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Aviad Ben Harush
As the developer&Founder of Capital Steps , my philosophy has always been rooted in robustness and stress-testing against real-world conditions. However, the markets are constantly evolving, and so must our tools.
I am currently undergoing an intensive academic deep-dive into Data Science and Machine Learning to bring the next generation of logic to my algorithms. I believe that true edge comes from understanding the math from scratch, not just using ready-made libraries.
As part of this research, I have released an implementation of the k-Nearest Neighbors (kNN) algorithm, built entirely from scratch in Python without relying on "black box" libraries. This exercise is part of my broader effort to test how classification algorithms can be used to improve market regime filtering for XAUUSD.
You can review the code and my research progress here: https://github.com/Aviad25/kNN-implementation-from-scratch
What does this mean for Capital Steps? My goal is to implement these adaptive learning capabilities into future updates of Capital Steps, allowing the EA to better distinguish between noise and valid structural alignment in real-time .
Stay tuned for further updates.
I am currently undergoing an intensive academic deep-dive into Data Science and Machine Learning to bring the next generation of logic to my algorithms. I believe that true edge comes from understanding the math from scratch, not just using ready-made libraries.
As part of this research, I have released an implementation of the k-Nearest Neighbors (kNN) algorithm, built entirely from scratch in Python without relying on "black box" libraries. This exercise is part of my broader effort to test how classification algorithms can be used to improve market regime filtering for XAUUSD.
You can review the code and my research progress here: https://github.com/Aviad25/kNN-implementation-from-scratch
What does this mean for Capital Steps? My goal is to implement these adaptive learning capabilities into future updates of Capital Steps, allowing the EA to better distinguish between noise and valid structural alignment in real-time .
Stay tuned for further updates.
Aviad Ben Harush
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Capital Steps Algorithmus - Expert Advisor (EA) Entwickelt für reale Marktbedingungen Viele Expert Advisors zeigen in kontrollierten Backtesting-Umgebungen gute Ergebnisse, scheitern jedoch unter realen Handelsbedingungen aufgrund der Ausführungslatenz, Marktmikrostruktureffekten oder broker-seitigen Beschränkungen. Der Capital Steps Algorithmus wurde speziell entwickelt, um diese Einschränkungen zu überwinden. 🛡️ Robustheit und Strategiephilosophie Das System wurde unter simulierten realen