EMA Price Range by tuanduongEMA Price Range Indicator – Dynamic Range Analysis with Custom EMA (tuanduong2511)
Overview
The EMA Price Range Indicator is designed to help traders visualize the distance between price action and a key Exponential Moving Average (EMA). This indicator dynamically calculates the range from each candle to a user-defined EMA and displays it in a real-time table. By understanding the relationship between price and the EMA, traders can better gauge potential support, resistance, and overextension in the market.
Key Features
✅ Customizable EMA – Allows users to choose the EMA period that best suits their strategy (default: 144).
✅ Real-Time Range Calculation – Computes the absolute difference between the EMA and the price (using the high or low, depending on whether the candle is above or below the EMA).
✅ Minimalist UI – The EMA is plotted directly on the chart, while a small table in the bottom-right corner provides numerical insights, reducing chart clutter.
✅ Versatile Use Cases – Suitable for trend-following traders (identifying pullbacks to EMA) and mean-reversion traders (spotting extended price movements).
How It Works
User-Defined EMA:
The script calculates an Exponential Moving Average (EMA) based on the selected period.
EMA adapts dynamically, giving more weight to recent price movements.
Range Calculation:
If the price is above the EMA, the range is measured from the high point of the candle to the EMA.
If the price is below the EMA, the range is measured from the low point of the candle to the EMA.
This approach ensures that we’re measuring the most relevant distance for price interaction.
Live Table Display:
The current EMA value and the distance (range) from the price are displayed in a small table in the bottom-right corner of the chart.
How to Use It
📌 Trend Traders: Use the indicator to track pullbacks to key EMAs (e.g., EMA 50, 144, or 200). When the price is far from the EMA, it may indicate an overextended trend or potential retracement zone.
📌 Mean Reversion Traders: Look for extreme deviations between price and the EMA. Large distances can signal potential price snapbacks to the mean.
📌 Scalping & Day Trading: Short-term traders can use it with fast EMAs (e.g., EMA 21 or 34) to measure quick price movements relative to short-term momentum.
Why This Indicator?
Unlike traditional EMA indicators, which only plot a moving average, this script provides quantifiable price distance to the EMA, helping traders make data-driven decisions. It allows traders to answer:
✅ Is the price stretched too far from the EMA?
✅ Should I wait for a pullback before entering?
✅ Is the trend strong, or is the price losing momentum?
By integrating EMA-based range analysis, traders gain a clearer understanding of market conditions and can improve their entry, exit, and risk management strategies.
M-oscillator
Gioteen-NormThe "Gioteen-Norm" indicator is a versatile and powerful technical analysis tool designed to help traders identify key market conditions such as divergences, overbought/oversold levels, and trend strength. By normalizing price data relative to a moving average and standard deviation, this indicator provides a unique perspective on price behavior, making it easier to spot potential reversals or continuations in the market.
The indicator calculates a normalized value based on the difference between the selected price and its moving average, scaled by the standard deviation over a user-defined period. Additionally, an optional moving average of this normalized value (Green line) can be plotted to smooth the output and enhance signal clarity. This dual-line approach makes it an excellent tool for both short-term and long-term traders.
***Key Features
Divergence Detection: The Gioteen-Norm excels at identifying divergences between price action and the normalized indicator value. For example, if the price makes a higher high while Red line forms a lower high, it may signal a bearish divergence, hinting at a potential reversal.
Overbought/Oversold Conditions: Extreme values of Red line (e.g., significantly above or below zero) can indicate overbought or oversold conditions, helping traders anticipate pullbacks or bounces.
Trend Strength Insight: The normalized output reflects how far the price deviates from its average, providing a measure of momentum and trend strength.
**Customizable Parameters
Traders can adjust the period, moving average type, applied price, and shift to suit their trading style and timeframe.
**How It Works
Label1 (Red Line): Represents the normalized price deviation from a user-selected moving average (SMA, EMA, SMMA, or LWMA) divided by the standard deviation over the specified period. This line highlights the relative position of the price compared to its historical range.
Label2 (Green Line, Optional): A moving average of Label1, which smooths the normalized data to reduce noise and provide clearer signals. This can be toggled on or off via the "Draw MA" option.
**Inputs
Period: Length of the lookback period for normalization (default: 100).
MA Method: Type of moving average for normalization (SMA, EMA, SMMA, LWMA; default: EMA).
Applied Price: Price type used for calculation (Close, Open, High, Low, HL2, HLC3, HLCC4; default: Close).
Shift: Shifts the indicator forward or backward (default: 0).
Draw MA: Toggle the display of the Label2 moving average (default: true).
MA Period: Length of the moving average for Label2 (default: 50).
MA Method (Label2): Type of moving average for Label2 (SMA, EMA, SMMA, LWMA; default: SMA).
**How to Use
Divergence Trading: Look for discrepancies between price action and Label1. A bullish divergence (higher low in Label1 vs. lower low in price) may suggest a buying opportunity, while a bearish divergence could indicate a selling opportunity.
Overbought/Oversold Levels: Monitor extreme Label1 values. For instance, values significantly above +2 or below -2 could indicate overextension, though traders should define thresholds based on the asset and timeframe.
Trend Confirmation: Use Label2 to confirm trend direction. A rising Label2 suggests increasing bullish momentum, while a declining Label2 may indicate bearish pressure.
Combine with Other Tools: Pair Gioteen-Norm with support/resistance levels, RSI, or volume indicators for a more robust trading strategy.
**Notes
The indicator is non-overlay, meaning it plots below the price chart in a separate panel.
Avoid using a Period value of 1, as it may lead to unstable results due to insufficient data for standard deviation calculation.
This tool is best used as part of a broader trading system rather than in isolation.
**Why Use Gioteen-Norm?
The Gioteen-Norm indicator offers a fresh take on price normalization, blending statistical analysis with moving average techniques. Its flexibility and clarity make it suitable for traders of all levels—whether you're scalping on short timeframes or analyzing long-term trends. By publishing this for free, I hope to contribute to the TradingView community and help traders uncover hidden opportunities in the markets.
**Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Always backtest and validate any strategy before trading with real capital, and use proper risk management.
MACD Z-ScoreMACD Z-Score Indicator Description
This indicator takes the traditional MACD and converts its histogram into a standardized z‑score. It does so by first calculating the MACD using a fast and a slow moving average (which you can choose to compute with either SMA or EMA). The MACD histogram is then derived as the difference between the MACD line and a signal line (again, with your choice of smoothing method).
Next, the indicator computes a z‑score of that histogram over a user‑defined lookback period. In simple terms, it measures how far (in terms of standard deviations) the current histogram value deviates from its average. This standardization makes it easier to compare the MACD’s momentum across different assets or timeframes. There’s also an option to further smooth the z‑score with an EMA to reduce noise.
Finally, the indicator plots the resulting z‑score along with horizontal reference lines at key levels (such as 1, -1, 2, -2, 3, and -3) and changes the background color when the z‑score exceeds a high threshold (above 2) or drops below a low threshold (below -2), providing a visual cue for potential long or short conditions.
This indicator is ideal for traders looking for a normalized way to assess momentum, helping them to easily spot when the MACD histogram deviates significantly from its typical range.
Market Push Meter - CoffeeStyleMarket Push Meter - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the Market Push Meter indicator, a sophisticated volume analysis tool developed by CoffeeKiller with the help and assistance of FindBetterTrades that measures and visualizes the ongoing battle between buyers and sellers through volume pressure analysis.
🔔 **Warning: This Is Not a Standard Volume Indicator** 🔔 This indicator analyzes volume pressure in a unique way, combining directional volume with price action to identify market imbalances between buyers and sellers. All credit for the core logic for this indicator goes to FindBetterTrades and his/hers Volume Pressure Histogram (Normalized) (this is my adaptation and style added to that core logic, thus the CoffeeStyle name was added).
Core Concept: Volume Pressure Analysis
The foundation of this indicator lies in measuring the imbalance between buying and selling volume, providing insights into which market participants are exerting more pressure on price movements.
Volume Pressure Columns: Buying vs Selling Force
- Positive Green Columns: Net buying pressure
- Negative Red Columns: Net selling pressure
- Color intensity varies based on pressure strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during buying phases
- Low Marker Line (Cyan): Tracks the lowest point reached during selling phases
- Creates visual boundaries showing pressure extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important pressure peaks
- Helps identify potential reversal points and pressure exhaustion
Reference Lines:
- Overbought Level: Threshold for extreme selling pressure
- Oversold Level: Threshold for extreme buying pressure
- Used to identify potential reversal zones
Core Components
1. Volume Pressure Calculation
- Separation of up-volume and down-volume
- Calculation of net volume pressure
- Smoothing for consistent visualization
- Normalization against total volume for percentage scaling
2. Boundary Tracking System
- Automatic detection of highest values in buying phases
- Automatic detection of lowest values in selling phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Threshold Settings
- Extreme threshold multiplier for identifying significant pressure
- Overbought/oversold levels for potential reversals
- Dynamic color coding based on pressure intensity
- Alert conditions for key pressure levels
Main Features
Volume Analysis Settings
- Customizable volume MA length
- Signal smoothing for clearer readings
- Optional log scale for handling wide range variations
- Adjustable threshold multiplier for sensitivity
Visual Elements
- Color-coded columns showing pressure direction and strength
- Dynamic marker lines for pressure boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Overbought/oversold reference lines
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for pressure strength
- Peak formation for potential reversals
- Color changes for pressure direction and intensity
- Alert conditions for extreme pressure levels
Customization Options
- Volume analysis parameters
- Marker line visibility and colors
- Peak marker display options
- Log scale toggle for handling various markets
- Overbought/oversold threshold adjustments
Trading Applications
1. Trend Identification
- Volume pressure crossing above zero: buying pressure emerging
- Volume pressure crossing below zero: selling pressure emerging
- Column color: indicates pressure direction
- Column height: indicates pressure strength
- Signal line: confirms overall trend direction
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Volume pressure approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing pressure
- Readings beyond overbought/oversold levels: potential reversal zones
3. Pressure Analysis
- Breaking above previous high boundary: accelerating buying pressure
- Breaking below previous low boundary: accelerating selling pressure
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Extreme readings: potential climactic buying/selling
4. Market Structure Assessment
- Consecutive higher peaks: strengthening buying structure
- Consecutive lower troughs: strengthening selling structure
- Peak comparisons: relative strength of pressure phases
- Boundary line steps: market structure levels
Optimization Guide
1. Volume Analysis Settings
- Volume MA Length: Default 25 provides balanced signals
- Lower values (10-15): More responsive, potentially noisier
- Higher values (30-50): Smoother, fewer false signals
- Signal Smoothing Length: Default 8 provides good balance
- Lower values: More responsive to pressure changes
- Higher values: Smoother trend identification
2. Threshold Settings
- Extreme Threshold Multiplier: Default 20.0
- Lower values: More signals, potentially more noise
- Higher values: Fewer signals, but more significant
- Overbought/Oversold Levels: Defaults at 20/-20
- Adjust based on instrument volatility
- Wider settings for more volatile instruments
3. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider log scale for instruments with wide volume ranges
4. Alert Settings
- Configure alerts for high buying pressure
- Configure alerts for high selling pressure
- Set additional alerts for zero-line crosses
- Consider timeframe when setting alert sensitivity
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm pressure changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong pressure
- Use with price action for entry/exit precision
- Consider extreme threshold crossings as significant signals
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong buying phase: positive columns breaking above marker line
- Strong selling phase: negative columns breaking below marker line
- Columns approaching zero: potential pressure shift
- Columns beyond overbought/oversold: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with price action oscillators for divergence detection
- Combine with traditional volume indicators for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when volume pressure breaks above previous high marker line
- Enter short when volume pressure breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in buying phases for shorting opportunities
- Look for consecutive higher troughs in selling phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for volume pressure beyond overbought/oversold levels
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme market conditions
4. Volume Color Strategy
- Enter long when columns turn bright green (increasing buying pressure)
- Enter short when columns turn bright red (increasing selling pressure)
- Exit when color intensity fades (decreasing pressure)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Volume pressure crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant buying pressure peaks
Bearish Market Scenario
- Volume pressure crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant selling pressure troughs
Consolidation Scenario
- Volume pressure oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Pressure values remain small
Understanding Market Dynamics Through Market Push Meter
At its core, this indicator provides a unique lens to visualize market pressure through volume analysis:
1. Volume Imbalance: By separating and comparing buying volume (up candles) from selling volume (down candles), the indicator provides insights into which side is exerting more pressure in the market.
2. Normalized Pressure: The indicator normalizes volume pressure as a percentage of total volume, making it more comparable across different market conditions and instruments.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of pressure in both directions, helping to identify when markets are making new pressure extremes.
4. Exhaustion Signals: The peak detection system highlights moments where pressure has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from volume pressure, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences and market
- Consider overall market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
DAMA OSC - Directional Adaptive MA OscillatorOverview:
The DAMA OSC (Directional Adaptive MA Oscillator) is a highly customizable and versatile oscillator that analyzes the delta between two moving averages of your choice. It detects trend progression, regressions, rebound signals, MA cross and critical zone crossovers to provide highly contextual trading information.
Designed for trend-following, reversal timing, and volatility filtering, DAMA OSC adapts to market conditions and highlights actionable signals in real-time.
Features:
Support for 11 custom moving average types (EMA, DEMA, TEMA, ALMA, KAMA, etc.)
Customizable fast & slow MA periods and types
Histogram based on percentage delta between fast and slow MA
Trend direction coloring with “Green”, “Blue”, and “Red” zones
Rebound detection using close or shadow logic
Configurable thresholds: Overbought, Oversold, Underbought, Undersold
Optional filters: rebound validation by candle color or flat-zone filter
Full visual overlay: MA lines, crossover markers, rebound icons
Complete alert system with 16 preconfigured conditions
How It Works:
Histogram Logic:
The histogram measures the percentage difference between the fast and slow MA:
hist_value = ((FastMA - SlowMA) / SlowMA) * 100
Trend State Logic (Green / Blue / Red):
Green_Up = Bullish acceleration
Blue_Up (or Red_Up, depending the display settings) = Bullish deceleration
Blue_Down (or Green_Down, depending the display settings) = Bearish deceleration
Red_Down = Bearish acceleration
Rebound Logic:
A rebound is detected when price:
Crosses back over a selected MA (fast or slow)
After being away for X candles (rebound_backstep)
Optional: filtered by histogram zones or candle color
Inputs:
Display Options:
Show/hide MA lines
Show/hide MA crosses
Show/hide price rebounds
Enable/disable blue deceleration zones
DAMA Settings:
Fast/Slow MA type and length
Source input (close by default)
Overbought/Oversold levels
Underbought/Undersold levels
Rebound Settings:
Use Close and/or Shadow
Rebound MA (Fast/Slow)
Candle color validation
Flat zone filter rebounds (between UnderSold and UnderBought)
Available MA type:
SMA (Simple MA)
EMA (Exponential MA)
DEMA (Double EMA)
TEMA (Triple EMA)
WMA (Weighted MA)
HMA (Hull MA)
VWMA (Volume Weighted MA)
Kijun (Ichimoku Baseline)
ALMA (Arnaud Legoux MA)
KAMA (Kaufman Adaptive MA)
HULLMOD (Modified Hull MA, Same as HMA, tweaked for Pine v6 constraints)
Notes:
**DEMA/TEMA** reduce lag compared to EMA, useful for faster reaction in trending markets.
**KAMA/ALMA** are better suited to noisy or volatile environments (e.g., BTC).
**VWMA** reacts strongly to volume spikes.
**HMA/HULLMOD** are great for visual clarity in fast moves.
Alerts Included (Fully Configurable):
Golden Cross:
Fast MA crosses above Slow MA
Death Cross:
Fast MA crosses below Slow MA
Bullish Rebound:
Rebound from below MA in uptrend
Bearish Rebound:
Rebound from above MA in downtrend
Bull Progression:
Transition into Green_Up with positive delta
Bear Progression:
Transition into Red_Down with negative delta
Bull Regression:
Exit from Red_Down into Blue/Green with negative delta
Bear Regression:
Exit from Green_Up into Blue/Red with positive delta
Crossover Overbought:
Histogram crosses above Overbought
Crossunder Overbought:
Histogram crosses below Overbought
Crossover Oversold:
Histogram crosses above Oversold
Crossunder Oversold:
Histogram crosses below Oversold
Crossover Underbought:
Histogram crosses above Underbought
Crossunder Underbought:
Histogram crosses below Underbought
Crossover Undersold:
Histogram crosses above Undersold
Crossunder Undersold:
Histogram crosses below Undersold
Credits:
Created by Eff_Hash. This code is shared with the TradingView community and full free. do not hesitate to share your best settings and usage.
Market Conditions with RSI v6Market Conditions with RSI Indicator
This indicator combines price action, volume, and RSI (Relative Strength Index) to identify market conditions and generate trading signals.
What It Does
The indicator classifies market conditions into four categories:
1.Strong Bullish: When price is rising, volume is up, and the volume-based "open interest" is increasing
2.Weak Bullish: When price is rising, but volume is down, and the volume-based "open interest" is decreasing
3.Weak Bearish: When price is declining, volume is up, and the volume-based "open interest" is increasing
4.Strong Bearish: When price is declining, volume is down, and the volume-based "open interest" is decreasing
These market conditions are then combined with RSI readings to generate buy and sell signals.
## How to Use It
1. Add the indicator to your TradingView chart
2. The indicator will display below your price chart (since it's not an overlay)
3. Look for buy signals (green triangles at the bottom) and sell signals (red triangles at the top)
4. Use the color-coded background to quickly identify the current market condition
5. Check the information table in the top-right corner for detailed metrics
What It Shows
1. RSI Line: The blue line showing the Relative Strength Index value
2. Background Color:
- Green = Strong Bullish
- Light Green = Weak Bullish
- Orange = Weak Bearish
- Red = Strong Bearish
3. Buy Signals (green triangles) appear when:
- Strong Bullish condition with RSI below 50 (catching momentum early)
- Weak Bearish condition with RSI below 30 (oversold opportunity)
4. Sell Signals (red triangles) appear when:
- Strong Bearish condition with RSI above 50 (catching downward momentum)
- Weak Bullish condition with RSI above 70 (overbought opportunity)
5. Information Table showing:
- Current market condition
- RSI value
- Price direction (rising/declining)
- Volume status (up/down)
- Volume-based "open interest" proxy (up/down)
Customization Options
You can adjust:
- RSI Length (default: 14)
- RSI Overbought Level (default: 70)
- RSI Oversold Level (default: 30)
- Volume Moving Average Length (default: 20)
- "Open Interest" Moving Average Length (default: 20)
Pivot Length Percentiles Oscillator# Pivot Length Percentiles Oscillator: Technical Mechanics Explained
## Introduction
The Pivot Length Percentiles Oscillator is a statistical approach to identifying potential market reversals by analyzing the distribution of price movements relative to pivot points. This publication explains the technical mechanics behind the indicator.
## Core Mechanics
### 1. Pivot Point Detection
The indicator begins by identifying significant pivot highs and lows using a user-defined lookback period:
- `lft`: Number of bars to the left of potential pivot point
- `rht`: Number of bars to the right of potential pivot point
These parameters determine how "significant" a pivot needs to be to qualify for analysis.
### 2. Distance Measurement & Historical Database
For each new pivot point identified, the indicator:
- Calculates the absolute price distance from the previous pivot of the same type
- Records the number of candles between consecutive pivots
- Stores these measurements in dynamic arrays that build a historical database
### 3. Statistical Distribution Analysis
Rather than using fixed values, the oscillator analyzes the complete distribution of historical pivot distances and calculates key percentile values:
- `lw` (Low Percentile): Lower boundary for statistical significance
- `md` (Mid Percentile): Median statistical boundary
- `hi` (High Percentile): Upper boundary for statistical extremes
### 4. Oscillator Construction
Two primary oscillator lines are calculated:
- Green line (`osc1`): Measures current price's fall below recent highs with `low - ta.highest(high, lft)`
- Red line (`osc2`): Measures current price's rise above recent lows with `high - ta.lowest(low, lft)`
### 5. Threshold Generation
The percentile values from the historical distribution create dynamic threshold lines:
- For downside movements: Scaled versions of the low percentile (`lw_distance_low`) and high percentile (`hi_distance_low`)
- For upside movements: Scaled versions of the low percentile (`lw_distance_high`) and high percentile (`hi_distance_high`)
### 6. Signal Logic
Entry signals are generated when:
- **Bullish Signal**: The downside oscillator crosses below a statistical threshold while price continues showing downward momentum (close < previous close AND close < previous open)
- **Bearish Signal**: The upside oscillator crosses above a statistical threshold while price continues showing upward momentum (close > previous close AND close > previous open)
### 7. Visualization Options
Users can toggle between:
- Standard view: Shows the oscillator and threshold lines
- Percentile view: Displays the current movement's percentile rank within the historical distribution
## Implementation Notes
- The indicator scales threshold values by 0.9 to create a slight buffer that reduces false signals
- The movement's continuation is confirmed by checking both close-to-close and close-to-open relationships
- Arrays dynamically update throughout the chart's history, making the indicator increasingly accurate as more data is processed
## Mathematical Framework
The core statistical function calculates percentiles using linear interpolation between values when needed:
```
calculate_percentile(array, percentile) =
sortedValue +
fraction * (sortedValue - sortedValue )
```
where `index = (array.size - 1) * percentile / 100`
This mathematical approach ensures the thresholds adapt dynamically to changing market conditions rather than relying on fixed values.
PARKER Currency Strength with RESETS v 3.00PARKER Currency Strength v3.00 is a comprehensive multi-currency strength indicator designed for Forex traders who want detailed insights into major currency performance. Here are some of its key features:
Customizable Session Resets:
The indicator supports automatic resets of currency strength calculations at the start of each major market session (Sydney, Tokyo, London, and New York). You can also enable a custom reset with a user-defined reset time and name.
User-Defined Market Hours:
With the new "Market Settings" section, you can set the open and close times for each market (Sydney, Tokyo, London, and New York) using hour and minute inputs. This allows you to tailor the session times to your local time zone or trading preferences.
Session Shading and Labels:
The background color of the indicator pane changes based on the active market session. Labels are generated at the start of each session to provide clear visual cues. Market session labels and times are also displayed on the chart for quick reference.
Dual Mode Display:
In addition to the reset-based currency strength calculations, the indicator can plot "normal" (continuous) currency strength lines at 50% transparency, allowing you to compare different calculation methods side by side.
Fully Customizable Appearance:
Customize line colors, widths, and offsets for each currency pair via user inputs, enabling a personalized and clear display that fits your trading style.
This indicator is ideal for Forex traders who require a dynamic and highly customizable tool to monitor currency strength, adapt to different market sessions, and make informed trading decisions based on real-time performance data.
Multi-Signal Trading Indicator (MSTI)Multi-Signal Trading Indicator (MSTI)
Overview
The Multi-Signal Trading Indicator (MSTI) is a comprehensive technical analysis tool that combines eight powerful indicators into a single, unified system. Designed to identify high-probability trading opportunities, MSTI generates precise buy and sell signals by analyzing multiple market factors simultaneously. The indicator excels at detecting potential reversals and trend continuations while filtering out market noise.
Key Features
8 Core Technical Components
MACD: Identifies momentum changes and potential trend reversals
RSI: Detects overbought and oversold conditions
Bollinger Bands: Analyzes price volatility and extreme conditions
Stochastic Oscillator: Identifies potential turning points in price
Moving Averages: Confirms trend direction using dual SMAs
Volume Analysis: Validates price movements with volume confirmation
Fibonacci Levels: Identifies key support/resistance areas
Divergence Detection: Spots divergences between price and momentum
Advanced Predictive Capabilities
Volume Surge Detection: Identifies significant volume increases that often precede major price movements
Enhanced Divergence Analysis: Detects both regular and hidden divergences for early reversal signals
Support/Resistance Tests: Identifies successful tests of key support/resistance zones
Momentum Change Detection: Spots early shifts in price momentum using Rate of Change
Order Flow Analysis: Tracks buying/selling pressure through On-Balance Volume
Signal Quality Management
Adjustable Signal Thresholds: Customize the number of conditions required for signal generation
Multiple Quality Levels: Choose between Normal, High, and Maximum quality settings
Strength Measurement: Displays signal strength as a percentage for better decision-making
Repeat Signal Prevention: Eliminates duplicate signals to reduce noise
Visual Features
Clear Chart Markers: Buy/sell signals displayed directly on price chart
Comprehensive Info Panel: Shows status of all components and overall signal information
Customizable Colors: Adjust visual elements to match your chart theme
Practical Applications
For Day Traders
Identify short-term reversal points with high accuracy
Validate entries with multiple confirmations
Filter out false signals during choppy market conditions
For Swing Traders
Spot early trend changes before they become obvious
Enter positions with higher confidence and precision
Hold positions through noise by following true trend signals
For Position Traders
Identify major trend reversals with multiple confirmations
Filter out minor retracements from significant trend changes
Time entries and exits with greater precision
Customization Options
MSTI is highly customizable with over 30 adjustable parameters allowing you to:
Fine-tune each technical component
Adjust signal quality and filtering
Enable/disable specific components
Customize visual appearance
Usage Tips
Start with the Normal quality setting to understand signal frequency
Progress to High or Maximum settings for fewer but higher quality signals
Adjust minimum conditions based on market volatility
Enable trend filter in trending markets for better signal accuracy
Enable volatility filter to avoid signals during low-volatility periods
Oracle Prediction Futur
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Indicator Description: Oracle Prediction Futur
The Oracle Prediction Futur is a sophisticated technical indicator designed for traders and analysts looking to gain insights into market trends through the analysis of price movements. This Pine Script™ code integrates innovative elements to enhance the trading experience and is governed by the Mozilla Public License 2.0.
Key Features:
Normalization of Closing Prices:
The indicator normalizes closing prices over a defined lookback period (100 periods) to provide a percentage-based representation of the current price relative to its historical range. This helps in identifying potential price extremes.
Peak and Trough Detection:
It identifies and plots peak tops and bottom troughs based on normalized closing values. Peak tops are marked with vibrant magenta circles, while peak bottoms are indicated by soothing cyan circles, helping traders visually spot significant turning points in the price action.
Dynamic Background Gradient:
The indicator features a visually appealing gradient background that represents market sentiment. The background color transitions between bear and bull colors based on the position of the normalized close within the 0-100 range. This provides an immediate visual cue about the strength or weakness of the market.
Horizontal Reference Lines:
The indicator includes horizontal lines at key levels (9.51 and 92.5) for quick reference, which can help to gauge areas of potential support or resistance.
User-Friendly Visuals:
The combination of background colors, dynamic plots, and clear labeling offers a user-friendly visual representation, making it easier to interpret market conditions at a glance.
Overlay Options:
As an overlay-free indicator, it maintains clarity on the price chart while providing insightful trends and forecasts.
Practical Application:
Traders can utilize the Oracle Prediction Futur indicator to identify potential entry and exit points in their trading strategies. By observing the peaks, troughs, and background color shifts, users can better understand market momentum and price action.
How to Use:
Deploy this indicator on your trading platform, and analyze the peaks and troughs along with the normalized close line and background gradient to inform your trading decisions. Look for alignment between price action and the signaling provided by the indicator for optimized trading results.
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
FiveFactorEdgeUses ATR14, TSI, RSI, Fast Stochastic and Slow Stochastic information to determine potential high and low price, trend strength and direction. The information ia easy to read, self-descriptive and color coded for quick reference. Since it incorporates 5 different elements it could be used by itself but as with any indicator it's highly recommended to use it with other tried and true indicators.
OG Trend MeterDescription:
The OG Trend Meter gives you a visual snapshot of multiple timeframe trends in one glance. Built for speed and clarity, it helps confirm direction across key intraday timeframes: 1m, 5m, 15m, and 30m.
How it works:
Each timeframe analyzes EMA alignment, price action, and momentum.
Displays clear green/red indicators for bullish/bearish trends on each timeframe.
Great for aligning trades with higher timeframe bias.
Best for:
Traders who want multi-timeframe confirmation before pulling the trigger.
Reducing fakeouts by staying with the dominant trend.
Scalping with the 1m chart while respecting 5m–30m direction.
Pair With: OG Supertrend or EMA Stack for high-probability confluence.
OG ATR RangeDescription:
The OG ATR Tool is a clean, visualized version of the Average True Range indicator for identifying volatility, stop-loss levels, and realistic price movement expectations.
How it works:
Calculates the average range (in points/pips) of recent candles.
Overlays ATR bands to help define breakout potential or squeeze zones.
Can be used to size trades or set dynamic stop-loss and target levels.
Best for:
Intraday traders who want to avoid unrealistic targets.
Volatility-based setups and breakout strategies.
Creating position sizing rules based on instrument volatility.
Pro Tip: Combine with your trend indicators to set sniper entries and exits that respect volatility.
NBSG Mox-ZThe Mox-Z provides a visual representation of momentum and trend strength, enhanced with statistical bands to identify significant levels based on prior momentum.
What It Does
The indicator calculates the Mox-Z value as (EMA12(close) - EMA26(close)) - EMA9(EMA12(close) - EMA26(close))) * 3 using the higher timeframe's closing prices. This value is plotted as a histogram, with colors indicating its position relative to zero and Z-score bands:
Bright Green: Above +0.7 SD (strong bullish momentum).
Bright Red: Below -0.7 SD (strong bearish momentum).
Dark Green: Above zero but below +0.7 SD (moderate bullish momentum).
Dark Red: Below zero but above -0.7 SD (moderate bearish momentum).
Z-score bands are computed over a 200-period lookback on the higher timeframe, using a 0.7 multiplier on the standard deviation, offering a statistical context for the histogram's values.
How to Use It
Use the histogram to gauge momentum shifts on the selected higher timeframe (e.g., weekly momentum on a daily chart).
Bright colors (green/red) suggest potential overextension or strong trend continuation, useful for timing entries or exits.
Dark colors indicate moderate momentum, often signaling consolidation or early trend development.
The ±0.7 SD bands (gray lines) highlight statistically significant levels, aiding in identifying extremes relative to the past 200 periods of the chosen timeframe.
Originality and Purpose
Unlike standard MACD histograms, this script replicates the Mox-Z Indicator's unique scaling (*3 multiplier) and applies it strictly to higher timeframe data, avoiding current timeframe bias. The addition of Z-score bands provides a statistical edge, making it distinct from typical momentum indicators while maintaining simplicity for practical trading.
Settings
Higher Timeframe: Default is "1W" (weekly), but adjust to any timeframe higher than your chart (e.g., "1D" for daily, "1M" for monthly).
This indicator is ideal for traders seeking a higher timeframe momentum perspective with clear visual cues, without relying on complex multi-indicator setups.
Momentum Volatility Ratio | AlphaNattMomentum Volatility Ratio | AlphaNatt
The Momentum Volatility Ratio (MVR) is a sophisticated indicator that measures price impulses relative to an asset's inherent volatility. Unlike standard momentum indicators, MVR adapts to changing market conditions by normalizing momentum against historical volatility patterns, helping traders identify truly significant price movements.
Key Features:
• Adapts automatically to each asset's volatility profile
• Distinguishes between normal market noise and significant impulses
• Beautiful gradient visualization with modern Quantra-inspired aesthetics
• Responsive and clear signals with minimal lag
• Customizable sensitivity and appearance settings
How It Works:
The MVR calculates normalized price momentum and adjusts it by recent volatility metrics. This volatility-adjustment ensures the indicator remains consistent across different market environments and timeframes. When price momentum exceeds what would be expected given the asset's normal volatility, the indicator shows a significant impulse that traders can act upon.
Indicator Components:
• Cyan Histogram/Background - Represents positive momentum impulses
• Magenta Histogram/Background - Represents negative momentum impulses
• Neutral Bands - Define the transition between normal and significant impulses
• Gradient Background - Provides visual context for impulse strength
• Smooth Histogram - Shows the main impulse signal with a beautiful glow effect
Trading Signals:
1. Strong Positive Impulse - When cyan histogram bars grow significantly above the zero line
2. Strong Negative Impulse - When magenta histogram bars extend significantly below the zero line
3. Impulse Weakening - When histogram bars begin to shrink toward the zero line
4. Momentum Shift - When the histogram changes color, indicating a potential trend change
Customizable Parameters:
• Length - Base calculation period for momentum (default: 6)
• Volatility Lookback - Historical period for volatility calculation (default: 100)
• Neutral Bands Length - Smoothing period for neutral bands (default: 15)
• Neutral Bands Multiplier - Controls width of neutral bands (default: 0.5)
• Standard Deviation Lookback - Period for standard deviation calculation (default: 150)
• Standard Deviation Multiplier - Controls sensitivity of extreme bands (default: 2.5)
• Style - Choose between Classic, Modern, and Signal visualization modes
Best Practices:
• Use MVR alongside price action for confirmation
• Watch for extreme readings followed by momentum shifts
• Pay attention to divergences between price and MVR
• Consider longer-term trends when interpreting signals
• Use shorter settings for more frequent signals, longer settings for less noise
About the Opus Series:
The MVR indicator is part of the Opus series of premium-quality technical indicators designed with both functional excellence and aesthetic beauty. Opus indicators feature smooth gradients, crisp visualization, and powerful analytical capabilities to enhance your trading experience.
For questions, feedback, or custom indicator requests, please feel free to leave a comment or contact me directly.
Happy Trading!
Not financial Advice
QuantJazz Turbine Trader BETA v1.17QuantJazz Turbine Trader BETA v1.17 - Strategy Introduction and User Guide
Strategy Introduction
Welcome to the QuantJazz Turbine Trader BETA v1.17, a comprehensive trading strategy designed for TradingView. This strategy is built upon oscillator principles, drawing inspiration from the Turbo Oscillator by RedRox, and incorporates multiple technical analysis concepts including RSI, MFI, Stochastic oscillators, divergence detection, and an optional FRAMA (Fractal Adaptive Moving Average) filter.
The Turbine Trader aims to provide traders with a flexible toolkit for identifying potential entry and exit points in the market. It presents information through a main signal line oscillator, a histogram, and various visual cues like dots, triangles, and divergence lines directly on the indicator panel. The strategy component allows users to define specific conditions based on these visual signals to trigger automated long or short trades within the TradingView environment.
This guide provides an overview of the strategy's components, settings, and usage. Please remember that this is a BETA version (v1.17). While developed with care, it may contain bugs or behave unexpectedly.
LEGAL DISCLAIMER: QuantJazz makes no claims about the fitness or profitability of this tool. Trading involves significant risk, and you may lose all of your invested capital. All trading decisions made using this strategy are solely at the user's discretion and responsibility. Past performance is not indicative of future results. Always conduct thorough backtesting and risk assessment before deploying any trading strategy with real capital.
This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International.
Core Concepts and Visual Elements
The Turbine Trader indicator displays several components in its own panel below the main price chart:
1. Signal Line (Avg & Avg2): This is the primary oscillator. It's a composite indicator derived from RSI, MFI (Money Flow Index), and Stochastic calculations, smoothed using an EMA (Exponential Moving Average).
Avg: The faster smoothed signal line.
Avg2: The slower smoothed signal line.
Color Coding: The space between Avg and Avg2 is filled. The color (Neon Blue/gColor or Neon Purple/rColor) indicates the trend based on the relationship between Avg and Avg2. Blue suggests bullish momentum (Avg > Avg2), while Purple suggests bearish momentum (Avg2 > Avg).
Zero Line Crosses: Crossovers of the Avg line with the zero level can indicate shifts in momentum.
2. Histogram (resMfi): This histogram is based on smoothed and transformed MFI calculations (Fast MFI and Slow MFI).
Color Coding: Bars are colored Neon Blue (histColorUp) when above zero, suggesting bullish pressure, and Neon Purple (histColorDn) when below zero, suggesting bearish pressure. Transparency is applied.
Zero Line Crosses: Crossovers of the histogram with the zero level can signal potential shifts in money flow.
3. Reversal Points (Dots): Dots appear on the Signal Line (specifically on Avg2) when the color changes (i.e., Avg crosses Avg2).
Small Dots: Appear when a reversal occurs while the oscillator is in an "extreme" zone (below -60 for bullish reversals, above +60 for bearish reversals).
Large Dots: Appear when a reversal occurs outside of these extreme zones.
Colors: Blue (gRdColor) for bullish reversals (Avg crossing above Avg2), Purple (rRdColor) for bearish reversals (Avg crossing below Avg2).
4. Take Profit (TP) Signals (Triangles): Small triangles appear above (+120) or below (-120) the zero line.
Bearish Triangle (Down, Purple rTpColor): Suggests a potential exit point for long positions or an entry point for short positions, based on the oscillator losing upward momentum above the 50 level.
Bullish Triangle (Up, Blue gTpColor): Suggests a potential exit point for short positions or an entry point for long positions, based on the oscillator losing downward momentum below the -50 level.
5. Divergence Lines: The strategy automatically detects and draws potential regular and hidden divergences between the price action (highs/lows) and the Signal Line (Avg).
Regular Bullish Divergence (White bullDivColor line, ⊚︎ label): Price makes a lower low, but the oscillator makes a higher low. Suggests potential bottoming.
Regular Bearish Divergence (White bearDivColor line, ⊚︎ label): Price makes a higher high, but the oscillator makes a lower high. Suggests potential topping.
Hidden Bullish Divergence (bullHidDivColor line, ⊚︎ label): Price makes a higher low, but the oscillator makes a lower low. Suggests potential continuation of an uptrend.
Hidden Bearish Divergence (bearHidDivColor line, ⊚︎ label): Price makes a lower high, but the oscillator makes a higher high. Suggests potential continuation of a downtrend.
Delete Broken Divergence Lines: If enabled, newer divergence lines originating from a similar point will replace older ones.
6. Status Line: A visual bar at the top (95 to 105) and bottom (-95 to -105) of the indicator panel. Its color intensity reflects the confluence of signals:
Score Calculation: +1 if Avg > Avg2, +1 if Avg > 0, +1 if Histogram > 0.
Top Bar (Bullish): Bright Blue (gStatColor) if score is 3, Faded Blue if score is 2, Black otherwise.
Bottom Bar (Bearish): Bright Purple (rStatColor) if score is 0, Faded Purple if score is 1, Black otherwise.
Strategy Settings Explained
The strategy's behavior is controlled via the settings panel (gear icon).
1. Date Range:
Start Date, End Date: Define the period for backtesting. Trades will only occur within this range.
2. Optional Webhook Configuration: (For Automation)
3C Email Token, 3C Bot ID: Enter your 3Commas API credentials if you plan to automate trading using webhooks. The strategy generates JSON alert messages compatible with 3Commas. You can go ahead and just leave the text field as defaulted, "TOKEN HERE" / "BOT ID HERE" if not using any bot automations at this time. You can always come back later and automate it. More info can be made available from QuantJazz should you need automation assistance with custom indicators and trading strategies.
3. 🚀 Signal Line:
Turn On/Off: Show or hide the main signal lines (Avg, Avg2).
gColor, rColor: Set the colors for bullish and bearish signal line states.
Length (RSI): The lookback period for the internal RSI calculation. Default is 2.
Smooth (EMA): The smoothing period for the EMAs applied to the composite signal. Default is 9.
RSI Source: The price source used for RSI calculation (default: close).
4. 📊 Histogram:
Turn On/Off: Show or hide the histogram.
histColorUp, histColorDn: Set the colors for positive and negative histogram bars.
Length (MFI): The base lookback period for MFI calculations. Default is 5. Fast and Slow MFI lengths are derived from this.
Smooth: Smoothing period for the final histogram output. Default is 1 (minimal smoothing).
5.💡 Other:
Show Divergence Line: Toggle visibility of regular divergence lines.
bullDivColor, bearDivColor: Colors for regular divergence lines.
Show Hidden Divergence: Toggle visibility of hidden divergence lines.
bullHidDivColor, bearHidDivColor: Colors for hidden divergence lines.
Show Status Line: Toggle visibility of the top/bottom status bars.
gStatColor, rStatColor: Colors for the status line bars.
Show TP Signal: Toggle visibility of the TP triangles.
gTpColor, rTpColor: Colors for the TP triangles.
Show Reversal points: Toggle visibility of the small/large dots on the signal line.
gRdColor, rRdColor: Colors for the reversal dots.
Delete Broken Divergence Lines: Enable/disable automatic cleanup of older divergence lines.
6. ⚙️ Strategy Inputs: (CRITICAL for Trade Logic)
This section defines which visual signals trigger trades. Each signal (Small/Large Dots, TP Triangles, Bright Bars, Signal/Histogram Crosses, Signal/Histogram Max/Min, Divergences) has a dropdown menu:
Long: This signal can trigger a long entry.
Short: This signal can trigger a short entry.
Disabled: This signal will not trigger any entry.
Must Be True Checkbox: If checked for a specific signal, that signal's condition must be met for any trade (long or short, depending on the dropdown selection for that signal) to be considered. Multiple "Must Be True" conditions act as AND logic – all must be true simultaneously.
How it Works:
The strategy first checks if all conditions marked as "Must Be True" (for the relevant trade direction - long or short) are met.
If all "Must Be True" conditions are met, it then checks if at least one of the conditions not marked as "Must Be True" (and set to "Long" or "Short" respectively) is also met.
If both steps pass, and other filters (like Date Range, FRAMA) allow, an entry order is placed.
Example: If "Large Bullish Dot" is set to "Long" and "Must Be True" is checked, AND "Bullish Divergence" is set to "Long" but "Must Be True" is not checked: A long entry requires BOTH the Large Bullish Dot AND the Bullish Divergence to occur simultaneously. If "Large Bullish Dot" was "Long" but not "Must Be True", then EITHER a Large Bullish Dot OR a Bullish Divergence could trigger a long entry (assuming no other "Must Be True" conditions are active).
Note: By default, the strategy is configured for long-only trades (strategy.risk.allow_entry_in(strategy.direction.long)). To enable short trades, you would need to comment out or remove this line in the Pine Script code and configure the "Strategy Inputs" accordingly.
7. 💰 Take Profit Settings:
Take Profit 1/2/3 (%): The percentage above the entry price (for longs) or below (for shorts) where each TP level is set. (e.g., 1.0 means 1% profit).
TP1/2/3 Percentage: The percentage of the currently open position to close when the corresponding TP level is hit. The percentages should ideally sum to 100% if you intend to close the entire position across the TPs.
Trailing Stop (%): The percentage below the highest high (for longs) or above the lowest low (for shorts) reached after the activation threshold, where the stop loss will trail.
Trailing Stop Activation (%): The minimum profit percentage the trade must reach before the trailing stop becomes active.
Re-entry Delay (Bars): The minimum number of bars to wait after a TP is hit before considering a re-entry. Default is 1 (allows immediate re-entry on the next bar if conditions met).
Re-entry Price Offset (%): The percentage the price must move beyond the previous TP level before a re-entry is allowed. This prevents immediate re-entry if the price hovers around the TP level.
8. 📈 FRAMA Filter: (Optional Trend Filter)
Use FRAMA Filter: Enable or disable the filter.
FRAMA Source, FRAMA Period, FRAMA Fast MA, FRAMA Slow MA: Parameters for the FRAMA calculation. Defaults provided are common starting points.
FRAMA Filter Type:
FRAMA > previous bars: Allows trades only if FRAMA is significantly above its recent average (defined by FRAMA Percentage and FRAMA Lookback). Typically used to confirm strong upward trends for longs.
FRAMA < price: Allows trades only if FRAMA is below the current price (framaSource). Can act as a baseline trend filter.
FRAMA Percentage (X), FRAMA Lookback (Y): Used only for the FRAMA > previous bars filter type.
How it Affects Trades: If Use FRAMA Filter is enabled:
Long entries require the FRAMA filter condition to be true.
Short entries require the FRAMA filter condition to be false (as currently coded, this acts as an inverse filter for shorts if enabled).
How to Use the Strategy
1. Apply to Chart: Open your desired chart on TradingView. Click "Indicators", find "QuantJazz Turbine Trader BETA v1.17" (you might need to add it via Invite-only scripts or if published publicly), and add it to your chart. The oscillator appears below the price chart, and the strategy tester panel opens at the bottom.
2. Configure Strategy Properties: In the Pine Script code itself (or potentially via the UI if supported), adjust the strategy() function parameters like initial_capital, default_qty_value, commission_value, slippage, etc., to match your account, broker fees, and risk settings. The user preferences provided (e.g., 1000 initial capital, 0.1% commission) are examples. Remember use_bar_magnifier is false by default in v1.17.
3. Configure Inputs (Settings Panel):
Set the Date Range for backtesting.
Crucially, configure the ⚙️ Strategy Inputs. Decide which signals should trigger entries and whether they are mandatory ("Must Be True"). Start simply, perhaps enabling only one or two signals initially, and test thoroughly. Remember the default long-only setting unless you modify the code.
Set up your 💰 Take Profit Settings, including TP levels, position size percentages for each TP, and the trailing stop parameters. Decide if you want to use the re-entry feature.
Decide whether to use the 📈 FRAMA Filter and configure its parameters if enabled.
Adjust visual elements (🚀 Signal Line, 📊 Histogram, 💡 Other) as needed for clarity.
4. Backtest: Use the Strategy Tester panel in TradingView. Analyze the performance metrics (Net Profit, Max Drawdown, Profit Factor, Win Rate, Trade List) across different assets, timeframes, and setting configurations. Pay close attention to how different "Strategy Inputs" combinations perform.
5. Refine: Based on backtesting results, adjust the input settings, TP/SL strategy, and signal combinations to optimize performance for your chosen market and timeframe, while being mindful of overfitting.
6. Automation (Optional): If using 3Commas or a similar platform:
Enter your 3C Email Token and 3C Bot ID in the settings.
Create alerts in TradingView (right-click on the chart or use the Alert panel).
Set the Condition to "QuantJazz Turbine Trader BETA v1.17".
In the "Message" box, paste the corresponding placeholder, which will pass the message in JSON from our custom code to TradingView to pass through your webhook: {{strategy.order.alert_message}}.
In the next tab, configure the Webhook URL provided by your automation platform. Put a Whale sound, while you're at it! 🐳
When an alert triggers, TradingView will send the pre-formatted JSON message from the strategy code to your webhook URL.
Final Notes
The QuantJazz Turbine Trader BETA v1.17 offers a wide range of customizable signals and strategy logic. Its effectiveness heavily depends on proper configuration and thorough backtesting specific to the traded asset and timeframe. Start with the default settings, understand each component, and methodically test different combinations of signals and parameters. Remember the inherent risks of trading and never invest capital you cannot afford to lose.
[blackcat] L2 Gradient RSIVWAPOVERVIEW
The L2 Gradient RSIVWAP indicator offers traders a powerful tool for assessing market conditions by combining Relative Strength Index (RSI) with Volume Weighted Average Price (VWAP). It features dynamic coloring and clear buy/sell signals to enhance decision-making.
Customizable Inputs: Adjust key parameters such as RSI-VWAP length, oversold/overbought levels, and smoothing period.
Gradient Color Visualization: Provides intuitive gradient coloring to represent RSI-VWAP values.
Buy/Sell Indicators: On-chart labels highlight potential buying and selling opportunities.
Transparent Fills: Visually distinguishes overbought and oversold zones without obscuring other data.
Access the TradingView platform and select the chart where you wish to implement the indicator.
Go to “Indicators” in the toolbar and search for “ L2 Gradient RSIVWAP.”
Click “Add to Chart” to integrate the indicator into your chart.
Customize settings via the input options:
Toggle between standard RSI and RSI-based VWAP.
Set preferred lengths and thresholds for RSI-VWAP calculations.
Configure the smoothing period for ALMA.
Performance can vary based on asset characteristics like liquidity and volatility.
Historical backtests do not predict future market behavior accurately.
The ALMA function, developed by Arnaud Legoux, enhances response times relative to simple moving averages.
Buy and sell signals are derived from RSI-VWAP crossovers; consider additional factors before making trades.
Special thanks to Arnaud Legoux for creating the ALMA function.
Power Struggle [GOODY]📊 Power Struggle – Gauge the Battle Between Bulls & Bears
"Power Struggle " is an advanced, multi-layered market strength and momentum analysis tool. It combines the classic Elder Impulse System and Elder-Ray Power Columns with modern enhancements like visual gauges, momentum shift alerts, and volume-based divergence detection — all in one clean and intuitive interface.
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🧠 What This Indicator Shows You:
✅ Bull vs Bear Power Columns
• Visualize who’s in control with clean columns showing Bull and Bear dominance.
• Fully integrated with EMA-based Impulse logic to detect trend conviction.
✅ Buy/Sell Signal Labels & Alerts
• Trend-following signals based on dynamic power thresholds.
• Green = Bull Confirmed | Red = Bear Confirmed
• Alerts included for all signal and divergence conditions.
✅ Dynamic Volume Gauge (Horizontal or Vertical)
• A powerful gauge showing real-time buyer/seller strength.
• Includes divergence detection when volume and price disagree, often a warning sign.
• 🔄 Fully customizable layout, position, flip, rotation, and gradient styling.
✅ Active Column Gauge
• Tracks real-time momentum shifts within each candle.
• Highlights power shifts with emoji markers (🐂/🐻), and calculates where price closes within each candle's range.
✅ Volume-in-Candle Labels (Optional)
• See raw Buy vs Sell volume numbers inside the candles.
• Easily spot if price moves are supported by actual volume.
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⚙️ Customizable Settings
• 🎚️ Set thresholds for signal strictness
• 🔔 Use built-in alerts for:
o Bullish/Bearish Impulse
o Bull/Bear Power Thresholds
o Bullish/Bearish Divergences
o Momentum Shifts
Smart MACD Reversal Oscillator Pro [TradeDots]The TradeDots Smart MACD Reversal Oscillator Pro is an advanced technical analysis tool that combines traditional MACD functionality with multi-layered signal detection and divergence identification systems. This comprehensive oscillator helps traders identify potential market reversals, trend continuations, and extremes with greater precision than conventional indicators.
📝 HOW IT WORKS
Accumulation & Distribution Detection System
The indicator begins with a proprietary calculation that identifies potential accumulation and distribution phases:
Calculation: Processes EMA differentials with specific time constants to detect underlying accumulation/distribution pressure
Visualization: Green-filled areas indicate accumulation phases (bullish pressure building) while red-filled areas show distribution phases (bearish pressure building)
Significance: This system often identifies trend reversals before traditional indicators by detecting institutional buying/selling activity
Multi-Timeframe MACD Implementation
Unlike traditional MACD indicators that use a single timeframe, this oscillator incorporates multiple calculation methods:
1. Primary Oscillator: Uses a proprietary calculation that combines price extremes with smoothed averages:
Implements specialized moving average types (SMMA and ZLEMA)
Generates a histogram that changes color based on price position relative to these averages
Produces a signal line that identifies crossover opportunities
2. Secondary MACD: Traditional MACD implementation with customizable parameters:
User-selectable MA types (SMA/EMA) for both oscillator and signal line
Color-coded histogram for momentum visualization
Separate crossover detection system
Dynamic Band System
The indicator implements an innovative dynamic band system to identify overbought and oversold conditions:
Band Calculation: Analyzes historical oscillator values to establish statistically significant extremes
Adaptive Scaling: Automatically adjusts to different market volatility regimes using a customizable Y-axis scale factor
Signal Integration: Incorporates band levels into signal generation for higher-probability trades
Signal Generation System
Four distinct signal types are generated to identify potential trading opportunities:
Green Dots: Bullish crossover signals (primary oscillator crosses above signal line)
Red Dots: Bearish crossover signals (primary oscillator crosses below signal line)
Blue Dots: Secondary MACD bullish crossovers in oversold territory
Orange Dots: Secondary MACD bearish crossovers in overbought territory
Advanced Divergence Detection
The oscillator incorporates a sophisticated divergence detection system:
Regular Divergences: Identifies when price makes lower lows while the oscillator makes higher lows (bullish) or price makes higher highs while the oscillator makes lower highs (bearish)
Hidden Divergences: Optional detection of continuation patterns (currently disabled by default)
Visual Markers: Clear labels identifying divergence formations directly on the chart
Zero-Line Filter: Optional filtering to only detect divergences that don't cross the zero line
🛠️ HOW TO USE
Signal Interpretation
Momentum Direction
Histogram Color: Green shades indicate bullish momentum, red shades indicate bearish momentum
Oscillator Position: Above zero indicates bullish momentum, below zero indicates bearish momentum
Filled Background: Green fill shows accumulation phases, red fill shows distribution phases
Buy Signals (In Order of Strength)
Bullish Divergence + Green Dot: Highest probability reversal signal (price making lower lows while oscillator makes higher lows, followed by crossover)
Green Dot Below Short Average Line: Strong oversold reversal signal
Green Dot + Blue Dot Alignment: Multiple indicator confirmation
Green Dot During Green Fill Expansion: Trend continuation signal
Sell Signals (In Order of Strength)
Bearish Divergence + Red Dot: Highest probability reversal signal (price making higher highs while oscillator makes lower highs, followed by crossover)
Red Dot Above Long Average Line: Strong overbought reversal signal
Red Dot + Orange Dot Alignment: Multiple indicator confirmation
Red Dot During Red Fill Expansion: Trend continuation signal
Trading Strategies
Divergence Trading Strategy
Identify "Bullish" or "Bearish" divergence labels on the chart
Wait for confirming dot signal in the same direction
Enter when both divergence and dot signal align
Set stops based on recent swing points
Target the opposite band or previous significant level
Overbought/Oversold Reversal Strategy
Wait for the oscillator to reach extreme bands (Long or Short Average lines)
Look for crossover signals at these extreme levels:
Bullish Crossover (Oversold): Green dots when oscillator is below Short Average
Bearish Crossover (Overbought): Red dots when oscillator is above Long Average
Enter when price confirms the reversal
Set stops beyond the recent extreme
Target the opposite band or at least the zero line
Multi-Confirmation Strategy
For highest probability trades, look for:
Multiple signal types aligning (e.g., Green + Blue dots or Red + Orange dots)
Signals occurring at band extremes
Divergence patterns reinforcing the signal direction
Background fill color supporting the signal (green fill for buys, red fill for sells)
⚙️ CUSTOMIZATION OPTIONS
The indicator offers extensive customization to adapt to different markets and trading styles:
Y-axis scale factor: Controls the band range multiplier (default 2.5)
Parameter 1: Controls the smoothing period for main calculations (default 8)
Parameter 2: Controls the signal line calculation period (default 9)
Fast/Slow Length: Controls traditional MACD calculation periods (12/26)
Oscillator MA Type: Selection between SMA and EMA for main oscillator
Signal Line MA Type: Selection between SMA and EMA for signal line
Divergence Settings: Customizable lookback parameters and display options
Don't touch the zero line?: Toggle option for divergence filtering
❗️LIMITATIONS
Signal Lag: The system identifies reversals after they have begun, potentially missing the absolute bottom or top
False Signals: Can occur during periods of high volatility or during ranging markets
Divergence Validation: Not all divergences lead to reversals; confirmation is essential
Timeframe Sensitivity: The indicator works best on intermediate timeframes (15m to 4h) for most markets
Bar Closing Requirement: All signals are based on closed candles and may be subject to change until the candle closes
RISK DISCLAIMER
Trading involves substantial risk, and most traders may incur losses. All content, tools, scripts, articles, and education provided by TradeDots are for informational and educational purposes only. Past performance is not indicative of future results.
This oscillator should be used as part of a complete trading approach that includes proper risk management, consideration of the broader market context, and confirmation from price action patterns. No trading system can guarantee profits, and users should always exercise caution and use appropriate position sizing.
Adaptive KDJ (MTF)Hey guys,
this is an adaptive MTF KDJ oscillator.
Pick up to 3 different timeframes, choose a weighting if you want and enjoy the beautiful signals it will show you.
The length of every timeframe is adaptive and based of the timeframe's ATR.
The plot shows the smoothed average of the 3 KDJ values.
Large triangles show KDJ crossings.
Small triangles show anticipations of possible crossings.
I found out it works best with 1m, 5m, 15m and weighting=1 for forex scalping in 1m.
Use other indicators for confluence.
Bitcoin Polynomial Regression ModelThis is the main version of the script. Click here for the Oscillator part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines. The Oscillator version can be found here.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
