Podcast Atlas
concept Updated 2026-08-08 Tags: Investing, Research, Valuation, Process

MAPER Investment Research Framework

MAPER is the company-research framework described by [[WuWeizhi|吴伟志]] in A股的春夏秋冬：种树、种粮、种菜. The source defines its dimensions as business model, competitive advantage, growth space, management, and earnings or certainty, then uses them to distinguish superficial theme exposure from investable company understanding.

MAPER sits between broad AI Investment Research and traditional Financial Statement Analysis. AI can collect and organize information, but the analyst still has to answer whether the business model is good, what the industry success factors are, who has the advantage, how large the runway is, whether management can execute, and what earnings certainty supports the valuation.

The source also separates broad reading from deep reading. Broad reading asks what the company does, where it sits, and whether the industry is worth more work; deep reading asks whether the company is the best candidate, who is better, what barriers exist, how growth space converts to profit, and whether a position deserves size.

Key Claims

  • Research should begin with problem definition and classification before the analyst reads everything available.
  • Business model and growth space are especially important for [[GrowthInvesting|growth investing]] because a high multiple requires long future earning power.
  • Competitive advantage cannot be inferred only from being a leader; the analyst must know the industry’s key success factors.
  • AI summaries are inputs, not evidence by themselves, because logic, common sense, and market context still need verification.
  • The framework’s output should feed portfolio action through [[ResearchIndexPortfolioConstruction|research indexes]], ranking, and weight choices.

Connections