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MA Alignment DetectorMA Alignment Detector : If it is bullish MA alignment, the color becomes red, if it is bearlish MA alignment, the color become green.
Elite MTF EMA Reclaim Signals Only ( With Market Presets)This indicator is a multi-timeframe trend-continuation entry tool.
It’s designed to help you enter pullback trades in strong trends while blocking choppy or low-quality conditions.
It works by:
Requiring Daily + 1H trend alignment
Enforcing EMA structure (5/10/20/50) on the 6-minute chart
Confirming momentum (EMA slope + curvature)
Blocking trades during chop (low ATR, weak ADX, tight EMAs, recent EMA crosses)
Triggering entries only after a Pullback → Reclaim → (optional) Retest
How to use it (6-minute execution)
Set chart to 6-minute
Select Market (Forex, XAUUSD, Crypto, or Indices)
Select Preset
Elite → fewest, cleanest trades
Balanced → best everyday default
Aggressive → more signals, more risk
Trade only when you see a LONG or SHORT triangle
Avoid trades when CHOP or HTF block markers appear
Place stops beyond EMA50 or recent structure, target 2R–4R+
Optional:
Turn on Looser LTF Mode or Allow reclaim without pullback for more signals
Use Next bar confirmation for cleaner entries, Reclaim close for faster entries
Bottom line:
The indicator doesn’t hunt trades—it filters the market so you only trade when trend, momentum, and structure are aligned.
EMA 9, 21, 200//@version=6
indicator("EMA 9, 21, 200", overlay=true)
// EMA inputs
emaFastLength = 9
emaMidLength = 21
emaSlowLength = 200
// Calculate EMAs
emaFast = ta.ema(close, emaFastLength)
emaMid = ta.ema(close, emaMidLength)
emaSlow = ta.ema(close, emaSlowLength)
// Plot EMAs
plot(emaFast, color=color.yellow, title="EMA 9", linewidth=2)
plot(emaMid, color=color.orange, title="EMA 21", linewidth=2)
plot(emaSlow, color=color.red, title="EMA 200", linewidth=2)
Advanced Algo [From India]Here is a **shortened, more concise, and TradingView-ready version** of the description, with
**“TG – SWIFT Algo V1.1” replaced by “Advanced Algo ”** and explanations tightened while keeping clarity and professionalism.
---
🙏 Introduction & Gratitude
> *I have taken so much from this TradingView community over the years — ideas, learning, and inspiration.
> It’s time to give back a small contribution with gratitude.*
**Advanced Algo ** is a **non-repainting, rule-based intraday indicator** designed primarily for **crypto markets**, optimized for **5-minute and 15-minute timeframes**.
The goal is to provide **clean signals, disciplined trade structure, and consistent execution logic**.
---
📌 Indicator Overview
**Advanced Algo **:
* Generates **confirmed BUY / SELL signals**
* Automatically plots **Entry, Take-Profit, and Stop-Loss levels**
* Maintains **one active trade at a time** to avoid over-trading
* Tracks results via a **lightweight statistics table**
This is a **decision-support tool**, not a prediction system or financial advice.
---
## ⚙️ High-Level Logic
### 1️⃣ Adaptive Moving Average Engine
The indicator compares two adaptive moving averages:
* **Fast MA** (close-based)
* **Slow MA** (open-based)
Selectable MA types:
* **TEMA**
* **Hull MA**
* **ALMA** (default – low lag & smooth)
A small **price delay** is applied to ensure **true non-repainting behavior**.
---
### 2️⃣ Signal Generation (Confirmed Bars Only)
* **BUY** → Fast MA crosses above Slow MA
* **SELL** → Fast MA crosses below Slow MA
Signals are generated **only after candle confirmation**.
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### 3️⃣ Trade Lifecycle Control
Once a trade starts:
* Entry price is fixed
* TP & SL are calculated using percentage inputs
* No new trades are allowed until the current trade exits
This prevents signal clustering and emotional over-trading.
---
### 4️⃣ Intrabar TP & SL Handling
Although entries are bar-confirmed:
* **Take-Profit and Stop-Loss execute intrabar**
* Trades exit immediately when price is touched
This closely matches real-market behavior on lower timeframes.
---
## 📊 Visuals & Statistics
* **Blue** → Entry
* **Purple** → Take Profit
* **Maroon** → Stop Loss
* Green & red fills show reward and risk zones
Optional labels mark:
* Entries
* TP hits
* SL hits
A simple stats table tracks:
* Buy TP / Sell TP
* Buy SL / Sell SL
---
## ⏱ Recommended Usage
**Best suited for:**
* Crypto markets (BTC, ETH, liquid altcoins)
* **5m and 15m timeframes**
* Trending or moderately volatile conditions
**Tips:**
* Start with default settings
* Adjust TP & SL based on volatility
* Avoid low-volume or highly ranging markets
---
## 🔔 Alerts & Automation
The script includes structured alerts for:
* Entries
* TP & SL exits
These can be used for **manual alerts or automated execution workflows**.
---
## ⚠️ Disclaimer
* No indicator guarantees profits
* Always backtest and forward-test before live trading
* Proper risk management is essential
This script is shared **for educational and analytical purposes only**.
---
## 🤝 Closing Note
If this tool adds structure or clarity to your trading, then it has fulfilled its purpose.
Feedback and constructive suggestions are always welcome.
**Trade responsibly and stay disciplined.**
MA Crossover with R SquaredThis indicator enhances the classic Moving Average (MA) crossover strategy with statistical filtering and prediction capabilities.
Let me explain what it does:
Instead of just showing when a fast MA crosses above/below a slow MA, this indicator adds R² (R-squared) filtering to identify higher-quality crossovers and predicts future crossovers.
What is R²?
R² (Coefficient of Determination) is a statistical measure that shows how well one variable explains the movement of another variable. In simpler terms:
R² = 1.0: Perfect relationship - 100% of the movement in one MA is explained by the other MA
R² = 0.8: Strong relationship - 80%
R² = 0.5: Moderate relationship - 50%
R² = 0.0: No relationship - 0%
Imagine two cars driving on a highway:
High R² (0.9): Both cars are in the same lane, moving together consistently
Low R² (0.3): One car is weaving between lanes while the other stays straight - poor coordination.
Traditional MA crossovers often generate false signals during:
Choppy markets (price bouncing around)
Sideways/ranging markets
Low volatility periods
News events causing temporary spikes
The R² Solution:
R² acts as a "quality filter" that answers: "How meaningful this crossover is?"
What this means:
Before R² filtering: Every crossover generates a signal
After R² filtering: Only crossovers with R² > threshold generate signals
Result: Fewer but higher-quality signals.
MARKET REGIME DETECTION
High R² (> 0.7): Strong trending market - MA crossovers are reliable
Medium R² (0.4-0.7): Moderate trending - use with caution
Low R² (< 0.4): Choppy/range-bound market - avoid MA crossover signals
Increasing R²: MAs are converging/moving together more closely
Decreasing R²: MAs are diverging/losing coordination
Sudden R² drop: Potential market regime change.
Why Square the Correlation?
Correlation: Measures direction AND strength (-1 to +1)
R²: Measures strength ONLY (0 to 1)
In trading: We care about relationship strength, not direction
Direction is already indicated by crossover type (bullish/bearish)
Real-World Interpretation:
If R² = 0.64, it means:
64% of the variation in the fast MA is explained by the slow MA
36% is "noise" or unexplained movement
The MAs are moderately coordinated.
R² Trend Confirmation:
Entry: When crossover occurs AND R² is above threshold
Confirmation: R² continues rising after entry
Exit: R² drops below threshold (relationship weakening)
Multi-Timeframe R² Analysis
Check R² on higher timeframe for trend context
Use current timeframe for entry signals
Example: Daily R² > 0.7 gives bullish bias, use 1-hour for entries.
R² LIMITATIONS & CAUTIONS
1. Lagging Nature
R² is calculated from past data
By the time R² is high, the trend may already be established
2. Not a Standalone Indicator
R² should confirm other signals, not generate them alone
Always combine with price action, volume, support/resistance
3. Curve Fitting Risk
Don't over-optimize R² thresholds on historical data
What worked in the past may not work in the future
Use R² as a filter, not a predictor
4. Market-Specific Behavior
R² thresholds that work in trending stocks may fail in Forex
Cryptocurrencies may require different R² settings than commodities
Always test on your specific market/instrument
Before Taking Any Signal:
✅ Does the crossover have a colored circle? (R² > threshold)
✅ What's the R² number shown? (Higher = better)
✅ Is R² rising or falling? (Rising = strengthening relationship)
✅ Check history table - what happened with similar R² values?
✅ Consider prediction - does it align with current signal?
Simple R² Rules of Thumb:
R² > 0.8: Excellent signal quality
R² 0.6-0.8: Good signal quality
R² 0.4-0.6: Moderate - use additional confirmation
R² < 0.4: Poor - avoid or use extreme caution
Think of R² as:
A quality control inspector for MA crossovers
A relationship therapist for your moving averages
A statistical bouncer that only lets strong signals through
Higher win rate + Better risk/reward = More profitable trading
This script transforms the basic "when lines cross" approach into a sophisticated, statistically-validated trading system. R² is the secret sauce that separates random crossovers (Golden/Death) from meaningful trend changes.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
ADVANCED NIFTY OPTION BUY SELLADVANCED NIFTY OPTION BUY SELL – V1 is a non-repainting, trend-following TradingView indicator specially designed for NIFTY Index Options (CE / PE) traders.
This indicator focuses on:
Eliminating over-trading
Providing high-quality, low-frequency signals
Avoiding trades during sideways markets
It combines EMA crossover, RSI momentum, and ADX trend strength to deliver clean and reliable buy/sell signals.
Accurate Swing Trading + Support Resistance 2 more setting accurate swing trading, 2 setting mode. 1 trend. 2. buy sell. and add support resisten
Smart Money Fluid [JOAT]
Smart Money Fluid — Accumulation and Distribution Flow Analysis
Smart Money Fluid tracks institutional-style accumulation and distribution patterns using a sophisticated combination of Money Flow Index, Chaikin Money Flow, and VWAP-relative price analysis. It aims to reveal whether larger participants may be accumulating (buying) or distributing (selling)—information that can precede significant price moves.
What Makes This Indicator Unique
Unlike single money flow indicators, Smart Money Fluid:
Combines three different money flow methodologies into one composite signal
Detects divergences between price and money flow automatically
Identifies high-volume conditions that add conviction to signals
Provides both the composite signal and individual component values
Features a momentum histogram showing flow acceleration
What This Indicator Does
Combines multiple money flow indicators into a composite signal (0-100 scale)
Identifies accumulation zones (potential institutional buying) and distribution zones (potential selling)
Detects divergences between price and money flow
Highlights high-volume conditions for stronger signals
Tracks momentum direction within the flow
Provides comprehensive dashboard with all component values
Composite Calculation Explained
The Smart Money Flow composite combines three proven money flow methodologies:
// Component 1: Money Flow Index (MFI) - 40% weight
// Measures buying/selling pressure using price and volume
float mfi = 100 - (100 / (1 + mfRatio))
// Component 2: Chaikin Money Flow (CMF) - 30% weight
// Measures accumulation/distribution based on close position within range
float cmf = sum(mfVolume, length) / sum(volume, length) * 100
// Component 3: VWAP Price Strength - 30% weight
// Measures price position relative to volume-weighted average price
float priceVsVWAP = (close - vwap) / vwap * 100
// Final Composite (scaled to 0-100)
float rawSMF = (mfi * 0.4 + (cmf + 50) * 0.3 + (50 + priceVsVWAP * 5) * 0.3)
float smf = ta.ema(rawSMF, smoothLength)
State Classification
Accumulating (Green Zone) — SMF above accumulation threshold (default: 60). Suggests institutional buying may be occurring.
Distributing (Red Zone) — SMF below distribution threshold (default: 40). Suggests institutional selling may be occurring.
Neutral (Gray Zone) — SMF between thresholds. No clear accumulation or distribution detected.
Divergence Detection
The indicator automatically detects divergences using pivot analysis:
Bullish Divergence — Price makes a lower low while SMF makes a higher low. This suggests selling pressure is weakening despite lower prices—potential reversal signal.
Bearish Divergence — Price makes a higher high while SMF makes a lower high. This suggests buying pressure is weakening despite higher prices—potential reversal signal.
Divergences are marked with "DIV" labels on the chart.
Visual Features
SMF Line with Glow — Main composite line with gradient coloring and glow effect
Signal Line — Slower EMA of SMF for crossover signals
Flow Momentum Histogram — Shows the difference between SMF and signal line with four-color coding:
- Bright green: Positive and accelerating
- Faded green: Positive but decelerating
- Bright red: Negative and accelerating
- Faded red: Negative but decelerating
Zone Backgrounds — Green tint in accumulation zone, red tint in distribution zone
Reference Lines — Dashed lines at accumulation/distribution thresholds, dotted line at 50
Strong Signal Markers — Triangles appear when accumulation/distribution occurs with high volume
Divergence Labels — "DIV" markers when divergences are detected
Color Scheme
Accumulation Color — Default: #00E676 (bright green)
Distribution Color — Default: #FF5252 (red)
Neutral Color — Default: #9E9E9E (gray)
Gradient Coloring — SMF line transitions smoothly between colors based on value
Dashboard Information
The on-chart table (top-right corner) displays:
Current SMF value with state coloring
State classification (ACCUMULATING, DISTRIBUTING, or NEUTRAL)
Flow momentum direction (Up/Down with magnitude)
MFI component value
CMF component value with directional coloring
Volume status (High or Normal)
Active divergence detection (Bullish, Bearish, or None)
Inputs Overview
Calculation Settings:
Money Flow Length — Period for flow calculations (default: 14, range: 5-50)
Smoothing Length — EMA smoothing period (default: 5, range: 1-20)
Divergence Lookback — Bars for pivot detection in divergence analysis (default: 5, range: 2-20)
Sensitivity:
Accumulation Threshold — Level above which accumulation is detected (default: 60, range: 50-90)
Distribution Threshold — Level below which distribution is detected (default: 40, range: 10-50)
High Volume Multiplier — Multiple of average volume for "high volume" classification (default: 1.5x, range: 1.0-3.0)
Visual Settings:
Accumulation/Distribution/Neutral Colors — Customizable color scheme
Show Flow Histogram — Toggle momentum histogram
Show Divergences — Toggle divergence detection and labels
Show Dashboard — Toggle the information table
Show Zone Background — Toggle colored backgrounds in accumulation/distribution zones
Alerts:
Await Bar Confirmation — Wait for bar close before triggering (recommended)
How to Use It
For Trend Confirmation:
Accumulation during uptrends confirms buying pressure
Distribution during downtrends confirms selling pressure
Divergence between price trend and SMF warns of potential reversal
For Reversal Detection:
Bullish divergence at price lows suggests potential bottom
Bearish divergence at price highs suggests potential top
Strong signals (triangles) with high volume add conviction
For Entry Timing:
Enter longs when SMF crosses into accumulation zone
Enter shorts when SMF crosses into distribution zone
Wait for high volume confirmation for stronger signals
Use divergences as early warning for position management
Alerts Available
SMF Accumulation Started — SMF entered accumulation zone
SMF Distribution Started — SMF entered distribution zone
SMF Strong Accumulation — Accumulation with high volume
SMF Strong Distribution — Distribution with high volume
SMF Bullish Divergence — Bullish divergence detected
SMF Bearish Divergence — Bearish divergence detected
Best Practices
High volume during accumulation/distribution adds significant conviction
Divergences are early warnings—don't trade them alone
Use in conjunction with price action and support/resistance
Works best on liquid markets with reliable volume data
This indicator is provided for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management before making trading decisions.
— Made with passion by officialjackofalltrades
Adaptive 2 EMA Cloud (Trend-Aware)Adaptive 2 EMA Cloud (Trend-Aware)
This indicator combines a classic 2-EMA cloud and crossover with an adaptive Trend vs Chop filter designed to reduce whipsaws during sideways markets.
Instead of treating every EMA crossover equally, this script evaluates EMA separation and directional commitment (normalized by ATR) to determine whether price is trending or chopping. Signals can optionally be filtered so they only appear during qualified trend conditions.
What This Indicator Does
Plots two configurable EMAs with a filled EMA cloud
Marks bullish and bearish EMA crossovers
Classifies market state as BULLISH / BEARISH / CHOP
Optionally filters signals during chop
Highlights chop zones with a subtle background
Displays a movable Trend status label (Top / Bottom × Left / Middle / Right) with offset controls to avoid UI overlap
This makes the indicator useful both as:
A visual trend context tool
A signal filter to pair with discretionary or systematic entries
Quick Presets (Main Framework)
Scalp / Fast (1–2 min)
Built for speed and momentum bursts. Uses tighter EMAs and stricter filters to avoid chop on very fast charts.
EMA pairs (choose one):
5 / 9
8 / 13
slopeLen: 4–6
minDistATR: 0.25–0.40
minSlopeATR: 0.06–0.12
Balanced Intraday (3–5 min)
General-purpose intraday setup. Balances early trend participation with chop filtering. Recommended starting point if unsure.
EMA pairs (choose one):
8 / 13
9 / 21
slopeLen: 5–8
minDistATR: 0.18–0.30
minSlopeATR: 0.04–0.08
Slower / Swing (15–60 min)
Designed for higher timeframes and smoother trends. Allows longer trends to develop without requiring sharp acceleration.
EMA pairs (choose one):
13 / 21
21 / 34
slopeLen: 8–14
minDistATR: 0.10–0.22
minSlopeATR: 0.02–0.06
Input Guide (Streamlined)
minDistATR — EMA Separation
Sets the minimum EMA spacing (ATR-normalized) required for a trend.
Higher = stricter, fewer signals
Filters EMA compression / ranges
Too much chop → increase
Too few signals → decrease
Too low = congestion signals · Too high = late entries
minSlopeATR — EMA Slope / Commitment
Sets the minimum directional strength (ATR-normalized) of the EMAs.
Higher = stricter, fewer signals
Filters weak drift and slow grind
Signals stall → increase
Miss smooth trends → decrease
Too low = flat EMAs allowed · Too high = requires acceleration
slopeLen — Slope Lookback
Controls how quickly the filter reacts.
Lower = faster, noisier
Higher = smoother, fewer signals
3–5 responsive · 8–14 stable
atrLen — Normalization
Stabilizes distance and slope across symbols and timeframes.
Leave at 14 normally
Use 20–30 during extreme volatility shifts
Notes
This is an indicator, not a strategy. It does not backtest or predict outcomes.
No filter eliminates chop entirely—this tool is designed to reduce low-quality conditions, not remove them.
Best results come from matching presets to timeframe first, then making small adjustments only when behavior is clearly off.
UM Premarket Volume DashboardSUMMARY
Do you track the largest percent movers in the premarket?
Instantly compare current premarket volume to its recent average with built-in trend confirmation.
⸻
DESCRIPTION
This indicator is a compact premarket intelligence dashboard that combines live volume analysis with adaptive trend detection. It highlights unusually strong premarket activity while confirming directional bias using either a Nadaraya–Watson Estimator (NWE) or traditional moving averages.
The goal is to quickly identify symbols that are both active and aligned with trend before the regular trading session begins.
⸻
HOW IT WORKS
• Calculates average daily volume using a 50-day rolling average
• Tracks live premarket volume between 04:00–09:30 (exchange time)
• Computes a rolling average of prior premarket sessions and blends in the current day’s partial premarket volume in real time
• Highlights premarket volume in dark green when it exceeds both a user-defined threshold and the rolling premarket average
• Determines bullish or bearish trend status using a selectable method:
• Nadaraya–Watson Estimator (NWE)
• EMA, WMA, or SMA
• Trend status is based on directional slope (current value vs prior bar)
• Displays percent gain from the previous regular-session close (4:00pm ET)
• Shows total shares outstanding for quick liquidity context (when available)
⸻
DEFAULT SETTINGS
• Trend Method: Nadaraya–Watson Estimator (NWE)
• NWE Lookback Window (h): 8
• NWE Relative Weighting (r): 8
• Regression Length: 120 bars
• Premarket Average Days: 10
• Premarket Green Volume Threshold: 50,000 shares
• Average Daily Volume: 50-day SMA
• Trend Source: Close
⸻
SUGGESTED SETTINGS AND USES
• Use the default NWE settings for smoother, adaptive trend confirmation, especially on lower timeframes (1–5 minute charts) during premarket
• Switch to EMA or WMA if you prefer faster trend flips or want behavior consistent with MA-based systems
• Increase the Premarket Volume Threshold for large-cap stocks or ETFs to reduce noise
• Decrease the threshold for small-cap stocks to surface early momentum names
Ideal for:
• Premarket gap scanners
• Momentum continuation setups
• Liquidity confirmation before market open
• Building dynamic watchlists for the opening bell
This indicator is best used as a filtering and confirmation tool, not as a standalone entry signal.
Trend Regime Bands (EMA 50 / 150 / 200)📘 Trend Regime Bands – EMA 50·150·200
Overview
Trend Regime Bands is a visual trend-context indicator designed to help users quickly understand whether the market is in a bullish or bearish regime. The indicator uses the alignment of EMA 50, EMA 150, and EMA 200 to determine overall trend direction, while additional EMAs are used only to create color-based bands for visual context. No buy or sell signals are generated.
How Trend Direction Is Determined
Trend direction is derived exclusively from the relative positioning of: EMA 50 (short-term trend) , EMA 150 (medium-term trend) , EMA 200 (long-term trend) . Bullish regime: EMA 50 ≥ EMA 150 ≥ EMA 200 . Bearish regime: EMA 50 < EMA 150 < EMA 200. These three EMAs act as the decision framework for the indicator.
What the Color Bands Represent : The indicator displays two visual bands on the chart:
Fast Band (Momentum Context) - Built using faster EMAs, Represents short-term momentum and pullback behavior. Brighter color intensity reflects stronger momentum
Slow Band (Regime Context) - Built using slower EMAs. Represents broader trend structure and regime stability.Deeper color intensity reflects stronger trend alignment
The color of both bands follows the trend direction determined by EMA 50/150/200:
Green shades indicate a bullish regime. Red shades indicate a bearish regime. Color intensity increases or decreases smoothly based on trend strength.
How to Use This Indicator
Use the bands to understand market context, not as entry or exit signals. Strong, bright bands suggest a well-established trend. Lighter bands indicate weaker or transitioning trends. The indicator works across intraday, swing, and higher timeframes. This tool is best used alongside price action, support/resistance, or other confirmation methods.
Important Notes
This indicator does not provide buy or sell signals. It does not predict future price movement. It is intended solely as a visual trend-regime and context tool
Summary
Trend Regime Bands offers a clean, distraction-free way to visualize bullish and bearish market regimes using EMA structure and color intensity, helping traders maintain directional awareness and discipline.
ATR-Normalized VWMA DeviationThis indicator measures how far price deviates from the Volume-Weighted Moving Average ( VWMA ), normalized by market volatility ( ATR ). It identifies significant price reversal points by combining price structure and volatility-adjusted deviation behavior.
The core idea is to use VWMA as a dynamic trend anchor, then measure how far price travels away from it relative to recent volatility . This helps highlight when price has stretched too far and may be due for a reversal or pullback.
How it works:
VWMA deviation is calculated as the difference between price and the VWMA.
That deviation is divided by ATR (Average True Range) to normalize for current volatility.
The script tracks the highest and lowest normalized deviations over the chosen lookback period.
It also tracks price structure (highest/lowest highs/lows) over the same period.
A reversal signal is generated when a historical extreme in deviation aligns with a price structure extreme, and a confirmed reversal candle forms.
You get visual signals and color highlights where these conditions occur.
Settings explained:
Lookback period defines how many bars the script uses to find recent extremes.
ATR length controls how volatility is measured.
VWMA length controls how the volume-weighted moving average is calculated.
Signal filters help refine entries based on price vs deviation behavior.
Display options let you customize how signals and levels appear on the chart.
This indicator is especially useful for spotting potential turning points where price has moved far from VWMA relative to volatility, suggesting possible exhaustion or overextension.
Tips for use:
Combine with broader trend context (higher timeframe support/resistance).
Use with risk management rules (position sizing, stops) — signals are guides, not guaranteed entries.
Adjust lookback and ATR settings based on your trading timeframe and asset volatility.
RS Rating Multi-Timeframe v2RS Rating Multi-Timeframe
A relative strength rating indicator modeled after IBD's proprietary RS Rating system. This indicator measures a stock's price performance relative to the S&P 500 (or any benchmark you choose) and converts it to a 1-99 rating scale.
How It Works
The indicator calculates weighted performance ratios across four timeframes:
40% weight: 63-day (3-month) performance
20% weight: 126-day (6-month) performance
20% weight: 189-day (9-month) performance
20% weight: 252-day (12-month) performance
This weighting emphasizes recent performance while still accounting for longer-term strength—the same methodology used by leading growth stock research services.
Rating Scale
90-99: Elite relative strength (top 10% of stocks)
80-89: Strong relative strength (top 20%)
50-79: Average performance
30-49: Below average
1-29: Weak relative strength (bottom 30%)
Features
Customizable benchmark index (default: S&P 500)
Optional moving average overlay (EMA or SMA)
Visual zones with color-coded backgrounds
Signal markers when RS crosses key thresholds (80 and 30)
Info table showing current rating, daily change, MA value, and raw score
Built-in alerts for threshold crossovers
Pine Screener Compatible
This indicator includes state-based plots specifically designed for TradingView's Pine Screener. You can screen watchlists for:
RS Above 90, 80, 70, or 50
RS Below 50 or 30
RS Above/Below its moving average
Custom thresholds using the raw RS Rating value
In the Pine Screener, select the "Screener RS Above 80" output and set it to "True" (or equals 1) to find all stocks currently above 80—not just those crossing on that bar.
Usage Tips
Growth investors typically look for stocks with RS Ratings above 80, indicating the stock is outperforming 80% of the market. Combining high RS Rating with other technical signals (breakouts, volume, moving averages) can help identify leading stocks.
Jack Dunn (Mean Reversion, Z-score + Vol Filter + Trend Filter))based on mean reversion and z score
FOR 1M XAUUSD or 5M USDJPY
High-Probability Scalper (Market Open)Market open is where volatility is real, spreads are tight, and momentum shows itself early. This scalping strategy is built specifically to operate during that window, filtering out low-quality signals that usually appear later in the session.
Instead of trading all day, the logic is restricted to the first 90 minutes after market open, where continuation moves and fast pullbacks are more reliable.
What This Strategy Does
This script looks for short-term momentum alignment using:
Fast vs slow EMA structure
RSI confirmation to avoid chasing extremes
ATR-based risk control
Session-based filtering to trade only when volume matters
It’s designed for intraday scalping, not swing trading.
Core Trading Logic
1. Market Open Filter
Trades are allowed only between 09:30 – 11:00 exchange time.
This avoids low-liquidity chop and focuses on the period where most breakouts and reversals form.
2. Trend Confirmation
Bullish bias: 9 EMA crosses above 21 EMA
Bearish bias: 9 EMA crosses below 21 EMA
This keeps trades aligned with short-term direction instead of random entries.
3. Momentum Check (RSI)
RSI is used as a quality filter, not as an overbought/oversold signal.
Long trades only when RSI is strong but not extended
Short trades only when RSI shows weakness without exhaustion
This removes late entries and reduces whipsaws.
Entries & Exits
Entries
Executed only on confirmed candles
No intrabar repainting
One position at a time
Risk Management
Stop-loss based on ATR
Take-profit calculated using a fixed risk–reward ratio
Same structure for both long and short trades
This keeps risk consistent across different symbols and volatility levels.
Why This Strategy Works Better at Market Open
Volume is highest
False breakouts are fewer
EMA crosses have follow-through
RSI behaves more cleanly
By not trading all day, the strategy avoids most of the noise that kills scalpers.
Best Use Cases
Index futures
High-liquidity stocks
Major crypto pairs during active sessions
1m to 5m timeframes
What This Strategy Is NOT
Not a martingale
Not grid-based
Not designed for ranging markets
Not a “set and forget” system
It’s a controlled scalping template meant for disciplined execution.
How to Use It Properly
Test on multiple symbols
Adjust ATR length for volatility
Tune RSI ranges per market
Always forward-test before live alerts
Final Note
This strategy focuses on structure, timing, and risk, not indicator stacking.
If you trade the open, this gives you a clear framework instead of emotional entries.
If you want:
Alerts
Session customization
News filters
Partial exits
You can extend this logic without breaking the core system.
Adaptive ML Trailing Stop [BOSWaves]Adaptive ML Trailing Stop – Regime-Aware Risk Control with KAMA Adaptation and Pattern-Based Intelligence
Overview
Adaptive ML Trailing Stop is a regime-sensitive trailing stop and risk control system that adjusts stop placement dynamically as market behavior shifts, using efficiency-based smoothing and pattern-informed biasing.
Instead of operating with fixed ATR offsets or rigid trailing rules, stop distance, responsiveness, and directional treatment are continuously recalculated using market efficiency, volatility conditions, and historical pattern resemblance.
This creates a live trailing structure that responds immediately to regime change - contracting during orderly directional movement, relaxing during rotational conditions, and applying probabilistic refinement when pattern confidence is present.
Price is therefore assessed relative to adaptive, condition-aware trailing boundaries rather than static stop levels.
Conceptual Framework
Adaptive ML Trailing Stop is founded on the idea that effective risk control depends on regime context rather than price location alone.
Conventional trailing mechanisms apply constant volatility multipliers, which often results in trend suppression or delayed exits. This framework replaces static logic with adaptive behavior shaped by efficiency state and observed historical outcomes.
Three core principles guide the design:
Stop distance should adjust in proportion to market efficiency.
Smoothing behavior must respond to regime changes.
Trailing logic benefits from probabilistic context instead of fixed rules.
This shifts trailing stops from rigid exit tools into adaptive, regime-responsive risk boundaries.
Theoretical Foundation
The indicator combines adaptive averaging techniques, volatility-based distance modeling, and similarity-weighted pattern analysis.
Kaufman’s Adaptive Moving Average (KAMA) is used to quantify directional efficiency, allowing smoothing intensity and stop behavior to scale with trend quality. Average True Range (ATR) defines the volatility reference, while a K-Nearest Neighbors (KNN) process evaluates historical price patterns to introduce directional weighting when appropriate.
Three internal systems operate in tandem:
KAMA Efficiency Engine : Evaluates directional efficiency to distinguish structured trends from range conditions and modulate smoothing and stop behavior.
Adaptive ATR Stop Engine : Expands or contracts ATR-derived stop distance based on efficiency, tightening during strong trends and widening in low-efficiency environments.
KNN Pattern Influence Layer : Applies distance-weighted historical pattern outcomes to subtly influence stop placement on both sides.
This design allows stop behavior to evolve with market context rather than reacting mechanically to price changes.
How It Works
Adaptive ML Trailing Stop evaluates price through a sequence of adaptive processes:
Efficiency-Based Regime Identification : KAMA efficiency determines whether conditions favor trend continuation or rotational movement, influencing stop sensitivity.
Volatility-Responsive Scaling : ATR-based stop distance adjusts automatically as efficiency rises or falls.
Pattern-Weighted Adjustment : KNN compares recent price sequences to historical analogs, applying confidence-based bias to stop positioning.
Adaptive Stop Smoothing : Long and short stop levels are smoothed using KAMA logic to maintain structural stability while remaining responsive.
Directional Trailing Enforcement : Stops advance only in the direction of the prevailing regime, preserving invalidation structure.
Gradient Distance Visualization : Gradient fills reflect the relative distance between price and the active stop.
Controlled Interaction Markers : Diamond markers highlight meaningful stop interactions, filtered through cooldown logic to reduce clustering.
Together, these elements form a continuously adapting trailing stop system rather than a fixed exit mechanism.
Interpretation
Adaptive ML Trailing Stop should be interpreted as a dynamic risk envelope:
Long Stop (Green) : Acts as the downside invalidation level during bullish regimes, tightening as efficiency improves.
Short Stop (Red) : Serves as the upside invalidation level during bearish regimes, adjusting width based on efficiency and volatility.
Trend State Changes : Regime flips occur only after confirmed stop breaches, filtering temporary price spikes.
Gradient Depth : Deeper gradient penetration indicates increased extension from the stop rather than imminent reversal.
Pattern Influence : KNN weighting affects stop behavior only when historical agreement is strong and remains neutral otherwise.
Distance, efficiency, and context outweigh isolated price interactions.
Signal Logic & Visual Cues
Adaptive ML Trailing Stop presents two primary visual signals:
Trend Transition Circles : Display when price crosses the opposing trailing stop, confirming a regime change rather than anticipating one.
Stop Interaction Diamonds : Indicate controlled contact with the active stop, subject to cooldown filtering to avoid excessive signals.
Alert generation is limited to confirmed trend transitions to maintain clarity.
Strategy Integration
Adaptive ML Trailing Stop fits within trend-following and risk-managed trading approaches:
Dynamic Risk Framing : Use adaptive stops as evolving invalidation levels instead of fixed exits.
Directional Alignment : Base execution on confirmed regime state rather than speculative reversals.
Efficiency-Based Tolerance : Allow greater price fluctuation during inefficient movement while enforcing tighter control during clean trends.
Pattern-Guided Refinement : Let KNN influence adjust sensitivity without overriding core structure.
Multi-Timeframe Context : Apply higher-timeframe efficiency states to inform lower-timeframe stop responsiveness.
Technical Implementation Details
Core Engine : KAMA-based efficiency measurement with adaptive smoothing
Volatility Model : ATR-derived stop distance scaled by regime
Machine Learning Layer : Distance-weighted KNN with confidence modulation
Visualization : Directional trailing stops with layered gradient fills
Signal Logic : Regime-based transitions and controlled interaction markers
Performance Profile : Optimized for real-time chart execution
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Tight adaptive trailing for short-term momentum control
15 - 60 min : Structured intraday trend supervision
4H - Daily : Higher-timeframe regime monitoring
Suggested Baseline Configuration:
KAMA Length : 20
Fast/Slow Periods : 15 / 50
ATR Period : 21
Base ATR Multiplier : 2.5
Adaptive Strength : 1.0
KNN Neighbors : 7
KNN Influence : 0.2
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive chop or overreaction : Increase KAMA Length, Slow Period, and ATR Period to reinforce regime filtering.
Stops feel overly permissive : Reduce the Base ATR Multiplier to tighten invalidation boundaries.
Frequent false regime shifts : Increase KNN Neighbors to demand stronger historical agreement.
Delayed adaptation : Decrease KAMA Length and Fast Period to improve responsiveness during regime change.
Adjustments should be incremental and evaluated over multiple market cycles rather than isolated sessions.
Performance Characteristics
High Effectiveness:
Markets exhibiting sustained directional efficiency
Instruments with recurring structural behavior
Trend-oriented, risk-managed strategies
Reduced Effectiveness:
Highly erratic or event-driven price action
Illiquid markets with unreliable volatility readings
Integration Guidelines
Confluence : Combine with BOSWaves structure or trend indicators
Discipline : Follow adaptive stop behavior rather than forcing exits
Risk Framing : Treat stops as adaptive boundaries, not forecasts
Regime Awareness : Always interpret stop behavior within efficiency context
Disclaimer
Adaptive ML Trailing Stop is a professional-grade adaptive risk and regime management tool. It does not forecast price movement and does not guarantee profitability. Results depend on market conditions, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates structure, volatility, and contextual risk management.
TwinSmooth ATR Bands | QuantEdgeBTwinSmooth ATR Bands | QuantEdgeB
🔍 Overview
TwinSmooth ATR Bands | QuantEdgeB is a dual-smoothing, ATR-adaptive trend filter that blends two complementary smoothing engines into a single baseline, then builds dynamic ATR bands around it to detect decisive breakouts. When price closes above the upper band it triggers a Long regime; when it closes below the lower band it flips to Short—otherwise it stays neutral. The script enhances clarity with regime-colored candles, an active-band fill, and an optional on-chart backtest table.
✨ Key Features
1. 🧠 Twin-Smooth Baseline (Dual Engine Blend)
- Computes two separate smoothed baselines (a slower “smooth” leg + a faster “responsive” leg).
- Blends them into a single midpoint baseline for balanced stability + speed.
- Applies an extra EMA smoothing pass to produce a clean trend_base.
2. 📏 ATR Volatility Bands
- Builds upper/lower bands using ATR × multiplier around the trend_base.
- Bands expand in volatile conditions and contract when markets quiet down—auto-adapting without manual tweaks.
3. ⚡ Clear Breakout Regime Logic
- Long when close > upperBand.
- Short when close < lowerBand.
- Neutral otherwise (no forced signals inside the band zone).
4. 🎨 Visual Clarity
- Plots only the active band (lower band in long regime, upper band in short regime).
- Fills between active band and price for instant regime context.
- Colors candles to match the current state (bullish / bearish / neutral).
- Multiple color palettes + transparency control.
💼 Use Cases
• Trend Confirmation Filter: Use the regime as a higher-confidence trend gate for entries from other indicators.
• Breakout/Breakdown Trigger: Trade closes outside ATR bands to catch momentum expansions.
• Volatility-Aware Stops/Targets: Bands naturally reflect volatility, making them useful as adaptive reference levels.
• Multi-Timeframe Alignment: Confirm higher-timeframe regime before executing on lower timeframes.
🎯 For Who
• Trend Traders who want clean regime shifts without constant whipsaw.
• Breakout Traders who prefer confirmation via ATR expansion rather than raw MA crossovers.
• System Builders needing a simple, robust “state engine” (Long / Short / Neutral) to plug into larger strategies.
• Analysts who want quick on-chart validation with a backtest table.
⚙️ Default Settings
• SMMA Length (Base Smooth Leg): 24
• TEMA Length (Base Responsive Leg): 8
• EMA Extra Smoothing: 14
• ATR Length: 14
• ATR Multiplier: 1.1
• Color Mode: Alpha
• Color Transparency: 30
• Backtest Table: On (toggleable)
• Backtest Start Date: 09 Oct 2017
• Labels: Off by default
📌 Conclusion
TwinSmooth ATR Bands | QuantEdgeB merges a dual-speed smoothing core into a single trend baseline, then wraps it with ATR-based bands to deliver clean, volatility-adjusted breakout signals. With regime coloring, active-band plotting, and optional backtest stats, it’s a compact, readable tool for spotting momentum shifts and trend continuation across any market and timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Next-Gen Market Signal Dashboard Key Features:
Trend Detection: EMA50 and EMA200 highlight bullish and bearish trends with subtle background coloring.
Momentum Indicators: RSI, MACD, and Stochastic Oscillator confirm signal strength and market momentum.
Volatility Filter: ATR ensures signals are only triggered during active market conditions.
Visual Signals: Animated triangles and colored backgrounds for LONG (green) and SHORT (red) signals.
Take Profit / Stop Loss: Automatic, elegant TP and SL lines to guide trades.
Compact Multi-Indicator Panel: Displays RSI, MACD, Stochastic, and ATR with color-coded strength indicators.
Mini-Guide: Integrated panel explanations help quickly interpret signals without confusion.
Alerts: Built-in alerts for all LONG and SHORT signals.
Trade Secrets by Pratik - Dual Intraday StrategyThe "Trade Secrets by Pratik" strategy is a high-momentum, dual-direction trading system designed to capture explosive moves after brief market pullbacks. It relies on a rigorous combination of trend-following moving averages and a strength filter.
1. Core Concept
The strategy identifies "Clean Pullbacks"—brief pauses in a strong trend where the price stays strictly away from the short-term average (10 EMA). This indicates extreme momentum, as buyers (in an uptrend) or sellers (in a downtrend) are too aggressive to allow a deeper correction.
2. Technical Filters
Trend Direction: Price must be above both 10 and 35 EMAs for Buys, and below both for Sells.
Strength Filter (RSI): Requires an RSI > 60 for Longs (to ensure high demand) and RSI < 40 for Shorts (to ensure heavy selling pressure).
3. Trade Execution
The Setup: Look for a "Floating Candle"—a Red candle for Buys or a Green candle for Sells that does not touch the 10 EMA.
The Trigger: A trade is entered only if the very next candle breaks the "Setup Candle's" high (Buy) or low (Sell).
Risk-Reward: Aim for a fixed 1:3 Ratio, ensuring that one winner covers three losing trades.
4. Safety Logic
The system includes a "No-Same-Candle-Exit" rule, preventing the script from triggering a Stop Loss on the same bar as the Entry. This filters out immediate price "whipsaws" and ensures the trade has room to develop.
S&D Trend Pullback StrategyThis is simple indicator for myself to alert me when in trend pullback and entry.
Use in M5 chart.
SL put 30-50pips
TP can set 30-90pips
UVOL Thrust TrackerUVOL Thrust Tracker identifies institutional breadth thrusts using NYSE up-volume as a percentage of total volume (USI:UVOL / USI:TVOL), plotted directly on price.
The indicator highlights:
TRUE 90% UVOL thrusts (rare, high-conviction breadth events)
Surrogate thrust clusters (multi-day 80–89% participation)
Cluster failures (momentum that fails to expand)
Structural thrust failures (2022-style false starts)
A regime filter based on the chart symbol’s moving averages separates bull vs bear environments, dynamically adjusting thresholds and failure logic.
This tool is designed for regime confirmation and risk management, not short-term entries. TRUE thrusts typically confirm trend continuation, while failures warn when breadth support breaks down.
Note: This indicator is intended for regime and risk assessment, not precise entries or exits.
