ICT & SMC Multi-Timeframe by [KhedrFX]Transform your trading experience with the ICT & SMC Multi-Timeframe by indicator. This innovative tool is designed for traders who want to harness the power of multi-timeframe analysis, enabling them to make informed trading decisions based on key market insights. By integrating concepts from the Inner Circle Trader (ICT) and Smart Money Concepts (SMC), this indicator provides a comprehensive view of market dynamics, helping you identify potential trading opportunities with precision.
Key Features
- Multi-Timeframe Analysis: Effortlessly switch between various timeframes (5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, daily, and weekly) to capture the full spectrum of market movements.
- High and Low Levels: Automatically calculates and displays the highest and lowest price levels over the last 20 bars, highlighting critical support and resistance zones.
- Market Structure Visualization: Identifies the last swing high and swing low, allowing you to recognize current market trends and potential reversal points.
- Order Block Detection: Detects significant order blocks, pinpointing areas of strong buying or selling pressure that can indicate potential market reversals.
- Custom Alerts: Set alerts for when the price crosses above or below identified order block levels, enabling you to act swiftly on trading opportunities.
How to Use the Indicator
1. Add the Indicator to Your Chart
- Open TradingView.
- Click on the "Indicators" button at the top of the screen.
- Search for "ICT & SMC Multi-Timeframe by " in the search bar.
- Click on the indicator to add it to your chart.
2. Select Your Timeframe
- Use the dropdown menu to choose your preferred timeframe (5, 15, 30, 60, 240, D, W) for analysis.
3. Interpret the Signals
- High Level (Green Line): Represents the highest price level over the last 20 bars, acting as a potential resistance level.
- Low Level (Red Line): Represents the lowest price level over the last 20 bars, acting as a potential support level.
- Last Swing High (Blue Cross): Indicates the most recent significant high, useful for identifying potential reversal points.
- Last Swing Low (Orange Cross): Indicates the most recent significant low, providing insight into market structure.
- Order Block High (Purple Line): Marks the upper boundary of a detected order block, suggesting potential selling pressure.
- Order Block Low (Yellow Line): Marks the lower boundary of a detected order block, indicating potential buying pressure.
4. Set Alerts
- Utilize the alert conditions to receive notifications when the price crosses above or below the order block levels, allowing you to stay informed about potential trading opportunities.
5. Implement Risk Management
- Always use proper risk management techniques. Consider setting stop-loss orders based on the identified swing highs and lows or the order block levels to protect your capital.
Conclusion
The ICT & SMC Multi-Timeframe by indicator is an essential tool for traders looking to enhance their market analysis and decision-making process. By leveraging multi-timeframe insights, market structure visualization, and order block detection, you can navigate the complexities of the market with confidence. Start using this powerful indicator today and take your trading to the next level.
⚠️ Trade Responsibly
This tool helps you analyze the market, but it’s not a guarantee of profits. Always do your own research, manage risk, and trade with caution.
Cerca negli script per "30年国债收益率"
Sahid Strategy v2This script identifies potential buy/sell signals using:
Pivot Points - Detects swing highs/lows (price reversals)
Confirmation Filters - Reduces false signals using:
RSI (momentum)
Moving Average (trend direction)
Optional MACD (trend confirmation)
Key Features
Signal Type Trigger Conditions
BUY - Price makes a swing low (pivot)
Copy
- RSI ≤ 30 (oversold)
- Price above trend MA
- MACD bullish (optional) |
| SELL | - Price makes a swing high (pivot)
- RSI ≥ 70 (overbought)
- Price below trend MA
- MACD bearish (optional) |
Visual Signals
Green "BUY" labels below price bars
Red "SELL" labels above price bars
Purple trend line (20-period EMA/SMA)
Orange/blue circles showing raw pivot points
Optional Tools
Debug Table (top-right): Shows real-time:
RSI value
Price vs MA position
MACD status
Alerts - Triggers audible/visual notifications
Customization
Adjust in settings:
Pivot sensitivity (left/right bars)
RSI levels (30/70 by default)
MA type/length (20-period EMA/SMA)
Toggle MACD filter on/off
Best For: Swing trading in trending markets (1H-4H timeframes). Signals appear faster than classic pivot strategies but still require confirmation from other analysis tools.
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB
🛠️ Overview
Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions.
Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes.
✨ Key Features
🔹 Trend Following with Adaptive Sensitivity
The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum.
🔹 Volatility-Adjusted Filtering
The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility.
🔹 Clear Signal Generation
QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals.
🔹 Customizable Visual & Signal Settings
With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments.
📊 How It Works
1️⃣ DEMA Calculation
DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise.
2️⃣ SuperTrend with Percentile Filtering
The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data:
• Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier)
• Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier)
These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction.
3️⃣ Signal Generation
• Long Signal: Triggered when price crosses below the SuperTrend Lower Band
• Short Signal: Triggered when price crosses above the SuperTrend Upper Band
The indicator provides signals with corresponding trend direction based on these crossovers.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style.
• 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered.
• 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias.
👥 Who Should Use QDT?
✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets.
✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns.
✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods.
✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering.
⚙️ Customization & Default Settings
- DEMA Length(30): Controls the lookback period for DEMA calculation
- Percentile Length(10): Sets the lookback period for percentile filtering
- ATR Length(14): Defines the length for calculating ATR (used in SuperTrend)
- ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation
- SuperTrend Length(30):Defines the length for SuperTrend calculations
📌 How to Use QDT in Trading
1️⃣ Trend-Following Strategy
✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band).
✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band).
✔ Hold positions as long as QDT continues to provide the same direction.
2️⃣ Reversal Strategy
✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion.
3️⃣ Volatility-Driven Entries
✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets.
🧠 Why It Works
QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments.
🔹 Conclusion
The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points.
🔹 Key Takeaways:
1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection
2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic
3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Normalized MACD with RSI & Stoch RSI + SignalsNormalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
Here’s a clear and concise description of your updated Pine Script indicator:
⸻
Normalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
⸻
Key Components:
① MACD (Normalized):
• The Moving Average Convergence Divergence (MACD) originally has an unlimited numerical range.
• Normalization Method:
• Uses a custom tanh(x) function implemented directly in Pine Script:
\tanh(x) = \frac{e^{x}-e^{-x}}{e^{x}+e^{-x}}
• MACD values are scaled using this method to a range of 0–100, with the neutral line at exactly 50.
• Interpretation:
• Values above 50 indicate bullish momentum.
• Values below 50 indicate bearish momentum.
② RSI (Relative Strength Index):
• Measures market momentum on a 0–100 scale.
• Traditional RSI interpretation:
• Overbought conditions: RSI > 70–80.
• Oversold conditions: RSI < 30–20.
③ Stochastic RSI:
• Combines RSI and Stochastic Oscillator to give short-term, highly sensitive signals.
• Helps identify immediate market extremes:
• Above 80 → Short-term overbought.
• Below 20 → Short-term oversold.
⸻
How the Indicator Works:
• Visualization:
• All three indicators (Normalized MACD, RSI, Stochastic RSI) share the same 0–100 scale.
• Clear visual lines and reference levels:
• Midline at 50 indicates neutral momentum.
• Dashed lines at 20 and 80 clearly mark oversold/overbought zones.
• Trading Signals (Recommended approach):
• Bullish Signal (Potential Buy):
• Normalized MACD crosses above 50.
• RSI below or approaching oversold zone (below 30–20).
• Stochastic RSI below 20, indicating short-term oversold conditions.
• Bearish Signal (Potential Sell):
• Normalized MACD crosses below 50.
• RSI above or approaching overbought zone (above 70–80).
• Stochastic RSI above 80, indicating short-term overbought conditions.
⸻
Why Use This Indicator?
• Harmonized Signals:
Normalization of MACD significantly improves clarity and comparability with RSI and Stochastic RSI, providing a unified momentum picture.
• Intuitive Analysis:
Traders can rapidly and intuitively identify momentum shifts without needing multiple indicator windows.
• Improved Decision-Making:
Clear visual references and signals help reduce subjective interpretation, potentially improving trading outcomes.
⸻
Suggested Usage:
• Combine with traditional support
Pre-Market High/Low (Static Lines + Labels)
Pre-Market Range ✅
Draws the Pre-Market High & Low from 4:00 AM to 9:30 AM ET using accurate 1-minute intraday data.
Static Lines 📏
Plots dashed horizontal lines that remain visible all day across all timeframes — including 1m, 5m, 15m, 1h, 4h, and Daily.
Price Labels 🔖
Includes real-time price labels so you can easily reference exact pre-market levels on the chart.
Session Lock 🕒
Lines are locked in after 9:30 AM and remain visible even if you switch timeframes or turn off extended hours.
Trading Utility 🎯
Ideal for identifying key breakout levels, intraday support/resistance zones, and setting risk parameters.
LUX CLARA - EMA + VWAP (No ATR Filter) - v6EMA STRAT SHOUT OUTOUTLIERSSSSS
Overview:
an intraday strategy built around two core principles:
Trend Confirmation using the 50 EMA (Exponential Moving Average) in relation to the VWAP (Volume-Weighted Average Price).
Entry Signals triggered by the 8 EMA crossing the 50 EMA in the direction of that confirmed trend.
Key Logic:
Bullish Trend if the 50 EMA is above VWAP. Only long entries are allowed when the 8 EMA crosses above the 50 EMA during that bullish phase.
Bearish Trend if the 50 EMA is below VWAP. Only short entries are allowed when the 8 EMA crosses below the 50 EMA during that bearish phase.
Intraday Focus: Trades are restricted to a user-defined session window (default 7:30 AM–11:30 AM), aligning entries/exits with peak intraday liquidity.
Exit Rule: Positions close automatically when the 8 EMA crosses back in the opposite direction of the entry.
Why It Works:
EMA + VWAP helps detect both immediate momentum (EMAs) and overall institutional bias (VWAP).
By confining trades to a set intraday window, the strategy aims to capture morning volatility while avoiding choppy afternoon or overnight sessions.
Customization:
Users can adjust EMA lengths, session times, or incorporate stops/targets for additional risk management.
It can be tested on various symbols and intraday timeframes to gauge performance and robustness.
NasyI## NasyI - Multi-Timeframe Technical Analysis Toolkit
### English Description
**NasyI** is a comprehensive technical analysis indicator designed to provide traders with a complete view of market dynamics across multiple timeframes. This indicator combines the power of Exponential Moving Averages (EMAs), Simple Moving Averages (MAs), Volume Weighted Average Price (VWAP), and key support/resistance levels to help traders identify trend direction, potential reversal points, and optimal entry/exit opportunities.
#### Key Features
1. **Multi-Timeframe Analysis System**
- 2-minute EMAs (13, 48) for ultra-short-term trend identification
- 5-minute EMAs (9, 13, 21, 48, 200) for short-term trend confirmation
- Daily EMAs (5, 13, 21, 48, 100, 200) and MAs (20, 50, 100, 200) for longer-term perspective
- Color-coded bands between key EMAs to visually identify trend strength and direction
2. **Advanced VWAP Integration**
- Daily VWAP for intraday support/resistance
- Weekly VWAP for medium-term price reference
- Monthly VWAP for long-term institutional price levels
- All VWAPs properly reset at their respective time period boundaries
3. **Critical Price Level Identification**
- Previous day high/low lines for identifying key breakout and breakdown levels
- Pre-market high/low tracking to identify potential intraday support/resistance zones
- All levels displayed with distinct line styles for easy identification
4. **Dynamic Trend Analysis**
- Color-coded bands between EMAs display trend strength and direction:
- Green bands indicate uptrend conditions (9 EMA > 21 EMA > 48 EMA)
- Red bands indicate downtrend conditions (9 EMA < 21 EMA < 48 EMA)
- Yellow bands indicate neutral/confused market conditions
- Visual representation makes trend changes immediately apparent
5. **Comprehensive Customization Options**
- Fully customizable colors for all indicators and bands
- Adjustable transparency settings for visual clarity
- Optional price labels with customizable placement and appearance
- Ability to show/hide specific components based on trading preferences
#### Trading Applications
This indicator is particularly valuable for:
1. **Day Trading & Scalping**: The 2-minute and 5-minute EMAs with color bands provide clear short-term trend direction and potential reversal signals.
2. **Swing Trading**: Daily EMAs and MAs offer perspective on the larger trend, helping to align short-term trades with the broader market direction.
3. **Gap Trading**: Previous day and pre-market levels help identify potential gap fill scenarios and breakout/breakdown opportunities.
4. **VWAP Trading Strategies**: Multiple timeframe VWAPs allow for identifying institutional participation levels and potential reversal zones.
5. **EMA Cross Systems**: The various EMAs can be used to identify golden crosses and death crosses across multiple timeframes.
#### How the Components Work Together
The power of NasyI comes from the integration of these different technical elements:
1. The short-timeframe EMAs (2m, 5m) provide immediate trend information, while the daily EMAs/MAs provide context about the larger market structure.
2. The color bands between EMAs offer instant visual confirmation of trend alignment or divergence across timeframes.
3. Previous day and pre-market levels add horizontal support/resistance zones to complement the dynamic moving averages.
4. Multiple timeframe VWAPs provide additional confirmation of institutional activity levels and potential reversal points.
By combining these elements, traders can develop a comprehensive market view that integrates price action, trend direction, and key support/resistance levels all in one indicator.
#### Usage Instructions
1. Apply the NasyI indicator to your chart (works best on intraday timeframes from 1-minute to 30-minute).
2. Observe the relationship between price and the various EMAs:
- Price above the 2m/5m EMAs with green bands indicates bullish short-term conditions
- Price below the 2m/5m EMAs with red bands indicates bearish short-term conditions
3. Use the daily EMAs/MAs and VWAPs as targets for potential price movements and reversal zones.
4. Previous day and pre-market high/low lines provide key levels to watch for breakouts or breakdowns.
5. Customize the appearance according to your preferences using the extensive settings options.
This indicator represents a unique approach to technical analysis by combining multiple timeframe perspectives into a single, visually intuitive display that helps traders make more informed decisions based on a comprehensive view of market conditions.
### 中文描述
**NasyI** 是一个全面的技术分析指标，旨在为交易者提供跨多个时间周期的完整市场动态视图。该指标结合了指数移动平均线（EMA）、简单移动平均线（MA）、成交量加权平均价格（VWAP）和关键支撑/阻力水平的力量，帮助交易者识别趋势方向、潜在反转点和最佳进出场机会。
#### 主要特点
1. **多时间周期分析系统**
- 2分钟EMAs（13，48）用于超短期趋势识别
- 5分钟EMAs（9，13，21，48，200）用于短期趋势确认
- 日线EMAs（5，13，21，48，100，200）和MAs（20，50，100，200）用于更长期的视角
- 关键EMAs之间的彩色带状区域直观显示趋势强度和方向
2. **高级VWAP整合**
- 日内VWAP作为日内支撑/阻力
- 周内VWAP作为中期价格参考
- 月内VWAP作为长期机构价格水平
- 所有VWAP在各自的时间周期边界正确重置
3. **关键价格水平识别**
- 前一交易日高点/低点线用于识别关键突破和跌破水平
- 盘前高点/低点跟踪用于识别潜在的日内支撑/阻力区域
- 所有水平以不同的线条样式显示，便于识别
4. **动态趋势分析**
- EMAs之间的彩色带状区域显示趋势强度和方向：
- 绿色带状区域表示上升趋势（9 EMA > 21 EMA > 48 EMA）
- 红色带状区域表示下降趋势（9 EMA < 21 EMA < 48 EMA）
- 黄色带状区域表示中性/混乱市场条件
- 视觉表示使趋势变化立即显现
5. **全面的自定义选项**
- 所有指标和带状区域的颜色完全可定制
- 可调节的透明度设置，提高视觉清晰度
- 可选的价格标签，带有可定制的位置和外观
- 能够根据交易偏好显示/隐藏特定组件
#### 交易应用
此指标对以下方面特别有价值：
1. **日内交易和短线交易**：2分钟和5分钟EMAs与色带提供清晰的短期趋势方向和潜在反转信号。
2. **摇摆交易**：日线EMAs和MAs提供对更大趋势的视角，帮助将短期交易与更广泛的市场方向对齐。
3. **缺口交易**：前一日和盘前水平帮助识别潜在的缺口填充情况和突破/跌破机会。
4. **VWAP交易策略**：多时间周期VWAP允许识别机构参与水平和潜在反转区域。
5. **EMA交叉系统**：各种EMAs可用于识别跨多个时间周期的黄金交叉和死亡交叉。
#### 组件如何协同工作
NasyI的强大之处在于这些不同技术元素的集成：
1. 短时间周期EMAs（2m，5m）提供即时趋势信息，而日线EMAs/MAs提供关于更大市场结构的背景。
2. EMAs之间的色带提供趋势对齐或跨时间周期分歧的即时视觉确认。
3. 前一日和盘前水平添加水平支撑/阻力区域，补充动态移动平均线。
4. 多时间周期VWAP提供机构活动水平和潜在反转点的额外确认。
通过结合这些元素，交易者可以发展出全面的市场视图，整合价格行动、趋势方向和关键支撑/阻力水平于一个指标中。
#### 使用说明
1. 将NasyI指标应用到您的图表上（最适合1分钟至30分钟的日内时间周期）。
2. 观察价格与各种EMAs之间的关系：
- 价格位于2m/5m EMAs之上，带有绿色带状区域，表示看涨的短期条件
- 价格位于2m/5m EMAs之下，带有红色带状区域，表示看跌的短期条件
3. 使用日线EMAs/MAs和VWAPs作为潜在价格移动和反转区域的目标。
4. 前一日和盘前高点/低点线提供需要关注的突破或跌破的关键水平。
5. 使用广泛的设置选项根据您的偏好自定义外观。
这个指标代表了一种独特的技术分析方法，将多个时间周期的视角结合到一个单一的、视觉直观的显示中，帮助交易者基于对市场条件的全面视图做出更明智的决策。
Uptrick X PineIndicators: Z-Score Flow StrategyThis strategy is based on the Z-Score Flow Indicator developed by Uptrick. Full credit for the original concept and logic goes to Uptrick.
The Z-Score Flow Strategy combines statistical mean-reversion logic with trend filtering, RSI confirmation, and multi-mode trade execution, offering a flexible and structured approach to trading both reversals and trend continuations.
Core Concepts Behind Z-Score Flow
1. Z-Score Mean Reversion Logic
The Z-score measures how far current price deviates from its statistical mean, in standard deviations.
A high positive Z-score (e.g. > 2) suggests price is overbought and may revert downward.
A low negative Z-score (e.g. < -2) suggests price is oversold and may revert upward.
The strategy uses Z-score thresholds to trigger signals when price deviates far enough from its mean.
2. Trend Filtering with EMA
To prevent counter-trend entries, the strategy includes a trend filter based on a 50-period EMA:
Only allows long entries if price is below EMA (mean-reversion in downtrends).
Only allows short entries if price is above EMA (mean-reversion in uptrends).
3. RSI Confirmation and Lockout System
An RSI smoothing mechanism helps confirm signals and avoid whipsaws:
RSI must be below 30 and rising to allow buys.
RSI must be above 70 and falling to allow sells.
Once a signal occurs, it is "locked out" until RSI re-enters the neutral zone (30–70).
This avoids multiple signals in overextended zones and reduces overtrading.
Entry Signal Logic
A buy or sell is triggered when:
Z-score crosses below (buy) or above (sell) the threshold.
RSI smoothed condition is met (oversold and rising / overbought and falling).
The trend condition (EMA filter) aligns.
A cooldown period has passed since the last opposite trade.
This layered approach helps ensure signal quality and timing precision.
Trade Modes
The strategy includes three distinct trade modes to adapt to various market behaviors:
1. Standard Mode
Trades are opened using the Z-score + RSI + trend filter logic.
Each signal must pass all layered conditions.
2. Zero Cross Mode
Trades are based on the Z-score crossing zero.
This mode is useful in trend continuation setups, rather than mean reversion.
3. Trend Reversal Mode
Trades occur when the mean slope direction changes, i.e., basis line changes color.
Helps capture early trend shifts with less lag.
Each mode can be customized for long-only, short-only, or long & short execution.
Visual Components
1. Z-Score Mean Line
The basis (mean) line is colored based on slope direction.
Green = bullish slope, Purple = bearish slope, Gray = flat.
A wide shadow band underneath reflects current trend momentum.
2. Gradient Fill to Price
A gradient zone between price and the mean reflects:
Price above mean = bearish zone with purple overlay.
Price below mean = bullish zone with teal overlay.
This visual aid quickly reveals market positioning relative to equilibrium.
3. Signal Markers
"𝓤𝓹" labels appear for buy signals.
"𝓓𝓸𝔀𝓷" labels appear for sell signals.
These are colored and positioned according to trend context.
Customization Options
Z-Score Period & Thresholds: Define sensitivity to price deviations.
EMA Trend Filter Length: Filter entries with long-term bias.
RSI & Smoothing Periods: Fine-tune RSI confirmation conditions.
Cooldown Period: Prevent signal spam and enforce timing gaps.
Slope Index: Adjust how far back to compare mean slope.
Visual Settings: Toggle mean lines, gradients, and more.
Use Cases & Strategy Strengths
1. Mean-Reversion Trading
Ideal for catching pullbacks in trending markets or fading overextended price moves.
2. Trend Continuation or Reversal
With multiple trade modes, traders can choose between fading price extremes or trading slope momentum.
3. Signal Clarity and Risk Control
The combination of Z-score, RSI, EMA trend, and cooldown logic provides high-confidence signals with built-in filters.
Conclusion
The Z-Score Flow Strategy by Uptrick X PineIndicators is a versatile and structured trading system that:
Fuses statistical deviation (Z-score) with technical filters.
Provides both mean-reversion and trend-based entry logic.
Uses visual overlays and signal labels for clarity.
Prevents noise-driven trades via cooldown and lockout systems.
This strategy is well-suited for traders seeking a data-driven, multi-condition entry framework that can adapt to various market types.
Full credit for the original concept and indicator goes to Uptrick.
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
Candle Height & Trend Probability DashboardDescription and Guide
Description:
This Pine Script for TradingView displays a dashboard that calculates the probability of price increases or decreases based on past price movements. It analyzes the last 30 candles (by default) and shows the probabilities for different timeframes (from 1 minute to 1 week). Additionally, it checks volatility using the ATR indicator.
Script Features:
Calculates probabilities of an upward (Up %) or downward (Down %) price move based on past candles.
Displays a dashboard showing probabilities for multiple timeframes.
Color-coded probability display:
Green if the upward probability exceeds a set threshold.
Red if the downward probability exceeds the threshold.
Yellow if neither threshold is exceeded.
Considers volatility using the ATR indicator.
Triggers alerts when probabilities exceed specific values.
How to Use:
Insert the script into TradingView: Copy and paste the script into the Pine Script editor.
Adjust parameters:
lookback: Number of past candles used for calculation (default: 30).
alertThresholdUp & alertThresholdDown: Thresholds for probabilities (default: 51%).
volatilityLength & volatilityThreshold: ATR volatility settings.
dashboardPosition: Choose where the dashboard appears on the chart.
Enable visualization: The dashboard will be displayed over the chart.
Set alerts: The script triggers notifications when probabilities exceed set thresholds.
Ichimoku Cloud Auto TF🧠 Timeframe Breakdown for Ichimoku Cloud Auto TF
Each timeframe in this indicator is carefully calibrated to reflect meaningful Ichimoku behavior relative to its scale. Here's how each one is structured and what it's best used for:
⏱️ 1 Minute (1m)
Tenkan / Kijun / Span B: 5 / 15 / 45
Use: Scalping fast price action.
Logic: Quick reaction to short-term momentum. Best for highly active traders or bots.
⏱️ 2 Minutes (2m)
Tenkan / Kijun / Span B: 6 / 18 / 54
Use: Slightly smoother than 1m, still ideal for scalping with a little more stability.
⏱️ 5 Minutes (5m)
Tenkan / Kijun / Span B: 8 / 24 / 72
Use: Intraday setups, quick trend capture.
Logic: Balanced between reactivity and noise reduction.
⏱️ 15 Minutes (15m)
Tenkan / Kijun / Span B: 9 / 27 / 81
Use: Short-term swing and intraday entries with higher reliability.
⏱️ 30 Minutes (30m)
Tenkan / Kijun / Span B: 10 / 30 / 90
Use: Intra-swing entries or confirmation of 5m/15m signals.
🕐 1 Hour (1H)
Tenkan / Kijun / Span B: 12 / 36 / 108
Use: Ideal for swing trading setups.
Logic: Anchored to Daily reference (1H × 24 ≈ 1D).
🕐 2 Hours (2H)
Tenkan / Kijun / Span B: 14 / 42 / 126
Use: High-precision swing setups with better context.
🕒 3 Hours (3H)
Tenkan / Kijun / Span B: 15 / 45 / 135
Use: Great compromise between short and mid-term vision.
🕓 4 Hours (4H)
Tenkan / Kijun / Span B: 18 / 52 / 156
Use: Position traders & intraday swing confirmation.
Logic: Designed to echo the structure of 1D Ichimoku but on smaller scale.
📅 1 Day (1D)
Tenkan / Kijun / Span B: 9 / 26 / 52
Use: Classic Ichimoku settings.
Logic: Standard used globally for technical analysis. Suitable for swing and position trading.
📆 1 Week (1W)
Tenkan / Kijun / Span B: 12 / 24 / 120
Use: Long-term position trading & institutional swing confirmation.
Logic: Expanded ratios for broader perspective and noise filtering.
🗓️ 1 Month (1M)
Tenkan / Kijun / Span B: 6 / 12 / 24
Use: Macro-level trend visualization and investment planning.
Logic: Condensed but stable structure to handle longer data cycles.
📌 Summary
This indicator adapts Ichimoku settings dynamically to your chart's timeframe, maintaining logical ratios between Tenkan, Kijun, and Span B. This ensures each timeframe remains responsive yet meaningful for its respective market context.
RSI Pro+ (Bear market, financial crisis and so on EditionIn markets defined by volatility, fear, and uncertainty – the battlegrounds of bear markets and financial crises – you need tools forged in resilience. Introducing RSI Pro+, a strategy built upon a legendary indicator born in 1978, yet engineered with modern visual clarity to remain devastatingly effective even in the chaotic financial landscapes of 3078.
This isn't about complex algorithms predicting the unpredictable. It's about harnessing the raw, time-tested power of the Relative Strength Index (RSI) to identify potential exhaustion points and capitalize on oversold conditions. RSI Pro+ cuts through the noise, providing clear, actionable signals when markets might be poised for a relief bounce or reversal.
Core Technology (The 1978 Engine):
RSI Crossover Entry: The strategy initiates a LONG position when the RSI (default period 11) crosses above a user-defined low threshold (default 30). This classic technique aims to enter when selling pressure may be waning, offering potential entry points during sharp downturns or periods of consolidation after a fall.
Modern Enhancements (The 3078 Cockpit):
RSI Pro+ isn't just about the signal; it's about providing a professional-grade visual experience directly on your chart:
Entry Bar Highlight: A subtle background flash on the chart signals the exact bar where the RSI crossover condition is met, alerting you to potential entry opportunities.
Trade Bar Coloring: Once a trade is active, the price bars are subtly colored, giving you immediate visual confirmation that the strategy is live in the market.
Entry Price Line: A clear, persistent line marks your exact average entry price for the duration of the trade, serving as a crucial visual anchor.
Take Profit Line: Your calculated Take Profit target is plotted as a distinct line, keeping your objective clearly in sight.
Custom Entry Marker: A precise shape (▲) appears below the bar where the trade entry was actually executed, pinpointing the start of the position.
On-Chart Info Table (HUD): A clean, customizable Heads-Up Display appears when a trade is active, showing vital information at a glance:
Entry Price: Your position's average cost basis.
TP Target: The calculated price level for your Take Profit exit.
Current PnL%: Real-time Profit/Loss percentage for the open trade.
Full Customization: Nearly every aspect is configurable via the settings menu:
RSI Period & Crossover Level
Take Profit Percentage
Toggle ALL visual enhancements on/off individually
Position the Info Table wherever you prefer on the chart.
How to Use RSI Pro+:
Add to Chart: Apply the "RSI Pro+ (Bear market...)" strategy to your TradingView chart. Ensure any previous versions are removed.
Access Settings: Click the cogwheel icon (⚙️) next to the strategy name on your chart.
Configure Inputs (Crucial Step):
RSI Crossover Level: This is key. The default (30) targets standard oversold conditions. In severe downturns, you might experiment with lower levels (e.g., 25, 20) or higher ones (e.g., 40) depending on the asset and timeframe. Observe where RSI(11) typically bottoms out on your chart.
Take Profit Percentage (%): Define your desired profit target per trade (e.g., enter 0.5 for 0.5%, 1.0 for 1%). The default is a very small 0.11%.
RSI Period: While default is 11, you can adjust this (e.g., the standard 14).
Visual Enhancements: Enable or disable the visual features (background highlights, bar coloring, lines, markers, table) according to your preference using the checkboxes. Adjust table position.
Observe & Backtest: Watch how the strategy behaves on your chosen asset and timeframe. Use TradingView's Strategy Tester to analyze historical performance based on your settings. No strategy works perfectly everywhere; testing is essential.
Important Considerations:
Risk Management: This specific script version focuses on a Take Profit exit. It does not include an explicit Stop Loss. You MUST manage risk through appropriate position sizing, potentially adding a Stop Loss manually, or by modifying the script.
Oversold ≠ Reversal: An RSI crossover is an indicator of potential exhaustion, not a guarantee of a price reversal.
Fixed TP: A fixed percentage TP ensures small wins but may exit before larger potential moves.
Backtesting Limitations: Past performance does not guarantee future results.
RSI Pro+ strips away complexity to focus on a robust, time-honored principle, enhanced with modern visuals for the discerning trader navigating today's (and tomorrow's) challenging markets
Long Term Profitable Swing | AbbasA Story of a Profitable Swing Trading Strategy
Imagine you're sailing across the ocean, looking for the perfect wave to ride. Swing trading is quite similar—you're navigating the stock market, searching for the ideal moments to enter and exit trades. This strategy, created by Abbas, helps you find those waves and ride them effectively to profitable outcomes.
🌊 Finding the Perfect Wave (Entry)
Our journey begins with two simple signs that tell us a great trading opportunity is forming:
- Moving Averages: We use two lines that follow price trends—the faster one (EMA 16) reacts quickly to recent price moves, and the slower one (EMA 30) gives us a longer-term perspective. When the faster line crosses above the slower line, it's like a clear signal saying, "Hey! The wave is rising, and prices might move higher!"
- RSI Momentum: Next, we check a tool called the RSI, which measures momentum (how strongly prices are moving). If the RSI number is above 50, it means there's enough strength behind this rising wave to carry us forward.
When both signals appear together, that's our green light. It's time to jump on our surfboard and start riding this promising wave.
⚓ Safely Riding the Wave (Risk Management)
While we're riding this wave, we want to ensure we're safe from sudden surprises. To do this, we use something called the Average True Range (ATR), which measures how volatile (or bumpy) the price movements are:
- Stop-Loss: To avoid falling too hard, we set a safety line (stop-loss) 8 times the ATR below our entry price. This helps ensure we exit if the wave suddenly turns against us, protecting us from heavy losses.
- Take Profit: We also set a goal to exit the trade at 11 times the ATR above our entry. This way, we capture significant profits when the wave reaches a nice high point.
🌟 Multiple Rides, Bigger Adventures
This strategy allows us to take multiple positions simultaneously—like riding several waves at once, up to 5. Each trade we make uses only 10% of our trading capital, keeping risks manageable and giving us multiple opportunities to win big.
🗺️ Easy to Follow Settings
Here are the basic settings we use:
- Fast EMA**: 16
- Slow EMA**: 30
- RSI Length**: 9
- RSI Threshold**: 50
- ATR Length**: 21
- ATR Stop-Loss Multiplier**: 8
- ATR Take-Profit Multiplier**: 11
These settings are flexible—you can adjust them to better suit different markets or your personal trading style.
🎉 Riding the Waves of Success
This simple yet powerful swing trading approach helps you confidently enter trades, clearly know when to exit, and effectively manage your risk. It’s a reliable way to ride market waves, capture profits, and minimize losses.
Happy trading, and may you find many profitable waves to ride! 🌊✨
Please test, and take into account that it depends on taking multiple longs within the swing, and you only get to invest 25/30% of your equity.
Reversal + Confirm ZonesThis script is written in Pine Script (version 5) for TradingView and creates an indicator called **"Reversal + Confirm Zones"**. It overlays visual zones on a price chart to identify potential reversal points and confirmation signals for trading. The indicator combines **Bollinger Bands** and **RSI** to detect overbought/oversold conditions (reversal zones) and uses **EMA crosses** and **MACD zero-line crosses** to confirm bullish or bearish trends. Below is a detailed explanation:
---
### **1. Purpose**
- The script highlights:
- **Reversal Zones**: Areas where the price might reverse due to being overbought (green) or oversold (red).
- **Confirmation Zones**: Areas where a trend reversal is confirmed using EMA and MACD signals (green for bullish, red for bearish).
- It provides visual backgrounds and alerts to assist traders in spotting potential trade setups.
---
### **2. Components**
The script is divided into two main parts: **Reversal Logic** and **Confirmation Logic**.
---
### **3. Reversal Logic (Red & Green Zones)**
#### **Bollinger Bands**
- **Parameters**:
- Length: 20 periods.
- Source: Closing price (`close`).
- Multiplier: 2.0 (standard deviations).
- **Calculation**:
- `basis`: 20-period Simple Moving Average (SMA).
- `dev`: 2 times the standard deviation of the price over 20 periods.
- `upper`: `basis + dev` (upper band).
- `lower`: `basis - dev` (lower band).
- **Purpose**: Identifies when the price moves outside the normal range (beyond 2 standard deviations).
#### **Relative Strength Index (RSI)**
- **Parameters**:
- Length: 14 periods.
- Low Threshold: 30 (oversold).
- High Threshold: 70 (overbought).
- **Calculation**: `rsiValue = ta.rsi(close, rsiLength)`.
- **Purpose**: Measures momentum to confirm overbought or oversold conditions.
#### **Zone Conditions**
- **Red Zone (Oversold)**:
- Condition: `close < lower` (price below lower Bollinger Band) AND `rsiValue < rsiLowThreshold` (RSI < 30).
- Visual: Light red background (`color.new(color.red, 80)`).
- Alert: "Deep Oversold Signal triggered!".
- **Green Zone (Overbought)**:
- Condition: `close > upper` (price above upper Bollinger Band) AND `rsiValue > rsiHighThreshold` (RSI > 70).
- Visual: Light green background (`color.new(color.green, 80)`).
- Alert: "Deep Overbought Signal triggered!".
#### **Interpretation**
- Red Zone: Suggests the price is oversold and may reverse upward.
- Green Zone: Suggests the price is overbought and may reverse downward.
---
### **4. Confirmation Logic (EMA and MACD Crosses)**
#### **Exponential Moving Averages (EMAs)**
- **Parameters**:
- Short EMA Length: 9 periods (user adjustable).
- Long EMA Length: 21 periods (user adjustable).
- **Calculation**:
- `emaShort = ta.ema(close, emaShortLength)`.
- `emaLong = ta.ema(close, emaLongLength)`.
- **Conditions**:
- **Bullish EMA Cross**: `emaCrossBullish = ta.crossover(emaShort, emaLong)` (9 EMA crosses above 21 EMA).
- **Bearish EMA Cross**: `emaCrossBearish = ta.crossunder(emaShort, emaLong)` (9 EMA crosses below 21 EMA).
#### **MACD**
- **Parameters**:
- Fast Length: 12 periods (user adjustable).
- Slow Length: 26 periods (user adjustable).
- Signal Smoothing: 9 periods (user adjustable).
- **Calculation**:
- ` = ta.macd(close, macdFastLength, macdSlowLength, macdSignalSmoothing)`.
- Only the MACD line and signal line are used; the histogram is ignored (`_`).
- **Conditions**:
- **Bullish MACD Cross**: `macdCrossBullish = ta.crossover(macdLine, 0)` (MACD crosses above zero).
- **Bearish MACD Cross**: `macdCrossBearish = ta.crossunder(macdLine, 0)` (MACD crosses below zero).
#### **Combined Confirmation Conditions**
- **Bullish Confirmation**:
- Condition: `bullishConfirmation = emaCrossBullish and macdCrossBullish`.
- Visual: Very light green background (`color.new(color.green, 90)`).
- Meaning: A bullish trend is confirmed when the 9 EMA crosses above the 21 EMA AND the MACD crosses above zero.
- **Bearish Confirmation**:
- Condition: `bearishConfirmation = emaCrossBearish and macdCrossBearish`.
- Visual: Very light red background (`color.new(color.red, 90)`).
- Meaning: A bearish trend is confirmed when the 9 EMA crosses below the 21 EMA AND the MACD crosses below zero.
---
### **5. Visual Outputs**
- **Reversal Zones**:
- Red background for oversold conditions.
- Green background for overbought conditions.
- **Confirmation Zones**:
- Light green background for bullish confirmation.
- Light red background for bearish confirmation.
- Note: The script does not plot the Bollinger Bands, EMAs, or MACD lines—only the background zones are visualized.
---
### **6. Alerts**
- **Deep Oversold Alert**: Triggers when the red zone condition is met.
- **Deep Overbought Alert**: Triggers when the green zone condition is met.
- No alerts are set for the confirmation zones (EMA/MACD crosses).
---
### **7. How It Works**
1. **Reversal Detection**:
- The script uses Bollinger Bands and RSI to flag extreme price levels (red for oversold, green for overbought).
- These zones suggest potential reversals but are not confirmed yet.
2. **Trend Confirmation**:
- EMA crosses (9/21) and MACD zero-line crosses provide confirmation of a trend direction.
- Bullish confirmation (green) occurs when both indicators align upward.
- Bearish confirmation (red) occurs when both indicators align downward.
3. **Trading Strategy**:
- Look for a red zone (oversold) followed by a bullish confirmation for a potential long entry.
- Look for a green zone (overbought) followed by a bearish confirmation for a potential short entry.
---
### **8. How to Use**
1. Add the script to TradingView.
2. Adjust inputs (EMA lengths, MACD settings) if desired.
3. Monitor the chart:
- Red zones indicate oversold conditions—watch for a potential upward reversal.
- Green zones indicate overbought conditions—watch for a potential downward reversal.
- Light green/red backgrounds confirm the trend direction after a reversal zone.
4. Set up alerts for oversold/overbought conditions to catch reversal signals early.
---
### **9. Key Features**
- **Dual Purpose**: Combines reversal detection (Bollinger Bands + RSI) with trend confirmation (EMA + MACD).
- **Visual Simplicity**: Uses background colors instead of plotting lines, keeping the chart clean.
- **Customizable**: Allows users to tweak EMA and MACD periods.
- **Alerts**: Notifies users of extreme conditions for timely action.
---
### **10. Limitations**
- No plotted indicators (e.g., Bollinger Bands, EMAs, MACD) for visual reference—relies entirely on background shading.
- Confirmation signals (EMA/MACD) may lag behind reversal zones, potentially missing fast reversals.
- No alerts for confirmation zones, limiting real-time notification of trend confirmation.
This script is ideal for traders who want a straightforward way to spot potential reversals and confirm them with trend-following indicators, all overlaid on the price chart.
Opening Range BreakoutThis is an Opening Range Breakout script. It will plot the opening range high and low (green and red lines, respectively) as determined by the user input (default is a 15 min window from market open, 9:30 - 9:45 am). The time period for the breakout is also configured by a user input (default is from 9:45 am - 2:30 pm).
Alerts are sent for breakouts either above (bullish) or below (bearish) the opening range high and low. An EMA is also used for trend confirmation before sending alerts for breakouts (to avoid false signals).
A bullish breakout is determined by all of the following being true:
- The current price being above the opening range high (green line)
- The EMA trending up (ie the current value of the EMA > prior EMA value)
- The current price is > the EMA
- The EMA is > the opening range high
A bearish breakout is determined by all of the following being true:
- The current price being below the opening range low (red line)
- The EMA trending down (ie the current value of the EMA < prior EMA value)
- The current price is < the EMA
- the EMA is < the opening range low
Enjoy this simple indicator!
Composite Reversal IndicatorOverview
The "Composite Reversal Indicator" aggregates five technical signals to produce a composite score that ranges from -5 (strongly bearish) to +5 (strongly bullish). These signals come from:
Relative Strength Index (RSI)
Moving Average Convergence Divergence (MACD)
Accumulation/Distribution (A/D)
Volume relative to its moving average
Price proximity to support and resistance levels
Each signal contributes a value of +1 (bullish), -1 (bearish), or 0 (neutral) to the total score. The raw score is plotted as a histogram, and a smoothed version is plotted as a colored line to highlight trends.
Step-by-Step Explanation
1. Customizable Inputs
The indicator starts with user-defined inputs that allow traders to tweak its settings. These inputs include:
RSI: Length (e.g., 14), oversold level (e.g., 30), and overbought level (e.g., 70).
MACD: Fast length (e.g., 12), slow length (e.g., 26), and signal length (e.g., 9).
Volume: Moving average length (e.g., 20) and multipliers for high (e.g., 1.5) and low (e.g., 0.5) volume thresholds.
Price Levels: Period for support and resistance (e.g., 50) and proximity percentage (e.g., 2%).
Score Smoothing: Length for smoothing the score (e.g., 5).
These inputs make the indicator adaptable to different trading styles, assets, or timeframes.
2. Indicator Calculations
The script calculates five key indicators using the input parameters:
RSI: Measures momentum and identifies overbought or oversold conditions.
Formula: rsi = ta.rsi(close, rsi_length)
Example: With a length of 14, it analyzes the past 14 bars of closing prices.
MACD: Tracks trend and momentum using two exponential moving averages (EMAs).
Formula: = ta.macd(close, macd_fast, macd_slow, macd_signal)
Components: MACD line (fast EMA - slow EMA), signal line (EMA of MACD line).
Accumulation/Distribution (A/D): A volume-based indicator showing buying or selling pressure.
Formula: ad = ta.accdist
Reflects cumulative flow based on price and volume.
Volume Moving Average: A simple moving average (SMA) of trading volume.
Formula: vol_ma = ta.sma(volume, vol_ma_length)
Example: A 20-bar SMA smooths volume data.
Support and Resistance Levels: Key price levels based on historical lows and highs.
Formulas:
support = ta.lowest(low, price_level_period)
resistance = ta.highest(high, price_level_period)
Example: Over 50 bars, it finds the lowest low and highest high.
These calculations provide the raw data for generating signals.
3. Signal Generation
Each indicator produces a signal based on specific conditions:
RSI Signal:
+1: RSI < oversold level (e.g., < 30) → potential bullish reversal.
-1: RSI > overbought level (e.g., > 70) → potential bearish reversal.
0: Otherwise.
Logic: Extreme RSI values suggest price may reverse.
MACD Signal:
+1: MACD line > signal line → bullish momentum.
-1: MACD line < signal line → bearish momentum.
0: Equal.
Logic: Crossovers indicate trend shifts.
A/D Signal:
+1: Current A/D > previous A/D → accumulation (bullish).
-1: Current A/D < previous A/D → distribution (bearish).
0: Unchanged.
Logic: Rising A/D shows buying pressure.
Volume Signal:
+1: Volume > high threshold (e.g., 1.5 × volume MA) → strong activity (bullish).
-1: Volume < low threshold (e.g., 0.5 × volume MA) → weak activity (bearish).
0: Otherwise.
Logic: Volume spikes often confirm reversals.
Price Signal:
+1: Close near support (within proximity %, e.g., 2%) → potential bounce.
-1: Close near resistance (within proximity %) → potential rejection.
0: Otherwise.
Logic: Price near key levels signals reversal zones.
4. Composite Score
The raw composite score is the sum of the five signals:
Formula: score = rsi_signal + macd_signal + ad_signal + vol_signal + price_signal
Range: -5 (all signals bearish) to +5 (all signals bullish).
Purpose: Combines multiple perspectives into one number.
5. Smoothed Score
A smoothed version of the score reduces noise:
Formula: score_ma = ta.sma(score, score_ma_length)
Example: With a length of 5, it averages the score over 5 bars.
Purpose: Highlights the trend rather than short-term fluctuations.
6. Visualization
The indicator plots two elements:
Raw Score: A gray histogram showing the composite score per bar.
Style: plot.style_histogram
Color: Gray.
Smoothed Score: A line that changes color:
Green: Score > 0 (bullish).
Red: Score < 0 (bearish).
Gray: Score = 0 (neutral).
Style: plot.style_line, thicker line (e.g., linewidth=2).
These visuals make it easy to spot potential reversals.
How It Works Together
The indicator combines signals from:
RSI: Momentum extremes.
MACD: Trend shifts.
A/D: Buying/selling pressure.
Volume: Confirmation of moves.
Price Levels: Key reversal zones.
By summing these into a composite score, it filters out noise and provides a unified signal. A high positive score (e.g., +3 to +5) suggests a bullish reversal, while a low negative score (e.g., -3 to -5) suggests a bearish reversal. The smoothed score helps traders focus on the trend.
Practical Use
Bullish Reversal: Smoothed score is green and rising → look for buying opportunities.
Bearish Reversal: Smoothed score is red and falling → consider selling or shorting.
Neutral: Score near 0 → wait for clearer signals.
Traders can adjust inputs to suit their strategy, making it versatile for stocks, forex, or crypto.
Cumulative Histogram TickThis script is designed to create a cumulative histogram based on tick data from a specific financial instrument. The histogram resets at the start of each trading session, which is defined by a fixed time.
Key Components:
Tick Data Retrieval:
The script fetches the closing tick values from the specified instrument using request.security("TICK.NY", timeframe.period, close). This line ensures that the script works with the tick data for each bar on the chart.
Session Start and End Detection:
Start Hour: The script checks if the current bar's time is 9:30 AM (hour == 9 and minute == 30). This is used to reset the cumulative value at the beginning of each trading session.
End Hour: It also checks if the current bar's time is 4:00 PM (hour == 16). However, this condition is used to prevent further accumulation after the session ends.
Cumulative Value Management:
Reset: When the start hour condition is met (startHour), the cumulative value (cumulative) is reset to zero. This ensures that each trading session starts with a clean slate.
Accumulation: For all bars that are not at the end hour (not endHour), the tick value is added to the cumulative total. This process continues until the end of the trading session.
Histogram Visualization:
The cumulative value is plotted as a histogram using plot.style_histogram. The color of the histogram changes based on whether the cumulative value is positive (green) or negative (red).
Usage
This script is useful for analyzing intraday market activity by visualizing the accumulation of tick data over a trading session. It helps traders identify trends or patterns within each session, which can be valuable for making informed trading decisions.
Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
Smart Liquidity Wave [The_lurker]"Smart Liquidity Wave" هو مؤشر تحليلي متطور يهدف لتحديد نقاط الدخول والخروج المثلى بناءً على تحليل السيولة، قوة الاتجاه، وإشارات السوق المفلترة. يتميز المؤشر بقدرته على تصنيف الأدوات المالية إلى أربع فئات سيولة (ضعيفة، متوسطة، عالية، عالية جدًا)، مع تطبيق شروط مخصصة لكل فئة تعتمد على تحليل الموجات السعرية، الفلاتر المتعددة، ومؤشر ADX.
فكرة المؤشر
الفكرة الأساسية هي الجمع بين قياس السيولة اليومية الثابتة وتحليل ديناميكي للسعر باستخدام فلاتر متقدمة لتوليد إشارات دقيقة. المؤشر يركز على تصفية الضوضاء في السوق من خلال طبقات متعددة من التحليل، مما يجعله أداة ذكية تتكيف مع الأدوات المالية المختلفة بناءً على مستوى سيولتها.
طريقة عمل المؤشر
1- قياس السيولة:
يتم حساب السيولة باستخدام متوسط حجم التداول على مدى 14 يومًا مضروبًا في سعر الإغلاق، ويتم ذلك دائمًا على الإطار الزمني اليومي لضمان ثبات القيمة بغض النظر عن الإطار الزمني المستخدم في الرسم البياني.
يتم تصنيف السيولة إلى:
ضعيفة: أقل من 5 ملايين (قابل للتعديل).
متوسطة: من 5 إلى 20 مليون.
عالية: من 20 إلى 50 مليون.
عالية جدًا: أكثر من 50 مليون.
هذا الثبات في القياس يضمن أن تصنيف السيولة لا يتغير مع تغير الإطار الزمني، مما يوفر أساسًا موثوقًا للإشارات.
2- تحليل الموجات السعرية:
يعتمد المؤشر على تحليل الموجات باستخدام متوسطات متحركة متعددة الأنواع (مثل SMA، EMA، WMA، HMA، وغيرها) يمكن للمستخدم اختيارها وتخصيص فتراتها ، يتم دمج هذا التحليل مع مؤشرات إضافية مثل RSI (مؤشر القوة النسبية) وMFI (مؤشر تدفق الأموال) بوزن محدد (40% للموجات، 30% لكل من RSI وMFI) للحصول على تقييم شامل للاتجاه.
3- الفلاتر وطريقة عملها:
المؤشر يستخدم نظام فلاتر متعدد الطبقات لتصفية الإشارات وتقليل الضوضاء، وهي من أبرز الجوانب المخفية التي تعزز دقته:
الفلتر الرئيسي (Main Filter):
يعمل على تنعيم التغيرات السعرية السريعة باستخدام معادلة رياضية تعتمد على تحليل الإشارات (Signal Processing).
يتم تطبيقه على السعر لاستخراج الاتجاهات الأساسية بعيدًا عن التقلبات العشوائية، مع فترة زمنية قابلة للتعديل (افتراضي: 30).
يستخدم تقنية مشابهة للفلاتر عالية التردد (High-Pass Filter) للتركيز على الحركات الكبيرة.
الفلتر الفرعي (Sub Filter):
يعمل كطبقة ثانية للتصفية، مع فترة أقصر (افتراضي: 12)، لضبط الإشارات بدقة أكبر.
يستخدم معادلات تعتمد على الترددات المنخفضة للتأكد من أن الإشارات الناتجة تعكس تغيرات حقيقية وليست مجرد ضوضاء.
إشارة الزناد (Signal Trigger):
يتم تطبيق متوسط متحرك على نتائج الفلتر الرئيسي لتوليد خط إشارة (Signal Line) يُقارن مع عتبات محددة للدخول والخروج.
يمكن تعديل فترة الزناد (افتراضي: 3 للدخول، 5 للخروج) لتسريع أو تبطيء الإشارات.
الفلتر المربع (Square Filter):
خاصية مخفية تُفعّل افتراضيًا تعزز دقة الفلاتر عن طريق تضييق نطاق التذبذبات المسموح بها، مما يقلل من الإشارات العشوائية في الأسواق المتقلبة.
4- تصفية الإشارات باستخدام ADX:
يتم استخدام مؤشر ADX كفلتر نهائي للتأكد من قوة الاتجاه قبل إصدار الإشارة:
ضعيفة ومتوسطة: دخول عندما يكون ADX فوق 40، خروج فوق 50.
عالية: دخول فوق 40، خروج فوق 55.
عالية جدًا: دخول فوق 35، خروج فوق 38.
هذه العتبات قابلة للتعديل، مما يسمح بتكييف المؤشر مع استراتيجيات مختلفة.
5- توليد الإشارات:
الدخول: يتم إصدار إشارة شراء عندما تنخفض خطوط الإشارة إلى ما دون عتبة محددة (مثل -9) مع تحقق شروط الفلاتر، السيولة، وADX.
الخروج: يتم إصدار إشارة بيع عندما ترتفع الخطوط فوق عتبة (مثل 109 أو 106 حسب الفئة) مع تحقق الشروط الأخرى.
تُعرض الإشارات بألوان مميزة (أزرق للدخول، برتقالي للضعيفة والمتوسطة، أحمر للعالية والعالية جدًا) وبثلاثة أحجام (صغير، متوسط، كبير).
6- عرض النتائج:
يظهر مستوى السيولة الحالي في جدول في أعلى يمين الرسم البياني، مما يتيح للمستخدم معرفة فئة الأصل بسهولة.
7- دعم التنبيهات:
تنبيهات فورية لكل فئة سيولة، مما يسهل التداول الآلي أو اليدوي.
%%%%% الجوانب المخفية في الكود %%%%%
معادلات الفلاتر المتقدمة: يستخدم المؤشر معادلات رياضية معقدة مستوحاة من معالجة الإشارات لتنعيم البيانات واستخراج الاتجاهات، مما يجعله أكثر دقة من المؤشرات التقليدية.
التكيف التلقائي: النظام يضبط نفسه داخليًا بناءً على التغيرات في السعر والحجم، مع عوامل تصحيح مخفية (مثل معامل التنعيم في الفلاتر) للحفاظ على الاستقرار.
التوزيع الموزون: الدمج بين الموجات، RSI، وMFI يتم بأوزان محددة (40%، 30%، 30%) لضمان توازن التحليل، وهي تفاصيل غير ظاهرة مباشرة للمستخدم لكنها تؤثر على النتائج.
الفلتر المربع: خيار مخفي يتم تفعيله افتراضيًا لتضييق نطاق الإشارات، مما يقلل من التشتت في الأسواق ذات التقلبات العالية.
مميزات المؤشر
1- فلاتر متعددة الطبقات: تضمن تصفية الضوضاء وإنتاج إشارات موثوقة فقط.
2- ثبات السيولة: قياس السيولة اليومي يجعل التصنيف متسقًا عبر الإطارات الزمنية.
3- تخصيص شامل: يمكن تعديل حدود السيولة، عتبات ADX، فترات الفلاتر، وأنواع المتوسطات المتحركة.
4- إشارات مرئية واضحة: تصميم بصري يسهل التفسير مع تنبيهات فورية.
5- تقليل الإشارات الخاطئة: الجمع بين الفلاتر وADX يعزز الدقة ويقلل من التشتت.
إخلاء المسؤولية
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#### **What is the Smart Liquidity Wave Indicator?**
"Smart Liquidity Wave" is an advanced analytical indicator designed to identify optimal entry and exit points based on liquidity analysis, trend strength, and filtered market signals. It stands out with its ability to categorize financial instruments into four liquidity levels (Weak, Medium, High, Very High), applying customized conditions for each category based on price wave analysis, multi-layered filters, and the ADX (Average Directional Index).
#### **Concept of the Indicator**
The core idea is to combine a stable daily liquidity measurement with dynamic price analysis using sophisticated filters to generate precise signals. The indicator focuses on eliminating market noise through multiple analytical layers, making it an intelligent tool that adapts to various financial instruments based on their liquidity levels.
#### **How the Indicator Works**
1. **Liquidity Measurement:**
- Liquidity is calculated using the 14-day average trading volume multiplied by the closing price, always based on the daily timeframe to ensure value consistency regardless of the chart’s timeframe.
- Liquidity is classified as:
- **Weak:** Less than 5 million (adjustable).
- **Medium:** 5 to 20 million.
- **High:** 20 to 50 million.
- **Very High:** Over 50 million.
- This consistency in measurement ensures that liquidity classification remains unchanged across different timeframes, providing a reliable foundation for signals.
2. **Price Wave Analysis:**
- The indicator relies on wave analysis using various types of moving averages (e.g., SMA, EMA, WMA, HMA, etc.), which users can select and customize in terms of periods.
- This analysis is integrated with additional indicators like RSI (Relative Strength Index) and MFI (Money Flow Index), weighted specifically (40% waves, 30% RSI, 30% MFI) to provide a comprehensive trend assessment.
3. **Filters and Their Functionality:**
- The indicator employs a multi-layered filtering system to refine signals and reduce noise, a key hidden feature that enhances its accuracy:
- **Main Filter:**
- Smooths rapid price fluctuations using a mathematical equation rooted in signal processing techniques.
- Applied to price data to extract core trends away from random volatility, with an adjustable period (default: 30).
- Utilizes a technique similar to high-pass filters to focus on significant movements.
- **Sub Filter:**
- Acts as a secondary filtering layer with a shorter period (default: 12) for finer signal tuning.
- Employs low-frequency-based equations to ensure resulting signals reflect genuine changes rather than mere noise.
- **Signal Trigger:**
- Applies a moving average to the main filter’s output to generate a signal line, compared against predefined entry and exit thresholds.
- Trigger period is adjustable (default: 3 for entry, 5 for exit) to speed up or slow down signals.
- **Square Filter:**
- A hidden feature activated by default, enhancing filter precision by narrowing the range of permissible oscillations, reducing random signals in volatile markets.
4. **Signal Filtering with ADX:**
- ADX is used as a final filter to confirm trend strength before issuing signals:
- **Weak and Medium:** Entry when ADX exceeds 40, exit above 50.
- **High:** Entry above 40, exit above 55.
- **Very High:** Entry above 35, exit above 38.
- These thresholds are adjustable, allowing the indicator to adapt to different trading strategies.
5. **Signal Generation:**
- **Entry:** A buy signal is triggered when signal lines drop below a specific threshold (e.g., -9) and conditions for filters, liquidity, and ADX are met.
- **Exit:** A sell signal is issued when signal lines rise above a threshold (e.g., 109 or 106, depending on the category) with all conditions satisfied.
- Signals are displayed in distinct colors (blue for entry, orange for Weak/Medium, red for High/Very High) and three sizes (small, medium, large).
6. **Result Display:**
- The current liquidity level is shown in a table at the top-right of the chart, enabling users to easily identify the asset’s category.
7. **Alert Support:**
- Instant alerts are provided for each liquidity category, facilitating both automated and manual trading.
#### **Hidden Aspects in the Code**
- **Advanced Filter Equations:** The indicator uses complex mathematical formulas inspired by signal processing to smooth data and extract trends, making it more precise than traditional indicators.
- **Automatic Adaptation:** The system internally adjusts based on price and volume changes, with hidden correction factors (e.g., smoothing coefficients in filters) to maintain stability.
- **Weighted Distribution:** The integration of waves, RSI, and MFI uses fixed weights (40%, 30%, 30%) for balanced analysis, a detail not directly visible but impactful on results.
- **Square Filter:** A hidden option, enabled by default, narrows signal range to minimize dispersion in high-volatility markets.
#### **Indicator Features**
1. **Multi-Layered Filters:** Ensures noise reduction and delivers only reliable signals.
2. **Liquidity Stability:** Daily liquidity measurement keeps classification consistent across timeframes.
3. **Comprehensive Customization:** Allows adjustments to liquidity thresholds, ADX levels, filter periods, and moving average types.
4. **Clear Visual Signals:** User-friendly design with easy-to-read visuals and instant alerts.
5. **Reduced False Signals:** Combining filters and ADX enhances accuracy and minimizes clutter.
#### **Disclaimer**
The information and publications are not intended to be, nor do they constitute, financial, investment, trading, or other types of advice or recommendations provided or endorsed by TradingView.
Adaptive Regression Channel [MissouriTim]The Adaptive Regression Channel (ARC) is a technical indicator designed to empower traders with a clear, adaptable, and precise view of market trends and price boundaries. By blending advanced statistical techniques with real-time market data, ARC delivers a comprehensive tool that dynamically adjusts to price action, volatility, volume, and momentum. Whether you’re navigating the fast-paced world of cryptocurrencies, the steady trends of stocks, or the intricate movements of FOREX pairs, ARC provides a robust framework for identifying opportunities and managing risk.
Core Components
1. Color-Coded Regression Line
ARC’s centerpiece is a linear regression line derived from a Weighted Moving Average (WMA) of closing prices. This line adapts its calculation period based on market volatility (via ATR) and is capped between a minimum of 20 bars and a maximum of 1.5 times the user-defined base length (default 100). Visually, it shifts colors to reflect trend direction: green for an upward slope (bullish) and red for a downward slope (bearish), offering an instant snapshot of market sentiment.
2. Dynamic Residual Channels
Surrounding the regression line are upper (red) and lower (green) channels, calculated using the standard deviation of residuals—the difference between actual closing prices and the regression line. This approach ensures the channels precisely track how closely prices follow the trend, rather than relying solely on overall price volatility. The channel width is dynamically adjusted by a multiplier that factors in:
Volatility: Measured through the Average True Range (ATR), widening channels during turbulent markets.
Trend Strength: Based on the regression slope, expanding channels in strong trends and contracting them in consolidation phases.
3. Volume-Weighted Moving Average (VWMA)
Plotted in orange, the VWMA overlays a volume-weighted price trend, emphasizing movements backed by significant trading activity. This complements the regression line, providing additional confirmation of trend validity and potential breakout strength.
4. Scaled RSI Overlay
ARC features a Relative Strength Index (RSI) overlay, plotted in purple and scaled to hover closely around the regression line. This compact display reflects momentum shifts within the trend’s context, keeping RSI visible on the price chart without excessive swings. User-defined overbought (default 70) and oversold (default 30) levels offer reference points for momentum analysis."
Technical Highlights
ARC leverages a volatility-adjusted lookback period, residual-based channel construction, and multi-indicator integration to achieve high accuracy. Its parameters—such as base length, channel width, ATR period, and RSI length—are fully customizable, allowing traders to tailor it to their specific needs.
Why Choose ARC?
ARC stands out for its adaptability and precision. The residual-based channels offer tighter, more relevant support and resistance levels compared to standard volatility measures, while the dynamic adjustments ensure it performs well in both trending and ranging markets. The inclusion of VWMA and scaled RSI adds depth, merging trend, volume, and momentum into a single, cohesive overlay. For traders seeking a versatile, all-in-one indicator, ARC delivers actionable insights with minimal noise.
Best Ways to Use the Adaptive Regression Channel (ARC)
The Adaptive Regression Channel (ARC) is a flexible tool that supports a variety of trading strategies, from trend-following to breakout detection. Below are the most effective ways to use ARC, along with practical tips for maximizing its potential. Adjustments to its settings may be necessary depending on the timeframe (e.g., intraday vs. daily) and the asset being traded (e.g., stocks, FOREX, cryptocurrencies), as each market exhibits unique volatility and behavior.
1. Trend Following
• How to Use: Rely on the regression line’s color to guide your trades. A green line (upward slope) signals a bullish trend—consider entering or holding long positions. A red line (downward slope) indicates a bearish trend—look to short or exit longs.
• Best Practice: Confirm the trend with the VWMA (orange line). Price above the VWMA in a green uptrend strengthens the bullish case; price below in a red downtrend reinforces bearish momentum.
• Adjustment: For short timeframes like 15-minute crypto charts, lower the Base Regression Length (e.g., to 50) for quicker trend detection. For weekly stock charts, increase it (e.g., to 200) to capture broader movements.
2. Channel-Based Trades
• How to Use: Use the upper channel (red) as resistance and the lower channel (green) as support. Buy when the price bounces off the lower channel in an uptrend, and sell or short when it rejects the upper channel in a downtrend.
• Best Practice: Check the scaled RSI (purple line) for momentum cues. A low RSI (e.g., near 30) at the lower channel suggests a stronger buy signal; a high RSI (e.g., near 70) at the upper channel supports a sell.
• Adjustment: In volatile crypto markets, widen the Base Channel Width Coefficient (e.g., to 2.5) to reduce false signals. For stable FOREX pairs (e.g., EUR/USD), a narrower width (e.g., 1.5) may work better.
3. Breakout Detection
• How to Use: Watch for price breaking above the upper channel (bullish breakout) or below the lower channel (bearish breakout). These moves often signal strong momentum shifts.
• Best Practice: Validate breakouts with VWMA position—price above VWMA for bullish breaks, below for bearish—and ensure the regression line’s slope aligns (green for up, red for down).
• Adjustment: For fast-moving assets like crypto on 1-hour charts, shorten ATR Length (e.g., to 7) to make channels more reactive. For stocks on daily charts, keep it at 14 or higher for reliability.
4. Momentum Analysis
• How to Use: The scaled RSI overlay shows momentum relative to the regression line. Rising RSI in a green uptrend confirms bullish strength; falling RSI in a red downtrend supports bearish pressure.
• Best Practice: Look for RSI divergences—e.g., price hitting new highs at the upper channel while RSI flattens or drops could signal an impending reversal.
• Adjustment: Reduce RSI Length (e.g., to 7) for intraday trading in FOREX or crypto to catch short-term momentum shifts. Increase it (e.g., to 21) for longer-term stock trades.
5. Range Trading
• How to Use: When the regression line’s slope is near zero (flat) and channels are tight, ARC indicates a ranging market. Buy near the lower channel and sell near the upper channel, targeting the regression line as the mean price.
• Best Practice: Ensure VWMA hovers close to the regression line to confirm the range-bound state.
• Adjustment: For low-volatility stocks on daily charts, use a moderate Base Regression Length (e.g., 100) and tight Base Channel Width (e.g., 1.5). For choppy crypto markets, test shorter settings.
Optimization Strategies
• Timeframe Customization: Adjust ARC’s parameters to match your trading horizon. Short timeframes (e.g., 1-minute to 1-hour) benefit from lower Base Regression Length (20–50) and ATR Length (7–10) for agility, while longer timeframes (e.g., daily, weekly) favor higher values (100–200 and 14–21) for stability.
• Asset-Specific Tuning:
○ Stocks: Use longer lengths (e.g., 100–200) and moderate widths (e.g., 1.8) for stable equities; tweak ATR Length based on sector volatility (shorter for tech, longer for utilities).
○ FOREX: Set Base Regression Length to 50–100 and Base Channel Width to 1.5–2.0 for smoother trends; adjust RSI Length (e.g., 10–14) based on pair volatility.
○ Crypto: Opt for shorter lengths (e.g., 20–50) and wider widths (e.g., 2.0–3.0) to handle rapid price swings; use a shorter ATR Length (e.g., 7) for quick adaptation.
• Backtesting: Test ARC on historical data for your asset and timeframe to optimize settings. Evaluate how often price respects channels and whether breakouts yield profitable trades.
• Enhancements: Pair ARC with volume surges, key support/resistance levels, or candlestick patterns (e.g., doji at channel edges) for higher-probability setups.
Practical Considerations
ARC’s adaptability makes it suitable for diverse markets, but its performance hinges on proper calibration. Cryptocurrencies, with their high volatility, may require shorter, wider settings to capture rapid moves, while stocks on longer timeframes benefit from broader, smoother configurations. FOREX pairs often fall in between, depending on their inherent volatility. Experiment with the adjustable parameters to align ARC with your trading style and market conditions, ensuring it delivers the precision and reliability you need.
FlexATRFlexATR: A Dynamic Multi-Timeframe Trading Strategy
Overview: FlexATR is a versatile trading strategy that dynamically adapts its key parameters based on the timeframe being used. It combines technical signals from exponential moving averages (EMAs) and the Relative Strength Index (RSI) with volatility-based risk management via the Average True Range (ATR). This approach helps filter out false signals while adjusting to varying market conditions — whether you’re trading on a daily chart, intraday charts (30m, 60m, or 5m), or even on higher timeframes like the 4-hour or weekly charts.
How It Works:
Multi-Timeframe Parameter Adaptation: FlexATR is designed to automatically adjust its indicator settings depending on the timeframe:
Daily and Weekly: On higher timeframes, the strategy uses longer periods for the fast and slow EMAs and standard periods for RSI and ATR to capture more meaningful trend confirmations while minimizing noise.
Intraday (e.g., 30m, 60m, 5m, 4h): The parameters are converted from “days” into the corresponding number of bars. For instance, on a 30-minute chart, a “day” might equal 48 bars. The preset values for a 30-minute chart have been slightly reduced (e.g., a fast EMA is set at 0.35 days instead of 0.4) to improve reactivity while maintaining robust filtering.
Signal Generation:
Entry Signals: The strategy enters long positions when the fast EMA crosses above the slow EMA and the RSI is above 50, and it enters short positions when the fast EMA crosses below the slow EMA with the RSI below 50. This dual confirmation helps ensure that signals are reliable.
Risk Management: The ATR is used to compute dynamic levels for stop loss and profit target:
Stop Loss: For a long position, the stop loss is placed at Price - (ATR × Stop Loss Multiplier). For a short position, it is at Price + (ATR × Stop Loss Multiplier).
Profit Target: The profit target is similarly set using the ATR multiplied by a designated profit multiplier.
Dynamic Trailing Stop: FlexATR further incorporates a dynamic trailing stop (if enabled) that adjusts according to the ATR. This trailing stop follows favorable price movements at a distance defined by a multiplier, locking in gains as the trend develops. The use of a trailing stop helps protect profits without requiring a fixed exit point.
Capital Allocation: Each trade is sized at 10% of the total equity. This percentage-based position sizing allows the strategy to scale with your account size. While the current setup assumes no leverage (a 1:1 exposure), the inherent design of the strategy means you can adjust the leverage externally if desired, with risk metrics scaling accordingly.
Visual Representation: For clarity and accessibility (especially for those with color vision deficiencies), FlexATR employs a color-blind friendly palette (the Okabe-Ito palette):
EMA Fast: Displayed in blue.
EMA Slow: Displayed in orange.
Stop Loss Levels: Rendered in vermilion.
Profit Target Levels: Shown in a distinct azzurro (light blue).
Benefits and Considerations:
Reliability: By requiring both EMA crossovers and an RSI confirmation, FlexATR filters out a significant amount of market noise, which reduces false signals at the expense of some delayed entries.
Adaptability: The automatic conversion of “day-based” parameters into bar counts for intraday charts means the strategy remains consistent across different timeframes.
Risk Management: Using the ATR for both fixed and trailing stops allows the strategy to adapt to changing market volatility, helping to protect your capital.
Flexibility: The strategy’s inputs are customizable via the input panel, allowing traders to fine-tune the parameters for different assets or market conditions.
Conclusion: FlexATR is designed as a balanced, adaptive strategy that emphasizes reliability and robust risk management across a variety of timeframes. While it may sometimes enter trades slightly later due to its filtering mechanism, its focus on confirming trends helps reduce the likelihood of false signals. This makes it particularly attractive for traders who prioritize a disciplined, multi-timeframe approach to capturing market trends.
Market Structure Break with Volume & ATR#### Indicator Overview:
The *Market Structure Break with Volume & ATR (MSB+VolATR)* indicator is designed to identify significant market structure breakouts and breakdowns using a combination of price action, volume analysis, and volatility (ATR). It is particularly useful for traders who rely on higher timeframes for swing trading or positional trading. The indicator highlights bullish and bearish breakouts, retests, fakeouts, and potential buy/sell signals based on RSI overbought/oversold conditions.
---
### Key Features:
1. *Market Structure Analysis*:
- Identifies swing highs and lows on a user-defined higher timeframe.
- Detects breakouts and breakdowns when price exceeds these levels with volume and ATR validation.
2. *Volume Validation*:
- Ensures breakouts are accompanied by above-average volume, reducing the likelihood of false signals.
3. *ATR Filter*:
- Filters out insignificant breakouts by requiring the breakout size to exceed a multiple of the ATR.
4. *RSI Integration*:
- Adds a momentum filter by considering overbought/oversold conditions using RSI.
5. *Visual Enhancements*:
- Draws colored boxes to highlight breakout zones.
- Labels breakouts, retests, and fakeouts for easy interpretation.
- Displays stop levels for potential trades.
6. *Alerts*:
- Provides alert conditions for buy and sell signals, enabling real-time notifications.
---
### Input Settings and Their Effects:
1. **Timeframe (tf):
- Determines the higher timeframe for market structure analysis.
- *Effect*: A higher timeframe (e.g., 1D) reduces noise and provides more reliable swing points, while a lower timeframe (e.g., 4H) may generate more frequent but less reliable signals.
2. **Lookback Period (length):
- Defines the number of historical bars used to identify significant highs and lows.
- *Effect*: A longer lookback period (e.g., 50) captures broader market structure, while a shorter period (e.g., 20) reacts faster to recent price action.
3. **ATR Length (atr_length):
- Sets the period for ATR calculation.
- *Effect*: A shorter ATR length (e.g., 14) reacts faster to recent volatility, while a longer length (e.g., 21) smooths out volatility spikes.
4. **ATR Multiplier (atr_multiplier):
- Filters insignificant breakouts by requiring the breakout size to exceed ATR × multiplier.
- *Effect*: A higher multiplier (e.g., 0.2) reduces false signals but may miss smaller breakouts.
5. **Volume Multiplier (volume_multiplier):
- Sets the volume threshold for breakout validation.
- *Effect*: A higher multiplier (e.g., 1.0) ensures stronger volume confirmation but may reduce the number of signals.
6. **RSI Length (rsi_length):
- Defines the period for RSI calculation.
- *Effect*: A shorter RSI length (e.g., 10) makes the indicator more sensitive to recent price changes, while a longer length (e.g., 20) smooths out RSI fluctuations.
7. *RSI Overbought/Oversold Levels*:
- Sets the thresholds for overbought (default: 70) and oversold (default: 30) conditions.
- *Effect*: Adjusting these levels can make the indicator more or less conservative in generating signals.
8. **Stop Loss Multiplier (SL_Multiplier):
- Determines the distance of the stop-loss level from the entry price based on ATR.
- *Effect*: A higher multiplier (e.g., 2.0) provides wider stops, reducing the risk of being stopped out prematurely but increasing potential losses.
---
### How It Works:
1. *Breakout Detection*:
- A bullish breakout occurs when the close exceeds the highest high of the lookback period, with volume above the threshold and breakout size exceeding ATR × multiplier.
- A bearish breakout occurs when the close falls below the lowest low of the lookback period, with similar volume and ATR validation.
2. *Retest Logic*:
- After a breakout, if price retests the breakout zone without closing beyond it, a retest label is displayed.
3. *Fakeout Detection*:
- If price briefly breaks out but reverses back into the range, a fakeout label is displayed.
4. *Buy/Sell Signals*:
- A sell signal is generated when price reverses below a bullish breakout zone and RSI is overbought.
- A buy signal is generated when price reverses above a bearish breakout zone and RSI is oversold.
5. *Stop Levels*:
- Stop-loss levels are plotted based on ATR × SL_Multiplier, providing a visual guide for risk management.
---
### Who Can Use It and How:
1. *Swing Traders*:
- Use the indicator on daily or 4-hour timeframes to identify high-probability breakout trades.
- Combine with other technical analysis tools (e.g., trendlines, Fibonacci levels) for confirmation.
2. *Positional Traders*:
- Apply the indicator on weekly or daily charts to capture long-term trends.
- Use the stop-loss levels to manage risk over extended periods.
3. *Algorithmic Traders*:
- Integrate the buy/sell signals into automated trading systems.
- Use the alert conditions to trigger trades programmatically.
4. *Risk-Averse Traders*:
- Adjust the ATR and volume multipliers to filter out low-probability trades.
- Use wider stop-loss levels to avoid premature exits.
---
### Where to Use It:
- *Forex*: Identify breakouts in major currency pairs.
- *Stocks*: Spot trend reversals in high-volume stocks.
- *Commodities*: Trade breakouts in gold, oil, or other commodities.
- *Crypto*: Apply to Bitcoin, Ethereum, or other cryptocurrencies for volatile breakout opportunities.
---
### Example Use Case:
- *Timeframe*: 1D
- *Lookback Period*: 50
- *ATR Length*: 14
- *ATR Multiplier*: 0.1
- *Volume Multiplier*: 0.5
- *RSI Length*: 14
- *RSI Overbought/Oversold*: 70/30
- *SL Multiplier*: 1.5
In this setup, the indicator will:
1. Identify significant swing highs and lows on the daily chart.
2. Validate breakouts with volume and ATR filters.
3. Generate buy/sell signals when price reverses and RSI confirms overbought/oversold conditions.
4. Plot stop-loss levels for risk management.
---
### Conclusion:
The *MSB+VolATR* indicator is a versatile tool for traders seeking to capitalize on market structure breakouts with added confirmation from volume and volatility. By customizing the input settings, traders can adapt the indicator to their preferred trading style and risk tolerance. Whether you're a swing trader, positional trader, or algorithmic trader, this indicator provides actionable insights to enhance your trading strategy.
Multi-Faceted Analysis ToolHere’s a detailed description for the **Multi-Faceted Analysis Tool** TradingView indicator:
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## Multi-Faceted Analysis Tool
### Overview
The **Multi-Faceted Analysis Tool** is a powerful TradingView indicator designed to enhance your technical analysis by combining several popular indicators: Simple Moving Average (SMA), Relative Strength Index (RSI), and Moving Average Convergence Divergence (MACD). This indicator provides traders with insightful market signals that can be tailored to fit various trading strategies and timeframes.
### Key Features
1. **Simple Moving Average (SMA)**:
- Plots a customizable SMA on the price chart. The length of the SMA can be adjusted to suit your analysis needs (default is set to 50). The SMA helps identify the overall trend direction.
2. **Relative Strength Index (RSI)**:
- Calculates and plots RSI values, providing insights into potential overbought or oversold market conditions. The user can customize the length of the RSI calculation (default is 14).
- Overbought (70) and oversold (30) levels are visually marked, helping traders identify potential reversal points.
3. **MACD**:
- Computes MACD values with customizable parameters for fast length, slow length, and signal length (defaults are 12, 26, and 9 respectively).
- The MACD histogram is displayed, highlighting the difference between the MACD line and the signal line, which can help traders visualize momentum shifts.
4. **Buy and Sell Signals**:
- Generates clear buy and sell signals based on RSI crossover with established thresholds (buy when RSI crosses above 30, sell when RSI crosses below 70). These signals are visually represented on the chart for easy decision-making.
5. **User-Friendly Customization**:
- All parameters are adjustable, allowing traders to set their preferred values based on individual strategies or market conditions. This flexibility ensures that the tool can cater to a wide range of trading styles.
