FundVal Live addresses the opacity of fund valuation by providing a transparent, real-time system. It uses detailed holdings, live market data, and rigorous mathematical models for objective analysis, targeting technically savvy users seeking data-driven insights beyond market sentiment.

How It Works

The system employs transparent holdings penetration, weighting real-time market data against known fund compositions. Its FastAPI/NumPy backend processes data from Eastmoney and Sina Finance, with AkShare for fund information. Core analysis relies on mathematical models (Sharpe Ratio, Max Drawdown, Volatility) computed via vectorized operations. An optional AI engine (LangChain, OpenAI/DeepSeek) provides data-driven insights and investment directives, eschewing market sentiment.

Quick Start & Requirements

Installation options include a cross-platform desktop application (downloadable executables), Docker deployment (recommended for servers), or command-line execution. The CLI requires Python 3.13+, Node.js 18+, and uv. Docker simplifies setup significantly. Users can find downloadable installers and Docker images via the project's GitHub releases page. Configuration for AI features requires API keys.

Highlighted Details

Supports real-time valuation for global markets (A-shares, HK, US) with multi-source data redundancy. Features advanced technical indicators (Sharpe Ratio, Max Drawdown). An AI audit generates direct investment instructions (Hold/Take Profit/DCA) based purely on mathematical facts. Portfolio management tools track costs, P&L, and provide visualizations. Subscription alerts for volatility and daily summaries are available.

Maintenance & Community

Community discussion is facilitated via a WeChat group. Specific details on core maintainers, sponsorships, or a public roadmap are not provided in the README.

Licensing & Compatibility

Licensed under GNU Affero General Public License v3.0 (AGPL-3.0). This strong copyleft license permits free use, modification, and distribution. However, modifications offered as a network service (SaaS) must be publicly available under AGPL-3.0, potentially limiting closed-source commercial integrations.

Limitations & Caveats

AI analysis requires valid OpenAI/DeepSeek API keys. Data and analysis are explicitly for technical research, not investment advice. The AGPL-3.0 license's SaaS requirements may restrict adoption in certain commercial contexts.