Buddy Stock Screening Indicator System
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About this skill
Problem
In A-share analysis, checking PE, ROE, or a single earnings snapshot can be misleading. A metric may only be normal within its industry, while sector flows and short-term trend are often missed. When multiple signals conflict, manual judgment can become unstable. BDFinLogic turns the question of whether fundamentals pass, whether entry timing is suitable, and whether trend is deteriorating into a reusable checklist.
How It Works
It builds a five-star rating system around the Buddy methodology, using 15 indicators such as ROE, cash-to-income ratio, goodwill to net assets, major shareholder pledge ratio, PEG, and northbound flows. The workflow first tests profitability, asset quality, operating efficiency, and valuation against industry benchmarks. It then applies sector relative strength, price position, and a three-year trend score before outputting a rating and risk notes.
Boundaries
This framework is better used as a stock screening and review checklist, not an automated trading signal. Thresholds depend on industry context, and cyclicals or financials may need special treatment. Northbound flows can lag, and sector and price data sources must be available. It is not investment advice; major anomalies still require announcements, cash flow, and sector conditions.
Use Cases
- Before building an A-share watchlist, score 15 financial indicators against industry benchmarks and mark pass/fail items.
- For candidate stocks, generate a five-star rating adjusted by sector strength, price position, and three-year trend.
- During portfolio risk review, inspect goodwill-to-net-assets, pledge ratio, and interest-bearing debt thresholds.
- When drafting stock notes, output rating, risk flags, and industry positioning using the fixed analysis template.
Best For
- Individual A-share investors who want a consistent fundamentals checklist for candidate stocks.
- Equity researchers who need financial metrics, sector strength, price position, and trend in reviews.
- Finance data engineers building reusable stock-screening prompts or analysis templates.
- Investment research team members producing stock risk notes and avoidance checklists.
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