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功夫量化

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Kungfu Quant integrates market data, AI factor research, backtesting, and trading workflows into a single product ecosystem, offering guided computation and a Python API. It enables factor screening and analysis based on Level 2 data and seamlessly connects to downstream strategy validation processes.

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What is 功夫量化?

Kungfu Trading’s current official website introduces its quantitative research capabilities under the “TRADER + AI” banner: it performs feature extraction, factor generation, and analysis based on full‑market Level 2 quotes and tick data, seamlessly connecting data utilization, factor screening, backtesting, and live trading. It provides research and execution tools; the website’s performance claims should not be interpreted as guarantees of trading outcomes.

Users without programming experience can perform computations through the mini-program and guided interface; users with development skills can write and invoke algorithms via the Python API to customize computational tasks. The official website’s market data table lists historical data starting from 2023, covering stocks, futures, convertible bonds, funds, indices, and other asset classes; actual data access rights must be confirmed on a per-service basis.

The product offers installation packages for Windows, Linux, and macOS, along with product documentation and a mini-program entry point. The official website’s pricing table and limited-time free promotion do not fully disclose the billing units, scope of applicability, or expiration dates; therefore, this entry does not categorize it as permanently free, nor does it cite unverified fixed pricing details.

Key features

  • Level 2 Market Data and Tick Data Research

  • AI factor generation and screening

  • Guided Intelligent Computing

  • Python API Custom Calculations

  • Backtesting and trading workflow integration

  • Windows, Linux, and macOS installation packages

Use cases and audience

Quantitative researchers, trading system developers, and related teams

  • Organize market data and factor research
  • Customize and validate quantitative computing workflows
  • Connect research with strategy execution tools
Input

Market data, factors, and strategy configurations that you’re authorized to use, along with Python algorithms.

Output

Factor analysis, calculation results, backtesting, and trading workflow outputs

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