Hellenic EMA Matrix - Α Ω PremiumHellenic EMA Matrix - Alpha Omega Premium
Complete User Guide
Table of Contents
Introduction
Indicator Philosophy
Mathematical Constants
EMA Types
Settings
Trading Signals
Visualization
Usage Strategies
FAQ
Introduction
Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market.
Key Features:
6 EMA types based on mathematical constants
Premium visualization with Neon Glow and Gradient Clouds
Automatic Fast/Mid/Slow EMA sorting
STRONG signals for powerful trends
Pulsing Ribbon Bar for instant trend assessment
Works on all timeframes (M1 - MN)
Indicator Philosophy
Why Mathematical Constants?
Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature:
Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions
Pi (3.14159) - Pi: circles, waves, cycles
e (2.71828) - Natural logarithm base: exponential growth, radioactive decay
Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles.
Mathematical Constants
Phi (Phi) - Golden Ratio
Phi = 1.618033988749895
Properties:
Phi² = Phi + 1 = 2.618
Phi³ = 4.236
Phi⁴ = 6.854
Application: Ideal for trending movements and Fibonacci corrections
Pi (Pi) - Pi Number
Pi = 3.141592653589793
Properties:
2Pi = 6.283 (full circle)
3Pi = 9.425
4Pi = 12.566
Application: Excellent for cyclical markets and wave structures
e (Euler) - Euler's Number
e = 2.718281828459045
Properties:
e² = 7.389
e³ = 20.085
e⁴ = 54.598
Application: Suitable for exponential movements and volatile markets
EMA Types
1. Phi (Phi) - Golden Ratio EMA
Description: EMA based on the golden ratio
Period Formula:
Period = Phi^n × Base Multiplier
Parameters:
Phi Power Level (1-8): Power of Phi
Phi¹ = 1.618 → ~16 period (with Base=10)
Phi² = 2.618 → ~26 period
Phi³ = 4.236 → ~42 period (recommended)
Phi⁴ = 6.854 → ~69 period
Recommendations:
Phi² or Phi³ for day trading
Phi⁴ or Phi⁵ for swing trading
Works excellently as Fast EMA
2. Pi (Pi) - Circular EMA
Description: EMA based on Pi for cyclical movements
Period Formula:
Period = Pi × Multiple × Base Multiplier
Parameters:
Pi Multiple (1-10): Pi multiplier
1Pi = 3.14 → ~31 period (with Base=10)
2Pi = 6.28 → ~63 period (recommended)
3Pi = 9.42 → ~94 period
Recommendations:
2Pi ideal as Mid or Slow EMA
Excellently identifies cycles and waves
Use on volatile markets (crypto, forex)
3. e (Euler) - Natural EMA
Description: EMA based on natural logarithm
Period Formula:
Period = e^n × Base Multiplier
Parameters:
e Power Level (1-6): Power of e
e¹ = 2.718 → ~27 period (with Base=10)
e² = 7.389 → ~74 period (recommended)
e³ = 20.085 → ~201 period
Recommendations:
e² works excellently as Slow EMA
Ideal for stocks and indices
Filters noise well on lower timeframes
4. Delta (Delta) - Adaptive EMA
Description: Adaptive EMA that changes period based on volatility
Period Formula:
Period = Base Period × (1 + (Volatility - 1) × Factor)
Parameters:
Delta Base Period (5-200): Base period (default 20)
Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0)
How it works:
During low volatility → period decreases → EMA reacts faster
During high volatility → period increases → EMA smooths noise
Recommendations:
Works excellently on news and sharp movements
Use as Fast EMA for quick adaptation
Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks
5. Sigma (Sigma) - Composite EMA
Description: Composite EMA combining multiple active EMAs
Composition Methods:
Weighted Average (default):
Sigma = (Phi + Pi + e + Delta) / 4
Simple average of all active EMAs
Geometric Mean:
Sigma = fourth_root(Phi × Pi × e × Delta)
Geometric mean (more conservative)
Harmonic Mean:
Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta)
Harmonic mean (more weight to smaller values)
Recommendations:
Enable for additional confirmation
Use as Mid EMA
Weighted Average - most universal method
6. Lambda (Lambda) - Wave EMA
Description: Wave EMA with sinusoidal period modulation
Period Formula:
Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency))
Parameters:
Lambda Base Period (10-200): Base period
Lambda Wave Amplitude (0.1-2.0): Wave amplitude
Lambda Wave Frequency (10-200): Wave frequency in bars
How it works:
Period pulsates sinusoidally
Creates wave effect following market cycles
Recommendations:
Experimental EMA for advanced users
Works well on cyclical markets
Frequency = 50 for day trading, 100+ for swing
Settings
Matrix Core Settings
Base Multiplier (1-100)
Multiplies all EMA periods
Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7)
Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74)
Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148)
Recommendations by timeframe:
M1-M5: Base = 5-10
M15-H1: Base = 10-15 (recommended)
H4-D1: Base = 15-25
W1-MN: Base = 25-50
Matrix Source
Data source selection for EMA calculation:
close - closing price (standard)
open - opening price
high - high
low - low
hl2 - (high + low) / 2
hlc3 - (high + low + close) / 3
ohlc4 - (open + high + low + close) / 4
When to change:
hlc3 or ohlc4 for smoother signals
high for aggressive longs
low for aggressive shorts
Manual EMA Selection
Critically important setting! Determines which EMAs are used for signal generation.
Use Manual Fast/Slow/Mid Selection
Enabled (default): You select EMAs manually
Disabled: Automatic selection by periods
Fast EMA
Fast EMA - reacts first to price changes
Recommendations:
Phi Golden (recommended) - universal choice
Delta Adaptive - for volatile markets
Must be fastest (smallest period)
Slow EMA
Slow EMA - determines main trend
Recommendations:
Pi Circular (recommended) - excellent trend filter
e Natural - for smoother trend
Must be slowest (largest period)
Mid EMA
Mid EMA - additional signal filter
Recommendations:
e Natural (recommended) - excellent middle level
Pi Circular - alternative
None - for more frequent signals (only 2 EMAs)
IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods:
Fast = EMA with smallest period
Mid = EMA with middle period
Slow = EMA with largest period
Therefore, you can select any combination - the indicator will arrange them correctly!
Premium Visualization
Neon Glow
Enable Neon Glow for EMAs - adds glowing effect around EMA lines
Glow Strength:
Light - subtle glow
Medium (recommended) - optimal balance
Strong - bright glow (may be too bright)
Effect: 2 glow layers around each EMA for 3D effect
Gradient Clouds
Enable Gradient Clouds - fills space between EMAs with gradient
Parameters:
Cloud Transparency (85-98): Cloud transparency
95-97 (recommended)
Higher = more transparent
Dynamic Cloud Intensity - automatically changes transparency based on EMA distance
Cloud Colors:
Phi-Pi Cloud:
Blue - when Pi above Phi (bullish)
Gold - when Phi above Pi (bearish)
Pi-e Cloud:
Green - when e above Pi (bullish)
Blue - when Pi above e (bearish)
2 layers for volumetric effect
Pulsing Ribbon Bar
Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart
Parameters:
Ribbon Position: Top / Bottom (recommended)
Pulse Speed: Slow / Medium (recommended) / Fast
Symbols and colors:
Green filled square - STRONG BULLISH
Pink filled square - STRONG BEARISH
Blue hollow square - Bullish (regular)
Red hollow square - Bearish (regular)
Purple rectangle - Neutral
Effect: Pulsation with sinusoid for living market feel
Signal Bar Highlights
Enable Signal Bar Highlights - highlights bars with signals
Parameters:
Highlight Transparency (88-96): Highlight transparency
Highlight Style:
Light Fill (recommended) - bar background fill
Thin Line - bar outline only
Highlights:
Golden Cross - green
Death Cross - pink
STRONG BUY - green
STRONG SELL - pink
Show Greek Labels
Shows Greek alphabet letters on last bar:
Phi - Phi EMA (gold)
Pi - Pi EMA (blue)
e - Euler EMA (green)
Delta - Delta EMA (purple)
Sigma - Sigma EMA (pink)
When to use: For education or presentations
Show Old Background
Old background style (not recommended):
Green background - STRONG BULLISH
Pink background - STRONG BEARISH
Blue background - Bullish
Red background - Bearish
Not recommended - use new Gradient Clouds and Pulsing Bar
Info Table
Show Info Table - table with indicator information
Parameters:
Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right
Size: Tiny / Small (recommended) / Normal / Large
Table contents:
EMA list - periods and current values of all active EMAs
Effects - active visual effects
TREND - current trend state:
STRONG UP - strong bullish
STRONG DOWN - strong bearish
Bullish - regular bullish
Bearish - regular bearish
Neutral - neutral
Momentum % - percentage deviation of price from Fast EMA
Setup - current Fast/Slow/Mid configuration
Trading Signals
Show Golden/Death Cross
Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal)
Symbols:
Yellow dot "GC" below - Golden Cross
Dark red dot "DC" above - Death Cross
Show STRONG Signals
STRONG BUY and STRONG SELL - the most powerful indicator signals
Conditions for STRONG BULLISH:
EMA Alignment: Fast > Mid > Slow (all EMAs aligned)
Trend: Fast > Slow (clear uptrend)
Distance: EMAs separated by minimum 0.15%
Price Position: Price above Fast EMA
Fast Slope: Fast EMA rising
Slow Slope: Slow EMA rising
Mid Trending: Mid EMA also rising (if enabled)
Conditions for STRONG BEARISH:
Same but in reverse
Visual display:
Green label "STRONG BUY" below bar
Pink label "STRONG SELL" above bar
Difference from Golden/Death Cross:
Golden/Death Cross = crossing moment (1 bar)
STRONG signal = sustained trend (lasts several bars)
IMPORTANT: After fixes, STRONG signals now:
Work on all timeframes (M1 to MN)
Don't break on small retracements
Work with any Fast/Mid/Slow combination
Automatically adapt thanks to EMA sorting
Show Stop Loss/Take Profit
Automatic SL/TP level calculation on STRONG signal
Parameters:
Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss
1.5 (recommended) - standard
1.0 - tight stop
2.0-3.0 - wide stop
Take Profit R:R (1.0-5.0): Risk/reward ratio
2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR)
1.5 - conservative
3.0-5.0 - aggressive
Formulas:
LONG:
Stop Loss = Entry - (ATR × Stop Loss ATR)
Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R)
SHORT:
Stop Loss = Entry + (ATR × Stop Loss ATR)
Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R)
Visualization:
Red X - Stop Loss
Green X - Take Profit
Levels remain active while STRONG signal persists
Trading Signals
Signal Types
1. Golden Cross
Description: Fast EMA crosses Slow EMA from below
Signal: Beginning of bullish trend
How to trade:
ENTRY: On bar close with Golden Cross
STOP: Below local low or below Slow EMA
TARGET: Next resistance level or 2:1 R:R
Strengths:
Simple and clear
Works well on trending markets
Clear entry point
Weaknesses:
Lags (signal after movement starts)
Many false signals in ranging markets
May be late on fast moves
Optimal timeframes: H1, H4, D1
2. Death Cross
Description: Fast EMA crosses Slow EMA from above
Signal: Beginning of bearish trend
How to trade:
ENTRY: On bar close with Death Cross
STOP: Above local high or above Slow EMA
TARGET: Next support level or 2:1 R:R
Application: Mirror of Golden Cross
3. STRONG BUY
Description: All EMAs aligned + trend + all EMAs rising
Signal: Powerful bullish trend
How to trade:
ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA
STOP: Below Fast EMA or automatic SL (if enabled)
TARGET: Automatic TP (if enabled) or by levels
TRAILING: Follow Fast EMA
Entry strategies:
Aggressive: Enter immediately on signal
Conservative: Wait for pullback to Fast EMA, then enter on bounce
Pyramiding: Add positions on pullbacks to Mid EMA
Position management:
Hold while STRONG signal active
Exit on STRONG SELL or Death Cross appearance
Move stop behind Fast EMA
Strengths:
Most reliable indicator signal
Doesn't break on pullbacks
Catches large moves
Works on all timeframes
Weaknesses:
Appears less frequently than other signals
Requires confirmation (multiple conditions)
Optimal timeframes: All (M5 - D1)
4. STRONG SELL
Description: All EMAs aligned down + downtrend + all EMAs falling
Signal: Powerful bearish trend
How to trade: Mirror of STRONG BUY
Visual Signals
Pulsing Ribbon Bar
Quick market assessment at a glance:
Symbol Color State
Filled square Green STRONG BULLISH
Filled square Pink STRONG BEARISH
Hollow square Blue Bullish
Hollow square Red Bearish
Rectangle Purple Neutral
Pulsation: Sinusoidal, creates living effect
Signal Bar Highlights
Bars with signals are highlighted:
Green highlight: STRONG BUY or Golden Cross
Pink highlight: STRONG SELL or Death Cross
Gradient Clouds
Colored space between EMAs shows trend strength:
Wide clouds - strong trend
Narrow clouds - weak trend or consolidation
Color change - trend change
Info Table
Quick reference in corner:
TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN)
Momentum %: Movement strength
Effects: Active visual effects
Setup: Fast/Slow/Mid configuration
Usage Strategies
Strategy 1: "Golden Trailing"
Idea: Follow STRONG signals using Fast EMA as trailing stop
Settings:
Fast: Phi Golden (Phi³)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
Wait for STRONG BUY
Enter on bar close or on pullback to Fast EMA
Stop below Fast EMA
Management:
Hold position while STRONG signal active
Move stop behind Fast EMA daily
Exit on STRONG SELL or Death Cross
Take Profit:
Partially close at +2R
Trail remainder until exit signal
For whom: Swing traders, trend followers
Pros:
Catches large moves
Simple rules
Emotionally comfortable
Cons:
Requires patience
Possible extended drawdowns on pullbacks
Strategy 2: "Scalping Bounces"
Idea: Scalp bounces from Fast EMA during STRONG trend
Settings:
Fast: Delta Adaptive (Base 15, Sensitivity 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base Multiplier: 5
Timeframe: M5, M15
Entry rules:
STRONG signal must be active
Wait for price pullback to Fast EMA
Enter on bounce (candle closes above/below Fast EMA)
Stop behind local extreme (15-20 pips)
Take Profit:
+1.5R or to Mid EMA
Or to next level
For whom: Active day traders
Pros:
Many signals
Clear entry point
Quick profits
Cons:
Requires constant monitoring
Not all bounces work
Requires discipline for frequent trading
Strategy 3: "Triple Filter"
Idea: Enter only when all 3 EMAs and price perfectly aligned
Settings:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi)
Base Multiplier: 15
Timeframe: H4, D1
Entry rules (LONG):
STRONG BUY active
Price above all three EMAs
Fast > Mid > Slow (all aligned)
All EMAs rising (slope up)
Gradient Clouds wide and bright
Entry:
On bar close meeting all conditions
Or on next pullback to Fast EMA
Stop:
Below Mid EMA or -1.5 ATR
Take Profit:
First target: +3R
Second target: next major level
Trailing: Mid EMA
For whom: Conservative swing traders, investors
Pros:
Very reliable signals
Minimum false entries
Large profit potential
Cons:
Rare signals (2-5 per month)
Requires patience
Strategy 4: "Adaptive Scalper"
Idea: Use only Delta Adaptive EMA for quick volatility reaction
Settings:
Fast: Delta Adaptive (Base 10, Sensitivity 3.0)
Mid: None
Slow: Delta Adaptive (Base 30, Sensitivity 2.0)
Base Multiplier: 3
Timeframe: M1, M5
Feature: Two different Delta EMAs with different settings
Entry rules:
Golden Cross between two Delta EMAs
Both Delta EMAs must be rising/falling
Enter on next bar
Stop:
10-15 pips or below Slow Delta EMA
Take Profit:
+1R to +2R
Or Death Cross
For whom: Scalpers on cryptocurrencies and forex
Pros:
Instant volatility adaptation
Many signals on volatile markets
Quick results
Cons:
Much noise on calm markets
Requires fast execution
High commissions may eat profits
Strategy 5: "Cyclical Trader"
Idea: Use Pi and Lambda for trading cyclical markets
Settings:
Fast: Pi Circular (1Pi)
Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50)
Slow: Pi Circular (3Pi)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
STRONG signal active
Lambda Wave EMA synchronized with trend
Enter on bounce from Lambda Wave
For whom: Traders of cyclical assets (some altcoins, commodities)
Pros:
Catches cyclical movements
Lambda Wave provides additional entry points
Cons:
More complex to configure
Not for all markets
Lambda Wave may give false signals
Strategy 6: "Multi-Timeframe Confirmation"
Idea: Use multiple timeframes for confirmation
Scheme:
Higher TF (D1): Determine trend direction (STRONG signal)
Middle TF (H4): Wait for STRONG signal in same direction
Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA)
Settings for all TFs:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base Multiplier: 10
Rules:
All 3 TFs must show one trend
Entry on lower TF
Stop by lower TF
Target by higher TF
For whom: Serious traders and investors
Pros:
Maximum reliability
Large profit targets
Minimum false signals
Cons:
Rare setups
Requires analysis of multiple charts
Experience needed
Practical Tips
DOs
Use STRONG signals as primary - they're most reliable
Let signals develop - don't exit on first pullback
Use trailing stop - follow Fast EMA
Combine with levels - S/R, Fibonacci, volumes
Test on demo before real
Adjust Base Multiplier for your timeframe
Enable visual effects - they help see the picture
Use Info Table - quick situation assessment
Watch Pulsing Bar - instant state indicator
Trust auto-sorting of Fast/Mid/Slow
DON'Ts
Don't trade against STRONG signal - trend is your friend
Don't ignore Mid EMA - it adds reliability
Don't use too small Base Multiplier on higher TFs
Don't enter on Golden Cross in range - check for trend
Don't change settings during open position
Don't forget risk management - 1-2% per trade
Don't trade all signals in row - choose best ones
Don't use indicator in isolation - combine with Price Action
Don't set too tight stops - let trade breathe
Don't over-optimize - simplicity = reliability
Optimal Settings by Asset
US Stocks (SPY, AAPL, TSLA)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 10-15
Timeframe: H4, D1
Features:
Use on daily for swing
STRONG signals very reliable
Works well on trending stocks
Forex (EUR/USD, GBP/USD)
Recommendation:
Fast: Delta Adaptive (Base 15, Sens 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base: 8-12
Timeframe: M15, H1, H4
Features:
Delta Adaptive works excellently on news
Many signals on M15-H1
Consider spreads
Cryptocurrencies (BTC, ETH, altcoins)
Recommendation:
Fast: Delta Adaptive (Base 10, Sens 3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M5, M15, H1
Features:
High volatility - adaptation needed
STRONG signals can last days
Be careful with scalping on M1-M5
Commodities (Gold, Oil)
Recommendation:
Fast: Pi Circular (1Pi)
Mid: Phi Golden (Phi³)
Slow: Pi Circular (3Pi)
Base: 12-18
Timeframe: H4, D1
Features:
Pi works excellently on cyclical commodities
Gold responds especially well to Phi
Oil volatile - use wide stops
Indices (S&P500, Nasdaq, DAX)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 15-20
Timeframe: H4, D1, W1
Features:
Very trending instruments
STRONG signals last weeks
Good for position trading
Alerts
The indicator supports 6 alert types:
1. Golden Cross
Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!"
When: Fast EMA crosses Slow EMA from below
2. Death Cross
Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!"
When: Fast EMA crosses Slow EMA from above
3. STRONG BULLISH
Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!"
When: All conditions for STRONG BUY met (first bar)
4. STRONG BEARISH
Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!"
When: All conditions for STRONG SELL met (first bar)
5. Bullish Ribbon
Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend"
When: EMAs aligned bullish + price above Fast EMA (less strict condition)
6. Bearish Ribbon
Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend"
When: EMAs aligned bearish + price below Fast EMA (less strict condition)
How to Set Up Alerts:
Open indicator on chart
Click on three dots next to indicator name
Select "Create Alert"
In "Condition" field select needed alert:
Golden Cross
Death Cross
STRONG BULLISH
STRONG BEARISH
Bullish Ribbon
Bearish Ribbon
Configure notification method:
Pop-up in browser
Email
SMS (in Premium accounts)
Push notifications in mobile app
Webhook (for automation)
Select frequency:
Once Per Bar Close (recommended) - once on bar close
Once Per Bar - during bar formation
Only Once - only first time
Click "Create"
Tip: Create separate alerts for different timeframes and instruments
FAQ
1. Why don't STRONG signals appear?
Possible reasons:
Incorrect Fast/Mid/Slow order
Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods
Base Multiplier too large
Solution: Reduce Base to 5-10 on lower timeframes
Market in range
Solution: STRONG signals appear only in trends - this is normal
Too strict EMA settings
Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10
Mid EMA too close to Fast or Slow
Solution: Select Mid EMA with period between Fast and Slow
2. How often should STRONG signals appear?
Normal frequency:
M1-M5: 5-15 signals per day (very active markets)
M15-H1: 2-8 signals per day
H4: 3-10 signals per week
D1: 2-5 signals per month
W1: 2-6 signals per year
If too many signals - market very volatile or Base too small
If too few signals - market in range or Base too large
4. What are the best settings for beginners?
Universal "out of the box" settings:
Matrix Core:
Base Multiplier: 10
Source: close
Phi Golden: Enabled, Power = 3
Pi Circular: Enabled, Multiple = 2
e Natural: Enabled, Power = 2
Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0
Manual Selection:
Fast: Phi Golden
Mid: e Natural
Slow: Pi Circular
Visualization:
Gradient Clouds: ON
Neon Glow: ON (Medium)
Pulsing Bar: ON (Medium)
Signal Highlights: ON (Light Fill)
Table: ON (Top Right, Small)
Signals:
Golden/Death Cross: ON
STRONG Signals: ON
Stop Loss: OFF (while learning)
Timeframe for learning: H1 or H4
5. Can I use only one EMA?
No, minimum 2 EMAs (Fast and Slow) for signal generation.
Mid EMA is optional:
With Mid EMA = more reliable but rarer signals
Without Mid EMA = more signals but less strict filtering
Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment
6. Does the indicator work on cryptocurrencies?
Yes, works excellently! Especially good on:
Bitcoin (BTC)
Ethereum (ETH)
Major altcoins (SOL, BNB, XRP)
Recommended settings for crypto:
Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M15, H1, H4
Crypto market features:
High volatility → use Delta Adaptive
24/7 trading → set alerts
Sharp movements → wide stops
7. Can I trade only with this indicator?
Technically yes, but NOT recommended.
Best approach - combine with:
Price Action - support/resistance levels, candle patterns
Volume - movement strength confirmation
Fibonacci - retracement and extension levels
RSI/MACD - divergences and overbought/oversold
Fundamental analysis - news, company reports
Hellenic Matrix:
Excellently determines trend and its strength
Provides clear entry/exit points
Doesn't consider fundamentals
Doesn't see major levels
8. Why do Gradient Clouds change color?
Color depends on EMA order:
Phi-Pi Cloud:
Blue - Pi EMA above Phi EMA (bullish alignment)
Gold - Phi EMA above Pi EMA (bearish alignment)
Pi-e Cloud:
Green - e EMA above Pi EMA (bullish alignment)
Blue - Pi EMA above e EMA (bearish alignment)
Color change = EMA order change = possible trend change
9. What is Momentum % in the table?
Momentum % = percentage deviation of price from Fast EMA
Formula:
Momentum = ((Close - Fast EMA) / Fast EMA) × 100
Interpretation:
+0.5% to +2% - normal bullish momentum
+2% to +5% - strong bullish momentum
+5% and above - overheating (correction possible)
-0.5% to -2% - normal bearish momentum
-2% to -5% - strong bearish momentum
-5% and below - oversold (bounce possible)
Usage:
Monitor momentum during STRONG signals
Large momentum = don't enter (wait for pullback)
Small momentum = good entry point
10. How to configure for scalping?
Settings for scalping (M1-M5):
Base Multiplier: 3-5
Source: close or hlc3 (smoother)
Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0)
Mid: None (for more signals)
Slow: Phi Golden (Phi²) or Pi Circular (1Pi)
Visualization:
- Gradient Clouds: ON (helps see strength)
- Neon Glow: OFF (doesn't clutter chart)
- Pulsing Bar: ON (quick assessment)
- Signal Highlights: ON
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0)
Scalping rules:
Trade only STRONG signals
Enter on bounce from Fast EMA
Tight stops (10-20 pips)
Quick take profit (+1R to +2R)
Don't hold through news
11. How to configure for long-term investing?
Settings for investing (D1-W1):
Base Multiplier: 20-30
Source: close
Fast: Phi Golden (Phi³ or Phi⁴)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi or 4Pi)
Visualization:
- Gradient Clouds: ON
- Neon Glow: ON (Medium)
- Everything else - to taste
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: OFF (use percentage stop)
Investing rules:
Enter only on STRONG signals
Hold while STRONG active (weeks/months)
Stop below Slow EMA or -10%
Take profit: by company targets or +50-100%
Ignore short-term pullbacks
12. What if indicator slows down chart?
Indicator is optimized, but if it slows:
Disable unnecessary visual effects:
Neon Glow: OFF (saves 8 plots)
Gradient Clouds: ON but low quality
Lambda Wave EMA: OFF (if not using)
Reduce number of active EMAs:
Sigma Composite: OFF
Lambda Wave: OFF
Leave only Phi, Pi, e, Delta
Simplify settings:
Pulsing Bar: OFF
Greek Labels: OFF
Info Table: smaller size
13. Can I use on different timeframes simultaneously?
Yes! Multi-timeframe analysis is very powerful:
Classic scheme:
Higher TF (D1, W1) - determine global trend
Wait for STRONG signal
This is our trading direction
Middle TF (H4, H1) - look for confirmation
STRONG signal in same direction
Precise entry zone
Lower TF (M15, M5) - entry point
Golden Cross or bounce from Fast EMA
Precise stop loss
Example:
W1: STRONG BUY active (global uptrend)
H4: STRONG BUY appeared (confirmation)
M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY
Advantages:
Maximum reliability
Clear timeframe hierarchy
Large targets
14. How does indicator work on news?
Delta Adaptive EMA adapts excellently to news:
Before news:
Low volatility → Delta EMA becomes fast → pulls to price
During news:
Sharp volatility spike → Delta EMA slows → filters noise
After news:
Volatility normalizes → Delta EMA returns to normal
Recommendations:
Don't trade at news release moment (spreads widen)
Wait for STRONG signal after news (2-5 bars)
Use Delta Adaptive as Fast EMA for quick reaction
Widen stops by 50-100% during important news
Advanced Techniques
Technique 1: "Divergences with EMA"
Idea: Look for discrepancies between price and Fast EMA
Bullish divergence:
Price makes lower low
Fast EMA makes higher low
= Possible reversal up
Bearish divergence:
Price makes higher high
Fast EMA makes lower high
= Possible reversal down
How to trade:
Find divergence
Wait for STRONG signal in divergence direction
Enter on confirmation
Technique 2: "EMA Tunnel"
Idea: Use space between Fast and Slow EMA as "tunnel"
Rules:
Wide tunnel - strong trend, hold position
Narrow tunnel - weak trend or consolidation, caution
Tunnel narrowing - trend weakening, prepare to exit
Tunnel widening - trend strengthening, can add
Visually: Gradient Clouds show this automatically!
Trading:
Enter on STRONG signal (tunnel starts widening)
Hold while tunnel wide
Exit when tunnel starts narrowing
Technique 3: "Wave Analysis with Lambda"
Idea: Lambda Wave EMA creates sinusoid matching market cycles
Setup:
Lambda Base Period: 30
Lambda Wave Amplitude: 0.5
Lambda Wave Frequency: 50 (adjusted to asset cycle)
How to find correct Frequency:
Look at historical cycles (distance between local highs)
Average distance = your Frequency
Example: if highs every 40-60 bars, set Frequency = 50
Trading:
Enter when Lambda Wave at bottom of sinusoid (growth potential)
Exit when Lambda Wave at top (fall potential)
Combine with STRONG signals
Technique 4: "Cluster Analysis"
Idea: When all EMAs gather in narrow cluster = powerful breakout soon
Cluster signs:
All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other
Gradient Clouds almost invisible
Price jumping around all EMAs
Trading:
Identify cluster (all EMAs close)
Determine breakout direction (where more volume, higher TFs direction)
Wait for breakout and STRONG signal
Enter on confirmation
Target = cluster size × 3-5
This is very powerful technique for big moves!
Technique 5: "Sigma as Dynamic Level"
Idea: Sigma Composite EMA = average of all EMAs = magnetic level
Usage:
Enable Sigma Composite (Weighted Average)
Sigma works as dynamic support/resistance
Price often returns to Sigma before trend continuation
Trading:
In trend: Enter on bounces from Sigma
In range: Fade moves from Sigma (trade return to Sigma)
On breakout: Sigma becomes support/resistance
Risk Management
Basic Rules
1. Position Size
Conservative: 1% of capital per trade
Moderate: 2% of capital per trade (recommended)
Aggressive: 3-5% (only for experienced)
Calculation formula:
Lot Size = (Capital × Risk%) / (Stop in pips × Pip value)
2. Risk/Reward Ratio
Minimum: 1:1.5
Standard: 1:2 (recommended)
Optimal: 1:3
Aggressive: 1:5+
3. Maximum Drawdown
Daily: -3% to -5%
Weekly: -7% to -10%
Monthly: -15% to -20%
Upon reaching limit → STOP trading until end of period
Position Management Strategies
1. Fixed Stop
Method:
Stop below/above Fast EMA or local extreme
DON'T move stop against position
Can move to breakeven
For whom: Beginners, conservative traders
2. Trailing by Fast EMA
Method:
Each day (or bar) move stop to Fast EMA level
Position closes when price breaks Fast EMA
Advantages:
Stay in trend as long as possible
Automatically exit on reversal
For whom: Trend followers, swing traders
3. Partial Exit
Method:
50% of position close at +2R
50% hold with trailing by Mid EMA or Slow EMA
Advantages:
Lock profit
Leave position for big move
Psychologically comfortable
For whom: Universal method (recommended)
4. Pyramiding
Method:
First entry on STRONG signal (50% of planned position)
Add 25% on pullback to Fast EMA
Add another 25% on pullback to Mid EMA
Overall stop below Slow EMA
Advantages:
Average entry price
Reduce risk
Increase profit in strong trends
Caution:
Works only in trends
In range leads to losses
For whom: Experienced traders
Trading Psychology
Correct Mindset
1. Indicator is a tool, not holy grail
Indicator shows probability, not guarantee
There will be losing trades - this is normal
Important is series statistics, not one trade
2. Trust the system
If STRONG signal appeared - enter
Don't search for "perfect" moment
Follow trading plan
3. Patience
STRONG signals don't appear every day
Better miss signal than enter against trend
Quality over quantity
4. Discipline
Always set stop loss
Don't move stop against position
Don't increase risk after losses
Beginner Mistakes
1. "I know better than indicator"
Indicator says STRONG BUY, but you think "too high, will wait for pullback"
Result: miss profitable move
Solution: Trust signals or don't use indicator
2. "Will reverse now for sure"
Trading against STRONG trend
Result: stops, stops, stops
Solution: Trend is your friend, trade with trend
3. "Will hold a bit more"
Don't exit when STRONG signal disappears
Greed eats profit
Solution: If signal gone - exit!
4. "I'll recover"
After losses double risk
Result: huge losses
Solution: Fixed % risk ALWAYS
5. "I don't like this signal"
Skip signals because of "feeling"
Result: inconsistency, no statistics
Solution: Trade ALL signals or clearly define filters
Trading Journal
What to Record
For each trade:
1. Entry/exit date and time
2. Instrument and timeframe
3. Signal type
Golden Cross
STRONG BUY
STRONG SELL
Death Cross
4. Indicator settings
Fast/Mid/Slow EMA
Base Multiplier
Other parameters
5. Chart screenshot
Entry moment
Exit moment
6. Trade parameters
Position size
Stop loss
Take Profit
R:R
7. Result
Profit/Loss in $
Profit/Loss in %
Profit/Loss in R
8. Notes
What was right
What was wrong
Emotions during trade
Lessons
Journal Analysis
Analyze weekly:
1. Win Rate
Win Rate = (Profitable trades / All trades) × 100%
Good: 50-60%
Excellent: 60-70%
Exceptional: 70%+
2. Average R
Average R = Sum of all R / Number of trades
Good: +0.5R
Excellent: +1.0R
Exceptional: +1.5R+
3. Profit Factor
Profit Factor = Total profit / Total losses
Good: 1.5+
Excellent: 2.0+
Exceptional: 3.0+
4. Maximum Drawdown
Track consecutive losses
If more than 5 in row - stop, check system
5. Best/Worst Trades
What was common in best trades? (do more)
What was common in worst trades? (avoid)
Pre-Trade Checklist
Technical Analysis
STRONG signal active (BUY or SELL)
All EMAs properly aligned (Fast > Mid > Slow or reverse)
Price on correct side of Fast EMA
Gradient Clouds confirm trend
Pulsing Bar shows STRONG state
Momentum % in normal range (not overheated)
No close strong levels against direction
Higher timeframe doesn't contradict
Risk Management
Position size calculated (1-2% risk)
Stop loss set
Take profit calculated (minimum 1:2)
R:R satisfactory
Daily/weekly risk limit not exceeded
No other open correlated positions
Fundamental Analysis
No important news in coming hours
Market session appropriate (liquidity)
No contradicting fundamentals
Understand why asset is moving
Psychology
Calm and thinking clearly
No emotions from previous trades
Ready to accept loss at stop
Following trading plan
Not revenging market for past losses
If at least one point is NO - think twice before entering!
Learning Roadmap
Week 1: Familiarization
Goals:
Install and configure indicator
Study all EMA types
Understand visualization
Tasks:
Add indicator to chart
Test all Fast/Mid/Slow settings
Play with Base Multiplier on different timeframes
Observe Gradient Clouds and Pulsing Bar
Study Info Table
Result: Comfort with indicator interface
Week 2: Signals
Goals:
Learn to recognize all signal types
Understand difference between Golden Cross and STRONG
Tasks:
Find 10 Golden Cross examples in history
Find 10 STRONG BUY examples in history
Compare their results (which worked better)
Set up alerts
Get 5 real alerts
Result: Understanding signals
Week 3: Demo Trading
Goals:
Start trading signals on demo account
Gather statistics
Tasks:
Open demo account
Trade ONLY STRONG signals
Keep journal (minimum 20 trades)
Don't change indicator settings
Strictly follow stop losses
Result: 20+ documented trades
Week 4: Analysis
Goals:
Analyze demo trading results
Optimize approach
Tasks:
Calculate win rate and average R
Find patterns in profitable trades
Find patterns in losing trades
Adjust approach (not indicator!)
Write trading plan
Result: Trading plan on 1 page
Month 2: Improvement
Goals:
Deepen understanding
Add additional techniques
Tasks:
Study multi-timeframe analysis
Test combinations with Price Action
Try advanced techniques (divergences, tunnels)
Continue demo trading (minimum 50 trades)
Achieve stable profitability on demo
Result: Win rate 55%+ and Profit Factor 1.5+
Month 3: Real Trading
Goals:
Transition to real account
Maintain discipline
Tasks:
Open small real account
Trade minimum lots
Strictly follow trading plan
DON'T increase risk
Focus on process, not profit
Result: Psychological comfort on real
Month 4+: Scaling
Goals:
Increase account
Become consistently profitable
Tasks:
With 60%+ win rate can increase risk to 2%
Upon doubling account can add capital
Continue keeping journal
Periodically review and improve strategy
Share experience with community
Result: Stable profitability month after month
Additional Resources
Recommended Reading
Technical Analysis:
"Technical Analysis of Financial Markets" - John Murphy
"Trading in the Zone" - Mark Douglas (psychology)
"Market Wizards" - Jack Schwager (trader interviews)
EMA and Moving Averages:
"Moving Averages 101" - Steve Burns
Articles on Investopedia about EMA
Risk Management:
"The Mathematics of Money Management" - Ralph Vince
"Trade Your Way to Financial Freedom" - Van K. Tharp
Trading Journals:
Edgewonk (paid, very powerful)
Tradervue (free version + premium)
Excel/Google Sheets (free)
Screeners:
TradingView Stock Screener
Finviz (stocks)
CoinMarketCap (crypto)
Conclusion
Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines:
Mathematical elegance - Phi, Pi, e instead of arbitrary numbers
Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar
Reliable signals - STRONG BUY/SELL work on all timeframes
Flexibility - 6 EMA types, adaptation to any trading style
Automation - auto-sorting EMAs, SL/TP calculation, alerts
Key Success Principles:
Simplicity - start with basic settings (Phi/Pi/e, Base=10)
Discipline - follow STRONG signals strictly
Patience - wait for quality setups
Risk Management - 1-2% per trade, ALWAYS
Journal - document every trade
Learning - constantly improve skills
Remember:
Indicator shows probability, not guarantee
Important is series statistics, not one trade
Psychology more important than technique
Quality more important than quantity
Process more important than result
Acknowledgments
Thank you for using Hellenic EMA Matrix - Alpha Omega Premium!
The indicator was created with love for mathematics, markets, and beautiful visualization.
Wishing you profitable trading!
Guide Version: 1.0
Date: 2025
Compatibility: Pine Script v6, TradingView
"In the simplicity of mathematical constants lies the complexity of market movements"
Signals
Buy/Sell Signals [WynTrader]My name is WynTrader. I cumulate 24 years of experience.
This Indicator produces Buy/Sell Signals using these features:
- Fast and Slow Moving averages (modifiable) optimized at EMA-8 and SMA-35
- Bollinger Bands (modifiable) optimized at Basis-18 and Multiplier-1
Also, the Buy/Sell Signals are conditioned by three Filters (optionable, modifiable) :
. Bollinger-Bands Lookback
. High-Low vs Candle Range %
. Distance from Fast and Slow Moving averages %
The Results Calculation presented in a Table are based :
- on the Current Chart Visible Range (optionable)
or
- on the specified TIme Frame Start and End Dates (modifiable)
The Table shows Calculation Results of the Buy and Sell Signals that are activated on the chart, with the Number of Trades (Signals), the Winning Points and the Win Rate %. The Buy&Hold starts calculation at the first Buy encountered.
So be surprised by my Buy/Sell Indicator. But always remember that the world is not perfect. The Graal Indicator, even with AI, doesn't already exist, maybe one day (all of us richier...), but not now. , depending on the chart product (stocks...), volatility, probabilities, unpredictable behaviour. , the moves, etc.
Enjoy
WynTrader
P. s. :
My name is WynTrader. I cumulate 24 years of experience. In 2001, I took an intensive technical analysis course taught by an exceptional friend, Cyril, who taught me everything I know. The foundation I gained through his teaching remains solid and relevant to this day, never failing me.
Before i made this Indicator, I have used many Trading View Buy/Sell Indicators using alone or combined RSI, SMI, OBV, MACD ATR, ADX, Neural, Fractal, Geometry, etc., that are already available for the Trading View community. A great thanks to those who give their time that help me build this tool.
Note that I'm not a programmer, so... ;-)
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
Andrei Marin4 EMA MTF (M5 + M30) – Buy/Sell on Close Above/Below🚀 4 EMA MTF (M5 + M30) — Trend Power Confirmation System
Catch the trend before it takes off.
This indicator fuses multi-timeframe momentum and precision trend alignment using 4 EMAs (2 from M5 + 2 from M30). When short- and mid-term trends lock in the same direction, you get clean, high-probability Buy and Sell signals — confirmed only on bar close, no repainting.
💡 The Concept
In trending markets, real consistency comes from multi-timeframe confluence.
This tool reads both your local M5 chart and the higher-timeframe M30 to detect moments when price breaks above or below all four EMAs — meaning both intraday and swing flows are aligned.
When the M5 and M30 EMAs agree, it’s not noise — it’s momentum.
✅ BUY → Price closes above all 4 EMAs
❌ SELL → Price closes below all 4 EMAs
🔒 No repaint: All conditions confirmed after bar close.
🔍 Features
🧭 4 EMA Fusion: EMA 20 & 50 on both M5 and M30 for double-layer confirmation.
⚡ Instant Visuals: Arrows mark fresh buy/sell signals only when trend alignment occurs.
🎨 Dynamic Background: Teal = bullish control, Red = bearish momentum.
🔔 Built-in Alerts: Receive instant notifications when new signals trigger.
🧩 Customizable: Change EMA lengths, higher-timeframe (HTF), or turn visuals on/off.
🧠 How It Works
Local EMAs (M5): Fast/Slow smoothing of short-term trend.
Higher-TF EMAs (M30): Pulled securely with request.security() and no repaint settings (lookahead_off).
Signals appear only once, when a new alignment is confirmed on close — eliminating fake flips.
⚙️ Inputs
Category Parameter Default Description
M5 Settings EMA rapide / EMA lente 20 / 50 Short-term trend layer
M30 Settings Timeframe HTF 30 Medium-term confirmation
M30 EMAs EMA rapide / EMA lente 20 / 50 Higher-timeframe trend filter
Display Show Labels / Background ON / ON Optional visuals
🧭 Why Traders Love It
🔹 Crystal-clear direction — no second guessing trend bias
🔹 No laggy repainting tricks — only confirmed data
🔹 Adaptable for all assets — Forex, Indices, Crypto, Metals
🔹 Perfect companion for scalpers and intraday swing traders
This is your trend alignment radar — simple, visual, and powerful.
🔔 Alerts
BUY ALERT: “Close above EMA20/50 (M5 + M30)”
SELL ALERT: “Close below EMA20/50 (M5 + M30)”
You can connect these alerts to bots, webhooks, or notifications — stay synced with every confirmed breakout.
⚠️ Notes
This is a confirmation tool, not a standalone entry system. Combine it with:
Structure breaks or liquidity sweeps
ATR-based stop losses
Volume or session filters
🌍 Summary
4 EMA MTF (M5 + M30) delivers multi-timeframe precision with clean, non-repainting signals that align your short-term and mid-term trends.
Designed for traders who demand clarity, momentum, and discipline.
💬 “When M5 and M30 agree — the trend just got serious.”
Marin Andrei - EMA 20-30 Price Alerts • Regime + Session Filter A clean and reliable trend-following alert system based on the 20 EMA and 30 EMA crossover zone, enhanced with multiple smart filters to eliminate noise and false signals. - configurable.
Core features:
✅ Trend confirmation: Buy only when price is above both EMAs; sell only when below.
📈 Slope & momentum filters: Optional slope and ATR-based spread validation.
🕒 Regime filter: Trade only in the direction of the higher-timeframe EMA trend (e.g., 200 EMA).
⏰ Session control: Limit signals to your preferred trading hours.
🔔 Built-in alerts: Instant notifications for clean buy/sell conditions.
Perfect for traders who want EMA-based precision entries with smarter filters for volatility, session timing, and overall market regime.
Session Gap Fill [LuxAlgo]The Session Gap Fill tool detects and highlights filled and unfilled price gaps between regular sessions. It features a dashboard with key statistics about the detected gaps.
The tool is highly customizable, allowing users to filter by different types of gaps and customize how they are displayed on the chart.
🔶 USAGE
By default, the tool detects all price gaps between sessions. A price gap is defined as a difference between the opening price of one session and the closing price of the previous session. In this case, the tool uses the opening price of the first bar of the session against the closing price of the previous bar.
A bullish gap is detected when the session open price is higher than the last close, and a bearish gap is detected when the session open price is lower than the last close.
Gaps represent a change in market sentiment, a difference in what market participants think between the close of one trading session and the open of the next.
What is useful to traders is not the gap itself, but how the market reacts to it.
Unfilled gaps occur when prices do not return to the previous session's closing price.
Filled gaps occur when prices come back to the previous session's close price.
By analyzing how markets react to gaps, traders can understand market sentiment, whether different prices are accepted or rejected, and take advantage of this information to position themselves in favor of bullish or bearish market sentiment.
Next, we will cover the Gap Type Filter and Statistics Dashboard.
🔹 Gap Type Filter
Traders can choose from three options: display all gaps, display only overlapping gaps, or display only non-overlapping gaps. All gaps are displayed by default.
An overlapping gap is defined when the first bar of the session has any price in common with the previous bar. No overlapping gap is defined when the two bars do not share any price levels.
As we will see in the next section, there are clear differences in market behavior around these types of gaps.
🔹 Statistics Dashboard
The Statistics Dashboard displays key metrics that help traders understand market behavior around each type of gap.
Gaps: The percentage of bullish and bearish gaps.
Filled: The percentage of filled bullish and bearish gaps.
Reversed: The percentage of filled gaps that move in favor of the gap
Bars Avg.: The average number of bars for a gap to be filled.
Now, let's analyze the chart on the left of the image to understand those stats. These are the stats for all gaps, both overlapping and non-overlapping.
Of the total, bullish gaps represent 55%, and bearish ones represent 44%. The gap bias is pretty balanced in this market.
The second statistic, Filled, shows that 63% of gaps are filled, both bullish and bearish. Therefore, there is a higher probability that a gap will be filled than not.
The third statistic is reversed. This is the percentage of filled gaps where prices move in favor of the gap. This applies to filled bullish gaps when the close of the session is above the open, and to filled bearish gaps when the close of the session is below the open. In other words, first there is a gap, then it fills, and finally it reverses. As we can see in the chart, this only happens 35% of the time for bullish gaps and 29% of the time for bearish gaps.
The last statistic is Bars Avg., which is the average number of bars for a gap to be filled. On average, it takes between one and two bars for both bullish and bearish gaps. On average, gaps fill quickly.
As we can see on the chart, selecting different types of gaps yields different statistics and market behavior. For example, overlapping gaps have a greater than 90% chance of being filled, whereas non-overlapping gaps have a less than 40% chance.
🔶 SETTINGS
Gap Type: Select the type of gap to display.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Filled Bullish Gap: Enable or disable this gap and choose the color.
Filled Bearish Gap: Enable or disable this gap and choose the color.
Unfilled Gap: Enable or disable this gap and choose the color.
Max Deviation Level: Enable or disable this level and choose the color.
Open Price Level: Enable or disable this level and choose the color.
Volume-Confirmed Reversal Engine [AlgoPoint]Volume-Confirmed Reversal Engine v2.0
Overview
A price pattern alone is not enough to signal a high-probability reversal. True market turning points—moments of capitulation or euphoria—are almost always confirmed by a significant spike in volume.
The Volume-Confirmed Reversal Engine is designed to identify these exact moments. It filters out low-conviction price movements and focuses only on reversal patterns that are backed by meaningful volume activity.
How It Works
The indicator's logic is based on a sequential confirmation process:
- High-Volume Anchor Candle: The engine first scans for an "Anchor Candle"—a candle that makes a new high or low over a user-defined look_back period. Critically, this candle's volume must also be significantly higher than the recent average. Low-volume breakouts are ignored.
- Setup Activation & Visualization: When a valid Anchor Candle is detected, the indicator enters a "setup" phase. It visually marks this on your chart by drawing a Setup Box around the high and low of the Anchor Candle, extending it forward for the duration of the confirm_in window.
- Confirmation & Signal: A final signal is only triggered if the price breaks out of the opposite side of the Setup Box within the confirmation window. This action, combined with the initial volume spike, confirms the reversal.
- Setup Box Visualization: See exactly which candle the indicator is watching and the key price levels (the box boundaries) that need to be broken for a signal.
Signal Strength Score (1-4): Every signal now comes with a score, providing insight into its quality based on four factors:
- The base price pattern is met.
- The initial Anchor Candle had high volume.
- The final Confirmation Candle also had high volume.
- The signal is aligned with the long-term macro trend (e.g., a BUY signal above the 200 EMA).
Status Dashboard: A simple panel on your chart tells you what the indicator is doing in real-time ("Scanning for Setups," "Watching Bullish Setup," etc.) and displays a countdown for how many bars are left for a confirmation.
How to Interpret & Use
- The Box: When a colored box appears, it's an early warning that a reversal setup is active. Watch the boundaries of the box for a potential breakout.
- The Score: Use the score to gauge the quality of a signal. A 3/4 or 4/4 score represents a very high-conviction setup where multiple technical factors are aligned.
- The Dashboard: Use the panel to understand the indicator's current state and the time-sensitivity of an active setup.
- The BUY/SELL Labels: These are the final, actionable triggers, appearing only after the full price and volume confirmation process is complete.
Power Hour Breakout Signals [LuxAlgo]The Power Hour Breakout tool helps traders identify key price levels from the Power Hour and spot breakouts from those levels easily. This tool features Power Hour extensions, Fibonacci levels, and session break marks for the trader's convenience.
🔶 USAGE
The Power Hour is defined as the last hour of the trading session and is set by default from 3:00 p.m. to 4:00 p.m. New York time. During this period, volume and volatility enter the market. Traders using higher timeframes may use this period to enter or exit positions by placing MOC (Market on Close) orders.
This tool highlights the Power Hour and the top and bottom price levels. Each time prices break out from these levels, a signal is displayed on the chart.
We can use the Power Hour to gauge market sentiment:
Bullish sentiment: Price trades above the Power Hour.
Mixed sentiment: Price trades within the Power Hour.
Bearish sentiment: Price trades below the Power Hour.
🔹 Displaying Power Hours and Breakouts
By default, all detected Power Hours are displayed. Traders can manually adjust this number by disabling the "Display All" parameter in the Settings panel.
Breakouts are displayed by default, too, but this feature can be disabled as well.
The chart above shows different configurations of these parameters.
🔹 Power Hour Extensions
Traders can use Power Hour extensions as potential targets for breakout signals.
In the settings panel, traders can select the percentage of the Power Hour price range to use for each extension. For example, 100% uses the full range, 200% uses the range twice, and so on.
As seen on the chart, traders can configure different percentages for the top and bottom extensions.
🔹 Fibonacci Levels
Traders can display default or custom Fibonacci levels on the Power Hour range to identify retracement opportunities and evaluate market movement strength. Each level can be enabled or disabled, as well as customized by level, color, and line style.
For example, as we can see on the chart, prices attempt to break out at the Power Hour top level, then retrace to the 0.618 Fibonacci level, and then rise to the 200% Power Hour top extension.
🔶 SETTINGS
Display Last X Power Hours: Select how many Power Hours to display or enable the Display All feature.
Power Hour (NY Time): Choose a custom Power Hour in New York time.
🔹 Breakouts
Breakouts: Enable or disable breakouts.
Bullish Breakout: Select color for bullish breakouts.
Bearish Breakout: Select color for bearish breakouts.
🔹 Extensions
Top Extension: Enable or disable the top extension and choose the percentage of Power Hour to use.
Bottom extension: Enable or disable the bottom extension and choose the percentage of Power Hour to use.
🔹 Fibonacci Levels
Display Fibonacci: Enable or disable Fibonacci levels.
Reverse: Reverse Fibonacci levels.
Levels, Colors & Style
Display Labels: Enable or disable labels and choose text size.
🔹 Style
Power Hour Colors
Extension Transparency: Choose the extension's transparency. 0 is solid, and 100 is fully transparent.
Session Breaks: Enable or disable session breaks.
Pivot Trend Flow [BigBeluga]🔵 OVERVIEW
Pivot Trend Flow turns raw swing points into a clean, adaptive trend band. It averages recent pivot highs and lows to form two dynamic reference levels; when price crosses above the averaged highs, trend flips bullish and a green band is drawn; when it crosses below the averaged lows, trend flips bearish and a red band is drawn. During an uptrend the script highlights breakouts of previous pivot highs with ▲ labels, and during a downtrend it flags breakdowns of previous pivot lows with ▼ labels—making structure shifts and continuation signals obvious.
🔵 CONCEPTS
Pivot-Based Averages : Recent pivot highs/lows are collected and averaged to create smoothed upper/lower reference levels.
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Trend State via Crosses : Close above the averaged-highs ⇒ bullish trend; close below the averaged-lows ⇒ bearish trend.
Trend Band : A colored band (green/red) is plotted and optionally filled to visualize the active regime around price.
Structure Triggers :
In bull mode the tool watches for prior pivot-high breakouts (▲).
In bear mode it watches for prior pivot-low breakdowns (▼).
🔵 FEATURES
Adaptive Trend Detection from averaged pivot highs/lows.
Clear Visuals : Green band in uptrends, red band in downtrends; optional fill for quick read.
Breakout/Breakdown Labels :
▲ marks breaks of previous pivot highs in uptrends
▼ marks breaks of previous pivot lows in downtrends
Minimal Clutter : Uses compact lines and labels that extend only on confirmation.
Customizable Colors & Fill for trend states and band styling.
🔵 HOW TO USE
Pivot Length : Sets how swing points are detected. Smaller = more reactive; larger = smoother.
Avg Window (pivots) : How many recent pivot highs/lows are averaged. Increase to stabilize the band; decrease for agility.
Read the Band :
Green band active ⇒ prioritize longs, pullback buys toward the band.
Red band active ⇒ prioritize shorts, pullback sells toward the band.
Trade the Triggers :
In bull mode, ▲ on a prior pivot-high break can confirm continuation.
In bear mode, ▼ on a prior pivot-low break can confirm continuation.
Combine with Context : Use HTF trend, S/R, or volume for confluence and to filter signals.
Fill Color Toggle : Enable/disable band fill to match your chart style.
🔵 CONCLUSION
Pivot Trend Flow converts swing structure into an actionable, low-lag trend framework. By blending averaged pivots with clean breakout/breakdown labels, it clarifies trend direction, timing, and continuation spots—ideal as a core bias tool or a confirmation layer in any trading system.
Estimated Manipulation Movement Signal [AlgoPoint]Follow the Footprints of Whale Movements That Drive the Market
Overview
The market is not always driven by natural supply and demand. Large players—often called "whales" or institutions—can create artificial price movements to trigger stop-losses, induce panic or FOMO, and build their large positions at favorable prices. These events are known as "stop hunts" or "liquidity grabs."
The EMMS indicator is a specialized tool designed to detect these specific moments of potential market manipulation. It does not follow trends in a traditional sense; instead, it identifies high-probability reversal points created by the calculated actions of Smart Money trapping other market participants.
How It Works: The 3-Module Logic
The indicator uses a multi-stage confirmation process to identify a potential stop hunt:
1. Anomaly Detection: The engine first scans the chart for "Anomaly Candles." These are candles with unusually high volume and a very long wick relative to their body. This combination signals a sudden, forceful, and potentially unnatural price push.
2. Liquidity Zone Detection: The indicator automatically identifies and tracks recent significant swing highs and lows. These levels are considered "Liquidity Zones" because they are areas where a large number of stop-loss orders are likely clustered. These are the "hunting grounds" for whales.
3. The Stop Hunt Signal: A final signal is generated only when these two events align in a specific sequence:
An Anomaly Candle (high volume, long wick) spikes through a previously identified Liquidity Zone.
The same candle then reverses, closing back inside the previous price range.
This sequence confirms that the move was likely a "trap" designed to engineer liquidity, and a reversal in the opposite direction is now highly probable.
How to Interpret & Use This Indicator
BUY Signal: A BUY signal appears after a sharp price drop that pierces a recent swing low (taking out the stops of long positions) and then aggressively reverses to close higher. This suggests that Smart Money has absorbed the panic selling they just induced. The signal indicates a potential move UP.
SELL Signal: A SELL signal appears after a sharp price spike that pierces a recent swing high (taking out the stops of short positions) and then aggressively reverses to close lower. This suggests that Smart Money has sold into the FOMO buying they just created. The signal indicates a potential move DOWN.
This indicator is best used as a high-probability confirmation tool, ideally in conjunction with your understanding of the overall market trend and structure.
Initial Balance Breakout Signals [LuxAlgo]The Initial Balance Breakout Signals help traders identify breakouts of the Initial Balance (IB) range.
The indicator includes automatic detection of IB or can use custom sessions, highlights top and bottom IB extensions, custom Fibonacci levels, and goes further with an IB forecast with two different modes.
🔶 USAGE
The initial balance is the price range made within the first hour of the trading session. It is an intraday concept based on the idea that high volume and volatility enter the market through institutional trading at the start of the session, setting the tone for the rest of the day.
The initial balance is useful for gauging market sentiment, or, in other words, the relationship between buyers and sellers.
Bullish sentiment: Price trades above the IB range.
Mixed sentiment: Price trades within the IB range.
Bearish sentiment: Price trades below the IB range.
The initial balance high and low are important levels that many traders use to gauge sentiment. There are two main ideas behind trading around the IB range.
IB Extreme Breakout: When the price breaks and holds the IB high or low, there is a high probability that the price will continue in that direction.
IB Extreme Rejection: When the price tries to break those levels but fails, there is a high probability that it will reach the opposite IB extreme.
This indicator is a complete Initial Balance toolset with custom sessions, breakout signals, IB extensions, Fibonacci retracements, and an IB forecast. All of these features will be explained in the following sections.
🔹 Custom Sessions and Signals
By default, sessions for Initial Balance and breakout signals are in Auto mode. This means that Initial Balance takes the first hour of the trading session and shows breakout signals for the rest of the session.
With this option, traders can use the tool for open range trading, making it highly versatile. The concept behind open range (OR) is the same as that of initial balance (IB), but in OR, the range is determined by the first minute, three or five minutes, or up to the first 30 minutes of the trading session.
As shown in the image above, the top chart uses the Auto feature for the IB and Breakouts sessions. The bottom chart has the Auto feature disabled to use custom sessions for both parameters. In this case, the first three minutes of the trading session are used, turning the tool into an Open Range trading indicator.
This chart shows another example of using custom sessions to display overnight NASDAQ futures sessions.
The left chart shows a custom session from the Tokyo open to the London open, and the right chart shows a custom session from the London open to the New York open.
The chart shows both the Asian and European sessions, their top and bottom extremes, and the breakout signals from those extremes.
🔹 Initial Balance Extensions
Traders can easily extend both extremes of the Initial Balance to display their preferred targets for breakouts. Enable or disable any of them and set the IB percentage to use for the extension.
As the chart shows, the percentage selected on the settings panel directly affects the displayed levels.
Setting 25 means the tool will use a quarter of the detected initial balance range for extensions beyond the IB extremes. Setting 100 means the full IB range will be used.
Traders can use these extensions as targets for breakout signals.
🔹 Fibonacci Levels
Traders can display default or custom Fibonacci levels on the IB range to trade retracements and assess the strength of market movements. Each level can be enabled or disabled and customized by level, color, and line style.
As we can see on the chart, after the IB was completed, prices were unable to fall below the 0.236 Fibonacci level. This indicates significant bullish pressure, so it is expected that prices will rise.
Traders can use these levels as guidelines to assess the strength of the side trying to penetrate the IB. In this case, the sellers were unable to move the market beyond the first level.
🔹 Initial Balance Forecast
The tool features two different forecasting methods for the current IB. By default, it takes the average of the last ten values and applies a multiplier of one.
IB Against Previous Open: averages the difference between IB extremes and the open of the previous session.
Filter by current day of the week: averages the difference between IB extremes and the open of the current session for the same day of the week.
This feature allows traders to see the difference between the current IB and the average of the last IBs. It makes it very easy to interpret: if the current IB is higher than the average, buyers are in control; if it is lower than the average, sellers are in control.
For example, on the left side of the chart, we can see that the last day was very bullish because the IB was completely above the forecasted value. This is the IB mean of the last ten trading days.
On the right, we can see that on Monday, September 15, the IB traded slightly higher but within the forecasted value of the IB mean of the last ten Mondays. In this case, it is within expectations.
🔶 SETTINGS
Display Last X IBs: Select how many IBs to display.
Initial Balance: Choose a custom session or enable the Auto feature.
Breakouts: Enable or disable breakouts. Choose custom session or enable the Auto feature.
🔹 Extensions
Top Extension: Enable or disable the top extension and choose the percentage of IB to use.
Bottom extension: Enable or disable the bottom extension and choose the percentage of IB to use.
🔹 Fibonacci Levels
Display Fibonacci: Enable or disable Fibonacci levels.
Reverse: Reverse Fibonacci levels.
Levels, Colors & Style
Display Labels: Enable or disable labels and choose text size.
🔹 Forecast
Display Forecast: Select the forecast method.
- IB Against Previous Open: Calculates the average difference between the IB high and low and the previous day's IB open price.
- Filter by Current Day of Week: Calculates the average difference between the IB high and low and the IB open price for the same day of the week.
Forecast Memory: The number of data points used to calculate the average.
Forecast Multiplier: This multiplier will be applied to the average. Bigger numbers will result in wider predicted ranges.
Forecast Colors: Choose from a variety of colors.
Forecast Style: Choose a line style.
🔹 Style
Initial Balance Colors
Extension Transparency: Choose the extension's transparency. 0 is solid, and 100 is fully transparent.
SuperSmoother MA OscillatorSuperSmoother MA Oscillator - Ehlers-Inspired Lag-Minimized Signal Framework
Overview
The SuperSmoother MA Oscillator is a crossover and momentum detection framework built on the pioneering work of John F. Ehlers, who introduced digital signal processing (DSP) concepts into technical analysis. Traditional moving averages such as SMA and EMA are prone to two persistent flaws: excessive lag, which delays recognition of trend shifts, and high-frequency noise, which produces unreliable whipsaw signals. Ehlers’ SuperSmoother filter was designed to specifically address these flaws by creating a low-pass filter with minimal lag and superior noise suppression, inspired by engineering methods used in communications and radar systems.
This oscillator extends Ehlers’ foundation by combining the SuperSmoother filter with multi-length moving average oscillation, ATR-based normalization, and dynamic color coding. The result is a tool that helps traders identify market momentum, detect reliable crossovers earlier than conventional methods, and contextualize volatility and phase shifts without being distracted by transient price noise.
Unlike conventional oscillators, which either oversimplify price structure or overload the chart with reactive signals, the SuperSmoother MA Oscillator is designed to balance responsiveness and stability. By preprocessing price data with the SuperSmoother filter, traders gain a signal framework that is clean, robust, and adaptable across assets and timeframes.
Theoretical Foundation
Traditional MA oscillators such as MACD or dual-EMA systems react to raw or lightly smoothed price inputs. While effective in some conditions, these signals are often distorted by high-frequency oscillations inherent in market data, leading to false crossovers and poor timing. The SuperSmoother approach modifies this dynamic: by attenuating unwanted frequencies, it preserves structural price movements while eliminating meaningless noise.
This is particularly useful for traders who need to distinguish between genuine market cycles and random short-term price flickers. In practical terms, the oscillator helps identify:
Early trend continuations (when fast averages break cleanly above/below slower averages).
Preemptive breakout setups (when compressed oscillator ranges expand).
Exhaustion phases (when oscillator swings flatten despite continued price movement).
Its multi-purpose design allows traders to apply it flexibly across scalping, day trading, swing setups, and longer-term trend positioning, without needing separate tools for each.
The oscillator’s visual system - fast/slow lines, dynamic coloration, and zero-line crossovers - is structured to provide trend clarity without hiding nuance. Strong green/red momentum confirms directional conviction, while neutral gray phases emphasize uncertainty or low conviction. This ensures traders can quickly gauge the market state without losing access to subtle structural signals.
How It Works
The SuperSmoother MA Oscillator builds signals through a layered process:
SuperSmoother Filtering (Ehlers’ Method)
At its core lies Ehlers’ two-pole recursive filter, mathematically engineered to suppress high-frequency components while introducing minimal lag. Compared to traditional EMA smoothing, the SuperSmoother achieves better spectral separation - it allows meaningful cyclical market structures to pass through, while eliminating erratic spikes and aliasing. This makes it a superior preprocessing stage for oscillator inputs.
Fast and Slow Line Construction
Within the oscillator framework, the filtered price series is used to build two internal moving averages: a fast line (short-term momentum) and a slow line (longer-term directional bias). These are not plotted directly on the chart - instead, their relationship is transformed into the oscillator values you see.
The interaction between these two internal averages - crossovers, separation, and compression - forms the backbone of trend detection:
Uptrend Signal : Fast MA rises above the slow MA with expanding distance, generating a positive oscillator swing.
Downtrend Signal : Fast MA falls below the slow MA with widening divergence, producing a negative oscillator swing.
Neutral/Transition : Lines compress, flattening the oscillator near zero and often preceding volatility expansion.
This design ensures traders receive the information content of dual-MA crossovers while keeping the chart visually clean and focused on the oscillator’s dynamics.
ATR-Based Normalization
Markets vary in volatility. To ensure the oscillator behaves consistently across assets, ATR (Average True Range) normalization scales outputs relative to prevailing volatility conditions. This prevents the oscillator from appearing overly sensitive in calm markets or too flat during high-volatility regimes.
Dynamic Color Coding
Color transitions reflect underlying market states:
Strong Green : Bullish alignment, momentum expanding.
Strong Red : Bearish alignment, momentum expanding.
These visual cues allow traders to quickly gauge trend direction and strength at a glance, with expanding colors indicating increasing conviction in the underlying momentum.
Interpretation
The oscillator offers a multi-dimensional view of price dynamics:
Trend Analysis : Fast/slow line alignment and zero-line interactions reveal trend direction and strength. Expansions indicate momentum building; contractions flag weakening conditions or potential reversals.
Momentum & Volatility : Rapid divergence between lines reflects increasing momentum. Compression highlights periods of reduced volatility and possible upcoming expansion.
Cycle Awareness : Because of Ehlers’ DSP foundation, the oscillator captures market cycles more cleanly than conventional MA systems, allowing traders to anticipate turning points before raw price action confirms them.
Divergence Detection : When oscillator momentum fades while price continues in the same direction, it signals exhaustion - a cue to tighten stops or anticipate reversals.
By focusing on filtered, volatility-adjusted signals, traders avoid overreacting to noise while gaining early access to structural changes in momentum.
Strategy Integration
The SuperSmoother MA Oscillator adapts across multiple trading approaches:
Trend Following
Enter when fast/slow alignment is strong and expanding:
A fast line crossing above the slow line with expanding green signals confirms bullish continuation.
Use ATR-normalized expansion to filter entries in line with prevailing volatility.
Breakout Trading
Periods of compression often precede breakouts:
A breakout occurs when fast lines diverge decisively from slow lines with renewed green/red strength.
Exhaustion and Reversals
Oscillator divergence signals weakening trends:
Flattening momentum while price continues trending may indicate overextension.
Traders can exit or hedge positions in anticipation of corrective phases.
Multi-Timeframe Confluence
Apply the oscillator on higher timeframes to confirm the directional bias.
Use lower timeframes for refined entries during compression → expansion transitions.
Technical Implementation Details
SuperSmoother Algorithm (Ehlers) : Recursive two-pole filter minimizes lag while removing high-frequency noise.
Oscillator Framework : Fast/slow MAs derived from filtered prices.
ATR Normalization : Ensures consistent amplitude across market regimes.
Dynamic Color Engine : Aligns visual cues with structural states (expansion and contraction).
Multi-Factor Analysis : Combines crossover logic, volatility context, and cycle detection for robust outputs.
This layered approach ensures the oscillator is highly responsive without overloading charts with noise.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Normalize with moderate ATR scaling; focus on slow-line confirmation.
Equities : Balance responsiveness with smoothing; useful for capturing sector rotations.
Cryptocurrency : Higher ATR multipliers recommended due to volatility.
Futures/Indices : Lower frequency settings highlight structural trends.
Timeframe Optimization:
Scalping (1-5min) : Higher sensitivity, prioritize fast-line signals.
Intraday (15m-1h) : Balance between fast/slow expansions.
Swing (4h-Daily) : Focus on slow-line momentum with fast-line timing.
Position (Daily-Weekly) : Slow lines dominate; fast lines highlight cycle shifts.
Performance Characteristics
High Effectiveness:
Trending environments with moderate-to-high volatility.
Assets with steady liquidity and clear cyclical structures.
Reduced Effectiveness:
Flat/choppy conditions with little directional bias.
Ultra-short timeframes (<1m), where noise dominates.
Integration Guidelines
Confluence : Combine with liquidity zones, order blocks, and volume-based indicators for confirmation.
Risk Management : Place stops beyond slow-line thresholds or ATR-defined zones.
Dynamic Trade Management : Use expansions/contractions to scale position sizes or tighten stops.
Multi-Timeframe Confirmation : Filter lower-timeframe entries with higher-timeframe momentum states.
Disclaimer
The SuperSmoother MA Oscillator is an advanced trend and momentum analysis tool, not a guaranteed profit system. Its effectiveness depends on proper parameter settings per asset and disciplined risk management. Traders should use it as part of a broader technical framework and not in isolation.
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
Trend ChannelThis Trend Channel is designed to simplify how traders view trends, while also keeping track of potential shifts in trends with signals. It is designed for traders that prefer less over more.
The indicator can be used for trend following, trend reversals and confirmation in combination with price or other indicators.
At the core is one EMA and a smoothed volatility based channel around it.
The purpose of the channel is to avoid false signals on trend reclaim or trend loss and instead identify trend deviations.
The indicator also incorporates long and short EMA cross-over signals to recognize possible shifts in trend without having to overlay multiple EMAs and keep the chart cleaner.
Additionally the indicator fires warnings for potential false signals on golden/death crosses with a letter "W" above/below the signal candle. Those warnings are based on the distance between price and the crossover. When the distance is above a certain threshold the indicator fires a warning that price might mean revert.
Traders can customize all inputs in the settings.
Rally Base Drop Signals [LuxAlgo]The Rally Base Drop indicator is built around the Supply and Demand (SND) concept known as "Rally, Base & Drop" Candles. These candle types are commonly used in this trading approach to identify price structure.
This indicator highlights bars by labeling them as "Rally," "Drop," or "Base" candles. It also identifies specific sequence patterns formed by these candles.
🔶 USAGE
The Rally, Base, Drop candlestick approach is a straightforward method for identifying price action structure.
Candles are categorized into three types, which are then analyzed to understand market structure and Supply/Demand levels.
Rally: Two or more consecutive bullish candles.
Drop: Two or more consecutive bearish candles.
Base: A single bullish or bearish candle that breaks the previous trend.
🔹 Rally & Drop Candles
These candles show clear directional momentum and signal whether demand or supply is dominating. They are helpful when identifying trends, as they highlight strong price movement.
🔹 Base Candles
In most SND strategies, "Base" can have several interpretations.
Typically, base candles represent short periods of consolidation that test the trend before continuation. They can also be found at turning points (tops or bottoms).
For this indicator, a base candle is simply one that does not follow the direction of nearby candles or is where a Drop and Rally meet. Multiple base candles often reflect indecision in the market, suggesting a temporary balance between buyers and sellers.
🔹 Reversal Sequences
Rally-Base-Drop (RBD)
Drop-Base-Rally (DBR)
In Supply and Demand analysis, these sequences are considered reversals. They mark zones where buyer and seller activity has shifted, which can lead to future price reactions. These areas are known as "Supply or Demand Zones" and are often revisited by price, making them useful for trade setups.
🔹 Continuation Sequences
Rally-Base-Rally (RBR)
Drop-Base-Drop (DBD)
Continuation sequences show a brief pause in the trend, followed by further movement in the same direction. In SND terms, they represent zones where orders accumulate before a continuation move. These are typically used to join ongoing trends, as they indicate sustained interest from buyers or sellers.
🔶 DETAILS
🔹 Color Modes
The script includes three color modes. "No Color" is self-explanatory, while the other two options relate to how candles are detected.
A Rally or Drop requires at least two candles to be successfully identified. As a result, detection occurs on the second candle. However, the full Rally or Drop includes both candles.
Two coloring methods are available:
Full Color: Once a Rally or Drop is detected (on the second bar), both candles are colored, starting from the first. This reflects the full pattern.
Color on Detection: Only the second candle (where detection occurs) is colored. This avoids changing past bars and may be useful for live analysis.
🔶 SETTINGS
Sequences: Select which sequences to display on the chart.
Bar Color Logic: Choose the preferred bar coloring method.
3 MA's with Crossing SignalsPlots three fully configurable moving averages on one chart and prints/alerts BUY/SELL signals when price crosses your chosen MA(s). Built to match TradingView’s built-ins exactly.
Features
Per-line MA type: SMA, EMA, SMMA (RMA), WMA, VWMA
Per-line settings: length, color, offset
Source control: Close, Open, High, Low, HL2, HLC3, OHLC4
Optional Heikin Ashi calculation for both the MAs and the cross price
Toggle signals vs MA1 / MA2 / MA3 independently
Alert conditions for every cross (ready for “Once per bar close”)
How signals work
UP when the selected price stream crosses above the chosen MA
DOWN when it crosses below
Signals/alerts follow your selected source (and HA toggle) to keep everything consistent.
Cyclic Reversal Engine [AlgoPoint]Overview
Most indicators focus on price and momentum, but they often ignore a critical third dimension: time. Markets move in rhythmic cycles of expansion and contraction, but these cycles are not fixed; they speed up in trending markets and slow down in choppy conditions.
The Cyclic Reversal Engine is an advanced analytical tool designed to decode this rhythm. Instead of relying on static, lagging formulas, this indicator learns from past market behavior to anticipate when the current trend is statistically likely to reach its exhaustion point, providing high-probability reversal signals.
It achieves this by combining a sophisticated time analysis with a robust price-action confirmation.
How It Works: The Core Logic
The indicator operates on a multi-stage process to identify potential turning points in the market.
1. Market Regime Analysis (The Brain): Before analyzing any cycles, the indicator first diagnoses the current "personality" of the market. Using a combination of the ADX, Choppiness Index, and RSI, it classifies the market into one of three primary regimes:
- Trending: Strong, directional movement.
- Ranging: Sideways, non-directional chop.
- Reversal: An over-extended state (overbought/oversold) where a turn is imminent.
2. Adaptive Cycle Learning (The "Machine Learning" Aspect): This is the indicator's smartest feature. It constantly analyzes past cycles by measuring the bar-count between significant swing highs and swing lows. Crucially, it learns the average cycle duration for each specific market regime. For example, it learns that "in a strong trending market, a new swing low tends to occur every 35 bars," while "in a ranging market, this extends to 60 bars."
3. The Countdown & Timing Signal: The indicator identifies the last major swing high or low and starts a bar-by-bar countdown. Based on the current market regime, it selects the appropriate learned cycle length from its memory. When the bar count approaches this adaptive target, the indicator determines that a reversal is "due" from a timing perspective.
4. Price Confirmation (The Trigger): A signal is never generated based on timing alone. Once the timing condition is met (the cycle is "due"), the indicator waits for a final price-action confirmation. The default confirmation is the RSI entering an extreme overbought or oversold zone, signaling momentum exhaustion. The signal is only triggered when Time + Price Confirmation align.
How to Use This Indicator
- The Dashboard: The panel in the bottom-right corner is your command center.
- Market Regime: Shows the current market personality analyzed by the engine.
- Adaptive Cycle / Bar Count: This is the core of the indicator. It shows the target cycle length for the current regime (e.g., 50) and the current bar count since the last swing point (e.g., 45). The background turns orange when the bar count enters the "due zone," indicating that you should be on high alert for a reversal.
- BUY/SELL Signals: A label appears on the chart only when the two primary conditions are met:
The timing is right (Bar Count has reached the Adaptive Cycle target).
The price confirms exhaustion (RSI is in an extreme zone).
A BUY signal suggests a downtrend cycle is likely complete, and a SELL signal suggests an uptrend cycle is likely complete.
Key Settings
- Pivot Lookback: Controls the sensitivity of the swing point detection. Higher values will identify more significant, longer-term cycles.
- Market Regime Engine: The ADX, Choppiness, and RSI settings can be fine-tuned to adjust how the indicator classifies the market's personality.
- Require Price Confirmation: You can toggle the RSI confirmation on or off. It is highly recommended to keep it enabled for higher-quality signals.
Momentum Index [BigBeluga]The Momentum Index is an innovative indicator designed to measure the momentum of price action by analyzing the distribution of positive and negative momentum values over a defined period. By incorporating delta-based calculations and smoothing techniques, it provides traders with a clear and actionable representation of market momentum dynamics.
🔵 Key Features:
Delta-Based Momentum Analysis:
Calculates the momentum of price by comparing its current state to its value from a defined number of bars back.
Inside a loop, it evaluates whether momentum values are above or below zero, producing a delta value that reflects the net momentum direction and intensity.
Double EMA Smoothing:
Smooths the raw delta-based momentum values with a double EMA filter, reducing noise and providing a clearer trend signal.
tmi(len) =>
sum = 0.0
sum1 = 0.0
above = 0.0
below = 0.0
src_ = src - src
for i = 0 to len
sum := sum + (src_ > nz(src_ ) ? 1 : -1)
sum1 := sum1 + (sum > 0 ? 1 : -1)
sum1 := emaEma(sum1, 10)
for i = 1 to len
above := above + (sum1 > 0 ? 1 : 0)
below := below + (sum1 > 0 ? 0 : 1)
Directional Momentum Signals:
Generates momentum shift signals and displays them on both the oscillator and the main chart:
- △ Aqua Triangles: Represent upward momentum shifts.
- ▽ Red Triangles: Represent downward momentum shifts.
Dynamic Gradient Display:
Highlights momentum zones with gradient fills:
- Aqua shades for positive momentum (above zero).
- Red shades for negative momentum (below zero).
Dashboard Display:
A dashboard summarizing the count of momentum values above and below zero for the defined period (Sentiment Length e.g. 100), helping traders assess market sentiment at a glance.
🔵 How It Works:
The indicator takes price momentum as its source and evaluates the number of momentum values above and below zero within a defined period.
The delta calculation aggregates this information, providing a net representation of the prevailing market momentum.
A double EMA filter is applied to the delta values, smoothing the momentum line and enhancing signal clarity.
Momentum shifts are highlighted with visual signals on the oscillator and price chart, while the gradient display provides a visual representation of intensity.
🔵 Use Cases:
Momentum Tracking: Identify whether market momentum is predominantly bullish or bearish.
Signal Confirmation: Use chart-based signals to confirm potential trend reversals or continuation.
Analyze Market Strength: Leverage the dashboard to quickly assess the distribution of momentum over the chosen period.
Overbought/Oversold Conditions: Utilize gradient zones to detect areas of momentum extremes and possible price exhaustion.
Momentum Index offers a refined approach to analyzing momentum dynamics, combining delta-based calculations with smoothing techniques and intuitive visuals, making it an essential tool for traders looking to anticipate market movements effectively.
Sequential Pattern Strength [QuantAlgo]🟢 Overview
The Sequential Pattern Strength indicator measures the power and sustainability of consecutive price movements by tracking unbroken sequences of up or down closes. It incorporates sequence quality assessment, price extension analysis, and automatic exhaustion detection to help traders identify when strong trends are losing momentum and approaching potential reversal or continuation points.
🟢 How It Works
The indicator's key insight lies in its sequential pattern tracking system, where pattern strength is measured by analyzing consecutive price movements and their sustainability:
if close > close
upSequence := upSequence + 1
downSequence := 0
else if close < close
downSequence := downSequence + 1
upSequence := 0
The system calculates sequence quality by measuring how "perfect" the consecutive moves are:
perfectMoves = math.max(upSequence, downSequence)
totalMoves = math.abs(bar_index - ta.valuewhen(upSequence == 1 or downSequence == 1, bar_index, 0))
sequenceQuality = totalMoves > 0 ? perfectMoves / totalMoves : 1.0
First, it tracks price extension from the sequence starting point:
priceExtension = (close - sequenceStartPrice) / sequenceStartPrice * 100
Then, pattern exhaustion is identified when sequences become overextended:
isExhausted = math.abs(currentSequence) >= maxSequence or
math.abs(priceExtension) > resetThreshold * math.abs(currentSequence)
Finally, the pattern strength combines sequence length, quality, and price movement with momentum enhancement:
patternStrength = currentSequence * sequenceQuality * (1 + math.abs(priceExtension) / 10)
enhancedSignal = patternStrength + momentum * 10
signal = ta.ema(enhancedSignal, smooth)
This creates a sequence-based momentum indicator that combines consecutive movement analysis with pattern sustainability assessment, providing traders with both directional signals and exhaustion insights for entry/exit timing.
🟢 Signal Interpretation
Positive Values (Above Zero): Sequential pattern strength indicating bullish momentum with consecutive upward price movements and sustained buying pressure = Long/Buy opportunities
Negative Values (Below Zero): Sequential pattern strength indicating bearish momentum with consecutive downward price movements and sustained selling pressure = Short/Sell opportunities
Zero Line Crosses: Pattern transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts when sequences break
Upper Threshold Zone: Area above maximum sequence threshold (2x maxSequence) indicating extremely strong bullish patterns approaching exhaustion levels
Lower Threshold Zone: Area below negative threshold (-2x maxSequence) indicating extremely strong bearish patterns approaching exhaustion levels
DTLLC Time & PriceDTLLC Time and Price with Signals
This indicator is built for traders who understand ICT concepts and want a structured, visual way to align time-based price action with key market levels. By combining customizable trading windows, breakout logic, and daily reference points, it helps you identify high-probability trade opportunities while filtering out market noise.
Key Features
1. Dual Custom Time Ranges (Kill Zones)
Set two independent time ranges per day (start/end hour and minute).
Each range identifies the highest high and lowest low within its window.
Built-in breakout detection generates buy/sell signals when price moves beyond these levels.
2. Volatility Filtering
Adjustable volatility threshold based on True Range relative to ATR.
Filters out low-quality signals during choppy, low-volatility conditions.
3. ATR-Based Stop Loss
Custom ATR length and stop-loss multiplier settings.
Automatically plots ATR-based stop levels for triggered trades.
4. Daily Key Levels
Plots Previous Day High, Previous Day Low, and Midnight Open continuously on the chart.
Useful for spotting breakout and reversal opportunities in line with ICT market structure concepts.
5. Liquidity & Engulfing Candle Highlights
Highlights potential liquidity grab zones (yellow candles) when significant highs/lows are set within your lookback period.
Detects bullish (green) and bearish (red) engulfing patterns for added confluence.
6. Visual & Signal Tools
Buy/Sell signals plotted directly on chart (separate colors for Range 1 and Range 2). Continuous plotting of reference levels to maintain market context throughout the session.
Example Use Case:
A common ICT-inspired reversal setup:
Wait for price to sweep the Previous Day’s High or Low during your chosen time range.
Look for a buy or sell signal with volatility confirmation.
Manage risk using the ATR-based stop-loss plot.
Disclaimer: This script is for educational purposes only and is not financial advice. Trade responsibly and always test strategies before applying them in live markets.
Mutanabby_AI | Fresh Algo V24Mutanabby_AI | Fresh Algo V24: Advanced Multi-Mode Trading System
Overview
The Mutanabby_AI Fresh Algo V24 represents a sophisticated evolution of multi-component trading systems that adapts to various market conditions through advanced operational configurations and enhanced analytical capabilities. This comprehensive indicator provides traders with multiple signal generation approaches, specialized assistant functions, and dynamic risk management tools designed for professional market analysis across diverse trading environments.
Primary Signal Generation Framework
The Fresh Algo V24 operates through two fundamental signal generation approaches that accommodate different market perspectives and trading philosophies. The Trending Signals Mode serves as the primary trend-following mechanism, combining Wave Trend Oscillator analysis with Supertrend directional signals and Squeeze Momentum breakout detection. This mode incorporates ADX filtering that requires values exceeding 20 to ensure sufficient trend strength exists before signal activation, making it particularly effective during sustained directional market movements where momentum persistence creates profitable trading opportunities.
The Contrarian Signals Mode provides an alternative approach targeting reversal opportunities through extreme market condition identification. This mode activates when the Wave Trend Oscillator reaches critical threshold levels, specifically when readings surpass 65 indicating potential bearish reversal conditions or drop below 35 suggesting bullish reversal opportunities. This methodology proves valuable during overextended market phases where mean reversion becomes statistically probable.
Advanced Filtering Mechanisms
The system incorporates multiple sophisticated filtering mechanisms designed to enhance signal quality and reduce false positive occurrences. The High Volume Filter requires volume expansion confirmation before signal activation, utilizing exponential moving average calculations to ensure institutional participation accompanies price movements. This filter substantially improves signal reliability by eliminating low-conviction breakouts that lack adequate volume support from professional market participants.
The Strong Filter provides additional trend confirmation through 200-period exponential moving average analysis. Long position signals require price action above this benchmark level, while short position signals necessitate price action below it. This ensures strategic alignment with longer-term trend direction and reduces the probability of trading against major market movements that could invalidate shorter-term signals.
Cloud Filter Configuration System
The Fresh Algo V24 offers four distinct cloud filter configurations, each optimized for specific trading timeframes and market approaches. The Smooth Cloud Filter utilizes the mathematical relationship between 150-period and 250-period exponential moving averages, providing stable trend identification suitable for position trading strategies. This configuration generates signals exclusively when price action aligns with cloud direction, creating a more deliberate but highly reliable signal generation process.
The Swing Cloud Filter employs modified Supertrend calculations with parameters specifically optimized for swing trading timeframes. This filter achieves optimal balance between responsiveness and stability, adapting effectively to medium-term price movements while filtering excessive market noise that typically affects shorter-term analytical systems.
For active intraday traders, the Scalping Cloud Filter utilizes accelerated Supertrend calculations designed to capture rapid trend changes effectively. This configuration provides enhanced signal generation frequency suitable for compressed timeframe strategies. The advanced Scalping+ Cloud Filter incorporates Hull Moving Average confirmation, delivering maximum responsiveness for ultra-short-term trading while maintaining signal quality through additional momentum validation processes.
Specialized Assistant Functionality
The system includes two distinct assistant modes that provide supplementary market analysis capabilities. The Trend Assistant Mode activates advanced cloud analysis overlays that display dynamic support and resistance zones calculated through adaptive volatility algorithms. These levels automatically adjust to current market conditions, providing visual guidance for identifying trend continuation patterns and potential reversal areas with mathematical precision.
The Trend Tracker Mode concentrates on long-term trend identification by displaying major exponential moving averages with color-coded fill areas that clarify directional bias. This mode maintains visual simplicity while providing comprehensive trend context evaluation, enabling traders to quickly assess broader market direction and align shorter-term strategies accordingly.
Dynamic Risk Management System
The integrated risk management system automatically adapts across all operational modes, calculating stop loss and take profit targets using Average True Range multiples that adjust to current market volatility. This approach ensures consistent risk parameters regardless of selected operational mode while maintaining relevance to prevailing market conditions.
Stop loss placement occurs at dynamically calculated distances from entry points, while three progressive take profit targets establish at customizable ATR multiples respectively. The system automatically updates these levels upon trend direction changes, ensuring current market volatility influences all risk calculations and maintains appropriate risk-reward ratios throughout trade management.
Comprehensive Market Analysis Dashboard
The sophisticated dashboard provides real-time market analysis including volatility measurements, institutional activity assessment, and multi-timeframe trend evaluation across five-minute through four-hour periods. This comprehensive market context assists traders in selecting appropriate operational modes based on current market characteristics rather than relying exclusively on historical performance data.
The multi-timeframe analysis ensures mode selection considers broader market context beyond the primary trading timeframe, improving overall strategic alignment and reducing conflicts between different temporal market perspectives. The dashboard displays market state classification, volatility percentages, institutional activity levels, current trading session information, and trend pressure indicators with professional formatting and clear visual hierarchy.
Enhanced Trading Assistants
The Fresh Algo V24 includes specialized trading assistant features that complement the primary signal generation system. The Reversal Dot functionality identifies potential reversal points through Wave Trend Oscillator analysis, displaying visual indicators when crossover conditions occur at extreme levels. These reversal indicators provide early warning signals for potential trend changes before they appear in the primary signal system.
The Dynamic Take Profit Labels feature automatically identifies optimal profit-taking opportunities through RSI threshold analysis, marking potential exit points at multiple levels for long positions and corresponding levels for short positions. This automated profit management system helps traders optimize exit timing without requiring constant manual monitoring of technical indicators.
Advanced Alert System
The comprehensive alert system accommodates all operational modes while providing granular notification control for various signal types and risk management events. Traders can configure separate alerts for normal buy signals, strong buy signals, normal sell signals, strong sell signals, stop loss triggers, and individual take profit target achievements.
Cloud crossover alerts notify traders when trend direction changes occur, providing early indication of potential strategy adjustments. The alert system includes detailed trade setup information, timeframe data, and relevant entry and exit levels, ensuring traders receive complete context for informed decision-making without requiring constant chart monitoring.
Technical Foundation Architecture
The Fresh Algo V24 combines multiple proven technical analysis components including Wave Trend Oscillator for momentum assessment, Supertrend for directional bias determination, Squeeze Momentum for volatility analysis, and various exponential moving averages for trend confirmation. Each component contributes specific market insights while the unified system provides comprehensive market evaluation through their mathematical integration.
The multi-component approach reduces dependency on individual indicator limitations while leveraging the analytical strengths of each technical tool. This creates a robust analytical framework capable of adapting to diverse market conditions through appropriate mode selection and parameter optimization, ensuring consistent performance across varying market environments.
Market State Classification
The indicator incorporates advanced market state classification through ADX analysis, distinguishing between trending, ranging, and transitional market conditions. This classification system automatically adjusts signal sensitivity and filtering parameters based on current market characteristics, optimizing performance for prevailing conditions rather than applying static analytical approaches.
The volatility measurement system calculates current market activity levels as percentages, providing quantitative assessment of market energy and helping traders select appropriate operational modes. Institutional activity detection through volume analysis ensures signal generation aligns with professional market participation patterns.
Implementation Strategy Considerations
Successful implementation requires careful matching of operational modes to prevailing market conditions and individual trading objectives. Trending modes demonstrate optimal performance during directional markets with sustained momentum characteristics, while contrarian modes excel during range-bound or overextended market conditions where reversal probability increases.
The cloud filter configurations provide varying degrees of confirmation strength, with smoother settings reducing false signal occurrence at the expense of some responsiveness to price changes. Traders must balance signal quality against signal frequency based on their risk tolerance and available trading time, utilizing the comprehensive customization options to optimize performance for their specific requirements.
Multi-Timeframe Integration
The system provides seamless multi-timeframe analysis through the integrated dashboard, displaying trend alignment across multiple time horizons from five-minute through four-hour periods. This analysis helps traders understand broader market context and avoid conflicts between different temporal perspectives that could compromise trade outcomes.
Session analysis identifies current trading session characteristics, providing context for expected market behavior patterns and helping traders adjust their approach based on typical session volatility and participation levels. This geographic market awareness enhances strategic decision-making and improves timing for trade execution.
Advanced Visualization Features
The indicator includes sophisticated visualization capabilities through gradient candle coloring based on MACD analysis, providing immediate visual feedback on momentum strength and direction. This enhancement allows rapid market assessment without requiring detailed indicator analysis, improving efficiency for traders managing multiple instruments simultaneously.
The cloud visualization system uses color-coded fill areas to clearly indicate trend direction and strength, with automatic adaptation to selected operational modes. This visual clarity reduces analytical complexity while maintaining comprehensive market information display through professional chart presentation.
Performance Optimization Framework
The Fresh Algo V24 incorporates performance optimization features including signal strength classification, automatic parameter adjustment based on market conditions, and dynamic filtering that adapts to current volatility levels. These optimizations ensure consistent performance across varying market environments while maintaining signal quality standards.
The system automatically adjusts sensitivity levels based on selected operational modes, ensuring appropriate responsiveness for different trading approaches. This adaptive framework reduces the need for manual parameter adjustments while maintaining optimal performance characteristics for each operational configuration.
Conclusion
The Mutanabby_AI Fresh Algo V24 represents a comprehensive solution for professional trading analysis, combining multiple analytical approaches with advanced visualization and risk management capabilities. The system's strength lies in its adaptive multi-mode design and sophisticated filtering mechanisms, providing traders with versatile tools for various market conditions and trading styles.
Success with this system requires understanding the relationship between different operational modes and their optimal application scenarios. The comprehensive dashboard and alert system provide essential market context and trade management support, enabling systematic approach to market analysis while maintaining flexibility for individual trading preferences.
The indicator's sophisticated architecture and extensive customization options make it suitable for traders at all experience levels, from those seeking systematic signal generation to advanced practitioners requiring comprehensive market analysis tools. The multi-timeframe integration and adaptive filtering ensure consistent performance across diverse market conditions while providing clear guidelines for strategic implementation.
Zero Lag Liquidity [AlgoAlpha]🟠 OVERVIEW
This script plots liquidity zones with zero lag using lower-timeframe wick profiles and high-volume wicks to mark key price reactions. It’s called Zero Lag Liquidity because it captures significant liquidity imbalances in real time by processing lower-TF price-volume distributions directly inside the wick of abnormal candles. The tool builds a volume histogram inside long upper/lower wicks, then calculates a local Point of Control (POC) to mark the price where most volume occurred. These levels act as visual liquidity zones, which can trigger labels, break signals, and trend detection depending on price interaction.
🟠 CONCEPTS
The core concept relies on identifying high-volume candles with unusually long wicks—often a sign of opposing liquidity. When a large upper or lower wick appears with a strong volume spike, the script builds a histogram of lower-timeframe closes and volumes inside that wick. It bins the wick into segments, sums volume per bin, and finds the POC. This POC becomes the liquidity level. The script then dynamically tracks whether price breaks above or rejects off these levels, adjusts the active trend regime accordingly, and highlights bars to help users spot continuation or reversal behavior. The logic avoids repainting or subjective interpretation by using fixed thresholds and lower-TF price action.
🟠 FEATURES
Dynamic liquidity levels rendered at POC of significant wicks, colored by bullish/bearish direction.
Break detection that removes levels once price decisively crosses them twice in the same direction.
Rejection detection that plots ▲/▼ markers when price bounces off levels intrabar.
Volume labels for each level, shown either as raw volume or percentage of total level volume.
Candle coloring based on trend direction (break-dominant).
🟠 USAGE
Use this indicator to track where liquidity has most likely entered the market via abnormal wick events. When a long wick forms with high volume, the script looks inside it (using your chosen lower timeframe) and marks the most traded price within it. These levels can serve as expected reversal or breakout zones. Rejections are marked with small arrows, while breaks trigger trend shifts and remove the level. You can toggle trend coloring to see directional bias after a breakout. Use the wick multiplier to control how selective the detector is (higher = stricter). Alerts and label modes help customize the signal for different asset types and chart styles.
On-Chain Signals [LuxAlgo]The On-Chain Signals indicator uses fundamental blockchain metrics to provide traders with an objective technical view of their favorite cryptocurrencies.
It uses IntoTheBlock datasets integrated within TradingView to generate four key signals: Net Network Growth, In the Money, Concentration, and Large Transactions.
Together, these four signals provide traders with an overall directional bias of the market. All of the data can be visualized as a gauge, table, historical plot, or average.
🔶 USAGE
The main goal of this tool is to provide an overall directional bias based on four blockchain signals, each with three possible biases: bearish, neutral, or bullish. The thresholds for each signal bias can be adjusted on the settings panel.
These signals are based on IntoTheBlock's On-Chain Signals.
Net network growth: Change in the total number of addresses over the last seven periods; i.e., how many new addresses are being created.
In the Money: Change in the seven-period moving average of the total supply in the money. This shows how many addresses are profitable.
Concentration: Change in the aggregate addresses of whales and investors from the previous period. These are addresses holding at least 0.1% of the supply. This shows how many addresses are in the hands of a few.
Large Transactions: Changes in the number of transactions over $100,000. This metric tracks convergence or divergence from the 21- and 30-day EMAs and indicates the momentum of large transactions.
All of these signals together form the blockchain's overall directional bias.
Bearish: The number of bearish individual signals is greater than the number of bullish individual signals.
Neutral: The number of bearish individual signals is equal to the number of bullish individual signals.
Bullish: The number of bullish individual signals is greater than the number of bearish individual signals.
If the overall directional bias is bullish, we can expect the price of the observed cryptocurrency to increase. If the bias is bearish, we can expect the price to decrease. If the signal is neutral, the price may be more likely to stay the same.
Traders should be aware of two things. First, the signals provide optimal results when the chart is set to the daily timeframe. Second, the tool uses IntoTheBlock data, which is available on TradingView. Therefore, some cryptocurrencies may not be available.
🔹 Display Mode
Traders have three different display modes at their disposal. These modes can be easily selected from the settings panel. The gauge is set by default.
🔹 Gauge
The gauge will appear in the center of the visible space. Traders can adjust its size using the Scale parameter in the Settings panel. They can also give it a curved effect.
The number of bars displayed directly affects the gauge's resolution: More bars result in better resolution.
The chart above shows the effect that different scale configurations have on the gauge.
🔹 Historical Data
The chart above shows the historical data for each of the four signals.
Traders can use this mode to adjust the thresholds for each signal on the settings panel to fit the behavior of each cryptocurrency. They can also analyze how each metric impacts price behavior over time.
🔹 Average
This display mode provides an easy way to see the overall bias of past prices in order to analyze price behavior in relation to the underlying blockchain's directional bias.
The average is calculated by taking the values of the overall bias as -1 for bearish, 0 for neutral, and +1 for bullish, and then applying a triangular moving average over 20 periods by default. Simple and exponential moving averages are available, and traders can select the period length from the settings panel.
🔶 DETAILS
The four signals are based on IntoTheBlock's On-Chain Signals. We gather the data, manipulate it, and build the signals depending on each threshold.
Net network growth
float netNetworkGrowthData = customData('_TOTALADDRESSES')
float netNetworkGrowth = 100*(netNetworkGrowthData /netNetworkGrowthData - 1)
In the Money
float inTheMoneyData = customData('_INOUTMONEYIN')
float averageBalance = customData('_AVGBALANCE')
float inTheMoneyBalance = inTheMoneyData*averageBalance
float sma = ta.sma(inTheMoneyBalance,7)
float inTheMoney = ta.roc(sma,1)
Concentration
float whalesData = customData('_WHALESPERCENTAGE')
float inverstorsData = customData('_INVESTORSPERCENTAGE')
float bigHands = whalesData+inverstorsData
float concentration = ta.change(bigHands )*100
Large Transactions
float largeTransacionsData = customData('_LARGETXCOUNT')
float largeTX21 = ta.ema(largeTransacionsData,21)
float largeTX30 = ta.ema(largeTransacionsData,30)
float largeTransacions = ((largeTX21 - largeTX30)/largeTX30)*100
🔶 SETTINGS
Display mode: Select between gauge, historical data and average.
Average: Select a smoothing method and length period.
🔹 Thresholds
Net Network Growth : Bullish and bearish thresholds for this signal.
In The Money : Bullish and bearish thresholds for this signal.
Concentration : Bullish and bearish thresholds for this signal.
Transactions : Bullish and bearish thresholds for this signal.
🔹 Dashboard
Dashboard : Enable/disable dashboard display
Position : Select dashboard location
Size : Select dashboard size
🔹 Gauge
Scale : Select the size of the gauge
Curved : Enable/disable curved mode
Select Gauge colors for bearish, neutral and bullish bias
🔹 Style
Net Network Growth : Enable/disable historical plot and choose color
In The Money : Enable/disable historical plot and choose color
Concentration : Enable/disable historical plot and choose color
Large Transacions : Enable/disable historical plot and choose color
