Jack Dunn (Mean Reversion, Z-score + Vol Filter + Trend Filter))based on mean reversion and z score
FOR 1M XAUUSD or 5M USDJPY
移动平均线
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.
A-Share Broad-Based ETF Dual-Core Timing System1. Strategy Overview
The "A-Share Broad-Based ETF Dual-Core Timing System" is a quantitative trading strategy tailored for the Chinese A-share market (specifically for broad-based ETFs like CSI 300, CSI 500, STAR 50). Recognizing the market's characteristic of "short bulls, long bears, and sharp bottoms," this strategy employs a "Left-Side Latency + Right-Side Full Position" dual-core driver. It aims to safely bottom-fish during the late stages of a bear market and maximize profits during the main ascending waves of a bull market.
2. Core Logic
A. Left-Side Latency (Rebound/Bottom Fishing)
Capital Allocation: Defaults to 50% position.
Philosophy: "Buy when others fear." Seeks opportunities in extreme panic or momentum divergence.
Entry Signals (Triggered by any of the following):
Extreme Panic: RSI Oversold (<30) + Price below Bollinger Lower Band + Bullish Candle Close (Avoid catching falling knives).
Oversold Bias: Price deviates more than 15% from the 60-day MA (Life Line), betting on mean reversion.
MACD Bullish Divergence: Price makes a new low while MACD histogram does not, accompanied by strengthening momentum.
B. Right-Side Full Position (Trend Following)
Capital Allocation: Aggressively scales up to Full Position (~99%) upon signal trigger.
Philosophy: "Follow the trend." Strike heavily once the trend is confirmed.
Entry Signals (All must be met):
Upward Trend: MACD Golden Cross + Price above 20-day MA.
Breakout Confirmation: CCI indicator breaks above 100, confirming a main ascending wave.
Volume Support: Volume MACD Golden Cross, ensuring price increase is backed by volume.
C. Smart Risk Control
Bear Market Exhaustion Exit: In a bearish trend (MA20 < MA60), the strategy does not "hold and hope." It immediately liquidates left-side positions upon signs of rebound exhaustion (breaking below MA20, touching MA60 resistance, or RSI failure).
ATR Trailing Stop: Uses Average True Range (ATR) to calculate a dynamic stop-profit line that rises with the price to lock in profits.
Hard Stop Loss: Forces a stop-loss if the left-side bottom fishing fails and losses exceed a set ATR multiple, preventing deep drawdowns.
3. Recommendations
Target Assets: High liquidity broad-based ETFs such as CSI 300 ETF (510300), CSI 500 ETF (510500), ChiNext ETF (159915), STAR 50 ETF (588000).
Timeframe: Daily Chart.
IDAHL | QuantEdgeBIDAHL | QuantEdgeB
🔍 Overview
The IDAHL indicator builds adaptive, volatility-aware threshold bands from two separate ALMA lines—one smoothed from recent highs, the other from recent lows—then uses percentiles of those lines to define a dynamic “high/low” channel. Price crossing above or below that channel triggers clear long/short signals, with on-chart candle coloring, fills, optional labels and even a built-in backtest table.
✨ Key Features
• 📈 Dual ALMA Bands (with DEMA pre-smoothing)
o High ALMA: ALMA applied to DEMA-smoothed highs (high → DEMA(30) → ALMA).
o Low ALMA: ALMA applied to DEMA-smoothed lows (low → DEMA(30) → ALMA).
• 📊 Percentile Thresholds
o Computes a high threshold at the Xth percentile of the High ALMA over a lookback window.
o Computes a low threshold at the Yth percentile of the Low ALMA.
o Shifts each threshold forward by a small period to reduce repainting.
• ⚡ Dynamic Channel Logic
o When price closes above the high percentile line, the “final” threshold flips down to the low percentile line (and vice versa), creating an adaptive channel that only moves when the outer bound is violated.
o Inside the channel, the threshold holds its last value to avoid whipsaw.
• 🎨 Visual & Alerts
o Plots the two percentile lines and fills between them with a color that reflects the current regime (green for long, yellow for neutral, orange for short).
o Colors your candles to match the active signal.
o Optional “Long”/“Short” labels on confirmed flips.
o Alert conditions fire on each long/short crossover.
• 📊 On-Chart Backtest Metrics
o Toggle on a small performance table—complete with win-rate, net P/L, drawdown—from your chosen start date, without any extra code.
⚙️ How It Works
1. Adaptive Smoothing (ALMA)
o Uses ALMA (Arnaud Legoux Moving Average) for smooth, low-lag filtering. In this script, the inputs are additionally pre-smoothed with DEMA(30) to reduce noise before ALMA is applied—improving stability on highs/lows.
2. Percentile Lines
o The High ALMA series feeds a linear-interpolation percentile function to generate the upper bound; the Low ALMA produces the lower bound.
o These lines are offset by a small look-ahead (X bars) to reduce repaint behavior.
3. Channel Logic
o Breakout Flip: When the selected source (default: Close) closes above the upper bound, the active threshold “jumps” to the lower bound—locking in a new channel until price next crosses.
o Breakdown Flip: Conversely, a close below the lower bound flips the threshold to the upper bound.
4. Signal Generation
o Long while the source is above the current “final” threshold.
o Short while below.
o Neutral inside the channel before any flip.
5. Visualization & Alerts
o Dynamic fills between the two percentile lines change hue as the regime flips.
o Candles adopt the regime color.
o Optional pinned “Long”/“Short” labels at flip bars.
o Alerts on every signal crossover of the zero-based regime line.
6. Backtest Table
o From your chosen start date, a mini-table displays cumulative P/L, win rate and drawdown for this strategy—handy for quick in-chart validation.
🎯 Who Should Use It
• Breakout Traders hunting for adaptive channels that auto-recenter on new highs/lows.
• Volatility Traders who want thresholds that expand and contract with market turbulence.
• Trend-Chasers seeking a fresh take on high/low channels with built-in smoothing.
• Systematic Analysts who appreciate on-chart backtesting without leaving TradingView.
⚙️ Default Settings
• ALMA Length: 14
• Percentile Length: 35 bars
• Percentile Lookback Period (offset): 4 bars
• Upper Percentile: 92%
• Lower Percentile: 50%
• Threshold Source: Close
• Visuals: Candle coloring on, labels off by default, “Strategy” palette
• Backtest Table: on by default (toggleable)
• Start Date (Backtest): 09 Oct 2017
📌 Conclusion
IDAHL blends two smooth, low-lag ALMA filters (fed by DEMA-smoothed highs/lows) with percentile-based channel construction for a self-rewiring high/low envelope. It gives you robust breakout/breakdown signals, immediate visual context via colored fills and candles, optional labels, alerts, and even performance stats—everything you need to spot and confirm regime shifts in one compact script.
🔹 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.
EMA 8/21 & SMA 50/200 - NDAThese are a useful combination of Moving Averages.
I use these on the Daily chart.
There;s not much to add here - happy charting!
Bens Platypus Dual VWAP_Rolling 7D vs Weekly AnchoredBen’s Platypus Dual VWAP: Rolling 7D vs Weekly Anchored (optional σ bands)
Weekly-anchored VWAP resets on Monday (exchange time). That makes sense for assets tied to a traditional weekly “market open,” but BTC trades 24/7 and often doesn’t respect Monday as a real regime boundary—so the Monday reset can create a mechanical jump that looks like signal but is just arithmetic. If you drive entries/exits off that reset, some algos will get spooked into early entries, fake “stretch” readings, or sudden mean shifts that aren’t actually market behaviour.
This indicator fixes that by plotting:
• Rolling 7D VWAP (thick aqua): a continuous trailing VWAP that does not reset on Mondays, giving you a stable mean for reversion logic.
• Weekly Anchored VWAP (thin purple): kept for context, so you can see the reset effect rather than accidentally trade it.
Result: you can visually compare the two means and quantify when “weekly structure” is useful versus when it’s just a calendar artifact on a 24/7 market.
Ichimoku MTF Heatmap W/ adj alert placement W and D cloud ALERTShows green FLAG 50 bars back when Daily and Weekly Cloud metrics are ACTIVE.
rosh Swift ALGO-X based on ema for xauusd scalping use with original settings, assured 100 pips per day
WN 5-20-50 SMA Setup (Discrete Lines = SL TP) Multiple Entries Pretty Simple Script as I got this idea from a YouTuber that showed us how to use AI to make TradingView Indicators.
When the 5 day Simple Moving Average Goes Above the 20 day Simple Moving Average it issues a BUY Signal when the Trend itself is over the 50 day Simple Moving Average.
When the 5 day Simple Moving Average Goes Below the 20 day Simple Moving Average it issues a SELL Signal when the Trend itself is under the 50 day Simple Moving Average.
The Green Cloud Represents price over the 50 day Simple Moving Average. BUY signals will only show up in the green cloud.
The Red Cloud Represents price under the 50 day Simple Moving Average. SELL signals will only show up in the green cloud.
The lines represent Stop Loss and two Take Profit Levels. Take Profit 1 is 1.5x the stop loss and Take Profit 2 is 3x the Stop Loss.
This version of the Script has multiple Trend signals for entries so you can scale into a trade when the Trend is being aggressive.
SB A / A++ ALERT ENGINE (Alerts Only)SB A / A++ Alert Engine
Session-Based Level Rejection Strategy (Automation-Ready)
Overview
The SB A / A++ Alert Engine is a rules-based TradingView indicator designed to identify high-probability institutional-style reversal trades using Stacey Burke–inspired concepts such as previous day levels, session structure, opening ranges, and round numbers.
This tool is alerts-only by design, making it ideal for:
TradingView alerts
Webhook automation
Telegram / Discord signal delivery
External trade execution systems
It does not repaint and evaluates signals on confirmed bar close only.
---
Core Trading Idea
Price frequently reacts at important reference levels during active trading sessions.
This script looks for rejection + confirmation at those levels and grades setups based on confluence and candle quality.
Only A-grade and A++-grade setups are alerted.
---
What the Script Detects
📌 Key Levels (Confluence Engine)
Previous Day High / Low
Initial Balance (Mon–Tue range, active Wed–Fri)
Session Opening Range (first hour of London / NY)
Round Numbers (configurable tick spacing)
Each level touched contributes to confluence — without double-counting the same zone.
---
🕒 Session Control
Signals are only allowed during:
London Session
New York Session
Includes:
Session resets
Max alerts per session
Cooldown between signals
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🔎 Candle Confirmation
Valid signals require clear rejection behavior, such as:
Bullish / Bearish Engulfing candle
Strong Pin Bar (wick ≥ 2× body)
---
🧠 Trade Grades
A Trade
Valid session
ATR percentile filter passed
≥ 1 level of confluence
Directional rejection
A++ Trade
All A-Trade rules
Strong confirmation candle (engulf or pin)
≥ 2 independent confluence zones
Grades are displayed visually and included in alert payloads.
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📊 Volatility Filter (ATR Percentile)
Instead of fixed ATR thresholds, the script uses an ATR percentile rank, ensuring trades only trigger when volatility is above normal for that market.
This adapts automatically across:
Forex
Indices
Futures
Crypto
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Visual Output
▲ Green / Lime triangles → LONG (A / A++)
▼ Orange / Red triangles → SHORT (A / A++)
Color intensity reflects trade grade
Optional session shading (if enabled)
---
Alerts & Automation
All alerts are webhook-ready and structured for automation.
Each alert includes:
Symbol
Timeframe
Direction (LONG / SHORT)
Trade grade (A or A++)
Confluence count
Entry price (close of signal bar)
Designed to integrate with:
Telegram bots
Trade execution bridges
Risk management engines
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What This Script Is (and Is Not)
✅ IS
A high-quality signal engine
Non-repainting
Automation-friendly
Institutional level-based logic
❌ IS NOT
A scalping indicator
A prediction tool
A “trade every candle” system
This tool favors patience, structure, and quality over frequency.
---
Recommended Usage
Timeframes: M5 – M15
Best markets: FX majors, indices, liquid crypto
Combine with your own execution, risk, and trade management rules
---
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice. Always test on demo or paper trading before using live capital.
PM/PW/PD/OVN/CD Highs & Lows with prices+ EMAsPM/PW/PD/OVN/CD Highs & Lows with prices
+
3 customizable EMAs (def 12/34/55)
Early Trend Warning Using MTF AnalysisAs an active trader and software professional, I build my own indicators. I built this one today which I want to share with fellow traders.
If you are a trend trader then HTF/MTF analysis is very critical. It is virtually impossible to constantly track multiple tickers all the time. One should not take a buy trade when MTF is bearish and vice versa. This indicator solves this problem.
The EMA Trend Warning indicator helps traders detect potential trend changes early by analyzing price interactions with multi-timeframe Exponential Moving Averages (EMAs) and their momentum. It sends instant alerts when price crosses above or below EMAs with supporting momentum, making it easier to capture bullish or bearish moves.
The EMA Trend Warning indicator detects potential trend changes by monitoring price against 14-period EMAs on multiple timeframes: 15-minute, 30-minute, and 1-hour charts. It sends alerts when the price crosses above or below the EMA with supporting momentum, helping traders identify early bullish or bearish signals.
How It Works:
1. Calculates 14-period EMA on 15m, 30m, and 1H charts.
2. Computes EMA slopes to determine momentum direction.
3. BUY alert triggers when price crosses above the 15m EMA and at least one EMA slope is upward.
4. SELL alert triggers when price crosses below the 15m EMA and at least one EMA slope is downward.
5. Alerts fire once per bar and track previous state to avoid repeated notifications.
Features:
1. Multi-timeframe EMA monitoring.
2. Momentum confirmation with EMA slopes.
3. Instant BUY/SELL alerts.
4. Tracks previous trend state to prevent alert spam.
Benefits:
1. Detects trend changes early for better entry timing.
2. Confirms trend across multiple timeframes.
3. Saves time with automated alerts.
4. Helps traders align trades with market momentum.
Please consider this indicator as EARLY WARNING ONLY. Take trade based on multiple confluences post receiving any warning. I have tested it on BTCUSD since yesterday, multiple warning alerts were 100% perfect.
Multi-Fractal Trading Plan [Gemini] v22Multi-Fractal Trading Plan
The Multi-Fractal Trading Plan is a quantitative market structure engine designed to filter noise and generate actionable daily strategies. Unlike standard auto-trendline indicators that clutter charts with irrelevant data, this system utilizes Fractal Geometry to categorize market liquidity into three institutional layers: Minor (Intraday), Medium (Swing), and Major (Institutional).
This tool functions as a Strategic Advisor, not just a drawing tool. It calculates the delta between price and structural pivots in real-time, alerting you when price enters high-probability "Hot Zones" and generating a live trading plan on your dashboard.
Core Features
1. Three-Tier Fractal Engine The algorithm tracks 15 distinct fractal lengths simultaneously, aggregating them into a clean hierarchy:
Minor Structure (Thin Lines): Captures high-frequency volatility for scalping.
Medium Structure (Medium Lines): Identifies significant swing points and intermediate targets.
Major Structure (Thick Lines): Maps the "Institutional" defense lines where trend reversals and major breakouts occur.
2. The Strategic Dashboard A dynamic data panel in the bottom-right eliminates analysis paralysis:
Floor & Ceiling Targets: Displays the precise price levels of the nearest Support and Resistance.
AI Logic Output: The script analyzes market conditions to generate a specific command, such as "WATCH FOR BREAKOUT", "Near Lows (Look Long?)", or "WAIT (No Setup)".
3. "Hot Zone" Detection Never miss a critical test of structure.
Dynamic Alerting: When price trades within 1% (adjustable) of a Major Trend Line, the indicator’s labels turn Bright Yellow and flash a warning (e.g., "⚠️ WATCH: MAJOR RES").
Focus: This visual cue highlights the exact moment execution is required, reducing screen fatigue.
4. The Quant Web & Markers
Pivot Validation: Deep blue fractal markers (▲/▼) identify the exact candles responsible for the structure.
Inter-Timeframe Web: Faint dotted lines connect Minor pivots directly to Major pivots, visualizing the "hidden" elasticity between short-term noise and long-term trend anchors.
5. Enterprise Stability Engine Engineered to solve the "Vertical Line" and "1970 Epoch" glitches common in Pine Script trend indicators. This engine is optimized for Futures (NQ/ES), Forex, and Crypto, ensuring stability across all timeframes (including gaps on ETH/RTH charts).
Operational Guide
Consult the Dashboard: Before executing, check the "Strategy" output. If it says "WAIT", the market is in chop. If it says "WATCH FOR BOUNCE", prepare your entry criteria.
Monitor Hot Zones: A Yellow Label indicates price is testing a major liquidity level. This is your signal to watch for a rejection wick or a high-volume breakout.
Utilize the Web: Use the faint web lines to find "confluence" where a short-term pullback aligns with a long-term trend line.
Configuration
Show History: Toggles "Ghost Lines" (Blue) to display historical structure and broken trends.
Fractal Points: Toggles the geometric pivot markers.
Hot Zone %: Adjusts the sensitivity of the Yellow Warning system (Default: 1%).
Max Line Length: A noise filter that removes stale or "spiderweb" lines that are no longer statistically relevant.
Dynamic EMA Trend Table [Customizable]Overview
The Dynamic EMA Trend Table is a comprehensive dashboard designed to give traders an instant overview of the market trend across five distinct Exponential Moving Averages (EMAs). Instead of cluttering your chart with multiple lines, this script organizes the data into a clean, customizable table, allowing you to assess trend alignment at a glance.
How It Works
This indicator calculates five user-defined EMAs (defaulting to the popular 5, 20, 50, 100, and 200 periods). It then compares the Current Price against each EMA value to determine the immediate trend status:
Bullish State: When the current price is above the specific EMA, the table cell turns Green (customizable).
Bearish State: When the current price is below the specific EMA, the table cell turns Red (customizable).
This logic allows swing traders and scalpers to instantly see if the asset is in a strong uptrend (all cells Green), a strong downtrend (all cells Red), or a consolidation phase (mixed colors).
Key Features
Fully Customizable Periods: Change the length of all 5 EMAs to fit your specific strategy (e.g., Fibonacci numbers or standard Swing Trading settings).
Dynamic UI: Position the table anywhere on the screen (Top/Bottom/Left/Right) and adjust the size to fit your screen resolution.
Visual Cleanliness: You can choose to show the table only, or toggle the "Show EMAs on Chart" option to plot the actual lines on your chart.
Smart Coloring: The lines on the chart (if enabled) inherit the same color logic as the table—turning Green when price is above them and Red when price is below.
Settings & Configuration
Price Source: Select Close, High, Low, etc. (Default is Close).
Table Position & Size: Customize where the dashboard appears.
EMA Lengths: Set your 5 preferred lookback periods.
Color Theme: Fully adjustable colors for Bullish, Bearish, Neutral, and Background elements to match your chart theme (Dark/Light mode friendly).
Use Case Example
Trend Confirmation: A trader looking for a "Buy" entry might wait for the short-term EMAs (5 and 20) and the medium-term EMA (50) to all turn Green in the table before entering.
Support/Resistance Watch: By quickly glancing at the values in the table, you can see exactly where the 200 EMA sits without needing to scroll back on your chart to find the line.
Universal Moving Average🙏🏻 UMA (Universal Moving Average) represents the most natural and prolly ‘the’ final general universal entity for calculating rolling typical value for any type of time-series. Simply via different weighting schemes applied together, it encodes:
Location of each datapoint in corresponding fields (price, time, volume)
Informational relevance of each datapoint via using windowing functions that are fundamental in nature and go beyond DSP inventions & approximations
Innovation in state space (in our case = volatility)
The real beauty of this development: being simply a weighting scheme that can be applied to anything: be it weighted median , weighted quantile regression, or weighted KDE , or a simple weighted mean (like in this script). As long as a method accepts weights, you can harness the power of this entity. It means that final algorithmic complexity will match your initial tool.
As a moving ‘average’ it beats ALMA, KAMA, MAMA, VIDYA and all others because it is a simple and general entity, and all it does is encoding ‘all’ available information. I think that post might anger a lot of people, because lotta things will be realized as legacy and many paywalls gonna be ignored, specially for the followers of DSP cult, the ones who yet don’t understand that aggregated tick data is not a signal omg, it’s a completely different type of time series where your methods simply don’t fit even closely. I am also sorry to inform y’all, that spectral analysis is much closer to state-space methods in spirit than to DSP. But in fact DSP is cool and I love it, well for actual signals xD
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Weights explained & how to use them: as I already said, the whole thing is based on combining different set of weights, and you can turn them on/off in script settings. Btw I've set em up defaults so you can use the thing on price data out of the box right away.
Price, Time, Volume weights: encode location of every datapoint in Price & TIme & Volume field
Howtouse: u have to disable one weight that corresponds to the field you apply UMA to. E.g if you apply UMA to prices, you turn off price weighting And turn on time and volume weighting. Or if you apply UMA to volume delta, you turn off volume weighting And turn on price and time weighting.
Higher prices are more important, this asymmetry is confirmed and even proved by the fact that prices can’t be negative (don’t even mention that incorrect rollover on CL contract in 2k20...).
Signal weights: encode actuality/importance/relevance of datapoints.
Howtouse: in DSP terms, it provides smoothing, but also compensates for the lag it introduces. This smoothness is useful if you use slope reversals for signal generation aka watching peaks and valleys in a moving average shape. It's also better to perturb smoothed outputs with this , this way you inject high freq content back, But in controlled way!
Signal = information.
The fundamental universal entity behind so-called “smoothing” in DSP has nothing to do with signals and goes eons beyond DSP. This is simply about measuring the relevance of data in time.
First, new datapoints need some time to be “embedded” into the timeline, you can think of it as time proof, kinda stuff needs time to be proved, accepted; while earliest datapoints lose relevance in time.
Second, along with the first notion, at the same time there’s the counter notion that simply weights new data more, acting as a counterweight from the down-weighting of the latest datapoints introduced by the first notion.
The first part can be represented as PDF of beta(2, 2) window (a set of weights in our case). It’s actually well known as the Welch window, that lives in between so called statistical and DSP worlds, emerges in multiple contexts. Mainstream DSP users tho mostly don’t use this one, they use primitive legacy windowing function, you can find all kinds on this wiki page.
Now the second part, where DSP adepts usually stop, is to introduce the second compensating windowing function. Instead they try to reduce window size, or introduce other kinds of volatility weights, do some tricks, but it ain’t provides obviously. The natural step here is to simply use the integral of the initial window; if the initial window is beta(2, 2) then what we simply need is CDF of beta(2, 2), in fact the vertically inverted shape of it aka survival function . That’s it bros. Simply as that.
When both of these are applied you have smth magical, your output becomes smooth and yet not lagging. No arbitrary windowing functions, tricks with data modification etc
Why beta(2, 2)? It naturally arises in many contexts, it’s based on one of the most fundamental functions in the universe: x^2. It has finite support. I can talk more bout it on request, but I am absolutely sure this is it.
^^ impulse response of the resulting weighs together (green) compared with uniform weights aka boxcar (red). Made with this script .
Weighing by state: encodes state-space innovation of each datapoint, basically magnitude of changes, strength of these changes, aka volatility.
Howtouse: this makes your moving average volatility aware in proper math ways. The influence of datapoints will be stronger when changes are stronger. This is weighting by innovations, or weighting by volatility by using squared returns.
Why squared returns? They encode state‑space innovations properly because the innovation of any continuous‑time semimartingale is about its quadratic variation, and quadratic variation is built from squared increments, not absolute increments.
Adaptive length is not the right way to introduce adaptivity by volatility xD. When you weight datapoints by squared returns you’re already dynamically varying ‘effective’ data size, you don’t need anything else.
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It’s all good, progress happens, that’s how the Universe works, that's how Universal Moving Average works. Time to evolve. I might update other scripts with this complete weighting scheme, either by my own desire or your request.
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∞
cd_VW_Cx IMPROVED - Quant VWAP System: Regime, Magnets & Z-ScoQuant VWAP System: Regime, Magnets & Z-Score Matrix
This indicator is a comprehensive Quantitative Trading System designed to move beyond simple support and resistance. Instead of static lines, it uses Statistical Probability (Z-Score) and Standard Deviation to define the current market regime, identify institutional value zones, and project high-probability liquidity targets.
It is engineered for Day Traders and Scalpers (Crypto & Futures) who need to know if the market is Trending, Ranging, or preparing for a Breakout.
1. The "Regime" System (Standard Deviation Bands)
The core engine anchors a VWAP (Volume Weighted Average Price) to your chosen timeframe (Daily, Weekly, or Monthly) and projects volatility bands based on market variance.
The Trend Zone (Inner Band / 1.0 SD): This is the "Fair Value" zone. In a healthy trend, price will pull back into this zone and hold. A hold here signals a high-probability continuation (Trend Following).
The Reversion Zone (Outer Band / 2.0 SD): This represents a statistical extreme. Price rarely sustains movement beyond 2 Standard Deviations without a reversion. A touch of this band signals "Overbought" or "Oversold" conditions.
2. Liquidity Magnets (Virgin VWAPs)
The script automatically tracks "Unvisited VWAPs" from previous sessions. These are price levels where significant volume occurred but have not yet been re-tested.
The Logic: Algorithms often target these "open loops." The script visualizes them as Blue Dashed Lines with price tags.
Smart Scaling (Anti-Scrunch): Includes a custom "Ghost Engine" that automatically hides or "ghosts" magnets that are too far away. This prevents your chart from being squashed (scrunched) on lower timeframes, keeping your candles perfectly readable while still tracking targets in the background.
3. The Quant Matrix (Dashboard)
A real-time Heads-Up Display (HUD) that interprets the data for you:
Regime: Detects Volatility Squeezes. If the bands compress, it signals "⚠ SQUEEZE", warning you to stop mean-reversion trading and prepare for an explosive breakout.
Bias: Color-coded Trend Direction (Bullish/Bearish) based on VWAP slope.
Signal: actionable text prompts such as "BUY DIP" (Trend Following), "FADE EXT" (Mean Reversion), or "PREP BREAK" (Squeeze).
4. Visual Intelligence
Bold Day Separators: Clear, vertical dotted dividers with Date Stamps to instantly separate trading sessions.
Dynamic Labels: Floating labels on the right axis identify exactly which deviation level is which, preventing chart confusion.
How to Use
Strategy A: The Trend Pullback (continuation)
Check Matrix: Ensure Bias is BULLISH (Green).
Wait: Allow price to pull back into the Inner Band (Dark Green Zone).
Trigger: If price holds the Center VWAP or the -1.0 SD line, enter Long.
Target: The next Liquidity Magnet above or the +2.0 SD band.
Strategy B: The Reversion Fade (Counter-Trend)
Check Matrix: Ensure price is labeled "EXTREME" or Signal says "FADE EXT".
Trigger: Price touches or pierces the Outer Band (2.0 SD).
Action: Enter counter-trend (Short) with a target back to the Center VWAP (Mean Reversion).
Strategy C: The Magnet Target
Identify a "MAGNET" line (Blue Dashed) near current price.
These act as high-probability Take Profit levels. Price will often rush to these levels to "close the loop" before reversing.
Settings
Anchor: Daily (default), Weekly, or Monthly.
Magnet Focus Range: Adjusts how aggressively the script hides distant magnets to fix chart scaling (Default: 2%).
Visuals: Fully customizable colors, label sizes, and dashboard position.
Witch-Fire ALMA signals: Dynamic Liquidity & Trend GlowThe Witch-Fire ALMA is a high-precision trend bias and liquidity mapping tool designed for price action traders and Smart Money practitioners. Unlike traditional indicators that clutter your chart with lagging signals, this script provides a "clean-yet-powerful" visual anchor to help you stay on the right side of the market while identifying key Points of Interest (POIs).
At its core, the script utilizes an optimized Arnaud Legoux Moving Average (ALMA). Known for its superior ability to balance smoothness and responsiveness, the ALMA effectively filters out market noise and "whipsaws" that often plague standard EMAs.
Key Features:
The Witch-Fire Glow: A neon-styled ALMA line that shifts between Bullish Green and Bearish Red. The white core provides surgical precision for price intersection, while the outer glow visualizes the strength and dominance of the current trend.
Scaled Liquidity Levels: Automatically maps Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL). These levels are dynamic—they scale proportionally with your ALMA settings. This ensures that the liquidity zones you see are always relevant to the trend cycle you are analyzing.
Strategic Bias Background: A subtle background tint provides an instant psychological filter. Only look for Longs in the green zone and Shorts in the red zone to maintain a high-probability strike rate.
How to Trade with Witch-Fire:
Identify the Bias: Look at the Fire ALMA. If the "fire" is red and the price is below the line, your bias is strictly bearish.
Watch the Sweeps: Wait for the price to "sweep" (pierce with a wick) the horizontal SSL (Green) or BSL (Red) lines.
Execution: Look for a strong rejection candle (long wick, small body) at these levels that closes back towards the ALMA line.
Best Used On: 15m, 1H, and 4H timeframes. Works exceptionally well for Crypto, Forex, and Indices.
