Range Bound Channel Index (RBCI) w/ Expanded Source Types [Loxx]Range Bound Channel Index (RBCI) w/ Expanded Source Types is a reversal and trend indicator. This version includes Bollinger bands to show trend exhaustion
What is Range Bound Channel Index (RBCI)?
Range Bound Channel Index (RBCI) is calculated by using a channel (bandwidth) filter (CF). Channel filter simultaneously fulfills two functions: removes low frequent trend formed by low frequent components of the spectrum; removes high frequency noise formed by the high frequent components of the spectrum.
When RBCI approaches its local maximum the prices approach upper border of the trading channel and when RBCI approach its local minimum the prices approach the lower border of the trading corridor.
Included:
-Toggle on/off bar coloring
-Loxx's Expanded Source Types
Cari dalam skrip untuk "band"
Bollinger CloudsThis indicator plots Bollinger Bands for your current timeframe (e.g 5 minutes) and also plots the Bollinger Bands for a higher timeframe (15 minutes for 5 minute timeframe). Then the gaps between the current and higher timeframe upper and lower bands is filled to create clouds which can be used as entry zones. Like Bollinger Bands, this indicator shouldn't be solely used for entries, use it in conjunction with other indicators.
Bollinger Band Timeframes
Current / Higher
1 minute / 5 minutes
3 minutes / 10 minutes
5 minutes / 15 minutes
10 minutes / 30 minutes
15 minutes / 1 hour
30 minutes / 2 hours
45 minutes / 1.5 hours
1 hour / 4 hours
2 hours / 8 hours
2.5 hours / 10 hours
4 hours / 1 Day
1 Day / 3 Days
3 Days / 9 Days
5 Days / 2 Weeks
1 Week / 1 Month
Waddah Attar Explosion V3 [NHK] -Bollinger - MACDWaddah Attar Explosion Version3 indicator to work in Forex and Crypto, This indicator oscillates above and below zero and the Bollinger band is plotted over the MACD Histogram to take quick decisions, Colors are changed for enhanced look. dead zone is plotted in a background area and option is provided to hide dead zone. One can easily detect sideways market movement using Bollinger band and volume. when volume is in between Bollinger band no trades are to be taken as volume is low and market moving in sideways
credits to: @shayankm and @LazyBear
Read the main description below...
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This is a port of a famous MT4 indicator. This indicator uses MACD /BB to track trend direction and strength. Author suggests using this indicator on 30mins.
Explanation from the indicator developer:
"Various components of the indicator are:
Dead Zone Line: Works as a filter for weak signals. Do not trade when the up or down histogram is in between Dead Zone.
Histograms:
- Pink histogram shows the current down trend.
- Blue histogram shows the current up trend.
- Sienna line / Bollinger Band shows the explosion in price up or down.
Signal for ENTER_BUY: All the following conditions must be met.
- Blue histogram is raising.
- Blue histogram above Explosion line.
- Explosion line raising.
- Both Blue histogram and Explosion line above DeadZone line.
Signal for EXIT_BUY: Exit when Blue histogram crosses below Explosion line / Bollinger Band.
Signal for ENTER_SELL: All the following conditions must be met.
- Pink histogram is raising.
- Pink histogram above Explosion line.
- Explosion line raising.
- Both Pink histogram and Explosion line above DeadZone line.
Signal for EXIT_SELL: Exit when Pink histogram crosses below Explosion line.
All of the parameters are configurable via options page. You may have to tune it for your instrument.
fi - 5EMA + BB - 5 emas en un mismo indicador junto con las bandas de bollinguer.
- Opcion de timeframe
- Actualizado a version 5
//Indicador adaptado a medida sobre "4EMA lines EMA Cross @Philacone + Bollinger Bands by Alessiof"
//Todos los méritos para Alessiof, muchas gracias!!!
Correlations P/L Range (in percent)This script shows the inefficiency of the markets.
Comparing two (correlated) symbols, the values above 0 means the main symbol (at the top of the graph)
outperforms the other. A value below 0 means the main symbol underperforms the other.
The band displays different entries until the last candle. Any P/L (of the band range)
is visible in the band. Example: given a band range length of 5, then all last 5 values
are compares with the current value for both symbols. Or in other words:
If symbol A, lets say ETHUSD outperforms, lets say BITCOIN (the main symbol), in the last
5 candles, then we would see all values of the band are negative.
Any question, comment or improvements are welcome.
Julius Single TrailJulius Single Trail — How it works
This indicator combines a Kalman-like smoothed Donchian midline with an ATR-style volatility buffer to create a single adaptive trailing line that flips with trend. It also recolors candles to reflect regime and visually marks ranging conditions using Bollinger Band width. Optionally, it adds a dotted price line and can hide default candles for a clean, unified look.
Core logic
Donchian midpoint: Calculates the middle of the highest high and lowest low over Donchian Length. This is the directional anchor.
Kalman-like smoothing: Applies a lightweight exponential update to the Donchian midpoint using Alpha, reducing noise while staying responsive.
Volatility buffer: Uses RMA of True Range over Volatility Length multiplied by Volatility Multiplier to form an adaptive offset around the smoothed midline.
Dynamic trail:
Up-trend regime (regime = 1): The trail is kMid - offset and only ratchets upward (math.max), acting like a long stop.
Down-trend regime (regime = -1): The trail is kMid + offset and only ratchets downward (math.min), acting like a short stop.
Flip conditions: Regime flips only when price is on the far side of both the smoothed midpoint and the current trail:
Flip to down when close < kMid and close < dynTrail
Flip to up when close > kMid and close > dynTrail
Candle styling:
Wick color shows immediate price direction (green for bullish, red for bearish).
Body color follows the trail’s regime (Uptrend Color or Downtrend Color).
In ranging conditions, all candle elements turn gray.
Ranging detection:
Computes Bollinger Bands on close with BB Length and BB Multiplier.
Calculates width as a percentage of the basis. If width% (optionally smoothed) is below Range Threshold %, candles are gray to signal consolidation.
What it plots
Dynamic Trail: A single, thick line that changes color by regime:
Uptrend: Uptrend Color (default lime)
Downtrend: Downtrend Color (default red)
Optional Trail Fill to Close: A translucent band between the trail and the close (disabled by default).
Optional Dotted Price Line: A dotted horizontal line at the current price (toggle via Show Dotted Price Line).
Candle treatment:
You can hide default candles (Hide Default Candles), then use a separate custom-candle script for wick/body/border mapping. In this script, default candles can be made fully transparent to let the trail and colors dominate.
Inputs
Donchian Length: Window for the highest/lowest used to form the midline.
Kalman Alpha 0–1: Smoothing factor for the midline. Higher = more responsive, lower = smoother.
Volatility Length: RMA length of True Range for the volatility buffer.
Volatility Multiplier: Scales the buffer around the midline. Higher widens the trail, reducing flips.
Uptrend Color / Downtrend Color: Trail and body color by regime.
Show Cloud To Close: Fills between price and trail using the trail’s color.
Hide Default Candles: Makes the native candles fully transparent.
Show Dotted Price Line / Price Line Color: Toggles and colors the dotted price line.
Ranging parameters:
BB Length (Ranging) and BB Multiplier (Ranging): Bollinger Band settings.
Range Threshold %: If BB width% < threshold, candles turn gray to indicate range.
Use Smoothed Width / Width Smoothing Length: Smooths BB width% before comparison.
Signals and interpretation
Regime shifts:
Bullish flip: When price closes above both the smoothed midpoint and the current trail. Trail switches to the lower band (kMid - offset) and ratchets up.
Bearish flip: When price closes below both the smoothed midpoint and the current trail. Trail switches to the upper band (kMid + offset) and ratchets down.
Trend bias:
Green trail/body: Favor long bias; trail can serve as a dynamic stop.
Red trail/body: Favor short bias; trail can serve as a dynamic stop.
Ranging filter:
Gray candles: Lower-probability trend continuation; consider reducing position sizing, waiting for a breakout, or using mean-reversion tactics.
How to use it
Trend following:
Enter in the direction of the regime when flips occur or on pullbacks that respect the trail.
Use the trail as a stop-loss guide: exit when price closes beyond the trail and the regime flips.
Range awareness:
When candles turn gray, avoid trend entries or switch to range tactics. Wait for color to return and a clean flip.
Tuning suggestions:
Faster, more responsive: Lower Donchian Length, increase Alpha, lower Volatility Length and/or Volatility Multiplier.
Smoother, fewer flips: Increase Donchian Length, decrease Alpha, increase Volatility Length and/or Volatility Multiplier.
Ranging strictness: Increase Range Threshold % to mark ranges more often; smooth the width to avoid choppiness.
Example settings
Swing trading:
Donchian Length: 50
Alpha: 0.25
Vol Length: 14
Vol Mult: 1.6
BB Length: 20, BB Mult: 2.0, Range Threshold %: 2.0, Smoothed width ON (20)
Intraday (more responsive):
Donchian Length: 20–30
Alpha: 0.4–0.6
Vol Length: 10–14
Vol Mult: 1.2–1.6
Range Threshold %: 1.5–2.5 depending on instrument
Alerts (suggested)
Regime flips:
Condition: close > dynTrail and close > kMid -> Alert: Bullish regime
Condition: close < dynTrail and close < kMid -> Alert: Bearish regime
Range state:
Condition: BB width% < threshold -> Alert: Ranging
You can wire these using alertcondition() on the flip conditions and isRange variable inside the script.
Notes and limitations
This is a single-side ratcheting trail per regime, designed to reduce whipsaw by requiring price to clear both the midpoint and the trail before flipping.
Like all trend tools, it can lag tops/bottoms and may chop in low-volatility, sideways markets.
For assets with highly irregular volatility, retune Volatility Multiplier and Range Threshold %.
Short description (for header):
Adaptive, single-line trailing stop based on Kalman-smoothed Donchian mid + ATR-style buffer. Colors candles by regime, grays out ranges via BB width. Optional price line and cloud.
If you want, I can add alertcondition() for the flip and range events and a light custom-candle overlay so you can publish with built-in alert templates and consistent candle styling.
The Vishnu Zone Ver 2 by Dr. Sudhir Khollam## 📜 **The Vishnu Zone — Trade When the Brahma Zone Ends**
**Author:** Dr. Sudhir Khollam (SALSA© Method of Astrology & Market Psychology)
**Category:** Volatility Phase Detection / Bollinger Band Expansion Analysis
---
### 🔶 **Concept Overview**
In the **SALSA© Market Philosophy**, every market phase follows a cosmic rhythm —
* **Brahma Phase** represents *creation and expansion* (high volatility and strong directional movement).
* **Vishnu Phase** represents *maintenance and stability* (where expansion cools down and balanced opportunities appear).
**“The Vishnu Zone”** indicator identifies the exact moments when the **Brahma Phase ends** — signaling that the expansion has completed and the market is likely to enter a more stable, tradable state.
This is a **precision-timing indicator** that helps traders avoid entering at the end of impulsive phases and instead prepare for equilibrium-based trades (mean reversion, range setups, or steady trends).
---
### ⚙️ **How It Works**
The indicator measures **Bollinger Band Width (BBW)** to quantify expansion and contraction in volatility.
1. It calculates the **adaptive expansion threshold** using the average BBW over a rolling lookback period.
2. When the current BBW **drops below** this adaptive threshold **after being above it**, the script marks it as the **end of the Brahma Phase**.
3. This moment is shown visually as:
* 🕉 **“Vishnu” label** above the candle
* A **horizontal dotted line** extending for several bars
Together, these mark a **Vishnu Zone**, where the market transitions from expansion to consolidation — an ideal time for stabilization or entry planning.
---
### 📊 **Inputs & Settings**
| Parameter | Description |
| ---------------------------------- | ------------------------------------------------------------------------------ |
| **Bollinger Band Length** | The number of bars used for SMA and standard deviation (default 20). |
| **Bollinger Multiplier** | Determines the width of Bollinger Bands (default 2.0). |
| **Adaptive Lookback Period** | Rolling window to calculate the mean BBW for dynamic adjustment (default 150). |
| **Expansion Multiplier** | Multiplies the mean BBW to define the expansion threshold (default 1.35). |
| **Horizontal Line Extension Bars** | Number of bars to extend the Vishnu Zone line into the future (default 40). |
| **Show End-of-Brahma Labels?** | Toggle 🕉 labels on/off. |
| **Show Horizontal Lines?** | Toggle Vishnu Zone lines on/off. |
---
### 🔔 **Alerts**
When the **Brahma Phase ends**, the indicator triggers an alert:
> *“Brahma Phase Ends, Vishnu has taken over.”*
This helps traders receive real-time notification of volatility contraction and possible entry zones.
---
### 🧠 **Best Practices**
* Works effectively on **5-minute to 1-hour timeframes** for intraday trading.
* Best paired with **momentum or volume filters** to confirm trend exhaustion.
* Avoid entering during rapid expansion (Brahma phase). Wait for a Vishnu signal to ensure market stabilization.
---
### 🌌 **Philosophical Interpretation (SALSA© Principle)**
Just as Vishnu sustains the universe after Brahma’s creation, the market too enters a **maintenance phase** after every burst of expansion.
Recognizing this shift allows traders to align with **cosmic rhythm and price psychology**, not just technical metrics.
---
### 🧩 **Summary**
✅ Detects when expansion volatility ends
✅ Marks transition zones between impulsive and stable phases
✅ Sends real-time alerts
✅ Adaptive and self-adjusting across markets and assets
✅ Simple, clean visualization — ideal for disciplined trading
---
### ⚡ **Use Case**
Perfect for traders who:
* Prefer **low-risk entries** after volatility spikes
* Trade **mean reversion**, **range breakouts**, or **volatility collapses**
* Believe in the **cyclic nature of market energy**
---
Pro Scalper - Kalman Supertrend with Dynamic OB/OS Zones═══════════════════════════════════════════════════════════════════
PRO SCALPER - KALMAN SUPERTREND WITH DYNAMIC OB/OS ZONES
Developed by Zakaria Safri
═══════════════════════════════════════════════════════════════════
A powerful day trading and scalping indicator designed for the 30-minute
timeframe, combining advanced Kalman filtering with Supertrend analysis
and VWMA-based overbought/oversold detection for stocks and cryptocurrencies.
🎯 KEY FEATURES
═══════════════════════════════════════════════════════════════════
✅ Kalman-Filtered Supertrend
• Advanced noise reduction using Kalman Filter mathematics
• Reduces false signals by filtering market noise
• Adaptive trend-following with dynamic support/resistance
✅ Clear Buy/Sell Signals
• Green "BUY" labels for long entries
• Red "SELL" labels for short entries
• Signals trigger on confirmed trend reversals
• Matrix-style candle coloring (Green=Bull, Red=Bear)
✅ Dynamic Overbought/Oversold Zones
• VWMA-based adaptive zones
• Automatically adjusts to market volatility
• Visual zone highlighting with fills
✅ Reversal Signal Detection
• "R" markers identify potential reversals
• Vertical lines highlight reversal bars
• Based on price rejection from OB/OS zones
✅ Smart Take Profit System
• Automatic TP levels at OB/OS zones
• "X" markers when targets are hit
• Based on higher-high/lower-low logic
✅ Live Entry Price Table
• Shows current trend direction
• Displays last signal type (BUY/SELL)
• Real-time entry price tracking
✅ Comprehensive Alert System
• Buy/Sell signal alerts
• Reversal detection alerts
• Take profit hit notifications
• All alerts are non-repainting
📊 HOW IT WORKS
═══════════════════════════════════════════════════════════════════
1. KALMAN FILTER
The indicator applies Kalman filtering to price and ATR data, using
mathematical equations derived from Rudolf E. Kalman's work. This
advanced filtering technique:
• Smooths price data while maintaining responsiveness
• Removes outliers and reduces market noise
• Adapts to changing market conditions
• Improves signal accuracy and reliability
2. MODIFIED SUPERTREND
A customized Supertrend calculation that uses:
• Kalman-filtered HL2 price instead of raw prices
• Filtered ATR for volatility measurement
• Adaptive trailing bands that follow price
• Trend detection with minimal lag
3. VWMA DYNAMIC ZONES
Volume-Weighted Moving Average bands that:
• Calculate from highest/lowest prices over lookback period
• Adapt to current volatility and price range
• Identify true overbought/oversold conditions
• Provide logical take-profit targets
4. SIGNAL GENERATION
• BUY: When price breaks above Supertrend (trend flips bullish)
• SELL: When price breaks below Supertrend (trend flips bearish)
• REVERSAL: When price rejects from OB/OS zones
• TAKE PROFIT: When price reaches target zones or forms HH/LL
⚙️ SETTINGS GUIDE
═══════════════════════════════════════════════════════════════════
🔧 KALMAN FILTER SETTINGS
┌─────────────────────────────────────────────────────────────┐
│ Gain (0.7) → Higher = More responsive, Less smooth │
│ Momentum (0.3) → Higher = More momentum, Less filtering │
└─────────────────────────────────────────────────────────────┘
📈 SUPERTREND SETTINGS
┌─────────────────────────────────────────────────────────────┐
│ ATR Period (10) → Lookback for volatility calculation │
│ ATR Multiplier (3.0) → Distance of bands (lower = more sigs)│
└─────────────────────────────────────────────────────────────┘
📊 VWMA BANDS (OB/OS ZONES)
┌─────────────────────────────────────────────────────────────┐
│ VWMA Length (20) → Smoothing period │
│ Overbought Multiplier (1.5) → OB zone distance │
│ Oversold Multiplier (1.5) → OS zone distance │
│ Band Lookback (20) → Range calculation period │
└─────────────────────────────────────────────────────────────┘
💡 USAGE INSTRUCTIONS
═══════════════════════════════════════════════════════════════════
RECOMMENDED SETUP:
• Timeframe: 30 minutes (optimized for intraday trading)
• Markets: Stocks, Cryptocurrencies, Forex
• Risk Management: Always use stop losses
• Confirmation: Combine with volume and support/resistance
ENTRY SIGNALS:
1. Wait for BUY/SELL label to appear
2. Check trend direction (candle color)
3. Confirm entry on next candle open
4. Set stop loss below/above Supertrend line
EXIT SIGNALS:
1. Take profit at "X" markers
2. Exit on opposite signal
3. Exit on reversal "R" if against your position
4. Manual exit at predetermined R:R ratio
REVERSAL TRADING:
1. Wait for "R" marker in OB/OS zone
2. Confirm with candlestick pattern
3. Enter counter-trend trade
4. Target middle VWMA or opposite zone
🎨 VISUAL ELEMENTS
═══════════════════════════════════════════════════════════════════
• GREEN LINE → Bullish Supertrend (support)
• RED LINE → Bearish Supertrend (resistance)
• CYAN LINE → VWMA baseline
• RED ZONE → Overbought area
• GREEN ZONE → Oversold area
• GREEN CANDLES → Bullish trend active
• RED CANDLES → Bearish trend active
• BUY LABEL → Long entry signal
• SELL LABEL → Short entry signal
• R MARKER → Reversal signal
• X MARKER → Take profit hit
⚠️ IMPORTANT NOTES
═══════════════════════════════════════════════════════════════════
✓ NON-REPAINTING: All signals are confirmed on candle close
✓ BACKTESTING: Test on your specific market before live trading
✓ RISK MANAGEMENT: Use proper position sizing and stop losses
✓ MARKET CONDITIONS: Works best in trending and range-bound markets
✓ CONFLUENCE: Combine with other analysis for best results
⚡ Best Performance:
• Trending markets with clear momentum
• Moderate to high volatility environments
• 30-minute to 1-hour timeframes
• Liquid markets with tight spreads
⚠️ Avoid Using:
• During major news events (high slippage)
• In extremely choppy/sideways markets
• On illiquid assets with wide spreads
• Without proper risk management
📚 METHODOLOGY
═══════════════════════════════════════════════════════════════════
This indicator combines three proven technical analysis methods:
1. TREND FOLLOWING (Supertrend)
Captures major price movements and momentum
2. MEAN REVERSION (VWMA Zones)
Identifies extremes and potential reversals
3. NOISE FILTERING (Kalman)
Reduces false signals and improves accuracy
By integrating these approaches with volume weighting and adaptive
calculations, the Pro Scalper provides a comprehensive trading system
suitable for active traders and scalpers.
⚖️ DISCLAIMER
═══════════════════════════════════════════════════════════════════
This indicator is provided for educational and informational purposes
only. It does not constitute financial advice, and past performance
does not guarantee future results.
Trading carries substantial risk of loss and is not suitable for all
investors. Always:
• Do your own research and analysis
• Use proper risk management
• Never risk more than you can afford to lose
• Test thoroughly before live trading
• Consult a financial advisor if needed
The creator (Zakaria Safri) assumes no liability for trading losses
incurred using this indicator.
📞 ABOUT THE DEVELOPER
═══════════════════════════════════════════════════════════════════
Developer: Zakaria Safri
Specialization: Advanced algorithmic trading indicators
Focus: Noise reduction, signal filtering, and trend analysis
• Regular updates and improvements
• Community feedback integration
• Bug fixes and optimization
• Feature requests welcome
📋 VERSION INFO
═══════════════════════════════════════════════════════════════════
Version: 1.0
Created: 2024
License: Mozilla Public License 2.0
Author: Zakaria Safri
═══════════════════════════════════════════════════════════════════
Happy Trading! 📈
Developed with precision by Zakaria Safri
═══════════════════════════════════════════════════════════════════
Squeeze Momentum MACDSqueeze Momentum MACD
🧠 Description
Squeeze Momentum MACD combines the concept of market volatility compression (the “squeeze”) from Bollinger Bands (BB) and Keltner Channels (KC) with a MACD-style momentum oscillator to reveal potential breakout phases.
The indicator first calculates:
BB Width = Upper Band − Lower Band
KC Width = Upper Band − Lower Band
Then it computes their difference:
Δ = BB Width − KC Width
When Δ > 0 → BB width is greater than KC width → volatility is expanding → potential momentum breakout.
When Δ < 0 → BB is inside KC → volatility is compressing → potential squeeze phase before expansion.
This Δ value is then processed through a MACD-style calculation:
MACD Line = EMA(fast) − EMA(slow)
Signal Line = EMA(MACD, signal length)
Histogram = MACD − Signal
The result is a visual momentum oscillator that behaves like MACD but measures volatility expansion instead of price direction.
🔹 Features:
Dynamic 4-color MACD & Signal lines (positive/negative + rising/falling)
Optional display of raw BB & KC widths
Fully adjustable parameters for BB, KC, and MACD
Works on all timeframes and instruments
🔹 Ideal For:
Detecting market squeezes and breakout momentum
Timing entries before volatility expansion
Integrating volatility and momentum into a single framework
Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD)
Concept & Purpose
The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart.
Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption).
This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators.
In simple terms:
When MPD expands upward → buyer pressure dominates.
When MPD contracts downward → seller pressure dominates.
Calculation Overview
MPD uses a structural candle formula to compute directional pressure:
Body Ratio = (Close − Open) / (High − Low)
Wick Differential = (Lower Wick − Upper Wick) / (High − Low)
Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight)
Then it applies:
EMA smoothing (to stabilize short-term noise)
Standard deviation normalization (to maintain consistent scaling)
ATR projection (to adapt the signal visually to volatility)
This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart.
Customizable Inputs
Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes.
How to Use
The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator.
The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility.
The red line represents the ATR envelope, which defines the market’s expected volatility range.
MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope:
Above the ATR band → positive pressure and bullish bias.
Below the ATR band → negative pressure and bearish bias.
Hovering near the ATR band → neutral or indecisive conditions.
The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility.
Positive % = buying dominance.
Negative % = selling dominance.
Higher absolute values = stronger momentum compared to volatility.
To trade with MPD:
Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control.
Note transitions above or below the ATR level for early signs of momentum shifts.
Combine MPD signals with price structure, key levels, or volume for confirmation.
This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility.
Disclaimer
It introduces a novel structural–pressure approach to visualizing market dynamics.
For educational and analytical purposes only; this does not constitute financial advice.
Fisher Transform Trend Navigator [QuantAlgo]🟢 Overview
The Fisher Transform Trend Navigator applies a logarithmic transformation to normalize price data into a Gaussian distribution, then combines this with volatility-adaptive thresholds to create a trend detection system. This mathematical approach helps traders identify high-probability trend changes and reversal points while filtering market noise in the ever-changing volatility conditions.
🟢 How It Works
The indicator's foundation begins with price normalization, where recent price action is scaled to a bounded range between -1 and +1:
highestHigh = ta.highest(priceSource, fisherPeriod)
lowestLow = ta.lowest(priceSource, fisherPeriod)
value1 = highestHigh != lowestLow ? 2 * (priceSource - lowestLow) / (highestHigh - lowestLow) - 1 : 0
value1 := math.max(-0.999, math.min(0.999, value1))
This normalized value then passes through the Fisher Transform calculation, which applies a logarithmic function to convert the data into a Gaussian normal distribution that naturally amplifies price extremes and turning points:
fisherTransform = 0.5 * math.log((1 + value1) / (1 - value1))
smoothedFisher = ta.ema(fisherTransform, fisherSmoothing)
The smoothed Fisher signal is then integrated with an exponential moving average to create a hybrid trend line that balances statistical precision with price-following behavior:
baseTrend = ta.ema(close, basePeriod)
fisherAdjustment = smoothedFisher * fisherSensitivity * close
fisherTrend = baseTrend + fisherAdjustment
To filter out false signals and adapt to market conditions, the system calculates dynamic threshold bands using volatility measurements:
dynamicRange = ta.atr(volatilityPeriod)
threshold = dynamicRange * volatilityMultiplier
upperThreshold = fisherTrend + threshold
lowerThreshold = fisherTrend - threshold
When price momentum pushes through these thresholds, the trend line locks onto the new level and maintains direction until the opposite threshold is breached:
if upperThreshold < trendLine
trendLine := upperThreshold
if lowerThreshold > trendLine
trendLine := lowerThreshold
🟢 Signal Interpretation
Bullish Candles (Green): indicate normalized price distribution favoring bulls with sustained buying momentum = Long/Buy opportunities
Bearish Candles (Red): indicate normalized price distribution favoring bears with sustained selling pressure = Short/Sell opportunities
Upper Band Zone: Area above middle level indicating statistically elevated trend strength with potential overbought conditions approaching mean reversion zones
Lower Band Zone: Area below middle level indicating statistically depressed trend strength with potential oversold conditions approaching mean reversion zones
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant developments without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency and clarity
Configuration Presets: Three parameter sets available - Default (balanced settings), Scalping (faster response with higher sensitivity), and Swing Trading (slower response with enhanced smoothing)
Color Customization: Four color schemes including Classic, Aqua, Cosmic, and Custom options for personalized chart aesthetics
Regression Channel (ShareScope-style, parallel)What it does
Replicates ShareScope’s Trend of displayed data look: a single straight linear-regression line (dashed) across a chosen window with parallel, constant-width bands above and below, plus optional shading.
Use it to see the overall trend gradient for a period and a statistically sized channel based on the fit’s residual error.
How it works (math, short)
Computes an OLS regression once over the analysis window.
Residual standard error s is derived from SSE and degrees of freedom (n−2).
Band half-width is constant across the window:
Mean CI (narrower): half = z * s / √n
Prediction (wider): half = z * s * √(1 + 1/n)
Three straight, parallel lines are drawn from the regression endpoints; midline is dashed.
This is intentionally not a tapered CI (which widens at the ends). It matches the visual behaviour of ShareScope’s shaded trend line channel.
Inputs
Source – Price series (Close, High, Low, HL2, etc.).
Use last N bars / N (bars) – Rolling window length.
From / To (date mode) – Alternative fixed date window.
Confidence (%) – 90 / 95 / 99 / Custom (uses z≈t).
Custom Z (t) – Override the quantile if desired.
Prediction bands – Use wider prediction envelope instead of mean CI.
Shade region + colors / opacity / line width.
Usage
To mimic ShareScope exactly, pick the same date span (use date mode) and set Confidence 99%.
Choose Prediction OFF for a tighter “confidence” look; ON for a wider, more permissive channel.
If ShareScope used High as source, set Source = High here as well.
Notes & limitations
TradingView does not expose the visible viewport to Pine. The script cannot auto-read “displayed data.” Use last N bars or date range.
Bands are parallel by design. Prices may close outside; the channel does not bend.
Window capped at 5,000 bars for performance. No alerts are emitted.
Differences vs TV’s native tools
Linear Regression (drawing) – manual object; no statistical sizing or shading.
Linear Regression Channel (indicator) – uses price standard deviations around the regression; width is a user stdev multiple.
This script – uses residual error of the OLS fit and a z/t quantile to size a statistically meaningful parallel channel.
Changelog
r3.1 – Guard fix (no return at top level), minor refactor, stable line updates.
r3 – Switched to single-fit OLS with parallel constant-width bands (ShareScope look).
(Earlier experimental builds r1–r2.2 implemented rolling/tapered CI; superseded.)
Disclaimer: Educational use only. Not investment advice.
PSAR+EMA+Hull+BBDescription
This all-in-one indicator combines four proven tools:
Parabolic SAR (Everget) — trend direction and potential reversals.
Exponential Moving Averages (20/50/100/200) — customizable lengths, colors, and offsets.
Hull Suite (InSilico) — smooth trend detection with multiple variations (HMA, THMA, EHMA).
Bollinger Bands — volatility and dynamic support/resistance.
Features
Toggle each module on/off in settings.
Fully configurable inputs (lengths, colors, offsets, multipliers).
Optional PSAR labels, highlights, and state fill.
Hull can color candles, draw band fills, and pull from higher timeframes.
Bollinger Bands include multiple basis types, stdev multipliers, and fill transparency.
Built-in alerts: PSAR direction change, Hull trending up/down.
Category
Trend Analysis (with Volatility as secondary).
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview
The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis.
🟢 How It Works
The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor:
bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5
adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio
alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor))))
This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes:
var float adaptiveTrend = source
adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source)
finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter
ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods:
volatility = ta.atr(volatilityPeriod)
upperBound = bollingerTrendValue + (volatility * volatilityMultiplier)
lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier)
The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell).
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity
Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency
Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
RSI Crossover AlertRSI Crossover Alert Indicator - User Guide
The RSI Crossover Alert Indicator is a comprehensive technical analysis tool that detects multiple types of RSI crossovers and generates real-time alerts. It combines traditional RSI analysis with signal lines, divergence detection, and multi-level crossing alerts.
1. Multiple Crossover Detection
- RSI/Signal Line Cross: Signals a primary trend change.
- RSI/Second Signal Cross: Confirmation signals for stronger trends.
- Level Crossings: Crosses of Overbought 70, Oversold 30, and Midline 50.
- Divergence Detection: Hidden and regular divergences for reversal signals.
2. Alert Types
- Alert: RSI > Signal
Description: Bullish momentum is building.
Signal: Consider long positions.
- Alert: RSI < Signal
Description: Bearish momentum is building.
Signal: Consider short positions.
- Alert: RSI > 70
Description: Entering the overbought zone.
Signal: Prepare for a potential reversal.
- Alert: RSI < 30
Description: Entering the oversold zone.
Signal: Watch for a bounce opportunity.
- Alert: RSI crosses 50
Description: A shift in momentum.
Signal: Trend confirmation.
3. Visual Components
- Lines: RSI blue, Signal orange, Second Signal purple
- Histogram: Visualizes momentum by showing the difference between RSI and the Signal line.
- Background Zones: Red overbought, Green oversold
- Markers: Up/down triangles to indicate crossovers.
- Info Table: Real-time RSI values and status.
Strategy 1: Classic Crossover
- Entry Long: RSI crosses above the Signal Line AND RSI is below 50.
- Entry Short: RSI crosses below the Signal Line AND RSI is above 50.
- Take Profit: On the opposite signal.
- Stop Loss: At the recent swing high/low.
Strategy 2: Extreme Zone Reversal
- Entry Long: RSI is below 30 and crosses above the Signal Line.
- Entry Short: RSI is above 70 and crosses below the Signal Line.
- Risk Management: Higher win rate but fewer signals. Use a minimum 2:1 risk-reward ratio.
Strategy 3: Divergence Trading
- Setup: Enable divergence alerts and look for price/RSI divergence. Wait for an RSI crossover for confirmation.
- Entry: Enter on the crossover after the divergence appears. Place the stop loss beyond the starting point of the divergence.
Strategy 4: Multi-Timeframe Confirmation
1. Check the higher timeframe e.g. Daily to identify the main trend.
2. Use the current timeframe e.g. 4H/1H for your entry.
3. Only enter in the direction of the main trend.
4. Use the RSI crossover as the entry trigger.
Optimal Settings by Market
- Forex Major Pairs
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 70/30
- Crypto High Volatility
RSI Length: 10-12, Signal Length: 6-8, Overbought/Oversold: 75/25
- Stocks Trending
RSI Length: 14-21, Signal Length: 9-12, Overbought/Oversold: 70/30
- Commodities
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 80/20
Risk Management Rules
1. Position Sizing: Never risk more than 1-2% on a single trade. Reduce size in ranging markets.
2. Stop Loss Placement: Place stops beyond the recent swing high/low for crossovers. Using an ATR-based stop is also effective.
3. Profit Taking: Take partial profits at a 1:1 risk-reward ratio. Switch to a trailing stop after reaching 2:1.
1. Filtering Signals
- Combine with volume indicators.
- Confirm the trend on a higher timeframe.
- Wait for candlestick pattern confirmation.
2. Avoid Common Mistakes
- Don't trade every single crossover.
- Avoid taking signals against a strong trend.
- Do not ignore risk management.
3. Market Conditions
- Trending Market: Focus on midline 50 crosses.
- Ranging Market: Look for reversals from overbought/oversold levels.
- Volatile Market: Widen the overbought/oversold levels.
- If you get too many false signals:
Increase the signal line period, add other confirmation indicators, or use a higher timeframe.
- If you are missing major moves:
Decrease the RSI length, shorten the signal line period, or check your alert settings.
Recommended Combinations
1. RSI + MACD: For dual momentum confirmation.
2. RSI + Bollinger Bands: For volatility-adjusted signals.
3. RSI + Volume: To confirm the strength of a signal.
4. RSI + Moving Averages: To use as a trend filter.
This indicator provides a comprehensive RSI analysis. Success depends on proper configuration, risk management, and combining signals with the overall market context. Start with the default settings, then optimize based on your trading style and market conditions.
4H Bollinger Breakout StrategyThis strategy leverages Bollinger Bands on the 4-hour timeframe for long and short trades in trending or ranging markets. Entries trigger on BB breakouts with optional filters for volume, trend, and RSI. Exits occur on opposite BB crosses. Customizable for long-only, short-only, or indicator mode via code comments. Supports forex, stocks, or crypto with full equity allocation and 0.1% commission.
Length (Default: 20): Period for BB basis and std dev; shorter for sensitivity, longer for smoothing.
Basis MA Type (Default: SMA): Selects MA for middle band (SMA, EMA, etc.); EMA for faster response.
Source (Default: Close): Price input for calculations; use close for standard accuracy.
StdDev Multiplier (Default: 1.8): Band width control; higher for fewer signals, lower for more.
Offset (Default: 0): Shifts BB plots; typically unchanged.
Use Filters (Default: True): Applies volume, trend, RSI checks to filter signals.
Volume MA Length (Default: 20): For volume filter (long: >105% avg, short: >120%).
Trend MA Length (Default: 80): SMA for trend filter (long: above MA, short: below).
RSI Length (Default: 14): For short filter (entry if RSI <85).
Use Long/Short Signals (Defaults: True): Toggles directions; long entry on lower BB crossover, short on upper crossunder.
Visuals: BB plots (blue basis, red upper, green lower), orange trend MA, filled background.
Labels/Alerts: Green/red for long entry/exit, yellow/purple for short; alert conditions included.
Volatility-Adjusted Momentum Score (VAMS) [QuantAlgo]🟢 Overview
The Volatility-Adjusted Momentum Score (VAMS) measures price momentum relative to current volatility conditions, creating a normalized indicator that identifies significant directional moves while filtering out market noise. It divides annualized momentum by annualized volatility to produce scores that remain comparable across different market environments and asset classes.
The indicator displays a smoothed VAMS Z-Score line with adaptive standard deviation bands and an information table showing real-time metrics. This dual-purpose design enables traders and investors to identify strong trend continuation signals when momentum persistently exceeds normal levels, while also spotting potential mean reversion opportunities when readings reach statistical extremes.
🟢 How It Works
The indicator calculates annualized momentum using a simple moving average of logarithmic returns over a specified period, then measures annualized volatility through the standard deviation of those same returns over a longer timeframe. The raw VAMS score divides momentum by volatility, creating a risk-adjusted measure where high volatility reduces scores and low volatility amplifies them.
This raw VAMS value undergoes Z-Score normalization using rolling statistical parameters, converting absolute readings into standardized deviations that show how current conditions compare to recent history. The normalized Z-Score receives exponential moving average smoothing to create the final VAMS line, reducing false signals while preserving sensitivity to meaningful momentum changes.
The visualization includes dynamically calculated standard deviation bands that adjust to recent VAMS behavior, creating statistical reference zones. The information table provides real-time numerical values for VAMS Z-Score, underlying momentum percentages, and current volatility readings with trend indicators.
🟢 How to Use
1. VAMS Z-Score Bands and Signal Interpretation
Above Mean Line: Momentum exceeds historical averages adjusted for volatility, indicating bullish conditions suitable for trend following
Below Mean Line: Momentum falls below statistical norms, suggesting bearish conditions or downward pressure
Mean Line Crossovers: Primary transition signals between bullish and bearish momentum regimes
1 Standard Deviation Breaks: Strong momentum conditions indicating statistically significant directional moves worth following
2 Standard Deviation Extremes: Rare momentum readings that often signal either powerful breakouts or exhaustion points
2. Information Table and Market Context
Z-Score Values: Current VAMS reading displayed in standard deviations (σ), showing how far momentum deviates from its statistical norm
Momentum Percentage: Underlying annualized momentum displayed as percentage return, quantifying the directional strength
Volatility Context: Current annualized volatility levels help interpret whether VAMS readings occur in high or low volatility environments
Trend Indicators: Directional arrows and change values provide immediate feedback on momentum shifts and market transitions
3. Strategy Applications and Alert System
Trend Following: Use sustained readings beyond the mean line and 1σ band penetrations for directional trades, especially when VAMS maintains position in upper or lower statistical zones
Mean Reversion: Focus on 2σ extreme readings for contrarian opportunities, particularly effective in sideways markets where momentum tends to revert to statistical norms
Alert Notifications: Built-in alerts for mean crossovers (regime changes), 1σ breaks (strong signals), and 2σ touches (extreme conditions) help monitor multiple instruments for both continuation and reversal setups
Euclidean Range [InvestorUnknown]The Euclidean Range indicator visualizes price deviation from a moving average using a geometric concept Euclidean distance. It helps traders identify trend strength, volatility shifts, and potential overextensions in price behavior.
Euclidean Distance
Euclidean distance is a fundamental concept in geometry and machine learning. It measures the "straight-line distance" between two points in space. In time series analysis, it can be used to measure how far one sequence deviates from another over a fixed window.
euclidean_distance(src, ref, len) =>
var float sum_sq_diff = na
sum_sq_diff := 0.0
for i = 0 to len - 1
diff = src - ref
sum_sq_diff += diff * diff
math.sqrt(sum_sq_diff)
In this script, we calculate the Euclidean distance between the price (source) and a smoothed average (reference) over a user-defined window. This gives us a single scalar that reflects the overall divergence between price and trend.
How It Works
Moving Average Calculation: You can choose between SMA, EMA, or HMA as your reference line. This becomes the "baseline" against which the actual price is compared.
Distance Band Construction: The Euclidean distance between the price and the reference is calculated over the Window Length. This value is then added to and subtracted from the average to form dynamic upper and lower bands, visually framing the range of deviation.
Distance Ratios and Z-Scores: Two distance ratios are computed: dist_r = distance / price (sensitivity to volatility); dist_v = price / distance (sensitivity to compression or low-volatility states)
Both ratios are normalized using a Z-score to standardize their behavior and allow for easier interpretation across different assets and timeframes.
Z-Score Plots: Z_r (white line) highlights instances of high volatility or strong price deviation; Z_v (red line) highlights low volatility or compressed price ranges.
Background Highlighting (Optional): When Z_v is dominant and increasing, the background is colored using a gradient. This signals a possible build-up in low volatility, which may precede a breakout.
Use Cases
Detect volatile expansions and calm compression zones.
Identify mean reversion setups when price returns to the average.
Anticipate breakout conditions by observing rising Z_v values.
Use dynamic distance bands as adaptive support/resistance zones.
Notes
The indicator is best used with liquid assets and medium-to-long windows.
Background coloring helps visually filter for squeeze setups.
Disclaimer
This indicator is provided for speculative analysis and educational purposes only. It is not financial advice. Always backtest and evaluate in a simulated environment before live trading.
Commodity Trend Reactor [BigBeluga]
🔵 OVERVIEW
A dynamic trend-following oscillator built around the classic CCI, enhanced with intelligent price tracking and reversal signals.
Commodity Trend Reactor extends the traditional Commodity Channel Index (CCI) by integrating trend-trailing logic and reactive reversal markers. It visualizes trend direction using a trailing stop system and highlights potential exhaustion zones when CCI exceeds extreme thresholds. This dual-level system makes it ideal for both trend confirmation and mean-reversion alerts.
🔵 CONCEPTS
Based on the CCI (Commodity Channel Index) oscillator, which measures deviation from the average price.
Trend bias is determined by whether CCI is above or below user-defined thresholds.
Trailing price bands are used to lock in trend direction visually on the main chart.
Extreme values beyond ±200 are treated as potential reversal zones.
🔵 FEATURES\
CCI-Based Trend Shifts:
Triggers a bullish bias when CCI crosses above the upper threshold, and bearish when it crosses below the lower threshold.
Adaptive Trailing Stops:
In bullish mode, a trailing stop tracks the lowest price; in bearish mode, it tracks the highest.
Top & Bottom Markers:
When CCI surpasses +200 or drops below -200, it plots colored squares both on the oscillator and on price, marking potential reversal zones.
Background Highlights:
Each time a trend shift occurs, the background is softly colored (lime for bullish, orange for bearish) to highlight the change.
🔵 HOW TO USE
Use the oscillator to monitor when CCI crosses above or below threshold values to detect trend activation.
Enter trades in the direction of the trailing band once the trend bias is confirmed.
Watch for +200 and -200 square markers as warnings of potential mean reversals.
Use trailing stop areas as dynamic support/resistance to manage stop loss and exit strategies.
The background color changes offer clean confirmation of trend transitions on chart.
🔵 CONCLUSION
Commodity Trend Reactor transforms the simple CCI into a complete trend-reactive framework. With real-time trailing logic and clear reversal alerts, it serves both momentum traders and contrarian scalpers alike. Whether you’re trading breakouts or anticipating mean reversions, this indicator provides clarity and structure to your decision-making.
2-Day Volume Weighted Average Price (VWAP)This indicator extends TradingView’s built-in VWAP by calculating a volume-weighted average price over a continuous two-day window (yesterday + today), anchoring VWAP at the start of yesterday’s session and carrying it through to today’s close, but only plotting the segment that falls within the current trading session—yesterday’s data feeds into the calculation to ensure today’s VWAP reflects the prior session’s volume and price action, while the line drawn on your chart always begins at today’s session open.
Standard Deviation Bands: Optional ±1σ, ±2σ, and ±3σ envelopes, exactly as in the default VWAP, but based on the rolling two-day data.
Range Filter Strategy with ATR TP/SLHow This Strategy Works:
Range Filter:
Calculates a smoothed average (SMA) of price
Creates upper and lower bands based on standard deviation
When price crosses above upper band, it signals a potential uptrend
When price crosses below lower band, it signals a potential downtrend
ATR-Based Risk Management:
Uses Average True Range (ATR) to set dynamic take profit and stop loss levels
Take profit is set at entry price + (ATR × multiplier) for long positions
Stop loss is set at entry price - (ATR × multiplier) for long positions
The opposite applies for short positions
Input Parameters:
Adjustable range filter length and multiplier
Customizable ATR length and TP/SL multipliers
All parameters can be optimized in TradingView's strategy tester
You can adjust the input parameters to fit your trading style and the specific market you're trading. The ATR-based exits help adapt to current market volatility.
The Ultimate Buy and Sell Indicator: Unholy Grail Edition"You see, Watson, the market is not random—it simply whispers in a code too complex for the average trader. Lucky for you, I am not average."
They searched for the Holy Grail of trading for decades—promises, false prophets, and overpriced PDFs.
But they were all looking in the wrong place.
This isn’t a relic buried in the desert.
This is the Unholy Grail — a machine-forged fusion of logic, engineering, and tactical overkill .
Built by Sherlock Macgyver , this is not a mystical object. It’s a surveillance system for trend detection, signal validation, and precision entries .
⚠️ Important: This script draws its own candles.
To see it properly, disable regular candles by turning off "Body", "Wick" and "Border" colors.
🔧 What You’re Looking At
This overlay plots confirmed Buy/Sell signals , momentum-based “watch” zones , adaptive candle coloring , SuperTrend bias detection , dual Bollinger Bands , and a moving average ribbon .
It’s not “minimalist” —it’s comprehensive .
📍 Configuring the Tool: Follow the Breadcrumbs
Every setting includes a tooltip — read them . They're not filler. They explain exactly how each feature functions so you can dial this thing in like you're tuning a surveillance rig in a Cold War bunker .
If you skip them, you're walking blind in a minefield .
🕰️ Timeframes: The Signal Sweet Spot
Each asset has a tempo . You need to find the one where signals align with clarity —not chaos .
Start with 4H or 1H —work up or down from there.
Too many fakeouts? → Higher timeframe
Too slow? → Drop to 15m or 5m —but expect more noise and adjust settings accordingly.
The signals scale with time, but you must find the rhythm that best fits your asset—and your trading lifestyle .
♻️ RSI Cycle = Signal Sensitivity
This is the heart of the system . It controls how reactive the RSI engine is.
Adjust based on noise level and how often you can actually monitor your charts.
Short cycle (14–24): More signals, more speed, more noise
Longer cycle (36–64): Smoother entries, better for swing traders
Tip: If your signals feel too jittery, increase the cycle. If they lag too much, reduce it.
📉 SuperTrend: Your Trend Bias Compass
This isn’t your average SuperTrend. It adapts with RSI overlay logic and detects market “silence” via EMA compression— turning white right before the chaos . That said, you still control its aggression.
ATR Length = how many bars to average
ATR Factor = how tight or loose it hugs price
Lower = more sensitive (more trades, more noise)
Higher = confirmation only (fewer, but stronger signals)
Tweak until it feels like a sniper rifle.
No, you won’t get it perfect on the first try.
Yes, it’s worth it.
🛠️ Modular Signals: Why Things Fire (or Don’t)
Buy/Sell entries require conditions to align. The logic is modular, and that’s on purpose.
RSI signals only fire if RSI crosses its smoothed MA outside the dead zone and a “Watch” condition is active.
SuperTrend signals can be enabled to act on crossovers, optionally ignoring the Watch filter .
Watch conditions (colored squares) act as early recon and hint at possible upcoming trades.
Background color changes are “pre-signal warnings” and will repaint . Use them as leading signals, not gospel.
Want more trades? Loosen your filters .
Want sniper entries? Lock them down .
🌈 Candles and MAs: Visual Market Structure
Candles adapt in real-time to MA structure:
Green = bullish (above both fast/slow MAs)
Yellow = indecision (between)
Red = bearish (below both)
Buy/Sell signals override candles with bright orange and fuchsia —because subtlety doesn’t win wars .
You can also enable up to 8 customizable moving averages —great for confluence , trend confirmation , or just looking like a wizard .
🧠 Pro Usage Tips (TL;DR for Smart People):
Use tooltips in the settings menu —every toggle and slider is explained
Test timeframes until signal frequency and reliability match your goals
Adjust RSI cycle to reduce noise or speed up signals based on how frequently you trade
Tweak SuperTrend factor and ATR to fit volatility on your asset
Start with visual confirmation :
• Are watch signals lining up with trend zones?
• Are backgrounds firing before price moves?
• Are candle colors agreeing with signal direction?
📣 Alerts & Integration
Alerts are available for:
Buy/Sell entries (confirmed or advanced background)
Watch signals
Full band agreement (both Bollinger bands bullish or bearish)
Use these with webhook systems , bots , or your own trade journals .
Created by Sherlock Macgyver
Because sometimes the best trade…
is knowing exactly when not to take one.
Volumetric Entropy IndexVolumetric Entropy Index (VEI)
A volume-based drift analyzer that captures directional pressure, trend agreement, and entropy structure using smoothed volume flows.
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🧠 What It Does:
• Volume Drift EMAs : Shows buy/sell pressure momentum with adaptive smoothing.
• Dynamic Bands : Bollinger-style volatility wrappers react to expanding/contracting drift.
• Baseline Envelope : Clean structural white rails for mean-reversion zones or trend momentum.
• Background Shading : Highlights when both sides (up & down drift) are in agreement — green for bullish, red for bearish.
• Alerts Included : Drift alignment, crossover events, net drift shifts, and strength spikes.
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🔍 What Makes It Different:
• Most volume indicators rely on bars, oscillators, or OBV-style accumulation — this doesn’t.
• It compares directional EMAs of raw volume to isolate real-time bias and acceleration.
• It visualizes the twisting tension between volume forces — not just price reaction.
• Designed to show when volatility is building inside the volume mechanics before price follows.
• Modular — every element is optional, so you can run it lean or fully loaded.
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📊 How to Use It:
• Drift EMAs : Watch for one side consistently dominating — sharp spikes often precede breakouts.
• Bands : When they tighten and start expanding, it often signals directional momentum forming.
• Envelope Lines : Use as high-probability reversal or continuation zones. Bands crossing envelopes = potential thrust.
• Background Color : Green/red backgrounds confirm volume agreement. Can be used as a filter for other signals.
• Net Drift : Optional smoothed oscillator showing the difference between bullish and bearish volume pressure. Crosses above or below zero signal directional bias shifts.
• Drift Strength : Measures pressure buildup — spikes often correlate with large moves.
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⚙️ Full Customization:
• Turn every layer on/off independently
• Modify all colors, transparencies, and line widths
• Adjust band width multiplier and envelope offset (%)
• Toggle bonus plots like drift strength and net baseline
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🧪 Experimental Tools:
• Smoothed Net Drift trace
• Drift Strength signal
• Envelope lines and dynamic entropy bands with adjustable math
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Built for signal refinement. Made to expose directional imbalance before the herd sees it.
Created by @Sherlock_Macgyver
