botvs/strategies
Strategies
This project is a cross-language quantitative trading framework designed to implement and execute trading strategies consistently across Python, JavaScript, C++, and PineScript. It functions as a polyglot trading strategy translator and a multi-language algorithmic trading engine that maps high-level scripting and block-based logic to executable binaries.
The system features a financial domain-specific language parser that translates specialized trading syntax and visual programming blocks into a standardized internal representation. It includes a technical analysis pattern library providing standardized quantitative calculations to ensure identical numerical results across different programming runtimes.
The framework covers the algorithmic trading workflow, including quantitative trading development and technical analysis automation. It enables the translation of trading logic between diverse programming languages and the generation of multi-target code from a single strategy definition.
Features
- Algorithmic Trading Engines - Provides a core platform for executing automated trading strategies by mapping high-level logic to compiled binaries.
- Quantitative Trading Platforms - Provides an integrated environment for developing, backtesting, and executing algorithmic financial trading strategies across languages.
- Technical Indicator Calculators - Provides a standardized library of quantitative calculations to ensure consistent technical indicator results across different runtimes.
- Technical Analysis - Provides tools for calculating technical indicators and automating the detection of chart patterns.
- Trading Logic Mappings - Converts block-based programming structures into executable trading scripts via a direct mapping layer.
- Block-to-Code Generators - Implements a system that translates graphical block structures into executable trading source code.
- Cross-Language Semantic Standards - Ensures consistent evaluation and identical numerical results for quantitative patterns across different runtimes.
- Domain Specific Language Parsers - Provides a parser that translates specialized financial scripting syntax into a structured tree for analysis.
- Intermediate Representation Translation - Converts diverse trading language syntaxes into a target-neutral intermediate format to decouple parsing from execution.
- Multi-Target Code Generation - Emits executable source code in multiple target languages from a single unified strategy definition.
- Polyglot Execution Environments - Creates a bridge between high-level scripting languages and compiled binaries to run trading logic in diverse environments.
- Trading Strategy Translators - Implements a polyglot translator that converts trading logic across Python, JavaScript, C++, and PineScript.
- Algorithmic Trading - Provides the infrastructure for automating financial market analysis and executing quantitative investment models.
- Cross-Language Implementations - Maintains strict logic and numerical parity for technical analysis calculations across multiple programming language ports.
- Trading Strategy Definitions - Provides a framework for codifying financial logic and signal generation that can be targeted to multiple languages.
- Trading Strategy Frameworks - Offers a specialized software framework for building and managing automated quantitative trading strategies.
- Strategy Reference Implementations - Adapts trading logic across different languages like Python, JavaScript, and C++ for diverse platforms.
- Trading Logic Interfaces - Implements node-based visual scripting and DSL translation for defining financial indicators and trading logic.
- Strategy Frameworks - Repository of algorithmic trading strategies.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
