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License Repo Size Last Commit Python MQL5 Pine Script Jupyter Notebook
Retard Retail | Wanna be Quant | Independent Low-tier Researcher | Algorithmic Trader
Wildmind Quasars LLC Β© 2026

image 550619554_1506792687170986_7254869329101140500_n

Project Context

I value Psychology but put zero discretion when using automated Algorithmic Trading with philosophical trust. I hold no advantage over financial markets; I only risk what I can afford to lose. I acknowledge my blind spots and earnestly fill what I am lacking.

Manual & Semi-Algorithmic Trading

Manual Methodologies:        390 pages 

Research Paper

Algorithmic Trading Projects Count (not number of files)

  Pinescript language:          39
  MQL5 language:               9
  Python language:            31

  Simple Research papers:      8  ~  (22, 12, 22, 9, 6, 8, 28, 25 pages)

Sample simple research paper

recent update: Feb 25, 2026

Programable Forte

Pine Script Python Jupyter Notebook C++ MetaTrader 5 MQL5 Roblox Lua Overleaf LaTeX Exness GoCharting StrategyQuantAnalyzer Java Dukascopy Binance ftmo fundednext

Analysis 1 Analysis 2

System Overview

graph TD
    A[Market Data] --> B{Analysis & Strategy}
    B --> C[Pine Script - Signal Engineering/Viz]
    B --> D[MQL5 - Execution/Expert Advisors]
    B --> E[Python - Data Science/Modeling]
    C --> F[Trading Terminal]
    D --> F
    E --> G[Research Papers & Validation]
    G --> B

Project Structure

QRAT2025/
β”œβ”€β”€ MQL5 Folder/                # MT5 Expert Advisors and indicators
β”œβ”€β”€ Pinescript Folder/           # TradingView Signal Engineering
β”œβ”€β”€ Python Folder/               # Data Science, Analytics, and Modeling
β”œβ”€β”€ Research Papers/             # Strategy Validation & Papers
β”œβ”€β”€ Documents/                   # Reports and Attachments
β”œβ”€β”€ Concepts and Topics Folder/  # Educational Notebooks
└── LICENSE                      # Project License

Efficient Usage

To utilize this repository effectively, follow the standardized trading workflow:

  1. Explore Research Papers/ to understand strategy hypotheses and backtesting results.
  2. Review Python Folder/ for data preprocessing, signal analysis notebooks, and statistical modeling.
  3. Deploy technical indicators via Pinescript Folder/ for live market visualization on TradingView.
  4. Implement automated execution using Expert Advisors located in MQL5 Folder/ on MT5.

Citation

@misc{QRAT2025,
  author    = {Albeos, Rembrant Oyangoren},
  title     = {{QRAT2025}},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/algorembrant/QRAT2025},
  note      = {Hugging Face repository}
}
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