🇺🇸 English | 🇪🇸 Español
This repository contains notes, examples, and code developed while studying EasyLanguage, the programming language used in trading platforms such as TradeStation and MultiCharts.
The content is organized into two structured learning paths:
- 01 – Fundamentals: Core language concepts and basic trading components
- 02 – Advanced: Strategy development, modular design, multi-data systems, and risk management
The objective is to document the learning process while progressively building reusable components for algorithmic trading systems.
ℹ️ All strategies and indicators are documented in both English and Spanish.
⚠️ The content in this repository represents design ideas and learning experiments — not validated trading strategies. No systematic backtesting or parameter optimization has been performed on any of the systems documented here. Backtesting, walk-forward analysis, and performance evaluation are handled in a separate repository.
easylanguage-learning/
│
├── 01-fundamentals/
│ ├── indicators/
│ ├── paintbars/
│ ├── showme/
│ └── strategies/
│
├── 02-advanced/
│ ├── functions/
│ ├── indicators/
│ ├── paintbars/
│ ├── showme/
│ ├── strategies/
│ └── multi-data-strategies/
│
└── README.md
This section covers the essential building blocks required to develop indicators and basic trading systems in EasyLanguage.
- EasyLanguage syntax and structure
- Variables, inputs, and data types
- Built-in functions and reserved words
- Indicators and oscillators
- ShowMe studies
- PaintBar studies
- Basic trading strategies
- Chart analysis tools
🎯 Goal: Understand how trading logic is expressed programmatically in EasyLanguage, and build a solid foundation for more complex system development.
This section focuses on systematic trading and professional strategy development, including multi-data architectures that incorporate intermarket relationships.
- Strategy design and architecture
- Modular and reusable code design
- Multi-data strategies with intermarket filters
- Advanced indicators and microstructure analysis
- Infrastructure components (risk management, position sizing, session control)
- Code abstraction and maintainability
🎯 Goal: Transition from simple scripts to robust, scalable, and maintainable trading systems that can serve as the foundation for a systematic trading portfolio.
Part of the code and documentation in this repository has been developed with the assistance of Claude (Anthropic). This includes strategy design discussions, code review and refactoring, documentation drafting, and conceptual explanations of trading and programming topics.
All AI-assisted content has been reviewed, tested where applicable, and validated by the repository author. The use of AI is itself part of the learning process documented here — exploring how AI tools can support the development of algorithmic trading knowledge and accelerate the transition from concept to code.
This repository is intended strictly for educational purposes.
- Code and examples can be freely used and adapted for personal learning.
- Some scripts represent experiments or work in progress as concepts are explored and refined. They should not be treated as finished or production-ready systems.
- Nothing in this repository constitutes financial advice or a recommendation to trade any specific instrument or strategy.
- The strategies and indicators documented here are design explorations. They have not been subjected to systematic backtesting, walk-forward validation, or optimization. Past design logic does not imply future trading performance.
This repository is intended for educational purposes. Code and examples can be freely used and adapted for personal learning.