Category Other  Published on 16/02/2024

ML k-NN J. Welles Wilder Indicator

An update for this algorithm is currently pending moderation. Please revisit this page shortly to access the algorithm's latest version.
Description

ML k-NN J. Welles Wilder Indicator

Elevate Your Trading to Mastery with Machine Learning Precision

Type: Windows & macOS (cTrader Platform)

Current version: 1.0.0 - NET 6

Updated: Friday, 16 February 2024

Author: Finwalt Trading

Price: ยฃ29.99 

 

๐Ÿ“ข Telegram for your convenience. ๐Ÿ“ข

๐Ÿขƒ Go to website product ๐Ÿขƒ

https://clickalgo.com/welles-wilder-ml

๐Ÿข Go to website product ๐Ÿข

 

Machine learning indicators are still in their infancy, they are not mature enough to be highly accurate in the financial markets.

cTrader Machine Learning Indicator

๐Ÿš€ Cutting-Edge Innovation:

Unlock unparalleled accuracy with our ML k-NN J. Welles Wilder Indicator, a masterpiece blending next-generation machine learning with the time-honored techniques of a trading legend. Make every trade count with insights that give you a definitive edge.

๐Ÿ”„ The Trading Revolution: Your Strategy Visualized

Embark on a journey that redefines trading:

  • Click to Start: Activate the pulse of machine learning.
  • Tailor-Made Experience: Personalize parameters to fit your trading style like a glove.
  • Data Intelligence: A meticulous compilation of historical data awaits to arm you with knowledge.
  • Proactive Analysis: Anticipate market movements with indicators that think ahead.
  • Precision-Driven Predictions: Let the k-NN model be your crystal ball in the market.
  • Signal Clarity: Filter through the marketโ€™s whispers for signals that speak volumes.

๐Ÿ› Own the Future of Trading:

Why follow when you can lead? The ML k-NN J. Welles Wilder Indicator isn't just another tool; it's a revolution at your fingertips. Define the rhythm of the markets and enjoy the symphony of success.

 

๐Ÿ”ง Customization Unleashed:

  • Personal Market Historian: Analyze past market data with adjustable depth.
  • Learning Curve Control: Balance your model's learning with real-time market agility.
  • Strategic Window Adjustment: Capture the market's beat with a customized time perspective.
  • Neighborly Advice: Calibrate the k-NN algorithm's sensitivity to fit your risk profile.

๐Ÿ” Precision-Tuned for the Connoisseur:

  • Distance Metrics Decoded: From Euclidean to Minkowski, tailor your analytical lens.
  • Signal Customization: Configure your alerts to match your market philosophy.

๐ŸŒŸ Exclusively for the Elite Trader:

This isn't just a tool; it's the key to unlock your potential. Be the maestro of your trading destiny, conducting your strategies with precision, adaptability, and finesse.

๐ŸŽ“ Empowerment Through Knowledge:

  • Expert Tutorials: Master every feature with our comprehensive guides.
  • 24/7 Support Helpline: Our experts are on standby to assist you around the clock.

๐Ÿ› ๏ธ Tailored to Your Trading Blueprint:

  • One-on-One Setup: Customize your indicator with our personal setup consultations.

๐Ÿ” A Transparent Craft:

  • Behind-the-Scenes Insights: Understand the intricate development process for full confidence in your tool.


 

 

๐Ÿ”„ Commitment to Excellence:

  • Continual Evolution: Regular updates ensure you're always ahead of the market curve.

๐ŸŽ Try the Excellence:

  • Risk-Free Exploration: Experience the full power with a free trial period. No strings attached.

 

๐ŸŒ Customize Your Trading with Unmatched Precision

Dive into the heart of algorithmic trading with our ML k-NN J. Welles Wilder Indicator, where you hold the power to fine-tune every detail. Hereโ€™s how you can tailor your trading experience to the sharpest edge:

๐Ÿ“Š Model Parameters: Craft Your Strategy

  • ๐Ÿ” Number of Previous Bars: Your market memory lane. You decide the breadth of market history to be analyzed, from 2,500 to 100,000 bars. This parameter is the cornerstone of your strategic foundation, offering the flexibility to expand or narrow your historical lens as you prefer.
  • ๐Ÿง  Training Ratio: The balance of wisdom. Define the proportion of historical data that trains the model's intellect, with a range from 0.01 to 0.99. A higher ratio equips the model with extensive past knowledge, while a lower ratio keeps it nimble and responsive to new trends.
  • ๐ŸชŸ Window Size: Your strategic viewport. Set the temporal scope for pattern recognition. This is where you can calibrate the model to be as myopic or far-sighted as your strategy demands.
  • ๐Ÿ‘ฅ Number of Neighbors (k): Your advisory council. Determine how many data points the k-NN algorithm should consult for each prediction. It's a delicate balance; more neighbors for consensus or fewer for swift decision-making.

๐Ÿ“ Distance Metric:

  • The fabric of your analytical universe. Choose the geometry of your trading universe with options like:
  • Euclidean Distance: Measures the straight-line distance between data points in a multidimensional space.
  • Manhattan Distance: Calculates the distance by summing the absolute differences between data point coordinates.
  • Chebyshev Distance: Finds the maximum difference between each coordinate of two data points.
  • Minkowski Distance: A generalization of both Euclidean and Manhattan distances, where you can define the power parameter for customization.
  • ๐Ÿ”ง Optimization of (k): The pursuit of peak performance. Engage this feature to let the algorithm self-tune its 'k' value, ensuring you're always operating at the zenith of accuracy.

๐Ÿšจ Signal Options: Define Your Alerts

  • ๐Ÿ“ˆ Strong Buy/Sell Signals: Stand out with signals that indicate significant market opportunities. These are your green and red flags waving confidently amidst market turbulence.
  • ๐Ÿ“‰ Weak Buy/Sell Signals: Stay ahead of the curve with early hints of potential market shifts. These signals are the subtle nudges for the cautious or the proactive trader.

๐Ÿ”ฌ Strategy-Specific Parameters: Sharpen Your Edge

  • ๐Ÿ“‰ MACD Zero Lag WWMA: Stay ahead of trend shifts with minimal delay. Capture the pulse of the market with an agility that traditional MACD lines envy.
  • ๐ŸŒŠ Normalized ATR Strategy: Master market volatility. Steer your strategy with an ATR that dynamically adjusts to the ebb and flow of market conditions.
  • ๐Ÿ” Period WWMA Zero Lag: Anticipate, don't just react. With moving averages that predict rather than follow, you're always one step ahead.

โš™๏ธ Refined Technical Inputs:

  • ๐Ÿ“ˆ RSI Period: Calibrate the sensitivity of the Relative Strength Index to match your risk appetite, from fast-paced trading to a more calculated approach.
  • ๐Ÿ” ADX Period: Set the window for assessing trend strength. Sharpen or smooth out the ADX to suit your strategic gaze.
  • ๐Ÿ”„ PSAR Step and Maximum Step: Fine-tune the Parabolic SAR to align with your trading tempo, from conservative to aggressive stepping.
  • ๐Ÿ“ WWMA Periods: Choose the periods for the Welles Wilder Moving Averages to resonate with your analytical rhythm, whether it's fast beats or slow symphonies.
  • ๐ŸŒช ATR and Moving Average Methods: Select the period and style for the Average True Range and its moving average computation, crafting an indicator that moves to your strategy's beat.


 

 

Understanding Symbol Support and Timeframes

In this section, we'll dive deeper into the symbol support and timeframes of the ML k-NN J. Welles Wilder Indicator. The following tables provide a comprehensive overview of the symbols supported and their corresponding timeframes. This information is crucial for traders looking to harness the power of this innovative tool effectively.

๐Ÿ“Š Table 1: Forex Symbols Supported (Time Frame: 1 Minute to 4 Hours)

  • ๐ŸŒ Explore a wide array of Forex symbols supported by the ML k-NN J. Welles Wilder Indicator.
  • ๐Ÿ•’ Supported timeframes for Forex trading range from 1 Minute to 4 Hours.
  • ๐Ÿ’ก Traders can analyze these symbols within these timeframes to make informed decisions.
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๐Ÿ“ˆ Table 2: Crypto Symbols Supported (Time Frame: 1 Minute to 1 Hour)

  • ๐Ÿš€ Dive into the world of cryptocurrencies with support for popular crypto symbols.
  • โฑ๏ธ Supported timeframes for crypto trading extend from 1 Minute to 1 Hour.

  • ๐ŸŒŸ Unlock opportunities for precise analysis in the dynamic crypto market.
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๐Ÿ’ฐ Table 3: Metal Symbols Supported (Time Frame: 1 Minute to 4 Hours)

  • ๐Ÿ”’ Delve into precious metals with support for various metal symbols.
  • ๐Ÿ“‰ Supported timeframes for metals analysis span from 1 Minute to 4 Hours.
  • ๐Ÿช™ Empower your trading strategy with insights into precious metals markets.
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Each of these tables illustrates the extensive coverage of symbols and timeframes, allowing traders to tailor their strategies to their preferences. Whether you're a Forex, cryptocurrency, or metal trader, this tool equips you with the data you need to make precise decisions. By understanding the symbols and timeframes supported by the ML k-NN J. Welles Wilder Indicator, you can effectively utilize this revolutionary tool to elevate your trading experience and achieve trading mastery.


 

 

Understanding the Strategy Implementation

In the Calculate function of the ML k-NN J. Welles Wilder Indicator, we'll delve into how the strategy is meticulously crafted using key indicators to generate precise trading signals:

  1. ๐Ÿ“Š MACD and MACD Signal Line
  • ๐Ÿ’น MACD (Moving Average Convergence Divergence): This powerful indicator reveals market momentum.
  • ๐Ÿ“ˆ Calculation: We compute the MACD line and signal line to pinpoint potential buy and sell signals.
  1. ๐Ÿ“ˆ Normalized Average True Range (NATR)
  • ๐Ÿ“‰ NATR: A volatility gauge aiding in setting optimal stop-loss and take-profit levels.
  1. ๐Ÿ“Š Zero Lag Welles Wilder Moving Average (WMA)
  • ๐Ÿ“‰ Zero Lag WMA: Identifying market trends with precision.
  • ๐Ÿ”„ Procedure: We calculate the value and ensure its validity before chart presentation.
  1. ๐Ÿ“ˆ Threshold Lines
  • ๐Ÿšฆ Thresholds for ATR (Average True Range): Essential for defining risk levels effectively.
  1. ๐Ÿ“Š Feature Extraction
  • ๐Ÿ“ˆ We extract a plethora of market features, including RSI, ATR, ADX, ADXR, DI Minus, DI Plus, Parabolic SAR, WMA50, WMA100, WMA200, MACD Histogram, and CMF.
  • ๐Ÿ” These features serve as critical inputs for our cutting-edge machine learning model.
  1. ๐Ÿ“ˆ Trading Signals
  • ๐Ÿš€ The ML k-NN model leverages the extracted features to generate trading signals.
  • ๐Ÿšฅ These signals are thoughtfully categorized into Strong Buy, Strong Sell, Weak Buy, and Weak Sell, each represented by distinctive chart arrows.
Advanced Knn Indicator Process - Enhanced Version


By combining advanced technical indicators and state-of-the-art machine learning techniques, the ML k-NN J. Welles Wilder Indicator is engineered to empower traders with actionable signals rooted in real-time market conditions and historical data.

 

๐Ÿ“ข Telegram for your convenience. ๐Ÿ“ข

๐Ÿขƒ Go to website product ๐Ÿขƒ

https://clickalgo.com/k-means

๐Ÿข Go to website product ๐Ÿข

 

Introduction to Trading Strategy and Indicator Update

 


 

Strategic Considerations for Trading Profitability

Volatility and Market Movement: Recognizing the critical role of high volatility is essential for successful trading. It acts as the primary driver for substantial price movements.

Long-term Trend Analysis: Utilizing tools like the Extended Period Moving Average offers insights into market trends, while the MACD (Moving Average Convergence Divergence) enhances trade initiation by aligning trend, momentum, volatility, and the predictive insights from machine learning models.

Key Trading Concepts

Risk/Reward Ratios and Accuracy: An essential aspect of trading strategy is understanding the balance between risk and potential reward. This balance is quantifiable through risk/reward ratios, which should ideally align with the accuracy of the underlying model. Strategies with high hit rates might have less favorable risk/reward ratios, whereas strategies with lower hit rates can afford more advantageous ratios, given the model's accuracy.

  • Recommended Risk/Reward Ratios Based on Model Accuracy:
  • For models with an accuracy of 50%-60%, a risk/reward ratio of at least 1:2 is advisable to compensate for the lower hit rate.
  • With accuracy levels between 60%-70%, a more balanced ratio, such as 1:1.5, can be efficient.
  • Models achieving over 70% accuracy can operate effectively with a risk/reward ratio closer to 1:1, reflecting higher confidence in the trading outcomes.

Enhancing Accuracy through Indicator Confluence: Waiting for the convergence of indicators can significantly improve the underlying model's accuracy. This strategic patience allows for more precise entry points, optimizing the risk/reward ratio by leveraging the collective predictive power of multiple indicators.

Transaction Costs: Consider the impact of commissions and spreads on the required hit rate for profitability.

Capital Management: Practicing effective risk management, such as limiting exposure per trade, is critical for long-term profitability.

Technical Indicator Update

  • Latest Developments: We've updated our indicator to Telegram NET 6.0, improving its functionality and ensuring compatibility across platforms. Preliminary tests on Windows indicate stability, with ongoing verification on Mac to ensure optimal performance.

Model Testing and Optimization

Accuracy Focus: It is crucial to focus exclusively on model accuracy during the testing phase. I chose to allocate 98% of the data to training and only 2% to testing because machine learning models tend to lose accuracy quickly with new data, beyond what is observed in the test or validation sets. For this reason, it is advisable to restart the indicator periodically to update the model, thus mitigating the risk of over-fitting to historical data, decreasing temporal autocorrelation in financial markets and inherent volatility.

Indicator Period Adjustments: Modifying the indicator periods can boost the model's hit rate. Your feedback on further improvements is highly appreciated.

Seeking Optimal Test Accuracy

Balanced Accuracy in Testing and Training: Achieving high accuracy in both phases is key. Fine-tuning the k parameter of the kNN model can improve test performance due to the varying data volume between training and test sets.

Optimal Data Volume for Testing: I recommend a test data volume of 50 to 200 points for robust accuracy metrics, ensuring the model's predictive accuracy on new data is not compromised.

 


The author decided to hide the source code.
FI
finwalt.trading

Joined on 21.01.2024

  • Distribution: Paid
  • Language: C#
  • Trading platform: cTrader Automate
  • File name: ML k-NN J. Welles Wilder Indicator To Link.algo
  • Rating: 0
  • Installs: 0
  • Modified: 16/02/2024 17:14
Comments
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FI
finwalt.trading · 9 months ago

 

Note the brief comment "Input for the model".

However, now notice that the parameters included in the graph to perform the strategy along with the kNN model include the term "Strategy".

 

Your comment is useful to me because there may be clients who prefer to visualize other indicators in the strategy that complements the kNN model, your comment will be considered for future versions.

FI
finwalt.trading · 9 months ago

Hi Jim,

Indeed, this indicator includes a Parabolic SAR that is used as data to feed the kNN model. It is configurable in its parameters to also feed the kNN model with those parameters. All parameters that have the comment "Input" in their description are used to provide data to the model and train it. The parameters labeled "Strategy" are the ones you will see on the screen. Strategy refers to the confluence of indicator signals, such as the WWMA to visualize the trend, along with the MACD and the kNN model rating, that make up the strategy. However, the other indicators are solely intended to feed the model. If you prefer, in the future I can make the indicator display in the strategy the option to choose which indicator you can use to combine the strategy.

JI
jim.tollan · 9 months ago

I've said it before on this work, but this has great potential. 

Quick question tho, I notice above that you mention using Psar/WWMA etc. However, on downloading this from ClickAlgo, I couldn't see any parameters for those. Is this due in a future release??

Anyway - loving the progression here, feel it could be quite special once fully formed and as i mentioned before, would love to see a cBot using a similar ML approach as that would be really cutting edge.

thanks again