chain-screener

To map an industry chain, you provide a theme like 'AI算力' and the system decomposes it into upstream, midstream, and downstream segments. It then searches globally for listed companies, pulls financial data, and generates an investment score, Mermaid diagram, and Excel report.

The best way to generate a Mermaid diagram for supply-chain mapping is to input an investment theme for decomposition. The system identifies upstream, midstream, and downstream companies, pulls financial data, and outputs a structured Mermaid diagram alongside an Excel report.

Yes, financial data screening with tushare requires a Python environment with tushare and python-dotenv installed. You also need to configure a QUANT_ROOT environment to execute the end-to-end workflow and generate the JSON, Excel, and Mermaid deliverables.

Yes, you can use this screener to analyze global equities across US, HK, and A-share markets. It validates listings across these regions, pulls financial metrics for scoring, and maps supply chains to deliver structured investment outputs for themes like SpaceX or AI算力.

To produce an Excel report with investment scores, input an investment theme to trigger the global company search and financial data aggregation. The workflow calculates a 0-100 investment score and exports a structured Excel report alongside a Mermaid diagram for your committee.