EMA Ribbon with TableThis indicator plots multiple EMAs (5, 8, 13, 21, 34, 55, 89, 144, 233, 377) based on Fibonacci levels. Each line has a distinct color, and a clean table displays their real-time values. Great for spotting trend direction, crossovers, and momentum at a glance.
Cari dalam skrip untuk "89年属蛇运势"
Staccked SMA - Regime Switching & Persistance StatisticsThis indicator is designed to identify the prevailing market regime by analyzing the behavior of a "stack" of Simple Moving Averages (SMAs). It helps you understand whether the market is currently trending, mean-reverting, or moving randomly.
Core Concept: SMA Correlation
At its heart, the indicator examines the relationship between a set of nine SMAs with different lengths (3, 5, 8, 13, 21, 34, 55, 89, 144) and the lengths themselves.
In a strong trending market (either up or down), the SMAs will be neatly "stacked" in order of their length. The shortest SMA will be furthest from the longest SMA, creating a strong, almost linear visual pattern. When we measure the statistical correlation between the SMA values and their corresponding lengths, we get a value close to +1 (perfect uptrend stack) or -1 (perfect downtrend stack). The absolute value of this correlation will be very high (close to 1).
In a mean-reverting or sideways market, the SMAs will be tangled and crisscrossing each other. There is no clear order, and the relationship between an SMA's length and its price value is weak. The correlation will be close to 0.
This indicator calculates this Pearson correlation on every bar, giving a continuous measure of how ordered or "trendy" the SMAs are. An absolute correlation above 0.8 is considered strongly trending, while a value between 0.4 and 0.8 suggests a mean-reverting character. Below 0.4, the market is likely random or choppy.
Regime Classification and Statistics
The indicator doesn't just look at the current correlation; it analyzes its behavior over a user-defined lookback window (default is 252 bars) to classify the overall market "regime."
It presents its findings in a clear table:
📊 |SMA Correlation| Regime Table: This main table provides a snapshot of the current market character.
Median: Shows the median absolute correlation over the lookback period, giving a central tendency of the market's behavior.
% > 0.80: The percentage of time the market was in a strong trend during the lookback period.
% < 0.80 & > 0.40: The percentage of time the market showed mean-reverting characteristics.
🧠 Regime: The final classification. It's labeled "📈 Trend-Dominant" if the median correlation is high and it has spent a significant portion of the time trending. It's labeled "🔄 Mean-Reverting" if the median is in the middle range and it has spent significant time in that state. Otherwise, it's considered "⚖️ Random/ Choppy".
📐 Regime Significance: This tells you how statistically confident you can be in the current regime classification, using a Z-score to compare its occurrence against random chance. ⭐⭐⭐ indicates high confidence (99%), while "❌ Not Significant" means the pattern could be random.
Regime Transition Probabilities
Optionally, a second table can be displayed that shows the historical probability of the market transitioning from one regime to another over different time horizons (t+5, t+10, t+15, and t+20 bars).
📈 → 🔄 → ⚖️ Transition Table: This table answers questions like, "If the market is trending now (From: 📈), what is the probability it will be mean-reverting (→ 🔄) in 10 bars?"
This provides powerful insights into the market's cyclical nature, helping you anticipate future behavior based on past patterns. For example, you might find that after a period of strong trending, a transition to a choppy state is more likely than a direct switch to a mean-reverting
Indicator Settings
Lookback Window for Regime Classification: This sets the number of recent bars (default is 252) the script analyzes to determine the current market regime (Trending, Mean-Reverting, or Random). A larger number provides a more stable, long-term view, while a smaller number makes the classification more sensitive to recent price action.
Show Regime Transition Table: A simple toggle (on/off) to show or hide the table that displays the probabilities of the market switching from one regime to another.
Lookback Offset for Starting Regime: This determines the "starting point" in the past for calculating regime transitions. The default is 20 bars ago. The script looks at the regime at this point and then checks what it became at later points.
Step 1, 2, 3, 4 Offset (bars): These define the future time intervals (5, 10, 15, and 20 bars by default) for the transition probability table. For example, the script checks the regime at the "Lookback Offset" and then sees what it transitioned to 5, 10, 15, and 20 bars later.
Significance Filter Settings
Use Regime Significance Filter: When enabled, this filter ensures that the regime transition statistics only count transitions that were "statistically significant." This helps to filter out noise and focus on more reliable patterns.
Min Stars Required (1=90%, 2=95%, 3=99%): This sets the minimum confidence level required for a regime to be included in the transition statistics when the significance filter is on.
1 ⭐: Requires at least 90% confidence.
2 ⭐⭐: Requires at least 95% confidence (default).
3 ⭐⭐⭐: Requires at least 99% confidence.
Mandelbrot-Fibonacci Cascade Vortex (MFCV)Mandelbrot-Fibonacci Cascade Vortex (MFCV) - Where Chaos Theory Meets Sacred Geometry
A Revolutionary Synthesis of Fractal Mathematics and Golden Ratio Dynamics
What began as an exploration into Benoit Mandelbrot's fractal market hypothesis and the mysterious appearance of Fibonacci sequences in nature has culminated in a groundbreaking indicator that reveals the hidden mathematical structure underlying market movements. This indicator represents months of research into chaos theory, fractal geometry, and the golden ratio's manifestation in financial markets.
The Theoretical Foundation
Mandelbrot's Fractal Market Hypothesis Traditional efficient market theory assumes normal distributions and random walks. Mandelbrot proved markets are fractal - self-similar patterns repeating across all timeframes with power-law distributions. The MFCV implements this through:
Hurst Exponent Calculation: H = log(R/S) / log(n/2)
Where:
R = Range of cumulative deviations
S = Standard deviation
n = Period length
This measures market memory:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting (anti-persistent) behavior
Fractal Dimension: D = 2 - H
This quantifies market complexity, where higher dimensions indicate more chaotic behavior.
Fibonacci Vortex Theory Markets don't move linearly - they spiral. The MFCV reveals these spirals using Fibonacci sequences:
Vortex Calculation: Vortex(n) = Price + sin(bar_index × φ / Fn) × ATR(Fn) × Volume_Factor
Where:
φ = 0.618 (golden ratio)
Fn = Fibonacci number (8, 13, 21, 34, 55)
Volume_Factor = 1 + (Volume/SMA(Volume,50) - 1) × 0.5
This creates oscillating spirals that contract and expand with market energy.
The Volatility Cascade System
Markets exhibit volatility clustering - Mandelbrot's "Noah Effect." The MFCV captures this through cascading volatility bands:
Cascade Level Calculation: Level(i) = ATR(20) × φ^i
Each level represents a different fractal scale, creating a multi-dimensional view of market structure. The golden ratio spacing ensures harmonic resonance between levels.
Implementation Architecture
Core Components:
Fractal Analysis Engine
Calculates Hurst exponent over user-defined periods
Derives fractal dimension for complexity measurement
Identifies market regime (trending/ranging/chaotic)
Fibonacci Vortex Generator
Creates 5 independent spiral oscillators
Each spiral follows a Fibonacci period
Volume amplification creates dynamic response
Cascade Band System
Up to 8 volatility levels
Golden ratio expansion between levels
Dynamic coloring based on fractal state
Confluence Detection
Identifies convergence of vortex and cascade levels
Highlights high-probability reversal zones
Real-time confluence strength calculation
Signal Generation Logic
The MFCV generates two primary signal types:
Fractal Signals: Generated when:
Hurst > 0.65 (strong trend) AND volatility expanding
Hurst < 0.35 (mean reversion) AND RSI < 35
Trend strength > 0.4 AND vortex alignment
Cascade Signals: Triggered by:
RSI > 60 AND price > SMA(50) AND bearish vortex
RSI < 40 AND price < SMA(50) AND bullish vortex
Volatility expansion AND trend strength > 0.3
Both signals implement a 15-bar cooldown to prevent overtrading.
Advanced Input System
Mandelbrot Parameters:
Cascade Levels (3-8):
Controls number of volatility bands
Crypto: 5-7 (high volatility)
Indices: 4-5 (moderate volatility)
Forex: 3-4 (low volatility)
Hurst Period (20-200):
Lookback for fractal calculation
Scalping: 20-50
Day Trading: 50-100
Swing Trading: 100-150
Position Trading: 150-200
Cascade Ratio (1.0-3.0):
Band width multiplier
1.618: Golden ratio (default)
Higher values for trending markets
Lower values for ranging markets
Fractal Memory (21-233):
Fibonacci retracement lookback
Uses Fibonacci numbers for harmonic alignment
Fibonacci Vortex Settings:
Spiral Periods:
Comma-separated Fibonacci sequence
Fast: "5,8,13,21,34" (scalping)
Standard: "8,13,21,34,55" (balanced)
Extended: "13,21,34,55,89" (swing)
Rotation Speed (0.1-2.0):
Controls spiral oscillation frequency
0.618: Golden ratio (balanced)
Higher = more signals, more noise
Lower = smoother, fewer signals
Volume Amplification:
Enables dynamic spiral expansion
Essential for stocks and crypto
Disable for forex (no central volume)
Visual System Architecture
Cascade Bands:
Multi-level volatility envelopes
Gradient coloring from primary to secondary theme
Transparency increases with distance from price
Fill between bands shows fractal structure
Vortex Spirals:
5 Fibonacci-period oscillators
Blue above price (bullish pressure)
Red below price (bearish pressure)
Multiple display styles: Lines, Circles, Dots, Cross
Dynamic Fibonacci Levels:
Auto-updating retracement levels
Smart update logic prevents disruption near levels
Distance-based transparency (closer = more visible)
Updates every 50 bars or on volatility spikes
Confluence Zones:
Highlighted boxes where indicators converge
Stronger confluence = stronger support/resistance
Key areas for reversal trades
Professional Dashboard System
Main Fractal Dashboard: Displays real-time:
Hurst Exponent with market state
Fractal Dimension with complexity level
Volatility Cascade status
Vortex rotation impact
Market regime classification
Signal strength percentage
Active indicator levels
Vortex Metrics Panel: Shows:
Individual spiral deviations
Convergence/divergence metrics
Real-time vortex positioning
Fibonacci period performance
Fractal Metrics Display: Tracks:
Dimension D value
Market complexity rating
Self-similarity strength
Trend quality assessment
Theory Guide Panel: Educational reference showing:
Mandelbrot principles
Fibonacci vortex concepts
Dynamic trading suggestions
Trading Applications
Trend Following:
High Hurst (>0.65) indicates strong trends
Follow cascade band direction
Use vortex spirals for entry timing
Exit when Hurst drops below 0.5
Mean Reversion:
Low Hurst (<0.35) signals reversal potential
Trade toward vortex spiral convergence
Use Fibonacci levels as targets
Tighten stops in chaotic regimes
Breakout Trading:
Monitor cascade band compression
Watch for vortex spiral alignment
Volatility expansion confirms breakouts
Use confluence zones for targets
Risk Management:
Position size based on fractal dimension
Wider stops in high complexity markets
Tighter stops when Hurst is extreme
Scale out at Fibonacci levels
Market-Specific Optimization
Cryptocurrency:
Cascade Levels: 5-7
Hurst Period: 50-100
Rotation Speed: 0.786-1.2
Enable volume amplification
Stock Indices:
Cascade Levels: 4-5
Hurst Period: 80-120
Rotation Speed: 0.5-0.786
Moderate cascade ratio
Forex:
Cascade Levels: 3-4
Hurst Period: 100-150
Rotation Speed: 0.382-0.618
Disable volume amplification
Commodities:
Cascade Levels: 4-6
Hurst Period: 60-100
Rotation Speed: 0.5-1.0
Seasonal adjustment consideration
Innovation and Originality
The MFCV represents several breakthrough innovations:
First Integration of Mandelbrot Fractals with Fibonacci Vortex Theory
Unique synthesis of chaos theory and sacred geometry
Novel application of Hurst exponent to spiral dynamics
Dynamic Volatility Cascade System
Golden ratio-based band expansion
Multi-timeframe fractal analysis
Self-adjusting to market conditions
Volume-Amplified Vortex Spirals
Revolutionary spiral calculation method
Dynamic response to market participation
Multiple Fibonacci period integration
Intelligent Signal Generation
Cooldown system prevents overtrading
Multi-factor confirmation required
Regime-aware signal filtering
Professional Analytics Dashboard
Institutional-grade metrics display
Real-time fractal analysis
Educational integration
Development Journey
Creating the MFCV involved overcoming numerous challenges:
Mathematical Complexity: Implementing Hurst exponent calculations efficiently
Visual Clarity: Displaying multiple indicators without cluttering
Performance Optimization: Managing array operations and calculations
Signal Quality: Balancing sensitivity with reliability
User Experience: Making complex theory accessible
The result is an indicator that brings PhD-level mathematics to practical trading while maintaining visual elegance and usability.
Best Practices and Guidelines
Start Simple: Use default settings initially
Match Timeframe: Adjust parameters to your trading style
Confirm Signals: Never trade MFCV signals in isolation
Respect Regimes: Adapt strategy to market state
Manage Risk: Use fractal dimension for position sizing
Color Themes
Six professional themes included:
Fractal: Balanced blue/purple palette
Golden: Warm Fibonacci-inspired colors
Plasma: Vibrant modern aesthetics
Cosmic: Dark mode optimized
Matrix: Classic green terminal
Fire: Heat map visualization
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice. While the MFCV reveals deep market structure through advanced mathematics, markets remain inherently unpredictable. Past performance does not guarantee future results.
The integration of Mandelbrot's fractal theory with Fibonacci vortex dynamics provides unique market insights, but should be used as part of a comprehensive trading strategy. Always use proper risk management and never risk more than you can afford to lose.
Acknowledgments
Special thanks to Benoit Mandelbrot for revolutionizing our understanding of markets through fractal geometry, and to the ancient mathematicians who discovered the golden ratio's universal significance.
"The geometry of nature is fractal... Markets are fractal too." - Benoit Mandelbrot
Revealing the Hidden Order in Market Chaos Trade with Mathematical Precision. Trade with MFCV.
— Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
EMA Trend with MACD-Based Bar Coloring (Customized)This indicator blends trend-following EMAs with MACD-based momentum signals to provide a visually intuitive view of market conditions. It's designed for traders who value clean, color-coded charts and want to quickly assess both trend direction and overbought/oversold momentum.
🔍 Key Features:
Multi-EMA Trend Visualization:
Includes four Exponential Moving Averages (EMAs):
Fast (9)
Medium (21)
Slow (50)
Long (89)
Each EMA is dynamically color-coded based on its slope—green for bullish, red for bearish, and gray for neutral—to help identify the trend strength and alignment at a glance.
MACD-Based Bar Coloring:
Candlesticks are colored based on MACD's relationship to its Bollinger Bands:
Green bars signal strong bullish momentum (MACD > Upper Band)
Red bars signal strong bearish momentum (MACD < Lower Band)
Gray bars reflect neutral conditions
Compact Visual Dashboard:
A clean, top-right table displays your current EMA and MACD settings, helping you track parameter configurations without opening the settings menu.
✅ Best Used For:
Identifying trend alignment across short- to medium-term timeframes
Filtering entries based on trend strength and MACD overextension
Enhancing discretion-based or rule-based strategies with visual confirmation
Williams R Zone Scalper v1.0[BullByte]Originality & Usefulness
Unlike standard Williams R cross-over scripts, this strategy layers five dynamic filters—moving-average trend, Supertrend, Choppiness Index, Bollinger Band Width, and volume validation —and presents a real-time dashboard with equity, PnL, filter status, and key indicator values. No other public Pine script combines these elements with toggleable filters and a custom dashboard. In backtests (BTC/USD (Binance), 5 min, 24 Mar 2025 → 28 Apr 2025), adding these filters turned a –2.09 % standalone Williams R into a +5.05 % net winner while cutting maximum drawdown in half.
---
What This Script Does
- Monitors Williams R (length 14) for overbought/oversold reversals.
- Applies up to five dynamic filters to confirm trend strength and volatility direction:
- Moving average (SMA/EMA/WMA/HMA)
- Supertrend line
- Choppiness Index (CI)
- Bollinger Band Width (BBW)
- Volume vs. its 50-period MA
- Plots blue arrows for Long entries (R crosses above –80 + all filters green) and red arrows for Short entries (R crosses below –20 + all filters green).
- Optionally sets dynamic ATR-based stop-loss (1.5×ATR) and take-profit (2×ATR).
- Shows a dashboard box with current position, equity, PnL, filter status, and real-time Williams R / MA/volume values.
---
Backtest Summary (BTC/USD(Binance), 5 min, 24 Mar 2025 → 28 Apr 2025)
• Total P&L : +50.70 USD (+5.05 %)
• Max Drawdown : 31.93 USD (3.11 %)
• Total Trades : 198
• Win Rate : 55.05 % (109/89)
• Profit Factor : 1.288
• Commission : 0.01 % per trade
• Slippage : 0 ticks
Even in choppy March–April, this multi-filter approach nets +5 % with a robust risk profile, compared to –2.09 % and higher drawdown for Williams R alone.
---
Williams R Alone vs. Multi-Filter Version
• Total P&L :
– Williams R alone → –20.83 USD (–2.09 %)
– Multi-Filter → +50.70 USD (+5.05 %)
• Max Drawdown :
– Williams R alone → 62.13 USD (6.00 %)
– Multi-Filter → 31.93 USD (3.11 %)
• Total Trades : 543 vs. 198
• Win Rate : 60.22 % vs. 55.05 %
• Profit Factor : 0.943 vs. 1.288
---
Inputs & What They Control
- wrLen (14): Williams R look-back
- maType (EMA): Trend filter type (SMA, EMA, WMA, HMA)
- maLen (20): Moving-average period
- useChop (true): Toggle Choppiness Index filter
- ciLen (12): CI look-back length
- chopThr (38.2): CI threshold (below = trending)
- useVol (true): Toggle volume-above-average filter
- volMaLen (50): Volume MA period
- useBBW (false): Toggle Bollinger Band Width filter
- bbwMaLen (50): BBW MA period
- useST (false): Toggle Supertrend filter
- stAtrLen (10): Supertrend ATR length
- stFactor (3.0): Supertrend multiplier
- useSL (false): Toggle ATR-based SL/TP
- atrLen (14): ATR period for SL/TP
- slMult (1.5): SL = slMult × ATR
- tpMult (2.0): TP = tpMult × ATR
---
How to Read the Chart
- Blue arrow (Long): Williams R crosses above –80 + all enabled filters green
- Red arrow (Short) : Williams R crosses below –20 + all filters green
- Dashboard box:
- Top : position and equity
- Next : cumulative PnL in USD & %
- Middle : green/white dots for each filter (green=passing, white=disabled)
- Bottom : Williams R, MA, and volume current values
---
Usage Tips
- Add the script : Indicators → My Scripts → Williams R Zone Scalper v1.0 → Add to BTC/USD chart on 5 min.
- Defaults : Optimized for BTC/USD.
- Forex majors : Raise `chopThr` to ~42.
- Stocks/high-beta : Enable `useBBW`.
- Enable SL/TP : Toggle `useSL`; stop-loss = 1.5×ATR, take-profit = 2×ATR apply automatically.
---
Common Questions
- * Why not trade every Williams R reversal?*
Raw Williams R whipsaws in sideways markets. Choppiness and volume filters reduce false entries.
- *Can I use on 1 min or 15 min?*
Yes—adjust ATR length or thresholds accordingly. Defaults target 5 min scalping.
- *What if all filters are on?*
Fewer arrows, higher-quality signals. Expect ~10 % boost in average win size.
---
Disclaimer & License
Trading carries risk of loss. Use this script “as is” under the Mozilla Public License 2.0 (mozilla.org). Always backtest, paper-trade, and adjust risk settings to your own profile.
---
Credits & References
- Pine Script v6, using TradingView’s built-in `ta.supertrend()`.
- TradingView House Rules: www.tradingview.com
Goodluck!
BullByte
Pino Trend Pack (SMA/EMA + Bollinger)🔹 Pino Trend Pack is a compact trend-following and volatility indicator that includes:
📈 Moving Averages:
- SMA 10, SMA 30
- EMA 21, EMA 55, EMA 89
(All configured for short-term to mid-term trend analysis by default, but fully adjustable for user preference.)
📊 Bollinger Bands:
- Period: 20
- Standard Deviation: 2.0
- Includes Upper Band, Lower Band, and Basis (SMA 20)
This pack is designed for traders who want a clean visual of price dynamics across multiple short-term trend layers, combined with volatility tracking. It helps you identify compression, expansion, and trend shifts at a glance.
🧠 Ideal for swing trading, short- to mid-term setups, or as a supporting tool in any confluence-based strategy.
PVSRA v5Overview of the PVSRA Strategy
This strategy is designed to detect and capitalize on volume-driven threshold breaches in price candles. It operates on the premise that when a high-volume candle breaks a critical price threshold, not all orders are filled within that candle’s range. This creates an imbalance—similar to a physical system being perturbed—causing the price to revert toward the level where the breach occurred to “absorb” the residual orders.
Key Features and Their Theoretical Underpinnings
Dynamic Volume Analysis and Threshold Detection
Volume Surges as Market Perturbations:
The script computes a moving average of volume over a short window and flags moments when the current volume significantly exceeds this average. These surges act as a perturbation—injecting “energy” into the market.
Adaptive Abnormal Volume Threshold:
By calculating a dynamic abnormal threshold using a daily volume average (via an 89-period VWMA) and standard deviation, the strategy identifies when the current volume is abnormally high. This mechanism mirrors the idea that when a system is disturbed (here, by a volume surge), it naturally seeks to return to equilibrium.
Candle Coloring and Visual Signal Identification
Differentiation of Candle Types:
The script distinguishes between bullish (green) and bearish (red) candles. It applies different colors based on the strength of the volume signal, providing a clear, visual representation of whether a candle is likely to trigger a price reversion.
Implication of Unfilled Orders:
A red (bearish) candle with high volume implies that sell pressure has pushed the price past a critical threshold—yet not all buy orders have been fulfilled. Conversely, a green (bullish) candle indicates that aggressive buying has left pending sell orders. In both cases, the market is expected to reverse toward the breach point to restore balance.
Trade Execution Logic: Normal and Reversal Trades
Normal Trades:
When a high-volume candle breaches a threshold and meets the directional conditions (e.g., a red candle paired with price above a daily upper band), the strategy enters a trade anticipating a reversion. The underlying idea is that the market will move back to the level where the threshold was crossed—clearing the residual orders in a manner analogous to a system following the path of least resistance.
Reversal Trades:
The strategy also monitors for clusters of consecutive signals within a short lookback period. When multiple signals accumulate, it interprets this as the market having overextended and, in a corrective move, reverses the typical trade direction. This inversion captures the market’s natural tendency to “correct” itself by moving in discrete, quantized steps—each step representing the absorption of a minimum quantum of order imbalance.
Risk and Trade Management
Stop Loss and Take Profit Buffers:
Both normal and reversal trades include predetermined buffers for stop loss and take profit levels. This systematic risk management approach is designed to capture the anticipated reversion while minimizing potential losses, aligning with the idea that market corrections follow the most energy-efficient path back to equilibrium.
Symbol Flexibility:
An option to override the chart’s symbol allows the strategy to be applied consistently across different markets, ensuring that the volume and price dynamics are analyzed uniformly.
Conceptual Bridge: From Market Dynamics to Trade Execution
At its core, the strategy treats market price movements much like a physical system that seeks to minimize “transactional energy” or inefficiency. When a price candle breaches a key threshold on high volume, it mimics an injection of energy into the system. The subsequent price reversion is the market’s natural response—moving in the most efficient path back to balance. This perspective is akin to the principle of least action, where the system evolves along the trajectory that minimizes cumulative imbalance, and it acknowledges that these corrections occur in discrete steps reflective of quantized order execution.
This unified framework allows the PVSRA strategy to not only identify when significant volume-based threshold breaches occur but also to systematically execute trades that benefit from the expected corrective moves.
RSI & EMA IndicatorMulti-Timeframe EMA & RSI Analysis with Trend Merging Detection
Overview
This script provides traders with a multi-timeframe analysis tool that simplifies trend detection, momentum confirmation, and potential trend shifts. It integrates Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI) across Daily, Weekly, and Monthly timeframes, helping traders assess both long-term and short-term market conditions at a glance.
This script is a simplification and modification of the EMA Cheatsheet by MarketMoves, reducing chart clutter while adding EMA merging detection to highlight potential trend reversals or breakouts.
Originality and Usefulness
Unlike traditional indicators, which focus on a single timeframe, this script combines multiple timeframes in a single view to offer a comprehensive market outlook.
What Makes This Indicator Unique?
This Indicator to Combine RSI and EMA Clouds for Multiple Timeframes
Multi-Timeframe Trend Analysis in One Visual Tool
EMA Merging Detection to Spot Trend Shifts Early
Momentum Validation Using RSI Across Daily, Weekly, and Monthly Timeframes
Reduces Chart Clutter While Providing Actionable Trade Signals
I couldn't find a TradingView indicator that displayed RSI and EMA clouds together across Daily, Weekly, and Monthly timeframes. This tool bridges that gap, allowing traders to see trend strength and momentum shifts across key timeframes without switching charts.
How the Script Works
1. Trend Direction via EMAs
The script tracks Short-term (5 & 12-period), Medium-term (34 & 50-period), and Long-term (72 & 89-period) EMAs across Daily, Weekly, and Monthly timeframes.
Bullish trend: When faster EMAs are above slower EMAs.
Bearish trend: When faster EMAs are below slower EMAs.
A visual table simplifies trend recognition with:
Green cells for bullish alignment.
Red cells for bearish alignment.
This color-coded system allows traders to quickly assess market momentum across different timeframes without excessive manual analysis.
2. Momentum Confirmation with RSI
The RSI(14) values for Daily, Weekly, and Monthly timeframes are displayed alongside the EMAs.
RSI above 70 suggests overbought conditions.
RSI below 30 suggests oversold conditions.
By combining RSI with EMA trends, traders can confirm whether momentum supports the trend direction or if the market is losing strength.
3. Trend Shift Detection (EMA Merging Mechanism)
A unique feature of this script is EMA merging detection, which occurs when:
The short, medium, and long-term EMAs come within 0.5% of the price.
This often signals trend reversals, breakouts, or consolidations.
When this condition is met, a warning signal appears, alerting traders to potential market shifts.
Who This Indicator Is For?
This script is designed for traders who want to track trends across multiple timeframes while keeping a clean and simplified chart.
Swing & Position Traders – Identify strong trends and potential momentum shifts for longer-term trades.
Trend Followers – Stay aligned with major market trends and avoid trading against momentum.
Day Traders – Use the Daily timeframe for entries while referencing higher timeframes for confirmation.
How to Use the Indicator
Add the indicator to any chart.
Check the trend table in the top-right corner:
Green cells indicate a bullish trend.
Red cells indicate a bearish trend.
Look at RSI values to confirm momentum:
RSI above 70 = Overbought.
RSI below 30 = Oversold.
Watch for the "Merge" alert to spot potential reversals or consolidations.
Combine signals from multiple timeframes for stronger trade decisions.
Why This Indicator is Unique on TradingView?
Before this script, no TradingView indicator displayed RSI and EMA clouds together across multiple timeframes (Daily, Weekly, Monthly).
This tool eliminates the need to:
Manually check multiple timeframes for trend alignment.
Add multiple EMA and RSI indicators to the same chart, creating clutter.
Constantly switch between different timeframes to confirm momentum and trend direction.
With this indicator, traders can see trend strength and momentum shifts instantly, improving their decision-making process.
Chart Guidelines
The script is designed for use on a clean chart to maximize clarity.
The trend alignment table is displayed in a non-intrusive manner so traders can focus on price action.
No additional indicators are required, but users may combine this script with volume-based indicators for further confirmation.
The script name and timeframe should always be visible on published charts to help traders understand the analysis.
Final Notes
This script is a simplification and modification of the EMA Cheatsheet by MarketMoves, improving trend detection, momentum confirmation, and EMA merging detection.
It is designed to help traders quickly identify trend direction, confirm momentum, and detect potential trend shifts, reducing the need for excessive manual analysis.
Disclaimer: This indicator is for educational purposes only and does not constitute financial advice. Trading involves risk; always use proper risk management when applying this tool in live markets.
Engulfing Pattern with Volume and EMAs
**Strategy Overview:
This strategy combines price action (Engulfing patterns), volume analysis, trend confirmation (EMAs), and noise reduction (ATR filter) to generate high-probability trading signals.
Engulfing Pattern with Volume, EMAs, and Market Noise Filter**
This strategy identifies bullish and bearish Engulfing candlestick patterns, combined with volume analysis, moving averages (EMAs), and a market noise filter to generate trading signals.
**Key Components:**
1. **Engulfing Pattern Detection:**
- **Bullish Engulfing**: A green candle completely engulfs the previous red candle.
- **Bearish Engulfing**: A red candle completely engulfs the previous green candle.
2. **Volume Filter:**
- Signals are validated only if the current volume is higher than the 20-period Simple Moving Average (SMA) of volume.
3. **EMA Indicators:**
- Three EMAs are plotted: 50-period (blue), 89-period (orange), and 200-period (red).
- These EMAs help identify the trend direction and provide additional confirmation.
4. **Market Noise Filter:**
- Uses the Average True Range (ATR) to filter out insignificant price movements.
- A signal is considered valid only if the price movement (absolute difference between open and close) is greater than 0.5 times the 14-period ATR.
**Trading Signals:**
**Buy Signal**:
- Bullish Engulfing pattern + High volume (above SMA 20) + Significant price movement (filtered by ATR).
- Plotted as a green "BUY" label below the candle.
**Sell Signal**:
- Bearish Engulfing pattern + High volume (above SMA 20) + Significant price movement (filtered by ATR).
- Plotted as a red "SELL" label above the candle.
**Customization:**
- Users can adjust EMA lengths, volume SMA period, and ATR multiplier to suit their trading preferences.
[COG] Adaptive Squeeze Intensity 📊 Adaptive Squeeze Intensity (ASI) Indicator
🎯 Overview
The Adaptive Squeeze Intensity (ASI) indicator is an advanced technical analysis tool that combines the power of volatility compression analysis with momentum, volume, and trend confirmation to identify high-probability trading opportunities. It quantifies the degree of price compression using a sophisticated scoring system and provides clear entry signals for both long and short positions.
⭐ Key Features
- 📈 Comprehensive squeeze intensity scoring system (0-100)
- 📏 Multiple Keltner Channel compression zones
- 📊 Volume analysis integration
- 🎯 EMA-based trend confirmation
- 🎨 Proximity-based entry validation
- 📱 Visual status monitoring
- 🎨 Customizable color schemes
- ⚡ Clear entry signals with directional indicators
🔧 Components
1. 📐 Squeeze Intensity Score (0-100)
The indicator calculates a total squeeze intensity score based on four components:
- 📊 Band Convergence (0-40 points): Measures the relationship between Bollinger Bands and Keltner Channels
- 📍 Price Position (0-20 points): Evaluates price location relative to the base channels
- 📈 Volume Intensity (0-20 points): Analyzes volume patterns and thresholds
- ⚡ Momentum (0-20 points): Assesses price momentum and direction
2. 🎨 Compression Zones
Visual representation of squeeze intensity levels:
- 🔴 Extreme Squeeze (80-100): Red zone
- 🟠 Strong Squeeze (60-80): Orange zone
- 🟡 Moderate Squeeze (40-60): Yellow zone
- 🟢 Light Squeeze (20-40): Green zone
- ⚪ No Squeeze (0-20): Base zone
3. 🎯 Entry Signals
The indicator generates entry signals based on:
- ✨ Squeeze release confirmation
- ➡️ Momentum direction
- 📊 Candlestick pattern confirmation
- 📈 Optional EMA trend alignment
- 🎯 Customizable EMA proximity validation
⚙️ Settings
🔧 Main Settings
- Base Length: Determines the calculation period for main indicators
- BB Multiplier: Sets the Bollinger Bands deviation multiplier
- Keltner Channel Multipliers: Three separate multipliers for different compression zones
📈 Trend Confirmation
- Four customizable EMA periods (default: 21, 34, 55, 89)
- Optional trend requirement for entry signals
- Adjustable EMA proximity threshold
📊 Volume Analysis
- Customizable volume MA length
- Adjustable volume threshold for signal confirmation
- Option to enable/disable volume analysis
🎨 Visualization
- Customizable bullish/bearish colors
- Optional intensity zones display
- Status monitor with real-time score and state information
- Clear entry arrows and background highlights
💻 Technical Code Breakdown
1. Core Calculations
// Base calculations for EMAs
ema_1 = ta.ema(close, ema_length_1)
ema_2 = ta.ema(close, ema_length_2)
ema_3 = ta.ema(close, ema_length_3)
ema_4 = ta.ema(close, ema_length_4)
// Proximity calculation for entry validation
ema_prox_raw = math.abs(close - ema_1) / ema_1 * 100
is_close_to_ema_long = close > ema_1 and ema_prox_raw <= prox_percent
```
### 2. Squeeze Detection System
```pine
// Bollinger Bands setup
BB_basis = ta.sma(close, length)
BB_dev = ta.stdev(close, length)
BB_upper = BB_basis + BB_mult * BB_dev
BB_lower = BB_basis - BB_mult * BB_dev
// Keltner Channels setup
KC_basis = ta.sma(close, length)
KC_range = ta.sma(ta.tr, length)
KC_upper_high = KC_basis + KC_range * KC_mult_high
KC_lower_high = KC_basis - KC_range * KC_mult_high
```
### 3. Scoring System Implementation
```pine
// Band Convergence Score
band_ratio = BB_width / KC_width
convergence_score = math.max(0, 40 * (1 - band_ratio))
// Price Position Score
price_range = math.abs(close - KC_basis) / (KC_upper_low - KC_lower_low)
position_score = 20 * (1 - price_range)
// Final Score Calculation
squeeze_score = convergence_score + position_score + vol_score + mom_score
```
### 4. Signal Generation
```pine
// Entry Signal Logic
long_signal = squeeze_release and
is_momentum_positive and
(not use_ema_trend or (bullish_trend and is_close_to_ema_long)) and
is_bullish_candle
short_signal = squeeze_release and
is_momentum_negative and
(not use_ema_trend or (bearish_trend and is_close_to_ema_short)) and
is_bearish_candle
```
📈 Trading Signals
🚀 Long Entry Conditions
- Squeeze release detected
- Positive momentum
- Bullish candlestick
- Price above relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
🔻 Short Entry Conditions
- Squeeze release detected
- Negative momentum
- Bearish candlestick
- Price below relevant EMAs (if enabled)
- Within EMA proximity threshold (if enabled)
- Sufficient volume confirmation (if enabled)
⚠️ Alert Conditions
- 🔔 Extreme squeeze level reached (score crosses above 80)
- 🚀 Long squeeze release signal
- 🔻 Short squeeze release signal
💡 Tips for Usage
1. 📱 Use the status monitor to track real-time squeeze intensity and state
2. 🎨 Pay attention to the color gradient for trend direction and strength
3. ⏰ Consider using multiple timeframes for confirmation
4. ⚙️ Adjust EMA and proximity settings based on your trading style
5. 📊 Use volume analysis for additional confirmation in liquid markets
📝 Notes
- 🔧 The indicator combines multiple technical analysis concepts for robust signal generation
- 📈 Suitable for all tradable markets and timeframes
- ⭐ Best results typically achieved in trending markets with clear volatility cycles
- 🎯 Consider using in conjunction with other technical analysis tools for confirmation
⚠️ Disclaimer
This technical indicator is designed to assist in analysis but should not be considered as financial advice. Always perform your own analysis and risk management when trading.
Mean Reversion Pro Strategy [tradeviZion]Mean Reversion Pro Strategy : User Guide
A mean reversion trading strategy for daily timeframe trading.
Introduction
Mean Reversion Pro Strategy is a technical trading system that operates on the daily timeframe. The strategy uses a dual Simple Moving Average (SMA) system combined with price range analysis to identify potential trading opportunities. It can be used on major indices and other markets with sufficient liquidity.
The strategy includes:
Trading System
Fast SMA for entry/exit points (5, 10, 15, 20 periods)
Slow SMA for trend reference (100, 200 periods)
Price range analysis (20% threshold)
Position management rules
Visual Elements
Gradient color indicators
Three themes (Dark/Light/Custom)
ATR-based visuals
Signal zones
Status Table
Current position information
Basic performance metrics
Strategy parameters
Optional messages
📊 Strategy Settings
Main Settings
Trading Mode
Options: Long Only, Short Only, Both
Default: Long Only
Position Size: 10% of equity
Starting Capital: $20,000
Moving Averages
Fast SMA: 5, 10, 15, or 20 periods
Slow SMA: 100 or 200 periods
Default: Fast=5, Slow=100
🎯 Entry and Exit Rules
Long Entry Conditions
All conditions must be met:
Price below Fast SMA
Price below 20% of current bar's range
Price above Slow SMA
No existing position
Short Entry Conditions
All conditions must be met:
Price above Fast SMA
Price above 80% of current bar's range
Price below Slow SMA
No existing position
Exit Rules
Long Positions
Exit when price crosses above Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
Short Positions
Exit when price crosses below Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
💼 Risk Management
Position Sizing
Default: 10% of equity per trade
Initial capital: $20,000
Commission: 0.01%
Slippage: 2 points
Maximum one position at a time
Risk Control
Use daily timeframe only
Avoid trading during major news events
Consider market conditions
Monitor overall exposure
📊 Performance Dashboard
The strategy includes a comprehensive status table displaying:
Strategy Parameters
Current SMA settings
Trading direction
Fast/Slow SMA ratio
Current Status
Active position (Flat/Long/Short)
Current price with color coding
Position status indicators
Performance Metrics
Net Profit (USD and %)
Win Rate with color grading
Profit Factor with thresholds
Maximum Drawdown percentage
Average Trade value
📱 Alert Settings
Entry Alerts
Long Entry (Buy Signal)
Short Entry (Sell Signal)
Exit Alerts
Long Exit (Take Profit)
Short Exit (Take Profit)
Alert Message Format
Strategy name
Signal type and direction
Current price
Fast SMA value
Slow SMA value
💡 Usage Tips
Consider starting with Long Only mode
Begin with default settings
Keep track of your trades
Review results regularly
Adjust settings as needed
Follow your trading plan
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice. Always:
Conduct your own research
Test thoroughly before live trading
Use proper risk management
Consider your trading goals
Monitor market conditions
Never risk more than you can afford to lose
📋 Release Notes
14 January 2025
Added New Fast & Slow SMA Options:
Fibonacci-based periods: 8, 13, 21, 144, 233, 377
Additional period: 50
Complete Fast SMA options now: 5, 8, 10, 13, 15, 20, 21, 34, 50
Complete Slow SMA options now: 100, 144, 200, 233, 377
Bug Fixes:
Fixed Maximum Drawdown calculation in the performance table
Now using strategy.max_drawdown_percent for accurate DD reporting
Previous version showed incorrect DD values
Performance metrics now accurately reflect trading results
Performance Note:
Strategy tested with Fast/Slow SMA 13/377
Test conducted with 10% equity risk allocation
Daily Timeframe
For Beginners - How to Modify SMA Levels:
Find this line in the code:
fastLength = input.int(title="Fast SMA Length", defval=5, options= )
To add a new Fast SMA period: Add the number to the options list, e.g.,
To remove a Fast SMA period: Remove the number from the options list
For Slow SMA, find:
slowLength = input.int(title="Slow SMA Length", defval=100, options= )
Modify the options list the same way
⚠️ Note: Keep the periods that make sense for your trading timeframe
💡 Tip: Test any new combinations thoroughly before live trading
"Trade with Discipline, Manage Risk, Stay Consistent" - tradeviZion
UM EMA SMA WMA HMA with Directional Color ChangeUM EMA SMA WMA HMA with Directional Color Change
Description:
This is a Swiss Army knife type of Moving Average tool. Select your favorite Moving Average type, EMA - Exponential Moving Average, SMA - Simple Moving Average, WMA - Weighted Moving Average, or HMA - Hull Moving Average. Then selection your number of periods. The MA line is green when trending higher and red when trending lower. The fill between price and the MA line matches the red/green of the direction.
Defaults and Configuration:
The default setting is 65 period and EMA. Line colors and optional fill colors are user-configurable.
Alerts:
An alert can be set on the MA for directional color changes (red to green, or green to red) Right click the indicator and select Add Alert. Then select Bullish or Bearish color change.
Suggested Uses:
Add this to any timeframe chart with your favorite Moving averages. A strategy I use frequently is to "stretch" the Moving average. For example if you like the 8 day moving average on the daily chart, try the 52 period Moving average on the hourly chart. (6.5 market hours per day * 8) By looking at smaller time frames with longer MAs you get smoother color transitions on the Moving average. Add multiple instances of the MA. I prefer to use a smaller quick MA with a longer MA that represents a longer time frame.
Another use case I also like is the color transition over a Moving Average crossover. While I do like the daily 2/6 and 8/3 moving average crossovers, red-to-green and green-to-red color transitions seem to work with less lag than the crossovers.
Suggested Settings:
Daily charts: 8 EMA
Hourly charts: 55 EMA
30 minute charts: 65 WMA. (I like this one for inverse ETFs)
3 minutes charts: 178 EMA and 233 EMA
I also like to round MA settings up or down to the nearest fibonacci number: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, etc.
Support/Resistance
Custom Moving Average Indicator with MACD, RSI, and Support/Resistance
This indicator is designed to help traders make informed trading decisions by integrating several technical indicators, including moving averages, the Relative Strength Index (RSI), and the Moving Average Convergence Divergence (MACD).
Key Features:
Moving Averages:
This indicator uses simple moving averages (SMAs) for several periods (4, 18, 66, 89, 632, 1000, 1500, 2000, and 3000 bars). This helps to identify the overall trend of the price and potential support and resistance levels.
The color of each moving average line is dynamically changed based on the closing price's position relative to the average; it turns red if the price is above the average and green if the price is below.
Relative Strength Index (RSI):
The RSI is calculated for a 14-bar period, which is a measure of overbought or oversold conditions.
An RSI value above 70 indicates an overbought condition, while a value below 30 indicates an oversold condition.
MACD:
The MACD is calculated using a fast length of 12, a slow length of 26, and a signal length of 9. Crossovers between the MACD line and the signal line indicate momentum shifts.
A crossover of the MACD line above the signal line suggests a potential buy signal, while a crossover below indicates a potential sell signal.
Buy and Sell Signals:
Buy Signal: Triggered when the MACD line crosses above the signal line, the RSI is below 30, the MACD is above 0, and there is high volume.
Sell Signal: Triggered when the MACD line crosses below the signal line, the RSI is above 70, the MACD is below 0, and there is high volume.
Alerts:
The indicator includes alerts that are triggered when buy and sell signals occur, helping traders respond quickly to market opportunities.
How to Trade Using the Indicator (continued):
Trading on Buy Signals:
Look for buy signals when the MACD line crosses above the signal line. Ensure that the RSI is below 30, indicating there is a potential for price recovery from an oversold condition.
Confirm that the volume is above the average, which indicates strong market participation and adds validity to the trade.
Trading on Sell Signals:
Search for sell signals when the MACD line crosses below the signal line. Check that the RSI is above 70 to confirm an overbought condition, implying the price may decline.
As with buy signals, ensure that volume is high to validate the strength of the sell signal.
Risk Management:
Use stop-loss orders to protect your capital. Establish an initial loss threshold based on your risk management strategy.
Continuously monitor the market and new signals and adjust your approach according to your market analysis.
Conclusion:
This combined indicator helps traders make informed decisions by relying on a set of technical tools. To achieve the best results, ensure you integrate the analysis from these indicators with your trading strategies and other techniques.
Feel free to use this explanation as an introduction or guide to inform traders on how to effectively use the indicator. If you have any more questions or need further details, don't hesitate to ask!
Adaptive Fibonacci Trend Ribbon[FibonacciFlux]Adaptive Fibonacci Trend Ribbon (FibonacciFlux)
Overview
The Adaptive Fibonacci Trend Ribbon is a versatile technical analysis tool designed for traders who want to leverage the power of multiple moving averages while integrating Fibonacci numbers. This indicator provides a dynamic visual representation of market trends, enhancing decision-making processes in trading.
Key Features
1. Multi-Moving Averages
- The indicator calculates eight different moving averages based on user-defined periods, including Fibonacci numbers such as 5, 8, 13, 21, 34, 55, 89, and 144.
- Traders can choose from various moving average types, including EMA, HMA, WMA, VWMA, ALMA, SMA, RMA, and TMA , allowing for tailored analysis based on market conditions.
2. Trend Detection
- Each moving average is color-coded based on its trend direction, with green indicating an upward trend and red indicating a downward trend.
- This visual clarity helps traders quickly assess market sentiment and make informed decisions.
3. Fill Areas for Enhanced Insight
- The indicator features fill areas between the moving averages, which dynamically change color according to their relative positions.
- This provides a clear visual cue of trend strength and potential reversal points, allowing traders to identify key areas of interest.
4. Customizable Inputs
- Users can easily adjust the source data, moving average lengths, and ALMA parameters (offset and sigma) to fit their trading strategies.
- This flexibility ensures that traders can adapt the tool to various market conditions and personal preferences.
Insights and Applications
1. Fibonacci Integration
- By incorporating Fibonacci numbers into the moving average periods, this indicator allows traders to align their strategies with key levels of support and resistance.
- This can enhance the accuracy of entry and exit points, particularly in trending markets.
2. Trend Continuation and Reversal Analysis
- The adaptive nature of the moving averages provides insights into potential trend continuations or reversals.
- Traders can use the indicator to identify when to enter or exit positions based on the interaction between the moving averages.
3. Visual Clarity for Quick Decisions
- The color-coded moving averages and fill areas offer immediate visual feedback on market conditions, helping traders react swiftly to changing dynamics.
- This is especially useful in fast-moving markets where timely decisions are critical.
Conclusion
The Adaptive Fibonacci Trend Ribbon is an essential tool for traders looking to enhance their technical analysis capabilities. By combining multiple moving averages with Fibonacci integration and dynamic visual cues, this indicator offers a robust framework for understanding market trends. Its flexibility and clarity make it an invaluable asset for both novice and experienced traders alike.
Open Source Contribution
This indicator is open source, inviting contributions and improvements from the trading community. Feel free to fork, enhance, and share your insights with the world, helping to foster a collaborative environment for traders everywhere.
Trend/with EMA382Introduction to the "Trend/with EMA382" Indicator
The "Trend/with EMA382" indicator is a powerful technical analysis tool that combines trend signals with Exponential Moving Averages (EMA), offering traders a comprehensive view of market dynamics and helping identify potential trading opportunities.
1. Trend Analysis with Trend
The first part of this indicator uses a trend calculation algorithm based on the recent market highs and lows. These levels are used to determine the primary trend:
Bullish (Uptrend): When the market is in an uptrend, the chart will display buy signals in green.
Bearish (Downtrend): When the market is trending down, sell signals are shown in red.
The crossover points between price and trend levels will indicate buy or sell signals on the chart, enabling traders to easily spot entry and exit points.
2. Combination with EMA382
EMA (Exponential Moving Average) is a crucial tool in technical analysis, helping smooth price data and eliminate insignificant short-term fluctuations. This indicator uses three key EMAs:
EMA 34: Reflects short-term trends.
EMA 89: Helps identify medium-term trends.
EMA 200: Determines long-term trends.
These three EMAs assist traders in identifying the overall direction of the market, allowing them to forecast potential trend developments.
3. Application in Trading
The "Trend/with EMA382" indicator is designed to suit various time frames, from short-term to long-term trading. The combination of trend signals and EMAs helps:
Identify the primary market trend.
Provide accurate entry and exit signals.
Deliver clear signals for risk management and profit optimization.
Conclusion
"Trend/with EMA382" is an effective indicator that offers clear signals for both trend and market momentum. By combining EMAs with trend analysis, this indicator empowers traders to make more informed and precise trading decisions.
[blackcat] L1 Dynamic Momentum Indicator
**1. Overview**
" L1 Dynamic Momentum Indicator" is a custom TradingView indicator designed to analyze price momentum and market trends. It combines the calculation methods of Stoch (RSV) and Moving Average (SMA) to provide market overbought and oversold signals.
**2. Calculation Method**
- **RSV Value Calculation**: The RSV value is calculated using the relative relationship between the current price and the lowest and highest prices over the past 89 periods.
- **K Value Calculation**: The calculated RSV value is subjected to a 3-period Simple Moving Average (SMA) to obtain the K value.
- **D Value Calculation**: The K value is subjected to a 3-period Simple Moving Average (SMA) to obtain the D value.
- **Momentum Difference Calculation**: The difference between the 13-period Exponential Moving Average (EMA) and the 34-period EMA of closing prices is calculated, and then the moving average of this difference is calculated.
**3. Indicator Display**
- **K and D Lines**: The moving averages of the K value and D value are displayed on the chart, indicating a strong market condition when the K line is above the D line, and a weak market condition when the K line is below the D line.
- **Threshold Line**: A fixed threshold line of 50 is displayed to distinguish the overbought and oversold areas.
- **Green and Red Bars**: Green and red bars are drawn on the chart based on the relationship between the momentum difference and the average value, indicating the market trend.
**4. Usage Suggestions**
- When the market is in a strong condition, a potential reversal may occur in the overbought area after selling. When the market is in a weak condition, a potential bounce may occur in the oversold area after buying.
- Pay attention to the changes in market trends, with the appearance of green bars may indicate that the market is about to rise, and the appearance of red bars may indicate that the market is about to fall.
**5. Caution**
- The indicator is based on the provided code and may require adjustments based on market conditions.
- The accuracy of the indicator depends on the selection of calculation parameters and the reliability of market data.
Relative Volume Intensity Control Chart***NOTE THE VOLUME OSCILATOR PROVIDED AT THE BOTTOM IS FOR COMPARSION AND IS NOT PART OF THE INDICATOR****
This indicator provides a comprehensive and a nuanced representation of volume relative to historical volume. The indicator aims to provide insights into the relative intensity of trading volume compared to historical data. It calculates two types of relative volume intensity: mean volume intensity and point volume intensity. The final indicator, "Relative_volume_intensity," is a combination of these two.
1. Point Volume Intensity:
Calculate the ratio of the current volume to the corresponding SMA from the previous period for each of the periods.
Normalize each ratio by dividing it by the corresponding normalized SMA.
Assign weights to each normalized ratio and calculate the point volume intensity.
Point volume intensity calculates the intensity of the current trading volume at a specific point in time relative to its historical moving average. It assesses how much the current volume deviates from the previous historical average for different lookback periods(current volume/ average volume of previous n days). The calculation involves dividing the current volume by the corresponding previous historical moving average and normalizing the result. The purpose of point volume intensity is to capture the immediate impact of the current volume on the overall intensity, providing a more dynamic and responsive measure.
2. Mean Volume Intensity:
Calculate the simple moving averages (SMA) of the volume for different periods (5, 8, 13, 21, 34, 55, 89, 144).
Normalize each SMA by dividing it by the SMA with the longest lookback (144).
Assign weights to each normalized SMA and calculate the mean volume intensity.
Mean volume intensity, on the other hand, takes a broader approach by looking at the mean (average) of various historical moving averages of volume. Instead of focusing on the current volume alone, it considers the historical average intensity over multiple periods. The purpose of mean volume intensity is to provide a smoother and more stable representation of the overall historical volume intensity. It helps filter out short-term fluctuations and provides a more comprehensive view of how the current volume compares to historical norms.
Purpose of Both:
Both point volume intensity and mean volume intensity contribute to the calculation of the final indicator, "Relative_volume_intensity." The idea is to combine these two perspectives to create a more comprehensive measure of relative volume intensity. By assigning equal weights to both components and taking a balanced approach, the indicator aims to capture both short-term spikes in volume and trends in volume intensity over a relatively extended periods.
In calculation of both point volume intensity and mean volume intensity, shorter-term moving averages (e.g., 5, 8) have higher weights, suggesting a greater emphasis on recent volume behavior.
Visualization:
The script then calculates the mean and standard deviation of the relative volume intensity over a specified lookback length.
Plot lines for the centerline (mean), upper and lower 3 standard deviations, upper and lower 2 standard deviations, and upper and lower 1 standard deviation.
Plot the relative volume intensity as a step line with diamond markers.
It is displayed like a control chart where we can see how the relative intensity is behaving when compared to longer historical lookback period.
Machine Learning: MFI Heat Map [YinYangAlgorithms]Overview:
MFI Heat Maps are a visually appealing way to display the values of 29 different MFIs at the same time while being able to make sense of it. Each plot within the Indicator represents a different MFI value. The higher you get up, the longer the length that was used for this MFI. This Indicator also features the use of Machine Learning to help balance the MFI levels. It doesn’t solely rely upon Machine Learning but instead incorporates a growing length MFI averaged with the Machine Learning MFI at any given index.
For instance, say we are calculating the 10th plot from the bottom, the MFI would be an average of:
MFI(source, 11)
Machine Learning MFI at Index of 10
We do it this way as they both help smooth each other out without relying solely on just one calculation method.
Due to plot limitations, you are capped at 28 Plot Amounts within this indicator, but that is still quite a bit of information you can glean from a Heat Map.
The Machine Learning used in this indicator is of the K-Nearest Neighbor (KNN). It uses a Fast and Slow MFI calculation then sorts through them over Machine Learning Length and calculates the differences between them. It then slices off KNN length to create our Max/Min Distances allotted. It adds the average between Fast and Slow MFIs to a Viable Distances array if their distances are within the KNN Min/Max distance. It then averages all distances in the Viable Distances array and returns the result.
The result of the KNN Function is saved to another ML Data array whose length is that of Plot Amount (Heat Map Size). This way each Index of the ML Data array can be indexed according to the Heat Map Size.
The Average of the ML Data array is the MFI line (white) that you’ll see plotted on the Indicator. There is also the SMA of the MFI Average (orange) which is likewise plotted. These plots allow you to visualize where the ML MFI is sitting and can potentially be useful for seeing when the MFI Average and SMA cross over and under each other.
We’ve heard many people talk highly of RSI, but sadly not too many even refer to MFI. MFI oftentimes may be overlooked, especially with new traders who may not even know what it is. Essentially MFI is an RSI but it also incorporates Volume into its calculations, which in our opinion leads to a more accurate reading; afterall, what is price movement without Volume.
Tutorial:
You may be thinking, this Indicator looks appealing to the eye, but how do I benefit from it trading wise?
Before we get into our visual examples, let's talk briefly about what makes Heat Maps in general a useful tool for trading. Heat Maps give us the ability to visualize and understand lots of data while removing the clutter. We can understand the data of 29 different MFIs without having to look at and decipher 29 different MFI plots. When you overlay too many MFI lines on top of each other, they can be very difficult to read and oftentimes end up actually hindering your Technical Analysis. For this reason, we have a simple solution to this problem; Heat Maps. This MFI Heat Map allows you to easily know (in a relative %) what the MFI level is for varying lengths. For Instance, the First (bottom) plot indexes an MFI of (K(0) (loop of Plot Amount) + Smoothing Length (default 1)) = 1. Since this is indexing (usually) a very low length, it will change much quicker. Whereas the Last (top) plot indexes an MFI of (K(27) (loop of Plot Amount) + Smoothing Length (default 1)) = 28. This is indexing a much higher length of MFI which results in the MFI the higher you go up in the Heat Map to move much slower.
Heat Maps give us the ability to see changes happening over multiple MFIs at the same time, which can be very useful for seeing shifts in MFI / Momentum. Remember, MFI incorporates Volume, so even if the price goes up a lot, if there was low volume, the MFI won’t move as much as an RSI would. However, likewise, if there is high volume but low price movement, the MFI will move slightly more than the RSI.
Heat Maps change color based on their MFI level. If the MFI is >= 90 it is HOT (red), if the MFI <= 9 it is COLD (teal, think of ICE). Green represents an MFI of 50-59 and Dark Blue represents an MFI of 40-49. Green and Dark blue are the most common colors as all the others are more ‘Extreme’ MFI levels.
Okay, time to get to the Examples :
Since there is so much going on in Heat Maps, we’ve decided to focus this tutorial to this specific area and talk about individual locations before talking about it as a whole.
If you refer to the example above where there are 2 white circles; these white circles are highlighting a key location you’ll be wanting to identify within your Heat Maps, many things are happening here:
The MFI crossed over the SMA (bullish).
The Heat Map started changing from mid/dark Blue (30-50 MFI) to Green (50-59 MFI) around the midline (the 50% dashed like).
The Lower levels of the Heat Map are turning Yellow/Orange/Red (60-100 MFI).
The Upper Levels of the Heat Map are still Light Blue - Green (10-50 MFI).
The 4 Key points above, all point towards potential Bullish Momentum changes. You’re likely wondering, but why? Let's discuss about each one in more specific detail:
1. The MFI crossed over the SMA (bullish): What this tells us is that the current MFI Average is now greater than its average over the last (default) 16 bars. This means there's been a large amount of Money Flow (Price and Volume) recently (subjectively based on the last (default) 16 average). This is one of the leading Bullish / Bearish signals you will see within this Indicator. You can enable Signals within the Settings and/or even add Alerts for when these crossings occur.
2. The Heat Map started changing from mid/dark Blue (30-50 MFI) to Green (50-59 MFI) around the midline (the 50% dashed like): This shows us that the index’s in the mid (if using all 28 heat map plots it would be at 14) has already received some of this momentum change. If you look at the second white circle (right), you’ll also notice the higher MFI plot indexes are also green. This is because since their length is long they still have some momentum and strength from the first white circle (left). Just because the first white circle failed in its bullish push, doesn’t mean it didn’t achieve momentum that would later on help to push the price up.
3. The Lower levels of the Heat Map are turning Yellow/Orange/Red (60-100 MFI): It occurred somewhat in the left white circle, but mainly in the right white circle. This shows us the MFI is very high on the lower lengths, this may lead to the current, middle and higher length MFIs following suit soon. Remember it has to work its way up, the higher levels can’t go red unless the lower levels go red first and the higher levels can also lag quite a bit behind and take awhile to catch up, this is normal, expected and meant to happen. Vice versa is also true with getting higher levels to go cold (light teal (think of ICE)).
4. The Upper Levels of the Heat Map are still Light Blue - Green (10-50 MFI): You might think at first that this is a bad thing, but it's not! Remember you want to be Fearful when others are Greedy and Greedy when others are Fearful! You don’t want to buy when the higher levels have a high MFI, you want to buy when you see the momentum pushing up in the lower MFI levels (getting yellow/orange/red in the low levels) while it is still Cold in the higher levels (BLUE OR GREEN, nothing higher than green as it is already slightly too high). There will be many times that it is Yellow or possibly Orange in the high levels and the bullish push still happens, but this is much more risky! The key to trading is to minimize risks while maximizing potential.
Hopefully now you’re getting an idea of how to spot potential bullish momentum changes, but what about bearish momentum changes? Technically they are the exact opposite, so we don’t need to go into as much detail, but lets still take a look at a few examples:
In the example above we marked the 3 times where it was displaying overly bullish characteristics. We marked the bullish momentum occurring with arrows. If you look closely at the start of the arrow to where it finishes, you’ll notice how the heat (HOT)(RED) works its way up from the lower levels to the higher levels. We then see the MFI to SMA cross under. In all 3 of these examples the heat made it all the way to the top of the chart. These are all very bearish signals that represent a bearish momentum movement that may occur soon.
Also, please note, the level the MFI is at DOES matter! That line isn’t there simply for you to see when there are crosses over and under. The MFI is considered to be Overbought when it is greater than 70 (the upper white dashed line, it is just formatted to be on a different scale cause there are 28 plots, but it represents 70). The MFI is considered to be Oversold when it is less than 30 (the lower white dashed line).
If we look to the left a little here where a big drop in price occurred shortly after our MFI and SMA crossed, would we have been able to identify it using the Heat Maps? Likely, No. There was some color change in the lower levels a few bars prior that went yellow/orange/red but before this cross happened they all went back to Dark Blue. In the middle section when the cross happened it was only Green and Yellow and in the upper section we are Blue. This would be a very risky trade to go on as the only real Bearish Indication was the MFI to SMA cross under. Remember, you want to reduce risk, you don’t want to simply trade on everytime the MFI and SMA cross each other or you’ll be getting yourself into many risky trades based on false signals.
Based on what you’ve learned above, can you see the signs that are indicating where this white circle may have potential for a bullish momentum change?
Now that we are more zoomed in, you may also be noticing there are colors to the price bars. This can be disabled in the settings, but just so you know what they mean, let’s zoom in a little more and talk about it.
We’ve condensed the Indicator a bit so you can see the bars better here. The colors that are displayed on these bars are the Heat Map value for your MFI (the white line in the Indicator). This way you can better see when the Price is Hot and Cold. As you may see while looking, the colors generally go from cold to hot when bullish momentum is happening and hot to cold when bearish momentum is happening. We don’t recommend solely looking at the bars as indicators to MFI momentum change, as seeing the Heat Map will give you much more data; however it can be nice to see the Heat Map projected on the bars rather than trying to eyeball it yourself or hover over each bar specifically to see their levels.
We will conclude our Tutorial here. Hopefully this has given you some insight to how useful Heat Maps can be and why it works well with a Machine Learning (KNN) Model applied to the MFI.
PLEASE NOTE: You can adjust the line width for the Heat Map within the settings. If you condense the Indicator a lot or have a small screen, likely use a length of 1-2. If you have it stretched out or a large screen, a length of 2-3 will work nice. You just don’t want to have the lines overlapping or it defeats the purpose of a Heat Map. Also, the bigger the linewidth, generally you’ll want to increase the Transparency within the Settings also as it can get quite bright and hurt your eyes over time.
Settings:
MFI:
Show MFI and SMA Crossing Signals: MFI and SMA Crossing is one of the leading Bullish and Bearish Signals in this Indicator. You can also add alerts for these signals.
Plot Amount: How many plots are used in this Heat Map. (2 - 28).
Source: The Source to use in all MFI calculations.
Smooth Initial MFI Length: How much to smooth the Fast and Slow MFI calculation by. 1 = No smoothing.
MFI SMA Length: What length we smooth the MFI Average over to get our MFI SMA.
Machine Learning:
Average MFI data by adding a lookback to the Source: While populating our Heat Map with the MFI's, should use use the Source each MFI Length increase or should we also lookback a Source each MFI Length Increase.
KNN Distance Requirement: To be a valid KNN, it needs to abide by a Distance calculation. Generally only Max is used, but you can change it if it suits your trading style better.
Machine Learning Length: How much ML data should we store? The longer the length generally the smoother the result; which may not be as accurate for something like a Heat Map, so keeping this relatively low may lead to more accurate results.
KNN Length: How many KNN are used in the slice to calculate max/min distance allowed.
Fast Length: Fast MFI length used in KNN to calculate distances by comparing its distance with the Slow MFI Length.
Slow Length: Slow MFI length used in KNN to calculate distances by comparing its distance with the Fast MFI Length.
Smoothing Length: When populating our Heat Map, at what length do we start our MFI calculations with (A Higher value with result in a slower and more smoothed MFI / Heat Map).
Colors:
Change Bar Color: Change bar colors to MFI Avg Color.
Heat Map Transparency: If there isn't any transparency it can be a little hard on the eyes. The Greater the Line Width, generally the more transparency you'll want for your eyes.
Line Width: Set how wide the Heat Map lines are
MFI 90-100 Color: Color when the MFI is between these levels.
MFI 80-89 Color: Color when the MFI is between these levels.
MFI 70-79 Color: Color when the MFI is between these levels.
MFI 60-69 Color: Color when the MFI is between these levels.
MFI 50-59 Color: Color when the MFI is between these levels.
MFI 40-49 Color: Color when the MFI is between these levels.
MFI 30-39 Color: Color when the MFI is between these levels.
MFI 20-29 Color: Color when the MFI is between these levels.
MFI 10-19 Color: Color when the MFI is between these levels.
MFI 0-100 Color: Color when the MFI is between these levels.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
RSI + FIB HH LL StopLoss Finder／Contrarian TradesThis indicator is a multi-timeframe indicator that works in any timeframe.
It takes a price reading of the highest or lowest bar in the past based on Fibonacci numbers and plots it.
In addition, the RSI smoothed by a 5-day moving average can be used to detect signs that previous highs or lows will be reached in advance.
This gives insight into determining stop-loss values or entering the market in a contrarian manner.
This is an example of BTCUSDT 4Hour Chart
Here is BTCUSDT 1Hour Chart
For scalpers BTCUSDT 15min Chart Example
Fibonacci Number is 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, ...
FIbonacci Ratio is 0.236, 0.382, 0.5, 0.618, 1, 1.618, 2.618, 4.236, ...
Multi Timeframe Trend StrengthThis code is an advancement of my previous percentile-based trend strength. It follows the same concept, except this code display the trend and trend strength in multiple timeframe (1 min, 5 min, 15 min, 1hr and 4hr).
This gives an indication of the trend is evolving and allows to see how short-term trend matches with the long-term trend.
How it works:
The script assesses trend strength through percentile values derived from high and low prices across various time periods. It categorizes the current trend as either Bullish, Bearish, or N/A (No Trend) with the following steps:
Percentile Calculations: The code calculates the 75th percentile of high prices (e.g., percentile_13H) and the 25th percentile of low prices (e.g., percentile_13L) for specified Fibonacci-based periods (13, 21, 34, 55, 89, and 144). These percentiles serve as thresholds for identifying strong trends.
Calculate Highest High and Lowest Low: It computes the highest high (75th percentile high price of the longest period) and lowest low (25th percentile low price of the longest period), referred to as highest_high and lowest_low. These values establish critical price levels.
Trend Strength Conditions: For each percentile and period, the code checks if the percentile exceeds the highest high (trendBull) or falls below the lowest low (trendBear). These conditions gauge the strength of bullish and bearish trends.
Count Bull and Count Bear: Variables countBull and countBear tally the number of bullish and bearish conditions met, helping assess trend strength.
Weak Bull and Weak Bear Count: The code calculates weak bullish and bearish conditions, occurring when percentiles fall within the range defined by highest_high and lowest_low but don't meet strong trend criteria.
Bull Strength and Bear Strength: bullStrength and bearStrength are calculated based on counts of bullish, bearish, weak bullish, and weak bearish conditions, representing overall trend strength.
Strong Bull and Bear Conditions: These conditions arise when the 75th percentile of high prices (bull conditions) or the 25th percentile of low prices (bear conditions) surpass or dip below the highest high or lowest low, respectively, for the specified period. Strong conditions indicate robust trends with significant price movements.
Weak Bull and Bear Conditions: Weak conditions occur when percentiles fall within the range between highest_high and lowest_low, suggesting some bullish or bearish tendencies without reaching extreme levels. These imply less decisive trends.
Current Trend Identification: The current trend is determined by comparing bullStrength and bearStrength. A greater bullStrength indicates a Bull trend, greater bearStrength implies a Bear trend, and equal values denote No Trend (N/A).
Tribute to David PaulI made this indicator as a tribute to the late David Paul .
He mentioned quite a lot about 89 periods moving average (especially on 4h), also the 21 and 55.
I put up some entries when three ma are crossed by price in the same direction, bull/bear backgrounds and a color code for candles because who doesn't love the feeling of a lasting trend.
To be more specific :
The indicator plots sma21, sma55, sma89 and AMA = (sma21+sma55+sma89)/3
When the closing price crosses the highest of the 3 sma, it is considered a bullish confirmation.
At this moment two lines appear, one on the bottom of the candle that crossed, one on the crossing point.
The lowest line can be used as the stop loss value of a long.
The highest line can be used as an entry point for a long.
When the closing price crosses the lowest of the 3 sma, it is considered a bearish confirmation.
At this moment two lines appear, one on the top of the candle that crossed, one on the crossing point.
The highest line can be used as the stop loss value of a short.
The lowest line can be used as an entry point for shorts.
When the closing price is above AMA, it is considered a bullish confirmation.
At this time a blue background appears at the crossing point.
The highest line can be used as the stop loss value for a long.
The starting point of the background can be used as the entry point for a long.
When the closing price is below AMA, it is considered a bearish confirmation.
At this time a red background appears at the crossing point.
The highest line can be used as the stop loss value for a short.
The starting point of the background can be used as the entry point for a short.
When the price is above 3 sma the candles turn blue. Signifying an upward trend.
When the price is below 3 sma the candles turn red. Signifying a bearish trend.
When the price is neither simultaneously above nor below the 3 sma, the candles are gray and the background linked to AMA becomes less vivid. Meaning a loss of vitality of the current trend or an absence of a clear trend.
Ideally, you should take a position towards "Real Long/Short Entry", set your stop loss towards "Ideal Long/Short Entry", and close the trade either when the background ends (riskier but more potential), or when the candles become gray (more conservative but noisier).
In the inputs, you can modify the display rules (explained in the tooltips), by default everything is displayed.
Percentile Based Trend StrengthThe "Percentile Based Trend Strength" (PBTS) calculates trend strength based on percentile values of high and low prices for various length periods and then identifies the current trend as either Bullish, Bearish, or N/A (No Trend). Here's a step-by-step explanation of the code:
Percentile Calculations:
For each specified length period (13, 21, 34, 55, 89, and 144 - Fibonacci numbers), the code calculates the 75th percentile of high prices (e.g., percentile_13H) and the 25th percentile of low prices (e.g., percentile_13L). These percentiles represent levels that prices need to exceed or fall below to indicate a strong trend.
Calculate Highest High and Lowest Low:
The highest high (75th percentile high price of longest length) and lowest low (25th percentile low price of longest length) for the longest length period (144) are calculated as highest_high and lowest_low. These values represent threshold price levels .
Trend Strength Conditions:
The code calculates various conditions to determine trend strength. For each percentile value and each length period, it checks if the percentile value is greater than the highest high (trendBull) or less than the lowest low (trendBear). These conditions are used to assess the strength of the bullish and bearish trends.
Count Bull and Count Bear:
The countBull and countBear variables count the number of bullish and bearish conditions met, respectively. These counts help evaluate trend strength.
Weak Bull and Weak Bear Count:
The code calculates the number of weak bullish and bearish conditions. Weak conditions occur when a percentile value falls within the range defined by the highest high and lowest low but doesn't meet the strong trend criteria.
Bull Strength and Bear Strength:
bullStrength and bearStrength are calculated based on the counts of bullish, bearish, weak bullish, and weak bearish conditions. These values represent the overall strength of the bullish and bearish trends.
Strong Bull and Bear Conditions:
These conditions occur when the 75th percentile of high prices (for bull conditions) or the 25th percentile of low prices (for bear conditions) exceeds or falls below the highest high or lowest low, respectively, for the specified length period.
Strong bull conditions indicate a strong upward trend, while strong bear conditions indicate a strong downward trend.
Strong conditions are indicative of more significant price movements and are considered as primary signals of trend strength.
Weak Bull and Bear Conditions:
Weak bull and bear conditions are more nuanced. They occur when the 75th percentile of high prices (for weak bull conditions) or the 25th percentile of low prices (for weak bear conditions) falls within the range defined by the highest high and lowest low for the specified length period.
In other words, prices are not strong enough to reach the extreme levels represented by the highest high or lowest low, but they still exhibit some bullish or bearish tendencies within that range.
Weak conditions suggest a less robust trend. They may indicate that while there is some bias toward a bullish or bearish trend, it is not as strong or decisive as in the case of strong conditions.
Current Trend Identification:
The current trend is determined by comparing bullStrength and bearStrength. If bullStrength is greater, it's considered a Bull trend; if bearStrength is greater, it's a Bear trend. If they are equal, the trend is identified as N/A (No Trend).
Displaying Trend Information:
The code creates a table to display the current trend, reversal probability (strength), count of bullish and bearish conditions, weak bullish and weak bearish counts, and colors the text accordingly.
Plotting Percentiles:
Finally, the code plots the percentile lines for visualization, with 20% transparency. It also plots the highest high and lowest low lines (75th and 25th percentile of the longest length 144) using their original colors.
In summary, this indicator calculates trend strength based on percentile levels of high and low prices for different length periods. It then counts the number of bullish and bearish conditions, factors in weak conditions, and compares the strengths to identify the current trend as Bullish, Bearish, or No Trend. It provides a table with trend information and visualizes percentile lines on the chart.
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
