AI Summary

Overview

TSP: The Self-Hosted, Zero-Maintenance A-Share Quant Trading Workbench

Empower your quantitative trading strategies with TSP, a comprehensive, self-hosted platform designed for A-share markets. TSP seamlessly integrates stock selection, real-time monitoring, and backtesting, all managed with minimal operational overhead. Leverage the power of LLM-driven strategy customization, in-depth stock analysis, and intelligent market review. Its pluggable architecture allows for flexible integration of third-party data sources and personalized data extensions, making it an ideal personal open-source solution for quantitative traders.

Key Features

  • LLM-Powered Strategy Customization: Harness the capabilities of Large Language Models to define, analyze, and generate trading strategies tailored to your needs.
  • Integrated Workflow: Experience a unified platform for stock selection, real-time monitoring, and backtesting, ensuring data consistency and workflow efficiency across all stages.
  • Zero-Maintenance, Self-Hosted Deployment: Deploy TSP easily via Docker for a completely self-hosted experience, eliminating the need for ongoing maintenance and operational effort.
  • Pluggable Data Architecture: Effortlessly connect and integrate diverse third-party data sources. Extend its capabilities with custom data extensions for a truly personalized trading environment.
  • Real-Time Monitoring & Alerts: Stay ahead of market movements with full-time anomaly detection, including pre-market, intra-day, and deviation alerts, with customizable push notifications (including voice and Feishu).
  • Intelligent AI Assistant: Query your entire dataset conversationally. The AI assistant provides detailed, verifiable data retrieval, market analysis, and strategy insights directly within the platform.
  • High-Performance Engine: Built on the blazing-fast Polars data manipulation library, TSP delivers millisecond-level strategy execution and comprehensive data processing.
  • Deep Market Analysis: Gain insights from a 6-stage market sentiment cycle, concept and sector rotation analysis, and detailed stock-specific analysis combining technical, fundamental, and AI-driven perspectives.
  • Advanced Backtesting & Factor Research: Conduct robust factor and strategy backtesting (including minute-level data), explore factor mining, and perform sensitivity analysis.

Typical Use Cases

  • Quantitative Strategy Development: Design, test, and refine your proprietary trading strategies using a powerful, integrated toolkit driven by LLM capabilities.
  • Real-Time Market Surveillance: Set up custom alerts for specific stock movements, price anomalies, or strategy triggers to never miss critical market events.
  • Personalized Data Integration: Incorporate niche or proprietary data sources into your analysis pipeline without extensive coding, thanks to the pluggable data architecture.
  • Intelligent Market Review: Automate daily market recaps and gain AI-driven insights into market trends, sector rotations, and individual stock performance.
  • Low-Overhead Trading Operations: Deploy and manage a sophisticated quantitative trading platform without the burden of server maintenance or complex infrastructure management.
  • Educational and Research Tool: Explore quantitative finance concepts and build custom trading tools for learning and research purposes in a flexible, open-source environment.

Repository Trajectory

Trended #12 on daily

September 26, 2026

First tracked on GitTrend

September 26, 2026

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Contributors

Languages

Python

61%

TypeScript

38%

About

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源

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Topics

fastapi

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quant

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quantitative-finance

aigc

quantitative-trading

daily

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self-hosted

duckdb

stock

polars

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ai-agent

tdx

Contributors

Languages

Python

61%

TypeScript

38%