Serenity Perilla Leaf Stock Selection Framework
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About this skill
The Problem
- In high-momentum sectors, attention and coverage often concentrate on visible leaders, leaving less crowded upstream layers under-researched.
- Many “chokepoint” ideas are only conceptually connected to the terminal market, without clear proof of
BOMnecessity, competitive exclusivity, capacity rigidity, or pricing power. - A useful screen needs to separate physical supply bottlenecks from crowded demand-side narratives.
How the Skill Works
The skill turns Perilla Leaf Theory into a structured supply-chain workflow:
- Three hard standards: irreplaceability, capacity rigidity, and low expected gap; a candidate is rejected if any one fails.
- Chokepoint mapping: start from downstream demand and work backward to the shortest board where a supplier failure would stall the chain.
- Mosaic validation: cross-check patents, customer lists, capacity roadmaps, and upstream material or equipment constraints.
- Information-gap scoring: review sell-side coverage, report frequency, institutional holding, retail discussion, and consensus expectations.
- True bottleneck checks: combine qualitative questions with quantitative signals such as gross margin, customer concentration, CAPEX, expansion lead time, and competitor expansion difficulty.
- Human decision gate: end with buy, watch, or pass, while requiring the user to confirm sizing, stop-loss, and risk discipline.
Boundaries
- This is useful for engineering-led industry research and public-information synthesis, not licensed investment advice.
- Small, illiquid names carry higher risk of mispricing, route-switching, and fundamental reversal.
- The Serenity persona is not independently verified, and reported returns are not auditable; use the framework rather than following individual stock calls.
Use Cases
- When studying an AI optical module chain, map downstream orders back to lasers, materials, and equipment layers to shortlist chokepoints.
- While reviewing filings and financial statements, test a layer's gross margin, customer mix, CAPEX, and expansion cycle to verify a true bottleneck.
- During small-cap screening, compare sell-side coverage, report frequency, institutional holding, and retail discussion to gauge the order-eve stage.
- Before drafting research notes, consolidate patents, customer lists, and capacity maps into bottleneck identification and validation outputs.
Best For
- Buy-side analysts covering AI, robotics, and semiconductor supply chains who need to turn narratives into physical bottlenecks and evidence.
- Quant analysts building industry screens who need hard standards to filter pseudo-chokepoints and produce a reviewable candidate pool.
- Research-oriented investors tracking filings and earnings who need to test expansion lead time, gross margin, and pricing power behind bottleneck theses.
- Industry editors writing supply-chain notes who need patents, customers, and capacity data structured into actionable conclusions.
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