Key Price Levels + Zones"Support and resistance are rarely exact lines; hey are zones where price reacts."
This indicator upgrades standard horizontal levels by visualizing Liquidity Zones around the most critical intraday reference points: Pre-Market, Previous Day, and Previous Week Highs/Lows.
Unlike basic scripts that just draw thin lines, this tool combines the precision of exact price levels with the reality of market volatility. It offers deep customization, allowing you to separate line colors from zone colors, perfect for keeping your charts clean and professional.
Key Features
1. Dual Zone Logic (Dynamic Sizing)
• Price Tier Mode (Default): Zones are sized based on the asset price (e.g., higher-priced stocks get wider zones automatically). This mimics "psychological" levels.
• ATR Volatility Mode: Switches calculation to use the Average True Range (ATR). Zones expand during high volatility and contract during chop, adapting to the market conditions in real-time.
2. Ultimate Customization
• Separate Colors: You can finally set your Line Color (e.g., Bright Green) independently from your Zone Fill (e.g., Faint Grey).
• Individual Toggles: Turn the Line, Zone, or Label on/off individually for every single level.
• Line Styles: Differentiate daily levels (Solid) from weekly levels (Dashed) instantly.
3. The "Smart" Levels
• PM High/Low: Real-time Pre-Market tracking that freezes at the open.
• PD High/Low: Previous Day’s range.
• PW High/Low: Previous Week’s range (Critical for swing points).
---
Settings Guide
• Extension Style:
- Individual: Keeps history of levels for backtesting.
- Most Recent: Keeps the chart minimal by extending only today's levels.
• Zone Thickness Mode: Switch between "Price Tier" and "ATR Volatility".
• ATR Settings: Fully adjustable Length and Multiplier (when in ATR mode).
• Transparency: Global slider to control how subtle or bold the zones appear.
How to Trade This
• The "Trap": If price breaks a Line but fails to close outside the Zone, it is often a liquidity grab (fakeout).
• The Retest: Watch for price to break a level and use the Zone as a cushion for a bounce/retest entry.
Bantlar ve Kanallar
MAs + Bollinger Bands by @ETERNYWORLDMAs + Bollinger Bands by @ETERNYWORLD is the core trend and volatility layer inside the Trend Mastery Pro ecosystem, engineered by EternityWorld to deliver a clean, structured, and highly customizable market bias reading directly on the chart.
What’s Inside the Indicator
5 independent Moving Averages (EMA or SMA) with individual enable/disable toggles, lengths, colors, and widths.
Bollinger Bands with professional basis options: SMA, EMA, RMA/SMMA, WMA, VWMA, plus adjustable deviation multiplier and visual band fill.
Chart overlay compatibility, making trend and volatility easy to interpret for fast decisions.
Fully configurable alerts, enabling traders to stay proactive without missing high-probability expansion triggers.
Enhanced by Trend Mastery Pro Workflow
This indicator complements the 3-step methodology of Trend Mastery Pro:
Bias → defines the dominant trend direction.
Trigger → identifies breakout or momentum expansion zones using confluence with volatility.
Management → supports consistent risk execution when combined with external strategy rules and trade plans.
Key Strengths
✔ Unified trend + volatility envelope on chart
✔ Individual component control (no clutter, no guesswork)
✔ Noise reduction in consolidation environments
✔ Adaptable to crypto, forex, indices, commodities, and equities
✔ Reliable for intraday impulse plays and structured directional setups
How to Use It
Context: Align your analysis with the broader bias before execution.
Signal: Watch for volatility expansion and trend alignment for breakout scenarios.
Execution: Apply your risk plan (position size, partials, BE/trailing) based on your trading model.
Best Practices
🛡️ Tune sensitivity according to asset volatility and timeframe horizon
🛡️ Avoid trading against dominant bias during compression phases
🛡️ Always validate through backtesting and forward testing before scaling
🛡️ Log performance and refine parameters iteratively
Who It's For
Traders who want:
A repeatable and disciplined process
A professional visual structure
Less noise, more clarity, better bias alignment
A premium indicator suite that supports real decision-making
Compatibility
Seamlessly works with any asset and timeframe on TradingView supporting chart overlay indicators. Alerts are designed to help monitoring without being glued to the screen.
Disclaimer ⚠️
This product is not financial advice and does not guarantee results. Performance varies depending on market conditions, asset behavior, user configuration, and applied risk management. Always trade responsibly and follow your own risk plan.
Gridbot Ping Pong🏓 Gridbot Ping Pong is a dynamic grid bot indicator that generates buy and sell signals as price oscillates between automatically calculated support and resistance levels. The grid adapts to trending markets through adjustable tilt and anchor parameters, which control the grid slope and shift resistance respectively. Entry signals trigger when price touches grid levels, while take profit and stop signals manage position exits. Unlike traditional grid bots that require horizontal ranges, this indicator maintains its oscillation zone as price trends by tilting and shifting the grid structure to follow momentum. The grid bot approach aims to accumulate gains through frequent touches across multiple grid levels rather than seeking large directional moves. Like a ping pong ball in motion, price oscillates between grid levels — each touch generates a signal.
⚡ THEORY & CONCEPTS ⚡
Grid trading is a systematic approach that places buy and sell orders at predetermined price intervals, creating a grid of orders above and below a set price level. In ranging markets, this method capitalizes on natural price oscillations by buying at lower grid levels and selling at higher ones. Each completed round trip between levels represents a captured opportunity, and the frequency of these oscillations determines the grid's effectiveness. Traditional grid bots excel when price remains within the defined range, methodically accumulating gains as price bounces between levels.
However, traditional grid structures face significant challenges when markets begin to trend. Fixed horizontal levels that performed well during consolidation become liabilities during directional moves. An uptrend leaves buy orders unfilled while sell orders trigger prematurely, and a downtrend creates the opposite problem. Extended trends can result in accumulated positions at increasingly unfavorable prices, with no mechanism to adapt to the new market reality. The static nature of traditional grids assumes markets will return to the mean, yet sustained breakouts regularly invalidate this assumption.
Gridbot Ping Pong addresses these limitations through dynamic grid adaptation. The tilt parameter angles the grid in the direction of the prevailing trend, aligning support and resistance levels with market momentum rather than fighting against it. The anchor parameter creates buffer zones beyond the outer grid boundaries, requiring price to demonstrate conviction before triggering a grid shift. When price breaks through these buffers, the entire grid recenters to the new price level. This combination of tilting grids and controlled shifting allows the indicator to maintain grid trading mechanics while acknowledging that markets trend.
The grid adapts through a downtrend and early reversal. Entry signals (▲▼), take profit signals (△▽), and grid shifts demonstrate the ping pong sequence as price oscillates between levels.
The grid structure consists of five levels: two potential support levels below, a center base price, and two potential resistance levels above. These levels are calculated as percentage intervals from a dynamic base price, with the spacing parameter determining the distance between each level. Trend direction is derived from consecutive grid shifts, where multiple shifts in the same direction confirm momentum. The grid restricts entries to the trend direction — buy signals in uptrends, sell signals in downtrends — while counter-trend signals convert to exits when appropriate.
Full market cycle demonstrating grid adaptation through rally, reversal, decline, and recovery. Buy signals dominate during uptrends, sell signals during downtrends, with take profits at boundaries throughout. Two stop signals mark the trend reversals.
Tilt
The tilt mechanic introduces slope to the grid structure based on trend direction and momentum. When consecutive shifts occur in the same direction, the tilt increases, creating a steeper grid that tracks with the trend. As the trend progresses, support levels rise with it — buy signals trigger on pullbacks to these rising levels rather than static levels abandoned by price. Similarly, resistance levels fall during downtrends, keeping sell signals relevant to current price action. If the trend reverses and shifts occur in the opposite direction, the tilt resets and begins building in the new direction. The tilt strength parameter controls how aggressively the grid slopes, with higher values producing steeper angles. Negative tilt values invert this relationship, angling the grid against the prevailing momentum rather than with it. This counter-trend configuration positions support levels lower during uptrends and resistance levels higher during downtrends, favoring mean reversion entries that anticipate pullbacks rather than continuation.
Negative tilt applied during an uptrend. Despite the bullish price action from late November through December, the grids slope downward, positioning buy signals at deeper support levels. Take profit signals appear at resistance as price reaches the upper grid boundaries before pulling back. The counter-trend configuration captures oscillations within the rising market rather than chasing momentum.
Anchor
The anchor mechanic provides resistance to grid shifting. Buffer zones extend beyond the outer grid boundaries, requiring price to demonstrate conviction before triggering a shift. Higher anchor values create larger buffers, requiring more significant price movement. As consecutive shifts confirm a trend, the pro-trend buffer shrinks, allowing the grid to follow momentum with increasing ease. This lets the indicator commit to established trends while resisting premature shifts during consolidations. Tilt and anchor work in complementary tension: tilt rewards momentum by angling the grid, while anchor resists excessive shifting by requiring price conviction to recenter. When price breaks through these buffers, the entire grid recenters to the new price level and play continues on a fresh table.
Steady uptrend with minimal tilt. The flat grid segments demonstrate that shifting alone keeps the grid aligned with price action. Buy signals (▲) and take profit signals (▽) alternate as price bounces between levels, accumulating gains through repetition across the entire move.
Sustained uptrend from June through September. The grid follows the trend with increasing ease as consecutive shifts reduce the pro-trend buffer. The October consolidation eventually triggers a downward shift and stop signal, but the system adapts to the renewed uptrend in November with fresh entry signals.
Signal Generation
The indicator generates three signal types. Entry signals (▲▼) trigger when price reaches a grid level in the direction of the trend, initiating a new position. Take profit signals (△▽) trigger when price reaches a grid level against the trend direction while a position is held, capturing gains as the rally continues. Stop signals (⦿) trigger when a grid shift occurs while holding a position adverse to the new shift direction. The ball goes off the table.
Trend reversal from bearish to bullish. The grid follows the downtrend through November with consecutive sell signals. A stop signal (⦿) triggers at the bottom as the grid shifts adversely against the held position. The system resets and adapts to the emerging uptrend in December, generating fresh buy signals as the new direction establishes.
Trigger Options
The signal trigger determines what price data the indicator uses to detect grid touches, balancing responsiveness against confirmation.
Auto : The default setting, using wick-based detection for pro-trend signals and close-based detection for counter-trend signals. This balances responsiveness when entering with the trend against confirmation when signaling against it.
Wick Touch : Generates signals in real-time when the high or low touches a grid level, providing the fastest response to price interaction.
Wick Reverse : Requires the wick to cross through the grid level from the previous bar, confirming the touch before signaling.
SWMA : Uses a Symmetrically Weighted Moving Average as the trigger source, generating signals only when the smoothed price crosses grid levels.
Close : Uses the bar's closing price as the trigger source, providing confirmed signals after each bar completes.
Symmetrically Weighted Moving Average (SWMA) trigger during a trend reversal. The smoothed price line filters intrabar noise, generating signals only when the SWMA crosses grid levels rather than reacting to wick touches. The grid follows the downtrend through November, resets at the bottom, and adapts to the emerging uptrend in December.
Signal Safeguards
The indicator includes built-in protections to reduce overtrading and mitigate risk, keeping the ball in play longer:
Boundary Protection : New entries are blocked at the outermost grid levels where breakout risk is highest. Exits remain permitted at these boundaries.
Signal Spacing : Signals maintain one-level separation from the most recent signal, preventing clusters of entries at similar prices.
Trend Alignment : When conflicting conditions arise, signals align with the prevailing trend direction rather than fighting momentum.
Automatic Profit Taking : Counter-trend interactions convert to take profit signals when a position is held, capturing gains rather than reversing exposure.
Adverse Shift Stops : When the grid shifts against a held position, a stop signal triggers to exit before further adverse movement.
Cautious Breakout Entries : On the first shift in a new direction, entries are restricted to favorable grid levels until the trend confirms through consecutive shifts.
Shift Resistance : Counter-trend shifts always require full buffer conviction, while pro-trend shifts become easier only after the trend is confirmed.
🛠️ CONFIGURATION & SETTINGS 🛠️
Core Parameters
SPACING (%) : Sets the percentage distance between grid levels. Higher values create wider grids with more room between signals, lower values create tighter grids with more frequent signal opportunities.
TRIGGER : Selects the price source for signal detection. See Trigger Options above.
TILT : Controls the grid slope factor in the trend direction.
ANCHOR : Controls resistance to grid shifting.
Visual Settings
GRIDS : Sets the colors for support (lower) and resistance (upper) grid levels.
FILL : Sets the gradient fill colors between the price line and outer grid boundaries.
SWMA : Sets the color of the Symmetrically Weighted Moving Average line.
🏓 PLAYING GRIDBOT PING PONG 🏓
⚪The objective is not to predict where price will go, but to be present at each level when it arrives.
⚪Each touch at a boundary counts. Gains accumulate through repetition, not single swings.
⚪The rally continues until it doesn't. When the ball goes off the table, the game resets.
⚪The grid creates boundaries where price bounces back and forth. The table is set — the ball does the work.
⚪Price oscillates between defined levels. The grid is the table. Everything else is just ping pong.
Tennis is a form of ping pong. In fact, tennis is ping pong played while standing on the table. In fact, all racquet games are nothing but derivatives of ping pong. — George Carlin
⚠️ DISCLAIMER ⚠️
The Gridbot Ping Pong indicator is a visual analysis tool designed to illustrate grid trading concepts and serve as a framework for understanding grid bot mechanics. While the indicator generates entry, exit, and stop signals, no guarantee is made regarding the profitability of these signals. Like all technical indicators, the grid levels and signals generated by this tool may appear to align with favorable trading opportunities in hindsight. However, these signals are not intended as standalone recommendations for trading decisions. This indicator is intended for educational and analytical purposes, complementing other tools and methods of market analysis.
🧠 BEYOND THE CODE 🧠
Gridbot Ping Pong is part of the Grid Bot Series, building on the concepts introduced in the Grid Bot Simulator , Grid Bot Auto , and Grid Bot Parabolic indicators. While those tools established the foundation for grid-based analysis, this indicator introduces dynamic tilt and anchor mechanics that adapt to trending market conditions.
This indicator shares the same educational philosophy as the Fibonacci Time-Price Zones and the Fibonacci Geometry Series - providing frameworks for understanding market concepts through visualization and experimentation rather than black-box signals.
The Gridbot Ping Pong indicator, like other xxattaxx indicators , is designed to encourage both education and community engagement. Feedback and insights are invaluable to refining and enhancing this tool. We look forward to the creative applications, observations, and discussions this indicator inspires within the trading community.
Velocity Divergence Radar [JOAT]
Velocity Divergence Radar - Momentum Physics Edition
Overview
Velocity Divergence Radar is an open-source oscillator indicator that applies physics concepts to market analysis. It calculates price velocity (rate of change), acceleration (rate of velocity change), and jerk (rate of acceleration change) to provide a multi-dimensional view of momentum. The indicator also includes divergence detection and force vector analysis.
What This Indicator Does
The indicator calculates and displays:
Velocity - Rate of price change over a configurable period, smoothed with EMA
Acceleration - Rate of velocity change, showing momentum shifts
Jerk (3rd Derivative) - Rate of acceleration change, indicating momentum stability
Force Vectors - Volume-weighted acceleration representing market force
Kinetic Energy - Calculated as 0.5 * mass (volume ratio) * velocity squared
Momentum Conservation - Tracks momentum relative to historical average
Divergence Detection - Identifies when price and velocity diverge at pivots
How It Works
Velocity is calculated as smoothed rate of change:
calculateVelocity(series float price, simple int period) =>
float roc = ta.roc(price, period)
float velocity = ta.ema(roc, period / 2)
velocity
Acceleration is the change in velocity:
calculateAcceleration(series float velocity, simple int period) =>
float accel = ta.change(velocity, period)
float smoothAccel = ta.ema(accel, period / 2)
smoothAccel
Jerk is the change in acceleration:
calculateJerk(series float acceleration, simple int period) =>
float jerk = ta.change(acceleration, period)
float smoothJerk = ta.ema(jerk, period / 2)
smoothJerk
Force is calculated using F = m * a (mass approximated by volume ratio):
calculateForceVector(series float mass, series float acceleration) =>
float force = mass * acceleration
float forceDirection = math.sign(force)
float forceMagnitude = math.abs(force)
Signal Generation
Signals are generated based on velocity behavior:
Bullish Divergence: Price makes lower low while velocity makes higher low
Bearish Divergence: Price makes higher high while velocity makes lower high
Velocity Cross: Velocity crosses above/below zero line
Extreme Velocity: Velocity exceeds 1.5x the upper/lower zone threshold
Jerk Extreme: Jerk exceeds 2x standard deviation
Force Extreme: Force magnitude exceeds 2x average
Dashboard Panel (Top-Right)
Velocity - Current velocity value
Acceleration - Current acceleration value
Momentum Strength - Combined velocity and acceleration strength
Radar Score - Composite score based on velocity and acceleration
Direction - STRONG UP/SLOWING UP/STRONG DOWN/SLOWING DOWN/FLAT
Jerk - Current jerk value
Force Vector - Current force magnitude
Kinetic Energy - Current kinetic energy value
Physics Score - Overall physics-based momentum score
Signal - Current actionable status
Visual Elements
Velocity Line - Main oscillator line with color based on direction
Velocity EMA - Smoothed velocity for trend reference
Acceleration Histogram - Bar chart showing acceleration direction
Jerk Area - Filled area showing jerk magnitude
Vector Magnitude - Line showing combined vector strength
Radar Scan - Oscillating pattern for visual effect
Zone Lines - Upper and lower threshold lines
Divergence Labels - BULL DIV / BEAR DIV markers
Extreme Markers - Triangles at velocity extremes
Input Parameters
Velocity Period (default: 14) - Period for velocity calculation
Acceleration Period (default: 7) - Period for acceleration calculation
Divergence Lookback (default: 10) - Bars to scan for divergence
Radar Sensitivity (default: 1.0) - Zone threshold multiplier
Jerk Analysis (default: true) - Enable 3rd derivative calculation
Force Vectors (default: true) - Enable force analysis
Kinetic Energy (default: true) - Enable energy calculation
Momentum Conservation (default: true) - Enable momentum tracking
Suggested Use Cases
Identify momentum direction using velocity sign and magnitude
Watch for divergences as potential reversal warnings
Use acceleration to detect momentum shifts before price confirms
Monitor jerk for momentum stability assessment
Combine force and kinetic energy for conviction analysis
Timeframe Recommendations
Works on all timeframes. Higher timeframes provide smoother readings; lower timeframes show more granular momentum changes.
Limitations
Physics analogies are conceptual and not literal market physics
Divergence detection uses pivot-based lookback and may lag
Force calculation uses volume ratio as mass proxy
Kinetic energy is a derived metric, not actual energy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
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chart4me candel buy 1 hour the best candel buy 1 hour the best candel buy 1 hour the best candel buy 1 hour the best candel buy 1 hour the best candel buy 1 hour the best
Mid-term RibbonWhat the indicator is meant to tell you
-Mid-term trend direction (bullish vs bearish)
-Trend transitions when the ribbon flips color
-Trend strength (wider ribbon = stronger momentum)
-Helps traders stay in trends longer and avoid chop
Typical use cases
-Trend-following entries and exits
-Filtering trades in the direction of the ribbon
-Visual confirmation for other signals
-Swing trading and position trading
Colors are customizable
Only for educational purposes, no recommendation to buy or sell
Polynomial Regression Channel [ChartPrime]⯁ OVERVIEW
The Polynomial Regression Channel fits price action using advanced polynomial regression, extending beyond simple linear or logarithmic models. By leveraging matrix calculations, it builds a curved regression line that adapts to swings more naturally. The channel includes extrapolated forward projections, helping traders visualize where price may gravitate in the near future. Midline color shifts reflect directional bias, while prediction ranges are marked with dashed extensions, labeled prices, and a live table for clarity.
⯁ KEY FEATURES
Polynomial Regression Core:
Uses matrix algebra to calculate a polynomial fit of customizable degree, adapting to complex, non-linear market structures.
polyreg(source, length, degree, extrapolate) =>
total = length + extrapolate
X_all = matrix.new(total, degree + 1, 0.0)
for i = 0 to total - 1
for j = 0 to degree
matrix.set(X_all, i, j, math.pow(i, j))
// y (length × 1), oldest→newest over the fit window
y = matrix.new(length, 1, 0.0)
for i = 0 to length - 1
matrix.set(y, i, 0, source )
// X_train (first `length` rows of X_all)
X_tr = matrix.new(length, degree + 1, 0.0)
for i = 0 to length - 1
for j = 0 to degree
matrix.set(X_tr, i, j, matrix.get(X_all, i, j))
// OLS via normal equations: (X'X)^(-1)b = X'y ⇒ b = (X'X)^(-1) X'y
Xt = matrix.transpose(X_tr) // X'
XtX = matrix.mult(Xt, X_tr) // (X'X)
Xty = matrix.mult(Xt, y) // X'y
XtX_inv = matrix.inv(XtX) // (X'X)^(-1)
b = matrix.mult(XtX_inv, Xty) // b = (X'X)^(-1) X'y
// Predictions for all rows (fit + extrap)
preds = matrix.mult(X_all, matrix.col(b,0))
preds
Extrapolated Future Projections:
Forward-looking range (dashed lines + circular markers) shows where the fitted polynomial suggests price may move.
Dynamic Midline Coloring:
Regression midline shifts green when slope turns upward and magenta when slope turns downward, giving instant directional context.
Channel Boundaries:
Upper and lower levels expand from the midline using a volatility-based offset, framing potential overbought and oversold conditions.
Top-Right Data Table:
A live table displays Upper, Middle, and Lower Prediction values, updating in real time for quick reference without scanning the chart.
⯁ USAGE
Use the regression midline to gauge underlying market bias; green slopes suggest continuation, magenta slopes caution for weakness.
Watch dashed extrapolated ranges as potential targets or reaction zones during upcoming sessions.
Price labels and table values act as precise reference levels for planning entries, exits, or stop placement.
Increase Degree for more curve-fitting on choppy markets, or keep it low for broader trend approximation.
Adjust Period and Extrapolate length to balance stability vs. responsiveness.
⯁ CONCLUSION
The Polynomial Regression Channel offers a mathematically advanced way to visualize price trends and anticipate future paths. With matrix-driven polynomial fitting, extrapolated projections, and integrated live labels, it combines statistical rigor with practical trading visuals — a robust upgrade over standard regression channels.
Quicky's List 101this is my checklist to enter a trade,
and the grade level of each setup
so basiclly help me be more knowledgble of what i have ticked or not
deKoder | VWAP | Volume Weighted Average PriceAn advanced, open-source Volume Weighted Average Price indicator with multi-period anchoring, standard deviation bands, previous period value area extension, comprehensive alerts, and enhanced visual context.
This script is a significant upgrade over standard VWAP implementations (including TradingView's built-in VWAP (the basis for this script) and typical community versions). It is designed for experienced intraday, swing, and positional traders who require precise, context-aware mean reference levels with minimal chart clutter.
Key Features & Trading Value
1 | Previous Period Value Area Extension
Automatically extends the prior anchor period's VWAP and ±1σ bands into the current period as reference lines.
Optional translucent fill between the previous ±1σ bands creates a clear "previous value area" zone.
Why it matters : The edges of the prior period's value area often act as dynamic support/resistance or mean reversion zones. This visual persistence eliminates manual drawing and provides immediate context for reactions at prior fair value zones. These are especially powerful on intraday charts when using Daily/Weekly/Quarterly anchors.
2 | Comprehensive Approach Alerts
Configurable proximity-based alerts trigger when price approaches (from either side) any plotted level: current VWAP, all six deviation bands (±1σ, ±2σ, ±3σ), and previous period VWAP/±1σ value area.
Adjustable trigger percentage and minimum bar cooldown prevent alert spam during consolidation.
Why it matters : Enables hands-off monitoring of potential mean reversion setups, deviation extremes, or breakout/rejection candidates without constant screen watching.
3 | Additional Professional-Grade Enhancements
Flexible Anchor Periods : Daily, Weekly, Monthly, Quarterly (default), Yearly, Decade, Century, plus event-based resets (Earnings, Dividends, Splits).
Intelligent Visibility Controls :
Hide entire indicator on selected higher timeframes (1H and above).
Dynamic distance filter removes off-screen levels (based on % from price).
Limit plotting to last X bars for performance and clarity.
Real-Time Info Table :
Displays current anchor, timeframe, and rounded live values for VWAP and all bands, enabling fast access to precise level values for order placement.
Fully customisable position, text size, font (monospace option), and price level decimal rounding.
Right-Side Labels with Tooltips :
Clean, minimal labels at current levels with hover tooltips allow you to quickly identify the level without cluttering the chart.
Customizable Styling :
Independently adjustable colours for VWAP and each deviation band pair.
Offset support for forward/backward shifting.
Recommended Use Cases
Intraday Scalping/Mean Reversion : 5m–15m charts with Daily anchor + previous value area as primary reference.
Swing Entries : Higher timeframes (1H–4H) using Weekly or Quarterly VWAP for bias, with previous quarter's value area as major confluence.
Deviation Trading : Watch for price interaction with ±2σ/±3σ bands combined with approach alerts for potential exhaustion.
Institutional Benchmarking : Quarterly/Yearly anchors approximate common institutional VWAP reset periods.
Additional Notes
Source fixed to hlc3 (industry standard for VWAP).
Enjoy cleaner, more contextual VWAP analysis.
| | deKoder | |
Released December 2025 | Open Source
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ATR Bands (MA Distance)ATR Bands (MA Distance) plots volatility-based bands at a multiple of ATR away from a selected moving average.
Unlike percentage envelopes or standard deviation bands, this indicator measures distance from the moving average using ATR, representing the market’s normal “breathing range” rather than statistical probability.
Key Features
The center line is a selectable moving average (EMA, SMA, RMA/Wilder, or WMA).
Upper and lower bands are calculated as:
Moving Average ± ATR × Multiplier
Band width automatically adapts to changing market volatility.
Designed for consistent use across different markets and timeframes without parameter re-optimization.
Non-repainting: all values are calculated only from confirmed historical bars.
Intended Use
ATR Bands (MA Distance) is best used as a context and preparation tool , not as a direct entry or exit signal.
Typical use cases include:
Identifying areas where price is extended relative to its recent volatility.
Visualizing normal vs. stretched price distance from the moving average.
Supporting range-based analysis or trade preparation when combined with other indicators (e.g., oscillators).
Important Notes / How NOT to Use
This indicator does NOT generate buy or sell signals by itself .
Touching or crossing a band does not imply an automatic reversal.
In strong trending markets, price may stay outside the bands for extended periods.
ATR Bands should not be interpreted as overbought/oversold levels on their own.
This indicator does NOT repaint. Once a bar is closed, its values will not change.
For best results:
Use ATR Bands as a preparation zone, then wait for confirmation from your own entry logic.
Disable or ignore band-based mean-reversion ideas during strong trend conditions.
Concept Summary (Short)
ATR Bands (MA Distance) visualize how far price has moved from its moving average in terms of volatility, without repainting and without relying on percentage deviation or statistical assumptions.
Optional Short Description (Preview)
Volatility-based, non-repainting ATR bands plotted at a distance from a moving average.
Designed for market context and trade preparation — not standalone signals.
Nadaraya-Watson Envelope + EMA Filter (Optimized for BTC)Best Way to Use This Nadaraya-Watson EnvelopeThis indicator is not a standalone "holy grail" system — it's a powerful predictive tool that estimates where price is "likely" to go based on historical patterns.Core Idea:The orange line = predicted "fair value" or mean price path
The blue cloud = expected range (dynamic support/resistance)
Price tends to mean-revert to the orange line
Best Practices:Trade bounces in ranging markets:BUY at lower band (green) when price is below orange line
SELL at upper band (red) when price is above orange line
Target: the orange line or opposite band
Trade breakouts in trending markets:If price breaks and closes strongly outside the cloud → potential trend start
Wait for pullback to orange line for entry in trend direction
Best timeframes:5m–15m: Scalping bounces
1H–4H: Swing trading mean reversion
Add confluence for higher win rate:Only take BUY if price is above EMA 200 (uptrend bias)
Combine with volume spike or RSI oversold/overbought
Use with support/resistance levels
Risk management:Stop loss: just outside the envelope
Take profit: at orange line or next band
enjoy
Stochastic MAs+ (K Logit Bands)Below is a ready-to-paste **English TradingView publish description** that is detailed enough to satisfy the “Originality & usefulness” and “Description” house-rule expectations. It explains **what is original**, **why the components are combined**, **how they work together**, and **how to use it**, including practical presets and cautions.
---
## Title
**Stochastic MAs+ (K Logit Bands) — Extreme-Zone Reversion with Adaptive Percentile Bands**
## Overview
This script is a **Stochastic-based extreme-zone tool** designed for traders who want signals that occur **near statistically-defined extremes**, while reducing noise and overtrading.
It combines three ideas into one coherent workflow:
1. **Stochastic %K/%D with selectable smoothing MAs** (EMA/ZEMA/SMA/KAMA)
2. **Adaptive Logit Percentile Bands** computed **on %K** (not price) to define “extreme” zones dynamically
3. A **two-step signal workflow** (Touch → Re-entry → First K/D Cross) with **cooldown + invalidation rules** to suppress repeated signals in choppy markets
This is not a “mashup for convenience.” The logit-percentile bands and the signal state-machine are explicitly built to **solve a common Stochastic problem**: fixed 20/80 levels are often too generic, and raw K/D crosses can fire repeatedly in ranges. The components here work together to make Stochastic extremes more **context-aware** and signals more **selective**.
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## What makes it original / useful
### 1) Dynamic extremes based on the oscillator’s own distribution
Instead of using fixed 20/80, the script builds **percentile-based bands on transformed %K values**:
* **Logit transform** is used to expand sensitivity near 0 and 100 (where Stochastic tends to compress).
* A rolling buffer stores recent transformed values.
* **Percentiles** (e.g., 15% / 85%) define adaptive low/high bands that respond to changing volatility regimes.
Result: “Extreme” zones are **relative to recent market behavior**, which is often more practical than static thresholds.
### 2) A structured signal process to reduce overtrading
Classic Stochastic crossovers can spam signals. This script uses a **state-based trigger**:
**Long logic**
1. %K drops below the **adaptive low band** (touch/arm)
2. %K re-enters above the low band (re-entry)
3. The first bullish crossover occurs (K crosses above D) while K remains below the mid-band
**Short logic** is symmetrical.
Then it adds:
* **Cooldown**: prevents clustered entries during noisy periods
* **Max wait**: invalidates old setups if confirmation takes too long
* **Mid-band invalidation**: if K moves too far (crosses mid), the setup is considered late and discarded
This turns Stochastic into a **controlled mean-reversion trigger** rather than an always-on crossover machine.
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## How it works (plain-language)
### A) Stochastic with selectable smoothing (MAK/MAD)
* `%K` is computed from the standard Stochastic formula, then smoothed with your chosen MA.
* `%D` is computed by smoothing `%K` with a chosen MA.
**MA options**
* **EMA**: baseline responsive smoothing
* **ZEMA**: reduced lag (faster reactions)
* **SMA**: heavier smoothing (less noise)
* **KAMA**: adaptive smoothing (reacts faster when price moves, slower in noise)
### B) K-based Logit Percentile Bands
The script builds bands from **%K**, not from price:
* Convert K into logit space → store in rolling buffer
* Compute low/high percentiles in logit space
* Convert back to 0–100 space with logistic function
* Produce: **kLo / kHi / kMid**
This keeps the bands stable and meaningful even when volatility changes.
### C) Signal state-machine
* **Touch**: K enters extreme zone
* **Re-entry**: K exits the extreme zone
* **Trigger**: first K/D cross after re-entry, while still in the “early” half of the band (before mid)
The idea is to catch reversals **early**, but not on the very first noisy bounce.
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## How to use
### 1) Baseline setup (recommended starting point)
These defaults are already aligned with the script’s intent:
* Stoch: **21 / 3 / 7**
* Bands: **bandLen 200**, **low/high 0.15/0.85**, **logitGain 1.0**
* Signals: **cooldown 8**, **maxWait 24**, **Use D Direction Confirm ON**
This typically produces fewer, more selective signals than traditional 14/3/3 style settings.
### 2) Interpreting the plots
* **%K (purple)** and **%D (yellow)** are the smoothed oscillator lines.
* **kLo / kHi / kMid** are the adaptive bands.
* Labels:
* **“L”** appears near the low band when a long setup completes
* **“S”** appears near the high band when a short setup completes
### 3) Practical trading workflow
* Prefer using signals as **timing cues**, not as a complete strategy by themselves.
* Many traders combine this with:
* a trend filter (e.g., EMA200 direction)
* a volatility filter (avoid low-vol chop)
* or higher timeframe confirmation
The script is designed to give **high-quality entry timing near extremes**, but you still need a trade plan for exits and risk management.
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## Tuning guide (fast)
### Want signals closer to extremes (more selective)?
* Decrease / increase percentiles:
* lowPct **0.12** and highPct **0.88**
* Increase logitGain slightly:
* logitGain **1.1–1.2**
* Increase cooldown:
* cooldown **10–14**
### Want earlier signals (faster confirmations)?
* Use faster MA for %D (or reduce periodD):
* maD = **ZEMA** (or EMA)
* Reduce cooldown a bit:
* cooldown **5–8**
### Getting too many signals in ranges?
* Increase periodK to reduce chop:
* periodK **34**
* Increase cooldown
* Keep D confirm enabled
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## Strengths
* **Adaptive extreme zones**: bands adjust to changing regimes (better context than static 20/80)
* **Reduced noise**: the Touch→Re-entry→Cross structure avoids many “random” crosses
* **Configurable smoothing**: lets you tune response vs stability via MA type
* **Risk-friendly by design**: cooldown + invalidation reduce repeated entries during chop
## Limitations
* **Not a full strategy**: no position management, take-profit/stop rules, or trend filter included
* **Mean-reversion bias**: in strong trends, Stochastic can stay overbought/oversold for long periods
* **Band buffer needs history**: percentile bands are more reliable after enough bars have accumulated (bandLen)
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## Notes on repainting / confirmations
* The percentile band buffer uses **confirmed bars** (optional) to avoid unstable band updates during an incomplete candle.
* Signal labels are plotted when the full signal conditions are met (you can enforce confirmed-bar signals via settings).
---
## Suggested disclaimer (TradingView-friendly)
This indicator is for research and educational purposes and does not constitute financial advice. Always test settings on your market/timeframe and use proper risk management.
London Session + EMA 200 + UT BotCombined trading indicator featuring three powerful tools:🔵 London Session Box - Highlights the London trading session (0700-1600) with a customizable colored box to identify high-volume trading periods📈 EMA 200 - Exponential Moving Average for trend identification and dynamic support/resistance levels🎯 UT Bot - ATR-based trailing stop indicator with buy/sell signals and bar coloring for trend following
hassan box 2026This indicator is a tool designed to monitor general areas and predict future targets.
mncl's SL_TP FInderWe are all used to using the ATR to estimate the stop loss or take profit. So I wondered if there is another way since I found the ATR a little too far sometimes.
In this script, i combine other ways of finding your take profit or stop loss. These can be found in the settings. I also include a way to estimate the amount of money to risk per trade.
Have a go at it and let me know if you found it useful.
- mncl -
Volume Anomaly Reversal DetectionVolume Anomaly Reversal Detection (VARD System)
🎯 What This Indicator Does
This indicator identifies potential trend reversals by detecting abnormal volume activity that often precedes significant price movements. It combines volume anomaly detection with dynamic trend analysis to generate actionable BUY/SELL signals.
📊 Core Concept & Methodology
Volume Anomaly Detection
The indicator analyzes directional volume (buying vs selling pressure) from a lower timeframe and calculates Z-scores to identify statistically significant volume spikes.
Z-Score Formula:
Z = (Current Volume - Average Volume) / Standard Deviation
When volume exceeds the threshold (default: 3 standard deviations above mean), it signals unusual market activity - often caused by forced liquidations or capitulation.
Dynamic Trend Filter
A custom trend-following algorithm based on ATR (Average True Range) bands determines the current market direction:
Price above lower band = Uptrend
Price below upper band = Downtrend
Signal Logic
Volume anomaly detected during an existing trend
Trend reversal confirmed within the confirmation window
Signal generated = BUY or SELL label appears
⚙️ Settings Explained
SettingDefaultDescriptionAnalysis Timeframe15minLower timeframe for volume samplingStatistical Lookback200Bars used for Z-score calculationAnomaly Sensitivity3.0Z-score threshold (lower = more signals)Confirmation Window50Max bars between anomaly and trend flipATR Multiplier2.0Trend band widthTrend Period10ATR calculation length
📖 How To Use
Entry Signals
BUY: Green label appears below bar - consider long positions
SELL: Red label appears above bar - consider short positions
Volume Anomaly Markers (⬥)
Small diamonds indicate detected volume spikes
These are early warnings before confirmed signals
Useful for anticipating potential reversals
Trend Bands
Colored zones show active signal direction
Stay with the trend until opposite signal appears
Best Practices
Confirm with price action - Look for support/resistance levels
Use appropriate timeframes - Works on all timeframes, but 1H-4H recommended
Manage risk - Always use stop losses
Avoid ranging markets - Best in trending/volatile conditions
⚠️ Important Notes
No indicator is perfect - Use as part of a complete trading strategy
Volume data required - Will show warning if volume unavailable
Not financial advice - Always do your own research
🔔 Alerts Available
BUY Signal Confirmed
SELL Signal Confirmed
Volume Anomaly (Buy Setup)
Volume Anomaly (Sell Setup)
Vegas Double ChannelThe indicator utilizes the 144 and 169 channels as the minor level, and the 576 and 676 channels as the major level. The EMA12 serves as a filter.
Translation for the complete definition of the “Vegas Double Channel” indicator:
The “Vegas Double Channel” indicator is designed to analyze market trends and identify potential trading opportunities. It employs the following parameters:
Minor Level: The indicator considers the 144 and 169 channels as the minor level, which are used to identify short-term market movements.
Major Level: The 576 and 676 channels are classified as the major level, indicating longer-term market trends.
Filter: The EMA12 (Exponential Moving Average with a period of 12) acts as a filter to smooth out short-term noise and provide a clearer picture of the overall market trend.
TTM Squeeze Screener FriendlyTTM Squeeze indicator optimized for use with TradingView Pine Screener — computes squeeze on/just‑on/release and momentum on the chart symbol (60m default).
8x EMA + Labels + Trend + Volume Arrows + Developing VAH/VALThis indicator is a comprehensive trend, structure, and momentum tool designed for intraday and swing traders.
It combines multi-timeframe EMAs, dynamic EMA labels, developing Value Area High/Low, and volume-based entry signals into a single clean overlay.
Top 10 Bullish Wedge ScannerThe script does a check of all stocks and gives the top 10 list of stocks with bullish wedge formed on daily timeframe.
CUSUM Volatility BreakoutCUSUM Volatility Breakout A statistical trend-detection and volatility-breakout indicator that identifies subtle momentum shifts earlier than traditional tools.
OVERVIEW
The CUSUM control chart is a statistical tool designed to detect small, gradual shifts from a target value. In trading, it helps identify the early stages of a trend, giving traders a heads-up before momentum becomes obvious on standard price charts. By spotting these subtle movements, the CUSUM Volatility Breakout indicator (CUSUM VB) can highlight potential breakout opportunities earlier than traditional indicators. In other words, a statistical trend detection & breakout indicator.
Copyright © 2025 CoinOperator
HOW IT WORKS
CUSUM VB uses a combination of differenced price series, volume normalization, and dynamic control limits:
CUSUM Principle: Tracks cumulative deviations of price from a zero reference. Signals occur when cumulative deviations exceed a control limit shown on the chart and clears any enabled filters.
Adaptive Volatility: H adjusts automatically based on short- vs long-term ATR ratios, allowing faster detection during volatile periods and reduced false signals in calm markets.
Volume Weighting (optional): Amplifies price CUSUM values during high-volume bars to prioritize market participation strength.
ATR Confirmation (optional): Ensures breakouts are accompanied by expanded volatility.
Bollinger Band Squeeze Integration (optional): Confirms trend breakouts by detecting volatility contraction and release shown on the chart as triangles.
Signals:
Arrows on the price chart mark the bars where trades are actually filled, based on conditions detected on the prior signal bar.
Long Entry: Confirmed positive CUSUM breach (price & volume) with BB breakout (signal bar).
Short Entry: Confirmed negative CUSUM breach (price & volume) with BB breakout (signal bar).
Exit Signals: Triggered automatically by opposite-side signals.
Alerts, when created, fire on the bars where fills occur.
CHART COMPONENTS
CUSUM Upper Price (CU Price) and CUSUM Lower Price (CL Price) are green/red circles for confirmed signals.
● Rapid upward accumulation of CU Price indicates a developing bullish trend.
● Rapid downward accumulation of CL Price indicates a developing bearish trend.
Decision/Control limits (UCL/LCL, red)
Zero line (reference for the differenced price series baseline)
Optional BB triangles and volume CUSUM
SETUP AND CONFIGURATION
Differenced Price Series
Differenced Price Length and Lag
Increase differencing lag or window length → Increases variance of residuals → Wider control limits (UCL/LCL) → Slower to trigger.
Decrease lag or window → Tighter limits, more responsive to short-term regime shifts.
CUSUM Parameters
Volume-Weighted CUSUM
NOTE : Uses price length if 'Confirm Price with Volume' is disabled, otherwise will use volume length.
Amplifies CUSUM price responses during high-volume bars and reduces them during low-volume bars. This links trend detection to market participation strength.
Volume-Weighted CUSUM doesn’t replace price confirmation with volume; it modulates it by volume intensity, amplifying price signals when participation is strong and suppressing them when weak.
Recommended when analyzing assets with consistent volume patterns (e.g., stocks, major futures).
Disable for low-liquidity or irregular-volume instruments (e.g., crypto pairs, small-cap stocks).
ATR Confirmation
Enable this feature to confirm CUSUM signals only when price deviations are accompanied by higher-than-normal volatility. The indicator compares current ATR to a smoothed ATR to detect volatility expansion. This helps distinguish true breakouts from low-volatility noise and reduces false signals during quiet periods.
Adjust the ATR lookback length, smoothing length, and expansion factor to control sensitivity. Rule of thumb:
ATR Length ≈ 0.5 × differenced price length to 1.5 × differenced price length gives balanced sensitivity.
ATR Smoothing 5–10 bars.
ATR Expansion 5% to 50%.
CUSUM Input Mode
Select how CUSUM processes differenced price and log-normalized volume — either directly (Txfrm Data) or as deviations from a short-term EMA baseline (Residuals):
Txfrm Data = transformed input: differenced price & log-normalized volume as input for CUSUM (larger swings, more frequent control limit breaches)
Residuals = deviation from short-term EMA baseline (smaller swings, fewer control limit breaches, but higher signal quality).
Residual EMA Length: Defines how quickly the residual baseline adapts to recent differenced price moves. Shorter = more reactive; longer = smoother baseline. Keep EMA length moderate; over-smoothing can distort timing.
Control Sensitivity (K)
Increase K → Less sensitive → CUSUM accumulates slower → Fewer signals, captures only major trends.
Decrease K → More sensitive → CUSUM accumulates faster → More signals, captures minor swings too.
Reset Mode : Method of resetting CUSUM values.
Immediate Reset: Reset both immediately after any signal breach. Traditional SPC.
Opposite-Side Reset: Reset only the opposite side when a valid signal fires. Best for ongoing trend tracking.
Decay Reset: Gradually reduce CUSUM values toward zero with a decay factor each bar. Maintains trend memory but allows slow “forgetting.”
Threshold Reset: Reset only if CUSUM returns below a small threshold (10 % of H). Filters noise without full wipe.
No Reset / Continuous: Never reset; instead track running totals. Long-term cumulative bias measurement.
Conflict Handling : Method of handling conflicting signals.
Ignore Both: Discards both when overlap occurs.
Prioritize Latest: Chooses the direction implied by the most recent close.
Prioritize Stronger: Compares absolute magnitudes of CU Price vs CL Price.
Average Resolve: Looks at the difference; small overlap → ignore, otherwise pick direction by sign.
Sequential Confirm: Requires N consecutive same-direction signals before confirmation.
Volume Parameters (Optional)
Amplification Factor
Adjusts volume sensitivity and effectively rescales the log series of volume to a comparable magnitude with price changes.
Since price and volume are normalized in a compatible way, the amplification factor is used instead of independent K and H values for volume.
Bollinger Bands (Optional)
Lookback Synchronization
BB Lookback (for CUSUM): Number of bars that define a window for the BB signal to look back for the CUSUM signal.
CUSUM Lookback (for BB): Number of bars that define a window for the CUSUM signal to look back for the BB signal.
Both can be enabled for stricter alignment.
Relationship Between K, H, ARL₀ and ARL₁
H (max) is usually the only H you need to adjust. With everything else being constant, increasing either K or H (max) generally increases both ARL₀ and ARL₁ : higher thresholds reduce false alarms but slow detection, and lower thresholds do the opposite.
Increase Min Target ARL ratio →
ARL₀ increases (safer, fewer false alarms)
ARL₁ decreases or stays small (faster detection)
Control limits slightly expand to achieve separation
Strategy becomes more selective and stable
Decrease Min Target ARL ratio →
ARL₀ decreases (more false alarms tolerated)
ARL₁ increases (slower detection tolerated)
Control limits tighten
Strategy becomes more sensitive but lower quality
The ARL Ratio of ARL₀ / ARL₁ is typically between 3 and 8. This implies you want your ARL₀ (false-alarm interval) ≈ 'Min Target ARL ratio' × differenced price length window.
Example:
"Min Target ARL ratio = 4.0"
⇒ implies you want your ARL₀ (false-alarm interval) ≈ 4 × differenced price length.
Assume price length = 50 (typical differencing window).
ARL ratio = 4.0 → target ARL = 4 × 50 = 200 bars.
● On a 6-hour chart (≈4 bars/day) → ~50 days between expected false alarms (on average).
● On a daily chart → ~200 trading days between false alarms (very conservative).
ARL ratio = 8.0 → target ARL = 400 bars → twice as infrequent signals vs ratio=4.
ARL ratio = 2.0 → target ARL = 100 bars → about half the inter-signal interval.
Another way to think about it: probability of a false alarm on any bar ≈ 1 / target ARL. If you want ~1% of bars producing alarms, target ARL ≈ 100.
QUICK START
Start with the defaults.
Set price series → length/order/lag
Configure CUSUM thresholds → K, H min/max
1. Adjust the price differencing lag/window.
2. Verify that it captures real price inflection points without overreacting to bar noise.
Enable optional filters → Volume, ATR, BB
The optional Bollinger Bands squeeze usually works best if used with CUSUM Input Mode = Txfrm Data.
Monitor CUSUM chart → CU Price, CL Price, thresholds, zero line
Act on signals → data window / chart triangles
Adjust sensitivity → H (max), K, lengths
Monitor ARL ratio and CUSUM behavior for fine-tuning
Note : When you’ve finalized the length, lag, and order of the Price Difference, as well as the Ln(Vol) Series of “Confirm Price with Volume” if enabled, then pass both through the Augmented Dickey–Fuller (ADF) mean reversion test to ensure they are stationary, i.e., mean reverting. You can find a ready-made indicator for such use at . Many thanks to tbtkg for this indicator.
SUMMARY
CUSUM VB combines CUSUM statistical control, volatility-adaptive thresholds, volume weighting, and optional BB breakout confirmation to provide robust, actionable signals across a wide variety of trading instruments.
Why traders use it : Fast detection of shifts, reduced false alarms, versatile across markets.
Ideal for : Futures (continuous contracts), forex, crypto, stocks, ETFs, and commodity/index CFDs, especially where:
● Price and volume data exist
● Breakouts and volatility shifts are tradable
● There’s enough liquidity for meaningful signals
Visualization : Upper/lower CUSUM circles, UCL/LCL thresholds, optional highlight traded background, optional volume and BB overlays on the chart, optional entry/exit labels on the price chart, as well as entry/exit signals in the data window.
Alerts : For entry/exit labels when trades are actually filled.
CUSUM VB is designed for traders who want statistically grounded trend detection with configurable sensitivity, visual clarity, and multi-market versatility.
DISCLAIMER
This software and documentation are provided “as is” without any warranties of any kind, express or implied. CoinOperator assumes no responsibility or liability for any errors, omissions, or losses arising from the use or interpretation of this software or its outputs. Trading and investing carry inherent risks, and users are solely responsible for their own decisions and results.
