Goldilocks Pivot FractalsGOLDILOCKS PIVOT FRACTALS - DESCRIPTION
Overview
Goldilocks Pivot Fractals identifies swing highs and lows using fractal pattern recognition with professional visual presentation. This indicator marks potential reversal points where price creates distinct peaks and valleys - perfect pivot points for support, resistance, and market structure analysis.
The "Goldilocks" name reflects the perfectly balanced visual presentation: not too cluttered, not too plain, just right for professional traders. Unlike standard fractal indicators, this edition features fully customizable Buy/Sell labels with tick-based positioning, independent toggle controls, and a high-contrast color scheme optimized for both dark and light chart themes.
What Makes It Unique:
- Professional label system with full customization (colors, sizes, tick-based offsets)
- Toggle labels and arrow shapes independently
- High-contrast default colors (teal/maroon) optimized for maximum visibility
- Clean, trader-friendly interface with intuitive settings
- Works flawlessly on all timeframes and instruments
How to Use
PERIOD ADJUSTMENT & ADJUSTING SENSITIVITY
The Period(s) setting controls how many signals you see:
• Period = 2 (default): Shows more signals, catches smaller price swings - best for day trading and scalping
• Period = 3-4: Shows medium amount of signals, filters out tiny moves - good for swing trading (holding days to weeks)
• Period = 5 or higher: Shows fewer signals, only the biggest turning points - best for long-term position trading
- Simple rule: Lower number = more signals. Higher number = fewer, but stronger signals.
SIGNALS
🟢 "BUY Label" (Down Fractal)
- Marks swing lows and potential support zones
- Look for price bouncing up after the fractal forms
- Use for identifying pullback entry points in uptrends
- Place stops below recent BUY fractals
🔴 "SELL Label" (Up Fractal)
- Marks swing highs and potential resistance zones
- Look for price rejecting down after the fractal forms
- Use for identifying profit targets or short entries
- Place stops above recent SELL fractals
REPAINTING BEHAVIOR
⚠️ This indicator repaints by design. Fractals require N bars on both sides to confirm, so they appear N bars after the actual pivot point. This is normal and ensures accurate pivot identification. Wait for complete confirmation before trading.
TRADING APPLICATIONS
1. Support/Resistance: Mark key price levels for entries and exits
2. Market Structure: higher BUY fractals = uptrend, lower SELL fractals = downtrend
3. Stop Placement: Use recent fractals as logical stop-loss levels
4. Breakout Trading: Monitor price breaking above/below fractal levels
5. Trend Following: Enter on pullbacks to BUY fractals in uptrends
6. Swing Trading: Identify major swing points for position entries
CUSTOMIZATION OPTIONS
• Show BUY/SELL Labels**: Toggle professional text labels on/off
• Show Shapes: Toggle arrow shapes independently
• Offset (ticks): Adjust label distance from price bars for perfect positioning
• Colors: Customize backgrounds (default: teal/maroon) and text (default: white/yellow)
• Label Size: Choose from tiny, small, normal, large, or huge
The high-contrast default colors provide excellent visibility without adjustment, but full customization is available to match any chart theme.
Key Settings
Periods (n) (default: 2): Number of bars on each side of pivot. Lower = more signals, Higher = fewer, stronger signals
Show BUY/SELL Labels (default: ON): Display professional text labels
Show Shapes (default: ON): Display arrow shapes
BUY offset (ticks) (default: 8): Distance BUY labels appear below lows
SELL offset (ticks) (default: 8): Distance SELL labels appear above highs
Colors: Full customization - defaults optimized for visibility
Label size (default: normal): Visual prominence control
Key Features
✅ Professional pivot fractal detection
✅ Fully customizable Buy/Sell labels
✅ Independent toggle for labels and shapes
✅ Tick-based offset positioning
✅ High-contrast color scheme
✅ Works on all timeframes and instruments
✅ Clean, intuitive interface
✅ Adjustable sensitivity
✅ Perfect for support/resistance identification
✅ Ideal for market structure analysis
M-oscillator
SMI Trigger SystemSMI TRIGGER SYSTEM - DESCRIPTION
Overview
SMI Trigger System is a momentum oscillator that identifies trend changes and reversals using the Smoothed Stochastic Momentum Index (SMI). Features a color-changing line (green = bullish, red = bearish), cloud shading for momentum zones, and triangle markers that appear exactly when momentum flips.
What Makes It Unique:
Real-time color-changing momentum line
Cloud shading split at zero line
Triangle triggers at exact momentum flip points
Overbought/oversold limit lines
Built-in alerts for all key signals
Fully customizable appearance
Works on all timeframes
How to Use
THE DISPLAY
Green line/cloud: Bullish momentum
Red line/cloud: Bearish momentum
Above zero: Bulls in control
Below zero: Bears in control
Upper limit (+40): Overbought
Lower limit (-40): Oversold
SIGNALS
🟢 Green Triangle (▲) - Momentum flipping bullish. Buy signal, most powerful below zero.
🔴 Red Triangle (▼) - Momentum flipping bearish. Sell signal, most powerful above zero.
TRADING STRATEGIES
1. Trend Following
In uptrends: Only take green triangles, ignore red
In downtrends: Only take red triangles, ignore green
Use higher timeframe for trend, lower for entries
Example: Daily uptrend → trade green triangles on 1H chart
2. Limit Reversals
Red triangle at upper limit (+40) = strong reversal signal, go short
Green triangle at lower limit (-40) = strong reversal signal, go long
Wait for triangle AND price confirmation
Most reliable on 4H/Daily timeframes
3. Zero Line Trading
SMI crosses above zero → bullish bias, take green triangles
SMI crosses below zero → bearish bias, take red triangles
Zero acts as momentum baseline
4. Divergence Setups
Price higher high + SMI lower high = bearish divergence → take next red triangle
Price lower low + SMI higher low = bullish divergence → take next green triangle
Most powerful at overbought/oversold limits
ENTRIES & EXITS
Enter: On triangle appearance
Stop: Beyond recent opposite-color triangle
Target: Limit levels or opposite triangle
Add: Additional same-color triangles in strong trends
TIMEFRAME GUIDE
Scalping (1-5m): Lower %K to 3-4, take all trend-aligned triangles
Day trading (15-60m): Default settings (5/3), focus on limit reversals
Swing trading (4H-Daily): Higher %K to 7-10, trade only extreme readings
ADJUSTING SENSITIVITY
SMI %K Length (default: 5):
Lower (3-4) = More signals, faster - good for scalping
Higher (7-10) = Fewer signals, stronger - good for swing trading
SMI %D Length (default: 3):
Lower (1-2) = More responsive
Higher (5-7) = Smoother
ALERTS
Built-in alerts for:
Triangle appears (momentum flips)
SMI crosses zero (trend change)
SMI crosses limits (overbought/oversold)
Enable in settings, configure in TradingView alert dialog.
CUSTOMIZATION
Toggle cloud/triangles on/off
Adjust triangle size and positioning
Customize all colors
Triangle label cap prevents clutter
Key Settings
SMI %K Length (default: 5): Controls sensitivity and signal frequency
SMI %D Length (default: 3): Controls smoothing
SMI Limit (default: 40): Overbought/oversold threshold
Show SMI Cloud (default: ON): Cloud shading
Show SMI Flip Triangles (default: ON): Trigger markers
Triangle Size/Offset: Appearance customization
Enable Alerts (default: ON): Alert notifications
Key Features
✅ Color-changing momentum line
✅ Cloud shading for momentum zones
✅ Triangle triggers at exact flips
✅ Overbought/oversold limits
✅ Built-in alert system
✅ Fully customizable
✅ All timeframes
✅ Adjustable sensitivity
NPR21
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView.
Market Entropy [Alpha Extract]A sophisticated information theory-based market analysis system that measures price randomness and structural order using Shannon entropy calculations across price, returns, and volume distributions. Utilizing adaptive percentile-based thresholds and multi-timeframe confirmation, this indicator delivers institutional-grade regime classification distinguishing between structured trending conditions and chaotic ranging environments. The system's composite entropy framework combined with dynamic gradient visualization and MTF alignment validation provides comprehensive market state assessment for optimal strategy selection and risk management.
🔶 Advanced Shannon Entropy Engine
Implements pure information theory methodology using histogram distribution analysis with configurable bin counts to calculate normalized entropy values for price, returns, and volume metrics. The system constructs probability distributions from rolling windows, applies logarithmic entropy calculations, and normalizes against theoretical maximum entropy to produce 0-1 bounded measurements of market randomness and predictability.
float entropy = 0.0
float total = float(len)
for i = 0 to bins - 1
float count = array.get(bin_counts, i)
if count > 0
float prob = count / total
entropy -= prob * math.log(prob) / math.log(2)
float max_entropy = math.log(bins) / math.log(2)
result := entropy / max_entropy
🔶 Adaptive Percentile Threshold System
Features intelligent threshold determination using rolling percentile calculations over configurable calibration periods to establish structure and chaos zones that adapt to changing market characteristics. The system calculates lower percentile for structure threshold (ordered markets) and upper percentile for chaos threshold (random markets), enabling regime classification that adjusts automatically to market evolution.
🔶 Multi-Timeframe Alignment Framework
Implements comprehensive MTF entropy analysis retrieving composite entropy from three configurable higher timeframes with alignment validation logic. The system calculates divergence between current timeframe entropy and higher timeframe values, generating confirmation signals only when all timeframes exhibit entropy agreement within tolerance bands for enhanced signal reliability.
🔶 Three-Regime Classification Engine
Provides sophisticated market state determination classifying conditions as structure (entropy below lower threshold), chaos (entropy above upper threshold), or neutral (entropy between thresholds) with regime strength measurement. The system tracks regime transitions and calculates conviction scores based on distance from thresholds, enabling nuanced assessment of market order versus randomness.
🔶 Composite Entropy Architecture
Combines three distinct entropy measurements weighted by relevance to create unified market randomness metric with exponential smoothing for stability. The system applies 40% weight to price entropy (distribution shape), 35% to return entropy (movement patterns), and 25% to volume entropy (participation randomness), capturing comprehensive market microstructure information.
🔶 Dynamic Gradient Visualization System
Features advanced color blending engine that transitions between primary and secondary colors based on entropy momentum intensity with glow effects for conviction emphasis. The system calculates entropy rate of change, normalizes against recent extremes, and applies smooth color interpolation from secondary to primary hues as momentum intensifies, creating intuitive visual representation of regime strength.
🔶 Intelligent Zone Fill Architecture
Implements multi-layer gradient fills within structure and chaos zones that intensify as entropy moves deeper into extremes, providing immediate visual feedback on regime conviction. The system creates three-tier gradient levels at 33%, 66%, and 100% penetration into zones with progressively lower transparency, emphasizing extreme entropy conditions requiring attention.
🔶 Momentum-Based Divergence Detection
Generates entry signals when entropy crosses below bull divergence level or above bear divergence level, identifying potential regime transitions before price confirmation. The system monitors entropy momentum direction during threshold crossings and validates with MTF alignment, producing high-probability reversal signals at entropy extremes.
🔶 Normalized Display Framework
Provides 0-100 scaled visualization using adaptive min-max normalization calculated from percentile analysis, ensuring consistent visual interpretation across different market conditions and instruments. The system transforms raw composite entropy into normalized space with dynamic thresholds, enabling cross-market and cross-timeframe entropy comparison.
🔶 Regime Strength Measurement
Calculates conviction scores measuring depth of entropy penetration into structure or chaos zones relative to historical ranges, quantifying how definitively current conditions favor trending versus ranging strategies. The system produces 0-1 strength values that modulate visual intensity and can inform position sizing or strategy allocation decisions.
🔶 Performance Optimization Framework
Utilizes efficient array operations with optimized histogram calculations and configurable lookback limits to balance accuracy with computational efficiency. The system includes intelligent caching of percentile calculations and streamlined probability summations for smooth real-time entropy updates across extended historical periods.
🔶 Why Choose Market Entropy ?
This indicator delivers sophisticated market regime analysis through pure information theory methodology measuring actual randomness versus structure in price behavior. Unlike traditional volatility or trend indicators that measure price movement characteristics, Market Entropy quantifies the fundamental predictability of market conditions using Shannon entropy calculations. The system's composite approach combining price, return, and volume distributions with adaptive thresholds, MTF confirmation, and gradient visualization makes it essential for traders seeking objective regime classification to optimize strategy selection. Low entropy (structure zone) indicates ordered, trending conditions favorable for directional strategies, while high entropy (chaos zone) signals random, ranging markets better suited for mean reversion or reduced exposure. The indicator excels at identifying regime transitions before they become obvious in price action across cryptocurrency, forex, and equity markets.
IronRod Trigger SystemIRONROD TRIGGER SYSTEM
DESCRIPTION
IronRod Trigger System is a momentum oscillator based on the Stochastic Momentum Index (SMI) that identifies trend changes, momentum shifts, and range-bound "chop" zones. Features color-changing SMI lines, histogram columns showing momentum strength, and a visual chop zone that highlights when to trade versus when to stay on the sidelines.
The system combines momentum direction (green/red lines), momentum strength (histogram columns), and market context (chop zone cloud) into one clean visual package. The dynamic zero line changes color to signal trade conditions (cyan) versus hold conditions (orange).
What Makes It Unique:
Dual color-changing lines (SMI and AvgSMI) show momentum direction
Histogram columns display momentum strength
Chop zone cloud identifies low-momentum periods
Dynamic zero line (cyan = trade, orange = hold)
Three-color histogram (green = strong up, red = strong down, gray = weak)
Adjustable chop zone threshold
How to Use
THE DISPLAY
Lines:
Green = bullish momentum (rising)
Red = bearish momentum (falling)
Gray = neutral/sideways
Histogram Columns:
Green = strong bullish momentum
Red = strong bearish momentum
Gray = weak/choppy momentum
Zero Line:
Cyan (blue) = trade zone - momentum is directional
Orange = chop zone - momentum is weak, avoid trading
Chop Zone Cloud:
Gray shaded area = range where momentum is indecisive (±30 default)
TRADING STRATEGIES
1. Chop Zone Trading
Trade: Only when SMI is outside gray cloud AND zero line is cyan
Avoid: When SMI is inside cloud OR zero line is orange
Long: Green line appears above chop zone
Short: Red line appears below chop zone
This is the key feature - dramatically reduces whipsaws
2. Zero Line Crosses
Buy: SMI crosses above zero with cyan zero line
Sell: SMI crosses below zero with cyan zero line
Strongest signals when AvgSMI follows SMI across zero
Ignore crosses when zero line is orange (choppy)
3. Histogram Strength
Strong trend: Multiple consecutive green/red columns
Momentum building: Columns getting taller
Momentum fading: Columns turning gray = exit warning
Reversal signal: Gray columns after strong trend
4. Divergence Trading
Bearish divergence: Price higher high, SMI lower high → take red line signal
Bullish divergence: Price lower low, SMI higher low → take green line signal
Most powerful outside chop zone
ENTRIES & EXITS
Entries:
SMI line turns green outside chop zone (long)
SMI line turns red outside chop zone (short)
SMI crosses zero with cyan zero line
Exits:
SMI line changes color
SMI enters chop zone (orange zero line)
Histogram turns gray
Stops:
Below recent swing low (longs)
Above recent swing high (shorts)
ADJUSTING SETTINGS
Chop Zone (±) (default: 30):
Lower (15-25) = More trades, more whipsaws
Higher (35-50) = Fewer trades, higher quality
Adjust based on instrument volatility
Percent K Length (default: 5):
Lower (3-4) = More sensitive, faster signals - good for scalping
Higher (7-10) = Less sensitive, smoother - good for swing trading
Percent D Length (default: 4): Controls smoothing
SMI Bar Buffer (default: 4): Histogram color sensitivity
TIMEFRAME GUIDE
Scalping (1-5m): K=3, watch histogram color flips
Day trading (15-60m): Default settings, focus on zero crosses outside chop
Swing trading (4H-Daily): K=7-10, trade only strong trends outside chop
Key Settings
Percent K Length (default: 5): Lookback period - controls sensitivity
Percent D Length (default: 4): Smoothing period
Chop Zone (±) (default: 30): Range-bound zone threshold
SMI Bar Buffer (default: 4): Histogram color change sensitivity
Histogram Width (default: 1): Column thickness
Key Features
✅ Dual color-changing momentum lines
✅ Histogram columns show strength
✅ Chop zone cloud filters bad trades
✅ Dynamic zero line color
✅ Three-color histogram
✅ Adjustable chop threshold
✅ All timeframes
✅ Reduces whipsaws
MTG v2MTG v2 is a complete trend-following trading system that combines:
PSAR (Parabolic SAR) - Trend direction
200 EMA - Trend direction
EMAs (5, 13, 50) - Momentum confirmation
AMA (Adaptive Moving Average) - Intelligent exits
Smart Filters - Volume, ATR, choppy market detection
Purpose: Catch strong trends early and ride them for maximum profit.
CSA Infinity BridgeCSA Infinity Bridge - 14-Indicator Consensus Dashboard
Description
- CSA Infinity Bridge is a proprietary multi-indicator consensus system that analyzes 14 technical indicators simultaneously and displays their collective agreement in a real-time dashboard. The indicator provides clear LONG, SHORT, or NEUTRAL signals based on mathematical consensus, eliminating subjective interpretation.
Core Innovation
- Unlike single indicators requiring interpretation, this tool synthesizes signals from Heikin Ashi, SuperTrend, Momentum, CCI, MFI, DMI, CMO, RSI+TTM, Zero-Lag MACD, ROC, SMA50, and specialized combinations into a unified market state classification.
Key Features
- 14 independent technical indicators analyzed per bar
- Real-time consensus dashboard with color-coded Bull/Bear readings
- 5-tier market state classification (Bullish, Trending ↑, Neutral, Chop, Trending ↓, Bearish)
- TOTAL column displays agreement count (out of 14) showing conviction level
- STATE column provides clear LONG/SHORT/NEUTRAL recommendations
- Built-in alerts for strong consensus (11+) and state changes
- Customizable dashboard size (Tiny to Huge)
- Optional dashboard placement (Top Right, Bottom Right, Bottom Center, Top Center)
What Makes It Unique
- The consensus engine quantifies market conviction with a simple number: when 11+ indicators agree, high-probability setups appear. When agreement drops below 8, the system warns to reduce exposure or stay flat. This creates a rules-based framework eliminating emotional trading decisions. The flexible dashboard positioning allows seamless integration into any chart layout without obstructing price action.
Ideal For
- Day traders and scalpers on futures markets (MNQ, MES, MYM, MGC, MCL) who need objective signals based on multi-indicator confirmation. Works on any instrument and timeframe, optimized for 1-5 minute scalping.
How to Use
Setup:
- Add indicator to chart and customize dashboard size and position. Enable alerts for "Strong Bullish", "Strong Bearish", "LONG Signal", and "SHORT Signal".
Dashboard Columns:
- Individual cells show Bull/Bear for each of 14 indicators
- TREND shows market state (Bullish/Trending/Neutral/Chop)
- STATE shows trade recommendation (LONG/SHORT/NEUTRAL)
- TOTAL shows agreement count with color coding (green 10+, orange 7-9, gray <7)
Signal Interpretation:
- 11-14 Agreement: High-probability setups, use full position size
- 8-10 Agreement: Medium probability, use 50-75% size
- 6-7 Agreement: Low probability, scalp only or avoid
- 5 Agreement: Chop zone, stay flat
Entry Strategy:
- Enter LONG when TOTAL reaches 11+ with STATE showing LONG. Enter SHORT when TOTAL reaches 11+ with STATE showing SHORT. Use stops 10-15 ticks beyond recent swing points.
Exit Strategy:
- Exit when TOTAL drops to 7 or below, or when STATE changes to opposite direction. Take partial profits at 2R, trail remainder.
Risk Management:
- Position sizing: 100% at 12-14 agreement, 75% at 10-11, 50% at 8-9, avoid below 8. Never risk more than 1% per trade.
Best Timeframes:
- 1-min (scalping), 3-min (quick day trades), 5-min (standard day trading), 15-min (swing entries).
Harmonic Liquidity Waves [JOAT]Harmonic Liquidity Waves
Overview
Harmonic Liquidity Waves is an open-source oscillator indicator that combines multiple volume-based analysis techniques into a unified liquidity flow framework. It integrates VWAP calculations, Chaikin Money Flow (CMF), Money Flow Index (MFI), and Klinger Volume Oscillator (KVO) with custom harmonic wave calculations to provide a comprehensive view of volume dynamics and money flow.
What This Indicator Does
The indicator calculates and displays:
Liquidity Flow - Volume-weighted price movement accumulated over a lookback period
Harmonic Wave - Multi-depth smoothed oscillator derived from liquidity flow
Chaikin Money Flow (CMF) - Classic accumulation/distribution indicator
Money Flow Index (MFI) - Volume-weighted RSI showing buying/selling pressure
Klinger Volume Oscillator (KVO) - Trend-volume relationship indicator
Wave Interference - Combined constructive/destructive wave patterns
Volume Profile POC - Point of Control from simplified volume distribution
How It Works
The core liquidity flow calculation tracks volume-weighted price changes:
calculateLiquidityFlow(series float vol, series float price, simple int period) =>
float priceChange = ta.change(price)
float volumeFlow = vol * math.sign(priceChange)
// Accumulated over period using buffer array
float avgFlow = flowSum / period
avgFlow
The harmonic oscillator applies multi-depth smoothing:
harmonicOscillator(series float flow, simple int depth, simple int period) =>
float harmonic = 0.0
for i = 1 to depth
float wave = ta.ema(flow, period * i) / i
harmonic += wave
harmonic / depth
CMF measures accumulation/distribution using the Money Flow Multiplier:
float mfm = ((close - low) - (high - close)) / (high - low)
float mfv = mfm * vol
float cmf = ta.sum(mfv, period) / ta.sum(vol, period) * 100
Signal Generation
Liquidity shift signals occur when:
Bullish Shift: Smoothed wave crosses above signal line
Bearish Shift: Smoothed wave crosses below signal line
Strong signals require volume indicator confirmation:
Strong Bull: Bullish shift + CMF > 0 + MFI > 50 + KVO > 0
Strong Bear: Bearish shift + CMF < 0 + MFI < 50 + KVO < 0
Divergence detection compares price pivots with liquidity wave pivots to identify potential reversals.
Dashboard Panel (Bottom-Right)
Wave Strength - Normalized wave magnitude
Volume Pressure - Current volume vs average percentage
Flow Direction - BUYING or SELLING based on wave sign
Histogram - Wave minus signal line value
CMF - Chaikin Money Flow reading
MFI - Money Flow Index value (0-100)
KVO - Klinger oscillator value
Vol Confluence - Combined volume indicator score
Signal - Current actionable status
Visual Elements
Liquidity Wave - Main oscillator line
Wave Signal - Smoothed signal line for crossover detection
Wave Histogram - Difference between wave and signal
Wave Interference - Area plot showing combined wave patterns
CMF/KVO/MFI Lines - Individual volume indicator plots
Divergence Labels - BULL DIV / BEAR DIV markers
Shift Markers - Triangles for basic shifts, labels for strong shifts
Input Parameters
Wave Period (default: 21) - Base period for liquidity calculations
Volume Weight (default: 1.5) - Multiplier for volume emphasis
Harmonic Depth (default: 3) - Number of smoothing layers
Smoothing (default: 3) - Final wave smoothing period
Suggested Use Cases
Identify accumulation/distribution phases using CMF and wave direction
Confirm momentum with MFI overbought/oversold readings
Watch for divergences between price and liquidity flow
Use strong signals when multiple volume indicators align
Timeframe Recommendations
Best on 15m to Daily charts. Volume-based indicators require sufficient trading activity for meaningful readings.
Limitations
Volume data quality varies by exchange and instrument
Divergence detection uses pivot-based lookback and may lag
Volume Profile POC is simplified and not a full profile analysis
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
CSA Infinity BridgeCSA Infinity Bridge - Major Update: Full Transparency + Stricter Consensus
Update Notes (December 29, 2025):
- Big improvements based on real-user feedback!
- This version eliminates the confusion that sometimes occurred when the dashboard showed near-unanimous agreement (like 13/14) but one indicator was silently disagreeing.
Key Changes:
- All 14 indicators are now fully visible in the dashboard. Added a dedicated "TTM" column for the standalone TTM Wave (previously hidden). No more guessing which indicator is the holdout—you’ll see every single Bull/Bear vote clearly.
- Stricter consensus thresholds for higher-conviction signals:
- Strong Bullish/Bearish now requires 12+ out of 14 (previously 11+)
- Trending ↑/↓ requires 9+ out of 14 (previously 8+)
- This reduces whipsaws and makes LONG/SHORT signals more reliable, especially for novice traders.
Keeps the popular OBV replacement (volume confirmation instead of basic candle color).
- Perfect for anyone who wants a clean, trustworthy consensus dashboard without hidden surprises. Ideal for futures, stocks, crypto—any market with volume.
- Test it, compare it to the previous version, and let me know what you think!
Quality-Controlled Trend Strategy v2 (Expectancy Focused)This script focuses on quality control rather than curve-fitting.
No repainting, no intrabar tricks, no fake equity curves.
It uses confirmed-bar entries, ATR-based risk, and clean trend logic so backtests reflect what could actually be traded live.
If you publish scripts, this is the minimum structure worth sharing.
Why this script exists
TradingView’s public scripts are flooded with:
repainting indicators
no stop-loss logic
curve-fit entries that collapse live
strategies that look good only in hindsight
This script is intentionally boring but honest.
No repainting.
No intrabar tricks.
No fake equity curves
The goal is quality control, not hype.
What this strategy enforces
✔ Confirmed bars only
✔ Single source of truth for indicators
✔ Fixed risk structure
✔ No signal repainting
✔ Clean exits with unique IDs
✔ Works on any liquid market
Trading Logic (simple & auditable)
Trend filter
EMA 50 vs EMA 200
Entry
Pullback to EMA 50
RSI confirms momentum (not oversold/overbought)
Risk
ATR-based stop
Fixed R:R
One position at a time
This is the minimum bar for a strategy to be considered publish-worthy.
Why this helps TradingView quality
Most low-value scripts fail because they:
hide repainting logic
skip exits entirely
use inconsistent calculations
rely on hindsight candles
This strategy forces discipline:
every signal is confirmed
every trade has defined risk
behavior is repeatable across symbols & timeframes
If more scripts followed this baseline, TradingView’s public library would be far more usable.
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**.
---
## 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.
---
## 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.
---
## 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.
---
## 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
---
## 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)
---
## 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.
DCA + VA (Value Averaging) | UA versionDCA + VA (Value Averaging) | UA version
DCA + VA is a practical portfolio simulator for TradingView that compares two long-term investing approaches on any symbol:
• DCA (Dollar-Cost Averaging) — invest a fixed amount on a fixed schedule.
• VA (Value Averaging) — invest (and optionally sell) to keep the invested part of the portfolio close to a target growth path.
The indicator is plotted in a separate lower pane and is designed for realistic capital efficiency analysis, including the effect of cash sitting idle (“cash drag”).
What you see on the chart
• Two thick yellow lines
— DCA line: portfolio value under classic DCA
— VA line: portfolio value under Value Averaging
• Trade dots
— Small green dots : buys
— Small red dots : sells (VA only, if enabled)
• UA table + right-side labels
— key portfolio metrics for both strategies
Core assumptions
• Trades are executed at bar close ( close )
• Dividends and broker commissions are ignored (for now)
• Optional tax logic is available for VA sells: tax is applied to realized profit using average cost basis
Line mode
• Капітал+Кеш (default): shows total portfolio value = holdings + cash (honest “cash drag”)
• Лише капітал : shows holdings value only (invested part)
DCA logic (classic)
Start from Start date .
On each scheduled period ( Week / Month / Half-year / Year ) the script:
• adds the deposit amount to cash
• buys the asset for that amount (if cash is available)
VA logic (Value Averaging)
VA maintains a target value for the invested holdings (asset value only, cash not included ).
On each VA step:
Regular deposit is added to VA cash
Target is updated by period growth g (derived from annual CAGR and selected frequency)
If holdings value is below target → buy using cash (optionally add extra if enabled)
If holdings value is above target and selling is enabled → sell down to target (cash increases; optional profit tax applies)
Target update formula:
Target = Target × (1 + g) + Regular deposit
Optional controls
• Sell excess ( vaSellExcess ): allow sells when above target
• Add extra on drawdowns ( vaAddExtra ): allow additional contributions when cash isn’t enough
• Max extra per period ( vaMaxExtra ): cap extra contributions ( 0 = unlimited )
• Tax on sells ( vaUseTax / vaTaxRate ): apply tax to realized profit (average cost basis)
Table metrics (UA)
For both DCA and VA:
• Накопичено — total contributed cash
• Інвестовано — current invested cost basis
• Кеш — cash balance
• Капітал — portfolio value (based on selected line mode)
• Прибуток % — ROI in percent
• CAGR стратегії — annualized return based on elapsed time
Best use (recommended settings)
• Best timeframe: 1W
Weekly candles make long-term simulations cleaner and more realistic: less noise, fewer “micro” fluctuations, and more stable periodic triggers for DCA/VA steps.
• Recommended workflow:
Set chart timeframe to 1W
Choose deposit frequency (usually Тиждень or Місяць )
Start with Капітал+Кеш to see true cash drag
Compare DCA vs VA using Прибуток % and CAGR (not only absolute $)
• How to interpret results:
— If VA has higher capital but lower ROI %, it usually means you contributed more (extra funding enabled).
— If VA sells rarely, your target path may be aggressive (high CAGR + large deposits), so holdings don’t exceed the target often.
Notes
• If VA shows higher capital but lower profit % , it usually means more total contributions (extra funding enabled).
• Sells can be rare if the target path grows aggressively (high CAGR + large deposits).
SCR Signals(개요) 스토캐스틱, CCI, RSI를 결합한 지표입니다. 편의상 SCR이라고 명명할게요
* 블로거 'SOXL연구원님의 SCR을 지표화했습니다.
(지표설명)
1. 스토캐스틱은 %K길이, %K스무딩, %D스무딩이 각각 5,1,3 이 기본입니다. 어퍼밴드(과매수)는 80, 로우어밴드(과매도)는 20이며 설정해서 수정 가능합니다.
2. CCI는 길이 20이 기본입니다. 어퍼밴드(과매수)는 100, 로우어밴드(과매도)는 -100이며 역시 설정에서 변경가능합니다.
3. RSI 길이 14가 기본입니다. 어퍼밴드(과매수)는 70, 로우어밴드(과매도)는 30이며 역시 설정에서 변경가능합니다.
(시그널)
세개 지표 중 1개지표가 동시에 과매수 해소되는 순간 S1, 2개지표가 동시에 과매수 해소되는 순간 S2, 3개지표 동시에 과매수 해소시 S3로 하고 캔들 위쪽에 표시 / 세개 지표 중 1개지표가 과매도 진입시 B1, 2개지표가 동시에 과매도 진입시 B2, 3개지표가 동시에 과매도 진입시 B3로 하고 캔들 아래쪽에 표시
Overview
SCR is a combined signal system built from Stochastic, CCI, and RSI.
For convenience, I call this indicator SCR.
This script is an implementation/visualization of the SCR concept shared by the blogger “SOXL Researcher” (SOXL연구원).
Indicator Settings
Stochastic
Default parameters: %K Length = 5, %K Smoothing = 1, %D Smoothing = 3
Default bands: Overbought (Upper) = 80, Oversold (Lower) = 20
All values can be changed in the settings.
CCI
Default length: 20
Default bands: Overbought (Upper) = 100, Oversold (Lower) = -100
All values can be changed in the settings.
RSI
Default length: 14
Default bands: Overbought (Upper) = 70, Oversold (Lower) = 30
All values can be changed in the settings.
Signals (Plotted on the Main Price Chart)
Signals are generated when the indicators trigger their conditions on the same bar (simultaneously).
Overbought Resolution Signals (S) — plotted above candles
S1: Exactly 1 of the three indicators resolves overbT (overbought resolution) on the same bar
S2: Exactly 2 indicators resolve overbought on the same bar
S3: All 3 indicators resolve overbought on the same bar
Oversold Entry Signals (B) — plotted below candles
B1: Exactly 1 of the three indicators enters oversold on the same bar
B2: Exactly 2 indicators enter oversold on the same bar
B3: All 3 indicators enter oversold on the same bar
Multi-Indicator DashboardMulti-timeframe trading dashboard overlay on your chart. Analyzes Trend, Momentum, Swing, Strength, Direction, Volatility, and delivers a final VIEW (Bullish/Bearish/Flat) across 5 key timeframes. Perfect for quick multi-TF alignment checks! W → D → 2H → 1H → 15M
Features
Color-Coded Cells: Green (Bullish), Red (Bearish), Gray (Neutral).
Historical Mode: Toggle "Enable Historical View" → Slider picks N bars back (chart TF-aware: e.g., 10 bars = 2.5H on 15M).
Yellow vertical line + date label marks the exact bar
Quick Setup
Add to chart → Customize inputs.
Historical: Enable + slide "Bars Back" for past data snapshots.
Views Update Live: Real-time on current/historical bars.
Nuh's Complete Multi-Timeframe Dashboard v4.0Nuh's Complete Multi-Timeframe Dashboard v4.0 - Unified Power System
Professional Multi-Timeframe Technical Analysis Dashboard
Nuh's Complete Multi-Timeframe Dashboard v4.0 represents a comprehensive trading analysis system that unifies 20 powerful technical indicators across up to 6 customizable timeframes into a single, intelligent dashboard. This advanced indicator combines trend analysis (EMA, Alpha Trend, SuperTrend, ADX, DI), momentum oscillators (RSI, Stochastic RSI, MACD, CCI, Williams %R, WaveTrend, KST), volume indicators (OBV, CMF, Volume Analysis, MFI), and volatility measures (Squeeze Momentum, Bollinger Bands, ATR, Williams VIX Fix) to provide traders with a holistic market perspective. Each indicator can be independently enabled or disabled, allowing complete customization based on your trading strategy and preferences.
The revolutionary Weighted Power System is the core innovation of this dashboard, transforming raw indicator signals into actionable market power scores. Unlike traditional dashboards that simply count bullish or bearish signals, this system applies sophisticated weighting to each indicator based on your chosen preset (Balanced, Trend Focus, Momentum Focus, Volume Focus) or custom weights. It then combines these weighted signals across multiple timeframes—with timeframe-specific weighting for scalping, day trading, or swing trading styles—to calculate an Overall Market Power score. This provides you with clear percentage-based bullish and bearish power readings, eliminating guesswork and enabling confident trade decisions backed by mathematical confluence.
Built for serious traders who demand precision and flexibility, the dashboard features a fully customizable display with 20 indicator rows that can be reordered to match your preferences, color-coded gradient visualization for instant market sentiment recognition, and integrated Wundertrading-compatible alerts for automated trading. The system supports both legacy count-based alerts and modern power-threshold alerts, allowing you to receive notifications when market conditions meet your specified confluence requirements. Whether you're scalping on lower timeframes or swing trading on higher timeframes, this professional-grade tool adapts to your trading style while maintaining clean, readable visualization that won't clutter your charts.
RSI > 70 Buy / Exit on Cross Below 70This strategy buys when the RSI (Relative Strength Index) closes above 70, indicating strong market momentum. It closes the position as soon as the RSI crosses down and falls below 70, to secure profits before a possible reversal.
In summary:
Entry: RSI > 70
Exit: RSI crosses down below 70
It’s a momentum-based strategy that aims to take advantage of strong trends but exits as soon as the momentum weakens.
[RoyalNeuron] RSI-SMA [WidowMaker v1.0]Hey everyone,👋
This is WidowMaker v1.0 — my free take on a really clean, zero-lag smoothed RSI that actually helps you see momentum without all the noise.
What makes it different:
- Smoothed RSI (you pick SMA or EMA) so it doesn’t whipsaw as much as the default one
- Green line when momentum is rising, red when it’s falling — super easy to read at a glance
- Histogram turns solid green for strong upward push, solid red when things are fading
- Very faint green background in oversold (buy zone) and faint red in overbought (caution zone)
Quick way to use it:
- Green line + solid green histogram near the bottom (oversold) → good spot for longs
- Red line + solid red histogram near the top (overbought) → time to think about shorts or taking profit
I made it because I was tired of cluttered indicators that look cool but don’t help much in real trading.
I am thinking of an updated version, still thinking of what to add so that to add value.
Would love your honest feedback — like it, use it, tell me what you’d add. More free tools on the way!
Cheers,
RoyalNeuron 👑
RSI, Smoothed RSI, Momentum, Oscillator, Overbought, Oversold, Histogram, Green Red, Free, Alerts
Relative Strength Index SmoothedDefinition
The Relative Strength Index (RSI) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI, when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements.
History
J.Welles Wilder Jr. is the creator of the Relative Strength Index. A former Navy mechanic, Wilder would later go on to a career as a mechanical engineer. After a few years of trading commodities, Wilder focused his efforts on the study of technical analysis. In 1978 he published New Concepts in Technical Trading Systems. This work featured the debut of his new momentum oscillator, the Relative Strength Index, better known as RSI.
Over the years, RSI has remained quite popular and is now seen as one of the core, essential tools used by technical analysts the world over. Some practitioners of RSI have gone on to further build upon the work of Wilder. One rather notable example is Andrew Cardwell who used RSI for trend confirmation.
Calculation
RSI = 100 – 100/ (1 + RS)
RS = Average Gain of n days UP / Average Loss of n days DOWN
For a practical example, the built-in Pine Script function rsi(), could be replicated in long form as follows.
change = change(close)
gain = change >= 0 ? change : 0.0
loss = change < 0 ? (-1) * change : 0.0
avgGain = rma(gain, 14)
avgLoss = rma(loss, 14)
rs = avgGain / avgLoss
rsi = 100 - (100 / (1 + rs))
"rsi", above, is exactly equal to rsi(close, 14).
The basics
As previously mentioned, RSI is a momentum based oscillator. What this means is that as an oscillator, this indicator operates within a band or a set range of numbers or parameters. Specifically, RSI operates between a scale of 0 and 100. The closer RSI is to 0, the weaker the momentum is for price movements. The opposite is also true. An RSI closer to 100 indicates a period of stronger momentum.
- 14 days is likely the most popular period, however traders have been known to use a wide variety of numbers of days.
What to look for
Overbought/Oversold
Wilder believed that when prices rose very rapidly and therefore momentum was high enough, that the underlying financial instrument/commodity would have to eventually be considered overbought and a selling opportunity was possibly at hand. Likewise, when prices dropped rapidly and therefore momentum was low enough, the financial instrument would at some point be considered oversold presenting a possible buying opportunity.
There are set number ranges within RSI that Wilder consider useful and noteworthy in this regard. According to Wilder, any number above 70 should be considered overbought and any number below 30 should be considered oversold.
An RSI between 30 and 70 was to be considered neutral and an RSI around 50 signified “no trend”.
Some traders believe that Wilder’s overbought/oversold ranges are too wide and choose to alter those ranges. For example, someone might consider any number above 80 as overbought and anything below 20 as oversold. This is entirely at the trader’s discretion.
Divergence
RSI Divergence occurs when there is a difference between what the price action is indicating and what RSI is indicating. These differences can be interpreted as an impending reversal. Specifically there are two types of divergences, bearish and bullish.
Bullish RSI Divergence – When price makes a new low but RSI makes a higher low.
Bearish RSI Divergence – When price makes a new high but RSI makes a lower high.
Wilder believed that Bearish Divergence creates a selling opportunity while Bullish Divergence creates a buying opportunity.
Failure Swings
Failure swings are another occurrence which Wilder believed increased the likelihood of a price reversal. One thing to keep in mind about failure swings is that they are completely independent of price and rely solely on RSI. Failure swings consist of four “steps” and are considered to be either Bullish (buying opportunity) or Bearish (selling opportunity).
Bullish Failure Swing
RSI drops below 30 (considered oversold).
RSI bounces back above 30.
RSI pulls back but remains above 30 (remains above oversold)
RSI breaks out above its previous high.
Bearish Failure Swing
RSI rises above 70 (considered overbought)
RSI drops back below 70
RSI rises slightly but remains below 70 (remains below overbought)
RSI drops lower than its previous low.
Cardwell’s trend confirmations
Of course no one indicator is a magic bullet and almost nothing can be taken simply at face value. Andrew Cardwell, who was mentioned earlier, was one of those students who took Wilder’s RSI interpretations and built upon them. Cardwell’s work with RSI led to RSI being a great tool not just for anticipating reversals but also for confirming trends.
Uptrends/Downtrends
Cardwell made keen observations while studying Wilder’s ideas of divergence. Cardwell believed that:
Bullish Divergence only occurs in a Bearish Trend.
Bearish Divergence only occurs in an Bullish Trend.
Both Bullish and Bearish Divergence usually cause a brief price correction and not an actual trend reversal.
What this means is that essentially Divergence should be used as a way to confirm trends and not necessarily anticipate reversals.
Reversals
Cardwell also discovered what are referred to as Positive and Negative Reversals. Positive and Negative Reversals are basically the opposite of Divergence.
Positive Reversal occurs when price makes a higher low while RSI makes a lower low. Price proceeds to rise. Positive Reversals only occur in Bullish Trends.
Negative Reversal occurs when price makes a lower high while RSI makes a higher high. Price proceeds to fall. Negative Reversals only occur in Bearish Trends.
Positive and Negative Reversals can be boiled down to cases where price outperformed momentum. And because Positive and Negative Reversals only occur in their specified trends, they can be used as yet another tool for trend confirmation.
Summary
For more than four decades the Relative Strength Index (RSI) has been an extremely valuable tool for almost any serious technical analyst. Wilder’s work with momentum laid the groundwork for future chartists and analysts to dive in deeper to further explore the implications of his RSI modeling and its correlation with underlying price movements. As such, RSI is simply one of the best tools or indicators in a trader’s arsenal of market metrics to develop most any trading methodology. Only the novice will take one look at RSI and assume which direction the market will be heading next based off of one number. Wilder believed that a bullish divergence was a sign that the market would soon be on the rise, while Cardwell believed that such a divergence was merely a slight price correction on the continued road of a downward trend. As with any indicator, a trader should take the time to research and experiment with the indicator before relying on it as a sole source of information for any trading decision. When used in proper its perspective, RSI has proven to be a core indicator and reliable metric of price, velocity and depth of market.
Williams %R Smoothed (EMA colour & bar toggle)From TradingView's description:
Williams %R (%R) is a momentum-based oscillator used in technical analysis, primarily to identify overbought and oversold conditions. The %R is based on a comparison between the current close and the highest high for a user defined look back period. %R Oscillates between 0 and -100 (note the negative values) with readings closer to zero indicating more overbought conditions and readings closer to -100 indicating oversold. Typically %R can generate set ups based on overbought and oversold conditions as well overall changes in momentum.
What's special?
This indicator adds two additional EMA lines to the original Williams %R indicator. Default EMA lengths are 5 and 13. The result is 2 smoother average lines, which are easier to read.
This indicator includes:
- signals for EMA crosses. EMA crosses can help indicate confirmed trend changes. Default colors are green and red
- signals for trend reversals on the faster EMA line. Default colors are blue and orange
Alerts available for bullish/bearish crossovers and reversals.
Stochastic RSI (adjustable fast line color)Definition
The Stochastic RSI indicator (Stoch RSI) is essentially an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means that it is a measure of RSI relative to its own high/low range over a user defined period of time. The Stochastic RSI is an oscillator that calculates a value between 0 and 1 which is then plotted as a line. This indicator is primarily used for identifying overbought and oversold conditions.
History
The Stochastic RSI (Stoch RSI) indicator was developed by Tushard Chande and Stanley Kroll. They introduced their indicator in their 1994 book The New Technical Trader.
Calculation
In this example, a very common 14 Period Stoch RSI is used.
Stoch RSI = (RSI - Lowest Low RSI) / (Highest High RSI - Lowest Low RSI)
Here are some approximate benchmark levels:
14 Day Stoch RSI = 1 when RSI is at its highest level in 14 Days.
14 Day Stoch RSI = .8 when RSI is near the high of its 14 Day high/low range.
14 Day Stoch RSI = .5 when RSI is in the middle of its 14 Day high/low range.
14 Day Stoch RSI = .2 when RSI is near the low of its 14 Day high/low range.
14 Day Stoch RSI = 0 when RSI is at its lowest level in 14 Days.
The basics
It is important to remember that the Stoch RSI is an indicator of an indicator making it two steps away from price. RSI is one step away from price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is multiple steps away from price, Stoch RSI can have brief disconnects from actual price movement. That being said, as a range bound indicator, the Stoch RSI's primary function is identifying crossovers as well as overbought and oversold conditions.
What to look for
Overbought/Oversold
Overbought and Oversold conditions are traditionally different than the RSI. While RSI overbought and oversold conditions are traditionally set at 70 for overbought and 30 for oversold, Stoch RSI are typically .80 and .20 respectively. When using the Stoch RSI, overbought and oversold work best when trading along with the underlying trend.
During an uptrend, look for oversold conditions for points of entry.
During a downtrend, look for overbought conditions for points of entry.
Summary
When using Stoch RSI in technical analysis, a trader should be careful. By adding the Stochastic calculation to RSI, speed is greatly increased. This can generate many more signals and therefore more bad signals as well as the good ones. Stoch RSI needs to be combined with additional tools or indicators in order to be at its most effective. Using trend lines or basic chart pattern analysis can help to identify major, underlying trends and increase the Stoch RSI's accuracy. Using Stoch RSI to make trades that go against the underlying trend is a dangerous proposition.
Inputs
K
The time period to be used in calculating the %K. 3 is the default.
D
% D = Percent of Deviation between price and the average of previous prices (Momentum). The time period to be used in calculating the %D. 3 is the default.
RSI Length
The time period to be used in calculating the RSI
Stochastic Length
The time period to be used in calculating the Stochastic
RSI Source
Determines what data from each bar will be used in calculations. Close is the default.
Elite Cumulative Volume Delta OscillatorOverview
The Elite CVD+ is a premium-grade, session-resettable Cumulative Volume Delta indicator designed exclusively for professional futures and volume-profile traders. By focusing on the cleaner and more actionable Line-Focused mode, it transforms raw order flow data into a precise decision engine that reveals institutional buying/selling pressure, absorption, exhaustion, and high-probability reversal/continuation zones.
Unlike standard CVD tools that accumulate indefinitely or reset awkwardly, this version resets cleanly at your chosen anchor period (default daily) while pulling granular delta from lower timeframes when desired. The result: a smooth, non-repainting line that highlights real-time shifts in aggressive participation without the noise of perpetual accumulation.
Why This Indicator Is Elite-Level Useful
True Institutional Footprint
Cumulative Volume Delta measures the net aggressive buying (bid hits) vs. selling (ask hits). Sustained positive CVD = buyers in control; negative = sellers dominating. When price makes new highs on weakening CVD → classic bearish divergence signaling distribution. The session reset prevents old data from distorting current conviction, making divergences far more reliable than perpetual CVD.
Early Reversal Detection via Absorption & Extremes
Absorption highlighting flags scenarios where heavy delta pushes against price but price refuses to follow (e.g., massive selling into lows yet price holds or closes higher) — textbook trapping/retail stop-hunting.
Session CVD extremes with dynamic test zones pinpoint where aggressive flow is exhausted. Price returning to test these levels often produces high-R:R reversals.
Confluence-Rich Signals
Dual EMAs provide trend/filter context (crossovers, zero-line bounces). Dynamic coloring instantly shows momentum strength. Extreme single-bar delta highlights climax buying/selling. Built-in regular + hidden divergences align order flow with price structure.
Multi-Timeframe Consistency
Optional custom lower-TF delta fetch ensures the same granular data regardless of chart timeframe — critical for traders who switch between 1-min execution charts and 15-min/1H analysis charts.
Clean, Low-Lag Visuals
Thick CVD line with intelligent coloring, subtle backgrounds, persistent extreme lines, and optional labels keep the pane readable even during fast markets. No clutter from inferior candle representations.
How Professional Traders Use Elite CVD+ Most Successfully
Primary Setup Framework
Use on futures with reliable volume delta (ES, NQ, YM, CL, GC, etc.). Best timeframes: 3–15 minutes for intraday, 1H–4H for swing. Combine with price action structure (order blocks, fair value gaps, market profile highs/lows).
Practical Tips for Maximum Edge
Anchor Period: '1D' for regular session trading (resets at 00:00 exchange time). Use '1W' for weekly bias or '4H' for London/NY session-specific flow.
Lower Timeframe Delta: Enable custom and set to '1' or '3' for maximum granularity on indices. Leave disabled on higher charts for smoother read.
Absorption Tuning: Raise threshold to 80–90 on volatile instruments (NQ) to filter noise; lower to 70 on quieter ones (CL, GC).
Divergences: Most powerful on 15M+. Disable hidden on very low TFs if too noisy.
Alerts: Use the master “Any Event” alert for push/email/webhook notifications of zero crosses or new extremes — perfect for mobile monitoring.
Combination Tools: Pair with session VWAP, volume profile (fixed range at highs/lows), or psychological levels for triple confluence.
BTC - StableFlow: Pit-Stop & Refuel EngineBTC – StableFlow: Pit-Stop & Refuel Engine | RM
Strategic Context: The Institutional Gas Station In the high-speed race of the crypto markets, Stablecoins (USDT, USDC, DAI) represent the Fuel, and Bitcoin is the Race Car. Most traders only look at the car's speed (Price), but they ignore the gas tank. The StableFlow Engine is a telemetry dashboard designed to monitor the "Fuel Pressure" within the ecosystem, identifying exactly when the car is being refueled and when it is running on empty.
The Telemetry Logic: How to Read the Race
The indicator operates on a Relative Velocity model. We aren't just looking at how many Stablecoins exist; we are measuring the Acceleration of Stablecoin Market Cap relative to the Acceleration of BTC Price.
1. The Fuel Reservoir (The Histogram)
• Cyan Zones (Refuel): The gas station is open. Institutional "Dry Powder" is flowing into stables faster than it is being spent on BTC. The tank is filling up.
• Orange Zones (Exhaust): The "Overdrive." The car is driving faster than the gas can be pumped. Price is outperforming the stablecoin supply—this is unsustainable and usually precedes a stall.
2. Lap Transitions (The Grey Lines)
These vertical markers signify a Regime Shift . They trigger the moment the momentum crosses the zero-axis, visually distinguishing the transition between a "Net-Refueling" period and a "Net-Exhaustion" period. While not used as direct entry signals, they define the Macro Lap we are currently in.
Operational Playbook: The Pit-Stop Signals
We don't just buy because the tank is full; we buy when the car exits the pits and begins to accelerate. This is captured by our proprietary Pit-Stop Pips.
• Blue Pip (Pit-Stop Buy): Triggered when the Refuel momentum has peaked and is now rotating back into the market. The refuel is complete; the car is rejoining the race with a full tank.
• Red Pip (Exhaust Sell): Triggered when the price acceleration has overextended relative to its fuel source and begins to "roll over." The tank is near empty; time for a tactical pull-back.
Settings & Calibration: The Pit Wall Dashboard
Signal Mode & Logic The engine features a dual-mode signaling system to adapt to different market conditions (or your personal preferred logic):
• Consecutive Mode: Best for high-velocity trends. Fires a pip after n bars of momentum reversal (Default: 2 bars).
• Percentage (%) Mode: Best for structural fades. Fires a pip when the momentum retraces by a specific percentage (e.g., 15%) from its local peak, regardless of the bar count.
Recommended Calibration
While the engine is versatile across various timeframes, the Weekly (1W) chart is the preferred setting for identifying high-conviction macro signals. Lower timeframes provide tactical speed, but the 1W frame offers significantly cleaner signals by filtering out the daily market noise.
Weekly (1W) — The Macro Signal (Preferred): * Velocity Lookback: 20 | Smoothing: 5.
Peak Lookback: 25 (Represents roughly half a year of telemetry data). This is a good starting point for identifying major cycle rotations.
Daily (1D) — The Tactical Pulse: * Velocity Lookback: 20 | Smoothing: 5.
Peak Lookback: 25 (Represents one trading month of telemetry). Useful for active swing traders looking for entry/exit timing within an established macro trend.
Technical Documentation
Data Sourcing & Aggregation The script utilizes request.security to aggregate a "Big Three" Stablecoin Market Cap (USDT + USDC + DAI). This prevents "False Exhaustion" signals caused by capital simply migrating between different stablecoin assets.
Mathematical Foundation The core engine calculates the Rate of Change (ROC) for the Aggregate Stablecoin Supply and BTC Price over a synchronized lookback window.
Formula Logic: Fuel Pressure = EMA ( ROC(Stables) - ROC(BTC) )
The Pit-Stop Pips utilize a local peak-finding algorithm via ta.highest and ta.lowest within a rolling 25-bar window to calculate the Relative Retracement Magnitude . This ensures signals are mathematically tied to the volatility of the current market regime.
The Dual-Fuel Framework: StableFlow x Liquisync
The StableFlow Engine is designed to function as the tactical counterpart to the Liquisync: Macro Pulse Engine . While Liquisync monitors the Global Supply Line (the "Tanker Truck" of M2 Liquidity moving from Central Banks toward the track with a 60-day lead), StableFlow measures the Immediate Fuel Pressure (the "Dry Powder" already in the pit lane, ready to be pumped into the car).
By using both indicators in tandem, you can follow the Dual-Fuel Strategy: Liquisync identifies the fundamental macro regime, while StableFlow identifies the specific "Refuel" and "Exhaustion" pivots within that regime. We will be providing a comprehensive breakdown of this synchronized telemetry in our upcoming Substack Masterclass: The Dual-Fuel Architecture.
Risk Disclaimer & Credits
The StableFlow is a thematic macro tool tracking on-chain liquidity proxies. Stablecoin data is subject to exchange reporting delays. This is not financial advice; it is a telemetry model for institutional education. Rob Maths is not liable for losses incurred via use of this model.
Tags:
indicator, bitcoin, btc, stablecoins, usdt, flow, liquidity, macro, refuel, institutional, robmaths, Rob Maths
KAMA Oscillator | IkkeOmarThis script transforms the Kaufman Adaptive Moving Average (KAMA) into an oscillator format, designed to visualize trend direction with reduced noise sensitivity. It operates in two modes: a Raw mode that tracks price levels directly, and a Normalized mode that bounds the oscillator between -1 and +1 for easier comparison across assets.
The calculations are the same as for the Normalized KAMA Oscillator, but I added a few features that users of the old version wouldn't necessarily want.
How it works
Efficiency Ratio (ER): The script calculates the "efficiency" of price movement by comparing the net direction of price to the total volatility over a set period.
Adaptive Smoothing:
When volatility is high but direction is unclear (choppy), the KAMA slows down to filter noise.
When price trends clearly, the KAMA speeds up to track the move.
Normalization (Optional): If enabled, the script takes the raw KAMA value and scales it relative to its highest and lowest points over the Normalization lookback period. The result oscillates between -1 (extreme low) and +1 (extreme high).
The SMA Signal Logic
The script allows you to overlay an SMA (Simple Moving Average) on the oscillator. This serves as a dynamic baseline for the oscillator's momentum.
Signal Generation: A signal is generated when the KAMA Oscillator crosses its SMA.
Bullish: Oscillator crosses above the SMA.
Bearish: Oscillator crosses below the SMA.
Lag vs. Noise Trade-off:
Advantage (Reduced Lag): Crossing the SMA often triggers a signal earlier than waiting for the oscillator to change color (slope change) or cross the zero line. It identifies when immediate momentum is outperforming the recent average.
Risk (Increased Noise): During consolidation, the oscillator will hover close to the SMA line. This increases the probability of "whipsaws" (false signals) where the line crosses back and forth rapidly without a sustained trend. This signal is aggressive and should be used with trend filters.
Smart WaveTrend Crossover█ OVERVIEW
Smart WaveTrend Crossover is an indicator based on WaveTrend crossovers, designed to reduce the number of false signals typically produced by classic oscillator crossovers.
Instead of triggering a signal immediately at the line crossover, the indicator requires additional confirmation in the form of a price breakout from a box, created at the moment of the WaveTrend signal.
The script also includes:
- a trend filter based on a separate WaveTrend
- “fog” visualization
- candle coloring based on trend direction
- fully configurable entry signals
- automatic Take Profit / Stop Loss levels
- a real-time TP/SL table
█ CONCEPTS
Classic WaveTrend crossovers often generate noise, especially during consolidation.
Smart WaveTrend Crossover attempts to address this issue using a breakout confirmation mechanism:
- at the moment WT1 crosses WT2, a horizontal price box is created
- a trade signal is generated only when price closes outside the box
- an optional trend filter limits signals to the dominant market direction
The trend filter is built on a WaveTrend crossover using larger, slower parameters, independent from the signal-generating WaveTrend.
This allows short-term momentum to be separated from the broader market direction, and all trend filter parameters can be freely adjusted.
WaveTrend signal settings are not identical to the original / classic values.
They are configured to generate a higher number of signals, which works better in combination with breakout boxes and confirmation logic.
Signal sensitivity can be easily adjusted by modifying channel length and averaging parameters.
By default, show_only_matching is enabled:
- bullish crossover → bullish breakout only (BUY)
- bearish crossover → bearish breakout only (SELL)
█ FEATURES
WaveTrend (Signals & Trend):
- two independent WaveTrend setups:
- one for signal generation
- one for trend determination
- signal parameters configured more aggressively than classic defaults
- trend filter based on a slower WaveTrend crossover
- trend direction visualized using directional fog, not a histogram
WaveTrend Input Explanation:
- Channel Length – controls WaveTrend reaction speed (shorter = more signals)
- Average Length – smoothing of the main WT1 line
- MA Length – smoothing of the signal line WT2
- Source – price source used in calculations (default: hlc3)
Fog (Visualization):
- visual representation of market pressure in the direction of the trend
- fog height based on average candle size × offset_mult
- adjustable transparency or fully disableable
Breakout Boxes:
- a box is created on every WaveTrend direction change
- default height based on the signal candle range
- optional box expansion using average candle size × box_multiplier
Signals:
- triangles or “BUY / SELL” labels
- direction matching filter (show_only_matching)
- option to display all breakouts regardless of crossover direction
- built-in BUY and SELL alerts
Visual Settings:
- candle coloring based on WaveTrend trend direction
- full control over bullish and bearish colors
Risk Management – TP / SL:
- automatic TP1, TP2, TP3 and SL levels
- two calculation modes:
- Candle Multiplier – based on average candle range
- Percentage – percentage from entry price
- separate parameters for each level
- TP/SL lines drawn on the chart
- real-time TP/SL price table
█ HOW TO USE
Add the indicator to your TradingView chart → Indicators → search “Smart WaveTrend Crossover”
Key settings:
- WaveTrend Settings for Signals – signal sensitivity
- WaveTrend Settings for Trend – market direction filter
- Signal Settings – signal type and box logic
- Fog – pressure visualization
- Risk Management – TP/SL configuration
Signal meaning:
- BUY → upward breakout from a box after a bullish crossover
- SELL → downward breakout from a box after a bearish crossover
- visible boxes → breakout watch zones
- fog and candle color → current market direction
█ APPLICATIONS
Standalone entry system
- entering directly on BUY / SELL signals
- or entering on trend color change
Filter for price-action strategies
- using WaveTrend signals as directional confirmation
- e.g. level breakout + WaveTrend confirmation = entry
Trend indicator
- trading other tools only in the direction of the WaveTrend trend
- e.g. RSI breaks above 50 while WaveTrend trend is bullish
█ NOTES
- Default settings are a starting point and may require adjustment
- The indicator works best as part of a broader trading system
