DrFX Reversal Algo - MACD-RSI System with Dynamic Zone Filtering**DrFX Reversal Algo** is a sophisticated reversal detection system that combines MACD momentum analysis with RSI confirmation and dynamic support/resistance zone filtering. This indicator employs advanced mathematical filtering techniques to identify high-probability reversal points while minimizing false signals through intelligent zone-based filtering.
**Core Innovation & Originality**
This system uniquely integrates four key analytical components:
1. **Enhanced MACD Engine** - Customizable fast (20), slow (50), and signal (12) lengths with crossover/crossunder detection optimized for reversal identification
2. **RSI Power Classification** - 14-period RSI used to classify signal strength and trend bias, distinguishing between "Strong" and regular signals
3. **Kalman-Filtered Dynamic Zones** - Advanced mathematical smoothing of support/resistance levels using Kalman filter algorithms for noise reduction
4. **Gradient-Based Visual System** - Power-weighted bar coloring that visualizes trend strength using MACD histogram and RSI signal intensity
**System Architecture & Functionality**
**Signal Generation Methodology:**
The core algorithm detects MACD line crossovers above and below the signal line, then applies RSI-based classification. When RSI signal (RSI-50) is positive during bullish MACD crossovers, the system generates "Strong Buy" signals. When RSI signal is negative or neutral, it produces regular "Buy" signals. The inverse logic applies for sell signals.
**Dynamic Zone Calculation:**
Support and resistance zones are calculated using a multi-step process:
1. **Volatility Bands**: ATR-based upper/lower bands using (high+low)/2 ± ATR * multiplier
2. **Precise Zone Definition**: Integration of 20-period highest/lowest calculations with volatility bands
3. **Kalman Filter Smoothing**: Advanced noise reduction using configurable Q (0.01) and R (0.1) parameters
4. **Zone Validation**: Real-time adjustment based on price action and volatility changes
**Kalman Filter Implementation:**
The system employs a custom Kalman filter function for zone smoothing:
```
kf_k = kf_p / (kf_p + kf_r)
kf_x = kf_k * input + (1 - kf_k) * previous_estimate
kf_p = (1 - kf_k) * kf_p + kf_q
```
This mathematical approach reduces zone boundary noise while maintaining responsiveness to genuine support/resistance level changes.
**Unique Visual Features**
**Power-Based Gradient System:**
Bar coloring utilizes a sophisticated gradient calculation based on MACD histogram power (absolute value) and RSI signal strength. The system creates dynamic color transitions:
- **Bullish Gradient**: Green spectrum (0-255 intensity) based on histogram power
- **Bearish Gradient**: Red spectrum (0-255 intensity) based on histogram power
- **Consolidation**: Mixed gradient indicating uncertain market conditions
**Dynamic Zone Visualization:**
- **Support Zones**: Blue-filled areas between smoothed support boundaries
- **Resistance Zones**: Red-filled areas between smoothed resistance boundaries
- **Zone Adaptation**: Real-time boundary adjustment based on volatility and price action
**Signal Classification System**
**Signal Strength Hierarchy:**
1. **Strong Buy**: MACD bullish crossover + RSI signal > 0 (above 50-line)
2. **Regular Buy**: MACD bullish crossover + RSI signal ≤ 0 (below 50-line)
3. **Strong Sell**: MACD bearish crossover + RSI signal < 0 (below 50-line)
4. **Regular Sell**: MACD bearish crossover + RSI signal ≥ 0 (above 50-line)
**Optional Zone Filtering:**
When enabled, the system only displays signals when:
- Buy signals: Price above smoothed support zone end
- Sell signals: Price below smoothed resistance zone start
**Usage Instructions**
**Primary Signal Interpretation:**
- **Large Green Triangles**: Strong buy signals with RSI confirmation above 50
- **Small Green Triangles**: Regular buy signals with RSI below 50
- **Large Red Triangles**: Strong sell signals with RSI confirmation below 50
- **Small Red Triangles**: Regular sell signals with RSI above 50
**Zone Analysis:**
- **Blue Zones**: Dynamic support areas where buying interest may emerge
- **Red Zones**: Dynamic resistance areas where selling pressure may increase
- **Zone Breaks**: Price movement outside zones indicates potential trend continuation
**Bar Color Interpretation:**
- **Bright Green**: Strong bullish momentum (high MACD histogram power + positive RSI)
- **Dark Green**: Moderate bullish momentum
- **Bright Red**: Strong bearish momentum (high MACD histogram power + negative RSI)
- **Dark Red**: Moderate bearish momentum
- **Mixed Colors**: Consolidation or uncertain trend direction
**Optimal Usage Strategies:**
1. **Reversal Trading**: Focus on signals occurring near zone boundaries
2. **Confirmation Trading**: Use zone filter to reduce false signals in trending markets
3. **Momentum Trading**: Prioritize "Strong" signals with bright gradient bar coloring
4. **Multi-Timeframe**: Combine with higher timeframe trend analysis for context
**Parameter Customization**
**MACD Settings:**
- **Fast Length (20)**: Shorter periods increase sensitivity
- **Slow Length (50)**: Longer periods reduce noise
- **Signal Smoothing (12)**: Affects crossover signal timing
**Support/Resistance Settings:**
- **Volatility Period (10)**: ATR calculation period for zone width
- **Multiplier (5.0)**: Zone expansion factor based on volatility
**Visual Settings:**
- **Gradient Range (2000)**: Controls color intensity scaling
- **Zone Filtering**: Enables/disables signal filtering based on zone position
**Advanced Features**
**Alert System:**
Comprehensive alert functionality with detailed messages including symbol, timeframe, current price, and signal type. Separate enable/disable options for long and short alerts.
**Mathematical Precision:**
The Kalman filter implementation provides superior noise reduction compared to simple moving averages while maintaining responsiveness to genuine market structure changes.
**Important Considerations**
This system works optimally in markets with clear support/resistance levels and moderate volatility. The Kalman filter smoothing may introduce slight lag during rapid market movements. Strong signals generally provide higher probability setups but may be less frequent than regular signals.
The algorithm combines established techniques (MACD, RSI) with advanced filtering and zone detection methodologies. The integration of multiple confirmation methods helps reduce false signals while maintaining sensitivity to genuine reversal opportunities.
**Disclaimer**: This indicator is designed for educational and analytical purposes. Past performance does not guarantee future results. The system's effectiveness varies across different market conditions and timeframes. Always implement proper risk management and consider multiple confirmation methods before making trading decisions.
Wstęgi i Kanały
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview
The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis.
🟢 How It Works
The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor:
bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5
adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio
alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor))))
This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes:
var float adaptiveTrend = source
adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source)
finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter
ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods:
volatility = ta.atr(volatilityPeriod)
upperBound = bollingerTrendValue + (volatility * volatilityMultiplier)
lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier)
The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell).
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity
Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency
Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
Apex Edge – Wolfe Wave HunterApex Edge – Wolfe Wave Hunter
The modern Wolfe Wave, rebuilt for the algo era
This isn’t just another Wolfe Wave indicator. Classic Wolfe detection is rigid, outdated, and rarely tradable. Apex Edge – Wolfe Wave Hunter re-engineers the pattern into a modern, SMC-driven model that adapts to today’s liquidity-dominated markets. It’s not about drawing pretty shapes – it’s about extracting precision entries with asymmetric risk-to-reward potential.
🔎 What it does
Automatic Wolfe Wave Detection
Identifies bullish and bearish Wolfe Wave structures using pivot-based logic, symmetry filters, and slope tolerances.
Channel Glow Zones
Highlights the Wolfe channel and projects it forward into the future (bars are user-defined). This allows you to see the full potential of the trade before price even begins its move.
Stop Loss (SL) & Entry Arrow
At the completion of Wave 5, the algo prints a Stop Loss line and a tiny entry arrow (green for bullish, red for bearish). but the colours can be changed in user settings. This is the “execution point” — where the Wolfe setup becomes tradable.
Target Projection Lines
TP1 (EPA): Derived from the traditional 1–4 line projection.
TP2 (1.272 Fib): Optional secondary profit target.
TP3 (1.618 Fib): Optional extended target for large runners.
All TP lines extend into the future, so you can track them as price evolves.
Volume Confirmation (optional)
A relative volume filter ensures Wave 5 is formed with meaningful market participation before a setup is confirmed.
Alerts (ready out of the box)
Custom alerts can be fired whenever a bullish or bearish Wolfe Wave is confirmed. No need to babysit the charts — let the script notify you.
⚙️ Customisation & User Control
Every trader’s market and style is different. That’s why Wolfe Wave Hunter is fully customisable:
Arrow Colours & Size
Works on both light and dark charts. Choose your own bullish/bearish entry arrow colours for maximum visibility.
Tolerance Levels
Adjust symmetry and slope tolerance to refine how strict the channel rules are.
Tighter settings = fewer but cleaner zones.
Looser settings = more frequent setups, but with slightly lower structural quality.
Channel Glow Projection
Define how many bars forward the channel is drawn. This controls how far into the future your Wolfe zones are extended.
Stop Loss Line Length
Keep the SL visible without it extending infinitely across your chart.
Take Profit Line Colors
Each TP projection can be styled to your preference, allowing you to clearly separate TP1, TP2, and TP3.
This isn’t a one-size-fits-all tool. You can shape Wolfe detection logic to match the pairs, timeframes, and market conditions you trade most.
🚀 Why it’s different
Classic Wolfe waves are rare — this script adapts the model into something practical and tradeable in modern markets.
Liquidity-aligned — many setups align with structural sweeps of Wave 3 liquidity before driving into profit.
Entry built-in — most Wolfe scripts only draw the structure. Wolfe Wave Hunter gives you a precise entry point, SL, and projected TPs.
Backtest-friendly — you’ll quickly discover which assets respect Wolfe waves and which don’t, creating your own high-probability Wolfe watchlist.
⚠️ Limitations & Disclaimer
Not all markets respect Wolfe Waves. Some FX pairs, metals, and indices respect the structure beautifully; others do not. Backtest and create your own shortlist.
No guaranteed sweeps. Many entries occur after a liquidity sweep of Wave 3, but not all. The algo is designed to detect Wolfe completion, not enforce textbook liquidity rules.
Probabilistic, not predictive. Wolfe setups don’t win every time. Always use risk management.
High-RR focus. This is not a high-frequency tool. It’s designed for precision, asymmetric setups where risk is small and reward potential is large.
✅ The Bottom Line
Apex Edge – Wolfe Wave Hunter is a modern reimagination of the Wolfe Wave. It blends structural geometry, liquidity dynamics, and algo-driven execution into a single tool that:
Detects the pattern automatically
Provides SL, entry, and TP levels
Offers alerts for hands-off trading
Allows deep customisation for different markets
When it hits, it delivers outstanding risk-to-reward. Backtest, refine your tolerances, and build your watchlist of assets where Wolfe structures consistently pay.
This isn’t just Wolfe detection — it’s Wolfe trading, rebuilt for the modern trader.
Developer Notes - As always with the Apex Edge Brand, user feedback and recommendations will always be respected. Simply drop us a message with your comments and we will endeavour to address your needs in future version updates.
4H IB + BO Midpoint – [SANIXLAB]This indicator plots the Initial Balance (IB) high and low for each 4-hour period and automatically calculates potential breakout levels and midpoints.
At the start of every new 4-hour block the script:
Captures that block’s high and low (Initial Balance),
Draws horizontal lines at the IB high, low and midpoint,
Calculates breakout targets above and below the IB using (optional) extension factor,
Creates horizontal lines at those breakout levels and their midpoint,
Breakout areas extend as new bars arrive.
MR.L
维加斯双通道策略Vegas Channel Comprehensive Strategy Description
Strategy Overview
A comprehensive trading strategy based on the Vegas Dual Channel indicator, supporting dynamic position sizing and fund management. The strategy employs a multi-signal fusion mechanism including classic price crossover signals, breakout signals, and retest signals, combined with trend filtering, RSI+MACD filtering, and volume filtering to ensure signal reliability.
Core Features
Dynamic Position Sizing: Continue adding positions on same-direction signals, close all positions on opposite signals
Smart Take Profit/Stop Loss: ATR-based dynamic TP/SL, updated with each new signal
Fund Management: Supports dynamic total amount management for compound growth
Time Filtering: Configurable trading time ranges
Risk Control: Maximum order limit to prevent over-leveraging
Leverage Usage Instructions
Important: This strategy does not use TradingView's margin functionality
Setup Method
Total Amount = Actual Funds × Leverage Multiplier
Example: Have 100U actual funds, want to use 10x leverage → Set total amount to 100 × 10 = 1000U
Trading Amount Calculation
Each trade percentage is calculated based on leveraged amount
Example: Set 10% → Actually trade 100U margin × 10x leverage = 1000U trading amount
Maximum Orders Configuration
Must be used in conjunction with leveraged amount
Example: 1000U total amount, 10% per trade, maximum 10 orders = maximum use of 1000U
Note: Do not exceed 100% of total amount to avoid over-leveraging
Parameter Configuration Recommendations
Leverage Configuration Examples
Actual funds 100U, 5x leverage, total amount setting 500U, 10% per trade, 50U per trade, recommended maximum orders 10
Actual funds 100U, 10x leverage, total amount setting 1000U, 10% per trade, 100U per trade, recommended maximum orders 10
Actual funds 100U, 20x leverage, total amount setting 2000U, 5% per trade, 100U per trade, recommended maximum orders 20
Risk Control
Conservative: 5-10x leverage, 10% per trade, maximum 5-8 orders
Aggressive: 10-20x leverage, 5-10% per trade, maximum 10-15 orders
Extreme: 20x+ leverage, 2-5% per trade, maximum 20+ orders
Strategy Advantages
Signal Reliability: Multiple filtering mechanisms reduce false signals
Capital Efficiency: Dynamic fund management for compound growth
Risk Controllable: Maximum order limits prevent liquidation
Flexible Configuration: Supports various leverage and fund allocation schemes
Time Control: Configurable trading hours to avoid high-risk periods
Usage Notes
Ensure total amount is set correctly (actual funds × leverage multiplier)
Maximum orders should not exceed the range allowed by total funds
Recommend starting with conservative configuration and gradually adjusting parameters
Regularly monitor strategy performance and adjust parameters timely
维加斯通道综合策略说明
策略概述
基于维加斯双通道指标的综合交易策略，支持动态加仓和资金管理。策略采用多信号融合机制，包括经典价穿信号、突破信号和回踩信号，结合趋势过滤、RSI+MACD过滤和成交量过滤，确保信号的可靠性。
核心功能
动态加仓：同向信号继续加仓，反向信号全部平仓
智能止盈止损：基于ATR的动态止盈止损，每次新信号更新
资金管理：支持动态总金额管理，实现复利增长
时间过滤：可设置交易时间范围
风险控制：最大订单数限制，防止过度加仓
杠杆使用说明
重要：本策略不使用TradingView的保证金功能
设置方法
总资金 = 实际资金 × 杠杆倍数
示例：实际有100U，想使用10倍杠杆 → 总资金设置为 100 × 10 = 1000U
交易金额计算
每笔交易百分比基于杠杆后的金额计算
示例：设置10% → 实际交易 100U保证金 × 10倍杠杆 = 1000U交易金额
最大订单数配置
必须配合杠杆后的金额使用
示例：1000U总资金，10%单笔，最大10单 = 最多使用1000U
注意：不要超过总资金的100%，避免过度杠杆
参数配置建议
杠杆配置示例
实际资金100U，5倍杠杆，总资金设置500U，单笔百分比10%，单笔金额50U，建议最大订单数10单
实际资金100U，10倍杠杆，总资金设置1000U，单笔百分比10%，单笔金额100U，建议最大订单数10单
实际资金100U，20倍杠杆，总资金设置2000U，单笔百分比5%，单笔金额100U，建议最大订单数20单
风险控制
保守型：5-10倍杠杆，10%单笔，最大5-8单
激进型：10-20倍杠杆，5-10%单笔，最大10-15单
极限型：20倍以上杠杆，2-5%单笔，最大20单以上
策略优势
信号可靠性：多重过滤机制，减少假信号
资金效率：动态资金管理，实现复利增长
风险可控：最大订单数限制，防止爆仓
灵活配置：支持多种杠杆和资金配置方案
时间控制：可设置交易时间，避开高风险时段
使用注意事项
确保总资金设置正确（实际资金×杠杆倍数）
最大订单数不要超过总资金允许的范围
建议从保守配置开始，逐步调整参数
定期监控策略表现，及时调整参数
Double Median SD Bands | MisinkoMasterThe Double Median SD Bands (DMSDB) is a trend-following tool designed to capture market direction in a way that balances responsiveness and smoothness, filtering out excessive noise without introducing heavy lag.
Think of it like a house:
A jail (too restrictive) makes you miss opportunities.
No house at all (too unsafe) leaves you exposed to false signals.
DMSDB acts like a comfortable house with windows—protecting you from the noise while still letting you see what’s happening in the market.
🔎 Methodology
The script works in the following steps:
Standard Deviation (SD) Calculation
Computes the standard deviation of the selected price source (ohlc4 by default).
The user can choose whether to use biased (sample) or unbiased (population) standard deviation.
Raw Bands Construction
Upper Band = source + (SD × multiplier)
Lower Band = source - (SD × multiplier)
The multiplier can be adjusted for tighter or looser bands.
First Median Smoothing
Applies a median filter over half of the length (len/2) to both bands.
This reduces noise without creating excessive lag.
Second Median Smoothing
Applies another median filter over √len to the already smoothed bands.
This produces a balance:
Cutting the length → maintains responsiveness.
Median smoothing → reduces whipsaws.
The combination creates a fast yet clean band system ideal for trend detection.
📈 Trend Logic
The trend is detected based on price crossing the smoothed bands:
Long / Bullish (Purple) → when price crosses above the upper band.
Short / Bearish (Gold) → when price crosses below the lower band.
Neutral → when price remains between the bands.
🎨 Visualization
Upper and lower bands are plotted as colored lines.
The area between the bands is filled with a transparent zone that reflects the current bias:
Purple shading = Bullish zone.
Golden shading = Bearish zone.
This creates a visual tunnel for trend confirmation, helping traders quickly identify whether price action is trending or consolidating.
⚡ Features
Adjustable Length parameter (len) for dynamic control.
Adjustable Band Multiplier for volatility adaptation.
Choice between biased vs. unbiased standard deviation.
Double median smoothing for clarity + responsiveness.
Works well on cryptocurrencies (e.g., BTCUSD) but is flexible enough for stocks, forex, and indices.
✅ Use Cases
Trend Following → Ride trends by staying on the correct side of the bands.
Entry Timing → Use crossovers above/below bands for entry triggers.
Filter for Other Strategies → Can serve as a directional filter to avoid trading against the trend.
⚠️ Limitations & Notes
This is a trend-following tool, so it will perform best in trending conditions.
In sideways or choppy markets, whipsaws may still occur (although smoothing reduces them significantly).
The indicator is not a standalone buy/sell system. For best results, combine with volume, momentum, or higher-timeframe confluence.
All of this makes for a really unique & original tool, as it removes noise but keeps good responsitivity, using methods from many different principles which make for a smooth a very useful tool
QFL StDev Mean Reversal σ-Based Levels v.1.0🔹 Theory Behind the QFL σ-Based Mean Reversal Strategy
1. QFL Core Concept (Base + Bounce)
The QFL (Quickfingers Luc) method is a mean-reversion trading strategy built around the idea of “bases”:
A base is a strong support level, typically formed after a sharp move down, where buyers defended price.
When price drops below the base, it is considered an “overreaction” or “fake breakdown.”
The logic: after such a drop, price often snaps back upward (mean reversion).
In short:
Identify strong bases with volume confirmation.
Wait for a breakdown below the base (oversold condition).
Enter a long trade betting on a bounce back toward the mean.
2. σ-Based Levels (Standard Deviation Bands)
This version enhances QFL using statistics.
A moving average (SMA) of price defines the mean.
Standard Deviation (σ) measures volatility.
Multiple σ-levels define dynamic support/resistance:
Upper Band (Mean + 3σ) → Overbought zone.
Entry Band (Mean – 2σ) → Oversold trigger for entries.
TP Level (Mean + 3σ) → Take-profit target.
SL Level (Mean – 3σ) → Stop-loss safeguard.
This makes the strategy adaptive to volatility instead of relying on static levels.
3. Volume Confirmation
Not every dip below a base is worth trading. To filter noise:
The script requires pivot low detection (local support formation).
That pivot must coincide with volume spike confirmation:
Volume > SMA(Volume) × Factor.
This ensures breakdowns are meaningful, not just random dips.
4. Mean Reversion Logic
Entry triggers when:
A valid base has been established.
Price drops below the Entry Band (–2σ).
No active position is open.
Exit logic:
Take Profit → when price reaches the upper σ-based TP level.
Stop Loss → when price breaches the lower σ-based SL level.
This balances risk/reward using statistically significant levels.
🔹 Usage in TradingView
1. Adding to Chart
Copy and paste the script into TradingView Pine Editor.
Click Add to Chart → It overlays σ-bands, base levels, entry signals, and exit zones.
2. Inputs & Tuning Parameters
Volume Factor (default: 2.0)
Controls how strong a volume spike must be to confirm a base.
Higher = stricter filtering (fewer but stronger signals).
StDev Length (default: 20)
Window size for SMA + σ.
Shorter = more reactive (good for scalping).
Longer = smoother, more stable (good for swing trading).
Base Bounce Sigma (default: 3.0)
Defines how much price must bounce above pivot low to validate it as a base.
Drop Below Sigma (default: 2.0)
Defines how far below the mean price must drop to trigger entry (oversold).
Take Profit Sigma (default: 3.0)
Exit level above mean.
Higher = greedier (larger TP, fewer hits).
Lower = safer (quicker exits).
Stop Loss Sigma (default: 3.0)
Safety net if price continues falling instead of reverting.
Adjust based on asset volatility.
3. Chart Visuals
Blue line = Detected base.
Purple band = Entry zone (–2σ).
Green line = Take-profit target (+3σ).
Maroon line = Stop-loss boundary (–3σ).
Background purple highlight = Mean reversion signal zone.
Gray fill = Risk/reward channel from entry to TP.
4. Alerts
Entry Alert → When entry condition triggers.
Exit Alert → When trade closes (TP/SL).
Useful for automation with brokers via webhooks.
5. Best Markets & Timeframes
Works well on crypto, forex, and volatile equities.
Effective on 5m–1h charts for intraday trading.
On higher timeframes (4h–1D), it identifies swing trade reversals.
🔹 Strengths & Weaknesses
✅ Strengths
Combines QFL base logic with statistical volatility filtering.
Dynamic (σ-based) → adapts to changing volatility.
Filters weak setups with volume confirmation.
Provides automated TP & SL for risk management.
⚠️ Weaknesses
Mean reversion assumes price will bounce → vulnerable in strong trends.
Works better in ranging / sideways markets than trending ones.
Parameters must be optimized for each asset & timeframe.
Volume confirmation may be less reliable in markets with fake volume (e.g., some altcoins).
✅ In summary:
The QFL σ Mean Reversal Strategy is a volatility-adaptive, volume-filtered mean reversion system. It detects bases with pivot + volume logic, waits for an oversold drop below σ-bands, and enters trades betting on a bounce back toward the mean. TP and SL are defined statistically, making it more robust than traditional fixed-level QFL implementations.
Waves of Wealth Pair Trading RatioThis versatile indicator dynamically plots the ratio between two user-selected instruments, helping traders visualize relative performance and detect potential mean-reversion or trend continuation opportunities.
Features include:
User inputs for selecting any two instrument symbols for comparison.
Adjustable moving average period to track the average ratio over time.
Customizable standard deviation multiplier to define statistical bands for overbought and oversold conditions.
Visual display of the ratio line alongside upper and lower bands for clear trading signals.
Ideal for pair traders and market analysts seeking a flexible tool to monitor inter-asset relationships and exploit deviations from historical norms.
Simply set your preferred symbols and parameters to tailor the indicator to your trading style and assets of interest.
How to Use the Custom Pair Trading Ratio Indicator
Select symbols: Use the indicator inputs to set any two instruments you want to compare—stocks, commodities, ETFs, or indices. No coding needed, just type or select from the dropdown.
Adjust parameters: Customize the moving average length to suit your trading timeframe and style. The standard deviation multiplier lets you control sensitivity—higher values mean wider bands, capturing only larger deviations.
Interpret the chart:
The ratio line shows relative strength between the two instruments.
The middle line represents the average ratio (mean).
The upper and lower bands indicate statistical extremes where price action is usually overextended.
Trading signals:
Look to enter pair trades when the ratio moves outside the bands—expecting a return to the mean.
Use the bands and mean to set stop-loss and profit targets.
Combine with other analysis or fundamental insight for best results.
Panchak Dates High/Low 2024-2025 - UpdatedThis is showing Panchak Periods High and Low and plot line on high value and low value
Candle Colored by Volume Z-score with S/R [Morty]All Credits to :
I have just added Support and Resistance line
This indicator colors the candles according to the z-score of the trading volume. You can easily see the imbalance on the chart. You can use it at any timeframe.
In statistics, the standard score (Z-score) is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured. Raw scores above the mean have positive standard scores, while those below the mean have negative standard scores.
This script uses trading volume as source of z-score by default.
Due to the lack of volume data for some index tickers, you can also choose candle body size as source of z-score.
features:
- custom source of z-score
- volume
- candle body size
- any of above two
- all of above two
- custom threshold of z-score
- custom color chemes
- custom chart type
- alerts
default color schemes:
- green -> excheme bullish imbalance
- blue -> large bullish imbalance
- red -> excheme bearish imbalance
- purple -> large bearish imbalance
- yellow -> low volume bars, indicates "balance", after which volatility usually increases and tends to continue the previous trend
Examples:
* Personally, I use dark theme and changed the candle colors to black/white for down/up.
Volume as Z-score source
Bollinger Band Oscillator (Distance between 2 bands)📌 Bollinger Band Width Oscillator
Description
This indicator measures the distance between the Upper and Lower Bollinger Bands and displays it as an oscillator. It is designed to help traders track squeeze (contraction) and expansion phases in the market, which often precede significant price moves.
Calculation
Bollinger Bands are built from a moving average (MA) and standard deviation.
Band Width = Upper Band – Lower Band.
Users can normalize the width in three ways:
Absolute: raw value in price units.
% of Basis: width relative to the MA (useful for cross-asset or multi-timeframe comparison).
ATR-normalized: width divided by ATR, filtering out absolute volatility effects.
Interpretation
Low oscillator values → Bands are contracting → market is consolidating, often a precursor to volatility breakouts.
High oscillator values → Bands are expanding → market is experiencing strong volatility or following a breakout.
The included Signal line can help identify turning points when the oscillator crosses above/below it.
Customization
Select MA type (SMA, EMA, SMMA, WMA, VWMA).
Adjust StdDev multiplier.
Choose normalization (Absolute, % Basis, ATR).
Optional smoothing and histogram/line display.
👉 Practical Use:
Detect upcoming breakouts by spotting “squeeze” conditions.
Compare volatility regimes across assets or timeframes.
Enhance breakout or trend-following strategies with volatility context.
🔹 Short Description (for TradingView search/preview)
Measures the width of Bollinger Bands as an oscillator. Helps identify squeeze and expansion phases, anticipate breakouts, and track volatility across assets or timeframes.
EMA Crossover and Candle ColoringColors candles based on the 21D Ema , one or two closes above each and gives blue and orange dots for when the 5D ema is above or below the 21D ema
Simple system but it helps to identify trends
8 EMA/SMA + HMA + Pivot PointsMultiple customizeable Moing average indictors including Hall moving average, Exponential Moving average. Also includes Pivot Point indicator as an all-in-one indicator
Panchak Indicator 2025 - High/Low with OptionsPanchak high low line, plote high low of panchak dates candels
Full Numeric Panel For Scalping – By Ali B.AI Full Numeric Panel – Final (Scalping Edition)
This script provides a numeric dashboard overlay that summarizes the most important technical indicators directly on the price chart. Instead of switching between multiple panels, traders can monitor all key values in a single glance – ideal for scalpers and short-term traders.
🔧 What it does
Displays live values for:
Price
EMA9 / EMA21 / EMA200
Bollinger Bands (20,2)
VWAP (Session)
RSI (configurable length)
Stochastic RSI (RSI base, Stoch length, K & D smoothing configurable)
MACD (Fast/Slow/Signal configurable) → Line, Signal, and Histogram shown separately
ATR (configurable length)
Adds Dist% column: shows how far the current price is from each reference (EMA, BB, VWAP etc.), with green/red coloring for positive/negative values.
Optional Rel column: shows context such as RSI zone, Stoch RSI cross signals, MACD cross signals.
🔑 Why it is original
Unlike simply overlaying indicators, this panel:
Collects multiple calculations into one unified table, saving chart space.
Provides numeric precision (configurable decimals for MACD, RSI, etc.), so scalpers can see exact values.
Highlights signal conditions (crossovers, overbought/oversold, zero-line crosses) with clear text or symbols.
Fully customizable (toggle indicators on/off, position of the panel, text size, colors).
📈 How to use it
Add the script to your chart.
In the input menu, enable/disable the metrics you want (RSI, Stoch RSI, MACD, ATR).
Match the panel parameters with your sub-indicators (for example: set Stoch RSI = 3/3/9/3 or MACD = 6/13/9) to ensure values are identical.
Use the numeric panel as a quick decision tool:
See if RSI is near 30/70 zones.
Spot Stoch RSI crossovers or extreme zones (>80 / <20).
Confirm MACD line/signal cross and histogram direction.
Monitor volatility with ATR.
This makes scalping decisions faster without losing precision. The panel is not a signal generator but a numeric assistant that summarizes market context in real time.
⚡ This version fixes earlier limitations (no more vague mashup, clear explanation of originality, clean chart requirement). TradingView moderators should accept it since it now explains:
What the script is
How it is different
How to use it practically
Keyzone🔑 Keyzone Levels (KZ)
KZ3 (Light Green) → Short-term support zone
KZ8 (Dark Green) → Medium-term support / resistance zone
KZ21 (Orange) → Main decision zone, often used to confirm trend direction
KZ89 (Red) → Long-term boundary, defines strong support/resistance in Sideway markets
📌 Keyzone levels are dynamic zones that adjust as the market moves. They help identify bias (trend vs sideway) and setups such as Trap Reversal (TRS), Swing Reversal (SRS), and Snapback (SBS) in the Keyzone Master Framework.
σ-Based SL/TP (Long & Short). Statistical Volatility (Quant Upgrade of ATR)
Instead of ATR’s simple moving average, use standard deviation of returns (σ), realized volatility, or implied volatility (options data).
SL = kσ, TP = 2kσ (customizable).
Why better than ATR: more precise reflection of actual distribution tails, not just candle ranges.
Bollinger Bands (with Width/GaUGE)This overlay plots standard Bollinger Bands and makes volatility obvious. The fill between bands is color-coded by band width (tight = red “squeeze”, wide = teal “expansion”, mid = yellow). A compact table (top-right) shows live BB Gap ($) and BB Width (%), and the width also appears in the status line. Thresholds for squeeze/expansion are user-set. Use it to avoid low-volatility chop and time breakouts when width expands.
Fiery River Torgi### Description of the "Fiery River" (FR) Indicator
**Overview of the Indicator**
"Fiery River" (abbreviated as FR, with variants like "FR-Torg") is a technical indicator for TradingView, written in Pine Script version 6. It combines Fibonacci levels with exponential moving averages (EMAs) and standard deviations to dynamically plot support and resistance zones on price charts. The indicator calculates "effective close" prices based on candlestick bodies for better volatility representation, then derives levels using custom Fibonacci multipliers applied to deviations from the EMA midline. It supports multi-timeframe analysis by incorporating a secondary timeframe, making it ideal for traders analyzing trends, reversals, and extensions in various markets like forex or crypto. The name evokes a "fiery" stream of adaptive levels flowing across the chart. 🔥
**Key Features**
- **Level Construction**: Uses an EMA of the "effective close" price (derived from open/close max/min) and standard deviation to create a midline. Fibonacci levels are calculated by multiplying deviations with coefficients (e.g., 1.55, 1.89, 0.89), resulting in "long" and "short" lines. It plots 9 lines total: 5 for the primary timeframe (green, red, gray, black for shorts, and a midline) and 4 for the secondary timeframe (with transparency for distinction).
- **Color Scheme**: Green for weaker levels, red for stronger, gray for mid-range, and black for shorts/extensions.
- **Fills**: Adds green fills between level pairs to highlight potential trading zones, enhancing visual clarity.
- **Alerts**: Automatic notifications trigger when the price touches specific levels (e.g., "FM-Torgi green!" for the first green line), helping with timely signals.
- **Multi-Timeframe Support**: Pulls data from a secondary timeframe (e.g., daily while main is hourly) using `request.security`, allowing comparison across scales.
- **Customization**: Inputs for EMA periods (default 89), secondary timeframe, and multipliers for flexibility.
**How to Use**
1. Add the indicator to your TradingView chart via the "Indicators" menu.
2. Configure settings: Set EMA periods, choose a secondary timeframe (e.g., 'D' for daily), and adjust Fibonacci multipliers if needed.
3. Interpret levels: Use green/red zones for entries/exits, gray for mid-support, and shorts for extensions. Fills indicate high-probability areas.
4. Enable alerts for real-time notifications on level touches.
Best combined with other tools like RSI or volume for confirmation. It's suited for swing trading or scalping on volatile assets. 📈
**Advantages and Limitations**
- **Pros**: Highly adaptive to price movements, customizable, visually intuitive with fills and multi-timeframe depth. Efficient for identifying Fibonacci-based zones without manual drawing.
- **Cons**: Can clutter the chart with many lines if not managed; requires testing on different symbols as hardcoded multipliers may not fit all markets perfectly. Potential for false signals in sideways markets.
If you'd like me to expand on the code, suggest modifications, or provide examples, let me know! 😊
Fiery River### Description of the "Fiery River" (FR) Indicator
**Overview of the Indicator**
"Fiery River" (abbreviated as FR) is a technical indicator for TradingView, written in Pine Script version 6. It's designed for traders who incorporate Fibonacci levels with moving averages to analyze support and resistance zones. The indicator dynamically plots levels based on a selected moving average (MA) and Fibonacci multipliers, displaying them on the current timeframe and an additional secondary timeframe. This helps visualize potential reversal or continuation points, making analysis more comprehensive. The name "Fiery River" evokes a "fiery" flow of levels that "stream" across the chart, adapting to price movements. 🔥
**Key Features**
- **Level Construction**: The indicator calculates a moving average (EMA, SMA, WMA, RMA, or HMA) from the closing price and multiplies it by specified Fibonacci coefficients (0.618, 0.5, 0.382, 0.27, 0.18 for "long" levels and 1.618, 1.5, 1.382 for "short" levels). This creates 10 lines: 5 for the current timeframe (fully visible) and 5 for the secondary timeframe (with semi-transparency for distinction).
- **Color Scheme**: Levels are colored in gray, red, orange, and green, with additional "short" variants for extensions.
- **Fills**: Green fills are added between level pairs to highlight areas of interest, making the chart more visually intuitive.
- **Alerts**: Automatic notifications when the price touches levels (e.g., "Price touches Red line"), helping you stay on top of key moments.
- **Multi-Timeframe Support**: Incorporates a secondary timeframe (e.g., daily if the main is hourly) for comparing levels across different scales.
**How to Use**
1. Add the indicator to your chart in TradingView.
2. Customize settings in the panel: Select MA type, period (default 89), secondary timeframe, and Fibonacci coefficients.
3. Analyze levels as potential entry/exit points: Gray and red for stronger zones, green for weaker ones. Use fills to identify ranges.
4. Enable alerts for real-time signals.
It's ideal for strategies based on Fibonacci and trends, but always combine with other tools for confirmation. 📈
**Advantages and Limitations**
- **Pros**: Highly customizable, visually clear, supports multiple MA types and timeframes. Great for scalping and swing trading.
- **Cons**: Can create a lot of lines on the chart, potentially overwhelming if not managed. May require testing for optimal settings on volatile assets.
If you need any adjustments, more details, or help with the code, just let me know! 😊
Nikkei PER Curve (EPS Text Area Input)
This indicator visualizes the PER levels of the Nikkei 225 based on the dates and EPS data entered in the text area.
By plotting multiple PER multiplier lines, it helps users to understand the following:
Potential support and resistance levels based on PER multipliers
Comparison between the current stock price and theoretical valuation levels
Observation of PER trends and detection of deviations from standard valuation levels
Trading Decisions:
When the stock price approaches a specific PER line, it can serve as a reference for support or resistance.
During intraday chart analysis, PER lines are drawn based on the most recent EPS, making them useful as reference levels even during market hours.
Valuation Analysis:
On daily charts, it helps to assess whether the Nikkei is overvalued or undervalued compared to historical levels, or to identify changes in valuation levels.
Risk Management:
The theoretical price lines based on PER can be used as reference points for stop-loss or profit-taking decisions.
Simple Data Input:
EPS data is entered in a text area, one line per date, in comma-separated format:
YYYY/MM/DD,EPS
YYYY/MM/DD,EPS
Multiple entries can be input by using line breaks between each date.
Note: Dates for which no candlestick exists in the chart will not be displayed.
This allows easy updating of PER lines without complex spreadsheets or external tools.
EPS Data Input: Manual input of date and EPS via the text area; supports multiple data entries.
PER Multiplier Lines:
For evenly spaced lines, simply set the central multiplier and the interval between lines. The indicator automatically generates 11 lines (center ±5 lines).
For non-even spacing or individual multiplier settings, you can choose to adjust each line.
Close PER Labels: Displays the PER of the close price relative to the current EPS.
Timeframe Limitation: Use on daily charts (1D) or lower. PER lines cannot be displayed on higher timeframes.
Label Customization: Allows adjustment of text size, color, and position.
EPS Parsing: The indicator reads the input text area line by line, splitting each line by a comma to obtain the date and EPS value.
Data Storage: The dates and EPS values are stored in arrays. These arrays allow the script to efficiently look up the latest EPS for any given date.
PER Calculation: For each chart bar, the indicator calculates the theoretical price for multiple PER multipliers using the formula:
Theoretical Price = EPS × PER multiplier
Line Plotting: PER lines are drawn at these calculated price levels. Labels are optionally displayed for the close price PER.
Date Matching: If a date from the EPS data does not exist as a candlestick on the chart, the corresponding PER line is not plotted.
PER lines are theoretical values: They serve as psychological reference points and do not always act as true support or resistance.
Market Conditions: Lines may be broken depending on market circumstances.
Accuracy of EPS Data: Be careful with EPS input errors, as incorrect data will result in incorrect PER curves.
Input Format: Dates and EPS must be correctly comma-separated and entered one per line. Dates with no corresponding candlestick on the chart will not be plotted. Incorrect formatting may prevent lines from displaying.
Reliability: No method guarantees success in trading; use in combination with backtesting and other technical analysis tools.
このインジケータは、入力した日付とEPSデータを基に日経225のPER水準を視覚化するものです
複数のPER倍率ラインを描画することで、以下を把握するのに役立ちます：
PER倍率に基づく潜在的なサポート・レジスタンス水準や目安
現在の株価と理論上の評価水準との比較
過去から現在までのPER推移の観察
トレード判断:
株価が特定の倍率のPERラインに近づいたとき、抵抗や支持の目安としての活用
日中足表示時は、前日(最新日)のEPSに基づいたPERラインを表示するように作成しているので、場中でも参考目安として使用可能
評価分析:
過去の推移と比較して日経が割高か割安か、またはPER評価水準が変化したかの確認
リスク管理:
PERに基づく理論価格ラインを、損切りや利確の目安としての利用
簡単なデータ入力:
EPSデータはテキストエリアに手動入力。1行につき1日付・EPSをカンマ区切りで記入します
例
2025/09/19,2492.85
2025/09/18,2497.43
行を改行することで複数データ入力が可能
注意: チャート上にローソク足が存在しない日付のデータは表示されません
表計算や外部ツールを使わずに倍率を掛けたPERラインの作成・更新が簡単に行える
PER倍率ライン:
等間隔ラインの場合、中心倍率と各ラインの間隔を設定するだけで、自動的に中心値±5本、計11本のラインを作成
等間隔以外や個別設定したい場合は で調整可能
終値PERラベル: 現在のEPSに対する終値PERを表示
時間足制限: 日足(1日足)以下で使用すること。高い時間足ではPERラインは表示できません
ラベルカスタマイズ: 文字サイズ、色、位置を調整可能
EPSデータの読み取り: 改行を検知し1日分のデータとして識別し、カンマで分割して日付とEPS値を取得
配列への格納: 日付とEPSを配列に格納し、各バーに対して最新のEPSを参照できるようにする
PER計算: 各バーに対して、以下の式で複数のPER倍率の理論価格を計算：
理論価格 = EPS × PER倍率
日付照合: EPSデータの日付がチャート上にローソク足として存在したら格納した配列からデータを取得。ローソク足が存在しない場合、そのPERラインは表示されない
ライン描画: 計算した価格にPERラインを描画。必要に応じて終値PERラベルも表示。
PERラインは理論値であり心理的目安として機能することがありますが、必ずしも機能する訳ではない
その為、過去の検証や他のテクニカル指標と併用推奨
市況によってはラインを無視するように突破する可能性ことがある
EPSデータの入力ミスに注意すること。誤入力するとPER曲線が誤表示される
日付とEPSの入力は1行ずつ、正しい位置でカンマ区切りをいれること
ローソク足が存在しない日付のデータは正しく表示されないことがあるので注意
誤った入力形式ではラインが表示されない場合がある
