thehardwarestore.ai

where AI agents shop for the right tools

── 99235 repos indexed ── | filtered by tag: trading-algorithms
wilsonfreitas/awesome-quant ★ 30029 4106 APPLICATION

This repository is a curated list (awesome-list) of open-source quantitative finance libraries, packages, and resources. It provides a structured README.md organized by category, with inline language tags, and a pipeline that parses the list, enriches it with GitHub metadata (stars, last commit dates), and generates a static website deployed to GitHub Pages. The repo also includes automated tooling for pull-request review: a validation script that checks entry format, section placement, URL security, duplicate detection, and a full CI-driven PR review workflow. The core logic resides in parse.py (multi-threaded GitHub API enrichment), site/generate.py (static site generator), scripts/validate_readme.py (entry validation), and scripts/review_pr.py (automated PR review with offline URL reachability checks and cross-PR duplicate detection). The project is primarily a reference list, not an application or data pipeline, but it includes high-quality supporting tooling for maintainers and contributors.

RATING: 8.5/10 MAINT: active DRIFT: low
▸ 2 reusable components found
51bitquant/binance_grid_trader ★ 980 299 APPLICATION

Binance Grid Trader is a cryptocurrency trading bot that implements grid trading strategies for Binance Spot and Futures markets. The application features a modular architecture with separate layers for exchange gateways, event processing, strategy management, and user interface. It provides both a graphical interface built with PyQt5 and script-based execution modes for running trading strategies without UI. The system connects to Binance via REST and WebSocket APIs to receive market data and execute trades based on configurable grid strategies.

RATING: 8.4/10 MAINT: active DRIFT: medium
▸ 4 reusable components found
jesse-ai/jesse ★ 8651 1261 APPLICATION

Jesse is a mature, full-stack algorithmic trading framework designed for cryptocurrency backtesting, live/paper trading, hyperparameter optimization, Monte Carlo simulation, and rule significance testing. It combines a Python library with a FastAPI web server and a Nuxt.js dashboard, offering a comprehensive environment for developing and validating trading strategies. The repository also includes an MCP (Model Context Protocol) server for AI-assistant integration, over 180 technical indicators (many with Rust-accelerated backends), and a research API for programmatic strategy analysis. Architecture is modular with distinct layers: CLI entrypoint → web controllers / MCP tools → service layer → simulation engine (backtest/optimize/live) → exchange adapters. State management uses global singletons for in-memory simulation state, while persistent data is stored via Peewee ORM (PostgreSQL, optional TimescaleDB). The indicator library showcases a clean pattern with sequential/non-sequential modes and Rust fallback. However, the codebase shows signs of organic growth with some tightly coupled modules (global config, store singletons) and a large static frontend bundle that is opaque to analysis. Key strengths include the breadth of supported exchanges (10+), robust backtesting with realistic fee/margin/leverage modeling, and a well-designed MCP tool layer for AI-assisted development. Weaknesses include exchange driver duplication, a complex Rust subprocess for coordination, and dependency on many external APIs that require ongoing maintenance.

RATING: 8.1/10 MAINT: active DRIFT: medium
▸ 3 reusable components found
AlexWan/OsEngine ★ 1024 440 APPLICATION

OsEngine is a comprehensive, multi-exchange algorithmic trading platform for desktop (WPF/WinForms hybrid). It provides data downloading (OsData), backtesting (OsTester), walk-forward optimization (OsOptimizer), and live trading (OsTrader) with support for 30+ exchange connectors (MOEX, Binance, Bybit, OKX, Interactive Brokers, etc.). The platform includes a built-in technical indicator library (100+ indicators), a trading robot framework with attribute-based registration, and an MCP (Model Context Protocol) API for external AI/automation control. The architecture is modular: separate executables for different modes, a common server abstraction layer, and a consistent parameter system for bots and indicators. While the codebase is large and well-organized, it suffers from significant duplication across exchange connector entity classes and some copy-paste logic in trading robots. The UI mixes WPF and Windows Forms, and some patterns are legacy. Overall, it is a production-grade algorithmic trading platform with strong engineering practices and a rich feature set.

RATING: 7.9/10 MAINT: active DRIFT: medium
▸ 4 reusable components found
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