Equity Valuation Frameworkv1.0.4

Users request valuation of a specific stock to determine if it is cheap or expensive. The skill processes financial data to generate fair value estimates using multiples and DCF methods, focusing on margin of safety and risk assessment.

Users compare multiple stocks (e.g., A, B, C) to identify the most attractive investment. The skill analyzes peer sets, applies relative valuation multiples, and assesses quality metrics to rank options based on value and resilience.

Users need a decision-ready report for investment decisions, including bull/base/bear scenarios. The skill structures valuation outputs, quality checks, and risk reviews into a professional memo with explicit assumptions and confidence levels.

Users analyze stocks in cyclical industries like steel or chemicals. The skill adapts valuation with cycle-aware assumptions, normalizes margins, and highlights cycle-risk notes to provide conservative fair value ranges.

Users value banks or insurance companies, prioritizing P/B and ROE metrics over EBITDA. The skill evaluates asset quality, capital adequacy, and funding costs, with sector-specific adaptations for sustainability analysis.

This model transforms structured financial and market data into professional valuation reports. It relies on upstream data sources like vnstock-free-expert for inputs, applying standardized modules such as multiples and DCF to generate fair value estimates.

This model provides bull, base, and bear scenarios for equity valuation, incorporating macro and news contexts. It helps users assess risks and opportunities by triangulating methods and defining safety zones for informed decision-making.

This model evaluates business fundamentals like moat, governance, and balance-sheet risk through a checklist. It supports valuation by identifying strengths and weaknesses, enhancing confidence in investment theses and risk management.