Adaptive Scaled LevelsThis indicator allows users to manually define a list of price levels (e.g., round or psychological numbers) and automatically scales them to fit any asset's current price range using an intelligent anchor point. It then plots dynamic horizontal zones ideal for identifying potential supply/demand or reaction areas.
How It Works (Technical Methodology)
Manual Price List Input
Users enter a comma-separated list of price levels via a text area input (default example: 50,100,...,1400). These act as a "template" grid – often round numbers, psychological levels, or custom targets.
Auto-Scaling Logic (Core Innovation)
When enabled:
Calculates the average of the input list.
Determines a smart anchor price:
Default (Lock = 0): Close price of the highest-volume bar in the last user-defined lookback period (default 200 bars), fetched from a selectable timeframe (default Daily) via request.security().
Override: User can manually lock the anchor to any fixed price.
Computes a scale factor = Anchor / List Average.
Multiplies every input level by this factor to adapt the entire grid to the current market (e.g., scales low-price templates to BTC's 60k+ range).
Zone Construction
For each scaled level:
Creates a horizontal box centered on the level.
Height = Level × user-defined percentage (default 0.5%) for volatility-adjusted thickness.
Zones extend infinitely to the right for continuous reference.
Supply/Demand Coloring
Levels above current close: Supply color (default light gray) – potential resistance/overhead supply.
Levels below current close: Demand color (default cyan) – potential support/underlying demand.
Visual Elements
Transparent filled boxes with borders.
Optional labels showing "S" (Supply) or "D" (Demand) plus exact price.
Clean, non-cluttering design – redraws only on last bar for performance.
How to Use
This tool is perfect for plotting adaptive psychological/round number grids across any asset without manual adjustment.
Common Template: Use evenly spaced round numbers (e.g., 100 increments) as input – the script handles scaling.
BTC/ETH/Crypto: Enable auto-scaling with Daily timeframe anchor for high-volume alignment (often near fair value).
Forex/Stocks: Lower zone height % for tighter zones; use shorter lookback or lock anchor for stability.
Trading Applications:
Anticipate reactions/bounces at scaled levels (confluence with price action, volume, or order blocks).
Supply zones (above price): Potential short entries or take-profit targets.
Demand zones (below price): Potential long entries or stop-loss placement below.
Override anchor for specific analysis (e.g., lock to all-time high).
Best Practices: Combine with trend direction, higher-timeframe structure, or liquidity concepts for higher-probability setups.
Highly versatile – works on any timeframe/asset, especially volatile ones like cryptocurrencies where fixed levels quickly become irrelevant.
Disclaimer
This indicator is a technical analysis tool and should be used in conjunction with other forms of analysis. Past performance does not guarantee future results. Always use proper risk management.
Pesquisar nos scripts por "crypto"
Seasonality Table - [JTCAPITAL]Seasonality Table - is a modified way to use monthly return aggregation across multiple assets to identify seasonal trends in cryptocurrencies and indices.
The indicator works by calculating in the following steps:
Asset Selection
The user defines a list of assets to include in the seasonality table. By default, the script allows up to 32 assets, including popular cryptocurrencies like BTC, ETH, BNB, XRP, and others. Each asset is identified by its symbol (e.g., "CRYPTO:BTCUSD").
Monthly Return Calculation
For each asset, the script requests monthly price data using request.security. Specifically, it retrieves the monthly open, close, and month number. The monthly return is calculated as:
Return = (Close - Open) / Open
This step provides a normalized measure of performance for each asset per month.
Data Aggregation
The script stores two key arrays for each asset and month combination:
sumReturns: The cumulative sum of monthly returns
countReturns: The number of months with valid data
This allows averaging returns later while handling months with missing data gracefully.
Table Construction
Rows representing months (January–December)
Columns representing each asset
An additional column showing the average return for all assets per month
A final row showing the yearly average return for each asset
Filling the Table
The table cells are filled as follows:
Monthly returns are averaged for each asset and displayed as a percentage.
Positive returns are colored green, negative returns red.
Missing data is displayed as a gray “—” placeholder.
Each row’s values are normalized for the color gradient to show relative performance.
Averages Computation
The script calculates two types of averages:
Monthly Average Across Assets : Sum of all asset returns for a month divided by the number of valid data points.
Yearly Average Per Asset : Sum of all monthly returns for an asset divided by the number of months with valid data.
These averages are displayed in the last column and last row respectively, with gradient coloring for visual comparison.
Buy and Sell Conditions
This indicator does not generate explicit buy or sell signals. Instead, it provides a visual heatmap of historical seasonality, allowing traders to:
Identify months where an asset historically outperforms (bullish bias)
Identify months with weak historical performance (bearish caution)
Compare seasonal patterns across multiple assets for portfolio allocation
Filters can be applied by adjusting the asset list, changing the color mapping, or focusing on specific months to highlight seasonal anomalies.
Features and Parameters
Number of assets: Set how many assets are included in the table (1–32).
Assets: Input symbols for the assets you want to analyze.
Low % Color: Defines the color for the lowest monthly returns in the gradient.
High % Color: Defines the color for the highest monthly returns in the gradient.
Cleaned asset names for concise display.
Gradient-based visualization for easier pattern recognition.
Monthly and yearly averages for comparative analysis.
Specifications
Monthly Return Calculation
Uses the formula (Close - Open) / Open for each asset per month. This standardizes performance across different price scales and ensures comparability between assets.
Arrays for Storage
sumReturns: Float array storing cumulative monthly returns.
countReturns: Integer array storing the number of valid data points per month.
These arrays allow efficient aggregation and average calculations without overwriting previous values.
Data Retrieval via Security Calls
Requests monthly OHLC data for each asset using request.security.
Ensures calculations reflect the correct timeframe and allow for historical comparison.
Color and Text Assignment
Green text for positive returns, red for negative returns.
Gray cells indicate missing data.
Gradient background shows relative magnitude within the month.
Seasonality Analysis
The table visually encodes which months historically produce stronger returns.
Useful for portfolio rotation, risk management, and identifying cyclical trends.
Scalability
Supports up to 32 assets.
Dynamically adapts to the number of assets and data availability.
Gradient scales automatically per row for consistent comparison.
Trend Following $BTC - Multi-Timeframe Structure + ReversTREND FOLLOWING STRATEGY - MULTI-TIMEFRAME STRUCTURE BREAKOUT SYSTEM
Strategy Overview
This is an enhanced Turtle Trading system designed for cryptocurrency spot trading. It combines Donchian Channel breakouts with multi-timeframe structure filtering and ATR-based dynamic risk management. The strategy trades both long and short positions using reverse signal exits to maximize trend capture.
Core Features
Multi-Timeframe Structure Filtering
The strategy uses Swing High/Low analysis to identify market structure trends. You can customize the structure timeframe (default: 3 minutes) to match your trading style. Only enters trades aligned with the identified trend direction, avoiding counter-trend positions that often lead to losses.
Reverse Signal Exit System
Instead of using fixed stop-losses or time-based exits, this strategy exits positions only when a reverse entry signal triggers. This approach maximizes trend profits and reduces premature exits during normal market retracements.
ATR Dynamic Pyramiding
Automatically adds positions when price moves 0.5 ATR in your favor. Supports up to 2 units maximum (adjustable). This pyramid scaling enhances profitability during strong trends while maintaining disciplined risk management.
Complete Risk Management
Fixed position sizing at 5000 USD per unit. Includes realistic commission fees of 0.06% (Binance spot rate). Initial capital set at 10,000 USD. All backtest parameters reflect real-world trading conditions.
Trading Logic
Entry Conditions
Long Entry: Close price breaks above the 20-period high AND structure trend is bullish (price breaks above Swing High)
Short Entry: Close price breaks below the 20-period low AND structure trend is bearish (price breaks below Swing Low)
Position Scaling
Long positions: Add when price rises 0.5 ATR or more
Short positions: Add when price falls 0.5 ATR or more
Maximum 2 units including initial entry
Exit Conditions
Long Exit: Triggers when short entry signal appears (price breaks 20-period low + structure turns bearish)
Short Exit: Triggers when long entry signal appears (price breaks 20-period high + structure turns bullish)
Default Parameters
Channel Settings
Entry Channel Period: 20 (Donchian Channel breakout period)
Exit Channel Period: 10 (reserved parameter)
ATR Settings
ATR Period: 20
Stop Loss ATR Multiplier: 2.0
Add Position ATR Multiplier: 0.5
Structure Filter
Swing Length: 300 (Swing High/Low calculation period)
Structure Timeframe: 3 minutes
Adjust these based on your trading timeframe and asset volatility
Position Management
Maximum Units: 2 (including initial entry)
Capital Per Unit: 5000 USD
Visualization Features
Background Colors
Light Green: Bullish market structure
Light Red: Bearish market structure
Dark Green: Long position entry
Dark Red: Short position entry
Optional Display Elements (Default: OFF)
Entry and exit channel lines
Structure high/low reference lines
ATR stop-loss indicator
Next position add level
Entry/exit labels
Alert Message Format
The strategy sends notifications with the following format:
Entry: "5m Long EP:90450.50"
Add Position: "15m Add Long 2/2 EP:91000.25"
Exit: "5m Close Long Reverse Signal"
Where the first part shows your current chart timeframe and EP indicates Entry Price
Backtest Settings
Capital Allocation
Initial Capital: 10,000 USD
Per Entry: 5,000 USD (split into 2 potential entries)
Leverage: 0x (spot trading only)
Trading Costs
Commission: 0.06% (Binance spot VIP0 rate)
Slippage: 0 (adjust based on your experience)
Best Use Cases
Ideal Scenarios
Trending markets with clear directional movement
Moderate to high volatility assets
Timeframes from 1-minute to 4-hour charts
Best suited for major cryptocurrencies with good liquidity
Not Recommended For
Highly volatile choppy/ranging markets
Low liquidity small-cap coins
Extreme market conditions or black swan events
Usage Recommendations
Timeframe Guidelines
1-5 minute charts: Use for scalping, consider Swing Length 100-160
15-30 minute charts: Good for short-term trading, Swing Length 50-100
1-4 hour charts: Suitable for swing trading, Swing Length 20-50
Optimization Tips
Always backtest on historical data before live trading
Adjust swing length based on asset volatility and your timeframe
Different cryptocurrencies may require different parameter settings
Enable visualization options initially to understand entry/exit points
Monitor win rate and drawdown during backtesting
Technical Details
Built on Pine Script v6
No repainting - uses proper bar referencing with offset
Prevents lookahead bias with lookahead=off parameter
Strategy mode with accurate commission and slippage modeling
Multi-timeframe security function for structure analysis
Proper position state tracking to avoid duplicate signals
Risk Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Backtesting results may differ from live trading due to slippage, execution delays, and changing market conditions. The strategy performs best in trending markets and may experience drawdowns during ranging conditions. Always practice proper risk management and never risk more than you can afford to lose. It is recommended to paper trade first and start with small position sizes when going live.
How to Use
Add the strategy to your TradingView chart
Select your desired timeframe (1m to 4h recommended)
Adjust parameters based on your risk tolerance and trading style
Review backtest results in the Strategy Tester tab
Set up alerts for automated notifications
Consider paper trading before risking real capital
Tags
Trend Following, Turtle Trading, Donchian Channel, Structure Breakout, ATR, Cryptocurrency, Spot Trading, Risk Management, Pyramiding, Multi-Timeframe Analysis
---
Strategy Name: Trend Following BTC
Version: v1.0
Pine Script Version: v6
Last Updated: December 2025
Trend Following $ZEC - Multi-Timeframe Structure Filter + Revers# Trend Following CRYPTOCAP:ZEC - Strategy Guide
## 📊 Strategy Overview
Trend Following CRYPTOCAP:ZEC is an enhanced Turtle Trading system designed for cryptocurrency spot trading, combining Donchian Channel breakouts, multi-timeframe structure filtering, and ATR-based dynamic risk management for both long and short positions.
---
## 🎯 Core Features
1. Multi-Timeframe Structure Filtering
- Uses Swing High/Low to identify market structure
- Customizable structure timeframe (default: 1 minute)
- Only enters trades in the direction of the trend, avoiding counter-trend positions
2. Reverse Signal Exit
- No fixed stop-loss or fixed-period exits
- Exits only when a reverse entry signal triggers
- Maximizes trend profits, reduces premature exits
3. ATR Dynamic Pyramiding
- Adds positions when price moves 0.5 ATR in favorable direction
- Supports up to 2 units maximum (adjustable)
- Pyramid scaling to enhance profitability
4. Complete Risk Management
- Fixed position size (5000 USD per unit)
- Commission fee 0.06% (Binance spot rate)
- Initial capital 10,000 USD
---
## 📈 Trading Logic
Entry Conditions
✅ Long Entry:
- Close price breaks above 20-period high
- Structure trend is bullish (price breaks above Swing High)
✅ Short Entry:
- Close price breaks below 20-period low
- Structure trend is bearish (price breaks below Swing Low)
Add Position Conditions
- Long: Price rises ≥ 0.5 ATR
- Short: Price falls ≥ 0.5 ATR
- Maximum 2 units including initial entry
Exit Conditions
- Long Exit: When short entry signal triggers (price breaks 20-period low + structure turns bearish)
- Short Exit: When long entry signal triggers (price breaks 20-period high + structure turns bullish)
---
## ⚙️ Parameter Settings
Channel Settings
- Entry Channel Period: 20 (Donchian Channel breakout period)
- Exit Channel Period: 10 (reserved parameter, actually uses reverse signal exit)
ATR Settings
- ATR Period: 20
- Stop Loss ATR Multiplier: 2.0 (reserved parameter)
- Add Position ATR Multiplier: 0.5
Structure Filter
- Swing Length: 160 (Swing High/Low calculation period)
- Structure Timeframe: 1 minute (can change to 5/15/60, etc.)
Position Management
- Maximum Units: 2 (including initial entry)
- Capital Per Unit: 5000 USD
---
## 🎨 Visualization Features
Background Colors
- Light Green: Bullish structure
- Light Red: Bearish structure
- Dark Green: Long entry
- Dark Red: Short entry
Optional Display (Default: OFF)
- Entry/exit channel lines
- Structure high/low lines
- ATR stop-loss line
- Next add position indicator
- Entry/exit labels
---
## 📱 Alert Message Format
Strategy sends notifications on entry/exit with the following format:
- Entry: `1m Long EP:428.26`
- Add Position: `15m Add Long 2/2 EP:429.50`
- Exit: `1m Close Long Reverse Signal`
Where:
- `1m`/`15m` = Current chart timeframe
- `EP` = Entry Price
---
## 💰 Backtest Settings
Capital Allocation
- Initial Capital: 10,000 USD
- Per Entry: 5,000 USD (split into 2 entries)
- Leverage: 0x (spot trading)
Trading Costs
- Commission: 0.06% (Binance spot VIP0)
- Slippage: 0
---
## 🎯 Use Cases
✅ Best Scenarios
- Trending markets
- Moderate volatility assets
- 1-minute to 4-hour timeframes
⚠️ Not Suitable For
- Highly volatile choppy markets
- Low liquidity small-cap coins
- Extreme market conditions (black swan events)
---
## 📊 Usage Recommendations
Timeframe Suggestions
| Timeframe | Trading Style | Suggested Parameter Adjustment |
|-----------|--------------|-------------------------------|
| 1-5 min | Scalping | Swing Length 100-160 |
| 15-30 min | Short-term | Swing Length 50-100 |
| 1-4 hour | Swing Trading | Swing Length 20-50 |
Optimization Tips
1. Adjust swing length based on backtest results
2. Different coins may require different parameters
3. Recommend backtesting on 1-minute chart first before live trading
4. Enable labels to observe entry/exit points
---
## ⚠️ Risk Disclaimer
1. Past Performance Does Not Guarantee Future Results
- Backtest data is for reference only
- Live trading may be affected by slippage, delays, etc.
2. Market Condition Changes
- Strategy performs better in trending markets
- May experience frequent stops in ranging markets
3. Capital Management
- Do not invest more than you can afford to lose
- Recommend setting total capital stop-loss threshold
4. Commission Impact
- Frequent trading accumulates commission fees
- Recommend using exchange discounts (BNB fee reduction, etc.)
---
## 🔧 Troubleshooting
Q: No entry signals?
A: Check if structure filter is too strict, adjust swing length or timeframe
Q: Too many labels displayed?
A: Turn off "Show Labels" option in settings
Q: Poor backtest performance?
A:
1. Check if the coin is suitable for trend-following strategies
2. Adjust parameters (swing length, channel period)
3. Try different timeframes
Q: How to set alerts?
A:
1. Click "Alert" in top-right corner of chart
2. Condition: Select "Strategy - Trend Following CRYPTOCAP:ZEC "
3. Choose "Order filled"
4. Set notification method (Webhook/Email/App)
---
## 📞 Contact Information
Strategy Name: Trend Following CRYPTOCAP:ZEC
Version: v1.0
Pine Script Version: v6
Last Updated: December 2025
---
## 📄 Copyright Notice
This strategy is for educational and research purposes only.
All risks of using this strategy for live trading are borne by the user.
Commercial use without authorization is prohibited.
---
## 🎓 Learning Resources
To understand the strategy principles in depth, recommended reading:
- "The Complete TurtleTrader" - Curtis Faith
- "Trend Following" - Michael Covel
- TradingView Pine Script Official Documentation
---
Happy Trading! Remember to manage your risk 📈
100+ BTC Tracker + 182-Day Dormant (6-Month HODL)Instantly see what the biggest Bitcoin whales are doing — and exactly how much of the supply has been completely untouched for 6 full months or longer (182+ days), the strictest and most respected definition of true HODLing.
What this indicator shows you in real time:
Number of wallets holding ≥100 BTC (~15,800 whales)
Total Bitcoin controlled by these whales (~3.25 million BTC)
6-Month Dormant Supply — Bitcoin that hasn’t moved in 182+ days (~14.1 million BTC)
6-Month Dormant % — What percentage of circulating supply is truly locked away
Why 182 days matters:
The 6-month threshold (≈182 days) is the industry-standard cutoff used by Glassnode, CryptoQuant, and analysts worldwide to define ultra-long-term holders. These are the coins least likely to ever hit exchanges — the ultimate measure of conviction and scarcity.
Key features:Live or fallback? — Instantly know if you’re seeing real-time on-chain data (green) or verified backup values (yellow)
Works on free accounts — No paid data subscription required (though it becomes even more accurate with Glassnode/CryptoQuant add-ons)
Clean, non-intrusive design — Three bold plots + sleek dark table in the top-right corner
Always up to date — Fallback values manually verified as of November 21, 2025
Perfect for:
Spotting whale accumulation/distribution phases
Tracking real Bitcoin scarcity during bull or bear markets
Confirming long-term holder conviction before big moves
Add it to any BTC chart and instantly understand who really controls Bitcoin — and how much of it is locked away forever by the strongest hands in crypto.
Hellenic EMA Matrix - 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"
Asset Premium/Discount Monitor📊 Overview
The Asset Premium/Discount Monitor is a tool for analyzing the relative value between two correlated assets. It measures when one asset is trading at a premium or discount compared to its historical relationship with another asset, helping traders identify potential mean reversion opportunities, or pairs trading opportunities.
🎯 Use Cases
Perfect for analyzing:
NASDAQ:MSTR vs CRYPTO:BTCUSD - MicroStrategy's premium/discount to Bitcoin
NASDAQ:COIN vs BITSTAMP:BTCUSD - Coinbase's relative value to Bitcoin
NASDAQ:TSLA vs NASDAQ:QQQ - Tesla's premium to tech sector
Regional banks AMEX:KRE vs AMEX:XLF - Individual bank stocks vs financial sector
Any two correlated assets where relative value matters
Example of a trade: MSTR vs BTC - When indicator shows MSTR at 95% percentile (extreme premium): Short MSTR, Buy BTC. Then exit when the spread reverts to the mean, say 40-60% percentile.
🔧 How It Works
Core Calculation
Ratio Analysis: Calculates the price ratio between your asset and the correlated asset
Historical Baseline: Establishes the "normal" relationship using a 252-day moving average. You can change this.
Premium Measurement: Measures current deviation from historical average as a percentage
Statistical Context: Provides percentile rankings and standard deviation bands
The Math
Premium % = (Current Ratio / Historical Average Ratio - 1) × 100
🎨 Customization Options
Correlated Asset: Choose any symbol for comparison
Lookback Period: Adjust historical baseline (50-1000 days)
Smoothing: Reduce noise with moving average (1-50 days)
Visual Toggles: Show/hide bands and percentile lines
Color Themes: Customize premium/discount colors
📊 Interpretation Guide
Premium/Discount Reading
Positive %: Asset trading above historical relationship (premium)
Negative %: Asset trading below historical relationship (discount)
Near 0%: Asset at fair value relative to correlation
Percentile Ranking
90%+: Near recent highs - potential selling opportunity
10% and below: Near recent lows - potential buying opportunity
25-75%: Normal trading range
Signal Classifications
🔴 SELL PREMIUM: Asset expensive relative to recent range
🟡 Premium Rich: Moderately expensive, monitor for reversal
⚪ NEUTRAL: Fair value territory
🟡 Discount Opportunity: Moderately cheap, potential accumulation zone
🟢 BUY DISCOUNT: Asset cheap relative to recent range
🚨 Built-in Alerts
Extreme Premium Alert: Triggers when percentile > 95%
Extreme Discount Alert: Triggers when percentile < 5%
⚠️ Important Notes
Works best with highly correlated assets
Historical relationships can change - monitor correlation strength
Not investment advice - use as one factor in your analysis
Backtest thoroughly before implementing any strategy
🔄 Updates & Future Features
This indicator will be continuously improved based on user feedback. So... please give me your feedback!
Cycle Composite 3.6 WeightedThe Cycle Composite is a multi-factor market cycle model designed to classify long-term market behavior into distinct phases using normalized and weighted data inputs.
It combines ten key on-chain, dominance, volatility, sentiment, and trend-following metrics into a single composite output. The goal is to provide a clearer understanding of where the market may stand in the broader cycle (e.g., accumulation, early bull, late bull, or euphoria).
This version (3.4) introduces flexible weighting, trend strength markers, and additional context-aware signals such as risk-on confirmations and altseason flags.
Phases Identified:
The model categorizes the market into one of five zones:
Euphoria (> 85)
Late Bull (70 – 85)
Mid Bull (50 – 70)
Early Bull (30 – 50)
Fear (< 30)
Each phase is determined by a smoothed EMA of the weighted composite score.
Data Sources and Metrics Used (10 total):
BTC Dominance (CRYPTOCAP:BTC.D)
Stablecoin Dominance (USDT + USDC average) (inverted for risk-on)
ETH Dominance (CRYPTOCAP:ETH.D)
BBWP (normalized Bollinger Band Width % over 1-year window)
WVF (Williams VIX Fix for volatility spike detection)
NUPL (Net Unrealized Profit/Loss, external source)
CMF (Chaikin Money Flow, smoothed volume accumulation)
CEX Open Interest (custom input from DAO / external source)
Whale Inflows (custom input from whale exchange transfer data)
Google Trends Average (BTC, Crypto, Altcoin terms)
All inputs are normalized over a 200-bar window and combined via weighted averaging, where each weight is user-configurable.
Additional Features:
Phase Labels: Labels are printed only when a new phase is entered.
Bull Continuation Marker: Triangle up when composite makes higher highs and NUPL increases.
Weakening Marker: Triangle down when composite rolls over in Late Bull and NUPL falls.
Risk-On Signal: Green circle appears when CMF and Google Trends are both rising.
Altseason Flag: Orange diamond appears when dominance of "others.d" exceeds BTC.D and ETH.D and composite is above 50.
Background Shading: Each phase is shaded with a semi-transparent background color.
Timeframe-Aware Display: All markers and signals are shown only on weekly timeframe for clarity.
Intended Use:
This script is intended for educational and macro-trend analysis purposes.
It can be used to:
Identify macro cycle position (accumulation, bull phases, euphoria, etc.)
Spot long-term trend continuation or weakening signals
Add context to price action with external on-chain and sentiment data
Time rotation events such as altseason risk
Disclaimer:
This script does not constitute financial advice.
It is intended for informational and research purposes only.
Users should conduct their own due diligence and analysis before making investment decisions.
Fibonacci Levels with SMA SignalsThis strategy leverages Fibonacci retracement levels along with the 100-period and 200-period Simple Moving Averages (SMAs) to generate robust entry and exit signals for long-term swing trades, particularly on the daily timeframe. The combination of Fibonacci levels and SMAs provides a powerful way to capitalize on major trend reversals and market retracements, especially in stocks and major crypto assets.
The core of this strategy involves calculating key Fibonacci retracement levels (23.6%, 38.2%, 61.8%, and 78.6%) based on the highest high and lowest low over a 365-day lookback period. These Fibonacci levels act as potential support and resistance zones, indicating areas where price may retrace before continuing its trend. The 100-period SMA and 200-period SMA are used to define the broader market trend, with the strategy favoring uptrend conditions for buying and downtrend conditions for selling.
This indicator highlights high-probability zones for long or short swing setups based on Fibonacci retracements and the broader trend, using the 100 and 200 SMAs.
In addition, this strategy integrates alert conditions to notify the trader when these key conditions are met, providing real-time notifications for optimal entry and exit points. These alerts ensure that the trader does not miss significant trade opportunities.
Key Features:
Fibonacci Retracement Levels: The Fibonacci levels provide natural price zones that traders often watch for potential reversals, making them highly relevant in the context of swing trading.
100 and 200 SMAs: These moving averages help define the overall market trend, ensuring that the strategy operates in line with broader price action.
Buy and Sell Signals: The strategy generates buy signals when the price is above the 200 SMA and retraces to the 61.8% Fibonacci level. Sell signals are triggered when the price is below the 200 SMA and retraces to the 38.2% Fibonacci level.
Alert Conditions: The alert conditions notify traders when the price is at the key Fibonacci levels in the context of an uptrend or downtrend, allowing for efficient monitoring of trade opportunities.
Application:
This strategy is ideal for long-term swing trades in both stocks and major cryptocurrencies (such as BTC and ETH), particularly on the daily timeframe. The daily timeframe allows for capturing broader, more sustained trends, making it suitable for identifying high-quality entries and exits. By using the 100 and 200 SMAs, the strategy filters out noise and focuses on larger, more meaningful trends, which is especially useful for longer-term positions.
This script is optimized for swing traders looking to capitalize on retracements and trends in markets like stocks and crypto. By combining Fibonacci levels with SMAs, the strategy ensures that traders are not only entering at optimal levels but also trading in the direction of the prevailing trend.
Bitcoin Total VolumeThis Pine Script indicator, titled "Bitcoin Top 16 Volume," is designed to provide traders with an aggregate view of Bitcoin (BTC) spot trading volume across leading cryptocurrency exchanges. Unlike traditional volume indicators that focus on a single exchange, this tool compiles data from a selection of the top exchanges as ranked by CoinMarketCap, offering a broader perspective on overall market activity.
The indicator works by fetching real-time volume data for specific BTC trading pairs on various exchanges. It currently incorporates data from prominent platforms such as Binance (BTCUSDT), Coinbase (BTCUSD), OKX (BTCUSDT), Bybit (BTCUSDT), Kraken (BTCUSD), Bitfinex (BTCUSD), Bitstamp (BTCUSD), Gemini (BTCUSD), Upbit (BTCKRW), Bithumb (BTCKRW), KuCoin (BTCUSDT), Gate.io (BTCUSDT), MEXC (BTCUSDT), Crypto.com (BTCUSD), Poloniex (BTCUSDT), and BitMart (BTCUSDT). It's important to note that while the indicator aims to represent the "Top 16" exchanges, the actual number included may vary due to data availability within TradingView and the dynamic nature of exchange rankings.
The script then calculates the total volume by summing up the volume data retrieved from each of these exchanges. This aggregated volume is visually represented as a histogram directly on your TradingView chart, displayed in white by default. By observing the height of the histogram bars, traders can quickly assess the total trading volume for Bitcoin spot markets over different time periods, corresponding to the chart's timeframe.
This indicator is valuable for traders seeking to understand the overall market depth and liquidity of Bitcoin. Increased total volume can often signal heightened market interest and potential trend strength or reversals. Conversely, low volume might suggest consolidation or reduced market participation. Traders can use this indicator to confirm trends, identify potential breakouts, and gauge the general level of activity in the Bitcoin spot market across major exchanges. Keep in mind that the list of exchanges included may need periodic updates to accurately reflect the top exchanges as rankings on CoinMarketCap evolve.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
---
### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
---
### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
---
### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
---
### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
---
### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
---
### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
---
### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
Composite Indicator (CCI + ATR)Composite Indicator (CCI + ATR)
The Composite Indicator (CCI + ATR) combines the Commodity Channel Index (CCI) with the Average True Range (ATR) , providing traders with a dynamic tool for identifying entry and exit points based on momentum and volatility. This indicator is particularly useful for markets like cryptocurrencies, which often exhibit sharp sell-offs and gradual upward trends.
Key Features
Momentum Analysis with CCI: The CCI calculates price momentum by comparing the current price level to its average over a specific period. The indicator generates signals when CCI crosses predefined thresholds.
- Buy Signal: Triggered when CCI crosses above the lower threshold (e.g., -100).
- Sell Signal: Triggered when CCI crosses below the upper threshold (e.g., +100).
Volatility Filtering with ATR: The ATR measures market volatility, ensuring signals occur only during significant price movements.
Separate multipliers for buy and sell signals allow tailored filtering based on market behavior.
Stop Loss Calculation: Dynamic stop loss levels are calculated using the ATR multiplier to adapt to market volatility, offering better risk management.
How It Works
CCI Calculation: The CCI is calculated using the typical price ((High + Low + Close) / 3) and a user-defined length. It detects momentum changes by measuring deviations from the average price.
ATR Calculation: The ATR determines the average price range over a specified period, identifying the market’s volatility. The ATR SMA acts as a baseline to filter signals.
Buy Signal: A buy signal is triggered when:
- CCI crosses above the lower threshold (e.g., -100).
- ATR exceeds its SMA multiplied by the buy multiplier (e.g., 1.0).
Sell Signal: A sell signal is triggered when:
- CCI crosses below the upper threshold (e.g., +100).
- ATR exceeds its SMA multiplied by the sell multiplier (e.g., 0.95).
Stop Loss Integration:
- Long positions: Stop loss = Low – (ATR * ATR Multiplier)
- Short positions: Stop loss = High + (ATR * ATR Multiplier)
Advantages
Combines momentum (CCI) and volatility (ATR) for precise signal generation.
Customizable thresholds and multipliers for different market conditions.
Dynamic stop loss ensures better risk management in volatile markets.
Suggested Parameter Settings
CCI Length: 20 (default). Adjust as follows:
- 10–15: Shorter timeframes (e.g., 5-15 minutes).
- 20: General use for 1-hour timeframes.
- 30–50: Longer timeframes (e.g., 4-hour or daily charts).
CCI Threshold: 100 (default). Adjust as follows:
- 50–75: For more frequent signals in ranging markets.
- 100: Balanced for most trading conditions.
- 150–200: For strong trends to reduce noise.
ATR Length: 14 (default). Adjust as follows:
- 10–14: For assets with moderate volatility.
- 20: For assets with lower volatility.
ATR Buy Multiplier: 1.0 (default). Adjust as follows:
- 0.9–1.0: For gradual uptrends in crypto markets.
- 1.1–1.2: For stronger trend filtering.
ATR Sell Multiplier: 0.95 (default). Adjust as follows:
- 0.8–0.95: For sharp sell-offs.
- 1.0–1.1: For stable downward trends.
ATR Multiplier (Stop Loss): 1.5 (default). Adjust as follows:
- 1.0–1.2: For shorter timeframes or less volatile markets.
- 2.0–2.5: For highly volatile markets like cryptocurrencies.
Example Use Cases
Scalping (5-15 minute charts): Use CCI Length = 10, CCI Threshold = 75, ATR Buy Multiplier = 0.9, ATR Sell Multiplier = 0.8.
Day Trading (1-hour charts): Use CCI Length = 20, CCI Threshold = 100, ATR Buy Multiplier = 1.0, ATR Sell Multiplier = 0.95.
Swing Trading (4-hour or daily charts): Use CCI Length = 30, CCI Threshold = 150, ATR Buy Multiplier = 1.2, ATR Sell Multiplier = 1.0.
Final Thoughts The Composite Indicator (CCI + ATR) is a versatile tool designed to enhance trading decisions by combining momentum analysis with volatility filtering. Whether scalping or swing trading, this indicator provides actionable insights and robust risk management to navigate complex markets effectively.
BTC Slayer 9000 - Relative Risk-adjusted performanceBTC Slayer 9000: Relative Risk-Adjusted Performance
Dear friends and fellow traders,
I am pleased to introduce the BTC Slayer 9000, a script designed to provide clear insights into risk-adjusted performance relative to a benchmark. Whether you're navigating the volatile world of cryptocurrencies or exploring opportunities in stocks, this tool helps you make informed decisions by comparing assets against your chosen benchmark.
What Does It Do?
This indicator is based on the Ulcer Index (UI), a metric that measures downside risk. It calculates the Ulcer Performance Index (UPI), which combines returns and downside risk, and compares it to a benchmark (like BTC/USDT, SPY500, or any trading pair).
The result is the Relative UPI (RUPI):
Positive RUPI (green area): The asset's risk-adjusted performance is better than the benchmark.
Negative RUPI (red area): The asset's risk-adjusted performance is worse than the benchmark.
Why Use It?
Risk vs. Reward: See if the extra risk of an asset is justified by its returns.
Customizable Benchmark: Compare any asset against BTC, SPY500, or another chart.
Dynamic Insights: Quickly identify outperforming assets for long positions and underperformers for potential shorts.
How to Use:
Inputs:
Adjust the lookback period to set the time frame for analysis. 720 Period is meant to represent 30 days. I like to use 168 period because I do not hold trades for long.
Choose your comparison chart (e.g., BTC/USDT, SPY500, AAPL, etc.).
Interpretation:
Green Area Above 0: The asset offers better risk-adjusted returns than the benchmark.
Red Area Below 0: The benchmark is a safer or more rewarding option.
Perfect for All Traders
Whether you:
Trade Cryptocurrencies: Compare altcoins to BTC.
Invest in Stocks: Compare individual stocks to indices like SPY500.
Evaluate Portfolio Options: Decide between assets like AAPL or TSLA.
This indicator equips you with a systematic way to evaluate "Is the extra risk worth it?".
The script was compiled in Collaboration with ChatGPT
Smart DCA Strategy (Public)INSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost.
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on
BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
Stablecoin Delta [SAKANE]Overview
Stablecoin Delta is an indicator designed to provide a detailed analysis of the market trends of major stablecoins (USDT and USDC). Stablecoins play a crucial role in supporting the liquidity of the cryptocurrency market, and fluctuations in their supply significantly impact the prices of Bitcoin and other cryptocurrencies.
This indicator leverages data from CryptoCap to visualize the daily changes in the market capitalization of stablecoins. Traders can use this tool to understand the effects of stablecoin supply fluctuations on the market in a timely manner, enabling more strategic investment decisions.
The key benefits include the ability to quickly monitor stablecoin supply changes, utilize this data as a supplementary tool for predicting Bitcoin price movements, and identify both short-term market movements and long-term trends. This indicator is valuable for traders of all levels, from beginners to seasoned professionals.
Features
- Support for USDT and USDC Market Cap
Monitor the market trends of these two major stablecoins using data from CryptoCap. Users can also choose to analyze only one of them.
- Daily Net Change Calculation
Calculates the daily change in market capitalization compared to the previous day, providing a clear view of trends.
- Flexible Smoothing Options
Apply either SMA or EMA smoothing for both the histogram and the line chart, based on user preference.
- Customizable Colors
Customize the colors for the histogram (positive/negative) and line chart for better visualization.
Visualization
- Histogram
Displays daily net changes as a histogram, with positive changes (green) and negative changes (red) clearly differentiated.
- Smoothed Line Chart
Provides a smoothed line chart to make trend identification easier.
Use Cases
- In-depth Analysis of the Cryptocurrency Market
The supply of stablecoins is a critical factor influencing the price of Bitcoin and other cryptocurrencies. This indicator helps traders understand overall market liquidity, enabling more effective investment decisions.
- Short-Term and Long-Term Strategy Development
Trends derived from stablecoin supply fluctuations are essential for traders to gauge short-term price movements and long-term market flows.
- Real-Time Market Adjustment
In times of sudden market shifts, this tool enables traders to quickly assess changes in stablecoin supply and adjust their positions accordingly.
Future Plans
- Additional stablecoins will be considered for inclusion if their market share grows significantly.
Disclaimer
- This indicator relies on data from CryptoCap. The results are subject to the accuracy and timeliness of the data and should be used as reference information only.
SMT Divergence ICT 01 [TradingFinder] Smart Money Technique🔵 Introduction
SMT Divergence (short for Smart Money Technique Divergence) is a trading technique in the ICT Concepts methodology that focuses on identifying divergences between two positively correlated assets in financial markets.
These divergences occur when two assets that should move in the same direction move in opposite directions. Identifying these divergences can help traders spot potential reversal points and trend changes.
Bullish and Bearish divergences are clearly visible when an asset forms a new high or low, and the correlated asset fails to do so. This technique is applicable in markets like Forex, stocks, and cryptocurrencies, and can be used as a valid signal for deciding when to enter or exit trades.
Bullish SMT Divergence : This type of divergence occurs when one asset forms a higher low while the correlated asset forms a lower low. This divergence is typically a sign of weakness in the downtrend and can act as a signal for a trend reversal to the upside.
Bearish SMT Divergence : This type of divergence occurs when one asset forms a higher high while the correlated asset forms a lower high. This divergence usually indicates weakness in the uptrend and can act as a signal for a trend reversal to the downside.
🔵 How to Use
SMT Divergence is an analytical technique that identifies divergences between two correlated assets in financial markets.
This technique is used when two assets that should move in the same direction move in opposite directions.
Identifying these divergences can help you pinpoint reversal points and trend changes in the market.
🟣 Bullish SMT Divergence
This divergence occurs when one asset forms a higher low while the correlated asset forms a lower low. This divergence indicates weakness in the downtrend and can signal a potential price reversal to the upside.
In this case, when the correlated asset is forming a lower low, and the main asset is moving lower but the correlated asset fails to continue the downward trend, there is a high probability of a trend reversal to the upside.
🟣 Bearish SMT Divergence
Bearish divergence occurs when one asset forms a higher high while the correlated asset forms a lower high. This type of divergence indicates weakness in the uptrend and can signal a potential trend reversal to the downside.
When the correlated asset fails to make a new high, this divergence may be a sign of a trend reversal to the downside.
🟣 Confirming Signals with Correlation
To improve the accuracy of the signals, use assets with strong correlation. Forex pairs like OANDA:EURUSD and OANDA:GBPUSD , or cryptocurrencies like COINBASE:BTCUSD and COINBASE:ETHUSD , or commodities such as gold ( FX:XAUUSD ) and silver ( FX:XAGUSD ) typically have significant correlation. Identifying divergences between these assets can provide a strong signal for a trend change.
🔵 Settings
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
Bullish Divergence Line : Displays a line showing bullish divergence from the lows.
Bearish Divergence Line : Displays a line showing bearish divergence from the highs.
Bullish Divergence Label : Displays the "+SMT" label for bullish divergences.
Bearish Divergence Label : Displays the "-SMT" label for bearish divergences.
🔵 Conclusion
SMT Divergence is an effective tool for identifying trend changes and reversal points in financial markets based on identifying divergences between two correlated assets. This technique helps traders receive more accurate signals for market entry and exit by analyzing bullish and bearish divergences.
Identifying these divergences can provide opportunities to capitalize on trend changes in Forex, stocks, and cryptocurrency markets. Using SMT Divergence along with risk management and confirming signals with other technical analysis tools can improve the accuracy of trading decisions and reduce risks from sudden market changes.
XRP Comparative Price Action Indicator - Final VersionXRP Comparative Price Action Indicator - Final Version
The XRP Comparative Price Action Indicator provides a comprehensive visual analysis of XRP’s price movements relative to key cryptocurrencies and market indices. This indicator normalises price data across various assets, allowing traders and investors to assess XRP’s performance against its peers and major market influences at a glance.
Key Features:
• Normalised Price Data: Prices are scaled between 0.00 and 1.00,
enabling straightforward comparisons between different assets.
• Key Comparisons: Includes normalised prices for:
• XRP/USD (Bitstamp)
• XRP Dominance (CryptoCap)
• XRP/BTC (Bitstamp)
• BTC/USD (Bitstamp)
• BTC Dominance (CryptoCap)
• USDT Dominance (CryptoCap)
• S&P 500 (SPY)
• DXY (Dollar Index)
• ETH/USD (Bitstamp)
• ETH Dominance (CryptoCap)
• XRP/ETH (Binance)
• Visual Clarity: Each asset is plotted with distinct colors for easy identification,
with thicker lines enhancing visibility on the chart.
• Reference Lines: Optional horizontal lines indicate the minimum (0) and maximum (1) normalised values, providing clear reference points for analysis.
This indicator is ideal for traders looking to understand XRP’s relative performance, gauge market sentiment, and make informed trading decisions based on comparative price action.
Uptrick: Dual Moving Average Volume Oscillator
Title: Uptrick: Dual Moving Average Volume Oscillator (DPVO)
### Overview
The "Uptrick: Dual Moving Average Volume Oscillator" (DPVO) is an advanced trading tool designed to enhance market analysis by integrating volume data with price action. This indicator is specially developed to provide traders with deeper insights into market dynamics, making it easier to spot potential entry and exit points based on volume and price interactions. The DPVO stands out by offering a sophisticated approach to traditional volume analysis, setting it apart from typical volume indicators available on the TradingView platform.
### Unique Features
Unlike traditional indicators that analyze volume and price movements separately, the DPVO combines these two critical elements to offer a comprehensive view of market behavior. By calculating the Volume Impact, which involves the product of the exponential moving averages (EMAs) of volume and the price range (close - open), this indicator highlights significant trading activities that could indicate strong buying or selling pressure. This method allows traders to see not just the volume spikes, but how those spikes relate to price movements, providing a clearer picture of market sentiment.
### Customization and Inputs
The DPVO is highly customizable, catering to various trading styles and strategies:
- **Oscillator Length (`oscLength`)**: Adjusts the period over which the volume and price difference is analyzed, allowing traders to set it according to their trading timeframe.
- **Fast and Slow Moving Averages (`fastMA` and `slowMA`)**: These parameters control the responsiveness of the DPVO. A shorter `fastMA` coupled with a longer `slowMA` can help in identifying trends quicker or smoothing out market noise for more conservative approaches.
- **Signal Smoothing (`signalSmooth`)**: This input helps in reducing signal noise, making the crossover and crossunder points between the DVO and its smoothed signal line clearer and easier to interpret.
### Functionality Details
The DPVO operates through a sequence of calculated steps that integrate volume data with price movement:
1. **Volume Impact Calculation**: This is the foundational step where the product of the EMA of volume and the EMA of price range (close - open) is calculated. This metric highlights trading sessions where significant volume accompanies substantial price movements, suggesting a strong market response.
2. **Dynamic Volume Oscillator (DVO)**: The heart of the indicator, the DVO, is derived by calculating the difference between the fast EMA and the slow EMA of the Volume Impact. This result is then normalized by dividing by the EMA of the volume over the same period to scale the output, making it consistent across various trading environments.
3. **Signal Generation**: The final output is smoothed using a simple moving average of the DVO to filter out market noise. Buy and sell signals are generated based on the crossover and crossunder of the DVO with its smoothed version, providing clear cues for market entry or exit.
### Originality
The DPVO's originality lies in its innovative integration of volume and price movement, a novel approach not typically observed in other volume indicators. By analyzing the product of volume and price change EMAs, the DPVO captures the essence of market dynamics more holistically than traditional tools, which often only reflect volume levels without contextualizing them with price actions. This dual analysis provides traders with a deeper understanding of market forces, enabling them to make more informed decisions based on a combination of volume surges and significant price movements. The DPVO also introduces a unique normalization and smoothing technique that refines the oscillator's output, offering cleaner and more reliable signals that are adaptable to various market conditions and trading styles.
### Practical Application
The DPVO excels in environments where volume plays a crucial role in validating price movements. Traders can utilize the buy and sell signals generated by the DPVO to enhance their decision-making process. The signals are plotted directly on the trading chart, with buy signals appearing below the price bars and sell signals above, ensuring they are prominent and actionable. This setup is particularly useful for day traders and swing traders who rely on timely and accurate signals to maximize their trading opportunities.
### Best Practices
To maximize the effectiveness of the DPVO, traders should consider the following best practices:
- **Market Selection**: Use the DPVO in markets known for strong volume-price correlation such as major forex pairs, popular stocks, and cryptocurrencies.
- **Signal Confirmation**: While the DPVO provides powerful signals, confirming these signals with additional indicators such as RSI or MACD can increase trade reliability.
- **Risk Management**: Always use stop-loss orders to manage risks associated with trading signals. Adjust the position size based on the volatility of the asset to avoid significant losses.
### Practical Example + How to use it
Practical Example1: Day Trading Cryptocurrencies
For a day trader focusing on the highly volatile cryptocurrency market, the DPVO can be an effective tool on a 15-minute chart. Suppose a trader is monitoring Bitcoin (BTC) during a period of high market activity. The DPVO might show an upward crossover of the DVO above its smoothed signal line while also indicating a significant increase in volume. This could signal that strong buying pressure is entering the market, suggesting a potential short-term rally. The trader could enter a long position based on this signal, setting a stop-loss just below the recent support level to manage risk. If the DPVO later shows a crossover in the opposite direction with decreasing volume, it might signal a good exit point, allowing the trader to lock in profits before a potential pullback.
- **Swing Trading Stocks**: For a swing trader looking at stocks, the DPVO could be applied on a daily chart. If the oscillator shows a consistent downward trend along with increasing volume, this could suggest a potential sell-off, providing a sell signal before a significant downturn.
You can look for:
--> Increase in volume - You can use indicators like 24-hour-Volume to have a better visualization
--> Uptrend/Downtrend in the indicator (HH, HL, LL, LH)
--> Confirmation (Buy signal/Sell signal)
--> Correct Price action (Not too steep moves up or down. Stable moves.) (Optional)
--> Confirmation with other indicators (Optional)
Quick image showing you an example of a buy signal on SOLANA:
### Technical Notes
- **Calculation Efficiency**: The DPVO utilizes exponential moving averages (EMAs) in its calculations, which provides a balance between responsiveness and smoothing. EMAs are favored over simple moving averages in this context because they give more weight to recent data, making the indicator more sensitive to recent market changes.
- **Normalization**: The normalization of the DVO by the EMA of the volume ensures that the oscillator remains consistent across different assets and timeframes. This means the indicator can be used on a wide variety of markets without needing significant adjustments, making it a versatile tool for traders.
- **Signal Line Smoothing**: The final signal line is smoothed using a simple moving average (SMA) to reduce noise. The choice of SMA for smoothing, as opposed to EMA, is intentional to provide a more stable signal that is less prone to frequent whipsaws, which can occur in highly volatile markets.
- **Lag and Sensitivity**: Like all moving average-based indicators, the DPVO may introduce a slight lag in signal generation. However, this is offset by the indicator’s ability to filter out market noise, making it a reliable tool for identifying genuine trends and reversals. Adjusting the `fastMA`, `slowMA`, and `signalSmooth` inputs allows traders to fine-tune the sensitivity of the DPVO to match their specific trading strategy and market conditions.
- **Platform Compatibility**: The DPVO is written in Pine Script™ v5, ensuring compatibility with the latest features and functionalities offered by TradingView. This version takes advantage of optimized functions for performance and accuracy in calculations, making it well-suited for real-time analysis.
Conclusion
The "Uptrick: Dual Moving Average Volume Oscillator" is a revolutionary tool that merges volume analysis with price movement to offer traders a more nuanced understanding of market trends and reversals. Its ability to provide clear, actionable signals based on a unique combination of volume and price changes makes it an invaluable addition to any trader's toolkit. Whether you are managing long-term positions or looking for quick trades, the DPVO provides insights that can help refine any trading strategy, making it a standout choice in the crowded field of technical indicators.
Nothing from this indicator or any other Uptrick Indicators is financial advice. Only you are ultimately responsible for your choices.
MVRV-Z adjusted EN version (by ilyaevp95)Descriptions:
The MVRV Z-Score indicator is a powerful tool designed by original authors Murad Mahmudov and David Puell for BTC to help traders make informed decisions about their cryptocurrency investments. It is based on the MVRV (Market Value to Realized Value) metric, which measures the relationship between the market capitalization and the realized capitalization of a cryptocurrency. The indicator provides signals for accumulating or selling an asset based on deviations in market capitalization from realized capitalization.
How it works:
Market Capitalization : This is the total value of coins that have been issued at a given point in time. Market capitalization is calculated by multiplying the current price of the asset by the number of coins that have been issued.
Realized Capitalization (Realized Price) : This is the amount of money that has been spent on purchasing a particular asset. In the context of cryptocurrencies, it represents the sum of all transaction values for a specific blockchain. Realized capitalization can be calculated using historical data on transaction prices.
MVRV Metric : The MVRV metric compares market capitalization with realized capitalization, providing a measure of how overvalued or undervalued a cryptocurrency is relative to its historical transaction data. A high MVRV value indicates that the market is overvaluing the asset, while a low MVRV suggests undervaluation.
Z-Score Calculation : The Z-score is a statistical measure that normalizes the deviation of market capitalization from its mean value (realized capitalization) to a standard deviation. This makes it possible to compare assets that have different values and time periods, as it takes into account the volatility of the market.
Note: For accurate Z-score calculation, you need to use the indicator on a chart with a mostly complete historical data set for a specific cryptocurrency.
Signals : Based on the Z-score, the indicator generates signals for accumulation or sale. If the Z-score falls below a certain threshold (negative), it may indicate an opportunity to accumulate the asset. Conversely, if the Z-score rises above a positive threshold, it could suggest a potential sell signal.
The indicator uses a color-coded system to provide traders with visual cues:
Green background indicates a signal to accumulate.
Orange (Red) background indicates a signal to sell.
Deviations exceeding the specified thresholds by 1 and 2 Z (positive direction), 0.5 and 1 Z (negative direction) are highlighted in a brighter color, indicating more extreme deviations.
Note: The signals provided by this indicator should not be considered financial advice. Traders should conduct their own research (DYOR) before making any investment decisions.
Parameters: The indicator provides several parameters for customization:
Blockchain : The blockchain for which the analysis is performed. This allows the user to select the specific blockchain they are interested in analyzing. The default value is BTC.
Z threshold for positive deviations : This parameter sets the threshold above which the deviation will be considered positive. A higher value will result in fewer signals, while a lower value may generate more false signals. The default value is 3.0.
Z threshold for negative deviations : Similar to the previous parameter, this sets the threshold below which the deviation will be considered negative. The default value is 0.
Market Capitalization : There are two types of market capitalization available: Standard and Free float coin capitalization. Free float is calculated by multiplying its current price by the total number of units in free circulation - the number that are not locked in any contracts or other forms of restriction. For DASH, ZEC, BAT and ALGO available only Free float capitalization. The default value is "Standard"
Negative Deviation Filter Mode : When enabled, if the deviation has been positive for a certain number of previous weeks (the default value is 40 weeks), the indicator will not generate a signal to accumulate. This helps to avoid false signals during the start of a bearish market. This may be helpful for volatile coins, whose price can drastically fall below the realized price after the end of a bull market. The default setting is "disabled".
Display Options:
MVRV plot : Displays the MVRV metric for the selected blockchain.
Z-Score plot : Shows the Z-score calculated by the indicator.
Realized Price plot : Provides a visual representation of the realized price of the cryptocurrency on main chart.
S ignal Display : Choose whether to display signals on the main chart or in a separate panel.
Historical mode : Choose whether to show signals for all historical data on the chart or for a certain number of periods. The default setting is "disabled".
MC vs Total MCMC vs Total MC
this is an edit of StableCoin MC vs Total MC by Crypto5Max supporting muti timeframes and addition dominances
is a powerful and versatile TradingView indicator designed to help traders and analysts visualize the dominance of different types of cryptocurrencies (StableCoin, AltCoin, BTC, ETH) relative to the total market capitalization. This indicator provides a clear and concise way to monitor market trends and make informed decisions based on the dominance of specific cryptocurrency segments.
Key Features:
Customizable Time Frames: Select from a variety of time frames including 5 Min, 15 Min, 30 Min, 1HR, 2HR, 4HR, 8HR, and Daily to tailor the analysis to your needs.
Dominance Type Selection: Choose the type of market capitalization dominance you want to track - StableCoins, AltCoins, Bitcoin, or Ethereum.
Total Market Capitalization Options: Analyze the market with different total market capitalization metrics - total crypto market cap, total market cap excluding BTC, or total market cap excluding BTC and ETH.
Dynamic Label Display: A label that follows the plotted dominance line and dynamically displays the dominance percentage, providing a clear visual representation.
Invisible Background Option: Choose to have an invisible background for a cleaner chart presentation.
How It Works:
Time Frame Selection: Use the time_frame input to choose the desired time frame for your analysis.
Dominance Type Selection: Select the type of dominance to display using the mcap_type input.
Total Market Capitalization Selection: Choose the total market capitalization metric with the total_sym input.
Dominance Calculation: The indicator calculates the dominance of the selected cryptocurrency type as a percentage of the total market capitalization.
Visual Display: The chosen dominance is plotted on the chart, and a label displaying the dominance percentage is dynamically updated to follow the plotted line.
Use Cases:
Market Trend Analysis: Identify trends in the dominance of StableCoins, AltCoins, BTC, or ETH to gauge market sentiment.
Portfolio Allocation: Make informed decisions about portfolio allocation by understanding the market share of different cryptocurrency types.
Technical Analysis: Combine with other technical indicators to enhance your trading strategy and gain deeper market insights.
This indicator is essential for traders, analysts, and investors who want to stay ahead of market movements and make data-driven decisions based on the dominance of various cryptocurrency segments.
Example:
If you select "AltCoin" as the dominance type and "Total 3" as the total market capitalization, the indicator will plot the dominance of AltCoins (excluding BTC and ETH) as a percentage of the total crypto market capitalization (excluding BTC and ETH) on the selected time frame. The dynamic label will display this percentage, updating as the market evolves.
Elevate your market analysis with the MC vs Total MC indicator and gain a comprehensive view of cryptocurrency dominance trends.
MVRV Ratio - R.BonaldiMVRV Ratio Indicator
The MVRV Ratio Indicator is a powerful tool for cryptocurrency traders and investors. It provides a visual representation of the Market Value to Realized Value ratio, helping you assess whether a cryptocurrency is overvalued or undervalued.
What is the MVRV Ratio?
Market Value: The current market price of the cryptocurrency multiplied by its circulating supply.
Realized Value: The average price at which each unit of the cryptocurrency was last moved on the blockchain, providing a more realistic view of its actual value.
How to Use This Indicator:
Identify Critical Levels:
The indicator displays a blue line representing the MVRV Ratio.
Horizontal lines at levels 1 (red) and 3 (green) help you quickly see significant thresholds.
When the blue line is below the red line (MVRV < 1), the cryptocurrency is considered undervalued.
When the blue line is above the green line (MVRV > 3), the cryptocurrency is considered overvalued.
Visual Cues:
The background turns red when the MVRV Ratio is below 1, indicating potential buying opportunities.
The background turns green when the MVRV Ratio is above 3, signaling potential selling opportunities.
Why Use the MVRV Ratio?
Risk Management: By identifying overvalued and undervalued conditions, you can make more informed decisions, reducing the risk of buying high and selling low.
Market Sentiment: The MVRV Ratio provides insight into market sentiment, helping you gauge the overall mood and potential future movements.
Timing: Use the indicator to time your entries and exits more effectively, aligning your trades with the underlying value of the cryptocurrency.
Whether you're a long-term investor looking to accumulate during undervalued periods or a short-term trader aiming to capitalize on overvalued spikes, the MVRV Ratio Indicator offers a clear and concise way to enhance your trading strategy.
Liquidation Level ScreenerThe Liquidation Level Screener is an analytical tool designed for traders who seek a comprehensive view of potential liquidation zones in the market. This script, adaptable to almost any timeframe from 1 minute to 3 days, offers a unique perspective by mapping out key liquidation levels where significant market actions could occur.
Key Features:
Multi-Exchange Data Aggregation: Unlike many other indicators, the Liquidation Levels Indicator compiles data from multiple leading exchanges including Binance, Bitmex, Kraken, and Bitfinex. This approach ensures a more holistic and accurate representation of market sentiment, providing insights into potential liquidation points across various platforms.
Customizable Timeframes and Modes: The script is versatile, working effectively across various timeframes. It operates in two distinct modes:
Actual Levels Display: Visually represents potential liquidation levels.
Settings Mode: Showcases an open interest (OI) oscillator. When OI is exceptionally high, indicating a surge in opened positions at a specific candle, it signals traders to be vigilant about upcoming liquidation levels.
Three-Tier Liquidation System: The indicator categorizes liquidation levels into three distinct tiers based on open interest levels—1, 2, and 3—with Level 3 representing the highest concentration of open positions. This tiered approach allows traders to gauge the significance of each level and adjust their strategies accordingly.
Histogram Visualization: A novel feature of this script is the histogram on the chart's right side, representing the concentration of liquidation levels in specific market zones. This visual aid helps traders identify crucial areas that warrant close attention, enhancing decision-making.
Customizable Options:
Moving Averages: Choose from a wide range of moving average types, including VWMA, SMA, EMA, and more, to tailor the indicator to your analysis style.
Histogram Settings: Adjust the number of histograms, lookback bars, and their proximity to the latest candle, allowing for a personalized density and range of visualization.
Liquidation Level Sensitivity: Set thresholds for different liquidation levels, fine-tuning the indicator to detect varying degrees of market leverage.
Color Coding: Customize the color scheme for different leverage levels, enhancing visual clarity and ease of interpretation.
The Liquidation Level Screener offers a unique edge by highlighting potential zones where significant market movements can occur due to liquidations. By consolidating data from multiple exchanges, it provides a more rounded view of market behavior, which is essential in today’s interconnected trading environment. The tiered liquidation system and histogram feature equip traders with the ability to identify and focus on key market segments where high activity is expected. This tool is particularly valuable for traders who base their strategies on market liquidity and leverage dynamics.
Daily Network Value to Transactions Signal (NVTS)
Quote of GlassNode ...
The NVT Signal (NVTS) is a modified version of the original NVT Ratio.
It uses a 90 day moving average of the daily transaction volume in the denominator instead of the raw daily transaction volume.
This moving average improves the ratio to better function as a leading indicator.
The Network Value to Transactions (NVT) Ratio is calculated by dividing the market cap by the transferred on-chain volume measured in USD.
GlassNode says the NVT Ratio was created by Willy Woo.
I have peaked into Glassnode and took their idea.
I also added a few more Moving Averages to select from, and the length can also be changed.
This script does not depend on Glassnode alone, instead I pulls data of several services...
CoinMarketCap
CoinMetrics
GlassNode
IntoTheBlock
Therefor we have more Tokens to select from.
I have also blocked some faulty data of each service.
If you get a study error of any kind then there is no data available,
or you on a wrong timeframe.
Best to use this script in a daily chart.
And keep in mind it pulls data of yesterday.
Therefor the plot is offset by 1 to the left.
The script will check each service if the data for the chart is available.
Market Cap is taken in the following order ...
CainMarketCap
GlassNode
CoinMetrics
Transaction volume as USD is taken in the following order ...
IntoTheBlock
CoinMetrics
GlassNode
Happy Trading!
