Adaptive Linear Moving Average (9, 0.85, 6)
A technical indicator that combines the features of SMA and EMA. Uses a sigma parameter to adjust the responsiveness and an offset to shift the average, providing a customizable balance between lag a
Introduction
A technical indicator that combines the features of SMA and EMA. Uses a sigma parameter to adjust the responsiveness and an offset to shift the average, providing a customizable balance between lag and smoothness.
How Adaptive Linear Moving Average (9, 0.85, 6) Works
The Adaptive Linear Moving Average (ALMA) was developed by Arnaud Legoux and Dimitrios Kouzis-Loukas. It uses three parameters: Period (9), Sigma (0.85), and Offset (6). The Sigma parameter controls the smoothness (lower values = more responsive), while Offset shifts the average (0 = EMA-like, 1 = SMA-like).
In crypto strategy building, ALMA is used for:
• Customizable responsiveness - Adjust Sigma for different market conditions • Trend following - Excellent for identifying trend direction with minimal lag • Support/Resistance - Provides adaptive dynamic levels • Crossover strategies - Can be used with different parameter sets
ALMA is particularly effective in trending markets. The adaptability makes it suitable for various timeframes and market conditions.
Key Characteristics
Category: Moving Averages
Type: Technical Indicator
Application: Trend Following And Dynamic Support/Resistance
Timeframe: All timeframes supported (1m to 1M)
Using Adaptive Linear Moving Average (9, 0.85, 6) in Skyrexio Strategy Builder
Base Order Entry Conditions
Example Configuration:
First Condition: Close Price
Timeframe: 1H
Operator: Cross Above
Second Condition: Adaptive Linear Moving Average (9, 0.85, 6)This creates a signal based on the Adaptive Linear Moving Average (9, 0.85, 6) meeting the specified criteria.
Practical Applications
Entry Signal
Adaptive Linear Moving Average (9, 0.85, 6) meets threshold
Trending markets
Confirmation
Combine with volume
All conditions
Exit Signal
Adaptive Linear Moving Average (9, 0.85, 6) reversal
Profit taking
Risk Management
Adaptive Linear Moving Average (9, 0.85, 6) extreme values
Risk assessment
Advanced Applications
Multi-Timeframe Analysis
Combine different timeframes for robust signals:
Rule 1: Adaptive Linear Moving Average (9, 0.85, 6) (4H) meets condition
AND
Rule 2: Adaptive Linear Moving Average (9, 0.85, 6) (1H) confirms signalIndicator Combinations
Effective Combinations:
Adaptive Linear Moving Average (9, 0.85, 6) + Volume indicators (confirmation)
Adaptive Linear Moving Average (9, 0.85, 6) + Moving averages (trend context)
Adaptive Linear Moving Average (9, 0.85, 6) + Other momentum indicators (signal validation)
Take Profit and Stop Loss Applications
Take Profit Strategies
Multiple Rules Example:
Rule 1: Exit condition - Price reaches ALMA adaptive resistance
First Condition: Close Price
Timeframe: 1H
Operator: Greater Than
Second Condition: Adaptive Linear Moving Average (9, 0.85, 6)
Value: 1.055
OR
Rule 2: Exit condition - Ultimate Oscillator overbought
First Condition: Ultimate Oscillator
Timeframe: 1H
Operator: Greater Than
Second Condition: Value
Value: 78
OR
Rule 3: Exit condition - Volume pattern exhaustion
First Condition: Volume
Timeframe: 1H
Operator: Less Than
Second Condition: Simple Moving Average (20)
Value: 0.65Stop Loss Applications
Multiple Rules Example:
Rule 1: Stop loss - Price breaks ALMA adaptive support
First Condition: Close Price
Timeframe: 1H
Operator: Less Than
Second Condition: Adaptive Linear Moving Average (9, 0.85, 6)
Value: 0.985
OR
Rule 2: Stop loss - CCI oversold protection
First Condition: CCI
Timeframe: 1H
Operator: Less Than
Second Condition: Value
Value: -175
OR
Rule 3: Stop loss - True Strength Index breakdown
First Condition: True Strength Index
Timeframe: 1H
Operator: Cross Below
Second Condition: Value
Value: -30Adaptive Linear Moving Average (9, 0.85, 6) Strategy Bot
Configuration:
Base Order: Adaptive Linear Moving Average (9, 0.85, 6) condition as defined above
Additional Entries: Price Change mode, 2% intervals
Take Profit: 5% and 10% levels
Stop Loss: Indicator reversal OR 3% loss
Risk Management
Position Sizing
Use Adaptive Linear Moving Average (9, 0.85, 6) to assess market conditions:
Strong Signals: Full position size
Weak Signals: Reduced position size
Conflicting Signals: Avoid trading
Market Adaptation
Adjust Adaptive Linear Moving Average (9, 0.85, 6) parameters based on:
Current market volatility
Timeframe being traded
Historical performance
Skyrexio-Specific Features
AI Integration
The "Suggest with AI" button provides recommendations for:
Optimal Adaptive Linear Moving Average (9, 0.85, 6) parameters for current conditions
Best timeframes for Adaptive Linear Moving Average (9, 0.85, 6) analysis
Complementary indicators to use with Adaptive Linear Moving Average (9, 0.85, 6)
Real-Time Execution
Continuous Monitoring: 24/7 tracking across all timeframes
Instant Signals: Immediate order execution when conditions are met
Multi-Exchange: Consistent calculation across all supported exchanges
Best Practices
Entry Timing
Once per bar close: Recommended trigger type for Adaptive Linear Moving Average (9, 0.85, 6)
Confirmation: Always combine with other technical factors
Volume: Validate signals with volume analysis
Common Mistakes to Avoid
Over-optimization: Don't curve-fit parameters to historical data
Isolation: Never use Adaptive Linear Moving Average (9, 0.85, 6) as the only decision factor
Ignoring Context: Consider broader market conditions
Performance Optimization
Backtesting Guidelines
Test Adaptive Linear Moving Average (9, 0.85, 6) across different market conditions
Validate on multiple cryptocurrency pairs
Account for transaction costs and slippage
Use realistic execution assumptions
Market Conditions
Trending
High
Follow signals with trend
Ranging
Medium
Use mean reversion approach
Volatile
Variable
Reduce position sizes
Low Volume
Low
Wait for volume confirmation
Technical Considerations
Calculation Method
Adaptive Linear Moving Average (9, 0.85, 6) is calculated using:
Standard mathematical formulas
Consistent methodology across timeframes
Real-time updates with each new price tick
Parameter Optimization
Consider adjusting parameters for:
Different cryptocurrency pairs
Varying market conditions
Your risk tolerance and trading style
Conclusion
The Adaptive Linear Moving Average (9, 0.85, 6) is a valuable tool in the Skyrexio Strategy Builder arsenal for trend following and dynamic support/resistance. When used correctly with proper risk management and confirmation signals, it can significantly enhance trading performance. However, like all technical indicators, Adaptive Linear Moving Average (9, 0.85, 6) should be part of a comprehensive trading strategy that includes multiple confirmation factors.
The key to success with Adaptive Linear Moving Average (9, 0.85, 6) is understanding its strengths and limitations, combining it with other analysis techniques, and maintaining disciplined risk management. Skyrexio's AI-powered suggestions can help optimize Adaptive Linear Moving Average (9, 0.85, 6) parameters for current market conditions and your specific trading objectives.
Remember that no single indicator guarantees profitable trades. The most successful strategies combine multiple indicators, proper risk management, and sound trading psychology. Use Adaptive Linear Moving Average (9, 0.85, 6) as part of a well-rounded approach to cryptocurrency trading.
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