Finite Volume Elementwww.prorealcode.com
From ProRealTime,
"FVE is a money flow indicator but with two important differences from existing money flow indicators:
It resolves contradictions between intraday money flow indicators (such as Chaikin’s money flow) and interday money flow indicators (like On Balance Volume) by taking into account both intra- and interday price action. Unlike other money flow indicators which add or subtract all volume even if the security closed just 1 cent higher than the previous close, FVE uses a volatility threshold to take into account minimal price changes. The FVE provides 3 types of signals: The strongest signal is divergence between price and the indicator. Divergence can provide leading signals of breakouts or warnings of impending corrections. The classic method for detecting divergence is for FVE to make lower highs while price makes higher highs (negative divergence). An alternative method is to draw the linear regression line on both charts, and compare the slopes. A logical buy signal would be for FVE, diverging from price, to rise sharply and make a series higher highs and/or higher lows. The most obvious and coincident signal is the slope of the FVE line. An upward slope indicates that the bulls are in control and the opposite for downward. This is a unique and very important property of this indicator. Values above zero are bullish and indicate accumulation while values below zero indicate distribution. FVE crossing the zero line indicates that the short to intermediate balance of power is changing from the bulls to the bears or vice versa. The best scenario is when a stock is in the process of building a base, and FVE diverges from price and rises to cross the zero line from below, at a sharp angle. Conversely the crossing of the zero line from above is a bearish signal to liquidate positions or initiate a short trade."
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SCTI V28Indicator Overview | 指标概述
English: SCTI V28 (Smart Composite Technical Indicator) is a multi-functional composite technical analysis tool that integrates various classic technical analysis methods. It contains 7 core modules that can be flexibly configured to show or hide components based on traders' needs, suitable for various trading styles and market conditions.
中文: SCTI V28 (智能复合技术指标) 是一款多功能复合型技术分析指标，整合了多种经典技术分析工具于一体。该指标包含7大核心模块，可根据交易者的需求灵活配置显示或隐藏各个组件，适用于多种交易风格和市场环境。
Main Functional Modules | 主要功能模块
1. Basic Indicator Settings | 基础指标设置
English:
EMA Display: 13 configurable EMA lines (default shows 8/13/21/34/55/144/233/377/610/987/1597/2584 periods)
PMA Display: 11 configurable moving averages with multiple MA types (ALMA/EMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
VWAP Display: Volume Weighted Average Price indicator
Divergence Indicator: Detects divergences across 12 technical indicators
ATR Stop Loss: ATR-based stop loss lines
Volume SuperTrend AI: AI-powered super trend indicator
中文:
EMA显示：13条可配置EMA均线，默认显示8/13/21/34/55/144/233/377/610/987/1597/2584周期
PMA显示：11条可配置移动平均线，支持多种MA类型(ALMA/EMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
VWAP显示：成交量加权平均价指标
背离指标：12种技术指标的背离检测系统
ATR止损：基于ATR的止损线
Volume SuperTrend AI：基于AI预测的超级趋势指标
2. EMA Settings | EMA设置
English:
13 independent EMA lines, each configurable for visibility and period length
Default shows 21/34/55/144/233/377/610/987/1597/2584 period EMAs
Customizable colors and line widths for each EMA
中文:
13条独立EMA均线，每条均可单独配置显示/隐藏和周期长度
默认显示21/34/55/144/233/377/610/987/1597/2584周期的EMA
每条EMA可设置不同颜色和线宽
3. PMA Settings | PMA设置
English:
11 configurable moving averages, each with:
Selectable types (default EMA, options: ALMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
Independent period settings (12-1056)
Special ALMA parameters (offset and sigma)
Configurable data source and plot offset
Support for fill areas between MAs
Price lines and labels can be added
中文:
11条可配置移动平均线，每条均可：
选择不同类型(默认EMA，可选ALMA/RMA/SMA/SWMA/VWAP/VWMA/WMA)
独立设置周期长度(12-1056)
设置ALMA的特殊参数(偏移量和sigma)
配置数据源和绘图偏移
支持MA之间的填充区域显示
可添加价格线和标签
4. VWAP Settings | VWAP设置
English:
Multiple anchor period options (Session/Week/Month/Quarter/Year/Decade/Century/Earnings/Dividends/Splits)
3 configurable standard deviation bands
Option to hide on daily and higher timeframes
Configurable data source and offset settings
中文:
多种锚定周期选择(会话/周/月/季/年/十年/世纪/财报/股息/拆股)
3条可配置标准差带
可选择在日线及以上周期隐藏
支持数据源选择和偏移设置
5. Divergence Indicator Settings | 背离指标设置
English:
12 detectable indicators: MACD, MACD Histogram, RSI, Stochastic, CCI, Momentum, OBV, VWmacd, Chaikin Money Flow, MFI, Williams %R, External Indicator
4 divergence types: Regular Bullish/Bearish, Hidden Bullish/Bearish
Multiple display options: Full name/First letter/Hide indicator name
Configurable parameters: Pivot period, data source, maximum bars checked, etc.
Alert functions: Independent alerts for each divergence type
中文:
检测12种指标：MACD、MACD柱状图、RSI、随机指标、CCI、动量、OBV、VWmacd、Chaikin资金流、MFI、威廉姆斯%R、外部指标
4种背离类型：正/负常规背离，正/负隐藏背离
多种显示选项：完整名称/首字母/不显示指标名称
可配置参数：枢轴点周期、数据源、最大检查柱数等
警报功能：各类背离的独立警报
6. ATR Stop Loss Settings | ATR止损设置
English:
Configurable ATR length (default 13)
4 smoothing methods (RMA/SMA/EMA/WMA)
Adjustable multiplier (default 1.618)
Displays long and short stop loss lines
中文:
可配置ATR长度(默认13)
4种平滑方法(RMA/SMA/EMA/WMA)
可调乘数(默认1.618)
显示多头和空头止损线
7. Volume SuperTrend AI Settings | Volume SuperTrend AI设置
English:
AI Prediction:
Configurable neighbors (1-100) and data points (1-100)
Price trend length and prediction trend length settings
SuperTrend Parameters:
Length (default 3)
Factor (default 1.515)
5 MA source options (SMA/EMA/WMA/RMA/VWMA)
Signal Display:
Trend start signals (circle markers)
Trend confirmation signals (triangle markers)
6 Alerts: Various trend start and confirmation signals
中文:
AI预测功能：
可配置邻居数(1-100)和数据点数(1-100)
价格趋势长度和预测趋势长度设置
SuperTrend参数：
长度(默认3)
因子(默认1.515)
5种MA源选择(SMA/EMA/WMA/RMA/VWMA)
信号显示：
趋势开始信号(圆形标记)
趋势确认信号(三角形标记)
6种警报：各类趋势开始和确认信号
Usage Recommendations | 使用建议
English:
Trend Analysis: Use EMA/PMA combinations to determine market trends, with long-period EMAs (e.g., 144/233) as primary trend references
Divergence Trading: Look for potential reversals using price-indicator divergences
Stop Loss Management: Use ATR stop loss lines for risk management
AI Assistance: Volume SuperTrend AI provides machine learning-based trend predictions
Multiple Timeframes: Verify signals across different timeframes
中文:
趋势分析：使用EMA/PMA组合判断市场趋势，长周期EMA(如144/233)作为主要趋势参考
背离交易：结合价格与指标的背离寻找潜在反转点
止损设置：利用ATR止损线管理风险
AI辅助：Volume SuperTrend AI提供基于机器学习的趋势预测
多时间框架：建议在不同时间框架下验证信号
Parameter Configuration Tips | 参数配置技巧
English:
For short-term trading: Focus on 8-55 period EMAs and shorter divergence detection periods
For long-term investing: Use 144-2584 period EMAs with longer detection parameters
In ranging markets: Disable some EMAs, mainly rely on VWAP and divergence indicators
In trending markets: Enable more EMAs and SuperTrend AI
中文:
对于短线交易：可重点关注8-55周期的EMA和较短的背离检测周期
对于长线投资：建议使用144-2584周期的EMA和较长的检测参数
在震荡市：可关闭部分EMA，主要依靠VWAP和背离指标
在趋势市：可启用更多EMA和SuperTrend AI
Update Log | 更新日志
English:
V28 main updates:
Added Volume SuperTrend AI module
Optimized divergence detection algorithm
Added more EMA period options
Improved UI and parameter grouping
中文:
V28版本主要更新：
新增Volume SuperTrend AI模块
优化背离检测算法
增加更多EMA周期选项
改进用户界面和参数分组
Final Note | 最后说明
English: This indicator is suitable for technical traders with some experience. We recommend practicing with demo trading to familiarize yourself with all features before live trading.
中文: 该指标适合有一定经验的技术分析交易者使用，建议先通过模拟交易熟悉各项功能后再应用于实盘。
ALMA Optimized Strategy - Volatility Filter + UT BotThe strategy you provided is an ALMA Optimized Strategy implemented in Pine Script™ version 5 for TradingView. Here is a brief English summary of what it is and how it works:
It is a trend-following strategy combining multiple technical indicators to optimize trade entries and exits.
The core moving average used is the ALMA (Arnaud Legoux Moving Average), known for smoother and less lagging price smoothing compared to traditional EMAs or SMAs.
The strategy also uses other indicators:
Fast EMA (Exponential Moving Average)
EMA 50
ATR (Average True Range) for volatility measurement and dynamic stop loss and take profit levels
RSI (Relative Strength Index) for momentum with overbought/oversold levels
ADX (Average Directional Index) for confirming trend strength
Bollinger Bands as a volatility filter
Buy signals trigger when volatility is sufficient (ATR filter), price is above EMA 50 and ALMA, RSI indicates bullish momentum, ADX confirms trend strength, price is below the upper Bollinger Band, and there is a cooldown period to prevent repeated buys within a short time.
Sell signals are generated when price crosses below the fast EMA.
The strategy manages position entries and exits dynamically, applying ATR-based stop loss and take profit levels, and optionally a time-based exit.
Additionally, the script integrates the UT Bot, an ATR-based trailing stop and signal system, enhancing trade exit precision.
Buy and sell signals are visually marked on the chart with colored triangles for easy identification.
In essence, this strategy blends advanced smoothing (ALMA) with volatility filters and trend/momentum indicators to generate reliable buy and sell signals, while managing risk dynamically through ATR-based stops and profit targets. It aims to adapt to changing market conditions by filtering noise and confirming trends before entering trades.
BOS mark-out (by Lumiere)Advanced BOS Detection with Strict Swing Confirmation
This indicator implements BOS detection with several unique features:
🔹 Dual-Candle Swing Validation - Unlike most BOS indicators that use single candle swings, this uses a two-candle confirmation for swing highs/lows, analyzing both the candle wicks and body transitions.
🔹 Directional Lock System - Implements a state machine that prevents duplicate signals until an opposite-direction BOS occurs, reducing noise.
🔹 Precision Wick Analysis - Compares wicks between the reversal candle and confirmation candle to identify the true swing point.
🔹 Real-Time Update & Live Market Adaptation – The indicator continuously monitors price action and instantly updates BOS signals as new candles form, ensuring you never miss a BOS.
How It Differs From Other BOS Indicators:
Most public BOS indicators use simple HH/HL or LH/LL detection.
Many don't implement the directional locking mechanism.
Few use the two-candle wick comparison approach.
Wick-Based Precision uses the extreme wicks of two candles (not just the body).
Strict Confirmation requires a close beyond the swing point (no "wick breaks" counted).
Usage Examples:
🟦 Bullish BOS:
A green candle closes, followed by a red candle. This will be the new high, and if the next candle closes above the highest wick of those two, it will be a BOS (only if we had a bearish BOS before)
🟥 Bearish BOS:
A red candle closes, followed by a green candle. This will be the new low, and if the next candle closes below the lowest wick of those two, it will be a BOS (only if we had a Bullish BOS before)
RSI of RSI Deviation (RoRD)RSI of RSI Deviation (RoRD) - Advanced Momentum Acceleration Analysis
What is RSI of RSI Deviation (RoRD)?
RSI of RSI Deviation (RoRD) is a insightful momentum indicator that transcends traditional oscillator analysis by measuring the acceleration of momentum through sophisticated mathematical layering. By calculating RSI on RSI itself (RSI²) and applying advanced statistical deviation analysis with T3 smoothing, RoRD reveals hidden market dynamics that single-layer indicators miss entirely.
This isn't just another RSI variant—it's a complete reimagining of how we measure and visualize momentum dynamics. Where traditional RSI shows momentum, RoRD shows momentum's rate of change . Where others show static overbought/oversold levels, RoRD reveals statistically significant deviations unique to each market's character.
Theoretical Foundation - The Mathematics of Momentum Acceleration
1. RSI² (RSI of RSI) - The Core Innovation
Traditional RSI measures price momentum. RoRD goes deeper:
Primary RSI (RSI₁) : Standard RSI calculation on price
Secondary RSI (RSI²) : RSI calculated on RSI₁ values
This creates a "momentum of momentum" indicator that leads price action
Mathematical Expression:
RSI₁ = 100 - (100 / (1 + RS₁))
RSI² = 100 - (100 / (1 + RS₂))
Where RS₂ = Average Gain of RSI₁ / Average Loss of RSI₁
2. T3 Smoothing - Lag-Free Response
The T3 Moving Average, developed by Tim Tillson, provides:
Superior smoothing with minimal lag
Adaptive response through volume factor (vFactor)
Noise reduction while preserving signal integrity
T3 Formula:
T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
Where e1...e6 are cascaded EMAs and c1...c4 are volume-factor-based coefficients
3. Statistical Z-Score Deviation
RoRD employs dual-layer Z-score normalization :
Initial Z-Score : (RSI² - SMA) / StDev
Final Z-Score : Z-score of the Z-score for refined extremity detection
This identifies statistically rare events relative to recent market behavior
4. Multi-Timeframe Confluence
Compares current timeframe Z-score with higher timeframe (HTF)
Provides directional confirmation across time horizons
Filters false signals through timeframe alignment
Why RoRD is Different & More Sophisticated
Beyond Traditional Indicators:
Acceleration vs. Velocity : While RSI measures momentum (velocity), RoRD measures momentum's rate of change (acceleration)
Adaptive Thresholds : Z-score analysis adapts to market conditions rather than using fixed 70/30 levels
Statistical Significance : Signals are based on mathematical rarity, not arbitrary levels
Leading Indicator : RSI² often turns before price, providing earlier signals
Reduced Whipsaws : T3 smoothing eliminates noise while maintaining responsiveness
Unique Signal Generation:
Quantum Orbs : Multi-layered visual signals for statistically extreme events
Divergence Detection : Automated identification of price/momentum divergences
Regime Backgrounds : Visual market state classification (Bullish/Bearish/Neutral)
Particle Effects : Dynamic visualization of momentum energy
Visual Design & Interpretation Guide
Color Coding System:
Yellow (#e1ff00) : Neutral/balanced momentum state
Red (#ff0000) : Overbought/extreme bullish acceleration
Green (#2fff00) : Oversold/extreme bearish acceleration
Orange : Z-score visualization
Blue : HTF Z-score comparison
Main Visual Elements:
RSI² Line with Glow Effect
Multi-layer glow creates depth and emphasis
Color dynamically shifts based on momentum state
Line thickness indicates signal strength
Quantum Signal Orbs
Green Orbs Below : Statistically rare oversold conditions
Red Orbs Above : Statistically rare overbought conditions
Multiple layers indicate signal strength
Only appear at Z-score extremes for high-conviction signals
Divergence Markers
Green Circles : Bullish divergence detected
Red Circles : Bearish divergence detected
Plotted at pivot points for precision
Background Regimes
Green Background : Bullish momentum regime
Grey Background : Bearish momentum regime
Blue Background : Neutral/transitioning regime
Particle Effects
Density indicates momentum energy
Color matches current RSI² state
Provides dynamic market "feel"
Dashboard Metrics - Deep Dive
RSI² ANALYSIS Section:
RSI² Value (0-100)
Current smoothed RSI of RSI reading
>70 : Strong bullish acceleration
<30 : Strong bearish acceleration
~50 : Neutral momentum state
RSI¹ Value
Traditional RSI for reference
Compare with RSI² for acceleration/deceleration insights
Z-Score Status
🔥 EXTREME HIGH : Z > threshold, statistically rare bullish
❄️ EXTREME LOW : Z < threshold, statistically rare bearish
📈 HIGH/📉 LOW : Elevated but not extreme
➡️ NEUTRAL : Normal statistical range
MOMENTUM Section:
Velocity Indicator
▲▲▲ : Strong positive acceleration
▼▼▼ : Strong negative acceleration
Shows rate of change in RSI²
Strength Bar
██████░░░░ : Visual power gauge
Filled bars indicate momentum strength
Based on deviation from center line
SIGNALS Section:
Divergence Status
🟢 BULLISH DIV : Price making lows, RSI² making highs
🔴 BEARISH DIV : Price making highs, RSI² making lows
⚪ NO DIVERGENCE : No divergence detected
HTF Comparison
🔥 HTF EXTREME : Higher timeframe confirms extremity
📊 HTF NORMAL : Higher timeframe is neutral
Critical for multi-timeframe confirmation
Trading Application & Strategy
Signal Hierarchy (Highest to Lowest Priority):
Quantum Orb + HTF Alignment + Divergence
Highest conviction reversal signal
Z-score extreme + timeframe confluence + divergence
Quantum Orb + HTF Alignment
Strong reversal signal
Wait for price confirmation
Divergence + Regime Change
Medium-term reversal signal
Monitor for orb confirmation
Threshold Crosses
Traditional overbought/oversold
Use as alert, not entry
Entry Strategies:
For Reversals:
Wait for Quantum Orb signal
Confirm with HTF Z-score direction
Enter on price structure break
Stop beyond recent extreme
For Continuations:
Trade with regime background color
Use RSI² pullbacks to center line
Avoid signals against HTF trend
For Scalping:
Focus on Z-score extremes
Quick entries on orb signals
Exit at center line cross
Risk Management:
Reduce position size when signals conflict with HTF
Avoid trades during regime transitions (blue background)
Tighten stops after divergence completion
Scale out at statistical mean reversion
Development & Uniqueness
RoRD represents months of research into momentum dynamics and statistical analysis. Unlike indicators that simply combine existing tools, RoRD introduces several genuine innovations :
True RSI² Implementation : Not a smoothed RSI, but actual RSI calculated on RSI values
Dual Z-Score Normalization : Unique approach to finding statistical extremes
T3 Integration : First RSI² implementation with T3 smoothing for optimal lag reduction
Quantum Orb Visualization : Revolutionary signal display method
Dynamic Regime Detection : Automatic market state classification
Statistical Adaptability : Thresholds adapt to market volatility
This indicator was built from first principles, with each component carefully selected for its mathematical properties and practical trading utility. The result is a professional-grade tool that provides insights unavailable through traditional momentum analysis.
Best Practices & Tips
Start with default settings - they're optimized for most markets
Always check HTF alignment before taking signals
Use divergences as early warning , orbs as confirmation
Respect regime backgrounds - trade with them, not against
Combine with price action - RoRD shows when, price shows where
Adjust Z-score thresholds based on market volatility
Monitor dashboard metrics for complete market context
Conclusion
RoRD isn't just another indicator—it's a complete momentum analysis system that reveals market dynamics invisible to traditional tools. By combining momentum acceleration, statistical analysis, and multi-timeframe confluence with intuitive visualization, RoRD provides traders with a sophisticated edge in any market condition.
Whether you're scalping rapid reversals or positioning for major trend changes, RoRD's unique approach to momentum analysis will transform how you see and trade market dynamics.
See momentum's future. Trade with statistical edge.
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework
The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike.
## Theoretical Foundation
### Historical Context of Bear Market Prediction
Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models.
Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data.
### Methodological Framework
The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment.
The mathematical foundation follows the general form:
Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100
Where:
- Wi = Category weight (i = 1,2,3,4)
- Ci = Normalized category score
- Categories: Macroeconomic, Technical, Sentiment, Breadth
## Component Analysis
### 1. Macroeconomic Risk Factors
#### Yield Curve Analysis
The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations.
Implementation:
- 2Y-10Y Spread: Captures market expectations of monetary policy trajectory
- 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time
Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure.
#### Credit Risk Premium Assessment
High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress.
Threshold Calibration:
- Normal conditions: < 350 basis points
- Elevated risk: 350-500 basis points
- Severe stress: > 500 basis points
#### Currency and Commodity Stress Indicators
The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress.
### 2. Technical Analysis Factors
#### Multi-Timeframe Moving Average Analysis
The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules.
Implementation:
- Price relative to 50-day and 200-day simple moving averages
- Moving average convergence/divergence analysis
- Multi-timeframe MACD assessment (daily and weekly)
#### Momentum and Volatility Analysis
The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement.
### 3. Market Sentiment Factors
#### Volatility Index Analysis
The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average.
Calibration:
- Low volatility: VIX < 20
- Elevated concern: VIX 20-25
- High fear: VIX > 25
- Panic conditions: VIX > 30
#### Put-Call Ratio Analysis
Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets.
### 4. Market Breadth Factors
#### Advance-Decline Analysis
Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns.
Components:
- Daily advance-decline ratio
- Advance-decline line momentum
- McClellan Oscillator (Ema19 - Ema39 of A-D difference)
#### New Highs-New Lows Analysis
The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990).
## Dynamic Threshold Methodology
The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions.
Dynamic Threshold Calculation:
- Warning Level: Base threshold ± (Volatility × 1.0)
- Danger Level: Base threshold ± (Volatility × 1.5)
- Bounds: ±10-20 points from base threshold
## Professional Implementation
### Institutional Usage Patterns
Professional risk managers typically employ multi-factor bear market models in several contexts:
#### 1. Portfolio Risk Management
- Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70%
- Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached
- Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods
#### 2. Risk Budgeting
- Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations
- Stress Testing: Using probability levels to calibrate stress test scenarios
- Capital Requirements: Adjusting regulatory capital based on systemic risk assessment
#### 3. Client Communication
- Risk Reporting: Quantifying market risk for client presentations
- Investment Committee Decisions: Providing objective risk metrics for strategic decisions
- Performance Attribution: Explaining defensive positioning during market stress
### Implementation Framework
Professional traders typically implement such models through:
#### Signal Hierarchy:
1. Probability < 30%: Normal risk positioning
2. Probability 30-50%: Increased hedging, reduced leverage
3. Probability 50-70%: Defensive positioning, cash building
4. Probability > 70%: Maximum defensive posture, short exposure consideration
#### Risk Management Integration:
- Position Sizing: Inverse relationship between probability and position size
- Stop-Loss Adjustment: Tighter stops during elevated risk periods
- Correlation Monitoring: Increased attention to cross-asset correlations
## Strengths and Advantages
### 1. Comprehensive Coverage
The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes.
### 2. Dynamic Adaptability
The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes.
### 3. Real-Time Processing
Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management.
### 4. Transparency and Interpretability
The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals.
### 5. Historical Validation
Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power.
## Limitations and Weaknesses
### 1. Data Dependencies
The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions.
### 2. Regime Change Sensitivity
Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007).
### 3. False Signal Risk
Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods.
### 4. Currency and Geographic Bias
The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets.
### 5. Correlation Breakdown
During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002).
## References
Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851.
Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292.
Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24.
Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27.
Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26.
Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49.
Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261.
Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research.
Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720.
Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220.
Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46.
Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908.
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House.
Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125.
Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
[blackcat] L1 Multi-Component CCIOVERVIEW
The " L1 Multi-Component CCI" is a sophisticated technical indicator designed to analyze market trends and momentum using multiple components of the Commodity Channel Index (CCI). This script calculates and combines various CCI-related metrics to provide a comprehensive view of price action, offering traders deeper insights into market dynamics. By integrating smoothed deviations, normalized ranges, and standard CCI values, this tool aims to enhance decision-making processes. It is particularly useful for identifying potential reversal points and confirming trend strength. 📈
FEATURES
Multi-Component CCI Calculation: Combines smoothed deviation, normalized range, percent above low, and standard CCI for a holistic analysis, providing a multifaceted view of market conditions.
Threshold Lines: Overbought (200), oversold (-200), bullish (100), and bearish (-100) thresholds are plotted for easy reference, helping traders quickly identify extreme market conditions.
Visual Indicators: Each component is plotted with distinct colors and line styles for clear differentiation, making it easier to interpret the data at a glance.
Customizable Alerts: The script includes commented-out buy and sell signal logic that can be enabled for automated trading notifications, allowing traders to set up alerts based on specific conditions. 🚀
Advanced Calculations: Utilizes a combination of simple moving averages (SMA) and exponential moving averages (EMA) to smooth out price data, enhancing the reliability of the indicator.
HOW TO USE
Apply the Script: Add the script to your chart on TradingView by searching for " L1 Multi-Component CCI" in the indicators section.
Observe the Plotted Lines: Pay close attention to the smoothed deviation, normalized range, percent above low, and standard CCI lines to identify potential overbought or oversold conditions.
Use Threshold Levels: Refer to the overbought, oversold, bullish, and bearish threshold lines to gauge extreme market conditions and potential reversal points.
Confirm Trends: Use the standard CCI line to confirm trend direction and momentum shifts, providing additional confirmation for your trading decisions.
Enable Alerts: If desired, uncomment the buy and sell signal logic to receive automated alerts when specific conditions are met, helping you stay informed even when not actively monitoring the chart. ⚠️
LIMITATIONS
Fixed Threshold Levels: The script uses fixed threshold levels (200, -200, 100, -100), which may need adjustment based on specific market conditions or asset volatility.
No Default Signals: The buy and sell signal logic is currently commented out, requiring manual activation if you wish to use automated alerts.
Complexity: The multi-component approach, while powerful, may be complex for novice traders to interpret, requiring a solid understanding of technical analysis concepts. 📉
Not for Isolation Use: This indicator is not designed for use in isolation; it is recommended to combine it with other tools and indicators for confirmation and a more robust analysis.
NOTES
Smoothing Techniques: The script uses a combination of simple moving averages (SMA) and exponential moving averages (EMA) for smoothing calculations, which helps in reducing noise and enhancing signal clarity.
Multi-Component Approach: The multi-component approach aims to provide a more nuanced view of market conditions compared to traditional CCI, offering a more comprehensive analysis.
Customization Potential: Traders can customize the script further by adjusting the parameters of the moving averages and other components to better suit their trading style and preferences. ✨
THANKS
Thanks to the TradingView community for their support and feedback on this script! Special thanks to those who contributed ideas and improvements, making this tool more robust and user-friendly. 🙏
ADX and DI - Trader FelipeADX and DI - Trader Felipe
This indicator combines the Average Directional Index (ADX) and the Directional Indicators (DI+ and DI-) to help traders assess market trends and their strength. It is designed to provide a clear view of whether the market is in a trending phase (either bullish or bearish) and helps identify potential entry and exit points.
What is ADX and DI?
DI+ (Green Line):
DI+ measures the strength of upward (bullish) price movements. When DI+ is above DI-, it signals that the market is experiencing upward momentum.
DI- (Red Line):
DI- measures the strength of downward (bearish) price movements. When DI- is above DI+, it suggests that the market is in a bearish phase, with downward momentum.
ADX (Blue Line):
ADX quantifies the strength of the trend, irrespective of whether it is bullish or bearish. The higher the ADX, the stronger the trend:
ADX > 20: Indicates a trending market (either up or down).
ADX < 20: Indicates a weak or sideways market with no clear trend.
Threshold Line (Gray Line):
This horizontal line, typically set at 20, represents the threshold for identifying whether the market is trending or not. If ADX is above 20, the market is considered to be in a trend. If ADX is below 20, it suggests that the market is not trending and is likely in a consolidation phase.
Summary of How to Use the Indicator:
Trend Confirmation: Use ADX > 20 to confirm a trending market. If ADX is below 20, avoid trading.
Long Entry: Enter a long position when DI+ > DI- and ADX > 20.
Short Entry: Enter a short position when DI- > DI+ and ADX > 20.
Avoid Sideways Markets: Do not trade when ADX is below 20. Look for other strategies for consolidation phases.
Exit Strategy: Exit the trade if ADX starts to decline or if the DI lines cross in the opposite direction.
Combine with Other Indicators: Use additional indicators like RSI, moving averages, or support/resistance to filter and confirm signals.
Dskyz (DAFE) Adaptive Regime - Quant Machine ProDskyz (DAFE) Adaptive Regime - Quant Machine Pro:
Buckle up for the Dskyz (DAFE) Adaptive Regime - Quant Machine Pro, is a strategy that’s your ultimate edge for conquering futures markets like ES, MES, NQ, and MNQ. This isn’t just another script—it’s a quant-grade powerhouse, crafted with precision to adapt to market regimes, deliver multi-factor signals, and protect your capital with futures-tuned risk management. With its shimmering DAFE visuals, dual dashboards, and glowing watermark, it turns your charts into a cyberpunk command center, making trading as thrilling as it is profitable.
Unlike generic scripts clogging up the space, the Adaptive Regime is a DAFE original, built from the ground up to tackle the chaos of futures trading. It identifies market regimes (Trending, Range, Volatile, Quiet) using ADX, Bollinger Bands, and HTF indicators, then fires trades based on a weighted scoring system that blends candlestick patterns, RSI, MACD, and more. Add in dynamic stops, trailing exits, and a 5% drawdown circuit breaker, and you’ve got a system that’s as safe as it is aggressive. Whether you’re a newbie or a prop desk pro, this strat’s your ticket to outsmarting the markets. Let’s break down every detail and see why it’s a must-have.
Why Traders Need This Strategy
Futures markets are a gauntlet—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional traps that punish the unprepared. Meanwhile, platforms are flooded with low-effort scripts that recycle old ideas with zero innovation. The Adaptive Regime stands tall, offering:
Adaptive Intelligence: Detects market regimes (Trending, Range, Volatile, Quiet) to optimize signals, unlike one-size-fits-all scripts.
Multi-Factor Precision: Combines candlestick patterns, MA trends, RSI, MACD, volume, and HTF confirmation for high-probability trades.
Futures-Optimized Risk: Calculates position sizes based on $ risk (default: $300), with ATR or fixed stops/TPs tailored for ES/MES.
Bulletproof Safety: 5% daily drawdown circuit breaker and trailing stops keep your account intact, even in chaos.
DAFE Visual Mastery: Pulsing Bollinger Band fills, dynamic SL/TP lines, and dual dashboards (metrics + position) make signals crystal-clear and charts a work of art.
Original Craftsmanship: A DAFE creation, built with community passion, not a rehashed clone of generic code.
Traders need this because it’s a complete, adaptive system that blends quant smarts, user-friendly design, and DAFE flair. It’s your edge to trade with confidence, cut through market noise, and leave the copycats in the dust.
Strategy Components
1. Market Regime Detection
The strategy’s brain is its ability to classify market conditions into five regimes, ensuring signals match the environment.
How It Works:
Trending (Regime 1): ADX > 20, fast/slow EMA spread > 0.3x ATR, HTF RSI > 50 or MACD bullish (htf_trend_bull/bear).
Range (Regime 2): ADX < 25, price range < 3% of close, no HTF trend.
Volatile (Regime 3): BB width > 1.5x avg, ATR > 1.2x avg, HTF RSI overbought/oversold.
Quiet (Regime 4): BB width < 0.8x avg, ATR < 0.9x avg.
Other (Regime 5): Default for unclear conditions.
Indicators: ADX (14), BB width (20), ATR (14, 50-bar SMA), HTF RSI (14, daily default), HTF MACD (12,26,9).
Why It’s Brilliant:
Regime detection adapts signals to market context, boosting win rates in trending or volatile conditions.
HTF RSI/MACD add a big-picture filter, rare in basic scripts.
Visualized via gradient background (green for Trending, orange for Range, red for Volatile, gray for Quiet, navy for Other).
2. Multi-Factor Signal Scoring
Entries are driven by a weighted scoring system that combines candlestick patterns, trend, momentum, and volume for robust signals.
Candlestick Patterns:
Bullish: Engulfing (0.5), hammer (0.4 in Range, 0.2 else), morning star (0.2), piercing (0.2), double bottom (0.3 in Volatile, 0.15 else). Must be near support (low ≤ 1.01x 20-bar low) with volume spike (>1.5x 20-bar avg).
Bearish: Engulfing (0.5), shooting star (0.4 in Range, 0.2 else), evening star (0.2), dark cloud (0.2), double top (0.3 in Volatile, 0.15 else). Must be near resistance (high ≥ 0.99x 20-bar high) with volume spike.
Logic: Patterns are weighted higher in specific regimes (e.g., hammer in Range, double bottom in Volatile).
Additional Factors:
Trend: Fast EMA (20) > slow EMA (50) + 0.5x ATR (trend_bull, +0.2); opposite for trend_bear.
RSI: RSI (14) < 30 (rsi_bull, +0.15); > 70 (rsi_bear, +0.15).
MACD: MACD line > signal (12,26,9, macd_bull, +0.15); opposite for macd_bear.
Volume: ATR > 1.2x 50-bar avg (vol_expansion, +0.1).
HTF Confirmation: HTF RSI < 70 and MACD bullish (htf_bull_confirm, +0.2); RSI > 30 and MACD bearish (htf_bear_confirm, +0.2).
Scoring:
bull_score = sum of bullish factors; bear_score = sum of bearish. Entry requires score ≥ 1.0.
Example: Bullish engulfing (0.5) + trend_bull (0.2) + rsi_bull (0.15) + htf_bull_confirm (0.2) = 1.05, triggers long.
Why It’s Brilliant:
Multi-factor scoring ensures signals are confirmed by multiple market dynamics, reducing false positives.
Regime-specific weights make patterns more relevant (e.g., hammers shine in Range markets).
HTF confirmation aligns with the big picture, a quant edge over simplistic scripts.
3. Futures-Tuned Risk Management
The risk system is built for futures, calculating position sizes based on $ risk and offering flexible stops/TPs.
Position Sizing:
Logic: Risk per trade (default: $300) ÷ (stop distance in points * point value) = contracts, capped at max_contracts (default: 5). Point value = tick value (e.g., $12.5 for ES) * ticks per point (4) * contract multiplier (1 for ES, 0.1 for MES).
Example: $300 risk, 8-point stop, ES ($50/point) → 0.75 contracts, rounded to 1.
Impact: Precise sizing prevents over-leverage, critical for micro contracts like MES.
Stops and Take-Profits:
Fixed: Default stop = 8 points, TP = 16 points (2:1 reward/risk).
ATR-Based: Stop = 1.5x ATR (default), TP = 3x ATR, enabled via use_atr_for_stops.
Logic: Stops set at swing low/high ± stop distance; TPs at 2x stop distance from entry.
Impact: ATR stops adapt to volatility, while fixed stops suit stable markets.
Trailing Stops:
Logic: Activates at 50% of TP distance. Trails at close ± 1.5x ATR (atr_multiplier). Longs: max(trail_stop_long, close - ATR * 1.5); shorts: min(trail_stop_short, close + ATR * 1.5).
Impact: Locks in profits during trends, a game-changer in volatile sessions.
Circuit Breaker:
Logic: Pauses trading if daily drawdown > 5% (daily_drawdown = (max_equity - equity) / max_equity).
Impact: Protects capital during black swan events (e.g., April 27, 2025 ES slippage).
Why It’s Brilliant:
Futures-specific inputs (tick value, multiplier) make it plug-and-play for ES/MES.
Trailing stops and circuit breaker add pro-level safety, rare in off-the-shelf scripts.
Flexible stops (ATR or fixed) suit different trading styles.
4. Trade Entry and Exit Logic
Entries and exits are precise, driven by bull_score/bear_score and protected by drawdown checks.
Entry Conditions:
Long: bull_score ≥ 1.0, no position (position_size <= 0), drawdown < 5% (not pause_trading). Calculates contracts, sets stop at swing low - stop points, TP at 2x stop distance.
Short: bear_score ≥ 1.0, position_size >= 0, drawdown < 5%. Stop at swing high + stop points, TP at 2x stop distance.
Logic: Tracks entry_regime for PNL arrays. Closes opposite positions before entering.
Exit Conditions:
Stop-Loss/Take-Profit: Hits stop or TP (strategy.exit).
Trailing Stop: Activates at 50% TP, trails by ATR * 1.5.
Emergency Exit: Closes if price breaches stop (close < long_stop_price or close > short_stop_price).
Reset: Clears stop/TP prices when flat (position_size = 0).
Why It’s Brilliant:
Score-based entries ensure multi-factor confirmation, filtering out weak signals.
Trailing stops maximize profits in trends, unlike static exits in basic scripts.
Emergency exits add an extra safety layer, critical for futures volatility.
5. DAFE Visuals
The visuals are pure DAFE magic, blending function with cyberpunk flair to make signals intuitive and charts stunning.
Shimmering Bollinger Band Fill:
Display: BB basis (20, white), upper/lower (green/red, 45% transparent). Fill pulses (30–50 alpha) by regime, with glow (60–95 alpha) near bands (close ≥ 0.995x upper or ≤ 1.005x lower).
Purpose: Highlights volatility and key levels with a futuristic glow.
Visuals make complex regimes and signals instantly clear, even for newbies.
Pulsing effects and regime-specific colors add a DAFE signature, setting it apart from generic scripts.
BB glow emphasizes tradeable levels, enhancing decision-making.
Chart Background (Regime Heatmap):
Green — Trending Market: Strong, sustained price movement in one direction. The market is in a trend phase—momentum follows through.
Orange — Range-Bound: Market is consolidating or moving sideways, with no clear up/down trend. Great for mean reversion setups.
Red — Volatile Regime: High volatility, heightened risk, and larger/faster price swings—trade with caution.
Gray — Quiet/Low Volatility: Market is calm and inactive, with small moves—often poor conditions for most strategies.
Navy — Other/Neutral: Regime is uncertain or mixed; signals may be less reliable.
Bollinger Bands Glow (Dynamic Fill):
Neon Red Glow — Warning!: Price is near or breaking above the upper band; momentum is overstretched, watch for overbought conditions or reversals.
Bright Green Glow — Opportunity!: Price is near or breaking below the lower band; market could be oversold, prime for bounce or reversal.
Trend Green Fill — Trending Regime: Fills between bands with green when the market is trending, showing clear momentum.
Gold/Yellow Fill — Range Regime: Fills with gold/aqua in range conditions, showing the market is sideways/oscillating.
Magenta/Red Fill — Volatility Spike: Fills with vivid magenta/red during highly volatile regimes.
Blue Fill — Neutral/Quiet: A soft blue glow for other or uncertain market states.
Moving Averages:
Display: Blue fast EMA (20), red slow EMA (50), 2px.
Purpose: Shows trend direction, with trend_dir requiring ATR-scaled spread.
Dynamic SL/TP Lines:
Display: Pulsing colors (red SL, green TP for Trending; yellow/orange for Range, etc.), 3px, with pulse_alpha for shimmer.
Purpose: Tracks stops/TPs in real-time, color-coded by regime.
6. Dual Dashboards
Two dashboards deliver real-time insights, making the strat a quant command center.
Bottom-Left Metrics Dashboard (2x13):
Metrics: Mode (Active/Paused), trend (Bullish/Bearish/Neutral), ATR, ATR avg, volume spike (YES/NO), RSI (value + Oversold/Overbought/Neutral), HTF RSI, HTF trend, last signal (Buy/Sell/None), regime, bull score.
Display: Black (29% transparent), purple title, color-coded (green for bullish, red for bearish).
Purpose: Consolidates market context and signal strength.
Top-Right Position Dashboard (2x7):
Metrics: Regime, position side (Long/Short/None), position PNL ($), SL, TP, daily PNL ($).
Display: Black (29% transparent), purple title, color-coded (lime for Long, red for Short).
Purpose: Tracks live trades and profitability.
Why It’s Brilliant:
Dual dashboards cover market context and trade status, a rare feature.
Color-coding and concise metrics guide beginners (e.g., green “Buy” = go).
Real-time PNL and SL/TP visibility empower disciplined trading.
7. Performance Tracking
Logic: Arrays (regime_pnl_long/short, regime_win/loss_long/short) track PNL and win/loss by regime (1–5). Updated on trade close (barstate.isconfirmed).
Purpose: Prepares for future adaptive thresholds (e.g., adjust bull_score min based on regime performance).
Why It’s Brilliant: Lays the groundwork for self-optimizing logic, a quant edge over static scripts.
Key Features
Regime-Adaptive: Optimizes signals for Trending, Range, Volatile, Quiet markets.
Futures-Optimized: Precise sizing for ES/MES with tick-based risk inputs.
Multi-Factor Signals: Candlestick patterns, RSI, MACD, and HTF confirmation for robust entries.
Dynamic Exits: ATR/fixed stops, 2:1 TPs, and trailing stops maximize profits.
Safe and Smart: 5% drawdown breaker and emergency exits protect capital.
DAFE Visuals: Shimmering BB fill, pulsing SL/TP, and dual dashboards.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
How to Use
Add to Chart: Load on a 5min ES/MES chart in TradingView.
Configure Inputs: Set instrument (ES/MES), tick value ($12.5/$1.25), multiplier (1/0.1), risk ($300 default). Enable ATR stops for volatility.
Monitor Dashboards: Bottom-left for regime/signals, top-right for position/PNL.
Backtest: Run in strategy tester to compare regimes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see regime shifts and stops.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Backtest results may differ from live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Slippage: 3
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Adaptive Regime - Quant Machine Pro is more than a strategy—it’s a revolution. Crafted with DAFE’s signature precision, it rises above generic scripts with adaptive regimes, quant-grade signals, and visuals that make trading a thrill. Whether you’re scalping MES or swinging ES, this system empowers you to navigate markets with confidence and style. Join the DAFE crew, light up your charts, and let’s dominate the futures game!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
Volume Weighted Median Price (VWMP)The volume is indeed crucial for confirming price moves and understanding market conviction. While many traders are familiar with VWAP (Volume Weighted Average Price), this indicator introduces a lesser-known but powerful cousin: the Volume Weighted Median Price (VWMP).
What is VWMP?
Unlike VWAP, which calculates the average price weighted by volume over a period, VWMP identifies the median price level weighted by volume.
Think of it this way: If you line up all the trades within a specific lookback period, sorted by price, and then start accumulating the volume traded at each price level, the VWMP is the price level where 50% of the total volume occurred below it, and 50% occurred above it.
It essentially finds the "middle ground" of trading activity based on where the bulk of the volume actually traded, not just the average price.
Key Difference: VWMP vs. VWAP
VWAP: Volume Weighted Average Price. Sensitive to outliers (single large trades at extreme prices can skew the average).
VWMP: Volume Weighted Median Price. More robust to outliers. It represents the price that splits the period's volume distribution in half.
Because it uses the median, VWMP can sometimes provide a more stable or representative level of the "typical" price where significant volume is changing hands, especially in volatile markets or when large, anomalous trades occur.
How to Interpret and Use VWMP in trading
The VWMP plots as a line on your chart, similar to a moving average or VWAP. Here are a few ways traders might use it:
Dynamic Support and Resistance:
Like VWAP, the VWMP line can act as a dynamic level of interest.
Watch how price interacts with the VWMP. Consistent acceptance above VWMP might suggest bullish control and potential support.
Consistent rejection or acceptance below VWMP might indicate bearish control and potential resistance.
Trend Filter / Confirmation:
Uptrend: Look for price consistently staying above the VWMP line. Pullbacks to the VWMP that hold could offer entry opportunities.
Downtrend: Look for price consistently staying below the VWMP line. Rallies to the VWMP that fail could present shorting opportunities.
Use it to filter trades: Only take long trades if price is above VWMP, and short trades if below.
Mean Reversion Potential (Use with Caution):
When price extends significantly far away from the VWMP, some traders might look for potential reversion back towards this volume-based median level.
Important: This should not be used in isolation. Always look for confirmation from other indicators (like RSI, Stochastics, or candlestick patterns) before trading counter-trend reversions.
Confluence with Other Indicators:
VWMP works best when combined with other analysis tools.
Look for confluence: Does the VWMP align with a key Fibonacci level, a standard moving average, or a prior support/resistance zone? This confluence strengthens the level's potential significance.
Considerations
Lookback Period: The length input is crucial. A shorter period makes VWMP more responsive to recent action; a longer period makes it smoother and reflects longer-term volume distribution. Experiment to find what suits your timeframe and trading style.
Lagging Nature: Like all indicators based on past data, VWMP is inherently lagging. It reflects past volume distribution, not the future.
Market Context: Its effectiveness can vary depending on the market conditions (trending vs. ranging) and the asset being traded.
MTF Fibonacci Pivots with Mandelbrot FractalsMTF Fibonacci Pivots with Mandelbrot Fractals: Advanced Market Structure Analysis
Overview
The MTF Fibonacci Pivots with Mandelbrot Fractals indicator represents a significant advancement in technical analysis by combining multi-timeframe Fibonacci pivot levels with sophisticated fractal pattern recognition. This powerful tool identifies key support and resistance zones while predicting potential price reversals with remarkable accuracy.
Key Capabilities
This indicator provides traders with three distinct layers of market structure analysis:
Automatic Timeframe Adaptation: The primary pivot set automatically adjusts to your chart's timeframe, ensuring relevant support and resistance levels for your specific trading horizon.
1-Year Fibonacci Pivots: The second layer displays yearly pivots that reveal long-term market cycles and institutional price levels that often act as significant reversal points.
3-Year Fibonacci Pivots: The third layer unveils major market structure zones that typically remain relevant for extended periods, offering strategic context for position trading and long-term investment decisions.
Predictive Technology
What truly distinguishes this indicator is its advanced predictive capability powered by:
Mandelbrot Fractal Pattern Recognition: The indicator implements a sophisticated fractal detection algorithm that identifies recurring price patterns across multiple timeframes. Unlike conventional fractal indicators, it incorporates noise filtering and adaptive sensitivity to market volatility.
Tesla's 3-6-9 Principle Integration: The system incorporates Nikola Tesla's mathematical principle through a cubic Mandelbrot equation (Z_{n+1} = Z_n^3 + C where Z_0 = 0), creating a unique approach to pattern recognition that aligns with natural market rhythms.
Historical Pattern Matching: When a current price pattern exhibits strong similarity to historical formations, the indicator generates predictive targets with confidence ratings. Each prediction undergoes rigorous validation against multiple parameters including trend alignment, volatility context, and mathematical coherence.
Visual Intelligence System
The indicator's visual presentation enhances trading decision-making through:
Confidence-Based Visualization: Predictions display with intuitive star ratings, percentage confidence scores, and contextual information including price movement magnitude and estimated time to target.
Adaptive Color Harmonization: The color system intelligently adjusts to provide optimal visibility while maintaining a professional appearance suitable for any chart setup.
Trend Alignment Indicators: Each prediction includes references to the broader trend context, helping traders avoid counter-trend trades unless the reversal signal carries exceptional strength.
Strategic Applications
This indicator excels in multiple trading scenarios:
Intraday Trading: Identify high-probability reversal zones with precise timing
Swing Trading: Anticipate significant market turns at key structural levels
Position Trading: Recognize major cycle shifts for strategic entry and exit
The automatic 1-year and 3-year Fibonacci pivots provide institutional-grade reference points that typically define major market movements. These longer timeframes reveal critical zones that might be invisible on shorter-term analysis, giving you a significant edge in understanding where price is likely to encounter substantial buying or selling pressure.
This innovative approach to market analysis combines classical Fibonacci mathematics with cutting-edge fractal theory to create a comprehensive market structure visualization system that illuminates both present support/resistance levels and future price targets with exceptional clarity.
Setting Up MTF Fibonacci Pivots with Mandelbrot Fractals
Initial Setup
Adding this indicator to your TradingView charts is straightforward:
Navigate to the "Indicators" button on your chart toolbar
Search for "MTF Fibonacci Pivots with Mandelbrot Fractals"
Select the indicator to add it to your chart
A configuration panel will appear with various setting categories
Recommended Settings
The indicator comes pre-configured with optimal default settings, but you may want to adjust them based on your trading style:
For Day Trading (Timeframes 1-minute to 1-hour)
Pivots Timeframe 1: Auto (automatically adapts to your chart)
Pivots Timeframe 2: Daily
Pivots Timeframe 3: Weekly
Fractal Sensitivity: 2-3
Fractal Lookback Period: 20
Prediction Strength: 2
Color Theme: High Contrast or Dark Mode
For Swing Trading (Timeframes 4-hour to Daily)
Pivots Timeframe 1: Daily
Pivots Timeframe 2: Weekly
Pivots Timeframe 3: Monthly
Fractal Sensitivity: 1-2
Fractal Lookback Period: 30
Prediction Strength: 2-3
Color Theme: Default or Dimmed
For Position Trading (Timeframes Daily to Weekly)
Pivots Timeframe 1: Weekly
Pivots Timeframe 2: Monthly
Pivots Timeframe 3: Quarterly
Fractal Sensitivity: 1
Fractal Lookback Period: 50
Prediction Strength: 1
Color Theme: Monochrome or Pastel
Restoring Default Settings
If you've adjusted settings and wish to return to the defaults:
Right-click on the indicator name on your chart
Select "Settings" from the context menu
In the settings dialog, look for the "Reset All" button at the bottom
Confirm the reset when prompted
Alternatively, you can remove the indicator and add it again for a fresh start with default settings.
Advanced Settings Guidance
Visual Appearance
Use Gradient Colors: Enable for better visual differentiation between pivot levels
Color Transparency: 15% provides an optimal balance between visibility and chart clutter
Line Width: 1-2 for cleaner charts, 3+ for enhanced visibility
Fractal Analysis
Enable Fractal Analysis: Keep enabled for prediction capabilities
Fractal Box Spacing: Higher values (5-10) for cleaner displays, lower values (1-3) for more signals
Maximum Forecast Bars: 20 is optimal for most timeframes, adjust higher for longer predictions
Performance Considerations
Enable Self-Optimization: Keep enabled to maintain smooth chart performance
Resource Priority: Use "Balanced" for most computers, "Performance" for older systems
Force Pivot Display: Enable only when checking specific historical periods
Common Setup Mistakes to Avoid
Setting all timeframes too close together (e.g., Daily, Daily, Weekly) reduces the multi-timeframe advantage
Using high fractal sensitivity (4+) on noisy markets creates excessive signals
Setting fractal box spacing too low causes cluttered prediction boxes
Disabling self-optimization may cause performance issues on complex charts
Using incompatible color themes for your chart background reduces visibility
The indicator's power comes from its default 1-year and 3-year Fibonacci pivot settings, which highlight institutional levels while the auto-timeframe setting adapts to your trading horizon. These carefully balanced defaults provide an excellent starting point for most traders.
For optimal results, I recommend making minimal adjustments at first, then gradually customizing settings as you become familiar with the indicator's behavior in your specific markets and timeframes.
Screenshots:
Multiple AVWAP [OmegaTools]The Multiple AVWAP indicator is a sophisticated trading tool designed for professional traders who require precision in volume-weighted price tracking. This indicator allows for the deployment of multiple Anchored Volume Weighted Average Price (AVWAP) calculations simultaneously, offering deep insights into price movements, dynamic support and resistance levels, and trend structures across multiple timeframes.
This indicator caters to both institutional and retail traders by integrating flexible anchoring methods, multi-timeframe adaptability, and enhanced visualization features. It also includes deviation bands for statistical analysis, making it a comprehensive volume-based trading solution.
Key Features & Functionalities
1. Multiple AVWAP Configurations
Users can configure up to four distinct AVWAP calculations to track different market conditions.
Supports various anchoring methods:
Fixed: A traditional AVWAP that starts from a defined historical point.
Perpetual: A rolling VWAP that continuously adjusts over time.
Extension: An extension-based AVWAP that projects from past calculations.
High Volume: Anchors AVWAP to the highest volume bar within a specified period.
None: Option to disable AVWAP calculation if not required.
2. Advanced Deviation Bands
Implements standard deviation bands (1st and 2nd deviation) to provide a statistical measure of price dispersion from the AVWAP.
Serves as a dynamic method for identifying overbought and oversold conditions relative to VWAP pricing.
Deviation bands are customizable in terms of visibility, color, and transparency.
3. Multi-Timeframe Support
Users can assign different timeframes to each AVWAP calculation for macro and micro analysis.
Helps in identifying long-term institutional trading levels alongside short-term intraday trends.
4. Z-Score Normalization Mode
Option to standardize oscillator values based on AVWAP deviations.
Converts price movements into a statistical Z-score, allowing traders to measure price strength in a normalized range.
Helps in detecting extreme price dislocations and mean-reversion opportunities.
5. Customizable Visual & Aesthetic Settings
Fully customizable line colors, transparency, and thickness to enhance clarity.
Users can modify AVWAP and deviation band colors to distinguish between different levels.
Configurable display options to match personal trading preferences.
6. Oscillator Mode for Trend & Momentum Analysis
The indicator converts price deviations into an oscillator format, displaying AVWAP strength and weakness dynamically.
This provides traders with a momentum-based perspective on volume-weighted price movements.
User Guide & Implementation
1. Configuring AVWAPs for Optimal Use
Choose the mode for each AVWAP instance:
Fixed (set historical point)
Perpetual (rolling, continuously updated AVWAP)
Extension (projection from past AVWAP levels)
High Volume (anchored to highest volume bar)
None (disables the AVWAP line)
Adjust the length settings to fine-tune calculation sensitivity.
2. Utilizing Deviation Bands for Market Context
Activate deviation bands to see statistical boundaries of price action.
Monitor +1 / -1 and +2 / -2 standard deviation levels for extended price movements.
Consider price action outside of deviation bands as potential mean-reversion signals.
3. Multi-Timeframe Analysis for Institutional-Level Insights
Assign different timeframes to each AVWAP to compare:
Daily VWAP (institutional trading levels)
Weekly VWAP (swing trading trends)
Intraday VWAPs (short-term momentum shifts)
Helps identify where institutional liquidity is positioned relative to price.
4. Activating the Oscillator for Momentum & Bias Confirmation
The oscillator converts AVWAP deviations into a normalized value.
Use overbought/oversold levels to determine strength and potential reversals.
Combine with other indicators (RSI, MACD) for confluence-based trading decisions.
Trading Applications & Strategies
5. Trend Confirmation & Institutional VWAP Tracking
If price consistently holds above the primary AVWAP, it signals a bullish trend.
If price remains below AVWAP, it indicates selling pressure and a bearish trend.
Monitor retests of AVWAP levels for potential trend continuation or reversal.
6. Dynamic Support & Resistance Levels
AVWAP lines act as dynamic floating support and resistance zones.
Price bouncing off AVWAP suggests continuation, whereas breakdowns indicate a shift in momentum.
Look for confluence with high-volume zones for stronger trade signals.
7. Mean Reversion & Statistical Edge Trading
Prices that deviate beyond +2 or -2 standard deviations often revert toward AVWAP.
Mean reversion traders can fade extended moves and target AVWAP re-tests.
Helps in identifying exhaustion points in trending markets.
8. Institutional Liquidity & Volume Footprints
Institutions often execute large trades near VWAP zones, causing price reactions.
Tracking multi-timeframe AVWAP levels allows traders to anticipate key liquidity areas.
Use higher timeframe AVWAPs as macro support/resistance for swing trading setups.
9. Enhancing Momentum Trading with AVWAP Oscillator
The oscillator provides a momentum-based measure of AVWAP deviations.
Helps in confirming entry and exit timing for trend-following trades.
Useful for pairing with stochastic oscillators, MACD, or RSI to validate trade decisions.
Best Practices & Trading Tips
Use in Conjunction with Volume Analysis: Combine with volume profiles, OBV, or CVD for increased accuracy.
Adjust Timeframes Based on Trading Style: Scalpers can focus on short-term AVWAP, while swing traders benefit from weekly/daily AVWAP tracking.
Backtest Different AVWAP Configurations: Experiment with different anchoring methods and lookback periods to optimize trade performance.
Monitor Institutional Order Flow: Identify key VWAP zones where institutional traders may be active.
Use with Other Technical Indicators: Enhance trading confidence by integrating with moving averages, Bollinger Bands, or Fibonacci retracements.
Final Thoughts & Disclaimer
The Multiple AVWAP indicator provides a comprehensive approach to volume-weighted price tracking, making it ideal for professional traders. While this tool enhances market clarity and trade decision-making, it should be used as part of a well-rounded trading strategy with risk management principles in place.
This indicator is provided for informational and educational purposes only. Trading involves risk, and past performance is not indicative of future results. Always conduct your own analysis and due diligence before executing trades.
OmegaTools - Enhancing Market Clarity with Precision Indicators
Mehul - ADX Zero LagThis script combines two popular technical indicators into a single visualization:
1. **Average Directional Index (ADX)**:
- Measures trend strength on a scale from 0-100 (now normalized to 0-1 by dividing by 100)
- Displayed as a red line
- Adjustable smoothing and length parameters
2. **Zero Lag MACD (Modified Moving Average Convergence Divergence)**:
- An enhanced version of the traditional MACD with reduced lag
- Shows the relationship between fast and slow moving averages
- Main components include:
- MACD line (black)
- Signal line (gray)
- Histogram (green for positive, purple for negative)
- EMA of the MACD line (red)
- Optional crossing dots
Key features of the combined indicator:
- **Scale Adjustment**: Both indicators can be scaled independently (adxScale and macdScale parameters)
- **Visibility Toggles**: Each indicator can be shown or hidden
- **Advanced Customization**: Parameters for both indicators can be fine-tuned
- **Algorithm Selection**: Option to choose between the "Glaz" algorithm or the "real" zero lag algorithm
- **Display Options**: Toggles for visualization elements like crossing dots
The most significant technical aspect is that both indicators are displayed in the same pane with compatible scaling, achieved by normalizing the ADX values and applying user-defined scale factors to both indicators.
This combined indicator is designed to give traders a comprehensive view of both trend strength (from ADX) and momentum/direction (from Zero Lag MACD) in a single, easy-to-read visualization.
Ultimate Trading BotHow the "Ultimate Trading Bot" Works:
This Pine Script trading bot executes buy and sell trades based on a combination of technical indicators:
Indicators Used:
RSI (Relative Strength Index)
Measures momentum and determines overbought (70) and oversold (30) levels.
A crossover above 30 suggests a potential buy, and a cross below 70 suggests a potential sell.
Moving Average (MA)
A simple moving average (SMA) of 50 periods to track the trend.
Prices above the MA indicate an uptrend, while prices below indicate a downtrend.
Stochastic Oscillator (%K and %D)
Identifies overbought and oversold conditions using a smoothed stochastic formula.
A crossover of %K above %D signals a buy, and a crossover below %D signals a sell.
MACD (Moving Average Convergence Divergence)
Uses a 12-period fast EMA and a 26-period slow EMA, with a 9-period signal line.
A crossover of MACD above the signal line suggests a bullish move, and a cross below suggests bearish movement.
Trade Execution:
Buy (Long Entry) Conditions:
RSI crosses above 30 (indicating recovery from an oversold state).
The closing price is above the 50-period moving average (showing an uptrend).
The MACD line crosses above the signal line (indicating upward momentum).
The Stochastic %K crosses above %D (indicating bullish momentum).
→ If all conditions are met, the bot enters a long (buy) position.
Sell (Exit Trade) Conditions:
RSI crosses below 70 (indicating overbought conditions).
The closing price is below the 50-period moving average (downtrend).
The MACD line crosses below the signal line (bearish signal).
The Stochastic %K crosses below %D (bearish momentum).
→ If all conditions are met, the bot closes the long position.
Visuals:
The bot plots the moving average, RSI, MACD, and Stochastic indicators for reference.
It also displays buy/sell signals with arrows:
Green arrow (Buy Signal) → When all buy conditions are met.
Red arrow (Sell Signal) → When all sell conditions are met.
How to Use It in TradingView:
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
Waldo Momentum Cloud Bollinger Bands (WMCBB)
Title: Waldo Momentum Cloud Bollinger Bands (WMCBB)
Description:
Introducing the "Waldo Momentum Cloud Bollinger Bands (WMCBB)," an innovative trading tool crafted for those who aim to deepen their market analysis by merging two dynamic technical indicators: Dynamic RSI Bollinger Bands and the Waldo Cloud.
What is this Indicator?
WMCBB integrates the volatility-based traditional Bollinger Bands with a momentum-sensitive approach through the Relative Strength Index (RSI). Here’s how it works:
Dynamic RSI Bollinger Bands: These bands dynamically adjust according to the RSI, which tracks the momentum of price movements. By scaling the RSI to align with price levels, we generate bands that not only reflect market volatility but also the underlying momentum, offering a refined view of overbought and oversold conditions.
Waldo Cloud: This feature adds a layer of traditional Bollinger Bands, visualized as a 'cloud' on your chart. It employs standard Bollinger Band methodology but enhances it with additional moving average layers to better define market trends.
The cloud's color changes dynamically based on various market conditions, providing visual signals for trend direction and potential trend reversals.
Why Combine These Indicators?
Combining Dynamic RSI Bollinger Bands with the Waldo Cloud in WMCBB aims to:
Enhance Trend Identification: The Waldo Cloud's color-coded system aids in recognizing the overarching market trend, while the Dynamic RSI Bands give insights into momentum changes within that trend, offering a comprehensive view.
Improve Volatility and Momentum Analysis: While traditional Bollinger Bands measure market volatility, integrating RSI adds a layer of momentum analysis, potentially leading to more accurate trading signals.
Visual Clarity: The unified color scheme for both sets of bands, which changes according to RSI levels, moving average crossovers, and price positioning, simplifies the process of gauging market sentiment at a glance.
Customization: Users have the option to toggle the visibility of moving averages (MA) through the settings, allowing for tailored analysis based on individual trading strategies.
Usage:
Utilize WMCBB to identify potential trend shifts by observing price interactions with the dynamic bands or changes in the Waldo Cloud's color.
Watch for divergences between price movements and RSI to forecast potential market reversals or continuations.
This combination shines in sideways markets where traditional indicators might fall short, as it provides additional context through RSI momentum analysis.
Settings:
Customize parameters for both the Dynamic RSI and Waldo Cloud Bollinger Bands, including the calculation source, standard deviation factors, and moving average lengths.
WMCBB is perfect for traders seeking to enhance their market analysis through the synergy of momentum and volatility, all while maintaining visual simplicity. Trade with greater insight using the Waldo Momentum Cloud Bollinger Bands!
Aj's DikFat Adjusted ADXRAj's DikFat Adjusted ADXR
This indicator is designed to plot the Average Directional Index (ADX) and Average Directional Movement Rating (ADXR) on the chart. The ADX and ADXR are both used to measure the strength of a trend in the market. The script allows you to customize several parameters, including the ADX Length and the Moving Average Method used for smoothing the directional movement indicators.
Key Features:
- ADX Length : Defines the number of periods over which the ADX is calculated. This value can be adjusted by the user to suit different trading styles and timeframes.
- Moving Average Method : Choose between several smoothing methods, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Wilder's Moving Average, Weighted Moving Average (WMA), Hull Moving Average (HMA), or a Super Smooth Moving Average.
- Directional Indicators : The script calculates the +DI and -DI, which represent the positive and negative directional indicators respectively. These are then used to calculate the ADX.
- ADXR : The ADXR is calculated as the average of the current ADX value and the ADX value from 14 periods ago, providing a more smoothed representation of the trend strength.
How Traders Use ADX and ADXR:
- ADX : A rising ADX indicates an increasing trend strength, while a falling ADX suggests a weakening trend. A value above 25 is often considered an indication of a strong trend.
- ADXR : This indicator smooths the ADX over time, helping traders identify persistent trends. The ADXR can help filter out noise and provide a clearer picture of the trend's health.
Please note that this script and its indicators are designed to be used as tools for analysis, not as guarantees of market outcomes. Adjustments to the moving average method or ADX length can change the behavior of the indicators based on market conditions.
Price Imbalance as Consecutive Levels of AveragesOverview
The Price Imbalance as Consecutive Levels of Averages indicator is an advanced technical analysis tool designed to identify and visualize price imbalances in financial markets. Unlike traditional moving average (MA) indicators that update continuously with each new price bar, this indicator employs moving averages calculated over consecutive, non-overlapping historical windows. This unique approach leverages comparative historical data to provide deeper insights into trend strength and potential reversals, offering traders a more nuanced understanding of market dynamics and reducing the likelihood of false signals or fakeouts.
Key Features
Consecutive Rolling Moving Averages: Utilizes three distinct simple moving averages (SMAs) calculated over consecutive, non-overlapping windows to capture different historical segments of price data.
Dynamic Color-Coded Visualization: SMA lines change color and style based on the relationship between the averages, highlighting both extreme and normal market conditions.
Median and Secondary Median Lines: Provides additional layers of price distribution insight during normal trend conditions through the plotting of primary and secondary median lines.
Fakeout Prevention: Filters out short-term volatility and sharp price movements by requiring consistent historical alignment of multiple moving averages.
Customizable Parameters: Offers flexibility to adjust SMA window lengths and line extensions to align with various trading strategies and timeframes.
Real-Time Updates with Historical Context: Continuously recalculates and updates SMA lines based on comparative historical windows, ensuring that the indicator reflects both current and past market conditions.
Inputs & Settings
Rolling Window Lengths:
Window 1 Length (Most Recent) Bars: Number of bars used to calculate the most recent SMA. (Default: 5, Range: 2–300)
Window 2 Length (Preceding) Bars: Number of bars for the second SMA, shifted by Window 1. (Default: 8, Range: 2–300)
Window 3 Length (Third Rolling) Bars: Number of bars for the third SMA, shifted by the combined lengths of Window 1 and Window 2. (Default: 13, Range: 2–300)
Horizontal Line Extension:
Horizontal Line Extension (Bars): Determines how far each SMA line extends horizontally on the chart. (Default: 10 bars, Range: 1–100)
Functionality and Theory
1. Calculating Consecutive Simple Moving Averages (SMAs):
The indicator calculates three SMAs, each based on distinct and consecutive historical windows of price data. This approach contrasts with traditional MAs that continuously update with each new price bar, offering a static view of past trends rather than an ongoing one.
Mean1 (SMA1): Calculated over the most recent Window 1 Length bars. Represents the short-term trend.
Mean1=∑i=1N1CloseiN1
Mean1=N1∑i=1N1Closei
Where N1N1 is the length of Window 1.
Mean2 (SMA2): Calculated over the preceding Window 2 Length bars, shifted back by Window 1 Length bars. Represents the medium-term trend.
\text{Mean2} = \frac{\sum_{i=1}^{N_2} \text{Close}_{i + N_1}}}{N_2}
Where N2N2 is the length of Window 2.
Mean3 (SMA3): Calculated over the third rolling Window 3 Length bars, shifted back by the combined lengths of Window 1 and Window 2 bars. Represents the long-term trend.
\text{Mean3} = \frac{\sum_{i=1}^{N_3} \text{Close}_{i + N_1 + N_2}}}{N_3}
Where N3N3 is the length of Window 3.
2. Determining Market Conditions:
The relationship between the three SMAs categorizes the market condition into either extreme or normal states, enabling traders to quickly assess trend strength and potential reversals.
Extreme Bullish:
Mean3Mean2>Mean1
Mean3>Mean2>Mean1
Indicates a strong and sustained downward trend. SMA lines are colored purple and styled as dashed lines.
Normal Bullish:
Mean1>Mean2andnot in extreme bullish condition
Mean1>Mean2andnot in extreme bullish condition
Indicates a standard upward trend. SMA lines are colored green and styled as solid lines.
Normal Bearish:
Mean1Mean2>Mean1
Mean3>Mean2>Mean1
Normal Bullish:
Mean1>Mean2andnot in Extreme Bullish
Mean1>Mean2andnot in Extreme Bullish
Normal Bearish:
Mean1 Mean2 > Mean3
Visualization: All three SMAs are displayed as gold dashed lines.
Median Lines: Not displayed to maintain chart clarity.
Interpretation: Indicates a strong and sustained upward trend. Traders may consider entering long positions, confident in the trend's strength without the distraction of additional lines.
2. Normal Bullish Condition:
SMAs Alignment: Mean1 > Mean2 (not in extreme condition)
Visualization: Mean1 and Mean2 are green solid lines; Mean3 is gray.
Median Lines: A thin blue dotted median line is plotted between Mean1 and Mean2, with two additional thin blue dashed lines as secondary medians.
Interpretation: Confirms an upward trend while providing deeper insights into price distribution. Traders can use the median and secondary median lines to identify optimal entry points and manage risk more effectively.
3. Extreme Bearish Condition:
SMAs Alignment: Mean3 > Mean2 > Mean1
Visualization: All three SMAs are displayed as purple dashed lines.
Median Lines: Not displayed to maintain chart clarity.
Interpretation: Indicates a strong and sustained downward trend. Traders may consider entering short positions, confident in the trend's strength without the distraction of additional lines.
4. Normal Bearish Condition:
SMAs Alignment: Mean1 < Mean2 (not in extreme condition)
Visualization: Mean1 and Mean2 are red solid lines; Mean3 is gray.
Median Lines: A thin blue dotted median line is plotted between Mean1 and Mean2, with two additional thin blue dashed lines as secondary medians.
Interpretation: Confirms a downward trend while providing deeper insights into price distribution. Traders can use the median and secondary median lines to identify optimal entry points and manage risk more effectively.
Customization and Flexibility
The Price Imbalance as Consecutive Levels of Averages indicator is highly adaptable, allowing traders to tailor it to their specific trading styles and market conditions through adjustable parameters:
SMA Window Lengths: Modify the lengths of Window 1, Window 2, and Window 3 to capture different historical trend segments, whether focusing on short-term fluctuations or long-term movements.
Line Extension: Adjust the horizontal extension of SMA and median lines to align with different trading horizons and chart preferences.
Color and Style Preferences: While default colors and styles are optimized for clarity, traders can customize these elements to match their personal chart aesthetics and enhance visual differentiation.
This flexibility ensures that the indicator remains versatile and applicable across various markets, asset classes, and trading strategies, providing valuable insights tailored to individual trading needs.
Conclusion
The Price Imbalance as Consecutive Levels of Averages indicator offers a comprehensive and innovative approach to analyzing price trends and imbalances within financial markets. By utilizing three consecutive, non-overlapping SMAs and incorporating median lines during normal trend conditions, the indicator provides clear and actionable insights into trend strength and price distribution. Its unique design leverages comparative historical data, distinguishing it from traditional moving averages and enhancing its utility in identifying genuine market movements while minimizing false signals. This dynamic and customizable tool empowers traders to refine their technical analysis, optimize their trading strategies, and navigate the markets with greater confidence and precision.
Donchian Cloud-V1The Donchian Cloud-V1 is a technical analysis indicator inspired by the Ichimoku Cloud, but with a twist. It utilizes two Donchian Channel midline calculations to create a cloud-like price zone. This indicator aims to help traders identify potential areas of support and resistance, and also suggests that trades should be avoided when prices are within the cloud.
How it Works?
The Donchian Cloud-V1 calculates two Donchian Channel midlines:
Fast Donchian Channel: This midline is based on a shorter period, making it more responsive to price changes.
Slow Donchian Channel: This midline is based on a longer period, providing a smoother and more stable cloud formation.
The upper and lower bands of the traditional Donchian Channels are discarded, and the midlines become the cloud's upper and lower boundaries.
Interpretation
Price Above the Cloud: A price move above the cloud can be interpreted as a bullish signal, suggesting potential upward momentum.
Price Below the Cloud: A price move below the cloud can be interpreted as a bearish signal, suggesting potential downward momentum.
Price Within the Cloud: The indicator advises against taking any trades when the price is within the cloud itself, as the market may be unclear or ranging.
Benefits of Using the Donchian Cloud-V1
Visually Appealing: The cloud can provide a clear and concise view of potential support and resistance zones.
Customizable: The lengths of the fast and slow Donchian Channels can be adjusted to suit your trading style and preferred timeframe.
Complements Other Indicators: The Donchian Cloud-V1 can be used in conjunction with other technical indicators to strengthen trade signals.
Limitations to Consider
Lagging Indicator: Like many technical indicators, the Donchian Cloud-V1 is based on past price data and may not always perfectly predict future price movements.
False Signals: The cloud can generate false signals, especially in volatile markets.
Not a Standalone Strategy: The Donchian Cloud-V1 should ideally be used alongside other trading strategies and risk management techniques.
The Donchian Cloud-V1 is a valuable tool for traders who want to identify potential support and resistance zones and avoid making trades during periods of market uncertainty. Remember, it's important to backtest and paper trade any indicator before using it with real capital.
Rosiz Support 1### Description of the Custom Indicator: MACD + CMF + MOM
This custom indicator combines three powerful technical analysis tools: **MACD (Moving Average Convergence Divergence)**, **CMF (Chaikin Money Flow)**, and **MOM (Momentum)**, to provide a comprehensive view of market trends, momentum, and money flow in a single pane. Here's what each component offers:
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#### 1. **MACD (Moving Average Convergence Divergence)**
The **MACD** is a trend-following momentum indicator that shows the relationship between two moving averages of an asset’s price.
- **Purpose**: Identifies trend direction and momentum strength.
- **Key Components**:
- **MACD Line**: Difference between the fast and slow exponential moving averages (EMA).
- **Signal Line**: A smoothed moving average of the MACD line, acting as a trigger for buy/sell signals.
- **Histogram**: The difference between the MACD line and the signal line. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
- **Usage**: Look for crossovers (MACD crossing the signal line) to identify potential trend changes.
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#### 2. **CMF (Chaikin Money Flow)**
The **CMF** measures the volume-weighted average of accumulation and distribution over a specific period. It shows whether money is flowing into or out of an asset.
- **Purpose**: Detects buying or selling pressure based on price and volume.
- **Key Components**:
- **Positive CMF**: Indicates that the asset is being accumulated (buying pressure).
- **Negative CMF**: Indicates that the asset is being distributed (selling pressure).
- **Usage**: Values above 0 suggest bullish strength, while values below 0 suggest bearish strength.
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#### 3. **MOM (Momentum)**
The **Momentum Indicator** measures the rate of change of an asset's price over a specified period. It helps traders identify the speed of price movements.
- **Purpose**: Highlights the strength and direction of price momentum.
- **Key Components**:
- **Momentum Line**: Positive values indicate upward momentum, while negative values indicate downward momentum.
- **Usage**: A rising momentum line suggests strengthening price trends, while a falling line indicates weakening trends.
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### Benefits of Combining These Indicators:
1. **Trend Confirmation**: MACD provides a clear picture of trend direction and potential reversals.
2. **Volume-Based Insights**: CMF adds a layer of confirmation by analyzing money flow based on price and volume.
3. **Momentum Analysis**: MOM reveals the speed and strength of price movements, helping traders confirm breakouts or trend exhaustion.
4. **Enhanced Decision-Making**: The combination of these indicators allows traders to make more informed decisions by evaluating different aspects of market behavior in one pane.
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### How to Use:
- **Identify Trends**: Use MACD to identify overall trend direction and reversals.
- **Confirm Momentum**: Check MOM to validate the strength of the trend.
- **Gauge Buying/Selling Pressure**: Refer to CMF to confirm whether the price movement is backed by accumulation or distribution.
- **Entry/Exit Points**: Look for MACD crossovers, CMF shifts above/below zero, and momentum changes to refine entry and exit strategies.
This powerful tool integrates the strengths of three indicators, making it ideal for traders looking to analyze market conditions holistically and improve their timing and accuracy.
Volume Footprint POC for Every CandleCalculating and plotting the Point of Control (POC) for every candle on a volume footprint chart can provide valuable insights for traders. Here are some interpretations and uses of this information:
1. Identify Key Price Levels
Highest Traded Volume: The POC represents the price level with the highest traded volume for each candle. This level often acts as a significant support or resistance level.
Confluence Zones: When multiple POCs align at similar price levels over several candles, it indicates strong support or resistance zones.
2. Gauge Market Sentiment
Buyer and Seller Activity: High volume at certain price levels can indicate where buyers and sellers are most active. A rising POC suggests stronger buying activity, while a falling POC suggests stronger selling activity.
Volume Profile: Analyzing the volume profile helps in understanding the distribution of traded volume across different price levels, providing insights into market sentiment and potential reversals.
3. Spot Trends and Reversals
Trend Continuation: Consistent upward or downward shifts in POC levels can indicate a trend continuation. Traders can use this information to stay in trending positions.
Reversal Signals: A sudden change in the POC direction may signal a potential reversal. This can be used to take profits or enter new positions.
4. Intraday Trading Strategies
Short-Term Trading: Intraday traders can use the POC to make informed decisions on entry and exit points. For example, buying near the POC during an uptrend or selling near the POC during a downtrend.
Scalping Opportunities: High-frequency traders can use shifts in the POC to scalp small profits from price movements around these key levels.
5. Volume-Based Indicators
Confirmation of Other Indicators: The POC can be used in conjunction with other technical indicators (e.g., moving averages, RSI) to confirm signals and improve trading accuracy.
Support and Resistance: Combining the POC with traditional support and resistance levels can provide a more comprehensive view of the market dynamics.
In summary, the Point of Control (POC) is a valuable tool for traders to understand market behavior, identify key levels, and make more informed trading decisions. If you have specific questions or need further details on how to use this information in your trading strategy, feel free to ask! 😊
4Vietnamese 3x SupertrendThis strategy attempts to capture long positions in the Vietnamese stock market using a combination of three Supertrend indicators and additional filters. It utilizes pyramiding to enter up to three long positions with a 33.33% allocation each.
Key Elements:
Supertrend Indicators: Three Supertrend indicators are used with different lengths and multipliers to identify potential trend changes.
Entry Conditions:
The strategy looks for a downtrend on the slowest Supertrend (Supertrend3) followed by uptrends on the medium (Supertrend2) and fast (Supertrend1) Supertrends.
Alternatively, if Supertrend3 is still downtrending, but Supertrend1 is downtrending and a significant previous high (highestGreen) exists, an entry signal is generated.
An optional filter allows using the highest of the last two red candles for highestGreen calculation.
Entry Stop Loss:
An optional stop loss can be set based on the entry price of previous long positions, preventing further losses if the price falls below entry prices.
Exit Conditions:
Three exit options are available:
- All Downtrend Exit: Close all positions if all Supertrends turn uptrend and a bearish candlestick pattern (close price lower than open price) is formed.
- Average Price in Loss Exit: Close all positions if the average entry price of open positions is higher than the current closing price (indicating a loss).
- All Positions in Loss Exit: Close all positions if any of the following conditions are met:
A single open position exists, and its entry price is higher than the current close price.
Two open positions exist, and their entry prices are both higher than the current close price.
Three open positions exist, and their entry prices are all higher than the current close price.
Pyramiding: The strategy allows entering up to three long positions with a fixed allocation of 33.33% each.
Customization Options:
The strategy provides various input parameters to customize its behavior:
Supertrend lengths and multipliers for each indicator.
Option to use the highest of the last two red candles for highestGreen calculation.
Enabling/disabling Entry Stop Loss and different exit conditions.
Further Enhancements:
Explore additional entry and exit filters to refine trade signals.
Consider incorporating risk management techniques like position sizing and trailing stops.
Backtest the strategy with historical data to evaluate its effectiveness and identify potential areas for improvement.
Twiggs Money FlowTwiggs Money Flow (TMF)
This indicator is an implementation of the Twiggs Money Flow (TMF), a volume-based tool designed to measure buying and selling pressure over a specified period. TMF is an enhancement of Chaikin Money Flow (CMF), utilizing more sophisticated smoothing techniques for improved accuracy and reduced noise. This version is highly customizable and includes advanced features for both new and experienced traders.
What is Twiggs Money Flow?
Twiggs Money Flow was developed by Colin Twiggs to provide a clearer picture of market momentum and the balance between buyers and sellers. It uses a combination of price action, trading volume, and range calculations to assess whether a market is under buying or selling pressure.
Unlike traditional volume indicators, TMF incorporates Weighted Moving Averages (WMA) by default but allows for other moving average types (SMA, EMA, VWMA) for added flexibility. This makes it adaptable to various trading styles and market conditions.
Features of This Script:
Customizable Moving Average Types:
Select from SMA , EMA , WMA , or VWMA to smooth volume and price-based calculations.
Tailor the indicator to align with your trading strategy or the asset's behavior.
Optional HMA Smoothing:
Apply Hull Moving Average (HMA) smoothing for a cleaner, faster-reacting TMF line.
Perfect for traders who want to reduce lag and capture trends earlier.
Dynamic Thresholds for Signal Filtering:
Set user-defined thresholds for Long (LT) and Short (ST) signals to highlight significant momentum.
Focus on actionable trends by ignoring noise around neutral levels.
Bar Coloring for Visual Clarity:
Automatically colors your chart bars based on TMF values:
Aqua for strong bullish signals (above the long threshold).
Fuchsia for strong bearish signals (below the short threshold).
Gray for neutral or undecided market conditions.
Ensures that trend direction and strength are visually intuitive.
Configurable Lookback Period:
Adjust the sensitivity of TMF by customizing the length of the lookback period to suit different timeframes and market conditions.
How It Works:
True Range Calculation: The script determines the high, low, and close range to calculate buying and selling pressure.
Adjusted Volume: Incorporates the relationship between price and volume to gauge whether trading activity is favoring buyers or sellers.
Weighted Moving Averages (WMAs): Smooths both volume and adjusted volume values to eliminate erratic fluctuations.
TMF Line: Computes the ratio of adjusted volume to total volume, representing the net buying/selling pressure as a percentage.
HMA Option (if enabled): Smooths the TMF line further to reduce lag and enhance trend identification.
Bar Coloring Logic:
Bars are colored dynamically based on TMF values, thresholds, and smoothing preferences.
Provides an at-a-glance understanding of market conditions.
Input Parameters:
Lookback Period: Defines the number of bars used to calculate TMF (default: 21).
Use HMA Smoothing: Toggle Hull Moving Average smoothing (default: true).
HMA Smoothing Length: Length of the HMA smoothing period (default: 14).
Moving Average Type: Select SMA, EMA, WMA, or VWMA (default: WMA).
Long Threshold (LT): Threshold value above which a long signal is considered (default: 0).
Short Threshold (ST): Threshold value below which a short signal is considered (default: 0).
How to Use It:
Confirm Trends: TMF can validate trends by identifying periods of sustained buying or selling pressure.
Divergence Signals: Watch for divergences between price and TMF to anticipate potential reversals.
Filter Trades: Use the thresholds to ignore weak signals and focus on strong trends.
Combine with Other Indicators: Pair TMF with trend-following or momentum indicators (e.g., RSI, Bollinger Bands) for a comprehensive trading strategy.
Example Use Cases:
Spotting breakouts when TMF crosses above the long threshold.
Identifying sell-offs when TMF dips below the short threshold.
Avoiding sideways markets by ignoring neutral (gray) bars.
Notes:
This indicator is highly customizable, making it versatile across different assets (e.g., stocks, crypto, forex).
While the default settings are robust, tweaking the lookback period, moving average type, and thresholds is recommended for different trading instruments or strategies.
Always backtest thoroughly before applying the indicator to live trading.
This version of Twiggs Money Flow goes beyond standard implementations by offering advanced smoothing, custom thresholds, and enhanced visual feedback to give traders a competitive edge.
Add it to your charts and experience the power of volume-driven analysis!
