Machine Learning Adaptive Trend Toolkit [Velowave]

7 Apr

The Machine Learning Adaptive Trend Toolkit is a technical analysis tool that combines adaptive algorithms with comprehensive market feature extraction to provide insights into changing market conditions. Unlike static indicators with fixed parameters, this system continuously analyzes and adapts to the evolving market environment.

Core Technology
At the heart of this system is a dynamic approach to market analysis:
• Feature Engineering Pipeline: Extracts and normalizes volatility, momentum, volume, and trend strength metrics
• Market Regime Classification: Identifies 10 distinct market environments including trending, ranging, breakout, and reversal conditions
• Parameter Optimization: Automatically adjusts sensitivity based on detected market conditions
• Dynamic Wave Technology: Creates adaptive support/resistance levels that respond to changing volatility

⚠️ Signal Interpretation
Important: The indicator's wave crosses should be interpreted as trend change signals rather than direct buy/sell recommendations. These signals represent potential trend changes based on adaptive parameters, but require confirmation from other analysis before making trading decisions.


(Image showing example color customizability)

Custom Candle Behavior
The custom candlesticks in this indicator are designed to enhance trend visualization but will behave differently than default candlesticks:
• They use linear regression smoothing to reduce noise
• Their coloring is based on position relative to the adaptive wave, not merely open/close relationships
• They may show different patterns than traditional candlesticks on the same chart
• Trading strategies developed using traditional candlestick patterns may not apply directly to these custom candles
This modified representation helps visualize trend conditions more clearly but should be understood as an analytical tool rather than a direct replacement for traditional price action analysis.

Practical Applications
• Trend Identification
The adaptive wave system provides clear visualization of trend direction and strength, with dynamic support and resistance levels that adjust to current volatility conditions.
• Volatility-Adjusted Analysis
Parameters automatically optimize during high and low volatility periods, preventing false signals during consolidation while remaining responsive during breakouts.
• Regime-Based Strategy Selection
Knowing the current market regime allows you to apply appropriate trading techniques for specific conditions rather than using a one-size-fits-all approach.
• Visual Price Action Analysis
Enhanced candlestick coloring instantly communicates price position relative to the adaptive trend, helping you process market information more efficiently.


(Image showing only the supertrend wave and dynamic moving average)

Technical Components
• Adaptive Wave Algorithm: Creates dynamic support/resistance bands based on volatility, volume, and detected regime
• Dynamic Moving Average: Period automatically adjusts based on market conditions - shorter in trending markets, longer in ranging conditions
• Market Regime Engine: Continuously analyzes feature patterns to classify current conditions
• Custom Candlestick Visualization: Provides instant visual feedback on trend position and momentum

Implementation Details
For full transparency, the core calculations include:
• Volatility normalization through comparative ATR analysis
• Momentum feature extraction using multi-timeframe momentum indicators
• Trend strength quantification through price structure analysis
• Regime detection through feature pattern recognition
• Adaptive parameter adjustment based on detected market conditions

The system uses only historical and current price data for its calculations and analyses. It does not use predictive methodologies that could lead to misleading results. The indicator will show different values on an open bar than it will after the bar closes, which is standard behavior for indicators that use closing prices in their calculations.

Risk Disclaimer:
Trading involves significant risk. This indicator is designed as an analytical tool to enhance decision-making, not as a standalone trading system. Past performance is not indicative of future results.

25 Nov

Catatan Rilis

Update 1:
This release updated the code to Pinescript v6, improved machine learning logic, and added additional features to fine-tune the indicator however you need to. The core engine was re-built using Pine Script™ v6, moving away from static logic to a dynamic, matrix-based clustering system.
The new version provides a more "organic" adaptation to market structure. By mapping market conditions into a 4-dimensional mathematical space, the indicator can now recognize nuance in price action—distinguishing between a "healthy pullback" and a "trend reversal" with far greater accuracy.
Major System Upgrades:
-Matrix-Based Regime Detection: Previous versions used rigid rules to guess the market state. This version utilizes a true K-Means Clustering algorithm powered by Pine v6 matrices. It continuously calculates the Euclidean distance between current price action and 10 distinct market archetypes. This results in smoother transitions and smarter sensitivity adjustments.
-Asymmetric Wave Adaptation: Markets rarely move identically in both directions. The new Asymmetric Adaptation logic allows the trend bands to "breathe" differently based on the higher timeframe bias. In a strong uptrend, the system can lower the floor (support) to prevent wicks from stopping you out, while keeping the ceiling (resistance) tight to capture valid breakouts.
-Volume-Filtered Hull MA: We introduced a noise-reduction filter to the Moving Average baseline. The "Volume Threshold" feature allows the MA to ignore price updates that occur on low relative volume. This means the trend line tracks significant institutional money flow rather than retail noise.
-Advanced Signal Filtering: Two new filter modes allow you to align signals with your specific strategy. "HTF Trend Bias" uses slope and correlation from a higher timeframe (best for Swing Trading), while "Dynamic MA Slope" uses the angle of the current Hull MA (best for Scalping).

(Image showing an example of signal filtering, showing "Longs Only" or "Shorts Only")
Visual History & Data Panel: A new on-chart dashboard displays the current Trend State, Bias Strength, and Bias Direction. Additionally, you can enable "Historical Zones" to see vertical markers on the chart whenever the trend filter flipped state.

Tips for Optimization
1. Tuning for Your Timeframe
While the default settings are robust, different assets require different "Lookback" periods.
For Crypto/Volatile Assets: Consider enabling the "Volatility Focused" Weight Preset. This forces the ML to prioritize volatility compression and expansion.
For Forex/Indices: The "Trend Focused" preset often works better, as these markets tend to respect structural levels more than explosive volatility.
2. Using the Filters Effectively
The "Filter Signals by Trend" option is a powerful tool to reduce overtrading.
-Aggressive Mode: Set the "HTF Signal Threshold" to 0.0. This ensures you only trade in the direction of the bias, but doesn't require the bias to be strong.
-Conservative Mode: Raise the threshold to 0.2 or higher. This effectively creates a "No Trade Zone" during weak or sideways markets, keeping you out of chop until a clear trend emerges.

3. Turning Candles into a Trend Cloud
You can repurpose the "Custom Candles" feature to act as a smoothed trend visualizer rather than price bars.
LinReg Period: Set the "LinReg Period" in Custom Candle Settings to a very high value (e.g., 50 or 100).
Result: The candles will smooth out significantly, or a broad Moving Average ribbon. This is excellent for visualizing the macro trend direction without getting distracted by individual candle noise. See the image below for an example.


(Image showing an example of using the indicator as a trend cloud)

3. Mastering the "Volume Weight"
In the "Wave Settings", the Volume Weight controls how much the bands expand during high volume. If you find signals are too late during news spikes, increase the Volume Weight. This causes bands to widen faster when volume spikes, potentially keeping you in a trade during a "stop hunt."

Usage Examples
Scenario A: The Fakeout
Market Condition: Price spikes up rapidly but on low volume.
V6 Reaction: The Volume-Filtered MA ignores the price spike because relative volume is low. The trend baseline stays flat. The Matrix Engine identifies "Low Volatility/Ranging" despite the price jump, keeping the bands wide.
Result: The indicator avoids flipping bullish, saving you from buying the top of a fakeout.
Scenario B: The Strong Trend Pullback
Market Condition: Price is in a strong uptrend but drops sharply for 3 candles.
V6 Reaction: The Asymmetric Adaptation sees the bullish HTF Bias. It keeps the lower band (support) wide to accommodate the pullback.
Result: The price wicks down but doesn't close below the adaptive support. The trend remains green, allowing you to ride the move up when it resumes.

Disclaimer:
Trading involves significant risk. The Machine Learning Adaptive Trend Toolkit is an analytical tool designed to assist in decision-making, not make predictions. Always manage your risk and only use this indicator as part of a comprehensive trading system.