool used to measure the speed and intensity of price movement, oscillating between zero and one hundred. It is commonly applied to identify strength or weakness in market momentum across different time intervals. Despite its simple formula and wide usage, the behavior of RSI within specific ranges often provides more precise information than traditional overbought and oversold levels.
The Multi RSI layout displays three RSI values with periods 7, 14 and 42. The seven period RSI plays the primary role in short term analysis. When this value enters predefined ranges, it shows highly consistent and interpretable behavior that can signal trend continuation, corrections or the start of a range structure. The other two values, RSI 14 and RSI 42, help reveal higher timeframe momentum and provide context for the depth and quality of price movement.
Three potential zones are defined, each representing a behavioral range. The position zones forms the basis for signal interpretation :
High Potential : 78 to 85 & 22 to 15
Mid Potential : 70 to 78 & 30 to 22
Low Potential : 58 to 62 & 42 to 38
These zones highlight areas where RSI reacts in specific ways to price movement. Entering the High Potential range usually aligns with new highs or lows in price and often precedes continuation after a correction. In contrast, reactions inside the Mid Potential range frequently appear during clean ranges or channel structures. This approach focuses on momentum quality and structural behavior rather than classic overbought and oversold thresholds.
In summary, the logic behind the signals follows three principles :
Trend continuation, When RSI 7 enters the High Potential zone and price prints a new high or low, continuation after a correction becomes the most likely outcome.
Reversal or slowdown, When RSI exits the High Potential zone while price is reaching a previous high or low, the probability of a short term reversal increases.
Range behavior, In clean ranges or channel structures, RSI 7 typically reacts inside the Mid Potential zone and produces consistent swing responses.
🔵 How to Use
This method is based on observing the repeating behavior of RSI within momentum zones and identifying moments when price continues after a shallow correction or, conversely, when signs of slowing and reversal appear. RSI 7 plays the main role since it gives the most sensitive response to short term price changes. Its entry into or exit from a potential zone, combined with the position of price relative to recent highs and lows, forms the core of the signal logic. RSI 14 and RSI 42 provide higher timeframe confirmation and help evaluate the broader strength or weakness behind each movement.
🟣 Trend continuation after entering the High Potential zone
When RSI 7 reaches the High Potential zone while price forms a new high or low, the probability of continuation becomes very high. The typical sequence includes a short correction in price and a retreat of RSI toward the Mid Potential zone. As long as price structure remains intact and RSI turns upward again, continuation becomes the most likely scenario. As shown in the charts, price often expands strongly after this type of correction and breaks the previous high.
🟣 Reversal or slowdown after exiting the High Potential zone
If RSI 7 enters the High Potential zone but then exits while price is interacting with a previous high or low, conditions for a short term reversal appear. This behavior is clear in the charts, where price hits a supply or demand area and RSI can no longer return to the upper zone. The drop in RSI reflects weakening momentum and, when accompanied by a confirming candle, increases the chance of a reversal or at least a temporary pause.
🟣 Strong reversal after hitting the Mid Potential zone during deeper corrections
Sometimes price enters a deeper corrective phase and RSI 7 moves into or through the Mid Potential zone. When this occurs near a previous low, it can mark the start of a significant reversal. The charts show this pattern clearly, where RSI turns upward while price reacts to support. If the other RSI values show relative alignment, the probability of a strong rebound increases. This signal is often seen after fast declines and can mark the beginning of a recovery wave.
🟣 Range structure and repetitive reactions inside the Mid Potential zone
When price enters a clean range or channel, the behavior of RSI 7 changes completely. In such conditions, RSI repeatedly reacts inside the Mid Potential zone. Each time price touches the upper or lower boundary of the range, RSI approaches the upper or lower part of this zone as well. The result is a sequence of predictable swing reactions, perfectly suitable for mean reversion strategies. Breakouts in these environments also tend to show higher failure rates.
🟣 Sharp reactions and fast reversals at extreme levels (RSI near 90 or below 10)
Although this approach is not based on classic overbought and oversold logic, extremely high or low RSI readings such as ninety often produce strong immediate reactions in price. These conditions usually occur after sudden spikes or emotional breakouts. As visible in the charts, RSI collapses quickly after reaching such extremes and price often reverses sharply. While not a core signal, these moments add meaningful context to momentum interpretation.
🔵 Settings
RSI Setting : This section allows enabling or disabling the three RSI values, adjusting their calculation length and customizing their colors. It is designed to help separate short, medium and longer term momentum visually on the chart.
Zones Setting : This section controls the display of momentum zones and the color applied to each area. Adjusting these colors or toggling them on and off helps the trader visually track the intensity and structure of momentum.
Levels Setting : This section allows editing the numeric boundaries of the levels or showing and hiding each one individually. These levels form the visual framework for interpreting RSI behavior within the defined momentum zones.
🔵 Conclusion
Examining RSI behavior across different momentum zones shows that entering these ranges creates relatively consistent patterns in price movement. Reaching the High Potential zone often corresponds to later stages of a trend, where price has the strength to continue after a brief correction and structure remains intact. In contrast, reactions within the Mid Potential zone occur more frequently when the market transitions into a range or a limited movement phase, where repetitive oscillations dominate.
Overall, observing RSI inside these zones helps distinguish between trending movement, corrective phases and range conditions with greater clarity. Entry or exit from each zone provides insight into the underlying strength or weakness of momentum and reveals where the market is positioned within its movement cycle. This perspective, based on momentum regions rather than traditional values alone, offers a more refined understanding of price behavior and highlights the likely direction of the next move.
Bands
INAZUMA Bollinger BandsThis is an indicator based on the widely used Bollinger Bands, enhanced with a unique feature that visually emphasizes the "strength of the breakout" when the price penetrates the bands.
Main Features and Characteristics
1. Standard Bollinger Bands Display
Center Line (Basis): Simple Moving Average (\text{SMA(20)}).
1 sigma Lines: Light green (+) and red (-) lines for reference.
2 sigma Lines (Upper/Lower Band): The main dark green (+) and red (-) bands.
2. Emphasized Breakout Zones: "INAZUMA / Flare" and "MAGMA"
The key feature is the activation of colored, expanding areas when the candlestick's High or Low breaks significantly outside the \pm 2\sigma bands.
Upper Side (Green Base / Flare):
When the High exceeds the +2\sigma line, a green gradient area expands upwards.
Indication: This visually suggests strong buying pressure or overbought conditions. The color deepens as the price moves further away, indicating higher momentum.
Lower Side (Red Base / Magma):
When the Low falls below the -2 sigma line, a red gradient area expands downwards.
Indication: This visually suggests strong selling pressure or oversold conditions. The color deepens as the price moves further away, indicating higher momentum.
Key Insight: This visual aid helps traders quickly assess the momentum and market excitement when the price moves outside the standard Bollinger Bands range. Use it as a reference for judging trend strength and potential entry/exit points.
Customizable Settings
You can adjust the following parameters in the indicator settings:
Length: The period used for calculating the Moving Average and Standard Deviation. (Default: 20)
StdDev (Standard Deviation): The multiplier for the band width (e.g., 2.0 for -2 sigma). (Default: 2.0)
Source: The price data used for calculation (Default: close).
TDI Fibonacci Volatility Bands Candle Coloring [cryptalent]"This is an advanced Traders Dynamic Index (TDI) candle coloring system, designed for traders seeking precise dynamic analysis. Unlike traditional TDI, which typically relies on a 50 midline with a single standard deviation band (±1 SD), this indicator innovatively incorporates Fibonacci golden ratio multiples (1.618, 2.618, 3.618 times standard deviation) to create multi-layered dynamic bands. It precisely divides the RSI fast line (green line) position into five distinct strength zones, instantly reflecting them on the candle colors, allowing you to grasp market sentiment in real-time without switching to a sub-chart.
Core Calculation Logic:
RSI Period (default 20), Band Length (default 50), and Fast MA Smoothing Period (default 1) are all adjustable.
The midline is the Simple Moving Average (SMA) of RSI, with upper and lower bands calculated by multiplying Fibonacci multiples with Standard Deviation (STDEV), generating three dynamic band sets: 1.618, 2.618, and 3.618.
Traders can quickly identify the following scenarios:
Extreme Overbought Zone (Strong Bullish, Red): Fast line exceeds custom threshold (default 82) and breaks above the specified band (default 2.618). This often signals overheating, potentially a profit-taking point or reversal short entry, especially at trend tops.
Extreme Oversold Zone (Strong Bearish, Green): Fast line drops below custom threshold (default 28) and breaks below the specified band (default 2.618). This is a potential strong rebound starting point, ideal for bottom-fishing or long entries.
Medium Bullish Zone (Yellow): Fast line surpasses medium threshold (default 66) and stands above the specified band (default 1.618), indicating bullish dominance in trend continuation.
Medium Bearish Zone (Orange): Fast line falls below medium threshold (default 33) and breaks below the specified band (default 1.618), signaling bearish control in segment transitions.
Neutral Zone (No Color Change): Fast line within custom upper and lower limits (default 34~65), retaining original candle colors to avoid noise interference during consolidation.
Color priority logic flows from strong to weak (Extreme > Medium > Neutral), ensuring no conflicts. All parameters are highly customizable, including thresholds, band selections (1.618/2.618/3.618/Midline/None), color schemes, and even optional semi-transparent background coloring (default off, transparency 90%) for enhanced visual layering.
Applicable Scenarios:
Intraday Trading: Capture extreme color shifts as entry/exit signals.
Swing Trading: Use medium colors to confirm trend extensions.
Long-Term Trend Following: Filter noise in neutral zones to focus on major trends.
Supports various markets like forex, stocks, and cryptocurrencies. After installation, adjust parameters in settings to match your strategy, and combine with other indicators like moving averages or support/resistance for improved accuracy.
If you're a TDI enthusiast, this will make your trading more intuitive and efficient!
IDLP – Intraday Daily Levels Pro [FXSMARTLAB]🔥 IDLP – Intraday Daily Levels Pro
IDLP – Intraday Daily Levels Pro is a precision toolkit for intraday traders who rely on objective daily structure instead of repainting indicators and noisy signals.
Every level plotted by IDLP is derived from one simple rule:
Today’s trading decisions must be based on completed market data only.
That means:
✅ No use of the current day’s unfinished data for levels
✅ No lookahead
✅ No hidden repaint behavior
IDLP reconstructs the previous trading day from the intraday chart and then projects that structure forward onto the current session, giving you a stable, institutional-style intraday map.
🧱 1. Previous Daily Levels (Core Structure)
IDLP extracts and displays the full previous daily structure, which you can toggle on/off individually via the inputs:
Previous Daily High (PDH)
Previous Daily Low (PDL)
Previous Daily Open
Previous Daily Close,
Previous Daily Mid (50% of the range)
Previous Daily Q1 (25% of the range)
Previous Daily Q3 (75% of the range)
All of these come from the day that just closed and are then locked for the entire current session.
What these levels tell you:
PDH / PDL – true extremes of yesterday’s price action (liquidity zones, breakout/reversal points).
Previous Daily Open / Close – how the market positioned itself between session start and end
Mid (50%) – equilibrium level of the previous day’s auction.
Q1 / Q3 (25% / 75%) internal structure of the previous day’s range, dividing it into four equal zones and helping you see if price is trading in the lower, middle, or upper quarter of yesterday’s range.
All these levels are non-repaint: once the day is completed, they are fixed and never change when you scroll, replay, or backtest.
🎯 2. Previous Day Pivot System (P, S1, S2, R1, R2)
IDLP includes a classic floor-trader pivot grid, but critically:
It is calculated only from the previous day’s high, low, and close.
So for the current session, the following are fixed:
Pivot P – central reference level of the previous day.
Support 1 (S1) and Support 2 (S2)
Resistance 1 (R1) and Resistance 2 (R2)
These levels are widely used by institutional desks and algos to structure:
mean-reversion plays, breakout zones, intraday targets, and risk placement.
Everything in this section is non-repaint because it only uses the previous day’s fully closed OHLC.
📏 3. 1-Day ADR Bands Around Previous Daily Open
Instead of a multi-day ADR, IDLP uses a pure 1-Day ADR logic:
ADR = Range of the previous day
ADR = PDH − PDL
From that, IDLP builds two clean bands centered around the previous daily Open:
ADR Upper Band = Previous Day Open + (ADR × Multiplier)
ADR Lower Band = Previous Day Open − (ADR × Multiplier)
The multiplier is user-controlled in the inputs:
ADR Multiplier (default: 0.8)
This lets you choose how “tight” or “wide” you want the ADR envelope to be around the previous day’s open.
Typical use cases:
Identify realistic intraday extension targets, Spot exhaustion moves beyond ADR bands, Frame reversals after reaching volatility extremes, Align trades with or against volatility expansion
Again, since ADR is calculated only from the completed previous day, these bands are totally non-repaint during the current session.
🔒 4. True Non-Repaint Architecture
The internal logic of IDLP is built to guarantee non-repaint behavior:
It reconstructs each day using time("D") and tracks:
dayOpen, dayHigh, dayLow, dayClose for the current day
prevDayOpen, prevDayHigh, prevDayLow, prevDayClose for the previous day
At the moment a new day starts:
The “current day” gets “frozen” into prevDay*
These prevDay* values then drive: Previous Daily Levels, Pivots, ADR.
During the current day:
All these “previous day” values stay fixed, no matter what happens.
They do not move in real time, they do not shift in replay.
This means:
What you see in the past is exactly what you would have seen live.
No fake backtests.
No illusion of perfection from repainting behavior.
🎯 5. Designed For Intraday Traders
IDLP – Intraday Daily Levels Pro is made for:
- Day traders and scalpers
- Index and FX traders
- Prop firm challenge trading
- Traders using ICT/SMC-style levels, liquidity, and range logic
- Anyone who wants a clean, institutional-style daily framework without noise
You get:
Previous Day OHLC
Mid / Q1 / Q3 of the previous range
Previous-Day Pivots (P, S1, S2, R1, R2)
1-Day ADR Bands around Previous Day Open
All calculated only from closed data, updated once per day, and then locked.
Gold Fair Value [Alpha Extract]Gold-anchored Bitcoin fair value model is a macro-fundamental valuation indicator that anchors Bitcoin price assessment to gold market dynamics, establishing fair value zones through percentage change influence modelling and adaptive band multipliers. This overlay system provides institutional-grade context for identifying accumulation zones, distribution zones, and fair value equilibrium across all market cycles with minimal chart clutter through sophisticated gradient fill visualization.
🔶 Gold-Anchored Valuation Framework
Establishes Bitcoin's theoretical fair value by integrating daily gold price movements into a smoothed asset baseline, applying percentage change calculations over configurable periods to measure gold's momentum influence. The system translates gold's relative strength or weakness into Bitcoin price expectations through adjustable influence multipliers, creating a dynamic fair value line that adapts to shifting macro-fundamental relationships between digital and traditional store-of-value assets.
🔶 Multi-Layer Statistical Band System
Implements asymmetric upper and lower band multipliers applied to the fair value baseline, creating five distinct valuation zones: extreme overvaluation, moderate overvaluation, fair value equilibrium, moderate undervaluation, and extreme undervaluation. The asymmetric configuration (default 1.46x upper, 0.74x lower) reflects Bitcoin's historical tendency toward asymmetric volatility patterns with more violent upside moves and grinding downside action, optimizing zone accuracy for actionable trading decisions.
🔶 Gradient Fill Visualization
Employs sophisticated transparency-based gradient fills between bands to create visually intuitive valuation heat maps, with darker orange shading indicating proximity to fair value and lighter shading showing extreme deviation zones. The system maintains chart readability by hiding individual band lines while preserving the filled zones, eliminating visual clutter while delivering maximum information density for rapid market assessment without overwhelming the trader with excessive line plots.
🔶 Historical Context & Position Management
The lower band zones have historically preceded periods of constructive price behavior including consolidation phases and early-stage recovery rallies, while upper band interactions have preceded distribution and correction events. This historical pattern recognition enables traders to position proactively based on valuation extremes rather than reactively chasing momentum, supporting systematic accumulation during undervaluation periods and graduated profit-taking during overvaluation extremes.
All analysis provided by Alpha Extract is for educational and informational purposes only. The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations.
Hyper Squeeze Sniper (Dual Side: Long + Short)Hyper Squeeze Sniper (Dual Side Strategy)
This script is a comprehensive Volatility Breakout System designed to identify and trade explosive price moves following periods of consolidation. It combines the classical "Squeeze" theory with Linear Regression Momentum, Volume Analysis, and an ATR-based Trailing Stop to filter false signals and manage risk effectively.
The script operates on a logic of "Compression -> Explosion -> Trend Following" suitable for both Long and Short positions.
🛠 Detailed Methodology (How it works)
1. The Squeeze Detection (Consolidation) The core concept relies on the relationship between Bollinger Bands (BB) and Keltner Channels (KC).
Condition: When the Bollinger Bands (Standard Deviation) contract and fall inside the Keltner Channels (ATR based), it indicates a period of extremely low volatility (The Squeeze).
Visual: The background turns Gray to indicate "Do Not Trade / Wait Mode".
2. Momentum Confirmation (Linear Regression) Instead of using standard lagging indicators, this script utilizes Linear Regression of the price deviation to determine the direction of the breakout.
If the Linear Regression Slope > 0, the bias is Bullish.
If the Linear Regression Slope < 0, the bias is Bearish.
3. Volume Validation To avoid fake breakouts, a Volume Spike filter is applied. A signal is only valid if the current volume exceeds its moving average by a defined multiplier (Default x1.2).
4. Risk Management: ATR Trailing Stop Once a trade is entered, the script calculates a dynamic Trailing Stop based on the Average True Range (ATR).
- Long: The stop line trails below the price and never moves down.
- Short: The stop line trails above the price and never moves up.
- Exit: The position is closed immediately when the price breaches this volatility-based safety line.
How to Use
1. Wait: Look for the Gray Background. This is the accumulation phase.
2. Entry:
LONG: Wait for a Green Triangle ▲ (Price breaks Upper BB + Vol Spike + Bullish Momentum).
SHORT: Wait for a Red Triangle ▼ (Price breaks Lower BB + Vol Spike + Bearish Momentum).
3. Exit: Close the position when the "X" mark appears or when candles cross the trailing safety line.
Settings
- BB Length/Mult: Adjust the sensitivity of the squeeze detection.
- Vol Spike Factor: Increase this to filter out low-volume breakouts.
- ATR Period/Mult: Adjust the trailing stop distance (Higher = Wider stop for swing trading).
Kernel Channel [BackQuant]Kernel Channel
A non-parametric, kernel-weighted trend channel that adapts to local structure, smooths noise without lagging like moving averages, and highlights volatility compressions, expansions, and directional bias through a flexible choice of kernels, band types, and squeeze logic.
What this is
This indicator builds a full trend channel using kernel regression rather than classical averaging. Instead of a simple moving average or exponential weighting, the midline is computed as a kernel-weighted expectation of past values. This allows it to adapt to local shape, give more weight to nearby bars, and reduce distortion from outliers.
You can think of it as a sliding local smoother where you define both the “window” of influence (Window Length) and the “locality strength” (Bandwidth). The result is a flexible midline with optional upper and lower bands derived from kernel-weighted ATR or kernel-weighted standard deviation, letting you visualize volatility in a structurally consistent way.
Three plotting modes help demonstrate this difference:
When the midline is shown alone, you get a smooth, adaptive baseline that behaves almost like a regression moving average, as shown in this view:
When full channels are enabled, you see how standard deviation reacts to local structure with dynamically widening and tightening bands, a mode illustrated here:
When ATR mode is chosen instead of StdDev, band width reflects breadth of movement rather than variance, creating a volatility-aware envelope like the example here:
Why kernels
Classical moving averages allocate fixed weights. Kernels let the user define weighting shape:
Epanechnikov — emphasizes bars near the current bar, fades fast, stable and smooth.
Triangular — linear decay, simple and responsive.
Laplacian — exponential decay from the current point, sharper reactivity.
Cosine — gentle periodic decay, balanced smoothness for trend filters.
Using these in combination with a bandwidth parameter gives fine control over smoothness vs responsiveness. Smaller bandwidths give sharper local sensitivity, larger bandwidths give smoother curvature.
How it works (core logic)
The indicator computes three building blocks:
1) Kernel-weighted midline
For every bar, a sliding window looks back Window Length bars. Each bar in this window receives a kernel weight depending on:
its index distance from the present
the chosen kernel shape
the bandwidth parameter (locality)
Weights form the denominator, weighted values form the numerator, and the resulting ratio is the kernel regression mean. This midline is the central trend.
2) Kernel-based width
You choose one of two band types:
Kernel ATR — ATR values are kernel-averaged, producing a smooth, volatility-based width that is not dependent on variance. Ideal for directional trend channels and regime separation.
Kernel StdDev — local variance around the midline is computed through kernel weighting. This produces a true statistical envelope that narrows in quiet periods and widens in noisy areas.
Width is scaled using Band Multiplier , controlling how far the envelope extends.
3) Upper and lower channels
Provided midline and width exist, the channel edges are:
Upper = midline + bandMult × width
Lower = midline − bandMult × width
These create smooth structures around price that adapt continuously.
Plotting modes
The indicator supports multiple visual styles depending on what you want to emphasize.
When only the midline is displayed, you get a pure kernel trend: a smooth regression-like curve that reacts to local structure while filtering noise, demonstrated here: This provides a clean read on direction and slope.
With full channels enabled, the behavior of the bands becomes visible. Standard deviation mode creates elastic boundaries that tighten during compressions and widen during turbulence, which you can see in the band-focused demonstration: This helps identify expansion events, volatility clusters, and breakouts.
ATR mode shifts interpretation from statistical variance to raw movement amplitude. This makes channels less sensitive to outliers and more consistent across trend phases, as shown in this ATR variation example: This mode is particularly useful for breakout systems and bar-range regimes.
Regime detection and bar coloring
The slope of the midline defines directional bias:
Up-slope → green
Down-slope → red
Flat → gray
A secondary regime filter compares close to the channel:
Trend Up Strong — close above upper band and midline rising.
Trend Down Strong — close below lower band and midline falling.
Trend Up Weak — close between midline and upper band with rising slope.
Trend Down Weak — close between lower band and midline with falling slope.
Compression mode — squeeze conditions.
Bar coloring is optional and can be toggled for cleaner charts.
Squeeze logic
The indicator includes non-standard squeeze detection based on relative width , defined as:
width / |midline|
This gives a dimensionless measure of how “tight” or “loose” the channel is, normalized for trend level.
A rolling window evaluates the percentile rank of current width relative to past behavior. If the width is in the lowest X% of its last N observations, the script flags a squeeze environment. This highlights compression regions that may precede breakouts or regime shifts.
Deviation highlighting
When using Kernel StdDev mode, you may enable deviation flags that highlight bars where price moves outside the channel:
Above upper band → bullish momentum overextension
Below lower band → bearish momentum overextension
This is turned off in ATR mode because ATR widths do not represent distributional variance.
Alerts included
Kernel Channel Long — midline turns up.
Kernel Channel Short — midline turns down.
Price Crossed Midline — crossover or crossunder of the midline.
Price Above Upper — early momentum expansion.
Price Below Lower — downward volatility expansion.
These help automate regime changes and breakout detection.
How to use it
Trend identification
The midline acts as a bias filter. Rising midline means trend strength upward, falling midline means downward behavior. The channel width contextualizes confidence.
Breakout anticipation
Kernel StdDev compressions highlight areas where price is coiling. Breakouts often follow narrow relative width. ATR mode provides structural expansion cues that are smooth and robust.
Mean reversion
StdDev mode is suitable for fade setups. Moves to outer bands during low volatility often revert to the midline.
Continuation logic
If price breaks above the upper band while midline is rising, the indicator flags strong directional expansion. Same logic for breakdowns on the lower band.
Volatility characterization
Kernel ATR maps raw bar movements and is excellent for identifying regime shifts in markets where variance is unstable.
Tuning guidance
For smoother long-term trend tracking
Larger window (150–300).
Moderate bandwidth (1.0–2.0).
Epanechnikov or Cosine kernel.
ATR mode for stable envelopes.
For swing trading / short-term structure
Window length around 50–100.
Bandwidth 0.6–1.2.
Triangular for speed, Laplacian for sharper reactions.
StdDev bands for precise volatility compression.
For breakout systems
Smaller bandwidth for sharp local detection.
ATR mode for stable envelopes.
Enable squeeze highlighting for identifying setups early.
For mean-reversion systems
Use StdDev bands.
Moderate window length.
Highlight deviations to locate overextended bars.
Settings overview
Kernel Settings
Source
Window Length
Bandwidth
Kernel Type (Epanechnikov, Triangular, Laplacian, Cosine)
Channel Width
Band Type (Kernel ATR or Kernel StdDev)
Band Multiplier
Visuals
Show Bands
Color Bars By Regime
Highlight Squeeze Periods
Highlight Deviation
Lookback and Percentile settings
Colors for uptrend, downtrend, squeeze, flat
Trading applications
Trend filtering — trade only in direction of the midline slope.
Breakout confirmation — expansion outside the bands while slope agrees.
Squeeze timing — compression periods often precede the next directional leg.
Volatility-aware stops — ATR mode makes channel edges suitable for adaptive stop placement.
Structural swing mapping — StdDev bands help locate midline pullbacks vs distributional extremes.
Bias rotation — bar coloring highlights when regime shifts occur.
Notes
The Kernel Channel is not a signal generator by itself, but a structural map. It helps classify trend direction, volatility environment, distribution shape, and compression cycles. Combine it with your entry and exit framework, risk parameters, and higher-timeframe confirmation.
It is designed to behave consistently across markets, to avoid the bluntness of classical averages, and to reveal subtle curvature in price that traditional channels miss. Adjust kernel type, bandwidth, and band source to match the noise profile of your instrument, then use squeeze logic and deviation highlighting to guide timing.
Damo's Custom EMA Bands 1.0I was making these manually for a long time. They just give me more peace of mind when I'm using EMAs. They feel more like a net catching price. These are easy to make. All they are is 3 EMAs with the Source at High, Low and (H+L)/2 for the midpoint.
I find on a 3-Day chart on BTC the 100 EMA is great for telling what trend we're are in.
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McMillan Volatility Bands (MVB) – with Entry Logic// McMillan Volatility Bands (MVB) with signal + entry logic
// Author: ChatGPT for OneRyanAlexander
// Notes:
// - Bands are computed using percentage volatility (log returns), per the Black‑Scholes framing.
// - Inner band (default 3σ) and outer band (default 4σ) are configurable.
// - A setup occurs when price closes outside the outer band, then closes back within the inner band.
// The bar that re‑enters is the "signal bar." We then require price to trade beyond the signal bar's
// extreme by a user‑defined cushion (default 0.34 * signal bar range) to confirm entry.
// - Includes alertconditions for both setups and confirmed entries.
Dynamic Fractal Flow [Alpha Extract]An advanced momentum oscillator that combines fractal market structure analysis with adaptive volatility weighting and multi-derivative calculus to identify high-probability trend reversals and continuation patterns. Utilizing sophisticated noise filtering through choppiness indexing and efficiency ratio analysis, this indicator delivers entries that adapt to changing market regimes while reducing false signals during consolidation via multi-layer confirmation centered on acceleration analysis, statistical band context, and dynamic omega weighting—without any divergence detection.
🔶 Fractal-Based Market Structure Detection
Employs Williams Fractal methodology to identify pivotal market highs and lows, calculating normalized price position within the established fractal range to generate oscillator signals based on structural positioning. The system tracks fractal points dynamically and computes relative positioning with ATR fallback protection, ensuring continuous signal generation even during extended trending periods without fractal formation.
🔶 Dynamic Omega Weighting System
Implements an adaptive weighting algorithm that adjusts signal emphasis based on real-time volatility conditions and volume strength, calculating dynamic omega coefficients ranging from 0.3 to 0.9. The system applies heavier weighting to recent price action during high-conviction moves while reducing sensitivity during low-volume environments, mitigating lag inherent in fixed-period calculations through volatility normalization and volume-strength integration.
🔶 Cascading Robustness Filtering
Features up to five stages of progressive EMA smoothing with user-adjustable robustness steps, each layer systematically filtering microstructure noise while preserving essential trend information. Smoothing periods scale with the chosen fractal length and robustness steps using a fixed smoothing multiplier for consistent, predictable behavior.
🔶 Adaptive Noise Suppression Engine
Integrates dual-component noise filtering combining Choppiness Index calculation with Kaufman’s Efficiency Ratio to detect ranging versus trending market conditions. The system applies dynamic damping that maintains full signal strength during trending environments while suppressing signals during choppy consolidation, aligning output with the prevailing regime.
🔶 Acceleration and Jerk Analysis Framework
Calculates second-derivative acceleration and third-derivative jerk to identify explosive momentum shifts before they fully materialize on traditional indicators. Detects bullish acceleration when both acceleration and jerk turn positive in negative oscillator territory, and bearish acceleration when both turn negative in positive territory, providing early entry signals for high-velocity trend initiation phases.
🔶 Multi-Layer Signal Generation Architecture
Combines three primary signal types with hierarchical validation: acceleration signals, band crossover entries, and threshold momentum signals. Each signal category includes momentum confirmation, trend-state validation, and statistical band context; signals are further conditioned by band squeeze detection to avoid low-probability entries during compression phases. Divergence is intentionally excluded for a purely structure- and momentum-driven approach.
🔶 Dynamic Statistical Band System
Utilizes Bollinger-style standard deviation bands with configurable multiplier and length to create adaptive threshold zones that expand during volatile periods and contract during consolidation. Includes band squeeze detection to identify compression phases that typically precede expansion, with signal suppression during squeezes to prevent premature entries.
🔶 Gradient Color Visualization System
Features color gradient mapping that dynamically adjusts line intensity based on signal strength, transitioning from neutral gray to progressively intense bullish or bearish colors as conviction increases. Includes gradient fills between the signal line and zero with transparency scaling based on oscillator intensity for immediate visual confirmation of trend strength and directional bias.
All analysis provided by Alpha Extract is for educational and informational purposes only. The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations.
CandleFlow — Adaptive-Colored Bollinger BandsEN — What it is
Classic Bollinger Bands with adaptive color. Bands turn green when the basis slope is rising and red when it is falling. Same BB math; only visuals adapt. Two-state only.
Features
• Works on any timeframe; built with daily crypto in mind
• Inputs: Length 20, Multiplier 2.0, MA Type (SMA/EMA/WMA), Slope Length, Up/Down thresholds, Band fill
• Alerts: Trend state turns Up / turns Down
Notes
• Invite-only access. Source code not provided.
• No profit guarantee; this is not financial advice.
KR — 요약
표준 볼린저 계산은 그대로, 기준선이 상승하면 초록/하락하면 빨강으로 자동 색상 전환. 일봉 크립토에 최적화. 입력값(기간 20, 배수 2.0, MA 타입, 기울기 길이, 상/하 임계값, 밴드 채우기), 알림(상승/하락 전환) 제공. 초대전용, 코드 비공개. 수익 보장 없음.
Trademark
Bollinger Bands® is a registered trademark of John Bollinger. Not affiliated or endorsed.
Advanced Candle Compression BollingerColors candles based on Bollinger Band width relative to its average — showing when volatility tightens.
Orange = medium compression
Red = strong compression
Candle color appears only after several consecutive bars meet the condition.
You can adjust thresholds, colors, bar count, and the Bollinger source (default: (High+Low+Close)/3).
Useful to spot low-volatility zones that often precede breakouts.
Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD)
Concept & Purpose
The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart.
Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption).
This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators.
In simple terms:
When MPD expands upward → buyer pressure dominates.
When MPD contracts downward → seller pressure dominates.
Calculation Overview
MPD uses a structural candle formula to compute directional pressure:
Body Ratio = (Close − Open) / (High − Low)
Wick Differential = (Lower Wick − Upper Wick) / (High − Low)
Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight)
Then it applies:
EMA smoothing (to stabilize short-term noise)
Standard deviation normalization (to maintain consistent scaling)
ATR projection (to adapt the signal visually to volatility)
This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart.
Customizable Inputs
Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes.
How to Use
The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator.
The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility.
The red line represents the ATR envelope, which defines the market’s expected volatility range.
MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope:
Above the ATR band → positive pressure and bullish bias.
Below the ATR band → negative pressure and bearish bias.
Hovering near the ATR band → neutral or indecisive conditions.
The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility.
Positive % = buying dominance.
Negative % = selling dominance.
Higher absolute values = stronger momentum compared to volatility.
To trade with MPD:
Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control.
Note transitions above or below the ATR level for early signs of momentum shifts.
Combine MPD signals with price structure, key levels, or volume for confirmation.
This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility.
Disclaimer
It introduces a novel structural–pressure approach to visualizing market dynamics.
For educational and analytical purposes only; this does not constitute financial advice.
Aggregated Scores Oscillator [Alpha Extract]A sophisticated risk-adjusted performance measurement system that combines Omega Ratio and Sortino Ratio methodologies to create a comprehensive market assessment oscillator. Utilizing advanced statistical band calculations with expanding and rolling window analysis, this indicator delivers institutional-grade overbought/oversold detection based on risk-adjusted returns rather than traditional price movements. The system's dual-ratio aggregation approach provides superior signal accuracy by incorporating both upside potential and downside risk metrics with dynamic threshold adaptation for varying market conditions.
🔶 Advanced Statistical Framework
Implements dual statistical methodologies using expanding and rolling window calculations to create adaptive threshold bands that evolve with market conditions. The system calculates cumulative statistics alongside rolling averages to provide both historical context and current market regime sensitivity with configurable window parameters for optimal performance across timeframes.
🔶 Dual Ratio Integration System
Combines Omega Ratio analysis measuring excess returns versus deficit returns with Sortino Ratio calculations focusing on downside deviation for comprehensive risk-adjusted performance assessment. The system applies configurable smoothing to both ratios before aggregation, ensuring stable signal generation while maintaining sensitivity to regime changes.
// Omega Ratio Calculation
Excess_Return = sum((Daily_Return > Target_Return ? Daily_Return - Target_Return : 0), Period)
Deficit_Return = sum((Daily_Return < Target_Return ? Target_Return - Daily_Return : 0), Period)
Omega_Ratio = Deficit_Return ≠ 0 ? (Excess_Return / Deficit_Return) : na
// Sortino Ratio Framework
Downside_Deviation = sqrt(sum((Daily_Return < Target_Return ? (Daily_Return - Target_Return)² : 0), Period) / Period)
Sortino_Ratio = (Mean_Return / Downside_Deviation) * sqrt(Annualization_Factor)
// Aggregated Score
Aggregated_Score = SMA(Omega_Ratio, Omega_SMA) + SMA(Sortino_Ratio, Sortino_SMA)
🔶 Dynamic Band Calculation Engine
Features sophisticated threshold determination using both expanding historical statistics and rolling window analysis to create adaptive overbought/oversold levels. The system incorporates configurable multipliers and sensitivity adjustments to optimize signal timing across varying market volatility conditions with automatic band convergence logic.
🔶 Signal Generation Framework
Generates overbought conditions when aggregated score exceeds adjusted upper threshold and oversold conditions below lower threshold, with neutral zone identification for range-bound markets. The system provides clear binary signal states with background zone highlighting and dynamic oscillator coloring for intuitive market condition assessment.
🔶 Enhanced Visual Architecture
Provides modern dark theme visualization with neon color scheme, dynamic oscillator line coloring based on signal states, and gradient band fills for comprehensive market condition visualization. The system includes zero-line reference, statistical band plots, and background zone highlighting with configurable transparency levels.
snapshot
🔶 Risk-Adjusted Performance Analysis
Utilizes target return parameters for customizable risk assessment baselines, enabling traders to evaluate performance relative to specific return objectives. The system's focus on downside deviation through Sortino analysis provides superior risk-adjusted signals compared to traditional volatility-based oscillators that treat upside and downside movements equally.
🔶 Multi-Timeframe Adaptability
Features configurable calculation periods and rolling windows to optimize performance across various timeframes from intraday to long-term analysis. The system's statistical foundation ensures consistent signal quality regardless of timeframe selection while maintaining sensitivity to market regime changes through adaptive band calculations.
🔶 Performance Optimization Framework
Implements efficient statistical calculations with optimized variable management and configurable smoothing parameters to balance responsiveness with signal stability. The system includes automatic band adjustment mechanisms and rolling window management for consistent performance across extended analysis periods.
This indicator delivers sophisticated risk-adjusted market analysis by combining proven statistical ratios in a unified oscillator framework. Unlike traditional overbought/oversold indicators that rely solely on price movements, the ASO incorporates risk-adjusted performance metrics to identify genuine market extremes based on return quality rather than price volatility alone. The system's adaptive statistical bands and dual-ratio methodology provide institutional-grade signal accuracy suitable for systematic trading approaches across cryptocurrency, forex, and equity markets with comprehensive visual feedback and configurable risk parameters for optimal strategy integration.
John Bollinger's Bollinger BandsJapanese below / 日本語説明は下記
This indicator replicates how John Bollinger, the inventor of Bollinger Bands, uses Bollinger Bands, displaying Bollinger Bands, %B and Bandwidth in one indicator with alerts and signals.
Bollinger Bands is created by John Bollinger in 1980s who is an American financial trader and analyst. He introduced %B and Bandwidth 30 years later.
🟦 What's different from other Bollinger Bands indicator?
Unlike the default Bollinger Bands or other custom Bollinger Bands indicators on TradingView, this indicator enables to display three Bollinger Bands tools into a single indicator with signals and alerts capability.
You can plot the classic Bollinger Bands together with either %B or Bandwidth or three tools altogether which requires the specific setting(see below settings).
This makes it easy to quantitatively monitor volatility changes and price position in relation to Bollinger Bands in one place.
🟦 Features:
Plots Bollinger Bands (Upper, Basis, Lower) with fill between bands.
Option to display %B or Bandwidth with Bollinger Bands.
Plots highest and lowest Bandwidth levels over a customizable lookback period.
Adds visual markers when Bandwidth reaches its highest (Bulge) or lowest (Squeeze) value.
Includes ready-to-use alert conditions for Bulge and Squeeze events.
📈Chart
Green triangles and red triangles in the bottom chart mark Bulges and Squeezes respectively.
🟦 Settings:
Length: Number of bars used for Bollinger Band middleline calculation.
Basis MA Type: Choose SMA, EMA, SMMA (RMA), WMA, or VWMA for the midline.
StdDev: Standard deviation multiplier (default = 2.0).
Option: Select "Bandwidth" or "%B" (add the indicator twice if you want to display both).
Period for Squeeze and Bulge: Lookback period for detecting the highest and lowest Bandwidth levels.(default = 125 as specified by John Bollinger )
Style Settings: Colors, line thickness, and transparency can be customized.
📈Chart
The chart below shows an example of three Bollinger Bands tools: Bollinger Band, %B and Bandwidth are in display.
To do this, you need to add this indicator TWICE where you select %B from Option in the first addition of this indicator and Bandwidth from Option in the second addition.
🟦 Usage:
🟠Monitor Volatility:
Watch Bandwidth values to spot volatility contractions (Squeeze) and expansions (Bulge) that often precede strong price moves.
John Bollinger defines Squeeze and Bulge as follows;
Squeeze:
The lowest bandwidth in the past 125 period, where trend is born.
Bulge:
The highest bandwidth in the past 125 period where trend is going to die.
According to John Bollinger, this 125 period can be used in any timeframe.
📈Chart1
Example of Squeeze
You can see uptrends start after squeeze(red triangles)
📈Chart2
Example of Bulge
You can see the trend reversal from downtrend to uptrends at the bulge(green triangles)
📈Chart3
Bulge DOES NOT NECESSARILY mean the beginning of a trend in opposite direction.
For example, you can see a bulge happening in the right side of the chart where green triangles are marked. Nevertheless, uptrend still continues after the bulge.
In this case, the bulge marks the beginning of a consolidation which lead to the continuation of the trend. It means that a phase of the trend highlighted in the light blue box came to an end.
Note: light blue box is not drawn by the indicator.
Like other technical analysis methods or tools, these setups do not guarantee birth of new trends and trend reversals. Traders should be carefully observing these setups along with other factors for making decisions.
🟠Track Price Position:
Use %B to see where price is located in relation to the Bollinger Bands.
If %B is close to 1, the price is near upper band while %B is close to 0, the price is near lower band.
🟠Set Alerts:
Receive alerts when Bandwidth hits highest and lowest values of bandwidth, helping you prepare for potential breakout, ending of trends and trend reversal opportunities.
🟠Combine with Other Tools:
This indicator would work best when combined with price action, trend analysis, or
market environmental analysis.
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このインジケーターはボリンジャーバンドの考案者であるジョン・ボリンジャー氏が提唱するボリンジャーバンドの使い方を再現するために、ボリンジャーバンド、%B、バンドウィズ(Bandwidth) の3つを1つのインジケーターで表示可能にしたものです。シグナルやアラートにも対応しています。
ボリンジャーバンドは1980年代にアメリカ人トレーダー兼アナリストのジョン・ボリンジャー氏によって開発されました。彼はその30年後に%Bとバンドウィズを導入しました。
🟦 他のボリンジャーバンドとの違い
TradingView標準のボリンジャーバンドや他のボリンジャーバンドとは異なり、このインジケーターでは3つのボリンジャーバンドツールを1つのインジケーターで表示し、シグナルやアラート機能も利用できるようになっています。
一般的に知られている通常のボリンジャーバンドに加え、%Bやバンドウィズを組み合わせて表示でき、設定次第では3つすべてを同時にモニターすることも可能です。これにより、価格とボリンジャーバンドの位置関係とボラティリティ変化をひと目で、かつ定量的に把握することができます。
🟦 機能:
ボリンジャーバンド（アッパーバンド・基準線・ロワーバンド）を描画し、バンド間を塗りつぶし表示。
オプションで%Bまたはバンドウィズを追加表示可能。
バンドウィズの最高値・最安値を、任意の期間で検出して表示。
バンドウィズが指定期間の最高値（バルジ※）または最安値（スクイーズ）に達した際にシグナルを表示。
※バルジは一般的にボリンジャーバンドで用いられるエクスパンションとほぼ同じ意味ですが、定義が異なります。(下記参照)
バルジおよびスクイーズ発生時のアラート設定が可能。
📈 チャート例
下記チャートの緑の三角と赤の三角は、それぞれバルジとスクイーズを示しています。
🟦 設定:
Length: ボリンジャーバンドの基準線計算に使う期間。
Basis MA Type: SMA, EMA, SMMA (RMA), WMA, VWMAから選択可能。
StdDev: 標準偏差の乗数（デフォルト2.0）。
Option: 「Bandwidth」または「%B」を選択（両方表示するにはこのインジケーターを2回追加）。
Period for Squeeze and Bulge: Bandwidthの最高値・最安値を検出する期間（デフォルトはジョン・ボリンジャー氏が推奨する125）。
Style Settings: 色、線の太さ、透明度などをカスタマイズ可能。
📈 チャート例
下のチャートは「ボリンジャーバンド」「%B」「バンドウィズ」の3つを同時に表示した例です。
この場合、インジケーターを2回追加し、最初に追加した方ではOptionを「%B」に、次に追加した方では「Bandwidth」を選択します。
🟦 使い方:
🟠 ボラティリティを監視する:
バンドウィズの値を見ることで、価格変動の収縮（スクイーズ）や拡大（バルジ）を確認できます。
これらはしばしば強い値動きの前兆となります。
ジョン・ボリンジャー氏はスクイーズとバルジを次のように定義しています：
スクイーズ: 過去125期間の中で最も低いバンドウィズ→ 新しいトレンドが生まれる場所。
バルジ: 過去125期間の中で最も高いバンドウィズ → トレンドが終わりを迎える場所。
この「125期間」はどのタイムフレームでも利用可能とされています。
📈 チャート1
スクイーズの例
赤い三角のスクイーズの後に上昇トレンドが始まっているのが確認できます。
📈 チャート2
バルジの例
緑の三角のバルジの箇所で下降トレンドから上昇トレンドへの反転が見られます。
📈 チャート3
バルジが必ずしも反転を意味しない例
下記のチャート右側の緑の三角で示されたバルジの後も、上昇トレンドが継続しています。
この場合、バルジは反転ではなく「トレンド一時的な調整（レンジ入り）」を示しており、結果的に上昇トレンドが継続しています。
この場合、バルジは水色のボックスで示されたトレンドのフェーズの終わりを示しています。
※水色のボックスはインジケーターが描画したものではありません。
また、他のテクニカル分析と同様に、これらのセットアップは必ず新しいトレンドの発生やトレンド転換を保証するものではありません。トレーダーは他の要素も考慮し、慎重に意思決定する必要があります。
🟠 価格とボリンジャーバンドの位置関係を確認する:
%Bを利用すれば、価格がバンドのどこに位置しているかを簡単に把握できます。
%Bが1に近ければ価格はアッパーバンド付近、0に近ければロワーバンド付近にあります。
🟠 アラートを設定する:
バンドウィズが一定期間の最高値または最安値に到達した際にアラートを設定することで、ブレイクアウトやトレンド終了、反転の可能性に備えることができます。
🟠 他のツールと組み合わせる:
このインジケーターは、プライスアクション、トレンド分析、環境認識などと組み合わせて活用すると最も効果的です。
JLine RZ+|SuperFundedJLINE with Resistance Zone+ — Quick Guide
What it is
This indicator generalizes the classic “JLINE” concept by letting you choose the MA type (SMA / EMA / WMA) and by converting mixed-order phases—when the fast/mid/slow MAs temporarily overlap—into forward-projected horizontal zones. It also shows a status label (current timeframe) and an optional higher-timeframe (HTF) status so you can align entries with broader trend context.
Why this is not a simple mashup
・Structure first: Instead of merely plotting MAs, the script detects mixed-order windows and tracks the max/min envelope formed by the 3 MAs during the overlap, then freezes and extends that range to the right as tradable zones (dynamic S/R derived from regime transitions).
・Context layering: You get a clear “Bullish/Bearish Perfect Order vs Mixed Zone” state, a color-coded MA band, and forward zones that persist beyond the regime change. This provides a workflow (identify structure → watch reactions at projected zones → confirm with status).
・Top-down alignment: The HTF status overlay makes it easy to avoid counter-trend trades or, if you prefer, time mean-reversion only when the current timeframe’s mixed zones line up with HTF conditions.
How it works (concise)
1. Compute fast/mid/slow MAs using your selected type (SMA/EMA/WMA).
2. Define states: Bullish Perfect Order (fast > mid > slow), Bearish Perfect Order (fast < mid < slow), or Mixed Zone (neither).
3. While Mixed, maintain an envelope using the highest/lowest of the three MAs. When the regime exits Mixed, save that envelope as a horizontal box and extend it into the future (older boxes auto-delete to keep the chart clean).
4. Paint an MA band between fast & slow with state-aware shading.
5. Show a corner label with the current state; optionally add the HTF state via request.security.
Parameters (UI mapping)
1. Moving Average Settings
・MA Type: SMA / EMA / WMA.
・Fast/Middle/Slow Period: Default 20/100/200, editable.
・Paint MA Band: Toggle the band fill between fast and slow MA.
2. Resistance Zone Settings
・Show Resistance Zone: Draw horizontal zones from mixed-order windows and extend to the right.
・Max Number of Zones: Cap the count; oldest zones are removed automatically.
・Zone Color: Set zone color/opacity.
3. Status Display Settings
・Show Status Label: On-chart label showing the current state.
・Label Position: Top/Bottom × Left/Right.
4. Multi-Timeframe Settings
・Show Higher Timeframe Status: Display the HTF state in the label.
・Higher Timeframe: Select the HTF (empty = disabled).
Practical usage
・Plan around zones: Treat zones as potential support/resistance derived from regime transitions. Observe how price reacts when it revisits/enters a zone.
・Align with trend: Prefer entries with the PO state (e.g., longs in Bullish PO) and use HTF status to filter. Mean-reversion is still possible, but require clear reaction (wick rejections, engulfings) at a zone.
・Manage clutter: If charts get busy, increase timeframe or lower “Max Number of Zones.”
・Risk first: SL beyond the opposite side of the zone; TPs can target adjacent zones or fixed R-multiples.
Notes & limitations
・Zones reflect MA-structure (mixed) envelopes, not price consolidations per se; they are structural guides, not guarantees.
・HTF readouts rely on request.security and your chosen timeframe; data quality and timing follow TradingView constraints.
Disclaimer
This tool suggests potential reaction areas; it cannot ensure outcomes. Volatility, news and liquidity conditions may invalidate any setup. Use appropriate position sizing and only risk capital you can afford to lose.
SuperFunded invite-only
To obtain access, please contact me via TradingView DM or the link in my profile.
JLINE with Resistance Zone (Advanced) — クイックガイド（日本語）
概要
本インジは、任意のMAタイプ（SMA / EMA / WMA）で高速・中速・低速の3本を描画し、順序が混在する期間（Mixed）で形成された3MAの最大値/最小値の包絡を水平ゾーンとして将来に延長して表示します。さらに、現在の状態ラベルと、任意で上位時間足（HTF）の状態も重ねて表示できます。
新規性（単なる寄せ集めではない点）
・構造を先に特定：MAを出すだけでなく、混在期間を検出→その間の3MA包絡を凍結して水平帯に変換→右に延長。レジーム転換由来のS/Rを作ります。
・文脈レイヤー：Bullish/BearishのパーフェクトオーダーとMixedを明示、MAバンドと将来に残るゾーンで、構造→反応→確認の手順が取りやすい構成。
・トップダウン整合：HTF状態をラベルに併記して、逆行を避けたり、逆張りでも根拠を強めたりできます。
使い方のヒント
ゾーン中心で計画：ゾーンはレジーム転換に基づく潜在的S/R。再訪時のローソク足の反応（ピンバー、包み足など）を確認してからエントリー。
トレンド整合：可能ならPO方向に合わせる。逆張りは明確な反応が条件。
視認性：時間軸を上げるか Max Number of Zones を下げて整理。
リスク管理：損切りは帯の反対側、利確は隣接ゾーンやR倍数で。
免責
ゾーンは反発を保証しません。ニュース・流動性の急変で機能しない場合があります。資金管理の徹底と自己責任でのご利用をお願いします。
SuperFunded招待専用スクリプト
このスクリプトはSuperFundedの参加者専用です。
Quantile Regression Bands [BackQuant]Quantile Regression Bands
Tail-aware trend channeling built from quantiles of real errors, not just standard deviations.
What it does
This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets.
Why “quantile” bands instead of Bollinger-style bands?
Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed.
Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars.
You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite.
How it works (intuitive)
Center line — a rolling linear regression approximates the local trend.
Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be.
Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets.
Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails.
Smoothing — a light EMA can be applied to reduce jitter in the line and bands.
What you see
Center (linear regression) line (optional).
Inner quantile bands (e.g., 25th/75th) with optional translucent fill.
Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.”
Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line.
Alerts when price crosses the outer bands (upper or lower).
How to read it
Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift.
Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials.
Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion.
Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope).
A simple trend interpretation can be derived from the bar colouring
Good use-cases
Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat.
Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center.
Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks.
Inputs (quick guide)
Source — price input used for the fit (default: close).
Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive.
Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer).
Show toggles — independently toggle center line, inner bands, outer bands, and their fills.
Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone.
Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels.
Bar Coloring — optional trend tint from the center line’s momentum.
Practical settings
Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95.
Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets.
Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps.
Signal ideas
Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue.
Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings.
Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band).
Alerts included
“Price Crosses Upper Outer Band” — potential overextension or breakout risk.
“Price Crosses Lower Outer Band” — potential capitulation or breakdown risk.
Notes
The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward.
Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars.
Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves.
Final thought
Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
Rolling Range Bands by tvigRolling Range Bands
Plots two dynamic price envelopes that track the highest and lowest prices over a Short and Long lookback. Use them to see near-term vs. broader market structure, evolving support/resistance, and volatility changes at a glance.
What it shows
• Short Bands: recent trading range (fast, more reactive).
• Long Bands: broader range (slow, structural).
• Optional step-line style and shaded zones for clarity.
• Option to use completed bar values to avoid intrabar jitter (no repaint).
How to read
• Price pressing the short high while the long band rises → short-term momentum in a larger uptrend.
• Price riding the short low inside a falling long band → weakness with trend alignment.
• Band squeeze (narrowing) → compression; watch for breakout.
• Band expansion (widening) → rising volatility; expect larger swings.
• Repeated touches/rejections of long bands → potential areas of support/resistance.
Inputs
• Short Window, Long Window (bars)
• Use Close only (vs. High/Low)
• Use completed bar values (stability)
• Step-line style and Band shading
Tips
• Works on any symbol/timeframe; tune windows to your market.
• For consistent scaling, pin the indicator to the same right price scale as the chart.
Not financial advice; combine with trend/volume/RSI or your system for entries/exits.
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution.
🔶 Advanced Noise Reduction
Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions.
advancedNoiseFilter(sourceData, filterLength, sigmaParam) =>
weightSum = 0.0
valueSum = 0.0
centerPoint = (filterLength - 1) / 2
for index = 0 to filterLength - 1
gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2))
weightSum += gaussianWeight
valueSum += sourceData * gaussianWeight
valueSum / weightSum
🔶 Adaptive Moving Average Core Engine
Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases.
// Calculate adaptive parameters
adaptiveLength = (periodLength - 1) / 2
logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0)
powerFactor = math.max(logFactor - 2, 0.5)
relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0
adaptivePower = math.pow(relativeVol, powerFactor)
bandwidthFactor = math.sqrt(adaptiveLength) * logFactor
🔶 Intelligent Market Structure Analysis
Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity.
🔶 Multi-Component Momentum Analysis
Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts.
// Z-score momentum analysis
rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod)
rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod)
rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation
if math.abs(rsiZScore) > zSignificanceLevel
rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal
❓How It Works
🔶 Dynamic Channel Configuration
Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy.
dynamicChannelEngine(baselineData, channelLength, methodType) =>
switch methodType
"ATR" => ta.atr(channelLength)
"Standard Deviation" => ta.stdev(baselineData, channelLength)
"Gaussian Deviation" =>
weightArray = array.new_float()
totalWeight = 0.0
for i = 0 to channelLength - 1
gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2))
weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i)
math.sqrt(weightedVariance / totalWeight)
🔶 Signal Processing Pipeline
Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation.
🔶 Confidence Transformation System
Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions.
🔶 Enhanced Visual Presentation
Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes.
🔶 Real-Time Information Dashboard
Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment.
🔶 Intelligent Alert System
Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration.
🔶 Performance Optimization
Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions.
This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
Snapfront WCTφ Coherence BandsSnapfront Coherence Bands — WCTφ (v6)
The Snapfront Coherence Bands (SCB) extend classic ATR-style bands with a coherence-driven engine. Instead of simple volatility envelopes, SCB adapt dynamically to market entropy, trend stability, and regime detection.
Core Features:
📊 WCTφ (Weighted Coherence Tracking) to measure entropy & disorder
🔍 Adaptive band width scaling with chaos factor (ATR × coherence)
🎯 Regime coloring:
Trend (lime)
Breakout (aqua)
Mean reversion (yellow)
Exhaustion (orange)
⚡ Squeeze detector with percentile-based compression zones
🟢/🔴 Entry/exit arrows on crossovers (optional)
Use Cases:
Spot high-clarity trend moves vs. noisy ranges
Anticipate volatility squeezes & breakout setups
Filter trades by regime classification
Visualize price stability with adaptive banding
⚠️ Invite-Only Access:
Available exclusively via SnapfrontTech. Subscription required.
ADR H/L + Bull/Bear TargetsThis indicator calculates the Average Daily/Weekly Range over any given period and plots the Bull and Bear targets for that Session Daily/Weekly or both. Classic targets are calculated at ADR/AWR +/- .50 .75 1.00 1.25. Green is for the + and RED is for the - but colors can been changed to suit.
In 'Settings' there is the ability to toggle:
1. How many sessions you want to plotting on your chart.
2. Switching ON/OFF Bull/Bear targets.
3. Line color/thickness
4. Ability to offset Header for ADR/AWR vertically.
5. I've put in there a FIB option as well as Classic. FIB counts are at .382 .50 .618 1.00 of ADR and labelled as such.
Matrix bands by JaeheeMatrix Bands — multi-sigma EMA bands for price dispersion context (no signals)
📌 What it is
Matrix Bands draws an EMA-based central line with multiple standard-deviation envelopes at ±1σ, ±1.618σ, ±2σ, ±2.618σ, ±3σ.
Thin core lines show the precise band levels, while subtle outer “glow” lines improve readability without obscuring candles.
📌 How it works (concept)
Basis: EMA of the selected source (default: close)
Dispersion: Rolling sample standard deviation over the same length
Bands: Basis ± k·σ for k ∈ {1, 1.618, 2, 2.618, 3}
This is not a strategy and does not generate trade signals.
It provides price dispersion context only.
📌 Why these levels together (justification of the combination)
Using multiple σ layers reveals graduated risk zones in one view:
±1σ: routine fluctuation
±1.618σ & ±2σ: extended but still common excursions
±2.618σ & ±3σ: statistically rare extremes, where mean-reversion risk or trend acceleration risk increases
Combining these specific multipliers allows traders to judge positioning vs. volatility instantly, without switching between separate indicators or re-configuring a single band.
📌 How it differs from classic Bollinger Bands
Unlike classic Bollinger Bands, which typically use an SMA basis and only ±2σ envelopes,
Matrix Bands uses an EMA basis for faster trend responsiveness and plots five sigma levels (±1, ±1.618, ±2, ±2.618, ±3).
This design allows traders to visualize market dispersion across multiple statistical thresholds simultaneously, making it more versatile for both trend-following and mean-reversion contexts.
📌 How to read it (context, not signals)
Mean-reversion context: Moves beyond ±2σ may indicate stretched conditions; wait for your own confirmation signals before acting
Trend context: In strong trends, price can “ride” the outer bands; sustained closes near +2σ~+3σ (uptrend) or −2σ~−3σ (downtrend) suggest persistent momentum
Regime observation: Band width expands in high volatility and contracts in quiet regimes; adjust stops and sizing accordingly
📌 Inputs
BB Length: lookback period for EMA and σ (default: 20)
Source: price source for calculations
📌 Design notes
Thin inner lines = exact levels
Soft outer lines = readability “glow” only; no effect on calculations
Overlay display keeps the chart uncluttered
📌 Limitations & good practice
No entry/exit logic; use with your own strategy rules
Volatility interpretation varies by timeframe
Past patterns do not guarantee future outcomes; risk management is essential
📌 Defaults & scope
Works on any symbol with OHLCV
No alerts, no strategy results, no performance claims
