Batoot Algo PureBatoot Algo (Pure Analysis Mode)
Indicator Overview
Batoot Algo is an advanced technical analysis indicator based on:
Price Action and geometric chart patterns
Higher Timeframe (HTF) trend filtering
Volume confirmation
Breakout & Retest logic
Head & Shoulders pattern detection
Analysis-only indicator. No Buy/Sell labels on the chart. Alerts and Dashboard only.
The goal is clean charts and smarter trading decisions.
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Entry Modes
Aggressive (Breakout)
Immediate entry on breakout
Requires:
Confirmed breakout
High volume
Optional trend alignment
Conservative (Retest)
Breakout → Wait for retest → Confirmation candle
Reduces false signals
Suitable for patient trading
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HTF Trend Filter
Uses EMA crossover on higher timeframe:
EMA 50
EMA 200
EMA50 > EMA200 → Bullish EMA50 < EMA200 → Bearish
Filter can be enabled or disabled in settings.
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Price Patterns Detected
Automatically detects and draws:
Bullish / Bearish Flags
Channels
Triangles / Pennants
Rising Wedge (Bearish)
Falling Wedge (Bullish)
The area between support and resistance lines is dynamically filled based on the pattern.
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Yellow Candle (High Volume)
Yellow candles indicate High Volume.
Triggered when:
Current candle volume >= Average volume of last 20 candles × volume multiplier
Default multiplier: 1.5
Confirms strong breakouts. Not a standalone entry signal.
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Head & Shoulders Detection
Supports:
Head & Shoulders (Bearish)
Inverse Head & Shoulders (Bullish)
Neckline drawn automatically. Breakout validated with volume. Pattern status shown in Dashboard.
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Dashboard
Displays:
Entry Mode (Aggressive / Conservative)
HTF Trend
Current Pattern
Head & Shoulders Status
Market Status: ENTRY BUY, ENTRY SELL, WAIT RETEST, SCANNING
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Alerts
Alerts trigger only when:
Pattern confirmed
Breakout / Retest logic satisfied
High volume confirmed
Trend filter (if enabled) passes
No trade labels plotted on chart.
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License & Attribution
Licensed under Creative Commons Attribution 4.0 (CC BY 4.0)
Free to use and modify. Attribution required. Removing or changing the author name is not allowed.
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This indicator is for technical analysis purposes only and is not financial advice. Always use proper risk management.
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Clean chart, smart analysis, better trading decisions.
[i]price
Laguerre Filter [BackQuant]Laguerre Filter
Overview
The Laguerre Filter is a powerful trend-following tool designed to smooth price action while maintaining responsiveness to market changes. It is based on the Laguerre recursive filter, which is a type of signal processing filter that adapts to both the current price dynamics and the underlying trend. The Laguerre Filter can be seen as a method to reduce market noise, enabling traders to more easily identify the strength and direction of trends while minimizing lag.
The Laguerre Filter is well-suited for markets with varying volatility levels, offering a smoother representation of price action without the delay associated with traditional moving averages. By dynamically adjusting to price movements, the Laguerre Filter provides a more adaptive and reliable signal compared to simpler smoothing techniques.
What is the Laguerre Filter?
The Laguerre Filter is derived from the Laguerre polynomial, which is used in signal processing for smooth filtering of data. The Laguerre filter is a recursive filter, meaning that each new value is calculated based on both the current price data and previous values, with a weighting system that allows it to adapt to market conditions. This recursive nature helps reduce the impact of short-term fluctuations, enabling the filter to focus on the underlying trend.
The Laguerre filter uses a feedback mechanism, where the input signal (price data) is smoothed iteratively. This iterative process helps avoid the lag that is typically associated with traditional moving averages while still capturing the overall trend direction.
The filter is designed to have:
Adaptive behavior: It reacts quickly to significant price changes while ignoring minor fluctuations.
Reduced noise: By filtering out random short-term price movements, it provides a clearer view of the underlying trend.
Customizability: Traders can adjust the filter’s sensitivity through user inputs, making it adaptable to different market conditions.
Core Calculation Methodology
The core of the Laguerre Filter lies in its recursive calculation:
Each new value is calculated using the previous value along with the current price input.
The recursive formula is governed by two key parameters: the damping factor (gamma) and the order of the filter (number of Laguerre elements).
The damping factor controls how responsive the filter is to changes in price. A higher gamma value makes the filter smoother but introduces more lag, while a lower gamma value makes it more reactive to price changes but can introduce more noise.
The order defines how many Laguerre elements are used in the calculation. A higher order results in a smoother output but with more delay, while a lower order provides a faster response but less smoothing.
The filter works by weighting previous values with a binomial weighting system, which assigns more weight to recent values and less weight to older values. This creates a dynamic smoothing effect that adapts to price volatility, ensuring that the filter is neither too slow nor too noisy.
Signal Logic and Trend Detection
The Laguerre Filter continuously evaluates the strength and direction of the trend by comparing the current smoothed value to the previous value:
If the current value is greater than the previous value, the trend is considered bullish, and the filter will signal a long condition.
If the current value is less than the previous value, the trend is considered bearish, and the filter will signal a short condition.
The trend detection logic is based on the recursive nature of the filter, which smooths price movements over time. This allows the filter to capture the broader trend while minimizing the influence of short-term price fluctuations.
The trend state is also visually represented by color-coding:
Green color represents an uptrend (bullish condition).
Red color represents a downtrend (bearish condition).
Neutral (white) indicates no clear trend direction.
This color-coding helps traders easily identify the prevailing trend and decide whether to enter or exit trades based on the trend's strength.
Laguerre Filter Behavior and Performance
The performance of the Laguerre Filter can be influenced by several factors:
Gamma (Damping Factor): A higher gamma value results in a smoother filter but increases lag. A lower gamma value allows for a faster response but may introduce more noise, making it more reactive to smaller price changes.
Filter Order: The order determines how many Laguerre elements are used in the filter calculation. A higher order provides more smoothing but increases lag, while a lower order results in a quicker response but less smoothing.
The sweet spot for gamma is typically between 0.7 and 0.85, where the filter offers a good balance between smoothness and responsiveness. The filter order is usually set to 4 for classic Laguerre filtering, but higher orders can be used for more smoothing if needed.
The Laguerre Filter’s performance shines in markets with sustained trends, where the filter can effectively capture and represent the underlying direction without excessive lag. It is particularly useful in volatile markets, as it helps smooth out noise while providing a clear picture of the trend.
Visual Presentation
The Laguerre Filter provides a dynamic, color-coded line that follows the trend direction. This line can be displayed alongside price data to visually highlight the market trend. In addition to the main Laguerre line, several visual enhancements can be applied:
Gradient fill between the price and the Laguerre Filter line, providing a visual cue for bullish or bearish market conditions.
Candle coloring to reflect the current trend, making it easier to spot trend reversals or confirmations directly on the chart.
Background shading to visually highlight areas of strong trend or consolidation.
Edge glow effect that highlights trend boundaries, making it easy to spot key levels of support or resistance.
These visual elements enhance the usability of the Laguerre Filter, allowing traders to quickly assess the market trend and make informed decisions.
Practical Use Cases
1) Trend Following
The Laguerre Filter is ideal for trend-following strategies. By using the filter to identify the prevailing trend, traders can:
Enter long positions when the Laguerre Filter turns bullish (green).
Enter short positions when the Laguerre Filter turns bearish (red).
By aligning trades with the dominant trend, traders can improve their chances of success.
2) Trend Strength Assessment
The Laguerre Filter can also be used to assess the strength of the trend:
A rising Laguerre value indicates a strengthening uptrend.
A falling Laguerre value indicates a strengthening downtrend.
A flattening Laguerre value signals weakening momentum or consolidation.
This information can be used to adjust position sizing or to decide when to enter or exit a trade.
3) Trade Management
The Laguerre Filter can also assist in trade management:
Use the Laguerre line as a trailing stop for long positions in an uptrend.
Scale out of positions as the Laguerre value begins to flatten or reverse.
Use the Laguerre Filter to avoid trades when the market is in consolidation or lacks a clear trend.
Tuning Guidelines
The Laguerre Filter can be adjusted for different market conditions using the following parameters:
Gamma (Damping Factor): Adjust for the desired level of responsiveness versus smoothness. Typical values range from 0.7 to 0.85.
Filter Order: Adjust to control the level of smoothing. The default value of 4 is a good starting point, but higher orders can be used for smoother filters.
Summary
The Laguerre Filter is a versatile and adaptive trend-following indicator that smooths price data and reduces noise, making it easier to identify and follow trends. By using recursive smoothing techniques and adjustable parameters, the Laguerre Filter provides an accurate representation of market conditions with minimal lag. It is especially useful in volatile markets where traditional moving averages may fail to capture the underlying trend. With its color-coded trend detection, gradient fills, and customizable settings, the Laguerre Filter is a powerful tool for traders looking to stay aligned with the prevailing market direction.
[SUMIT] Trade line strategy 05:00pm to 11:00pmSUMIT INGOLE
This indicator is created by Sumit Ingole, a trader from Maharashtra, India, based on real-time market experience.
It helps identify market direction and clean entry zones with a simple structure.
Best used with proper risk management.
Trade TrackerThis indicator is a lightweight trade P/L monitor that takes a manual entry price, direction (long/short), position size, and a configurable dollar value per point/tick.
It computes real-time profit/loss by comparing the current close to the entry price, converting the move into points and then dollars based on your size and tick value.
On the last bar, it draws an entry line at the specified price and renders a stacked label at that level showing Buy/Sell, size, dollar P/L (green/red), and the point P/L.
It continuously deletes and redraws the line/labels to keep the chart clean, and it also plots the entry price so the value is visible in the data window and price scale.
P/E Ratio (TTM)This indicator plots the trailing P/E ratio (TTM) using GAAP EPS (TTM) sourced directly from TradingView’s fundamental data. It includes valuation‑zone color coding, yearly labels, and a clean, compressed visual layout suitable for most equities.
The goal is to provide a fast, intuitive view of how expensive or cheap a stock is relative to its historical earnings power.
Note:
The indicator caps P/E values around 120 for visual clarity.
Negative P/E ratios are intentionally excluded, since P/E is undefined when EPS is negative.
You can adjust the cap or remove it entirely if you prefer a full‑range view.
This tool is especially useful for identifying periods when a company is trading at historically elevated or discounted valuation levels.
Quant Labs Edge Filter (Community Edition)A market-structure filter designed to identify when no real edge exists.
Edge Filter evaluates price location relative to structure to define market posture — long bias, short bias, or stand aside. It does not generate trade signals and is intentionally designed to reduce overtrading.
Clear Posture States
Near Highs — Short Bias
Near Lows — Long Bias
No Edge — Stand Aside
When edge is absent, patience is the strategy.
Why It Stands Out
Most indicators encourage action.
Edge Filter encourages restraint.
Its purpose is to protect capital, attention, and decision quality by filtering out low-quality environments.
Community Edition
This version publishes the core logic openly for transparency and education.
Private access versions may exist for traders seeking continuity and stewardship.
Bottom Line
Trade less.
Trade better.
Wait for edge.
— QuantLabs
Support & Resistance Automated📌 Support and Resistance Automated (Pivot-Based)
Support and Resistance Automated is a lightweight and fully automated indicator that plots key support and resistance levels using pivot highs and pivot lows. It helps traders quickly identify important price reaction zones without manual drawing.
This indicator is especially useful for price-action traders, swing traders, and intraday traders who rely on clean charts and objective levels.
🔍 How It Works
Pivot Highs → Resistance Levels
Pivot Lows → Support Levels
Each detected pivot creates a horizontal dotted line that extends forward, allowing you to observe how price reacts over time.
Once a level is formed, it is kept permanently on the chart — no repainting, no disappearing levels.
⚙️ Customizable Settings
You can easily adjust:
Left & Right Pivot Bars – control how strong a pivot must be
Line Extension Length
Line Width
Support & Resistance Colors
Show / Hide Pivot Highs and Pivot Lows independently
This flexibility allows the indicator to adapt to intraday, swing, or higher-timeframe analysis.
✅ Key Features
✔ Fully automatic support & resistance detection
✔ Based on proven pivot-point logic
✔ No repainting
✔ Clean, minimal chart appearance
✔ Unlimited support & resistance levels
✔ Works on all timeframes & instruments
📈 Best Use Cases
Identifying key demand and supply zones
Planning entries, targets, and stop-losses
Confluence with price action, RSI, moving averages
Breakout and rejection-based strategies
LARGER PRICE LINE Adjustable (UPDATED)LARGER PRICE LINE
I made this so I could SEE THE PRICE LINE BETTER and try to reduce some eye strain!!
Hope it helps... enjoy! comment for improvements or suggestions
Improved Adjustable Size and Color for the Price Line and Price Box
Adjustment for Price Line: Size and Color plus Solid Line, Dashed or Dotted Line
Adjustments include: Price Box Text Size and Color (Small, Normal, Large, Huge!)
Adjustable Right Side Offset for Price Box
Gap Tracker Indicator v5Gap Tracker Indicator - Description
Purpose: The Gap Tracker identifies price gaps on charts and visualizes unfilled gap zones that may act as future support/resistance levels.
What it shows:
Gap zones as colored rectangles:
Red boxes = bearish gaps (price gapped down, leaving unfilled space above)
Green boxes = bullish gaps (price gapped up, leaving unfilled space below)
How gaps form:
A gap occurs when the opening price of one candle is significantly different from the closing price of the previous candle
Common after weekends, holidays, or major news events when markets are closed
Gaps create "empty" price zones with no trading activity
Trading significance:
Many traders believe gaps tend to "fill" eventually (price returns to the gap zone)
Unfilled gaps can act as magnetic levels - price often revisits them
Gap zones may provide support (bullish gaps) or resistance (bearish gaps)
On your chart:
Multiple red boxes show unfilled bearish gaps where price gapped down
Green boxes show unfilled bullish gaps where price gapped up
The indicator tracks these zones until price fills them completely
Right side shows "GAP TRACKER" panel with active gaps: Aktywne (2), Zamknięte (9), Zakres 7d (168)
Key insight: The concentration of unfilled gaps suggests potential magnetic zones where price may return for "gap fill" trades. Traders often use these levels for entries, exits, or stop placement.
Kalman Hull Trend Score [BackQuant]Kalman Hull Trend Score
Overview
Kalman Hull Trend Score is a trend-strength and regime-evaluation indicator that combines two ideas, Kalman filtering and Hull-style smoothing, then measures persistence of that filtered trend using a rolling score. The goal is to produce a cleaner, more stable trend read than typical moving average tools, while still reacting fast enough to be practical in live markets.
Instead of treating a moving average as a simple line you cross, this indicator turns the filtered trend into an oscillator-like score that answers: “Is the smoothed trend consistently progressing, or is it stalling and degrading?”
Core idea
The indicator is built from two components:
A Kalman-based smoothing engine that estimates price state and reduces noise adaptively.
A Hull-style construction that uses multiple Kalman passes to create a responsive, low-lag trend filter.
Once the Kalman Hull filter is built, a persistence score is calculated by comparing the current Kalman Hull value to many past values. The result is a trend score that rises in sustained trends and compresses or flips during deterioration.
Why Kalman instead of standard smoothing
Traditional moving averages apply fixed smoothing rules regardless of market conditions. A Kalman filter behaves differently, it is designed to estimate an underlying state in noisy data, adjusting how much it “trusts” new price information versus prior estimates.
This script exposes that behavior through two key controls:
Measurement Noise: how noisy the observed price is assumed to be.
Process Noise: how much the underlying state is allowed to evolve from bar to bar.
Together, these settings let you tune the balance between smoothness and responsiveness without relying on blunt averaging alone.
Kalman filter mechanics (conceptual)
Each update cycle follows the classic structure:
Prediction: assume the state continues, and expand uncertainty by process noise.
Update: compute Kalman Gain, then blend the new price observation into the estimate.
Correction: reduce uncertainty based on how much the filter accepted the new information.
When measurement noise is higher, the filter becomes more conservative, smoothing harder. When process noise is higher, the filter adapts faster to regime changes, but can become more reactive.
Check out the original script:
Kalman Hull construction
The “Hull” component is not a standard HMA built from WMAs. Instead, it recreates the Hull idea using Kalman filtering as the smoothing primitive. The structure follows the same intent as HMA, reduce lag while keeping the line smooth, but does it with Kalman passes:
Apply Kalman smoothing over multiple effective lengths.
Combine them using the Hull-style weighting logic.
Run the combined output through another Kalman pass to finalize smoothing.
The result is a Kalman Hull filter that aims to track trend with less jitter than raw price, and less lag than slow averages.
Another Kalman Hull with Supertrend
Trend scoring logic
The trend score is computed by comparing the current Kalman Hull value to past Kalman Hull values over a fixed lookback range (1 to 45 bars in this script):
If current kalmanHMA > kalmanHMA , add +1
If current kalmanHMA < kalmanHMA , add -1
This produces a persistence score rather than a simple direction signal. Strong trends where the filter keeps advancing will accumulate positive comparisons. Weak trends, chop, or reversals will cause the score to flatten, decay, or flip negative.
Interpreting the score
Read the score as trend conviction and persistence:
High positive values: bullish persistence, the filtered trend is progressing consistently.
Low positive values: trend exists but is fragile, progress is slowing.
Near zero: indecision, range behavior, frequent challenges to structure.
Negative values: bearish persistence or sustained deterioration in the filtered trend.
The rate of change matters:
Score expansion suggests trend is gaining traction.
Score compression often signals consolidation or exhaustion.
Fast flips usually accompany regime transitions.
Signal thresholds and regime transitions
User-defined thresholds convert the score into regimes:
Long threshold: score must exceed this level to confirm bullish persistence.
Short threshold: a crossunder of the score triggers bearish regime transition.
This is intentionally conservative. Long bias is maintained while the score holds above the long threshold. Short transitions are event-triggered on breakdown via crossunder, helping avoid constant flipping during minor noise.
Signals are only plotted on regime changes (first bar of the flip), keeping them clean for alerts and backtests.
Visual presentation
The indicator provides multiple layers depending on how you want to use it:
Kalman Hull Trend Score oscillator, color-coded by active regime.
Optional Kalman Hull filter plotted on the price chart for structure context.
Optional threshold reference lines for quick regime mapping.
Optional candle coloring and background shading for instant readability.
You can run it as a pure score panel or as a combined panel + on-chart trend overlay.
How to use in practice
Trend filtering
Favor long setups when the score remains above the long threshold.
Reduce directional aggression when score compresses toward zero.
Treat a short-threshold breakdown as a regime risk event, not just a signal.
Trend quality assessment
Rising score supports continuation trades and adds confidence to breakouts.
Flat or falling score warns that trend persistence is fading.
If price trends but score fails to expand, trend may be weak or liquidity-driven.
Trade management
Use the Kalman Hull line as dynamic structure reference on chart.
Use score deterioration to scale out before a full regime flip.
Use regime flips as confirmation for bias shifts rather than prediction.
Tuning guidelines
Measurement Noise
Higher: smoother filter, fewer false shifts, slower to adapt.
Lower: more responsive, more sensitive to microstructure noise.
Process Noise
Higher: adapts quicker to sudden changes, but can become twitchy.
Lower: steadier state estimate, but slower during sharp regime transitions.
A practical approach is to first tune measurement noise until the Kalman Hull line matches the “clean trend structure” you want, then adjust process noise to control how quickly it reacts when the regime genuinely changes.
Summary
Kalman Hull Trend Score transforms a Kalman-based Hull-style trend filter into a quantified persistence oscillator. By combining adaptive Kalman smoothing with low-lag Hull logic and a rolling comparison score, it provides a cleaner read on trend quality than basic moving averages or single-condition trend tools. It is best used as a regime filter, trend strength gauge, and structure-aware trade management layer.
P/E, EPS, Price & Price-to-Sales DisplayThis indicator displays key fundamental valuation metrics for the selected stock.
It shows:
Earnings Per Share (EPS)
Price-to-Earnings (P/E) ratio
Calculated theoretical price based on P/E × EPS
Price-to-Sales (P/S) ratio
These values help traders quickly assess valuation without switching to separate financial panels.
🛠 Instructions for Use
Add the indicator to your chart.
Click on the three dots (⋯) next to the indicator name.
Select Move to → New pane above.
Minimize the indicator pane to display only the numerical values.
Hide the plotted lines if you want a clean, numbers-only view.
This setup allows you to monitor fundamental metrics efficiently without cluttering the price chart.
SA Trump Volatility Pattern Wick + Volume Shock ReversalDisclaimer (read first)
Educational use only — not financial advice. This script does not provide entries/exits, targets, position sizing, or profit guarantees. Trading (especially options/futures) involves substantial risk and can result in loss of principal (and more for leveraged products). Use at your own discretion.
Best use cases on the 2-Hour timeframe
On 2H, this script becomes a high-signal-quality “shock reversal” detector instead of a noisy candle toy. You’re essentially filtering for:
Large wick rejection
Small real body
Statistically unusual volume (Z-score > threshold)
Context alignment (trend filter + prior bar direction + optional RSI)
What 2H is best for
1) Detecting “event shock” reversals
2H bars often capture:
Macro headlines
Fed commentary
earnings reactions (for equities)
sudden volatility expansions
When the script fires on 2H, it often means:
“Aggressive push happened, liquidity got rejected, and participation was unusually high.”
That’s a structural clue, not a trade instruction.
2) Filtering false breakouts / breakdowns
The wick requirement is basically “failed continuation.”
On 2H, this is powerful around:
prior day highs/lows
weekly pivots
obvious consolidation edges
key moving averages (fast SMA / slow SMA gate)
Bull pattern = flush + reclaim behavior.
Bear pattern = pop + rejection behavior.
3) Options traders: timing “premium exposure windows”
On 2H, this is great for options traders who want to avoid buying premium into a fake move.
BullTrump on 2H can be used as a “don’t chase puts / be cautious short” context shift.
BearTrump on 2H can be used as a “don’t chase calls / be cautious long” context shift.
It’s a “regime hint” for the next few sessions, not a one-bar command.
4) Futures traders: rotation vs continuation framework
A 2H “Trump Candle” often marks:
the end of a liquidation leg
a stop-run / squeeze peak
a pivot moment where the market shifts from impulse to balance
Use it to decide whether you’re in:
continuation mode (trend carries)
or rotation mode (mean-reversion / two-way)
How to use it (2H workflow)
Step A — Keep it strict at first
Recommended defaults for 2H:
wickFracThreshold: 0.40–0.55
bodyMaxFrac: 0.35–0.45
volZThresh: 1.0–1.5
useRSIFilter: ON
RSI bull min / bear max: 45 / 55 (good baseline)
Step B — Treat triggers as “context events”
When it prints, ask 3 questions:
Where did it happen? (key level or random spot)
Was it aligned with trend gate? (SMA fast/slow)
Did volume Z-score spike? (true shock vs normal wick)
Higher quality triggers happen when:
the wick pierces a known level (prior swing / range edge)
and the close re-enters the range
and volume Z-score is meaningfully positive
Step C — Confirm with the next 1–2 candles (optional)
On 2H, it’s reasonable to wait for:
a follow-through close
or a hold above/below fast SMA
or a second “acceptance” candle
You can do this manually without changing code.
Other recommended timeframes (best to worst)
✅ 4H (even cleaner, fewer signals)
Use for:
swing context
multi-day pivots
big reversal points
✅ 1H (more signals, still structured)
Use for:
intraday + overnight context
day-trade bias shifts
✅ 30m (for active traders)
Use for:
tighter responsiveness
more setups
But requires more discretion; noise increases.
⚠️ 15m and below (only if you increase strictness)
If you want to run it on 5m/15m:
raise volZThresh (ex: 1.5–2.0)
raise wickFracThreshold (ex: 0.50–0.65)
lower bodyMaxFrac (ex: 0.25–0.35)
Otherwise it will trigger too often.
Best markets for this script
Works best on:
Index futures: /NQ, /ES (big volume makes Z-score meaningful)
Liquid ETFs: SPY, QQQ
High-volume large caps (AAPL, MSFT, NVDA etc.)
Less reliable on:
thin small caps (volume Z-score gets weird)
low-volume premarket candles
illiquid options underlyings
Signal Inside the Script ✅ SA ZoneEngine Bias Filtered is a market-structure bias and confirmation tool designed for futures To request access: 👉 Purchase here: trianchor.gumroad.com
Best GBT for this indicator
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chatgpt.com
chatgpt.com
Volatility Trend Score [BackQuant]Volatility Trend Score
Overview
Volatility Trend Score is a trend-strength and regime-evaluation indicator built to measure directional persistence, not just direction. Most trend tools answer “up or down” using slope, crossovers, or a single condition. This indicator answers a more useful question for real trading: “How consistently is trend structure holding up once volatility is accounted for?”
It does this by building a volatility-scaled trailing structure (ATR-based) and then scoring how that structure evolves over a configurable lookback range. The output is a continuous score that rises when trend is persistent and decays when price action becomes noisy, mean-reverting, or unstable.
What it is measuring (the real goal)
This indicator is not trying to predict reversals. It is trying to quantify whether the market is behaving like a trend market or a chop market. It focuses on:
Persistence: does structure keep pushing in one direction bar after bar?
Stability: are pullbacks being absorbed without breaking the trailing structure?
Regime: is the market trending strongly enough to justify directional bias?
If you already have entries from other systems, this becomes a high-quality trend filter and trade management layer.
Core idea
At its foundation, the indicator combines two parts:
A volatility-adjusted trailing level derived from ATR and a user-defined factor.
A rolling persistence score that compares the current trail to prior trail values over a configurable loop window.
The trailing structure adapts to volatility and enforces one-sided movement, while the scoring logic converts that behavior into a numeric measure of trend quality.
Inputs and what they actually control
Average True Range Period (calc_p)
Defines the ATR window used to estimate volatility. A higher value smooths the volatility estimate and makes the trailing structure less reactive.
Factor (atr_factor)
Scales the ATR band size. Higher values widen the trailing band, filtering more noise, reducing flip frequency, and generally producing slower but more stable regimes.
For Loop Start/End (start/end)
Defines the comparison window used to build the score. It effectively sets how many historical trail values the current trail is compared against.
Shorter ranges produce a faster, more responsive score.
Longer ranges produce a slower, more “confidence-based” score that only climbs when trend persistence is sustained.
Long/Short Thresholds (thresL/thresS)
Convert a continuous score into regime thresholds.
Long threshold is a “trend quality requirement” for bullish bias.
Short threshold is used as a deterioration / breakdown trigger via crossunder logic.
Volatility-adjusted trailing structure
The trailing line is built from ATR bands around price:
up = close + ATR * factor
dn = close - ATR * factor
Then a trailing value is maintained with one-sided ratcheting behavior:
If dn rises above the previous trail, the trail steps up (ratchets upward).
If up drops below the previous trail, the trail steps down (ratchets downward).
This “ratchet” behavior is important. It prevents the trail from oscillating with small countertrend moves, forcing the trail to represent meaningful structure rather than micro-noise. On-chart, this trail often behaves like dynamic support/resistance in trends.
Why the trail is a better base than raw price
Price itself is noisy, and volatility changes the meaning of “big move” vs “small move.” By anchoring structure to ATR:
A move is interpreted relative to current volatility, not in absolute points.
High-volatility chop is less likely to be misread as a trend.
Trend structure is normalized across assets and timeframes more reliably.
This is why the score remains usable even when switching from low-vol assets to high-vol crypto pairs.
Trend scoring logic
The score is built by repeatedly comparing the current trailing value to trailing values from prior bars across a loop window:
If current trail > trail , add +1
If current trail < trail , add -1
This is a persistence test, not a momentum calculation. In a strong trend, the trail should generally keep stepping in the trend direction, so current values will be greater than many past values (bullish) or lower than many past values (bearish). In chop, the trail fails to progress meaningfully, so the score compresses, oscillates, or bleeds out.
How to interpret the score
Think of the score as a “trend conviction meter”:
High positive values: bullish persistence, structure is advancing consistently.
Low positive values: bullish bias may exist, but trend quality is weak or unstable.
Near zero: indecision, range behavior, or frequent structure challenges.
Negative values: bearish dominance or sustained deterioration in structure.
The speed of score change matters too:
Fast expansion suggests a fresh regime gaining traction.
Slow grind suggests mature trend continuation.
Rapid compression often signals consolidation, exhaustion, or a transition phase.
Signals and regime transitions
This script uses two different styles of conditions (important detail):
Long condition: score > long threshold (state-based, persistent while true).
Short condition: crossunder(score, short threshold) (event-based trigger).
That means:
Long bias can remain active as long as score stays above the long threshold.
Short regime flips are triggered at the moment the score breaks down through the short threshold.
On the chart, long/short shapes are only plotted when the regime flips (first bar of the change), not on every bar, using:
Long shape when signal becomes 1 and previous signal was -1
Short shape when signal becomes -1 and previous signal was 1
This keeps signals clean and avoids spam, making it usable for alerts and regime tagging.
Visual presentation
The indicator is designed to work both as a panel oscillator and as an on-chart overlay:
Score plot (oscillator): color reflects active regime state.
Optional trail on price: volatility-scaled structure line on chart.
Optional threshold reference lines: clear regime boundaries.
Optional candle coloring: makes regime obvious without reading the panel.
Optional background shading: useful for quick scanning and backtesting visually.
You can use only the score, only the trail, or both together depending on your workflow.
Practical use cases
1) Trend filter for systems
Use the score as a regime gate:
Allow long entries only when score is above the long threshold.
Avoid longs when score compresses toward zero or loses the threshold.
Treat the short threshold break as “trend is no longer healthy.”
This often improves system expectancy by reducing exposure during low-conviction conditions.
2) Trend quality grading
Instead of treating all uptrends as equal:
Higher score = higher persistence, better continuation odds.
Score plateau = trend losing pressure, continuation becomes less reliable.
Score decay while price rises = trend is getting weaker under the hood.
This is useful for position sizing or deciding whether to add to winners.
3) Trade management and exits
Two complementary tools exist here:
Trail line can act as a dynamic stop reference or structure invalidation level.
Score behavior can be used to scale out when persistence fades (before a full flip).
Many traders use the trail for “hard structure” and the score for “soft deterioration.”
4) Breakout confirmation vs fakeouts
A breakout that immediately fails to build score is often low quality.
Healthy breakouts usually come with score expansion as structure advances.
Fakeouts often revert quickly, score fails to climb, and regime stays unstable.
Tuning guidelines
These are general behaviors you can expect when adjusting settings:
Higher ATR period and factor: slower regimes, fewer flips, cleaner structure.
Lower ATR period and factor: faster reaction, more sensitivity, more noise risk.
Longer loop range: score becomes more “confidence-based,” slower to change.
Shorter loop range: score becomes more “tactical,” faster but more jittery.
A good way to tune is to pick the trail behavior first (ATR period and factor), then tune the score window (loop) to match how quickly you want “trend conviction” to build.
Market behavior focus
Volatility Trend Score is most valuable in markets where volatility shifts frequently and fake trends are common, especially crypto. It is designed to:
Stay out of low-quality chop where most indicators whipsaw.
Quantify when volatility is being expressed directionally (constructive trend).
Provide a clean regime framework for filtering, alignment, and management.
Summary
Volatility Trend Score converts volatility-adjusted structure into a quantified measure of trend persistence. By combining an ATR-based trailing mechanism with a rolling comparison score, it provides a more reliable read on trend quality than single-condition indicators. It is best used as a regime filter, a trend strength gauge, and a trade management layer, helping you stay aligned with strong directional phases while avoiding low-conviction envir
Auction Context Engine ( Value Area, VWAP & Regime)📌 Indicator Name
Auction Context Engine (Value Area, VWAP & Regime)
Short name: ACE Context
🧠 Description
Auction Context Engine (ACE) is a professional market context and structure indicator based on Auction Market Theory.It is designed to help traders understand where the market is positioned, not to generate trade signals.
ACE focuses on:
• Developing Value Area (VAH / VAL)
• Developing Point of Control (POC)
• Session VWAP positioning
• Volatility regime expansion
• Opening Range context
• Failed auction / trap detection
• Market bias and environment quality
This indicator provides context only and is intended to be used alongside a separate execution strategy or system.
🎯 What This Indicator Is
✔ A context engine
✔ A market structure filter
✔ A bias alignment tool
✔ A regime and environment classifier
❌ What This Indicator Is NOT
✘ Not a signal generator
✘ Not a buy/sell system
✘ Not a strategy
✘ Not a profitability promise
📊 How To Use
Use ACE to answer:
• Is price accepting or rejecting value?
• Is the market in balance or expansion?
• Is VWAP supporting or opposing price?
• Is this a breakout environment or a trap?
• Is volatility expanding?
• Is the market trending or ranging?
You may then use your own execution strategy aligned with this context.
🟢 Core Components
Developing Value Area
• VAH / VAL dynamically update through the session
• POC tracks highest traded volume area
VWAP Position
• Above VWAP = bullish bias
• Below VWAP = bearish bias
Opening Range Context
• Detects breakouts or balance after session open
Volatility Regime
• Identifies expansion vs normal conditions
Failed Auction Detection
• Highlights trap conditions near value extremes
Market Quality
• Strong / Mixed / Weak environment classification
Context Table
• Clean 1-column vertical dashboard with color-coded bias
🔵 Visual Elements
• Developing VAH, VAL, POC lines
• Session VWAP
• Small context dots when environment turns READY
• Compact professional context table
⚙️ Settings
• Value Area bin size
• Value area percentage
• Opening range duration
• Regime expansion factor
• Line colors and thickness
• Context table ON/OFF
• Context dots ON/OFF
🧩 Best Use Case
This indicator is ideal for:
• Intraday trading
• Index futures and equities
• Options context filtering
• Trend / range regime identification
• Professional discretionary traders
⚠️ Disclaimer
This script is provided for educational and informational purposes only.It does not constitute financial or investment advice.Trading involves risk. Always use proper risk management.
Adjustable Price Line Size with Countdown Timer (Larger)Adjustable Size and Color for the Price Line and Timer so I Can See it Better From Across the Room...
Adjustments include: Price Line Width Size and Color (Small, Normal, Large, Huge)
Adjustment for: Solid Line, Dashed or Dotted Line
Countdown Timer: ON/OFF
I Can Now See The Price and Price Line From Across the Room!!
WYCKOFF_SHARED_LIBLibrary "WYCKOFF_SHARED_LIB"
EPS()
nz0(x)
Parameters:
x (float)
safe_div(num, den)
Parameters:
num (float)
den (float)
safe_div_eps(num, den)
Parameters:
num (float)
den (float)
safe_ratio(a, b)
Parameters:
a (float)
b (float)
clamp(x, lo, hi)
Parameters:
x (float)
lo (float)
hi (float)
wave_dir(startPx, endPx)
Parameters:
startPx (float)
endPx (float)
wave_amp(startPx, endPx)
Parameters:
startPx (float)
endPx (float)
wave_amp_atr(amp, atr)
Parameters:
amp (float)
atr (float)
wave_speed(ampATR, lenBars)
Parameters:
ampATR (float)
lenBars (int)
wave_eff(amp, path)
Parameters:
amp (float)
path (float)
build_wave_metrics(dir, lenBars, startPx, endPx, ampATR, speed, eff, volRel, epr)
Parameters:
dir (int)
lenBars (int)
startPx (float)
endPx (float)
ampATR (float)
speed (float)
eff (float)
volRel (float)
epr (float)
compare_waves(w0, w1)
Parameters:
w0 (WaveMetrics)
w1 (WaveMetrics)
strengthening_same_dir(c)
Parameters:
c (WaveCompare)
weakening_same_dir(c)
Parameters:
c (WaveCompare)
evr_by_waves(volSum0, ampATR0, volSum1, ampATR1)
Parameters:
volSum0 (float)
ampATR0 (float)
volSum1 (float)
ampATR1 (float)
WaveMetrics
Fields:
dir (series int)
lenBars (series int)
startPx (series float)
endPx (series float)
amp (series float)
ampATR (series float)
speed (series float)
eff (series float)
volRel (series float)
effortPerResult (series float)
WaveCompare
Fields:
amp_ratio (series float)
speed_ratio (series float)
eff_ratio (series float)
volRel_ratio (series float)
epr_ratio (series float)
EVR
Fields:
state (series int)
ICT CISD+FVG+OBThis script is a high-performance ICT suite designed for traders who want a professional, "noise-free" chart. It identifies core institutional patterns—Order Blocks, Fair Value Gaps, and Changes in State of Delivery (CISD)—across multiple timeframes.
The script features a proprietary Proximity Cleanup Engine that automatically deletes old or broken levels, keeping your workspace focused only on price action that is currently tradeable. It strictly follows directional delivery rules for CISD and includes a 50-candle "freshness" limit to ensure you never have to manually clear old data from your past bars.
Core Features
Intelligent CISD: Only triggers Bullish CISD on green candles and Bearish CISD on red candles.
Proximity Filter: Automatically wipes away any levels that are "miles away" from the current price.
Clean Workspace: Removes broken session highs/lows and mitigated zones instantly.
Full Customization: Toggle visibility and colors for every component via the settings menu.
Broadening Formation Structure Review ToolThis script provides an educational, checklist-based framework for studying Broadening Formations together with basic Strat-style reversal behavior and higher-timeframe direction. It is designed to show multiple structural conditions in one place so users can observe how they interact. It does not execute trades, generate signals, or provide financial advice.
What makes this script original is the integration of four components into a single logical framework:
• dynamic tracking of Broadening Formation high/low levels
• proximity evaluation relative to those levels
• classification of simple bar reversal behavior
• higher-timeframe open–close continuity checks
Instead of using these concepts as separate tools, the script combines them into a single checklist so users can see when multiple conditions occur at the same time.
Broadening Formation levels may be user-defined or automatically derived using:
• unlimited dynamic expansion
• range-limited dynamic expansion
• swing-pivot detection
• manual input mode
Users may also optionally lock levels once a structure is identified.
Proximity to BF levels can be measured in several ways, including percentage, ticks, points, dollars, ATR multiples, or expected-move multiples. The script can also detect when price takes out BF highs or lows.
The script classifies basic Strat-style price behavior, including:
• two-up / two-down moves
• outside bars
• failed 2U/2D reversals
• 2D→2U and 2U→2D reversals
A selectable higher timeframe (such as 60, 240, D, W, or M) is used to evaluate direction by comparing the higher-timeframe open and close.
The on-chart table summarizes:
• current BF High and BF Low levels
• proximity status relative to those levels
• whether BF highs or lows have been taken out
• reversal classification results
• higher-timeframe direction
• theoretical risk distance and 2R/3R projections
Optional alerts can notify when three-condition or four-condition checklist alignment occurs, based only on the logical rules visible in the script. Optional chart lines for BF levels may also be displayed.
Transparency and behavior notes
• swing pivots repaint until confirmed
• higher-timeframe direction is only final at bar close
• dynamically derived BF levels may update as price forms new extremes
This script is intended purely for market-structure study and education. It does not guarantee performance, predict outcomes, or recommend trades.
First Opening Price of the YearOverview
This indicator identifies and plots the opening price of the first trading session of the calendar year. The "Yearly Open" is a significant psychological level for traders and institutions, often serving as a major pivot point for the entire year's trend.
How it Works
The script utilizes Pine Script v5's persistent variables to track the year change.
Detection: It compares the current bar's year (year) with the previous bar's year (year ).
Storage: When a discrepancy is found (indicating a new year has started), the script captures the open price of that specific bar.
Persistence: Using the var keyword, this price is stored in memory and carried forward for every subsequent bar of the year without being recalculated.
Visualization: The price is plotted as a series of blue crosses (style_cross) to clearly mark the level on the chart.
Chart Analysis & Examples
The following examples demonstrate how this simple level dictates market structure across different assets:
Historical Pivot Points (S&P 500):
This chart demonstrates how the Yearly Open acts as a critical pivot. Notice in 2022 how price struggled around the open before dropping, while in 2023 and 2024, the yearly open provided a solid base for the subsequent rallies.
Trend Confirmation (Bitcoin):
In strong trending markets, the Yearly Open serves as a trailing support. As seen in this Bitcoin example, price maintaining its position above the blue line confirms a sustained bullish bias for the year, acting as a "floor" for the trend.
Market Structure & Bias (Gold):
This example highlights the "Line in the Sand" concept. The indicator clearly marks the starting point of the year, allowing traders to instantly gauge if the asset is net positive or negative year-to-date. It filters out the noise and focuses on the macro direction.
How to Use
Traders can use this indicator to determine the higher-timeframe bias:
Bullish Bias: When the current price is trading above the blue crosses, the market is considered to be positive relative to the start of the year.
Bearish Bias: When the current price is trading below the blue crosses, the market is negative relative to the start of the year.
Settings
This script is "plug and play" and requires no manual input adjustments. It automatically detects the timeframe and year changes based on the chart data provided.
Disclaimer
This tool is for informational purposes only and DOES NOT constitute financial advice. Always manage your risk appropriately.
Adaptive Trend Envelope [BackQuant]Adaptive Trend Envelope
Overview
Adaptive Trend Envelope is a volatility-aware trend-following overlay designed to stay responsive in fast markets while remaining stable during slower conditions. It builds a dynamic trend spine from two exponential moving averages and surrounds it with an adaptive envelope whose width expands and contracts based on realized return volatility. The result is a clean, self-adjusting trend structure that reacts to market conditions instead of relying on fixed parameters.
This indicator is built to answer three core questions directly on the chart:
Is the market trending or neutral?
If trending, in which direction is the dominant pressure?
Where is the dynamic trend boundary that price should respect?
Core trend spine
At the heart of the indicator is a blended trend spine:
A fast EMA captures short-term responsiveness.
A slow EMA captures structural direction.
A volatility-based blend weight dynamically shifts influence between the two.
When short-term volatility is low relative to long-term volatility, the fast EMA has more influence, keeping the trend responsive. When volatility rises, the blend shifts toward the slow EMA, reducing noise and preventing overreaction. This blended output is then smoothed again to form the final trend spine, which acts as the structural backbone of the system.
Volatility-adaptive envelope
The envelope surrounding the trend spine is not based on ATR or fixed percentages. Instead, it is derived from:
Log returns of price.
An exponentially weighted variance estimate.
A configurable multiplier that scales envelope width.
This creates bands that automatically widen during volatile expansions and tighten during compression. The envelope therefore reflects the true statistical behavior of price rather than an arbitrary distance.
Inner hysteresis band
Inside the main envelope, an inner band is constructed using a hysteresis fraction. This inner zone is used to stabilize regime transitions:
It prevents rapid flipping between bullish and bearish states.
It allows trends to persist unless price meaningfully invalidates them.
It reduces whipsaws in sideways conditions.
Trend regime logic
The indicator operates with three regime states:
Bullish
Bearish
Neutral
Regime changes are confirmed using a configurable number of bars outside the adaptive envelope:
A bullish regime is confirmed when price closes above the upper envelope for the required number of bars.
A bearish regime is confirmed when price closes below the lower envelope for the required number of bars.
A trend exits back to neutral when price reverts through the trend spine.
This structure ensures that trends are confirmed by sustained pressure rather than single-bar spikes.
Active trend line
Once a regime is active, the indicator plots a single dominant trend line:
In a bullish regime, the lower envelope becomes the active trend support.
In a bearish regime, the upper envelope becomes the active trend resistance.
In neutral conditions, price itself is used as a placeholder.
This creates a simple, actionable visual reference for trend-following decisions.
Directional energy visualization
The indicator uses layered fills to visualize directional pressure:
Bullish energy fills appear when price holds above the active trend line.
Bearish energy fills appear when price holds below the active trend line.
Opacity gradients communicate strength and persistence rather than binary states.
A subtle “rim” effect is added using ATR-based offsets to give depth and reinforce the active side of the trend without cluttering the chart.
Signals and trend starts
Discrete signals are generated only when a new trend regime begins:
Buy signals appear at the first confirmed transition into a bullish regime.
Sell signals appear at the first confirmed transition into a bearish regime.
Signals are intentionally sparse. They are designed to mark regime shifts, not every pullback or continuation, making them suitable for higher-quality trend entries rather than frequent trading.
Candle coloring
Optional candle coloring reinforces regime context:
Bullish regimes tint candles toward the bullish color.
Bearish regimes tint candles toward the bearish color.
Neutral states remain visually muted.
This allows the chart to communicate trend state even when the envelope itself is partially hidden or de-emphasized.
Alerts
Built-in alerts are provided for key trend events:
Bull trend start.
Bear trend start.
Transition from trend to neutral.
Price crossing the trend spine.
These alerts support hands-off trend monitoring across multiple instruments and timeframes.
How to use it for trend following
Trend identification
Only trade in the direction of the active regime.
Ignore counter-trend signals during confirmed trends.
Entry alignment
Use the first regime signal as a structural entry.
Use pullbacks toward the active trend line as continuation opportunities.
Trend management
As long as price respects the active envelope boundary, the trend remains valid.
A move back through the spine signals loss of trend structure.
Market filtering
Periods where the indicator remains neutral highlight non-trending environments.
This helps avoid forcing trades during chop or compression.
Adaptive Trend Envelope is designed to behave like a living trend structure. Instead of forcing price into static rules, it adapts to volatility, confirms direction through sustained pressure, and presents trend information in a clean, readable form that supports disciplined trend-following workflows.
Adaptive Strength Overlay (MTF) [BackQuant]Adaptive Strength Overlay (MTF)
A multi-timeframe RSI strength visualizer that projects oscillator “pressure” directly onto price using adaptive gradient fills between percent bands. Built to make strength, exhaustion, and regime context readable at a glance, without needing to stare at a separate oscillator panel.
Mean-Reversion mode example
What this indicator does
This indicator converts RSI strength into a chart overlay that reacts to momentum and extremes, then visualizes it as colored “pressure zones” around price.
Instead of plotting RSI in a sub-window, it:
Builds 1 to 3 symmetric percent bands above and below price.
Computes RSI strength on up to 3 different timeframes (MTF).
Smooths RSI with your selected moving average type.
Maps RSI values into discrete transparency “buckets”.
Fills between the bands with a gradient whose opacity reflects strength or exhaustion.
Displays a compact RSI table for all enabled timeframes.
Provides alert conditions for extremes and midline shifts on each timeframe.
The result is an overlay that looks like a dynamic envelope. When strength rises, the envelope “lights up” in the direction of the move. When strength becomes stretched, the outer zones become visually prominent.
Core idea: “Strength as an overlay”
RSI is normally interpreted in a separate oscillator panel. That makes context-switching slow:
You check price action.
You look down at RSI.
You mentally translate RSI into risk or trend bias.
This script removes that translation step by projecting strength directly onto the price area, using band fills as a visual language:
More visible fill = stronger strength or more extreme condition (depending on mode).
Less visible fill = weak strength or neutral state.
Two operating modes
1) Trend mode
Trend mode emphasizes strength aligned with direction:
When RSI is strong on the upside, upper bands become more visible.
When RSI is strong on the downside, lower bands become more visible.
Neutral RSI fades, so the chart de-clutters during chop.
Use Trend mode when:
You want a clean trend-following overlay.
You want to quickly see which timeframe(s) are powering the move.
You want to filter entries to moments when strength confirms direction.
2) Mean-Reversion mode
Mean-Reversion mode flips the emphasis to highlight exhaustion against the move :
Upper extremes become a “potential exhaustion” cue.
Lower extremes become a “potential exhaustion” cue.
The overlay is tuned to make stretched conditions obvious.
This is not an automatic “short overbought / long oversold” system. It is a visualization mode that makes “extended” conditions stand out faster, especially when multiple timeframes align.
How the bands work (Percent Bands)
The indicator constructs up to three symmetric envelopes around price:
Band 1: percent1 scaled by scale
Band 2: percent2 scaled by scale (optional)
Band 3: percent3 scaled by scale (optional)
The percent bands are simple deviations from the selected price source:
Upper = price * (1 + (percent * scaling)/100)
Lower = price * (1 - (percent * scaling)/100)
Why this matters:
It anchors “strength visualization” to meaningful price distance.
It makes the overlay comparable across assets because it’s percent-based.
It gives you a consistent spatial frame for reading momentum versus extension.
Multi-timeframe engine (MTF)
The script runs the same strength calculation on up to three timeframes:
Timeframe 1 uses the chart timeframe by default (empty string input).
Timeframe 2 is optional and defaults to Daily.
Timeframe 3 is optional and defaults to Weekly.
Each timeframe has:
Its own RSI period (len, len2, len3).
Its own smoothing length (slen, slen2, slen3).
The same smoothing type selection (EMA, HMA, etc).
This creates a layered view:
TF1 often reflects tactical pressure (entries/exits).
TF2 reflects structural pressure (swing context).
TF3 reflects macro bias (regime context).
When multiple timeframes agree, the fills stack and the overlay becomes visually louder. When they disagree, the overlay looks mixed or muted, which is exactly the point.
Smoothing options (why so many)
Raw RSI can be noisy. This script lets you smooth RSI with multiple MA types, which changes how “responsive” the overlay feels:
EMA/RMA smooth without lagging as hard as SMA.
HMA responds faster but can be twitchy.
LINREG can feel more “structural”.
ALMA and T3/TEMA provide heavier smoothing profiles with different lag characteristics.
This isn’t cosmetic. Your smoothing choice affects:
How early the overlay “lights up” in Trend mode.
How long extremes remain highlighted in Mean-Reversion mode.
How often fills flicker in chop.
Strength mapping (the transparency buckets)
Instead of mapping RSI to a continuous color scale, the script uses a discrete transparency ladder. That creates a clean, readable visual that avoids constant flickering.
The logic assigns two transparency values per timeframe:
Upper-side transparency responds to lower RSI zones (weak upside strength).
Lower-side transparency responds to higher RSI zones (strong upside strength).
Then the script uses those transparencies differently depending on mode:
Trend mode shows “strength aligned with direction”.
Mean-Reversion mode swaps the emphasis so “extremes” stand out as potential stretch.
You can think of it as:
Trend mode highlights continuation strength.
Mean-Reversion mode highlights potential exhaustion.
Fill stacking (how the overlay is built)
The overlay uses layered fills:
Fill from price to Band 1
Fill from Band 1 to Band 2 (if enabled)
Fill from Band 2 to Band 3 (if enabled)
Upper side uses the negative color (typically red) and lower side uses the positive color (typically green), because upper bands represent “above price” space and lower bands represent “below price” space. The intensity is controlled by the computed transparency per timeframe and selected mode.
Important behavior:
Disabling Band 2 or Band 3 can change how the stacked fills look, because you are removing fill segments.
If you want a clean look, run only Band 1.
If you want a “regime heat” look, run Bands 1–3 with higher scaling.
Table (MTF RSI dashboard)
A compact table prints RSI values for each configured timeframe:
Row labels show TF.
Values show the smoothed RSI output that drives the overlay.
Use it for quick confirmation:
If overlay looks strong but table RSI is neutral, your band settings might be too tight.
If TF3 RSI is extreme while TF1 is neutral, you are likely in a macro stretched regime with local consolidation.
Alerts (built-in)
Alerts are provided for each timeframe separately, covering:
Entering upper extreme (cross above 70)
Exiting upper extreme (cross below 70)
Entering lower extreme (cross below 30)
Exiting lower extreme (cross above 30)
Bullish midline cross (cross above 50)
Bearish midline cross (cross below 50)
This enables workflows like:
Notify when TF2 enters extreme, then wait for TF1 mean-reversion confirmation.
Notify when TF3 crosses midline, then only take TF1 trend setups in that direction.
How to use it (practical reads)
Trend mode reads
Strong continuation: TF1 and TF2 fills become clearly visible on the same side.
Healthy pullback: TF1 fades but TF2 stays visible, suggesting underlying structure remains strong.
Chop warning: fills alternate or remain mostly invisible, indicating neutral strength.
Mean-Reversion mode reads
Exhaustion zones: outer fills become prominent near the extremes, signaling stretched conditions.
Compression after extreme: fill fades while price stabilizes, suggesting “cooling off” rather than immediate reversal.
Multi-TF stretch: TF2 and TF3 extremes together often mark higher significance zones.
Recommended setup presets
Preset A: Clean trend overlay
Mode: Trend
Bands: only Band 1
Scale: 1–2
Smoothing: EMA, moderate slen (6–10)
TF2: Daily on intraday charts
Preset B: Regime and exhaustion mapper
Mode: Mean-Reversion
Bands: Bands 1–3
Scale: 2–4
Smoothing: T3 or RMA, slightly higher slen
TF2: Daily, TF3: Weekly
Limitations
This is a strength visualization tool, not a full entry/exit system.
Percent bands are not volatility-adjusted, they are distance frames. In very high vol conditions, you may need higher band percentages or higher scaling.
MTF values update on their own timeframe closes, so higher timeframes will step rather than update every bar.
Contract Size OverviewNever second-guess your position size again. This indicator displays your pre-configured contract or lot sizes for all your frequently traded instruments, so you always know exactly how much to trade the moment you open a chart.
🎯 Why Use This?
Switching between ES futures, crypto pairs, and forex? Each instrument likely has a different position size based on your risk management. Instead of calculating or remembering sizes every time, configure them once and let the indicator do the work.
✨ Key Features
Configure up to 10 symbols with custom position sizes
Full support for fractional sizes (0.1 BTC, 0.25 ETH, etc.)
Automatic symbol detection — works with continuous contracts (ES1!, NQH2025, etc.)
Two display modes: current symbol only or full watchlist
Optional large on-chart label for instant visibility
Fully customizable colors and positioning
📖 How To Use
Add the indicator to your chart
Open settings and enter your traded symbols (ES, NQ, BTCUSDT, etc.)
Set your default position size for each
Switch between charts — your size appears automatically
⚙️ Display Options
Single Mode : Shows only the current chart's position size — clean and minimal
List Mode : Displays all configured symbols with the current one highlighted
Large Label : Optional prominent display directly on the price chart
💡 Perfect For
Futures traders managing multiple contracts (ES, NQ, CL, GC)
Crypto traders with fractional position sizes
Anyone who trades multiple instruments with different risk allocations
Traders who want to eliminate sizing mistakes when switching markets
⚠️ Note
This is an informational overlay only. It does not execute trades or connect to any broker.
Opening Path Selector (EMA200 Context Tool)📝 Description
Opening Path Selector is a context-based indicator designed to help traders quickly identify which asset may offer the cleanest directional path at the market open.
This tool does not generate entry or exit signals.
Its purpose is to reduce decision fatigue during the first minutes of the session by ranking a small set of high-liquidity assets based on higher-timeframe EMA200 structure.
🔍 What this indicator evaluates
The dashboard compares a predefined group of major symbols and ranks them according to:
• Proximity to the nearest EMA200
• Relative position versus higher-timeframe EMA200 levels
• Directional context inferred from EMA structure
The result is a priority-based list that highlights which asset may present:
• Less immediate EMA resistance
• Clearer directional context
• Lower probability of early-session chop
📊 How to read the dashboard
• Priority – Ranking based on opening context
• Symbol – Evaluated instrument
• Nearest EMA200 – Distance and side relative to price
• Possible Path – Direction with less immediate EMA resistance
• Bias – Strength of the higher-timeframe context
Colored markers are used to provide fast visual identification of the highest-priority assets.
⚠️ Important notes
• This is a context and selection tool, NOT a trading system
• No buy/sell signals, alerts, TP, or SL logic are included
• Designed to be used alongside your own execution methodology
🔧 Compatibility
Due to Pine Script multi-symbol and multi-timeframe constraints, this public version is intentionally limited to a small set of symbols.
TradingView Pro / Premium or higher is recommended for consistent performance.
🔗 Complementary tools
This indicator can be complemented with Multi-Tool VWAP + EMAs (Multi-Timeframe) + Key Levels , which provides detailed visibility of multiple EMA levels, VWAP structure, and higher-timeframe reference zones directly on the chart.
While Opening Path Selector helps decide which asset to focus on at the open, the complementary tool can assist with in-chart context and confirmation once an asset has been selected.
Both tools are designed to serve different stages of the decision process and can be used independently.
