Nestor Jose Mendez Boza
Open MQL5 profileQuantitative Trading Systems Designer and Time Series Analysis Researcher
I am a multidisciplinary person who has dedicated the last seven years to the research and development of algorithmic trading systems. My work integrates advanced mathematics, data science, and an innovative vision of market analysis, with concrete achievements in international competitive environments.
Key Achievements:
International Competitions:
Robotrader 2023 (Interactive Brokers) with Python-based strategies.
Robotrader 2025 (Darwinex) using MQL5.
Development of Machine Learning models for structural break detection in time series during the ADAI Lab Challenge (Abu Dhabi, 2025).
Innovation in Market Analysis:
I have developed a pioneering approach that integrates mathematics, vibration theory, and sound patterns to analyze time series, transcending traditional technical methods. This unique perspective allows me to identify hidden structures and rhythms in financial data that conventional tools often miss.
Web: https://youtube.com/@fiboquantmx?si=h8ApV7axOvtMUfib
Technologies:
Python (Pandas, NumPy, Scikit-Learn)
MQL5 (custom indicators, Expert Advisors)
Machine Learning for time series forecasting
Signal processing and frequency analysis techniques
I am a multidisciplinary person who has dedicated the last seven years to the research and development of algorithmic trading systems. My work integrates advanced mathematics, data science, and an innovative vision of market analysis, with concrete achievements in international competitive environments.
Key Achievements:
International Competitions:
Robotrader 2023 (Interactive Brokers) with Python-based strategies.
Robotrader 2025 (Darwinex) using MQL5.
Development of Machine Learning models for structural break detection in time series during the ADAI Lab Challenge (Abu Dhabi, 2025).
Innovation in Market Analysis:
I have developed a pioneering approach that integrates mathematics, vibration theory, and sound patterns to analyze time series, transcending traditional technical methods. This unique perspective allows me to identify hidden structures and rhythms in financial data that conventional tools often miss.
Web: https://youtube.com/@fiboquantmx?si=h8ApV7axOvtMUfib
Technologies:
Python (Pandas, NumPy, Scikit-Learn)
MQL5 (custom indicators, Expert Advisors)
Machine Learning for time series forecasting
Signal processing and frequency analysis techniques
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