Trend Strength Matrix [JOAT]Trend Strength Matrix — Multi-Timeframe Confluence Analysis System
This indicator addresses a specific analytical challenge: how to efficiently compare multiple technical measurements across different timeframes while accounting for their varying scales and interpretations. Rather than managing separate indicator windows with different scales, this tool normalizes four distinct analytical approaches to a common -1 to +1 scale and presents them in a unified matrix format.
Why This Combination Adds Value
The core problem this indicator solves is analytical fragmentation. Traders often use multiple indicators but struggle with:
1. **Scale Inconsistency**: RSI ranges 0-100, MACD has no fixed range, ADX ranges 0-100 but measures strength not direction
2. **Timeframe Coordination**: Checking multiple timeframes requires switching between charts or cramming multiple indicators
3. **Cognitive Load**: Processing different indicator types simultaneously creates mental overhead
4. **Confluence Assessment**: Determining when multiple approaches agree requires manual comparison
This indicator specifically addresses these issues by creating a standardized analytical framework where different measurement approaches can be directly compared both within and across timeframes.
Originality and Technical Innovation
While the individual components (RSI, MACD, ADX, Moving Average) are standard, the originality lies in:
1. **Unified Normalization System**: Each component is mathematically transformed to a -1 to +1 scale using component-specific normalization that preserves the indicator's core characteristics
2. **Multi-Timeframe Weighting Algorithm**: Higher timeframes receive proportionally more weight (40% current, 25% next, 20% third, 15% fourth) based on the principle that longer timeframes provide more significant context
3. **Real-Time Confluence Scoring**: The composite calculation provides an instant assessment of how much the different analytical approaches agree
4. **Adaptive Visual Encoding**: The heatmap format allows immediate pattern recognition of agreement/disagreement across both indicators and timeframes
How the Components Work Together
Each component measures a different aspect of market behavior, and their combination provides a more complete analytical picture:
**Momentum Component (RSI-based)**: Measures the velocity of price changes by comparing average gains to losses
**Trend Component (MACD-based)**: Measures the relationship between fast and slow moving averages, indicating trend acceleration/deceleration
**Strength Component (ADX-based)**: Measures trend strength regardless of direction, then applies directional bias
**Position Component (MA-based)**: Measures price position relative to a reference average
The mathematical relationship between these components creates a comprehensive view:
- When all four agree (similar colors), it suggests multiple analytical approaches are aligned
- When they disagree (mixed colors), it highlights analytical uncertainty or transition periods
- The composite score quantifies the degree of agreement numerically
Detailed Component Analysis
**1. Momentum Oscillator Component**
This component transforms RSI into a centered oscillator by subtracting 50 and dividing by 50, creating a -1 to +1 range where 0 represents equilibrium between buying and selling pressure.
// Momentum calculation normalized to -1 to +1 scale
float rsi = ta.rsi(close, rsiLength)
float rsiScore = (rsi - 50) / 50
// Result: 0 at equilibrium, +1 at extreme overbought, -1 at extreme oversold
**2. Moving Average Convergence Component**
MACD is normalized by its own volatility (standard deviation) to create a bounded oscillator. This prevents the unbounded nature of MACD from dominating the composite calculation.
// MACD normalized by its historical volatility
= ta.macd(close, macdFast, macdSlow, macdSignal)
float macdStdev = ta.stdev(macdLine, 100)
float macdScore = macdStdev != 0 ? math.max(-1, math.min(1, macdLine / (macdStdev * 2))) : 0
**3. Directional Movement Component**
This combines ADX (strength) with directional movement (+DI vs -DI) to create a directional strength measurement. ADX alone shows strength but not direction; this component adds directional context.
// ADX-based directional strength
= calcADX(adxLength)
float adxStrength = math.min(adx / 50, 1) // Normalize ADX to 0-1
float adxDirection = plusDI > minusDI ? 1 : -1 // Direction bias
float adxScore = adxStrength * adxDirection // Combine strength and direction
**4. Price Position Component**
This measures price deviation from a moving average, weighted by the magnitude of deviation to distinguish between minor and significant displacements.
// Price position relative to moving average
float ma = ta.sma(close, maLength)
float maDirection = close > ma ? 1 : -1
float maDeviation = math.abs(close - ma) / ma * 10 // Percentage deviation scaled
float maScore = math.max(-1, math.min(1, maDirection * math.min(maDeviation, 1)))
Multi-Timeframe Integration Logic
The multi-timeframe system uses a weighted average that gives more influence to higher timeframes:
// Timeframe weighting system
float currentTF = composite * 0.40 // Current timeframe: 40%
float higherTF1 = composite_tf2 * 0.25 // Next higher: 25%
float higherTF2 = composite_tf3 * 0.20 // Third higher: 20%
float higherTF3 = composite_tf4 * 0.15 // Fourth higher: 15%
float multiTFComposite = currentTF + higherTF1 + higherTF2 + higherTF3
This weighting reflects the principle that higher timeframes provide more significant context for market direction, while lower timeframes provide timing precision.
What the Dashboard Shows
The heatmap displays a grid where:
Each row represents a timeframe
Each column shows one component's normalized reading
Colors indicate the value: green shades for positive, red shades for negative, gray for neutral
The rightmost column shows the composite average for that timeframe
Visual Elements
Moving Average Line — A simple moving average plotted on the price chart
Background Tint — Subtle coloring based on the composite score
Shift Labels — Markers when the composite crosses threshold values
Dashboard Table — The main heatmap display
Inputs
Calculation Parameters:
Momentum Length (default: 14)
MACD Fast/Slow/Signal (default: 12/26/9)
Directional Movement Length (default: 14)
Moving Average Length (default: 50)
Timeframe Settings:
Enable/disable multi-timeframe analysis
Select additional timeframes to display
How to Read the Display
Similar colors across a row indicate the components are showing similar readings
Mixed colors indicate the components are showing different readings
The composite percentage shows the average of all four components
Alerts
Composite crossed above/below threshold values
Strong readings (above 50% or below -50%)
Important Limitations and Realistic Expectations
This indicator displays current analytical conditions—it does not predict future price movements
Agreement between components indicates current analytical alignment, not future price direction
All four components are based on historical price data and inherently lag price action
Market conditions can change rapidly, making current readings irrelevant
Different parameter settings will produce different readings and interpretations
No combination of technical indicators can reliably predict future market behavior
Strong readings in one direction do not guarantee continued movement in that direction
The composite score reflects mathematical relationships, not market fundamentals or sentiment
This tool should be used as one input among many in a comprehensive analytical approach
Appropriate Use Cases
This indicator is designed for:
- Analytical organization and efficiency
- Multi-timeframe confluence assessment
- Pattern recognition in indicator relationships
- Educational study of how different analytical approaches relate
- Supplementary analysis alongside other methods
This indicator is NOT designed for:
- Standalone trading signals
- Guaranteed profit generation
- Market timing precision
- Replacement of fundamental analysis
- Automated trading systems
— Made with passion by officialjackofalltrades
Multitimeframe
Scalping MTF F-Bands Signals (L/S) + RSI Filter [RCOHelpline] v4Overview of Scalping MTF F-Bands Signals (L/S) + RSI Filter v4:
This indicator is a scalping / intraday signal system built on Multi-Timeframe (MTF) Fibonacci-style bands, combined with an RSI midline filter and an optional direction-lock mechanism designed to reduce repeated entries during unfavorable conditions.
The script focuses on identifying statistically stretched price areas rather than chasing momentum.
Core Concept
The indicator plots two independent Fibo Band layers (A & B).
Each layer is calculated using:
SMA (baseline)
ATR (volatility expansion)
Fibonacci-style multipliers
Both layers are calculated on user-selected higher timeframes and projected onto the current chart.
Signal Sources (A / B / BOTH)
You can choose how signals are generated:
A → Signals based only on Fibo Bands A
B → Signals based only on Fibo Bands B
BOTH → Signals require confluence between A and B
When BOTH is selected, a signal is triggered only if price simultaneously reaches valid zones on both band layers, helping filter noise.
Entry Logic
LONG
Price closes inside the Lower Zone (between Fib Band 2 and Band 3)
RSI is above the midline (default 50)
SHORT
Price closes inside the Upper Zone (between Fib Band 2 and Band 3)
RSI is below the midline (default 50)
All signals are designed to trigger on confirmed candle closes to reduce MTF instability.
Direction Lock System (Optional)
If enabled, the script locks the trade direction when a Stop Loss occurs before TP1 is reached.
This helps prevent repeated entries in the same direction during unfavorable or choppy conditions.
Unlock Logic
A locked direction can be unlocked when:
RSI crosses back over the midline
AND price closes again inside the valid Band 2–3 zone
With the optional setting enabled, a new entry may occur on the same candle as the unlock condition.
TP & Stop Logic (Price-Action Based)
This indicator uses structure-based exits, not fixed pip targets.
Before TP1
LONG → Two consecutive closes below Lower Band 3
SHORT → Two consecutive closes above Upper Band 3
After TP1
Stop automatically shifts to Break-Even
Any return to entry price closes the position
MTF & Usage Notes
The indicator relies on higher timeframe data
Signals are gated until band data is fully formed
Designed for structured price action environments
⚠️ Not recommended for:
High-impact news
Sudden volatility spikes
Extremely fast impulsive moves
PA SystemPA System
短简介 Short Description（放在最上面）
中文：
PA System 是一套以 AL Brooks 价格行为为核心的策略（Strategy），将 结构（HH/HL/LH/LL）→ 回调（H1/L1）→ 二次入场（H2/L2 微平台突破） 串成完整可回测流程，并可选叠加 BoS/CHoCH 结构突破过滤 与 Liquidity Sweep（扫流动性）确认。内置风险管理：定风险仓位、部分止盈、保本、移动止损、时间止损、冷却期。
English:
PA System is an AL Brooks–inspired Price Action strategy that chains Market Structure (HH/HL/LH/LL) → Pullback (H1/L1) → Second Entry (H2/L2 via Micro Range Breakout) into a complete backtestable workflow, with optional BoS/CHoCH structure-break filtering and Liquidity Sweep confirmation. Built-in risk management includes risk-based sizing, partial exits, breakeven, trailing stops, time stop, and cooldown.
⸻
1) 核心理念 Core Idea
中文：
这不是“指标堆叠”，而是一条清晰的价格行为决策链：
结构确认 → 回调出现 → 小平台突破（二次入场）→ 风控出场。
策略把 Brooks 常见的“二次入场”思路程序化，同时用可选的结构突破与扫流动性模块提升信号质量、减少震荡误入。
English:
This is not an “indicator soup.” It’s a clear price-action decision chain:
Confirmed structure → Pullback → Micro-range breakout (second entry) → Risk-managed exits.
The system programmatically implements the Brooks-style “second entry” concept, and optionally adds structure-break and liquidity-sweep context to reduce chop and improve trade quality.
⸻
2) 主要模块 Main Modules
A. 结构识别 Market Structure (HH/HL/LH/LL)
中文：
使用 pivot 摆动点确认结构，标记 HH/HL/LH/LL，并可显示最近一组摆动水平线，方便对照结构位置。
English:
Uses confirmed pivot swings to label HH/HL/LH/LL and optionally plots the most recent swing levels for clean structure context.
B. 状态机 Market Regime (State Machine + “Always In”)
中文：
基于趋势K强度、EMA关系与波动范围，识别市场环境（Breakout/Channel/Range）以及 Always-In 方向，用于过滤不合适的交易环境。
English:
A lightweight regime engine detects Breakout/Channel/Range and an “Always In” directional bias using momentum and EMA/range context to avoid low-quality conditions.
C. 二次入场 Second Entry Engine (H1→H2 / L1→L2)
中文：
• H1/L1：回调到结构附近并出现反转迹象
• H2/L2：在 H1/L1 后等待最小 bars，然后触发 Micro Range Breakout（小平台突破）并要求信号K收盘强度达标
这一段是策略的“主发动机”。
English:
• H1/L1: Pullback into structure with reversal intent
• H2/L2: After a minimum wait, triggers on Micro Range Breakout plus a configurable close-strength filter
This is the main “entry engine.”
D. 可选过滤器 Optional Filters (Quality Boost)
BoS/CHoCH（结构突破过滤）
中文： 可识别 BoS / CHoCH，并可要求“入场前最近 N bars 必须有同向 break”。
English: Detects BoS/CHoCH and can require a recent same-direction break within N bars.
Liquidity Sweeps（扫流动性确认）
中文： 画出 pivot 高/低的流动性水平线，检测“刺破后收回”的 sweep，并可要求入场前出现同向 sweep。
English: Tracks pivot-based liquidity levels, confirms sweeps (pierce-and-reclaim), and can require a recent sweep before entry.
E. FVG 可视化 FVG Visualization
中文： 提供 FVG 区域盒子与管理模式（仅保留未回补 / 仅保留最近N），主要用于区域理解与复盘，不作为强制入场条件（可自行扩展）。
English: Displays FVG boxes with retention modes (unfilled-only or last-N). Primarily for context/analysis; not required for entries (you can extend it as a filter/target).
⸻
3) 风险管理 Risk Management (Built-In)
中文：
• 定风险仓位：按账户权益百分比计算仓位
• SL/TP：基于结构 + ATR 缓冲，且限制最大止损 ATR 倍
• 部分止盈：到达指定 R 后减仓
• 保本：到达指定 R 后推到 BE
• 移动止损：到达指定 R 后开始跟随
• 时间止损：持仓太久不动则退出
• 冷却期：出场后等待 N bars 再允许新单
English:
• Risk-based sizing: position size from equity risk %
• SL/TP: structure + ATR buffer with max ATR risk cap
• Partial exits at an R threshold
• Breakeven at an R threshold
• Trailing stop activation at an R threshold
• Time stop to reduce chop damage
• Cooldown after exit to avoid rapid re-entries
⸻
4) 推荐使用方式 Recommended Usage
中文：
• 推荐从 5m / 15m / 1H 开始测试
• 想更稳：开启 EMA Filter + Break Filter + Sweep Filter，并提高 Close Strength
• 想更多信号：关闭 Break/Sweep 过滤或降低 Swing Length / Close Strength
• 回测时务必设置合理的手续费与滑点，尤其是期货/指数
English:
• Start testing on 5m / 15m / 1H
• For higher quality: enable EMA Filter + Break Filter + Sweep Filter and increase Close Strength
• For more signals: disable Break/Sweep filters or reduce Swing Length / Close Strength
• Use realistic commissions/slippage in backtests (especially for futures/indices)
⸻
5) 重要说明 Notes
中文：
结构 pivot 需要右侧确认 bars，因此结构点存在天然滞后（确认后不会再变）。策略逻辑尽量避免不必要的对象堆叠，并对数组/对象做了稳定管理，适合长期运行与复盘。
English:
Pivot-based structure requires right-side confirmation (inherent lag; once confirmed it won’t change). The script is designed for stability and resource-safe object management, suitable for long sessions and review.
⸻
免责声明 Disclaimer（建议原样保留）
中文：
本脚本仅用于教育与研究目的，不构成任何投资建议。策略回测结果受市场条件、手续费、滑点、交易时段、数据质量等影响显著。使用者需自行验证并承担全部风险。过往表现不代表未来结果。
English:
This script is for educational and research purposes only and does not constitute financial advice. Backtest results are highly sensitive to market conditions, fees, slippage, session settings, and data quality. Use at your own risk. Past performance is not indicative of future results.
BBands + Overbought/Oversold MarkersAdvanced Bollinger Bands indicator with overbought/oversold signals, automatic squeeze detection, and multi-timeframe (MTF) capabilities.
Retains all functions of the original Bollinger Bands indicator from TradingView with a few added features:
Overbought/Oversold Markers: Visual signals when price opens and closes outside the bands
🔴 Red Highlight & Arrow → Price opens & closes above the upper BB (potential overbought/excess momentum).
🟢 Green Highlight & Arrow → Price opens & closes below the lower BB (potential oversold/reversal).
Squeeze Detection: Automatically highlights when bandwidth reaches its lowest point (narrowest BB width) in the lookback period, signalling potential breakout zones
Multi-Timeframe Bands: Display Bollinger Bands from any timeframe on your current chart (e.g., weekly bands on a daily chart), including markers and squeeze zones
Dual Rendering MTF Modes: Choose between traditional plots (unlimited history) or smooth line drawing (~125-165 MTF bars of history)
Built-in Alerts: Set alerts for overbought conditions, oversold conditions, squeeze detection, or any combination
Fully Customizable: Adjust MA type (SMA/EMA/RMA/WMA/VWMA), standard deviation multiplier, colors, and marker styles
Perfect for: Swing traders, MTF analysis, volatility-based entries, and identifying consolidation/expansion cycles.
Realtime Buy/Sell/Delta/Volume + VTrend/HTF/ROCRealtime Buy/Sell/Delta/Volume + VTrend/HTF/ROC Table
A. Description:
This indicator provides a powerful, real-time table for traders, showing the latest buy/sell volumes, volume delta, volume trend (VTrend), higher timeframe (HTF) trend, and price rate-of-change (ROC) with visual arrows. It helps traders quickly assess market momentum, detect spikes in volume or price action, and align trades with higher timeframe trends.
Features:
1. Buy / Sell Volumes: Calculates buy and sell volume per candle based on close position within the high-low range.
2. Volume Delta (%): Shows the net difference between buy and sell volume as a percentage of total volume.
3. VTrend (Volume Trend): Compares the current candle’s close against the average of the previous N candles (default 4) and displays an arrow (↑/↓) for trend direction.
4. HTF Trend: Uses a higher timeframe EMA (default 1H, EMA 14) to show the trend direction with an arrow, helping align with larger market moves.
5. ROC (Rate of Change): Calculates price change relative to the SMA of previous N candles (default 14) and shows a percentage with an arrow for quick visual reference.
B. Real-time Alerts:
Alert 1: Bullish/Bearish volume spike in real-time.
Alert 2: MACD 15-min crossover confirmed by 1H HTF trend.
Alert 3: Delta % changes more than ±5% compared to previous candle.
Alert 4: ROC changes more than ±1% in real-time.
Customizable Table: Number of rows, font size, table position, and highlight for the current candle.
Totals Row: Displays cumulative totals for buy, sell, volume, and delta % at the bottom of the table.
C. How to Use:
1. Use the table to monitor live market activity in real-time.
2. Look for VTrend and HTF alignment with MACD/volume spikes to identify high-probability trades.
3. Use ROC to confirm price momentum or detect sudden reversals.
4. Set alerts to get instant notifications for volume or price changes.
D. Benefits:
1. Instant visualization of market strength and momentum.
2. Combines multiple indicators in one compact, easy-to-read table.
3. Real-time alerts help you act quickly without staring at charts constantly.
5. Perfect for day traders and scalpers who want to combine volume, delta, trend, and momentum analysis in one tool.
Dynamic Stoch200+MACD+Gann Confluence (Cardinal + Ordinal)If you're scrolling through hundreds of indicators on TradingView looking for a reliable edge, here's why this one stands out and deserves a spot on your chart:Ultra-High-Conviction Reversal Signals (Rare but Powerful)
Most indicators spam signals and repaint. This one requires four independent confluences to fire:Hidden bullish/bearish divergences on a very long-period Stochastic (200) – catches major cycle turns, not noise.Matching hidden divergences on MACD histogram – confirms momentum shift.A strong directional candle (close in top/bottom 20% of range) – filters weak wicks.
Price within ~1.75% of a dynamic Gann Square of 9 level (cardinal + ordinal angles).
Because it demands all four at once, signals are extremely rare — often only a handful per year on daily/weekly timeframes. When they appear, they frequently mark significant tops and bottoms.Fully Adaptive Gann Levels (No Static Lines)
Unlike most Gann scripts with fixed levels that quickly become irrelevant, this one:Automatically anchors to the most recent significant pivot low or high.
Calculates authentic Square of 9 rotations (45°, 90°, 135°, 180°, 225°, 270°, 315°, 360°).
Updates dynamically as new swings form — works on any timeframe and any market (BTC, stocks, forex, indices).
Clean & Customizable Toggle cardinal (strong) vs ordinal (intermediate) levels for plotting and signal checks.
Adjustable pivot sensitivity and proximity tolerance.
Minimal chart clutter: bold lines for major levels, subtle for intermediates, plus clear large triangles for entries.
Best For
Swing traders and position traders seeking high-probability reversal zones rather than frequent scalps. Excellent for Bitcoin and volatile assets where geometric levels + extreme momentum divergences often align at cycle extremes.In short: If you want an indicator that stays quiet most of the time but screams when a real reversal is likely — this is it. Add it, watch the Gann levels adapt, and wait patiently for the rare multi-confluence setups. Quality over quantity.
Nuh's Complete Multi-Timeframe Dashboard v4.0Nuh's Complete Multi-Timeframe Dashboard v4.0 - Unified Power System
Professional Multi-Timeframe Technical Analysis Dashboard
Nuh's Complete Multi-Timeframe Dashboard v4.0 represents a comprehensive trading analysis system that unifies 20 powerful technical indicators across up to 6 customizable timeframes into a single, intelligent dashboard. This advanced indicator combines trend analysis (EMA, Alpha Trend, SuperTrend, ADX, DI), momentum oscillators (RSI, Stochastic RSI, MACD, CCI, Williams %R, WaveTrend, KST), volume indicators (OBV, CMF, Volume Analysis, MFI), and volatility measures (Squeeze Momentum, Bollinger Bands, ATR, Williams VIX Fix) to provide traders with a holistic market perspective. Each indicator can be independently enabled or disabled, allowing complete customization based on your trading strategy and preferences.
The revolutionary Weighted Power System is the core innovation of this dashboard, transforming raw indicator signals into actionable market power scores. Unlike traditional dashboards that simply count bullish or bearish signals, this system applies sophisticated weighting to each indicator based on your chosen preset (Balanced, Trend Focus, Momentum Focus, Volume Focus) or custom weights. It then combines these weighted signals across multiple timeframes—with timeframe-specific weighting for scalping, day trading, or swing trading styles—to calculate an Overall Market Power score. This provides you with clear percentage-based bullish and bearish power readings, eliminating guesswork and enabling confident trade decisions backed by mathematical confluence.
Built for serious traders who demand precision and flexibility, the dashboard features a fully customizable display with 20 indicator rows that can be reordered to match your preferences, color-coded gradient visualization for instant market sentiment recognition, and integrated Wundertrading-compatible alerts for automated trading. The system supports both legacy count-based alerts and modern power-threshold alerts, allowing you to receive notifications when market conditions meet your specified confluence requirements. Whether you're scalping on lower timeframes or swing trading on higher timeframes, this professional-grade tool adapts to your trading style while maintaining clean, readable visualization that won't clutter your charts.
CME Quarterly ShiftsCME Quarterly Shifts - Institutional Quarter Levels
Overview:
The CME Quarterly Shifts indicator tracks price action based on actual CME futures contract rollover dates, not calendar quarters. This indicator plots the Open, High, Low, and Close (OHLC) for each quarter, with quarters defined by the third Friday of March, June, September, and December - the exact dates when CME quarterly futures contracts expire and roll over.
Why CME Contract Dates Matter:
Institutional traders, hedge funds, and large market participants typically structure their positions around futures contract expiration cycles. By tracking quarters based on CME rollover dates rather than calendar months, this indicator aligns with how major institutional players view quarterly timeframes and position their capital.
Key Features:
✓ Automatic CME contract rollover date calculation (3rd Friday of Mar/Jun/Sep/Dec)
✓ Displays Quarter Open, High, Low, and Close levels
✓ Vertical break lines marking the start of each new quarter
✓ Quarter labels (Q1, Q2, Q3, Q4) for easy identification
✓ Adjustable history - show up to 20 previous quarters
✓ Fully customizable colors and line widths
✓ Works on any instrument and timeframe
✓ Toggle individual OHLC levels on/off
How to Use:
Quarter Open: The opening price when the new quarter begins (at CME rollover)
Quarter High: The highest price reached during the current quarter
Quarter Low: The lowest price reached during the current quarter
Quarter Close: The closing price from the previous quarter
These levels often act as key support/resistance zones as institutions reference them for quarterly performance, rebalancing, and position management.
Settings:
Display Options: Toggle quarterly break lines, OHLC levels, and labels
Max Quarters: Control how many historical quarters to display (1-20)
Colors: Customize colors for each level and break lines
Styles: Adjust line widths for OHLC levels and quarterly breaks
Best Practices:
Combine with other Smart Money Concepts (liquidity, order blocks, FVGs)
Watch for price reactions at quarterly Open levels
Monitor quarterly highs/lows as potential targets or stop levels
Use on higher timeframes (4H, Daily, Weekly) for clearer institutional perspective
Pairs well with monthly and yearly levels for multi-timeframe confluence
Perfect For:
ICT (Inner Circle Trader) methodology followers
Smart Money Concepts traders
Swing and position traders
Institutional-focused technical analysis
Traders tracking quarterly performance levels
Works on all markets: Forex, Indices, Commodities, Crypto, Stocks
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
HTF Candles on Lower Timeframes (Manual OHLC)Hi everyone, this indicator is designed to plot higher timeframes candles on the chart. Here are the details:
The data is built directly from OHLC values at specific time intervals, instead of using request.security.
It supports 1H / 2H / 4H / 8H / 1D higher timeframes, and can be viewed on lower timeframes such as 5m / 10m / 15m / 30m.
The main idea behind this chart is to serve as a foundation for building other indicators that need to operate on higher timeframes while still being visualized on lower timeframes.
Feel free to share your feedback or ideas for improvement in the comments below.
Mag 7 EMA Trend MonitorDashboard Layout:
1. Symbol Column: The Mag 7 tickers.
2. Trend Column: Visual Bull/Bear status.
3. Strength Column: Percentage distance from the mean (EMA 21).
4. Aggregate Row: Summary of market breadth and average sector pull/push.
How to Interpret the Trend Strength:
• Positive %: The stock is trading above its 21 EMA. A very high number (e.g., $+15\%$) might suggest the stock is "overbought" or overextended.
• Negative %: The stock is trading below its 21 EMA. A very low number (e.g., $-10\%$) might suggest it is "oversold."
• Avg Strength: This gives you a bird's-eye view of the sector. If the aggregate is "5 Up / 2 Down" but the Avg Strength is only $+0.5\%$, the trend is weak and might be exhausting.
"Pro-tips" for tool:
• Multi-Timeframe Correlation: Try setting the Dashboard Timeframe to "D" (Daily) while trading on a "5m" or "15m" chart. This allows you to see if your intraday trade is aligned with the "Big Money" trend of the week.
• The 4/7 Rule: Watch for that Aggregate row to hit 4 out of 7. In the Mag 7, since these stocks carry so much weight in the SPY and QQQ, a shift to a majority (4+) often precedes a move in the overall market indices.
V-Max Strategic Horizon: Cross-TF Coordinate Sync (Public EditioOverview
The V-Max Strategic Horizon is a technical visualization utility designed to solve the problem of coordinate drift during multi-timeframe analysis. It serves as a "Physical Coordinate Anchor," ensuring that high-level resistance and support boundaries from macro timeframes (e.g., 1H, 4H, or 1D) remain strictly locked and visible even when the trader scales down to 1M or 3M execution charts.
Core Technical Logic
Timeframe Anchoring Engine: The script utilizes request.security with a fixed lookback_cnt to pull the absolute highest and lowest price points from a specified anchor timeframe.
Absolute Coordinate Locking (Zero-Drift): Unlike manual horizontal lines that may become misaligned, this tool employs the line.new system with extend.both logic. This ensures the horizons are mathematically tied to the price scale, providing a consistent strategic reference across all chart resolutions.
High-Speed Computational Logic: To prevent the "Script Timeout" errors common in multi-timeframe indicators, the v11.0 engine eliminates iterative loops, favoring vectorized calculations for real-time responsiveness.
Dynamic Metadata Labeling: The script features an automated labeling system that dynamically identifies the source of the data (e.g., "1H Anchor") and displays the precise price coordinate, reducing cognitive load during high-frequency trading.
How to Use
Set Your Anchor: Choose your strategic timeframe (e.g., 1H for day trading, 1D for swing trading) in the settings.
Define the Scan Range: Adjust the lookback count to determine the "strength" of the historical horizon.
Execute with Context: Watch how the price interacts with the "Red" (Resistance) and "Green" (Support) horizons on your 3M chart to identify macro-rejections or breakouts.
產品概述
V-Max 戰略地平線 是一款解決多時框分析中座標位移問題的技術工具。它作為「物理座標錨點」，確保大週期（如 1H、4H 或 1D）的壓力與支撐邊界，在交易者切換至 1M 或 3M 執行圖表時，依然嚴格鎖定且清晰可見。
核心技術邏輯
時框錨定引擎：利用跨時框數據抓取技術，獲取指定基準時區的絕對價格極值。
絕對座標鎖定（零位移）：採用 line 渲染系統配合同步延伸邏輯，確保地平線在數學上與價格刻度綁定，提供一致的戰略參考。
極速運算邏輯：v11.0 引擎優化了跨時框數據處理，消除了複雜迴圈，確保在短線圖表上實現零延遲性能。
Access & Support
This script is published as a Free Public Utility in the TradingView Library. Disclaimer: For technical analysis purposes only.
Ocean Master [JOAT]Ocean Master QE - Advanced Oceanic Market Analysis with Quantum Flow Dynamics
Overview
Ocean Master QE is an open-source overlay indicator that combines multiple analytical techniques into a unified market analysis framework. It uses ATR-based dynamic channels, volume-weighted order flow analysis, multi-timeframe correlation (quantum entanglement concept), and harmonic oscillator calculations to provide traders with a comprehensive view of market conditions.
What This Indicator Does
The indicator calculates and displays several key components:
Dynamic Price Channels - ATR-adjusted upper, middle, and lower channels that adapt to current volatility conditions
Order Flow Analysis - Separates buying and selling volume pressure to calculate a directional delta
Smart Money Index - Volume-weighted order flow metric that highlights potential institutional activity
Harmonic Oscillator - Weighted combination of 10 Fibonacci-period EMAs (5, 8, 13, 21, 34, 55, 89, 144, 233, 377) to identify trend direction
Multi-Timeframe Correlation - Measures price correlation across 1H, 4H, and Daily timeframes
Wave Function Analysis - Momentum-based state detection that identifies when price action becomes decisive
How It Works
The core channel calculation uses ATR with a configurable quantum sensitivity factor:
float atr = ta.atr(i_atrLength)
float quantumFactor = 1.0 + (i_quantumSensitivity * 0.1)
float quantumATR = atr * quantumFactor
upperChannel := ta.highest(high, i_length) - (quantumATR * 0.5)
lowerChannel := ta.lowest(low, i_length) + (quantumATR * 0.5)
midChannel := (upperChannel + lowerChannel) * 0.5
Order flow is calculated by separating volume into buy and sell components based on candle direction:
The harmonic oscillator weights shorter EMAs more heavily using inverse weighting (1/1, 1/2, 1/3... 1/10), creating a responsive yet smooth trend indicator.
Signal Generation
Confluence signals require multiple conditions to align:
Bullish: Harmonic oscillator crosses above zero + positive Smart Money Index + positive Order Flow Delta
Bearish: Harmonic oscillator crosses below zero + negative Smart Money Index + negative Order Flow Delta
Dashboard Panel (Top-Right)
Bias - Current market direction based on price vs mid-channel
Entanglement - Multi-timeframe correlation score (0-100%)
Wave State - COLLAPSED (decisive) or SUPERPOSITION (uncertain)
Volume - Current volume relative to 20-period average
Volatility - ATR as percentage of price
Smart Money - Volume-weighted order flow reading
Visual Elements
Ocean Depth Layers - Gradient fills between channel levels representing different price zones
Channel Lines - Upper (surface), middle, and lower (seabed) dynamic levels
Divergence Markers - Triangle shapes when harmonic oscillator crosses zero
Confluence Labels - BULL/BEAR labels when multiple factors align
Suggested Use Cases
Identify trend direction using the harmonic oscillator and channel position
Monitor order flow for potential institutional activity
Use multi-timeframe correlation to confirm trade direction across timeframes
Watch for confluence signals where multiple factors align
Input Parameters
Length (default: 14) - Base period for channel and indicator calculations
ATR Length (default: 14) - Period for ATR calculation
Quantum Depth (default: 3) - Complexity factor for calculations
Quantum Sensitivity (default: 1.5) - Channel width multiplier
Timeframe Recommendations
Works on all timeframes. Higher timeframes (4H, Daily) provide smoother signals; lower timeframes require faster reaction times and may produce more noise.
Limitations
Multi-timeframe requests add processing overhead
Order flow estimation is based on candle direction, not actual order book data
Correlation calculations require sufficient historical data
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before trading.
- Made with passion by officialjackofalltrades
ETH Trading bot H1 Money maker i dont know what i did but it is looking good ; make sure you arent in a trade before you start the bot
5x Multi-Timeframe Moving AveragesSince I use EMA lines a lot and I typically want them based on one timeframe - say: D1 - while looking into higher or lower timeframes, I made this simple indicator:
- Up to 5 moving averages (SMA, EMA, ...)
- on chart timeframe or any defined timeframe (W, D, H4, H1, 30min, ...)
- each with user defined length / number of periods of calculation
- each in user defined line style, width and color.
Straight forward but very handy. Enjoy.
Juergen
Rachev Regime AnalyzerRachev Regime Analyzer ~ GForge
What It Does
Measures the ratio of extreme gains to extreme losses to identify whether markets favor bulls or bears. When your best moves are bigger than your worst moves, conditions are bullish. When the opposite is true, conditions are bearish.
Simple Interpretation:
Ratio > 1.2 → Bullish regime (tail gains exceed tail losses)
Ratio < 0.8 → Bearish regime (tail losses exceed tail gains)
Between → Neutral/transitional
Key Features
Two Modes:
Single Asset: Analyze current chart
Multi-Asset: Aggregate regime across 5 assets with custom weights (great for gauging overall crypto/market conditions)
Customizable:
Lookback period (20-200 bars)
Tail percentile (what counts as "extreme")
Bullish/bearish thresholds
6 color schemes
Optional MA smoothing
Visual Signals:
Buy/sell markers at threshold crosses
Background regime coloring
Info table with current values and confidence score
Configurable alerts
How to Use
Choose lookback period based on your timeframe (40-60 bars is a good start)
Watch for threshold crosses - these mark regime changes
Check confidence score - higher = more reliable
Use multi-asset mode to see if entire market is shifting (not just one coin)
Best combined with: Trend indicators, support/resistance, volume analysis
Parameters
Lookback: More bars = smoother, less responsive
Alpha (0.10): Defines extreme events - lower = more extreme
Thresholds: Adjust based on asset volatility
Return Type: Log returns recommended for most assets
What Makes It Useful
Unlike simple volatility measures, this shows asymmetry - whether extreme moves favor upside or downside. A ratio of 1.5 means your extreme gains are 50% larger than extreme losses - that's actionable information about risk-reward dynamics.
Multi-asset aggregation is particularly powerful for crypto traders wanting to gauge if BTC, ETH, SOL, etc. are all showing similar regime characteristics.
Disclaimer
Educational tool only. Not financial advice. Use proper risk management. No indicator works in isolation - always consider broader market context.
Developed by GForge
Comments and feedback welcome! 👍
Elite MTF EMA Reclaim StrategyThis script is a 6-minute execution MTF EMA “retest → reclaim” strategy. It looks for trend-aligned pullbacks into fast EMAs, then enters when price reclaims and (optionally) retests the reclaim level—while filtering out chop (low trend strength/volatility or recent EMA20/50 crosses) and enforcing higher-timeframe alignment (Daily + 1H, or whichever you select).
How to use
Run it on a 6-minute chart (that’s what the presets are tuned for).
Pick your Market (Forex / XAUUSD / Crypto / Indices) and a Preset:
Elite = strictest, cleanest (fewer signals)
Balanced = middle ground
Aggressive = most signals, loosest filters
Set HTF Alignment Mode:
D + H1 (recommended) for highest quality
Off if you want more trades / LTF-only testing
Leave Kill Chop = ON (recommended). If you’re not getting trades, this is usually the blocker.
Choose entry behavior:
If Require Retest = true, entries happen on the retest after reclaim (cleaner, later).
If Require Retest = false, entries trigger on reclaim using Reclaim Timing Default:
“Preset” uses the strategy’s recommended default per market/preset
or force Reclaim close / Next bar confirmation
For backtesting, keep Mode = Strategy (Backtest). For alerts/visual-only, set Mode = Indicator (Signals Only).
Use Show Signals (All Modes) to toggle triangles on/off without affecting trades.
Tip: If TradingView says “not enough data,” switch symbol history to “All,” reduce HTF alignment (try H1 only), or backtest a more recent date range.
SessionsThis indicator highlights the New York After Hours and Pre-Market session and visually defines its structure on the chart.
The session runs from 18:00 to 09:30 New York time, covering the full overnight and pre-market trading window leading into the regular cash open.
During this period, the script tracks and marks the high and low of the New York pre-market, allowing traders to clearly see the overnight range that often acts as key liquidity, support, and resistance during the regular trading session.
The session range can be displayed as a shaded background or as a high/low range, depending on user preference.
For clarity and precision, the indicator is visible only on intraday timeframes:
5-minute
30-minute
1-hour
This makes it especially useful for futures, index, and intraday traders who incorporate pre-market structure into their trading plans.
Sessions by nolimitCustom Trading Sessions Indicator (6 Sessions)
This indicator allows you to display up to 6 customizable trading sessions on your chart with full control over timing, colors, and timezone settings.
Features:
- 6 independent trading sessions that can be enabled/disabled individually
- Flexible time range settings for each session
- Individual color selection for each session background
- Timezone selection (UTC-12 to UTC+12) that applies to all sessions
- Clean, organized settings grouped by session
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.
Confluence Execution Engine (2of3)The Confluence Execution Engine is a high-performance logic gate designed to filter out market noise and identify high-probability "Golden" entries. It moves beyond simple indicator signals by acting as a mathematical validator for price action. This engine is designed for the Systematic Trader. It removes the "guesswork" of whether a move is real or an exhaustion pump by requiring a mathematical confluence of volume, multi-timeframe momentum, and volatility-adjusted space.
Why This Tool is Unique:
Multi-Dimensional Scoring, Momentum-Adjusted Stretch, Institutional Fingerprint (RVOL + Spike)
Unlike a standard MACD or RSI, this engine uses a weighted scoring matrix. It pulls a "Bundle" of data (WaveTrend, RSI, ROC) from four different timeframes simultaneously. It doesn't give a signal unless the mathematical weight of all four timeframes crosses your "Hurdle" (Base Threshold).
Standard "overbought" indicators are often wrong during strong trends. This engine uses Dynamic Z-Score logic. The Logic: If the price moves away from the mean, it checks the Rate of Change (ROC). The Result: If momentum is massive, the "Stretch" limit expands. It understands that a "stretched" price is actually a sign of strength in a breakout, not a reason to exit. It only warns of a TRAP RISK when the price is far from the mean but momentum is starting to stall.
The engine is gated by Relative Volume. If the market is "sleepy," the engine stays in "PATIENCE" mode. It specifically hunts for Volume Spikes (default 2.5x average). A signal is only upgraded to "HIGH CONVICTION" when an institutional volume spike occurs, confirming that "Big Money" is participating.
How to Operate the Engine
Define Your Hurdle: Set your Confluence Hurdle. A higher number (e.g., 14+) requires more agreement across timeframes, leading to fewer but higher-quality trades.
Monitor the Z/Dynamic Ratio: In the HUD, watch the Z: X.XX / Y.YY. When X approaches Y, you are reaching the edge of the momentum-adjusted move.
The Entry Trigger: Wait for a "LOOK FOR..." advice to turn into a "HIGH CONVICTION" signal (marked by a triangle shape). This confirms that the MTF scoring, Volume, and HTF Trend are all aligned.
Execute the Lines: Use the red and green "Ghost Lines" to set your orders. These are ATR-based, meaning they widen during high volatility to give your trade room to breathe.
For holistic trading system, pair with Volatility Shield Pro and Session Levels
