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Being towards death

Heed not to the tree-rustling and leaf-lashing rain, Why not stroll along, whistle and sing under its rein. Lighter and better suited than horses are straw sandals and a bamboo staff, Who's afraid? A palm-leaf plaited cape provides enough to misty weather in life sustain. A thorny spring breeze sobers up the spirit, I feel a slight chill, The setting sun over the mountain offers greetings still. Looking back over the bleak passage survived, The return in time Shall not be affected by windswept rain or shine.
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Quantitative Trading Beginner's Guide: Achieving Profit with Python Open Source Tools

#工具150
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VeighNa is an open-source quantitative trading system framework developed in Python, designed to provide a multifunctional trading platform for professional traders. It supports various applications such as quantitative trading, algorithmic trading, multi-account management, and data services. Key features include: - **Trading Interfaces**: Supports both domestic and international exchanges. - **Strategy Applications**: Offers multiple quantitative trading strategies and API integration. - **Event-Driven Engine**: Provides a simple API for event-driven trading. - **Database Adapters**: Compatible with both SQL and NoSQL databases. - **Data Services**: Connects to various data services for market data support. - **Cross-Process Communication**: Facilitates complex distributed trading systems. - **High-Performance Charts**: Supports large data volume chart displays and real-time updates. The technology stack includes Python as the programming language, the VeighNa framework, and compatibility with Windows and Ubuntu operating systems, requiring Python 3.10 or higher.

Project Introduction#

https://github.com/vnpy/vnpy#

VeighNa is an open-source quantitative trading system development framework based on Python, designed to provide a multifunctional quantitative trading platform for professional traders. Since its release, it has attracted numerous users from financial institutions and related fields, including private equity funds, securities companies, futures companies, and more.

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Application Scenarios#

  • Quantitative Trading: Provides traders with a one-stop solution from strategy development, backtesting to live trading.
  • Algorithmic Trading: Supports advanced trading features such as algorithmic order splitting and intelligent position shifting.
  • Multi-Account Management: Supports multi-account trading, facilitating asset management for traders.
  • Data Services: Connects various data services to provide comprehensive market data support for traders.

Functional Modules#

  • Trading Interface (gateway)

    • Domestic Market: Supports trading interfaces for major domestic exchanges.
    • Overseas Market: Supports trading interfaces for overseas exchanges.
    • Special Applications: Provides trading interfaces for special applications.

  • Strategy Applications (app)

    • Quantitative Strategies: Offers trading applications for various quantitative strategies.
    • API Interface Encapsulation: Provides underlying integration for Python trading API interfaces.

  • Event-Driven Engine (event)

    • As the core of event-driven trading programs, it provides a simple and easy-to-use API.

  • Database Adapter Interface (database)

    • SQL Type: Supports SQL-type databases.
    • NoSQL Type: Supports NoSQL-type databases.

  • Data Service Adapter Interface (datafeed)

    • Connects various data services to provide market data support for traders.

  • Cross-Process Communication Standard Component (rpc)

    • Used to implement complex trading systems for distributed deployment.

  • High-Performance Python Candlestick Charts (chart)

    • Supports large data volume chart display and real-time data update functionality.

Functional Features#

  • Multifunctional Quantitative Trading Platform: Integrates various trading interfaces to provide comprehensive quantitative trading support for traders.
  • Simple and Easy-to-Use API: Offers a simple and easy-to-use API, facilitating strategy development and backtesting for traders.
  • Wide Coverage of Trading Varieties: Supports various trading varieties in domestic and international markets.
  • Advanced Trading Features: Supports advanced trading features such as algorithmic order splitting and intelligent position shifting.
  • Multi-Account Trading Support: Supports multi-account trading, facilitating asset management for traders.

Project Technology Stack#

  • Programming Language: Python.
  • Development Framework: VeighNa (open-source quantitative trading system development framework based on Python).
  • Dependency Libraries: See setup.cfg and requirements.txt.
  • Operating Systems: Supports Windows 11 and above, Windows Server 2019 and above, Ubuntu 22.04 LTS and above.
  • Python Version: Python 3.10 and above (64-bit), Python 3.10 is recommended.
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