Trend Strength Matrix [JOAT]
Trend Strength Matrix — Multi-Timeframe Trend Health Dashboard
Trend Strength Matrix provides a comprehensive view of trend health across multiple timeframes and indicators. It combines RSI, MACD, ADX, and moving average alignment into a single heatmap-style dashboard with an overall strength score—giving you a complete picture of trend quality at a glance.
What Makes This Indicator Unique
Unlike single-indicator trend tools, Trend Strength Matrix:
Analyzes four different indicators simultaneously (RSI, MACD, ADX, MA)
Evaluates up to four timeframes at once for multi-timeframe confluence
Presents everything in an intuitive color-coded heatmap
Calculates a weighted composite score for overall trend assessment
Marks trend shifts directly on the chart
What This Indicator Does
Calculates trend scores from four different indicators
Analyzes up to four timeframes simultaneously
Creates a color-coded heatmap showing strength across all components
Generates a weighted composite score for overall trend assessment
Marks bullish and bearish trend shifts on the chart
Displays a trend-following moving average on the price chart
Component Scores Explained
Each indicator contributes a normalized score from -1 (strongly bearish) to +1 (strongly bullish):
RSI Score — (RSI - 50) / 50
- RSI of 70 = +0.4 (bullish)
- RSI of 30 = -0.4 (bearish)
- RSI of 50 = 0 (neutral)
MACD Score — MACD line normalized by its standard deviation
- Positive MACD = positive score
- Negative MACD = negative score
- Magnitude reflects strength
ADX Score — ADX strength multiplied by DI direction
- High ADX with DI+ > DI- = strong positive
- High ADX with DI- > DI+ = strong negative
- Low ADX = weak score regardless of direction
MA Score — Price position relative to moving average
- Price above MA = positive
- Price below MA = negative
- Distance from MA affects magnitude
Multi-Timeframe Analysis
The indicator analyzes multiple timeframes with weighted importance:
// Weighted MTF composite score
mtfScore = composite1 * 0.40 + // Current TF (40% weight)
composite2 * 0.25 + // TF2, e.g., 1H (25% weight)
composite3 * 0.20 + // TF3, e.g., 4H (20% weight)
composite4 * 0.15 // TF4, e.g., Daily (15% weight)
Higher timeframes provide context and trend direction, while lower timeframes provide timing and entry signals.
Dashboard Layout
The matrix displays a grid with:
Rows — Each timeframe (current, TF2, TF3, TF4)
Columns — Each indicator (RSI, MACD, ADX, MA, Score)
Cell Colors :
- Bright green: Score > 0.5 (strongly bullish)
- Faded green: Score 0.2 to 0.5 (moderately bullish)
- Gray: Score -0.2 to 0.2 (neutral)
- Faded red: Score -0.5 to -0.2 (moderately bearish)
- Bright red: Score < -0.5 (strongly bearish)
Overall Row — Shows weighted composite with trend classification
Trend Classifications
Based on the overall MTF score:
STRONG BULL — Score > 50%
BULLISH — Score 20% to 50%
NEUTRAL — Score -20% to 20%
BEARISH — Score -50% to -20%
STRONG BEAR — Score < -50%
Visual Features
Trend Moving Average — Optional MA line on price chart colored by trend direction
Trend Background — Subtle background tint showing overall trend direction
Trend Shift Labels — "BULL" and "BEAR" labels when trend direction changes
Heatmap Dashboard — Color-coded matrix showing all components and timeframes
Color Scheme
Bullish Color — Default: #00E676 (bright green)
Bearish Color — Default: #FF5252 (red)
Neutral Color — Default: #9E9E9E (gray)
Dashboard Header — #2962FF (blue)
Inputs Overview
Calculation Settings:
RSI Length — Period for RSI (default: 14, range: 5-30)
MACD Fast — Fast EMA period (default: 12, range: 5-30)
MACD Slow — Slow EMA period (default: 26, range: 10-50)
MACD Signal — Signal line period (default: 9, range: 3-20)
ADX Length — Period for ADX/DI (default: 14, range: 5-30)
MA Length — Period for trend MA (default: 50, range: 20-200)
Multi-Timeframe:
Enable Multi-Timeframe — Toggle MTF analysis (default: on)
Timeframe 2 — Second timeframe (default: 60 = 1 hour)
Timeframe 3 — Third timeframe (default: 240 = 4 hours)
Timeframe 4 — Fourth timeframe (default: D = Daily)
Visual Settings:
Bullish/Bearish/Neutral Colors — Customizable color scheme
Show Trend MA — Toggle moving average on price chart
Show Dashboard — Toggle the heatmap matrix
Dashboard Position — Choose corner placement (Top Right, Top Left, Bottom Right, Bottom Left)
How to Use It
For Trend Confirmation:
All green cells = strong bullish alignment across indicators and timeframes
All red cells = strong bearish alignment
Mixed colors = consolidation or transition period
Wait for alignment before entering trend trades
For Multi-Timeframe Analysis:
Higher timeframes (TF3, TF4) show the "big picture" trend
Lower timeframes (current, TF2) show immediate momentum
Best signals occur when all timeframes align
Divergence between timeframes suggests caution
For Entry Timing:
Enter when trend shifts from neutral to bullish/bearish
Look for "BULL" or "BEAR" labels on chart
Confirm with dashboard showing alignment
Use the trend MA as a trailing stop reference
Alerts Available
TSM Bullish Shift — Trend shifted from neutral/bearish to bullish
TSM Bearish Shift — Trend shifted from neutral/bullish to bearish
TSM Strong Bull — Score crossed above 50% (strong bullish)
TSM Strong Bear — Score crossed below -50% (strong bearish)
Best Practices
Wait for multiple timeframes to align before entering
Strong trends show green (or red) across all cells
Mixed colors suggest waiting for clarity
Use the overall score percentage to gauge conviction
— Made with passion by officialjackofalltrades
Trendingideas
Parsifal.Swing.TrendScoreThe Parsifal.Swing.TrendScore indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
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Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
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The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
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The Parsifal.Swing.TrendScore – Specifics
The Parsifal.Swing.TrendScore module combines short-term trend data with information about the current swing state, derived from raw price data and classical technical indicators. It provides an indication of how well the short-term trend aligns with the prevailing swing, based on recent market behavior.
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How Swing.TrendScore Works
The Swing.TrendScore calculates a swing score by collecting data within a bin (i.e., a single candle or time bucket) that signals an upside or downside swing. These signals are then aggregated together with insights from classical swing indicators.
Additionally, it calculates a short-term trend score using core technical signals, including:
• The Z-score of the price's distance from various EMAs
• The slope of EMAs
• Other trend-strength signals from additional technical indicators
These two components—the swing score and the trend score—are then combined to form the Swing.TrendScore indicator, which evaluates the short-term trend in context with swing behavior.
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How to Interpret Swing.TrendScore
The trend component enhances Swing.TrendScore’s ability to provide stronger signals when the short-term trend and swing state align.
It can also override the swing score; for example, even if a mean reversion appears to be forming, a dominant short-term trend may still control the market behavior.
This makes Swing.TrendScore particularly valuable for:
• Short-term trend-following strategies
• Medium-term swing trading
Unlike typical swing indicators, Swing.TrendScore is designed to respond more to medium-term swings rather than short-lived fluctuations.
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Behavior and Chart Representation
The Swing.TrendScore indicator fluctuates within a range, as most of its components are range-bound (though Z-score components may technically extend beyond).
• Historically high or low values may suggest overbought or oversold conditions
• The chart displays:
o A fast curve (orange)
o A slow curve (white)
o A shaded background representing the market state
• Extreme values followed by curve reversals may signal a developing mean reversion
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TrendScore Background Value
The Background Value reflects the combined state of the short-term trend and swing:
• > 0 (shaded green) → Bullish mode: swing and short-term trend both upward
• < 0 (shaded red) → Bearish mode: swing and short-term trend both downward
• The absolute value represents the confidence level in the market mode
Notably, the Background Value can remain positive during short downswings if the short-term trend remains bullish—and vice versa.
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How to Use the Parsifal.Swing.TrendScore
Several change points can act as entry triggers or aids:
• Fast Trigger: change in slope of the fast signal curve
• Trigger: fast line crosses slow line or the slope of the slow signal changes
• Slow Trigger: change in sign of the Background Value
Examples of these trigger points are illustrated in the accompanying chart.
Additionally, market highs and lows aligning with the swing indicator values may serve as pivot points in the evolving price process.
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As always, this indicator should be used in conjunction with other tools and market context in live trading.
While it provides valuable insight and potential entry points, it does not predict future price action.
Instead, it reflects recent tendencies and should be used judiciously.
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Extensions
The aggregation of information—whether derived from bins or technical indicators—is currently performed via simple averaging. However, this can be modified using alternative weighting schemes, based on:
• Historical performance
• Relevance of the data
• Specific market conditions
Smoothing periods used in calculations are also modifiable. In general, the EMAs applied for smoothing can be extended to reflect expectations based on relevance-weighted probability measures.
Since EMAs inherently give more weight to recent data, this allows for adaptive smoothing.
Additionally, EMAs may be further extended to incorporate negative weights, akin to wavelet transform techniques.

